THE UNIVERSITY OF NEW SOUTH WALES INSTITUTE OF ENVIRONMENTAL STUDIES FACULTY OF ARTS AND SOCIAL SCIENCES
HARNESSING BIOENERGY AS A DRIVER OF REVEGETATION: AN ANALYSIS OF POLICY OPTIONS FOR THE NEW SOUTH WALES CENTRAL WEST, AUSTRALIA
A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy
Supervised by Associate Professor John Merson (UNSW) and Associate Professor Mark Diesendorf (UNSW) Co-supervised by Mr Peter Ampt (The University of Sydney)
Alex Baumber
July 2012
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Date ……………………………………………...... Abstract
The revegetation of degraded and vulnerable land is a key objective of natural resource management policy in Australia. The production of woody energy crops could help to facilitate such revegetation, with examples including the cropping of mallee eucalypts in Western Australia and poplar and willow in Europe. This thesis seeks to add to the existing knowledge around woody energy crops for revegetation by exploring the applicability of these ideas to the Central West region of New South Wales (NSW), Australia. This includes analysis of the potential social, economic and environmental impacts of energy cropping in this region and the development of policy measures to guide the use of woody energy crops for revegetation.
The results of two case studies in the NSW Central West are presented, one in the Central Tablelands and another farther west in the wheat and sheep belt around the town of Condobolin. These two regions have much in common, but also possess notable differences in land use, climate, topography, demographic trends and natural resource management priorities. The case study results suggest that different strategies are likely to be required for bioenergy-based agroforestry in each region. Woody energy crops appear closer to being competitive with typical agriculture in the Central Tablelands, where large-scale bioenergy options such as electricity generation or liquid fuel production may be viable due to the presence of existing timber industry residues. At Condobolin, energy cropping appears less competitive at present, but small-scale options involving wood pellets, briquettes or electricity may be viable for small groups of landholders with high levels of interest in mallee cropping.
Recommendations are also presented on policy options that could be used to guide the development of bioenergy-based agroforestry in a sustainable manner. Policy development of this nature requires consideration of the differing issues, benchmarks and policy measures employed across the revegetation, plantation and bioenergy sectors. Key policy recommendations include measures to support landholders in the establishment of energy plantations, the tailoring of renewable energy incentive programs to promote bioenergy that contributes to revegetation goals and the use of land use planning regulations to mitigate negative land use impacts.
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Acknowledgements
I would like to thank my three supervisors, John Merson, Mark Diesendorf and Peter Ampt. Each of you has brought something different to the development of this thesis. John, your ability to get me to pull back and focus on the big picture has helped me to understand what a thesis needs to do. Mark, your intimate knowledge of renewable energy and attention to detail has helped to make this a document I can be proud of. Peter, I could never have hoped to tackle a project like this without your support and mentoring over many years and your insights into rural land use and landholder issues. I am also grateful for all the assistance I have received from the Graduate Research School, the Institute of Environmental Studies and the Faculty of Arts and Social Sciences at UNSW, including a generous UNSW Research Excellence scholarship, support with fieldwork and funding for overseas conference travel.
Thank you to everyone who assisted me with the case study research around Condobolin and the Central Tablelands. I couldn’t possibly have obtained the level of access to people and places that I did without your help. In particular, I would like to thank Sandy Booth for his invaluable advice and for introducing me to the issues and personalities involved with mallee cropping around Condobolin. I would also like to thank Peter Milthorpe for his insights into mallee cropping, Dave McDonald for connecting me with a wide range of landholders, Andrew Cumming for providing access to a working mallee plantation at Mt Mulga, Dean Patton for advice on mallee economics, James Martin for assisting with interviews and Ted Hayman for his advice and data on briquetting. For the Central Tablelands case study, I would like to thank DAFF and RIRDC for providing the funds to make it happen, Crelis Rammelt for coordinating the broader project, Sarah Terkes for providing support at critical times, Sebastian Pfautsch for his expert advice on plantation monitoring and Roger Arrow, Mitchell Clapham and Ned Coombes for providing access to their properties.
Lastly, but most fundamentally, I would like to thank my family and friends for all the support I have received throughout this process. In particular, I wish to thank my beloved partner Claire for all her advice and for all she’s had to put up with, and my son Simon for making everything joyful, even in the darkest moments of thesis editing. ii
Table of Contents Abstract ...... i
Acknowledgements ...... ii
Table of Contents ...... iii
List of Figures ...... viii
List of Tables ...... xiii
List of Acronyms and Abbreviations ...... xvi
Chapter 1: Introduction ...... 1
1.1 Key terms and thesis scope ...... 3
1.2 Sustainability and sustainable development ...... 9
1.3 Thesis structure ...... 12
Chapter 2: Literature Review……… ...... 14
2.1 Revegetation and ecological restoration ...... 15
2.1.1 Sustainability issues and revegetation objectives ...... 15
2.1.2 Revegetation policy instruments ...... 20
2.2 Plantations and agroforestry ...... 23
2.2.1 Notions of sustainability in the plantation sector ...... 24
2.2.2 Plantation policy in Australia ...... 30
2.2.3 Plantations and revegetation ...... 35
2.3 Bioenergy ...... 38
2.3.1 Notions of sustainability in the bioenergy sector ...... 39
2.3.2 Bioenergy policy in Australia ...... 54
2.4 Integrating notions of sustainability across the revegetation, plantation and bioenergy sectors ...... 61
2.5 Conclusion ...... 72
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Chapter 3: Conceptual Frameworks ...... 74
3.1 Multifunctionality ...... 74
3.1.1 Multifunctionality in Australia ...... 76
3.1.2 Multifunctionality versus strict prioritisation of outputs ...... 79
3.1.3 Multifunctional policy instruments...... 80
3.2 Conservation through Sustainable Use ...... 83
3.2.1 CSU in restoration, revegetation and agroforestry ...... 85
3.2.2 Key principles and tools for operationalising CSU ...... 87
3.3 Adoption of innovations by rural landholders ...... 93
3.3.1 Paradigms of diffusion and landholder adoption ...... 93
3.3.2 Policy development and research strategies for rural adoption ...... 98
3.4 Ecological Economics ...... 104
3.4.1 Fundamentals of ecological economics ...... 105
3.4.2 Implications for policy and research ...... 109
3.5 Resilience within adaptive complex systems ...... 116
3.5.1 Resilience principles ...... 117
3.5.2 Implications for policy and research ...... 121
3.6 Development of an integrated sustainability policy framework ...... 122
3.7 Conclusion ...... 132
Chapter 4: Introduction to Case Studies ...... 134
4.1 Background to the Condobolin Case Study ...... 135
4.1.1 Economic, social and environmental trends ...... 138
4.1.2 Bioenergy-based land use options for the Condobolin area ...... 144
4.2 Central Tablelands Case Study ...... 150
4.2.1 Economic, social and environmental trends ...... 151
4.2.2 Bioenergy-based land use options for the Central Tablelands ...... 159
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4.3 Regulatory and policy environment ...... 162
4.3.1 Natural resource management policy ...... 163
4.3.2 Plantations policy ...... 168
4.3.3 Bioenergy policy ...... 172
4.4 Case Study Goal and Research Questions ...... 178
4.5 Conclusion ...... 181
Chapter 5: Social Analysis ...... 182
5.1 Condobolin Case Study ...... 182
5.1.1 Methodology ...... 183
5.1.2 Results ...... 190
5.2 Central Tablelands Case Study ...... 199
5.2.1 Methodology ...... 200
5.2.2 Results ...... 207
5.3 Discussion ...... 222
5.4 Conclusion ...... 229
Chapter 6: Economic Analysis ...... 231
6.1 Demand-side Analysis ...... 232
6.1.1 Methodology ...... 233
6.1.2 Results ...... 255
6.2 Supply-side analysis ...... 269
6.2.1 Methodology ...... 270
6.6.2 Results ...... 291
6.3 Discussion ...... 301
6.4 Conclusion ...... 308
Chapter 7: Environmental Analysis ...... 310
7.1 Environmental protection requirements ...... 313
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7.1.1 Methodology ...... 313
7.1.2 Results ...... 317
7.2 Environmental enhancement opportunities ...... 321
7.2.1 Methodology ...... 322
7.2.2 Results ...... 327
7.3 Landscape function ...... 333
7.3.1 Methodology ...... 336
7.3.2 Results ...... 341
7.4 Discussion of results and identification of future research needs ...... 347
7.4.1 Biodiversity ...... 347
7.4.2 Hydrology ...... 353
7.4.3 Climate change ...... 358
7.5 Conclusion ...... 364
Chapter 8: Policy Development and Recommendations ...... 367
8.1 Problem-framing/orientation ...... 368
8.1.1 Issues, goals, synergies and trade-offs ...... 368
8.1.2 Scenarios for bioenergy-based agroforestry at the case study sites ...... 372
8.1.3 Policy problems for the case study sites ...... 377
8.2 Policy-framing ...... 379
8.2.1 Policy principles ...... 379
8.2.2 Policy goals for the case study sites ...... 383
8.3 Policy Evaluation ...... 386
8.3.1 Identification of policy options for the case study sites ...... 386
8.3.2 Assessment of policy instruments for the case study sites ...... 389
8.3.3 Selection of policy instruments ...... 407
8.4 Implementation through adaptive management ...... 416
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8.4.1 Policy measures recommended for full implementation ...... 417
8.4.2 Policy measures recommended for trial implementation ...... 418
8.4.3 Policy measures recommended for delay pending further research ...... 421
8.4.4 Policy measures recommended for no action under current conditions ...... 422
8.5 Conclusion ...... 423
Chapter 9: Conclusion ...... 425
References ...... 434
Appendix A: Participant Consent Form - Condobolin ...... 480
Appendix B: Participant Consent Form – Central Tablelands ...... 483
Appendix C: PRA Interview Sheet – Central Tablelands ...... 486
Appendix D: Central Tablelands Landholder Survey ...... 491
Appendix E: NSW Government Gross Margin Data ...... 500
Appendix F: 3-PG Modelling Parameters ...... 511
Appendix G: Treatment of plantation forestry under local environmental plans ...... 520
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List of Figures
Figure 1.1: Mallee eucalypt belts in Western Australia ...... 1
Figure 1.2: Thesis case study locations...... 2
Figure 1.3: Overlap between revegetation and restoration...... 4
Figure 1.4: Bioenergy as a proportion of global primary energy use...... 5
Figure 1.5: Bioenergy feedstocks and conversion pathways...... 6
Figure 1.6: Bioenergy as a percentage of Australian Renewable Energy Certificates (RECs) 2001-2010...... 8
Figure 1.7: Thesis structure based on hourglass model...... 12
Figure 2.1: Selected sustainability definitions for forestry and agriculture...... 25
Figure 2.2: Calculation of minimum and average carbon stocks within plantations...... 34
Figure 2.3: Top four producing countries for (a) ethanol and (b) biodiesel...... 44
Figure 2.4: GHG savings for selected solid biomass feedstocks...... 48
Figure 2.5: Impacts of ethanol production on the US grain sector...... 52
Figure 2.6: The role of mallee tree belts in mitigating dryland salinity in the wheatbelt of Western Australia...... 62
Figure 2.7: Value-systems implicit in the approaches of Gallagher (2008), Searchinger et al. (2008) and O’Connell et al. (2005)...... 70
Figure 2.8: Comparison of assumptions underlying two different visions of bioenergy...... 71
Figure 3.1: Conceptual model of land-sparing and wildlife-friendly farming...... 79
Figure 3.2: The key elements of the diffusion of innovations...... 95
Figure 3.3: Generalised model of adoption over time based on Rogers’ five adopter categories...... 97
Figure 3.4: Basic and modified versions of Pannell’s (2008) Public: Private Benefits Framework...... 103
Figure 3.5: Hypothetical supply and demand curves for natural capital stocks...... 111
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Figure 3.6: Public: Private Benefits Framework adapted for use with CNC...... 113
Figure 3.7: Representations of an adaptive cycle...... 118
Figure 3.8: Nesting of adaptive cycles within the panarchy...... 119
Figure 3.9: Comparison of sustainability policy frameworks from Dovers (2005), Clark (2002) and Diesendorf (2000)...... 123
Figure 4.1: Location of case study sites in NSW...... 134
Figure 4.2: Land uses around Condobolin...... 137
Figure 4.3: Annual rainfall and wheat harvests for the Condobolin district 1993-2010...... 138
Figure 4.4: “Best estimate” (50th percentile) climate change projections for NSW. ... 140
Figure 4.5: Blue mallee growing in a plantation at West Wyalong, NSW...... 145
Figure 4.6: Image of Fire Extender BIOBLOXTM product and packaging...... 148
Figure 4.7: Land use in the NSW Central Tablelands...... 151
Figure 4.8: CMA and LGA boundaries in the Central Tablelands...... 154
Figure 4.9: Change in generation target under the LRET 2011-2030...... 175
Figure 5.1: Property locations for interviewed landholders around Condobolin...... 184
Figure 5.2: Landholders reporting previous experience with tree-planting...... 191
Figure 5.3: Number of interviewees citing each type of benefit...... 192
Figure 5.4: Number of interviewees citing each type of barrier...... 193
Figure 5.5: Average number of discrete benefits and barriers cited by landholders. .... 194
Figure 5.6: Amount of land nominated by landholders for conversion to mallee...... 195
Figure 5.7: Policy options listed as first or equal first by interviewees...... 198
Figure 5.8: Location of interviews for PRA...... 201
Figure 5.9: “Vision” document presented at the start of each interview...... 202
Figure 5.10: Sub-regions selected following PRA...... 203
Figure 5.11: Distribution of major land use amongst survey respondents...... 210
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Figure 5.12: Distribution of major land use activities by sub-region...... 210
Figure 5.13: Distribution of major land use activities by property size class...... 211
Figure 5.14: Mean scores for benefits of agroforestry...... 213
Figure 5.15: Mean scores for agroforestry barriers...... 213
Figure 5.16: Land nominated for conversion to agroforestry by property size class. ... 215
Figure 5.17: Return required from agroforestry relative to current land use, by sub- region...... 217
Figure 5.18: Preferred land classes for agroforestry vs. distribution of land classes. ... 219
Figure 6.1: Percentiles for the 2010/11 NSW Regional Reference Price (RRP)...... 249
Figure 6.2: Relationship between tree age and wood fraction for eucalypt species with moderately dense leaves...... 255
Figure 6.3: Breakeven biomass price and scale for each demand-side bioenergy model under base case assumptions...... 256
Figure 6.4: Briquette sensitivity analysis results for (a) production costs and (b) briquette price...... 258
Figure 6.5: Wood pellet sensitivity analysis results for (a) pellet price, (b) exchange rate and (c) production cost...... 259
Figure 6.6: Ethanol sensitivity analysis results for (a) oil price, (b) exchange rate, (c) carbon price and (d) ethanol excise...... 260
Figure 6.7: Renewable diesel/jet fuel sensitivity analysis results for excise rates...... 261
Figure 6.8: Renewable diesel/jet fuel sensitivity analysis results for carbon price...... 262
Figure 6.9: Electricity sensitivity analysis results for (a) capital and operating costs, and (b) pre-processing and transport costs...... 263
Figure 6.10: Electricity sensitivity analysis results for (a) LGC price, and (b) carbon price...... 264
Figure 6.11: Electricity sensitivity analysis results for electricity price...... 265
Figure 6.12: Periods during 2010/11 in which the NSW Regional Reference Price for electricity was above the 90th percentile...... 266
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Figure 6.13: Breakeven biomass price for the 5 MW biomass-only electricity model based on peak-only generation...... 266
Figure 6.14: Breakeven biomass price under the Condobolin co-production model. ... 267
Figure 6.15: Breakeven biomass price under the Central Tablelands co-production model...... 267
Figure 6.16: Agroforestry trial sites used to test biomass yield assumptions...... 282
Figure 6.17: Field site measurements of tree basal area per hectare compared to 3-PG model predictions...... 283
Figure 6.18: Sensitivity analysis results for mallee biomass production...... 292
Figure 6.19: Sensitivity analysis results for the Condobolin typical agriculture model.294
Figure 6.20: Sensitivity analysis results for biomass price in the Central Tablelands. . 296
Figure 6.21: Central Tablelands agroforestry sensitivity analysis results...... 297
Figure 6.22: Sensitivity analyses for typical agriculture in the Central Tablelands. .... 298
Figure 6.23: Impact of policy options on mallee agroforestry EAV at Condobolin. .... 299
Figure 6.24: Impact of policy options on agroforestry EAV in the Central Tablelands.300
Figure 6.25: Cost-supply curve for potential biomass sources for co-firing at Wallerawang, NSW...... 303
Figure 7.1: Private rural land in the case study regions...... 312
Figure 7.2: Areas where plantation establishment is likely to restricted by policy measures...... 318
Figure 7.3: Potential revegetation corridors for biodiversity in the case study regions.323
Figure 7.4: Land capability hotspots for the case study regions...... 325
Figure 7.5: Central Tablelands hotspots for erosion (left) & dryland salinity (right). .. 326
Figure 7.6: Biodiversity and land capability hotspots for the Condobolin region...... 327
Figure 7.7: Overlap between environmental hotspots in the Central Tablelands...... 328
Figure 7.8: Landscape priorities in the tablelands portion of the Central West CMA region...... 329
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Figure 7.9: Environmental hotspots compared with available private rural land...... 330
Figure 7.10: Environmental hotspots compared with land capability (right) and property size (left) in the Central Tablelands...... 332
Figure 7.11: The trigger-transfer-reserve-pulse framework...... 333
Figure 7.12: Division of a hypothetical LFA transect into patches and inter-patches. . 334
Figure 7.13: Contribution of soil surface indicators to indices for stability, infiltration and nutrient cycling...... 335
Figure 7.14: Locations of LFA sites for (a) Condobolin and (b) Central Tablelands. .. 337
Figure 7.15: LFA results for Mt Mulga (Condobolin case study) +/- standard error. ... 341
Figure 7.16: Land units showing hard soils and a lack of litter cover at Mt Mulga. .... 342
Figure 7.17: LFA results for the Central Tablelands case study sites...... 344
Figure 7.18: Bank-trough micro-catchment...... 345
Figure 7.19: Biodiversity monitoring results for Western Australian oil mallee...... 349
Figure 7.20: Rainforest bird monitoring results for North Queensland...... 350
Figure 7.21: Impacts of a change from current vegetation cover to 100% tree cover in the Murray-Darling basin...... 355
Figure 7.22: Impacts of climate change on biomass yield for four plantation species by 2070...... 362
Figure 8.1: Major goals and issues identified in this research...... 370
Figure 8.2: Strategic agricultural land (SAL) identified in the New England and Northwest region of NSW...... 400
Figure 8.3: Cost-supply curve for renewable jet fuel from a range of biomass types. .. 405
Figure 8.4: Processes involved in Stage 4 of the policy framework...... 416
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List of Tables
Table 2.1: Sustainability issues from selected forestry and agriculture standards...... 27
Table 2.2: Sustainability issues from selected bioenergy sustainability standards...... 40
Table 2.3: GHG savings calculated for selected biofuels...... 46
Table 2.4: Feed-in tariffs offered for bioenergy in Germany...... 56
Table 2.5: UK Renewables Obligation “banding” for bioenergy sources...... 57
Table 2.6: Key sustainability issues, benchmarks and policy instruments for the revegetation, plantation and bioenergy sectors...... 65
Table 3.1: Ecosystem Approach principles matched to their most closely-related Addis Ababa principles...... 88
Table 3.2: Approaches to address bias in diffusion research...... 99
Table 3.3: Policy framework developed for application to the thesis case studies...... 126
Table 3.4: Policy instrument categories from Dovers (2005) and Pannell (2008)...... 129
Table 4.1: Wheat yield change across southeastern Australia under climate change...... 141
Table 4.2: NRM targets relating to revegetation under the Lachlan Catchment Action Plan...... 143
Table 4.3: CMA management targets most relevant to revegetation using woody perennials in the Central Tablelands...... 156
Table 4.4: Elements of each research question covered in Chapters 5, 6 and 7...... 180
Table 5.1: Breakdown of interviewees by category...... 183
Table 5.2: Questions used in semi-structured interviews...... 186
Table 5.3: Breakdown of survey respondents according to land size class...... 209
Table 5.4: Overall land conversion rate corrected from survey data...... 216
Table 6.1: Required rates of return used in previous Australian bioenergy studies...... 235
Table 6.2: Pellet production costs from previous studies ...... 237
Table 6.3: Base case pellet production assumptions and variations...... 238
Table 6.4: Base case briquette production assumptions and variations...... 240 xiii
Table 6.5: Base case ethanol production assumptions and variations...... 243
Table 6.6: Base case renewable diesel/jet fuel assumptions and variations...... 245
Table 6.7: Assumptions used in the electricity generation models...... 248
Table 6.8: Capital costs and average electricity prices for a peak-only 5 MW biomass plant...... 251
Table 6.9: Parameters used in the mallee production model for Condobolin...... 273
Table 6.10: Parameters used in the typical agriculture (1500ha) Condobolin model...... 276
Table 6.11: Species shortlisted for the Central Tablelands supply-side modelling...... 279
Table 6.12: Yield estimates for species considered for the agroforestry model...... 280
Table 6.13: Parameters used in the agroforestry production model for the Central Tablelands...... 285
Table 6.14: Typical agriculture parameters used in the Central Tablelands model...... 287
Table 6.15: Comparison between base case EAV for agroforestry and sheep grazing in the Central Tablelands...... 295
Table 6.16: Comparative impact of demand-side and supply-side policy interventions on project EAV at each case study site...... 307
Table 7.1: Land conversion scenarios used to analyse environmental restrictions...... 314
Table 7.2: Policy sources used to identify areas with plantation restrictions...... 316
Table 7.3: Landholder preferences compared with land availability in the Central Tablelands...... 320
Table 7.4: Land management units for Condobolin case study LFA site (Mt Mulga)...... 339
Table 7.5: Site/unit descriptions for Central Tablelands case study LFA sites...... 340
Table 7.6: Principles for enhancing wildlife conservation in Australian plantations...... 351
Table 7.7: Water use offsets for plantations under the Carbon Farming Initiative...... 356
Table 7.8: Qualitative assessment of climate change mitigation impacts...... 360
Table 8.1: Sustainability policy framework developed in Chapter 3...... 368
Table 8.2: Policy problems to be resolved for the case studies...... 378
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Table 8.3: Recommended policy principles...... 380
Table 8.4: Recommended policy goals...... 384
Table 8.5: Existing and potential policy instruments relating to revegetation, agroforestry and bioenergy at the case study sites...... 387
Table 8.6: Selection criteria for policy implementation from Dovers (2005) ...... 389
Table 8.7: Policy measures recommended for full implementation ...... 409
Table 8.8: Policy measures recommended for trial implementation ………………………….411
Table 8.9: Policy measures recommended for delay pending further research...... 414
Table 8.10: Policy measures recommended for no action under current conditions...... 415
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List of Acronyms and Abbreviations
A3P Australian Plantation Products and Paper Industry Council
ABARES Australian Bureau of Agricultural and Resource Economics and
Sciences
ACCU Australian Carbon Credit Unit
AEMO Australian Energy Market Operator
AFS Australian Forestry Standard
AUD Australian Dollar
bbl Barrel (unit of oil)
BOM Bureau of Meteorology
BMWHI Blue Mountains World Heritage Institute
CBD Convention on Biological Diversity
CFI Carbon Farming Initiative
CITES Convention on International Trade in Endangered Species
CMA Catchment Management Authority
CNC Critical Natural Capital
CO2-e Carbon dioxide equivalent
CSIRO Commonwealth Scientific and Industrial Research Organisation
CRRP Community Rainforest Reforestation Program
CSU Conservation through Sustainable Use
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Cth Commonwealth of Australia
DAFF Department of Agriculture, Fisheries and Forestry (Australian
Government)
DSE Dry Sheep Equivalent
ESFM Ecologically Sustainable Forest Management
EUR Euro
FAO Food and Agriculture Organization of the United Nations
FICCRF Forest Industries Climate Change Research Fund
FiT Feed-in Tariff
FSC Forest Stewardship Council gt Green tonne
GHG Greenhouse Gas
GIS Geographic Information System
GW Gigawatt
GWh Gigawatt-hour ha Hectare
IEA International Energy Agency
IES The Institute of Environmental Studies (at UNSW) iLUC Indirect Land Use Change
INFFER Investment Framework for Environmental Resources
IPCC Inter-governmental Panel on Climate Change
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IUCN International Union for Conservation of Nature
JPY Japanese Yen
LCA Life-cycle Assessment
LEP Local Environmental Plan
LFA Landscape Function Analysis
LGA Local Government Area
LGC Large-scale Generation Certificate
LRET Large-scale Renewable Energy Target
LUC Land Use Change
MBI Market Based Instrument
MIS Managed Investment Scheme
ML Megalitre
MW Megawatt
MWh Megawatt-hour
NEM National Electricity Market
NGO Non-government Organisation
NRM Natural Resource Management
NSW New South Wales
PRA Participatory Rural Appraisal
PVP Property Vegetation Plan
R&D Research and Development xviii
REC Renewable Energy Certificate
RET Renewable Energy Target
RFA Regional Forestry Agreement
RRP Regional Reference Price
RSB Roundtable on Sustainable Biofuels
RSPO Roundtable on Sustainable Palm Oil
RTFO Renewable Transport Fuel Obligation (UK Government)
SAN Sustainable Agriculture Network
SRC Short Rotation Coppicing
SRES Small-scale Renewable Energy Scheme
STC Small-scale Technology Certificate
UK United Kingdom (of Great Britain and Northern Ireland)
UN United Nations
UNSW The University of New South Wales
US United States (of America)
USD United States Dollar
WA Western Australia
WTO World Trade Organization
WWF World Wildlife Fund
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Chapter 1: Introduction
This thesis explores the idea that bioenergy could act as a commercial driver for agroforestry activities that help to address pressing natural resource management (NRM) issues in Australia’s agricultural landscapes, such as biodiversity loss, dryland salinity and soil erosion. This notion is not new, as a number of previous studies and trials have explored the connections between bioenergy and revegetation (e.g. Foran & Mardon 1999, Howard & Ozlack 2004, Smith 2009, Bennett, Simons & Speed 2011). The nascent Oil Mallee industry in Western Australia is one well-known example, involving the integration of mallee eucalypts into wheat fields (Figure 1.1). While this has largely been driven by a desire to mitigate dryland salinity, it has also been recognised that the development of commercially-viable mallee products, such as eucalyptus oil and bioenergy, is required for further adoption to take place (URS Australia 2009). Similar ideas have been pursued in Europe, where woody bioenergy crops such as willow (Salix spp.) and poplar (Populus spp.) have been shown to contribute to local environmental enhancements, including increases in soil organic matter, water quality and habitat for biodiversity (Simpson, Picchi, Gordon, Thevathasan, Stanturf & Nicholas 2009).
Figure 1.1: Mallee eucalypt belts in Western Australia. Source: Oil Mallee Australia (2012).
1 The contribution that this thesis seeks to make to the field of knowledge around bioenergy-based agroforestry is twofold. Firstly, it aims to increase understanding of the potential links between NRM goals and bioenergy production in southeastern Australia, specifically the Central West region of New South Wales (NSW). This region is the location for the two case studies explored in this thesis, one of which is centred on the town of Condobolin and the other in the area known as the Central Tablelands (Figure 1.2). These case studies build on previous research exploring woody energy crops in the NSW Central West, such as that of Abadi, Lefroy, Cooper, Hean and Davies (2006) and Total Catchment Management Services (2008).
Figure 1.2: Thesis case study locations. Both case studies are in the state of New South Wales, Australia.
The second key contribution of this thesis is the application of a sustainability policy framework to the development of bioenergy-based agroforestry in Australia. This involves the identification of policy measures that can promote desirable forms of bioenergy, agroforestry and revegetation while restricting activities that may have undesirable impacts. Policy development of this nature requires consideration of the diverse set of policy mechanisms that have already been employed across the bioenergy, plantation and revegetation sectors, as well as policy proposals aimed
2 specifically at the integration of bioenergy and revegetation (e.g. Howard & Ozlack 2004, URS Australia 2009). Thus, while this thesis covers social analysis of landholder attitudes, economic analysis of different bioenergy options and environmental analysis of potential agroforestry impacts, it is not restricted to any one of these tasks and is an unashamedly cross-disciplinary exercise.
1.1 Key terms and thesis scope
The term “revegetation” is used throughout this thesis to refer to activities that increase the amount of woody vegetation in a landscape in order to restore or enhance particular ecological functions. Since European settlement of Australia, many types of woodland and forest have experienced more than 30% clearing nation-wide, with the proportional loss even greater in many local areas (Beeton, Buckley, Jones, Morgan, Reichelt & Trewin 2006). This has contributed to problems such as biodiversity loss, soil erosion, dryland salinity and loss of stored carbon, making revegetation an important goal for Australian NRM policy at the national, state and regional levels, including at the two case study sites.
In the context of heavily-cleared forest and woodland environments, such as those found in the Central West of NSW, the term “revegetation” overlaps strongly with “ecological restoration”, which can be defined as “the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed” (Mansourian 2005, p. 9). These two terms are often used interchangeably in Australian NRM reports and policy documents, such as the 2011 Australian State of the Environment Report (Hatton, Cork, Harper, Joy, Kanowski, Mackay et al. 2011) or the recently-revised Catchment Action Plan for the NSW Central West (Central West Catchment Management Authority 2011). However, this is truly accurate only where ecosystem recovery requires an increase in vegetation and where vegetation is established with the aim of enhancing one or more ecosystem functions. Figure 1.3 shows the area of overlap between the terms revegetation and restoration, as used in this thesis. Activities that fall outside the scope of this thesis include restoration that does not require revegetation (e.g. clearing invasive plants) and revegetation of land that is undertaken
3 without any consideration of ecosystem enhancement (e.g. plantattions established solely for commercial harvest).
Restoration Revegetation
Restoration that is Activities that are Revegetation that not revegetation: both restoration is not restoration: e.g. clearing of and revegetation: e.g. replanting invasive scrub; e.g. re-establishing cleared land with removal of aquatic rainforest trees on a treees exclusively for weeds from a river previously cleared commercial harvest system rainforest site
Figure 1.3: Overlap between revegetation and restoration.
The term “agroforestry”, as used in this thesis, refers to “land-use systems and practices where woody perennialls are deliberately integrated with crops and/or animals on the same land management unit” (FAO 1993). Australian research and policy documents often class agroforestry as a sub-category of farm forestry (e.g. Department of Agriculture Fisheries and Forestry 2005, URS Forestry 2008b).. Under this approach, agroforestry is distingguuished by the use of wider tree spaacings and a greater degree of integration with agricultural production than is typical for the denser, monocultural plantations that make up most farm forestry in Australia. Australia’s plantation estate has undergone a major expansion in recent years (Bureau of Rural Sciences 2010), including a 50% increase in the area of land under farm forestry between 2001 and 2008 (URS Forestry 2008a). While this has largely been driven by demand for pulp and paper products, bioenergy has been identified as a potential driver of future growth by authors such as URS Forestry (2008b), Benneell, Hobbs and Ellis (2009) and Rodriguez, May, Herr, Farine and O'Connell (2011a). Bioenergy has been selected as the key agroforestry product option for investigation in this thesis for two main reasons:
4 1. The bioenergy sector is experiencing strong growth and technological development, potentially creating new commercial opportunities for agroforestry; and 2. The bioenergy sector is at the forefront of sustainability policy development globally, generating new and often controversial approaches to issues such as climate change mitigation, energy security, land use change, competition for resources, food security and socio-economic development.
Bioenergy refers to “energy produced from organic matter or biomass” (UN Energy 2007, p. 3), excluding fossilised organic matter such as coal. Bioenergy accounts for around 10% of the world’s primary energy supply (Bauen, Berndes, Junginger, Londo, Vuille, Ball et al. 2009) and is the dominant form of renewable energy globally (Figure 1.4). However, over 80% of global bioenergy use takes the form of traditional cooking and heating fuels such as fuelwood, charcoal, dung and agricultural residues. Less than 20% of global bioenergy use is made up of the “modern” forms of bioenergy that are the primary focus of this thesis, such as electricity, transport fuels and industrial process heat (IEA Bioenergy 2007).
Figure 1.4: Bioenergy as a proportion of global primary energy use. Reproduced from Bauen et al. (2009).
A key feature of modern bioenergy is its diversity, with a wide range of feedstocks, conversion pathways and products involved (Figure 1.5). While the term “biofuel” can be used to refer to solid, liquid or gaseous fuels, this thesis follows the common practice of restricting the term to liquid biofuels such as ethanol and biodiesel, unless
5 otherwise noted. Liquid biofuels are predominantly produced from sugar or starch crops via fermentation (e.g. sugarcane, grains) or oil crops via transesterification (e.g. canola, oil palm). However, there is a strong global research and development focus on so-called “second-generation” biofuels that can be produced from the woody or fibrous (i.e. lignocellulosic) components of biomass (e.g. Warden & Haritos 2008, CSIRO 2011b, Damartzis & Zabaniotou 2011). This focus on lignocellulosic material may result in bioenergy feedstocks becoming increasingly interchangeable between the liquid fuel and electricity sectors. The focus of this thesis is primarily on lignocellulosic feedstocks sourced from dedicated woody energy crops, with potential product options including electricity, heating and liquid biofuels.
Figure 1.5: Bioenergy feedstocks and conversion pathways. Source: International Energy Agency (2007). DME = dimethylether, FT Conv.= Fischer-Tropsch conversion. © OECD/IEA 2007
Australia, as with a number of other developed countries, has experienced steady growth in bioenergy use in recent years. In 2007/08, Australia generated over 2000 gigawatt hours (GWh) of electricity from biomass, up from around 1000 GWh in 1992/93 (Schuck 2010). The Clean Energy Council (2008) identified potential biomass
6 resources across Australia that could permit a fivefold increase in generation to over 10,000 GWh/yr by 2020, with over 70,000 GWh/yr possible in the long-term. These estimates are further reinforced by Rutovitz and Passey (2004), who identified sufficient biomass supplies for around 9000 GWh/yr in NSW alone, and by Elliston, Diesendorf and MacGill (2012), who developed simulations of 100% renewable electricity in Australia’s National Electricity Market with biomass contributions up to 28,000 GWh/yr.
Biofuel production in Australia is also rising, with ethanol production estimated to be up from 84 megalitres per year (ML/yr) in 2007 to 440 ML/yr in 2011 and biodiesel production up from 43 to 80 ML/yr over the same period (USDA Foreign Agricultural Service 2011). The successful commercialisation of second-generation biofuels could permit these volumes to be increased substantially, with Graham, Reedman, Rodriguez, Raison, Braid, Haritos et al. (2011) estimating that existing lignocellulosic biomass sources in Australia could yield 8000-9000 ML/yr of liquid biofuels, more than fifteen times the total biofuel production from first-generation sources in 20111.
A major factor in bioenergy expansion in Australia has been policy support such as the Renewable Energy Target (RET) for electricity and subsidies/tax breaks for biofuels. These have been motivated by goals of reducing greenhouse gas emissions, reducing reliance on oil imports and promoting regional development (Department of State and Regional Development 2007, Office of the Renewable Energy Regulator 2011). Due to its diversity of forms, bioenergy can substitute for many current uses of fossil fuels, which make up over 80% of global primary energy use (International Energy Agency 2008). Most bioenergy in Australia is currently sourced from wastes or residues of other processes. This includes electricity generation from sources such as bagasse (sugarcane processing residues) and landfill gas (Figure 1.6), as well as ethanol from waste wheat starch and molasses (sugar by-product) and biodiesel from tallow (animal fat) and used cooking oil (Productivity Commission 2011a).
1 Note that the electricity generation estimates of the Clean Energy Council (2008) and the biofuel estimates of Graham et al. (2011) were based on many of the same feedstocks.
7
Figure 1.6: Bioenergy as a percentage of Australian Renewable Energy Certificates (RECs) 2001-2010. Statistics include all RECs surrendered under Australia’s Renewable Energy Target, either voluntarily or to meet a company’s REC liability, as of 13 March 2012. Source: Office of the Renewable Energy Regulator (2012).
While wastes and residues represent the dominant bioenergy feedstocks in Australia, purpose-grown energy crops have expanded rapidly in a number of other countries over the past decade. This rapid growth has generated a number of sustainability concerns, including concerns that palm oil for biodiesel has contributed to deforestation in southeast Asia (Sheil, Casson, Meijaard, Noordwijk, Gaskell, Sunderland-Groves et al. 2009) and the diversion of US corn (maize) into ethanol production has caused global food prices to rise (Mitchell 2008). However, some energy crops have also demonstrated the potential for local soil and biodiversity benefits, such as cropping of willow and poplar in Europe (Simpson et al. 2009) and mallee eucalypts in Western Australia (URS Australia 2009). As a result of these impacts, the growing global interest in bioenergy development has been matched by a growing interest in issues of bioenergy sustainability, with government and non- government actors developing sustainability standards and other policy measures to
8 address these concerns (e.g. European Parliament & Council of the European Union 2009, Roundtable on Sustainable Biofuels 2010).
1.2 Sustainability and sustainable development
This thesis seeks to develop policy recommendations around sustainability and sustainable development, both of which are highly contested terms that have been defined in hundreds of different ways since they rose to prominence in the 1980s and 1990s (Keiner 2006). A fundamental element of sustainability is long-term persistence, reflecting concerns raised in seminal works such as The Limits to Growth (Meadows, Meadows, Randers & Behrens III 1972) that human activities are depleting non- renewable resources and threatening fundamental ecological support systems. However, sustainability is not solely about persistence or survival, but can incorporate other elements, such as the fulfilment of human needs, wants or demands, equity across human society and a requirement that elements of the natural world are maintained for reasons other than their capacity to sustain human needs. For example, Dovers (2005, p. 7) combines a number of these elements in the following description of sustainability:
“Sustainability refers to the ability of human society to persist in the long term in a manner that satisfies human development demands but without threatening the integrity of the natural world.”
The term “sustainable development” is also subject to interpretation. The following definition from the report Our Common Future (also known as The Brundtland Report) is probably the most commonly cited and influential definition of sustainable development:
“Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” (World Commission on Environment and Development 1987, p. 43) Despite being highly influential, the Brundtland definition of sustainable development has also received much criticism since it was developed. Keiner (2006, p. 2) contends that it is so inclusive and vague that it “loses its integrity as a political concept”, Lawn (2001, p. 13) believes that it represents “establishment appropriation” of the
9 sustainability concept and Diesendorf (2000) criticises it for allowing trade-offs between environmental and social values. AtKisson (2006, p. 238) argues that sustainable development is often reduced to “development-as-usual with a few green- looking additions or nods to social equity”. A key objective of this thesis is to understand what sustainability and sustainable development mean in relation to specific activities that combine agroforestry, bioenergy and revegetation at the case study sites. Further guidance can be found in the 27 principles of the Rio Declaration (United Nations Conference on Environment and Development 1992), many of which have flowed through to national policy statements and instruments. Chief amongst these are the precautionary principle and the principle of inter-generational equity, which are described under s3A of Australia’s Environmental Protection and Biodiversity Conservation Act 1999 (Cth) as follows:
x “If there are threats of serious or irreversible environmental damage, lack of full scientific certainty should not be used as a reason for postponing measures to prevent environmental degradation” (precautionary principle); and
x “The present generation should ensure that the health, diversity and productivity of the environment is maintained or enhanced for the benefit of future generations” (principle of inter-generational equity).
The precautionary principle and the principle of inter-generational equity provide guidance in managing the relationship between the environmental, economic and social aspects of sustainability, which are often referred to as the three “pillars” of sustainability. However, different perspectives will inevitably exist on critical matters such as what constitutes serious or irreversible damage and the extent to which economic, environmental and social objectives can be “traded-off” against one another. The idea that human-made capital (e.g. plantations) can be substituted for natural capital (e.g. forests) in order to maintain a total stock of capital for future generations is considered by some authors to be “weak” sustainability, as opposed to a “strong” approach to sustainability that regards many environmental values as having no adequate substitutes (Pearce 1993). In practice, there are few who would argue for either total substitutability or total non-substitutability and hence a continuum exists between strong and weak positions on sustainability (Dovers 2005).
10 The social pillar of sustainability is also subject to interpretation, with authors such as Marcuse (2006) arguing that social goals such as equity, justice and fairness should be seen as separate to sustainability, as unjust societies must first be made just before it is appropriate to sustain them. More commonly however, conceptualisations of sustainability and sustainable development incorporate social equity, as demonstrated by Diesendorf’s (2000, p. 19) argument that sustainable development should be seen as convenient shorthand for “ecologically sustainable and socially equitable development”. Even when social equity is explicitly included as part of sustainability, differing opinions and emphasis can be found, such as Diesendorf’s (2000) view of equity as “equal opportunity” versus Lawn’s notion of an equitable society as one in which “the difference between rich and poor is limited to what is considered fair and just” (Lawn 2001, p. 104). Notions of sustainable development often prioritise essential or basic needs such as “jobs, food, energy, water and sanitation” (World Commission on Environment and Development 1987), but explicit guidance is less common on which needs or wants should be assigned a low priority. Dovers (2005, p. 30) argues that value judgments of this nature are an intrinsic component of sustainability, stating that:
“Human behaviour is tied to human values, and values are intensely personal and political things, and sustainability has deeply normative or value-laden dimensions. To imagine otherwise would be unrealistic.”
The approach taken in this thesis is to view sustainability as a value-laden concept that represents a direction for society to head towards rather than an endpoint that can be clearly defined and reached. This follows Dovers’ (2005, p. 8) view of sustainability as a “higher order social goal” similar to democracy or justice. To avoid making trade- offs between the environment and social equity, this thesis seeks to identify forms of bioenergy-based agroforestry that meet Diesendorf’s (2000, p. 23) definition of sustainable development as “types of economic and social development that protect and enhance the natural environment and social equity”. However, it must be recognised that even activities that meet this ambitious goal will inevitably produce winners and losers, as certain environmental outcomes will be prioritised above others and the costs and benefits will be felt differently by different members of society.
11 1.3 Thesis structure
The structure of this thesis follows the “hourglass” model of research (Figure 1.7), starting with a broad set of research issues and questions, then narrrrowing to explore key factors at the case study level before broadening again to assesss the implications of the case study research for the broader concept of bioenergy-based agroforestry aimed at revegetation.
Figure 1.7: Thesis structure based on hourglass model.
Chapter 2 provides a broad overview of past research and existing policy in order to identify the key sustainability issues and policy responses that are relevant to the cross- disciplinary subject of this thesis. The scope of Chapter 2 is not reestricted to the NSW Central West or even to Australiia, but instead draws on international policy and research in order to understand how sustainability is conceptualised across the revegetation, plantation and bioenergy sectors. Chapter 3 complements Chapter 2 by exploring a range of conceptual fframeworks that can be used to inntegrate the key issues and questions under a common notion of sustainability. It focuses on five conceptual frameworks: multifunctionality, conservation through sustainable use, adoption theory, ecological economics and resilience. Each of these conceptual frameworks has implications for the case studies in terms of policy-framing, research methodologies and strategies for dealing with synergies and trade-offs. Chapter 3 concludes by presenting a policy development framework for application to the case studies,
12 drawing on the work of sustainability policy researchers such as Dovers (2005), Clark (2002) and Diesendorf (2000).
Chapter 4 narrows the focus of the thesis by introducing the two case studies at Condobolin and the Central Tablelands. It explores the social, economic and environmental context within which each case study operates and explores past and current actions in the key areas of revegetation, agroforestry and bioenergy. It also provides a detailed overview of the relevant policy measures for the case study sites, which complements the broader policy overview presented in Chapter 2.
Chapters 5, 6 and 7 contain the original case study research undertaken for this thesis, divided according to the three pillars of sustainable development (social, economic and environmental). This format has been selected rather than the use of separate chapters for each case study due to the fact that many of the same environmental and social issues are observed at each site and many of the same bioenergy options are relevant. Each chapter provides a comparison of results from the two case study sites.
Chapter 8 is structured according to the policy development framework outlined at the end of Chapter 3. At this point, the thesis becomes broader again by focusing not only on the development of policy options for the case study sites, but also considering the implications of these policy options for bioenergy-based agroforestry and revegetation more broadly. Chapter 8 draws upon the full range of policy measures, principles and strategies presented in the preceding chapters to offer recommendations for the integration of revegetation, agroforestry and bioenergy policy at the case study sites, as well as highlighting key knowledge gaps that require further research.
Finally, Chapter 9 presents the main conclusions of this thesis. It expands the scope beyond the case study sites to consider the broader lessons that can be learnt from the case study research and from the testing of a new framework for the development of sustainability policy around bioenergy-based agroforestry for revegetation. The implications of this research for policy development and future research extend across a range of sectors, disciplines and jurisdictions.
13 Chapter 2: Literature Review
This chapter presents a review of research and policy relating to revegetation, agroforestry and bioenergy. While the focus of this thesis is on the area of overlap between these three sectors of human activity, most research publications and policy documents have a more narrow focus. As such, this chapter explores each of these sectors separately (sections 2.1 to 2.3) before bringing the three sectors together to explore the sustainability issues that emerge where these activities intersect (section 2.4).
The aim of this chapter is not to identify and explain in detail every sustainability issue, production system and policy instrument that may be relevant to the NSW Central West, as Chapter 4 provides an introduction to these factors at the case study sites. Rather, the aim of this chapter is to examine how sustainability is conceptualised within the revegetation, plantation and bioenergy sectors and what implications these different conceptualisations have for the development of a combined notion of sustainability that can encompass all three sectors simultaneously. Often, the conceptualisations of sustainability used by policymakers are not fully detailed in policy documents and one has to work backwards, analysing the policy actions and stated goals to uncover the principles, priorities and value-judgments that underlie them.
Sustainability policy can take a variety of forms, including statute law, self-regulation, market mechanisms, research and development support, institutional change, assessment procedures and education (Dovers 2005). This chapter draws on policy examples from across the globe, but has a particular focus on Australia. A key influence on the Australian policy environment is the division of responsibilities under the Australian Constitution. The Commonwealth (also referred to as the Australian Government or federal government) has the power to legislate in areas such as taxation, trade, activities of corporations and international agreements, while the states retain control over important elements of policy-making around natural resource management, agriculture, forestry and energy. Some policy-making powers have also been devolved by state government to local government (councils) and regional natural
14 resource management agencies, which in NSW are known as Catchment Management Authorities (CMAs).
2.1 Revegetation and ecological restoration
As discussed in Chapter 1, revegetation for the purpose of ecological restoration encompasses a range of actions aimed at increasing the amount of vegetation within an ecosystem that has been modified through clearing, grazing or other activities. While some restoration activities may be more holistic than others, they all require implicit or explicit prioritisation of certain ecosystem attributes over others. As stated by Lindenmayer et al. (2008, p. 85), “even when conservation is the primary activity, different kinds of plans and actions will result from different objectives such as the maintenance of species diversity, the preservation of particular threatened species, the maintenance of ecological processes that generate diversity, the maintenance of ecosystem services”. Hence, in this thesis, it is considered that there are differing degrees of restoration, ranging from a focus on one particular ecosystem attribute or function (e.g. carbon sequestration or habitat for a single species), through to attempts to restore multiple ecosystem attributes simultaneously. Revegetation can play a role across this restoration spectrum.
2.1.1 Sustainability issues and revegetation objectives
Conservation of biodiversity (biological diversity) is one of the main drivers of revegetation and restoration activities around the world. Biodiversity refers to “the variety of life on Earth and the natural patterns it forms”, including the variety of species, their genetic diversity and the variety of ecosystems (Secretariat of the Convention on Biological Diversity 2000). Identified trends that threaten biodiversity globally include habitat destruction, modification of ecosystems, over-harvesting of species, introduction of invasive species and loss of genetic diversity. Habitat restoration is only one tool that is used to combat these trends, with others being the creation of protected areas, preservation of habitat on private land, sustainable use of wildlife, ex situ species conservation and mitigation of climate change.
15 Policy measures aimed at biodiversity conservation reveal much about the underlying values and objectives of policy-makers. The Convention on Biological Diversity (CBD) forms a key global framework based around three main goals: the conservation of biological diversity, the sustainable use of its components and the fair and equitable sharing of the benefits from the use of genetic resources (Secretariat of the Convention on Biological Diversity 2000). The CBD integrates these goals under the “ecosystem approach”, which recognises biodiversity “both for its intrinsic value and because of the key role it plays in providing the ecosystem and other services upon which we all ultimately depend” (Conference of the Parties to the Convention on Biological Diversity 2000). The ecosystem approach, as endorsed by the CBD, recognises the three pillars of sustainable development and embodies a number of guiding principles relating to equity, human well-being, precaution, adaptive management, participation, valuing multiple sources of information and the importance of scale.
Forest biodiversity is a particular focus of restoration policy under the CBD (Conference of the Parties to the Convention on Biological Diversity 2008), as well as for international conservation NGOs (non-governmental organisations) such as IUCN (International Union for Conservation of Nature), WWF (World Wildlife Fund) and Greenpeace. A joint 2002 WWF/IUCN project provides an example of this focus, promoting the concept of Forest Landscape Restoration as “a planned process that aims to regain ecological integrity and enhance human well-being in deforested or degraded landscapes” (Mansourian 2005, pp. 10-11). This approach includes a focus on landscape-scale implementation, stakeholder participation and the socio-economic dimensions of forest degradation.
As is the case globally, a particular focus of biodiversity conservation in Australia has been on forests and woodlands and it is in this context that the terms revegetation and restoration are often used interchangeably (e.g. Cork, Sattler & Alexandra 2006, Hatton et al. 2011). This focus is partly a response to high rates of clearing since European settlement (Beeton et al. 2006), but also significant is the fact that many forests are iconic ecosystems and provide habitat for native animals. Vesk and Mac Nally (2006, p. 357) emphasise that, in the agricultural landscapes of southern Australia, “woody vegetation provides most of the habitat structure and resources for
16 animals”. Moving from the national or state scale down to the regional scale, revegetation goals often become more specific. For example, the NSW Government goal that “By 2015 there is an increase in native vegetation extent and improvement in native vegetation condition” (Natural Resources Commission 2005, p. 69) has been translated into more specific regional targets by Catchment Management Authorities (CMAs), such as “by 2021, 8-16% of priority vegetation communities are being actively managed to achieve a good condition stable state, increase net extent and, where possible, increase connectivity” (Central West Catchment Management Authority 2011, p. 8).
In addition to habitat loss, habitat fragmentation can threaten biodiversity, with many remnant patches become increasingly small and isolated over time (Harrison & Bruna 1999, Watling & Donnelly 2006, Fleishman & Mac Nally 2007). The process of locating and designing revegetation sites, which Vesk and Mac Nally (2006) term “landscape reconstruction”, is a key element in combating fragmentation. Climate change has also been identified as a key threat to Australia’s fragmented habitats, with the small and isolated nature of many protected areas and the high degree of species endemism making Australia particularly susceptible to projections of higher temperatures, shifts in rainfall patterns and increased fire danger in coming decades (Hennessy, Fitzharris, Bates, Harvey, Howden, Hughes et al. 2007). As such, revegetation to improve habitat connectivity has been emphasised as an important climate change adaptation strategy by researchers such as Lindenmayer, Steffen, Burbidge, Hughes, Kitching, Musgrave et al. (2010) and Hatton et al. (2011).
While revegetation can help to increase patch size and improve connectivity, there is much debate about the best ways to carry out such activities (e.g. Vesk & Mac Nally 2006, Lindenmayer et al. 2008). The 2006 Australian State of the Environment Report cited the importance of revegetation and restoration, stating that “restoration will often be the only way to give some elements of biodiversity a reasonably secure future” (Beeton et al. 2006, p. 44). However, the report also highlighted challenges included a lack of fine-scale data, inconsistency between jurisdictions, poor understanding of many ecological communities and a lack of benchmarks against which to measure the success of restoration projects (Beeton et al. 2006). The 2011 State of the Environment
17 Report (Hatton et al. 2011) also has a strong focus on revegetation and restoration for biodiversity conservation and calls for a shift towards “decision science”, whereby monitoring, reporting and scenario modelling are used to identify the best locations and most cost-effective strategies for protecting habitat, increasing connectivity and restoring ecological functions.
Lindenmayer et al. (2008) argue that clear goals are often lacking in conservation and restoration work and propose an approach based around an initial visioning process, from which detailed objectives can be derived. One example of a visioning process is the selection of surrogate ecosystems to provide benchmarks for restoration. Surrogates may be selected based on the presence of valued species or functions, or according to notions of “naturalness”. The use of naturalness as a restoration benchmark is controversial and can be highly subjective. Such approaches may be based on an underlying value-system that views humans as separate from nature, as shown in Jordan’s (1994, p. 32) argument that restoration should aim to "compensate for human influence on an ecological system in order to return the system to its historic condition". Other authors view restoration as a human impact in itself, with Lindenmayer et al. (2008, p. 82) recognising that there are “different human perspectives on what is appropriate vegetation structure and condition” and arguing that it is “difficult to determine what is natural in landscapes long influenced by humans, where naturalness may not even be an appropriate characteristic to consider”. Similarly, Beeton et al. (2006, p. 44) argue that successful restoration may require that “absolute concepts of naturalness be abandoned in favour of management for specific objectives”.
In addition to biodiversity conservation, concerns about soil and water health can be key drivers of revegetation policy, encompassing issues such as soil erosion, salinity, desertification, eutrophication and siltation of waterways. Policy around these issues is more often focused at the local, regional or national scales rather than the global scale. Australia is particularly prone to the effects of dryland salinity, whereby the removal of deep-rooted perennial plants allows water tables to rise and bring salt to the surface. Southwest Western Australia, where land-clearing for wheat production has been extensive, is the worst affected area, possessing approximately 4.4 million of the 5.7
18 million hectares of land in Australia with “high potential to develop dryland salinity” (National Land and Water Resources Audit 2001). Other priority areas include parts of the Murray-Darling Basin, southwestern Victoria and central Queensland. Revegetation has been identified as a key tool for salinity mitigation (e.g. Environment Australia 2001, van Dijk, Hairsine, Arancibia & Dowling 2007) and generally involves either the establishment of deep-rooted perennials in groundwater recharge areas or the remediation of salinised land with salt-tolerant species.
In terms of water quality, revegetation is only one management tool alongside others such as revising farming techniques, preventing further clearing and managing water extraction and environmental flows. The 2006 Australian State of the Environment Report states that “extensive revegetation is required to improve river health” (Beeton et al. 2006, p. 63). As with biodiversity conservation and salinity mitigation, the location of revegetation areas and the selection of species are of critical importance for river health.
Another driver for revegetation is the mitigation of anthropogenic climate change through carbon sequestration. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) stated that “Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic GHG concentrations” (Intergovernmental Panel on Climate Change 2007, p. 39). Forests, soils and other elements of the biosphere have the capacity to sequester carbon and thus reduce atmospheric concentrations of carbon dioxide, the most significant greenhouse gas (GHG). The critical factor in selecting sites and species to achieve this goal is the amount of carbon that can be sequestered (both above and below ground), rather than attributes such as habitat quality, connectivity, erosion control or groundwater impacts. Due to the global nature of climate change, much of the policy development around revegetation for carbon sequestration occurs at a global scale, under the United Nations Framework Convention on Climate Change (UNFCCC) and its associated agreement, the Kyoto Protocol2. However, individual countries also play a role in developing rules around
2 Under the Kyoto Protocol’s category of land use, land use change and forestry (LULUCF), qualifying reforestation/afforestation must meet minimum canopy cover and tree height requirements for a “forest”,
19 biosequestration, as the Australian Government has done through the development of the Carbon Farming Initiative, which allows for sequestration activities that fall both within and outside of the Kyoto Protocol’s sequestration accounting rules (Department of Climate Change and Energy Efficiency 2010).
While there are clearly differences in the ways that problems relating to biodiversity loss, soils, water quality and climate change are framed in the development of revegetation policy, there are also some commonalities in terms the goals that have been set and the policy instruments employed. In particular, benchmarks for all types of revegetation are based around a goal of enhancing environmental values. This contrasts with many of the sustainability benchmarks employed in the forestry and agriculture sectors, which are based around maintaining selected values (discussed further in section 2.2).
The degree to which key threats to native vegetation have been controlled through complementary measures can be important in shifting the focus of policy-makers from maintenance to enhancement. For example, Beeton et al. (2006) highlight that state government policies to end broad-scale land clearing have been critical to the creation of a policy environment in Australia where revegetation and restoration can be prioritised. In countries with continuing high rates of deforestation, conservation efforts are more likely to focus on preventing further forest loss rather than revegetation. However, despite efforts to control vegetation clearing in Australia, the 2011 State of the Environment Report argues that management inputs are “still inadequate to halt or reverse the effects of land clearance” (Hatton et al. 2011, p. 665).
2.1.2 Revegetation policy instruments
Policy measures to promote revegetation generally feature the use of incentives that support or reward revegetation actions through grants or other payments. Regulation
while “revegetation” is not bound by these restrictions. Both categories have minimum area requirements and must occur on land that did not possess such vegetation as of 1990 (Schlamadinger, Boonpragob, Janzen, Kurz, Lasco, Smith et al. 2003).
20 can provide an important underpinning for revegetation policy by preventing further vegetation clearing, but is rarely used to compel landholders to undertake revegetation. Grants are the most common policy instrument used in Australia, such as those provided under the Australian Government’s Caring for our Country program and, prior to that, the Natural Heritage Trust (Commonwealth of Australia 2008). Funding programs may also be run by NGOs such as Greening Australia and Bush Heritage Australia. Grant programs generally aim to cover some of the costs of revegetation but do not seek to make revegetation profitable for a landholder or to cover the opportunity costs of taking land out of agricultural production.
As revegetation is generally regarded as having a net financial cost to landholders, the focus of economic analysis regarding revegetation often revolves around cost- effectiveness rather than profitability (e.g. Crossman & Bryan 2009, Pannell, Roberts, Alexander, Park & Marsh 2009). The social dimensions of revegetation are also an important consideration for policy development, including identifying synergies between the motivations of landholders and the goals of policy-makers (e.g. Herbohn, Emtage, Harrison, Smorfitt & Slaughter 2005). Compared with Australia, revegetation projects in developing countries often feature a greater focus on the alignment between socio-economic and environmental objectives, which can be crucial to maintaining outcomes over the long-term (e.g. Mansourian 2005, Oviedo 2005).
Market-based instruments are increasingly being employed as part of revegetation policy in Australia. Auction approaches, such as Victoria’s BushTender program (Department of Sustainability and Environment 2008), weigh up competing bids for funding against likely outcomes to determine cost-effectiveness. Other schemes are based on a model of payments for ecosystem services (PES), under which direct payments or tradable credits are allocated to certain revegetation activities that provide environmental services such as carbon sequestration or conservation of habitat. Some PES schemes allow the trading of credits generated by revegetation activities to businesses that want or need to offset the impact of an environmentally damaging activity, such as emitting greenhouse gases or clearing native vegetation. The key pre- requisites for tradable offset schemes are:
21 1. Demand for offsets for environmentally damaging activities, which may be created by a regulatory requirement to offset impacts or voluntary decisions by businesses to offset their impacts; 2. A system to verify that revegetation projects are able to provide the required ecosystem services (e.g. carbon sequestration or habitat value) and award credits accordingly; and 3. A market mechanism to allow trading to take place between those providing the environmental services and those wishing to undertake damaging activities.
The NSW Government introduced a scheme allowing carbon credits to be generated through revegetation in 2003 (Greenhouse Gas Reduction Scheme 2007). Under this scheme, major emitters of greenhouse gases face regulatory limits on emissions, which they are able to partially offset by purchasing credits from landholders undertaking revegetation that sequesters carbon. The NSW scheme is due to be replaced by the Australian Government’s new carbon pricing mechanism, which starts with a fixed- priced emissions permit system from mid-2012 before transitioning to a cap-and-trade scheme after 3 years (Commonwealth of Australia 2011b). This scheme will also allow offsetting through the Carbon Farming Initiative, which allows landholders to earn tradable credits for biosequestration. NSW also has a tradable credit scheme covering habitat for biodiversity, known as BioBanking. This scheme allows landholders to trade biodiversity values from their land to developers intending to impact on biodiversity through clearing elsewhere (Department of Environment and Climate Change 2007).
Different policy instruments for revegetation are underlain by differing principles, values and trade-offs in relation to sustainability. Schemes such as BushTender, carbon trading and BioBanking are based on an assumption that ecological values at a particular site are substitutable for values at other sites (and possibly for money). This places them at the “weak” end of the sustainability spectrum discussed in Chapter 1. However, the degree of substitutability varies depending on the rules of each scheme. Carbon trading and BioBanking also feature the “polluter-pays” principle, while BushTender is based on the “beneficiary-pays” principle, with the beneficiary being the public (represented by the government).
22
Revegetation policy can also feature other trade-offs between environmental, social and economic objectives, with carbon trading providing one of the clearest examples. At the global scale, the Kyoto Protocol includes social and economic considerations such as having differentiated responsibilities for developed and developing nations and the use of historic emissions levels to set future targets. The long-running policy debate regarding carbon pricing in Australia has resulted in numerous exemptions being proposed for particular industries and compensation for disadvantaged social groups (Commonwealth of Australia 2011b). This has also resulted in selective application of policy principles, such as the provision of a mechanism for landholders to earn credits by restoring vegetation but no requirement for landholders to purchase credits to clear vegetation or to cover other emissions from agriculture such as fertiliser use or methane emissions from grazing animals (Commonwealth of Australia 2011b).
In summary, revegetation and restoration policies in Australia are primarily motivated by concerns about biodiversity loss, soil and water degradation, and climate change. Such policies generally feature goals based around improving rather than maintaining ecological values. The framing of policy and the setting of goals and benchmarks for restoration are influenced by the scale of identified problems, the degree of uncertainty surrounding them, the prioritisation of ecological attributes and differing notions of “naturalness” and substitutability. Restoration through revegetation is generally viewed as a cost to landholders and thus economic incentives are often required that involve either direct funding from governments or market-based instruments that redirect funds from polluting industries to those undertaking revegetation. Details on the specific revegetation policy measures affecting the case study sites are presented in Chapter 4.
2.2 Plantations and agroforestry
This section is primarily concerned with forms of forestry and agriculture that involve plantations of woody perennials. Forestry practices such as the harvesting of native forests and agricultural practices involving annual crops or grazing are discussed only in relation to their influence on how notions of sustainability around plantations are framed. In particular, this section seeks to understand the key sustainability
23 considerations for agroforestry, whereby plantations are integrated with crop or livestock production on the same land management unit (FAO 1993). Section 2.3 deals with circumstances where the primary purpose of a plantation is to produce energy.
2.2.1 Notions of sustainability in the plantation sector
While revegetation involves the establishment of woody vegetation primarily for ecological enhancement, the primary motivation of the forestry and agriculture sectors is to satisfy human demands for timber, food, fibre or other commodities. Such activities clearly have an economic dimension, as harvested commodities can be sold for profit, as well as a social dimension relating to various human wants and needs. While the economic benefits of plantations are the primary motivation for their establishment and maintenance, it is often the environmental and social impacts of plantations that drive the development of policy invoking the terms “sustainable” or “sustainability”. These impacts can include environmental threats to biodiversity, soils, waterways and climatic stability, as well as social threats to land rights, workers’ rights and the equitable distribution of benefits. The framing of these sustainability issues and the selection of policy instruments reveals much about policymakers’ underlying values, principles, goals, priorities and visions for sustainability.
Defining sustainability in a forestry or agriculture context is contentious (Thompson, Jay, Connell, Norman & Vanclay 2006), with many different definitions found in policy documents, industry standards and academic publications. Figure 2.1 compares a number of prominent sustainability definitions from the forestry and agriculture sectors along a spectrum from “weak” to “strong”, based on the extent to which they allow for substitution between natural and human-made capital (as discussed in Chapter 1). The definitions cited in Figure 2.1 are predominantly from the forestry sector, reflecting the assertion of O'Connell, Braid, Raison, Handberg, Cowie, Rodriguez et al. (2009a, p. 69) that, compared to forestry, agriculture in Australia “does not have a comparable policy and regulatory framework with respect to setting and achieving sustainability goals”.
24 Ecologically Sustainable Forest Ecologically Sustainable Forest Management Sustainable Forestry Sustainable Forest Sustainability Management (Australian Forestry (Lindenmayer, Franklin Management Roundtable on (Department of Standard Limited 2007) & Fischer 2006) (Ministerial Conference on the Sustainable Agriculture Fisheries Protection of Forests in Europe Palm Oil The integration of …perpetuating and Forestry 2007) 2002, PEFC Council 2006) (Jennings & commercial and non- ecosystem integrity Nussbaumm ESFM is about commercial values of while continuing to The stewardship and use of 2004) managing forests to forests so that both the provide wood and non- forests and forest land in a way ensure they meet our material and non-material wood values; where and at a rate, that maintains their Sustainability present needs without welfare of society is ecosystem integrity biodiversity, productivity, implies affecting the options improved, whilst ensuring means the maintenance regeneration capacity, vitality and economic, they can provide for that the values of forests, of forest structure, their potential to fulfil now and in social and future generations both as a resource for species composition, the future, relevant ecological, environmental and, at the same time, commercial use and for and the rate of economic and social functions, at viability maintain and protect conservation, are not lost ecological processes local, national and global levels other forest values. or degraded for current and functions within the and does not cause damage to and future generations. bounds of normal other ecosystems. 25 disturbance regimes.
Weaker Stronger
Attributes of weak sustainability Attributes of strong sustainability x Intergenerational equity allows substitution of human- x Intergenerational equity requires conservation of biodiversity, made capital for natural capital ecological integrity, cultural diversity and critical capital x Focus on economic growth rather than the broader x Well-being includes ecological, social and economic concept of development indicators, but not necessarily economic growth x Ecologically sustainable development focuses on x Ecologically sustainable development focuses on achieving maintaining existing industries ecological sustainability, social equity and well-being
Figure 2.1: Selected sustainability definitions for forestry and agriculture. Weak/strong sustainability attributes from Diesendorf (2000).
Generally, the vaguer the definition in Figure 2.1, the “weaker” it is, as the opportunity for substitution of natural capital is greater. The two definitions most relevant to Australia, from the Department of Agriculture, Fisheries and Forestry (2007) and the Australian Forestry Standard Limited (2007), do not specify which forest values must be maintained or whether values can be traded off against one another. In contrast, the definitions of Lindenmayer et al. (2006) and the Ministerial Conference on the Protection of Forests in Europe (2002) leave less room for substitution, requiring that the capacity to meet human demands is maintained alongside specific elements of natural capital such as biodiversity, forest structure and ecological processes.
Just as definitions of sustainable forest management can differ, significant variations can also be found in the way that sustainability issues around plantations are identified and prioritised. Table 2.1 highlights these differences by comparing prominent sustainability criteria and principles relating to forestry and plantation management published by: x The Montréal Process Working Group (2007), an intergovernmental forest management grouping that includes Australia; x The Forest Stewardship Council (2002) or FSC, a prominent forest sector NGO; x The Sustainable Agriculture Network (2008) or SAN, also an NGO (part of the Rainforest Alliance); x Australian Forestry Standard Limited (2007) or AFS, an industry-led forestry certification program; and x The Roundtable on Sustainable Palm Oil (2007) or RSPO, an industry-led endeavour to promote sustainable palm oil production.
26 Table 2.1: Sustainability issues from selected forestry and agriculture standards. Criteria are summarised and paraphrased. Montréal Process FSC International AFS Criteria 2007 SAN Principles RSPO Principles 2007 Criteria 2007 Principles 2002 2008 1. Conservation of 1. Compliance with 1. Systematic management 1. Social & 1. Transparency biological diversity laws & FSC of a range of forest values environmental 2. Compliance with Principles management 2. Maintenance of 2. Public participation applicable laws & system regulations productive capacity 2. Tenure & use rights 3. Protection & maintenance 2. Ecosystem of forest ecosystems & responsibilities of forest biodiversity 3. Long-term economic conservation & financial viability 3. Maintenance of 3. Indigenous rights 4. Maintenance of the 3. Wildlife forest ecosystem 4. Community relations productive capacity of 4. Best practices by protection health & vitality & worker’s rights forests growers & millers 4. Water 4. Conservation & 5. Benefits from the 5. Maintenance of forest 5. Environmental conservation maintenance of soil forest ecosystem health/vitality responsibility & & water resources 5. Fair treatment & conservation of 6. Environmental 6. Protection of soil & water 5. Maintenance of good working natural resources & 27 impact resources forest contribution conditions biodiversity 7. Management plan 7. Maintenance of forest to carbon cycles 6. Occupational 6. Employees, contribution to carbon 8. Monitoring & health & safety individuals & 6. Maintenance & cycles assessment communities affected enhancement of 7. Community 8. Protection & maintenance by growers & mills long-term multiple 9. Maintenance of high relations of natural, cultural, socio-economic conservation value 7. Responsible social, recreational, 8. Integrated crop benefits forests development of new religious & spiritual management 7. Legal, institutional 10. Plantations (should plantings heritage 9. Soil & policy framework complement, take 8. Continuous 9. Maintenance & management & for conservation & pressure off & improvement in key enhancement of long- conservation sustainable promote restoration areas of activity term social & economic management of natural forests) 10.Integrated waste benefits management
Apart from the Montréal Process criteria, the other standards are designed for use in the certification of products for consumers who wish to avoid contributing to unsustainable forest harvesting or plantation establishment. Such certification is often interpreted to mean a product is sustainable and, in some cases, this is suggested by the standards themselves3. More commonly however, the stated aims of the standards are to “promote” the sustainability of forestry or agricultural production (e.g. Sustainable Agriculture Network 2008, p. 4) or to “support continual improvement” (e.g. Australian Forestry Standard Limited 2007, p. 4). It is also notable that some standards do not actually define key terms such as “sustainable” (Sustainable Agriculture Network 2008) or “stewardship” (Forest Stewardship Council 2005). The Montréal Process criteria have been designed for reporting rather than certification of products and thus do not use prescriptive terms like “must” or “shall” which are found in the other standards.
The principles and criteria shown in Table 2.1 reflect different stakeholder priorities and the different contexts in which the standards operate. The industry-led standards have a greater focus on economic aspects of sustainability, with the RSPO devoting one entire principle to “long-term economic and financial viability” and the AFS employing a notion of “productive capacity” that includes marketable forest goods and services but is “not usually applied to non-market benefits such as ecosystem services” (Australian Forestry Standard Limited 2007, p. 15). In contrast, the FSC and SAN standards treat economic benefits as a subset of broader social objectives, such as “benefits from the forest” (FSC) or “community relations” (SAN). The FSC’s notion of “ecological productivity” focuses not only on marketable goods but also requires maintenance of “natural cycles that affect the productivity of the forest ecosystem” (Forest Stewardship Council 2002, p. 6). The SAN requires a social and environmental management system, but not an economic one, and focuses on the distribution of economic benefits rather than economic viability. The Montréal Process falls somewhere in between, focusing on economic production factors such as growing
3 For example, the Roundtable on Sustainable Palm Oil (2007, p. 2) state that “sustainable palm oil production” is "delivered through the application of the following set of principles and criteria”. Similarly, Australian Forestry Standard Limited (2007, p. 9) state that “the AFS defines sustainable forest management according to a set of nine criteria”.
28 stock and harvest levels as well as on non-wood production, environmental services, cultural values and the resilience of forest communities.
In relation to the social pillar of sustainability, the FSC and RSPO standards have the strongest requirements for producers to demonstrate land tenure and usage rights. This reflects the fact that they have been developed for use in developing countries, where displacement of vulnerable people has been caused by the expansion of forestry activities (Larson, Cronkleton, Barry & Pacheco 2008) and oil palm plantations (Oxfam International 2007). In contrast, the AFS criteria (covering Australia only) and the SAN principles (covering agriculture but not forestry) have no requirements for producers to demonstrate land tenure, although they do require respect for community values and traditional uses. All five standards have clauses covering workers’ rights, with the SAN standard being the most detailed. The FSC standard has the strongest requirements on competition for water resources, stating that plantations “shall not” result in adverse impacts on water quantity or stream course drainage patterns (Forest Stewardship Council 2002, p. 10). The RSPO standard is the only one to specifically mention food security, albeit as a factor that may be considered under national interpretations of the standard.
In terms of environmental impacts, the most prominent issues appearing in the five standards are biodiversity conservation, soil and water protection and mitigation of climate change. While these are the same three issues that dominate the revegetation sector (discussed in section 2.1), there is major difference in terms of the benchmarks applied. While revegetation is primarily concerned with enhancement of environmental attributes, forestry and agriculture standards focus on maintenance. For example: x “maintenance of forest ecosystem health and vitality” (Montréal Process, p. 9) x “maintain or improve soil structure, fertility, and biological activity” (FSC, p. 10) x “maintain forests’ contribution to carbon cycles” (AFS, p. 27) x “maintain the integrity of aquatic or terrestrial ecosystems” (SAN, p. 19) x “maintain the quality and availability of surface and ground water” (RSPO, p. 14)
29 The focus on maintenance of environmental values extends to plantation establishment, which is not permitted to occur at the expense of “natural forest” (FSC & SAN), “primary forest” (RSPO) or “native vegetation” (AFS)4. The FSC and AFS allow some exceptions for “very limited” or “small-scale” clearing respectively, provided that the impacts are outweighed by related conservation benefits. The AFS allowance for clearing (less than 10% of a forest management unit up to a limit of 40ha) has been controversial and represents a trade-off between environmental and economic goals (Peacock & Wintle 2006, Peacock 2007).
2.2.2 Plantation policy in Australia
Plantation managers in Australia can voluntarily have their products certified under the AFS. FSC also intends to develop specific national standards for Australia (FSC Australia 2010). However, in addition to these voluntary standards, there are a number of government policy measures relating to plantation sustainability in Australia. Forestry policy is a joint state and Commonwealth responsibility, with a key policy measure being the Regional Forestry Agreements (RFAs) that integrate state responsibilities for natural resource management and Commonwealth powers over exports. The ten completed RFAs attempt to balance the forestry industry’s desire for certainty of access and supply with the environmental and social concerns of other stakeholders. RFAs outline forest areas that can be harvested and those that must be preserved within each region, as well as setting harvest limits and accrediting Ecologically Sustainable Forest Management (ESFM) systems. The establishment of plantations is actively encouraged under many ESFM plans (e.g Forests NSW 2005, 2008a) due to economic and social benefits and the potential to take pressure off native forests. While the RFA process includes stakeholder consultation and targeted scientific input, many aspects remain controversial, especially old growth forest logging and the determination of “sustainable” harvest rates (Brueckner & Horwitz 2005).
4 The Montréal Process has no equivalent requirement due to its focus on reporting rather than compliance.
30 In NSW, plantation establishment and management is primarily regulated under the Plantations and Reafforestation Code, which constitutes a regulation under the Plantations and Reafforestation Act 1999 (NSW) and is part of the accredited ESFM system in NSW. The Code places different restrictions on the clearing of different vegetation classes (e.g. rainforests, wetlands, woody native vegetation and regrowth) and sets requirements for buffer zones, soil and water protection, road construction and the protection of cultural heritage. The Code is focused on ensuring that ecological values are maintained under plantation development, but there is no requirement for plantations to improve ecological values. Furthermore, apart from the protection of cultural heritage sites, the Code does not attempt to cover economic or social aspects of sustainability such as economic viability, land rights or workers’ rights.
Taken together, the RFA framework and NSW Code present a vision of sustainability in which plantation expansion should be promoted, but must also be regulated to ensure that deleterious environmental impacts do not occur. The goal of plantation expansion has been further enshrined through Plantations2020, a joint initiative between state and federal governments, private forest growers and the forestry industry that has set a target of trebling Australia’s plantation estate between 1997 and 2020. The aims of this expansion are to keep pace with growing demand for timber and other forest products, to turn around Australia’s trade deficit in such products, to provide socio-economic benefits for regional Australia and to help solve natural resource management problems such as climate change and salinity (Plantations2020 2002). This strategy has seen an increase in Australia’s plantation estate of about 55% in the decade to 2008, almost entirely made up of native hardwoods (Bureau of Rural Sciences 2009). Farm forestry, which involves establishing plantations on existing cropping or grazing land, has also seen an increase in area of around 50% between 2001 and 2008 (URS Forestry 2008a).
A key policy instrument that has been used in Australia to promote plantation expansion has been the availability of income tax deductions for investments in forestry plantations through managed investment schemes (MIS). Under such schemes, investors contribute to a pool of funds but don’t play an active role in day-to-day plantation management (Plantations2020 2009). Any up-front investment in an MIS
31 plantation can be deducted from an investor’s taxable income in that year. While taxes must be paid on plantation income as it accrues (in 10-30 years’ time), the upfront tax deduction provides an important incentive to invest, especially for high income earners seeking to avoid high marginal income tax rates. As of 2009, MIS investment accounted for 80% of all new timber plantation investment in Australia (Plantations2020 2009).
While plantation development can offer socio-economic benefits for landholders and regional economies (Polglase, Paul, Hawkins, Siggins, Turner, Booth et al. 2008, Schirmer, Loxton & Campbell-Wilson 2008), rapid rates of plantation expansion have met with resistance in some rural communities due to factors such as loss of good agricultural land, competition for water, use of chemicals, visual amenity and population decline (e.g. Tonts & Schirmer 2005, Parsons, Frakes & Gerrand 2007, The Wilderness Society Tasmania 2010). Based on survey data from Western Australia and Tasmania, Williams (2009a, 2009b) suggests that plantations are more likely to be accepted if they are on poor quality or saline soils, are in areas with good water availability, are on land previously used for plantations, occupy only part of a property, involve local processing and are owned by farmers rather than outside investors. None of these factors are considered under the NSW Plantations and Reafforestation Code, but they do feature to varying degrees in the sustainability standards from the FSC, SAN and AFS (particularly water use and local employment). Criticism has also been levelled specifically at MIS policy, including the accusation that MIS plantation establishment has been aimed more at delivering tax breaks for investors than delivering lasting benefits for regional communities (e.g. Ajani 2008). Although tax rules were tightened in 2007 to ensure that MIS companies are set up for the establishment of viable plantations rather than for tax benefits alone, the collapse in 2009 of two prominent MIS companies, Timbercorp and Great Southern, sparked a renewed round of criticism (e.g. Williams & Hopkins 2009).
Apart from MIS tax-breaks, Low et al. (2010) explored a range of other policy options that could be used to promote plantation investment. These include tax credits that are based on rotation length rather than establishment costs, government-funded research and development (R&D), facilitation of industry partnerships, market regulations to
32 ensure a level playing field between forestry and other industries, greenhouse gas emissions trading schemes and renewable energy incentives programs. State government agencies, such as the Forest Science Centre within NSW Trade and Investment, undertake a range of research that is primarily focused on state-owned forests and plantations. In addition, the Joint Venture Agroforestry Program (JVAP) previously funded a range of R&D focused on the integration of plantations into agricultural landscapes, including genetic development, silvicultural practices, agroforestry design principles and the provision of ecosystem services such as windbreaks, salinity mitigation and carbon sequestration (RIRDC 2006). Renewable energy support is discussed further in section 2.3.
The role that carbon trading can play in promoting plantation establishment is similar to its role in promoting revegetation (discussed in section 2.1). Even though a plantation will be periodically harvested, it may still be able to generate carbon credits based on the difference between the pre-existing level of carbon stored in the land unit and the minimum or average level of carbon stored in the plantation over successive cycles of growth, harvesting and replanting. Figure 2.2 demonstrates how minimum or average carbon stocks can be calculated from plantations that have fluctuating carbon levels due to periodic harvesting or other disturbances, using examples from the NSW Greenhouse Gas Reduction Scheme and the Australian Government’s Carbon Farming Initiative.
33 Figure 2.2: Calculation of minimum and average carbon stocks within plantations. Graph (a) shows minimum carbon stocks within a plantation pool (Independent Regulatory and Pricing Tribunal 2009, p. 41), while (b) shows a five-year rolling average (Department of Climate Change and Energy Efficiency 2010, p. 20).
While Figure 2.2b shows a generalised approach to calculating average levels of carbon sequestration in harvested plantations, specific methodologies that would allow such plantations to earn carbon credits are yet to be developed under the Carbon Farming Initiative. Concerns have arisen that an expansion of commercial plantations supported by carbon credits could contribute to “adverse impacts on access to agricultural land, communities and employment” and “adverse impacts for other water
34 users and environmental flows” (Department of Climate Change and Energy Efficiency 2011, p. 12). Commonwealth regulations passed in late 2011 make a number of carbon sequestration activities ineligible for the Carbon Farming Initiative, including plantings on land that has been cleared of native vegetation in the three years prior, plantings funded through a forestry MIS and plantings in areas with greater than 600 mm mean annual rainfall that do not hold entitlements for their estimated use of water from rainfall5. Thus, the Carbon Farming Initiative, in its present form, is a policy instrument aimed primarily at non-harvested revegetation activities rather than the establishment of commercial plantations.
2.2.3 Plantations and revegetation
As demonstrated by plantation policy instruments such as the NSW Plantations and Reafforestation Code and the Australian Forestry Standard (AFS), notions of plantation sustainability predominantly focus on the maintenance of environmental and social values. However, examples can also be found where active ecosystem enhancement is seen as an integral part of plantation sustainability. For example, the SAN standard (Sustainable Agriculture Network 2008) requires active restoration in areas unsuitable for agriculture or bordering roads, while the FSC standard (Forest Stewardship Council 2002) requires a portion of the forest management area to be restored to natural forest cover, appropriate to the scale of the plantation. Within plantations themselves, the SAN standard sets minimum requirements for tree density, shade provision and the use of native species, while the FSC standard encourages wildlife corridors, streamside zones, species diversity, mosaics of different-aged stands and the use of native rather than exotic species.
Environmental expectations of plantations can vary not only between the authors of different sustainability standards, but also over time. Norton (2005) documents such a shift in expectations in New Zealand, where responsibility has increasingly been placed on plantation managers to improve environmental values rather than simply maintain them. In the 1980s, when NGOs were campaigning against the harvesting of New Zealand’s remaining native forests, the establishment of exotic pine plantations
5 Carbon Credits (Carbon Farming Initiative) Regulations 2011 (Cth)
35 on farmland was widely seen as an environmentally beneficial alternative. Norton reports that this changed somewhat after most remaining forests were protected in the late 1980s, with greater scrutiny then being applied to the impacts of plantations on soil, water and biodiversity. Although New Zealand pine plantations generally fare better against these criteria than the livestock grazing they replace, there have been increasing calls for plantations to approximate some of the functions of native forests, through measures such as mixed-species design, increased rotation length and landscape integration (Norton 2005).
Tonts and Schirmer (2005) discuss a similar shift in attitudes towards plantation expansion amongst environmental NGOs and the Western Australian Greens Part. Support for plantations amongst these groups, based on their potential to take pressure off native forests, was initially enthusiastic, extending as far as praising the quality of plantation woodchips and the employment opportunities they created. However, a more ambivalent feeling emerged after it became apparent that plantation development was predominantly taking the form of large-scale monocultures rather than integrated farm forestry involving a mixture of species and plantation designs. Parallels can also be found in Tasmania, where the Australian Conservation Foundation (2010) has endorsed plantation expansion as a key part of the solution to the long-running conflict over native forest harvesting, while the Wilderness Society Tasmania (2010) has opposed further plantation expansion due to issues such as chemical use and the loss of agricultural land. These examples highlight the difficulties in selecting a single point of reference for assessing plantation sustainability. Benchmarks can be based around what plantations help prevent (e.g. the harvesting of native forests), what they have replaced (e.g. grazing or cropping) or what they could potentially become (e.g. biodiverse forest ecosystems).
Where policy-makers seek to promote plantations that offer environmental enhancement, trade-offs are likely to be needed between economic and environmental goals, along with a mix of policy instruments that can both promote and guide plantation establishment. The Community Rainforest Reforestation Program (CRRP), which established 3200 ha of plantations in North Queensland between 1993 and 2000, highlights some of the policy issues that can emerge when the plantation forestry and
36 revegetation sectors overlap (Erskine, Lamb & Bristow 2005). The CRRP was established with four key goals (Vize, Killin & Sexton 2005): 1. Develop a sustainable private timber plantation resource for industry; 2. Address land degradation; 3. Improve water quality through riparian revegetation; and 4. Train a workforce to support long-term plantation establishment
The environmental goals (2 & 3) clearly feature benchmarks of enhancing rather than simply maintaining environmental values, while the socio-economic goals (1 & 4) were heavily influenced by the declaration of the Wet Tropics of Queensland World Heritage Area in 1988, which led to a loss of timber harvesting and concerns about industry decline and job losses. Vize et al. (2005) argue that a failure to agree on trade- offs between goals was a source of tension throughout the program.
The early stages of the CRRP were based on an assumption that the synergy between economic and environmental goals would drive reforestation that delivered both. Accordingly, the main focus was on extension services, such as the provision of information, free seedlings and planting assistance. However, most early plantings turned out to be small-scale and primarily for aesthetics or riparian rehabilitation, reflecting the assessment of Harrison et al. (2005, p. 269) that agroforestry was “marginally attractive as an investment and relatively high risk”. This led to a greater focus on economic drivers in the CRRP’s later stages (1995-2000), including a focus on larger plantings, a more commercial mix of species, planting levies to foster a sense of ownership, marketing strategies and demonstration sites (Vize et al. 2005). The primary focus of policy-makers was on plantation establishment rather than ongoing management and monitoring. Evaluation of project outcomes was hampered by the fact that CRRP plantations were not established in ways that allowed objective testing of hypotheses, such as the hypothesis that mixed-species plantations would enhance productivity and reduce risk (Lamb, Erskine & Huynh Duc Nhan 2005).
The example of the CRRP highlights the fundamental differences that can exist between revegetation support programs, which are generally aimed at delivering environmental benefits while assuming that actions will not be profitable, and
37 plantation policy, which is generally based on a benchmark of environmental neutrality and an assumption that plantations will be established primarily for profit. The fact that most of the initial plantation adoption under the CRRP was for aesthetics and rehabilitation rather than profit may have surprised stakeholders employing plantation sector assumptions, but would not necessarily surprise those employing assumptions from the revegetation sector.
In summary, notions of sustainability in the plantation sector generally feature goals of enhancing economic outcomes while maintaining environmental and social values that could be threatened by plantation expansion. These goals result in a combination of policy measures, including tax breaks and R&D designed to promote plantations, as well as regulations and industry standards that are designed to restrict inappropriate development. However, conceptualisations of plantation sustainability are not uniform, with different stakeholders identifying differing goals, threats, trade-offs and benchmarks. An overlap zone between the plantation and revegetation sectors can also be identified, where goals of environmental enhancement exert an influence on plantation establishment. Within this overlap zone, a diversity of policy instruments drawn from both sectors are likely to be required and complex policy interactions may result.
2.3 Bioenergy
As discussed in Chapter 1, bioenergy can take a variety of forms, including solid fuels (e.g. fuelwood, charcoal, wood pellets), liquid fuels (e.g. ethanol, biodiesel) and gaseous fuels (e.g. biogas, syngas). Bioenergy can also be produced from a wide variety of feedstocks, including wastes/residues and dedicated energy crops. The main focus of this section is on energy cropping, as this is where the goal of producing energy has the greatest influence on the way that land is managed. It is also the area of bioenergy that has seen the greatest development of sustainability policy in recent years, particularly driven by the expansion of liquid biofuel use in developed countries. However, as the majority of global bioenergy consumption is sourced from other feedstocks such as wastes or residues, the sustainability issues surrounding these feedstocks are also considered.
38 2.3.1 Notions of sustainability in the bioenergy sector
Many of the major sustainability issues that have emerged around bioenergy are also issues for other forestry and agriculture products, including opportunities for social and economic development and potential threats to biodiversity, landscape health, water quality and human rights. However, in recent years a number of issues have become particularly prominent in relation to bioenergy, including energy security, climate change mitigation, competing uses (e.g. “food versus fuel”) and indirect land use change. As with the plantation sector discussed in section 2.2, sustainability standards have been developed for bioenergy and these provide a useful overview of global sustainability issues. Table 2.2 summarises four such documents, from: x The United Nations (UN Energy 2007); x The European Union (European Parliament & Council of the European Union 2009); x The United Kingdom (Renewable Fuels Agency 2010); and x The Roundtable on Sustainable Biofuels (2010), or RSB.
39 Table 2.2: Sustainability issues from selected bioenergy sustainability standards. Criteria are summarised and paraphrased. UN Energy EU Directive on the promotion UK Carbon & Sustainability RSB Global Principles v2 2010 Sustainable Bioenergy of Energy from renewable Reporting Principles v3.3 2010 Framework 2007 sources 2009 (superseded in 2011) 1. Energy Services for Each member state shall: Carbon 1. Compliance with laws & the Poor regulations and international laws - Meet targets for renewable Greenhouse gas emissions & agreements 2. Agro-Industrial energy by 2020 savings (50% vs. fossil fuel Development & Job benchmark) 2. Consultative impact assessment and - Adopt a renewable energy Creation analysis of management process & action plan Environmental economic viability 3. Health & Gender Biofuel eligibility for targets Biomass production will not: 3. Climate change mitigation (50% 4. Implications for - Greenhouse gas emissions 1. Destroy or damage large savings vs. fossil fuel baseline) Agriculture savings (35% vs. fossil fuel carbon stocks (above or below 4. Human rights & labor rights 5. Food Security comparator) ground)
40 5. Contribution to social & economic 6. Government Budget - Raw materials shall not be 2. Lead to the destruction of or development Implications obtained from land with high damage to high biodiversity areas 6. Food security 7. Trade, Foreign biodiversity value (primary Exchange Balances & forest, nature protection areas, 3. Lead to soil degradation 7. Impacts on biodiversity, highly biodiverse grassland) ecosystems & conservation values Energy Security 4. Lead to the contamination or 8. Biodiversity & - Raw materials shall not be depletion of water sources 8. Soil degradation & soil health Natural Resource obtained from land with high carbon stock (e.g. wetlands, 5. Lead to air pollution 9. Water quality & quantity (surface Management & groundwater) continuously forested areas) Social 9. Climate Change 10. Air pollution - Raw materials shall not be Biomass production will not: obtained from peatland that 11. Production efficiency & risk 6. Adversely affect workers’ has been drained management rights & working relationships - European Commission to 12. Land rights & land use rights report every 2 years on food 7. Adversely affect existing land security & labour issues rights & community relations
The four standards presented in Table 2.2 differ in their purpose and context, covering both the promotion of bioenergy and the mitigation of threats. The UN Energy framework is less prescriptive than the other three, being designed for general guidance rather than certification of products. However, it is broader in scope, covering all forms of bioenergy and including issues such as socio-economic development and energy provision for the poor. In contrast, the EU, UK and RSB standards are designed for compliance and certification purposes and cover liquid biofuels only. The EU criteria define which biofuels can be counted against national targets under the EU’s renewable energy directive. The UK reporting principles were designed to perform a similar role in relation to the UK’s Renewable Transport Fuel Obligation, but have now been superseded by a set of criteria that replicate those operating at EU level (Department for Transport 2012). However, the now-defunct UK reporting principles have been included in Table 2.2 to highlight their much broader scope compared with the EU criteria, covering environmental factors such as soil, water and air quality, as well as social factors such as labour rights and land rights. The inclusion of social factors in bioenergy sustainability standards is contentious, as such provisions may conflict with the rules of the World Trade Organization (Charnovitz, Earley & Howse 2008).
The RSB standards, instigated by the Energy Center of École Polytechnique Fédérale de Lausanne, a Swiss academic institution, are designed for use in voluntary certification of biofuels. While no biofuel sustainability standards have been developed specifically for Australia, the RSB standards have been adopted for the assessment of biofuel sustainability under the NSW Biofuels Act 2007. This legislation promotes biofuels by mandating that a certain percentage of transport fuel sold in NSW is made up of ethanol and biodiesel. The RSB standards are yet to be fully implemented in NSW, as suppliers have been given time to achieve certification and can use other evidence to demonstrate sustainability in the meantime, such as planning approvals (Office of Biofuels 2012b).
The focus on liquid biofuels in the EU, UK and RSB standards is due to the rapid growth in demand for ethanol and biodiesel in developed countries and the emergence of issues such as forest clearing for palm oil in southeast Asia (Sheil et al. 2009) and
41 biofuel impacts on global food prices (Mitchell 2008). The EU’s renewable energy directive sets targets to promote multiple forms of bioenergy (transport fuels, electricity and heating), but requires binding sustainability criteria only for liquid biofuels. The lack of EU-wide sustainability criteria for biomass fuels used for electricity and heat is due to difficulties developing a harmonised scheme to cover the wide range of fuel types in use and a view that “sustainability risks relating to domestic biomass production originating from wastes and agricultural and forestry residues, where no land use change occurs, are currently low” (European Commission 2010b, p. 8). Individual EU countries may choose to impose sustainability criteria on biomass for electricity. The UK has opted to apply the same basic criteria for biomass electricity that the EU requires for biofuels (i.e. no feedstocks from land with high biodiversity or high carbon stocks), but with a higher greenhouse gas saving requirement of 60% for bioelectricity rather than the 35% required for biofuels (Department of Energy and Climate Change 2012b). The distinction between liquid biofuels and bioelectricity in sustainability standards may break down further in coming years, especially if the development of second-generation biofuels leads to greater interchange of feedstocks between bioenergy sectors.
The UN, EU, UK and RSB criteria share a number of similarities with the forestry and agriculture standards discussed in section 2.2, particularly in relation to the maintenance of environmental values relating to biodiversity, soil and water. However, they also place some unique obligations on bioenergy producers that are not generally applied to forestry and agriculture. All four sets of standards shown in Table 2.2 incorporate the notion that bioenergy should contribute to climate change mitigation in order to be considered sustainable, which is a notable divergence from the forestry and agriculture standards discussed in section 2.2. Other issues that feature more prominently in bioenergy standards are food security and energy security. The notion that bioenergy should contribute to landscape benefits such as the mitigation of salinity or soil erosion is not usually found within bioenergy sustainability standards. These issues are discussed further in section 2.4.
A major driver for bioenergy globally has been the potential for social and economic development, which is reflected most strongly in the UN and RSB standards. UN
42 Energy (2007, p. 4) argue that modern bioenergy (e.g. electricity, biogas, transport fuels) can “help meet the needs of the 1.6 billion people worldwide who lack access to electricity in their homes, and the 2.4 billion who rely on straw, dung and other traditional biomass fuels to meet their energy needs”. The production of bioenergy feedstocks for export also presents an opportunity for economic development (e.g. Mathews 2007, Gallagher 2008, Hausman & Wagner 2009).
Energy security is another major driver of bioenergy policy in both developing and developed countries, but is found in Table 2.2 only under the UN Energy framework. Energy security is most topical in relation to liquid biofuels due to their ability to act as a substitute for oil, especially in the transportation sector that makes up 60% of global oil consumption (International Energy Agency 2008). Global production of liquid biofuels is dominated by ethanol produced from corn (maize) in the United States and from sugarcane in Brazil, with biodiesel being the second-most important biofuel (Figure 2.3).
Perspectives on energy security can vary, with some researchers foreseeing a major risk from a peaking global oil supply (e.g. Hirsch, Bezdek & Wendling 2005, Future Fuels Forum 2008) and others having a more optimistic view of the potential for further increases in oil production (e.g. Energy Information Administration 2008). Energy security concerns also vary in scale from the local (e.g. providing modern energy services for local communities) to the national (e.g. replacing fuel imports) to the global (e.g. impacts of a peaking oil supply on the global economy). Concerns about over-reliance on foreign oil imports have been critical to the development of the corn ethanol industry in the US starting in the 1990s (Biomass Research and Development Board 2008) and the Brazilian sugarcane ethanol industry before it in the 1970s (Dufey, Vermeulen & Vorley 2007).
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Figure 2.3: Top four producing countries for (a) ethanol and (bb) biodiesel. Australia is included for comparriison. Data source: Energy Information Administration (2012).
Climate change appears as a prominent sustainability issue in all fofour standards shown in Table 2.2. With regards to climate change, bioenergy has been cast as both a potential solution and a potential threat. The Intergovernmental Panel on Climate
Change (2007, p. 68) has advised that stabilisation of atmosphericc CO2 levels is likely to require worldwide deployment of low greenhouse gas (GHG) emmission technologies and this is cited as the primary goal driving renewable energy poliicies that include bioenergy in Australia (Department of Climate Change and Energgy Efficiency 2011a) and the European Union (European Parliament & Council of the European Union 2009). However, some forms of bioenergy, particularly liquid biofuels, have been criticised for failing to achieve low GHG emissions when their fulll life-cycle is considered, due to factors such as fertiliser use (Crutzen, Mosier, Smith & Winiwarter
44 2007) and land use competition (Searchinger, Heimlich, Houghton, Dong, Elobeid, Fabiosa et al. 2008).
Viewed narrowly, bioenergy may be seen as “carbon neutral” in the sense that the carbon dioxide (CO2) emitted during combustion is equal to that taken out of the atmosphere during the growth of the feedstocks. However, a full GHG emissions life- cycle assessment also needs to take account of any process emissions (i.e. from planting, fertilising, harvesting, processing and transporting feedstocks), any non-CO2 greenhouse gases emitted during combustion (e.g. methane, nitrous oxide) and any land use change (LUC) emissions caused by converting land to energy crops. LUC emissions are dependent on the amount of carbon stored in the vegetation and soils before land use conversion compared to the amount stored after conversion. Carbon levels are likely to decrease if forests are cleared for annual crops, but may increase if woody perennial crops are planted on degraded land.
Life-cycle GHG assessments for biofuels are often expressed in terms of GHG “savings”, which are based on a comparison of the life-cycle GHG emissions for a biofuel with those of a comparable fossil fuel. LUC emissions can pose challenges for such calculations because they are not on-going, but rather represent a one-off change that occurs prior to feedstock production. In order to incorporate LUC emissions into life-cycle assessments, they are commonly amortised over a fixed period (e.g. 20 years) and assigned to each unit of biofuel produced over that period. An alternative approach involves first calculating the GHG savings from a biofuel excluding LUC emissions, then calculating the number of years of fossil fuel substitution that would be required to “pay back” any stored carbon emitted by the initial land use change. For example, Gibbs et al. (2008) calculated that, if tropical peat forests are cleared to produce palm oil for biodiesel, that biodiesel would need to be used as a diesel substitute for 918 years in order to pay back the emissions resulting from the loss of the peat forest.
The EU, UK and RSB standards all set life-cycle GHG savings benchmarks that biofuels must achieve relative to a comparable fossil fuel (petrol or diesel). The RSB standards, along with the now-defunct UK reporting criteria, set a benchmark of 50%
45 GHG savings, while the EU has set a lower benchmark of 35% that is due to rise to 50% in 2017 and 60% in 2018. Table 2.3 shows life-cycle GHG emissions savings for a range of biofuels that have been calculated using EU data on “typical” production (European Parliament & Council of the European Union 2009) and UK data on “default” emissions from land use change (Renewable Fuels Agency 2010).
Table 2.3: GHG savings calculated for selected biofuels. Fuel type & % GHG saving from Land % GHG saving including feedstock typical production in converted to land use change the EU (excluding grow emissions amortised over land use change)6 feedstock 20 years7 Ethanol - corn 56% Grassland, - 49% France Ethanol - 71% Grassland, 71 % (LUC emissions are sugarcane Brazil zero) Biodiesel - 88% None (waste 88 % used cooking feedstock) oil Biodiesel - 36% (no methane Forestland, -157% palm oil capture at mill) Malaysia 62% (methane capture Degraded land, 96% (includes bonus for at mill) Malaysia using degraded land) Dimethylether 95% None (waste 95% - wood waste feedstock)
The calculations in Table 2.3 highlight the impact that LUC emissions can have on life-cycle GHG savings. Two of the examples, French corn ethanol and Malaysian palm oil biodiesel with no methane capture, show negative GHG savings once LUC emissions are included (i.e. their life-cycle GHG emissions are greater than using a fossil fuel). Conversely, where energy crops are used to rehabilitate degraded land, the EU allows an emissions “bonus” to be factored in, reflecting the potential for energy
6 “Typical” production emissions from European Parliament and Council of the European Union (2009) 7 “Default” values for land use change emission from Renewable Fuels Agency (2010)
46 crops to increase levels of stored carbon in such land. Biofuels from waste feedstocks (e.g. used cooking oil) and second-generation processes (e.g. dimethylether from wood waste) also show high GHG savings in Table 2.3.
For Australian biofuels, the Productivity Commission (2011a) found that biodiesel delivered higher GHG savings than ethanol, particularly if produced from recycled cooking oil (87% savings), tallow (76%) and soybean oil (62%). In comparison, ethanol was found to deliver GHG savings of 53% using waste wheat starch or molasses and 43% using sorghum.
Solid biomass fuels used for electricity or heating often deliver GHG savings higher than those for liquid biofuels. Figure 2.4 shows European Commission (2010b) data on typical life-cycle GHG emissions for solid biomass fuels. These data highlight that GHG savings of over 90% (excluding LUC) are achievable for solid biomass fuels such as forest residues and short rotation tree crops. Emissions savings can be particularly high where local rather than imported biomass is used, fuel processing is minimal, coal is chosen as the fossil fuel comparator and biomass is used for heating rather than electricity.
Aside from differences in feedstocks and production systems, differences in life-cycle assessment methodology and assumptions can also impact on the perceived GHG performance of biofuels. For example, a prominent paper by Crutzen et al. (2007) suggested that NO2 emissions from fertiliser use are actually higher than is generally assumed by the Intergovernmental Panel on Climate Change (IPCC). Other authors such as ADAS (2008) and Berndes et al. (2011) have argued in response that the calculations used by Crutzen et al. (2007) over-estimated NO2 emissions from fertilisers.
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Figure 2.4: GHG savings for selected solid biomass feedstocks. Savings are relative to EU fossil fuels and exclude land use change. Source: European Commission (2010b).
Another contentious area for life-cycle GHG analysis is the allocation of process emissions to different co-products. One of the key reasons that waste feedstocks such as used cooking oil show strong GHG savings in Table 2.3 is that they are generally assigned little or no emissions from the production of the original crop (e.g. canola). O’Connell et al. (2009b) describe this as the “primary purpose” method of allocating emissions and suggest at least two other methods, based on either the relative mass of co-products or their relative economic value. The Productivity Commission’s GHG results for Australian ethanol from waste wheat starch provides an example of the primary purpose method, whereby all emissions associated with growing, harvesting and transporting the wheat crop were allocated to the higher-value food products from grain processing and none were allocated to the ethanol (Productivity Commission 2011b).
48 Other factors that can affect global warming potential but are not included in the estimates in Table 2.3 and Figure 2.4 include the timing of emissions (e.g. land use change now but fossil fuel substitution later), impacts on albido (e.g. replacing light- coloured grassland with darker plantations) and indirect land use change. Indirect land use change (iLUC) relates to land use changes that occur elsewhere as a consequence of a bioenergy project (Berndes et al. 2011). For example, if an energy crop plantation displaces cropping or grazing, those pre-existing activities may need to relocate into forested areas, causing loss of stored carbon and other impacts. The scale of iLUC impacts can vary from the local (e.g. a small shift of an agricultural frontier) to the global (e.g. diversion of corn to ethanol causing global price rises that create an incentive to clear land in other countries).
In a prominent and controversial paper, Searchinger et al. (2008) estimated that full life-cycle GHG emissions from US corn ethanol are 93% higher than emissions from gasoline if iLUC is included. The US Environment Protection Agency (US EPA) have undertaken their own GHG calculations for corn ethanol, finding that its life-cycle emissions were still 20% lower than for gasoline even with iLUC included (US EPA 2010). The difference between the US EPA result and that of Searchinger et al. (2008) is largely due to the differing assumptions used, particularly regarding the capacity for corn yields to increase in response to higher prices, the use of ethanol by-products as animal feed and the types of land converted for corn production globally (US EPA 2010). Berndes et al. (2011) cite a range of other studies that have calculated much lower iLUC emissions from US corn ethanol than those published by Searchinger et al. (2008).
Reviews of the indirect effects of biofuel production have been commissioned by the UK Government (Gallagher 2008) and by the EU (Al-Riffai, Dimaranan & Laborde 2010). While both reviews found that biofuel production can contribute to iLUC emissions, neither jurisdiction currently requires iLUC emissions to be included in biofuel GHG calculations, with the UK Government citing “a number of uncertainties associated with the available models” (Department for Transport 2012). Berndes et al. (2011, p. 53) argue that “short-term emissions from land use change are not sufficient
49 reason to exclude bioenergy from the list of worthwhile technologies for climate change mitigation”.
Apart from GHG emissions, land use change (both direct and indirect) can generate concerns relating to biodiversity loss, land degradation and displacement of vulnerable people. The expansion of oil palm plantations at the expense of tropical rainforests and peatlands in Indonesia and Malaysia has generated significant global attention, with biodiesel often singled out as a product of particular concern (e.g. Ernsting 2007, Soyka, Palmer & Engel 2007, Oxfam International 2007, Greenpeace 2007). However, these issues are not unique to bioenergy and also appear in the forestry and agriculture standards discussed in section 2.2. The relative importance of bioenergy as a driver of deforestation and dispossession compared to other products varies depending on the context. Sheil et al. (2009, p. 51) highlight that the rapid expansion of oil palm plantations in southeast Asia is primarily driven by demand for food and industrial products and “to a lesser extent demand and speculation for biofuel”. Conversely, a recent report from the International Land Coalition found that 40% of the large land transactions they reviewed in developing countries were for biofuels compared with only 25% for food production (Anseeuw, Wily, Cotula & Taylor 2012).
In Australia, the use of native forest biomass for electricity generation has been a prominent bioenergy sustainability issue, following a number of proposals that emerged in the late 1990s and early 2000s (Raison 2006). Groups such as the Wilderness Society (2003) have campaigned against the use of forest “wastes” for bioenergy on the grounds that this could increase overall forest harvesting, expand harvesting into old-growth areas and support harvesting that would otherwise be uneconomic, resulting in additional greenhouse gas emissions and loss of biodiversity. The woodchip industry is often cited as an analogous example of a “waste” product that has become a major driver of forest harvesting after being given an economic value (Forestmedia 2010). The National Association of Forest Industries argues that the use of native forest residues for bioenergy occurs in many other developed countries and that negative impacts are unlikely due to the low price of biomass for energy and strong restrictions on both the area of forest and the amount of forest material that is available for harvest (Rutovitz & Passey 2004).
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Another prominent sustainability issue highlighted by the standards shown in Table 2.2 is food security. This is a response to the “food versus fuel” debate that reached its zenith in 2008 as global food prices rose rapidly at the same time as global biofuel use8 (e.g. Oxfam International 2007, Dehue, Meyer & Hamelinck 2007, Eide 2008, Monbiot 2008, Brown 2008). Mitchell (2008, p. 16) argued in a World Bank report that these price rises were “caused by a confluence of factors, but the most important was the large increase in biofuels production from grains and oilseeds in the US and EU”. However, opinions vary on the relative importance of other contributing factors, which include poor harvests in major producing countries, regulatory policies (e.g. production quotas), growing demand for food, changing diets in emerging economies, exchange rates and speculation (Roundtable on Sustainable Biofuels 2010, O'Connell et al. 2009a).
Opinions also vary on the social impacts that rising food prices can have. While Eide (2008, p. 14) argued in a UN Food and Agriculture Organization report that “at least an additional hundred million persons are now food insecure” due to food price increases, Gallagher (2008, p. 52) concluded in his report to the UK Government that the impacts of food price rises on poor consumers were “clearly negative”, but “not normally large”. It is overly simplistic to view high food prices as always being bad and low prices as always being good. For example, much debate prior to the food price peak of 2008 focused on over-production and the unsustainably low prices being caused by “dumping” of subsidised agricultural commodities onto global markets by the US and EU at prices too low for developing world farmers to compete with (e.g. Murphy, Lilliston & Lake 2005, Brown 2008). The view presented by UN Energy (2007, p. 31) is that bioenergy production can affect food security in a variety of ways, but that “the current ‘food, feed or fuel’ debate tends to be overly simplistic and fails to reflect the full complexity of factors that determine food security at any given place and time”. The extent to which bioenergy and food production are perceived to be in competition varies between different fuels and feedstocks. US ethanol production has attracted much attention, consuming close to a third of the US corn crop in 2009/10 (USDA
8 World food prices subsequently fell during the global financial crisis before rising again in 2010/11 (FAO 2011).
51 2010). The impacts of this are complex, with Figure 2.5 showing that the dramatic rise in corn use for ethanol did not in fact cause a large-scale reduction in the availability of US corn for animal feed or export. However, the increased area planted to corn does appear to have come at least partially at the expense of the area planted to wheat. This highlights the potential for flow-on effects between interconnected agricultural commodity markets.
Figure 2.5: Impacts of ethanol production on the US grain sector. Historical (1990- 2009) and projected (2010-2019) data are shown for: (a) US corn usage; and (b) US acreage planted to corn, soybeans and wheat. Source: USDA (2010)
Given the global nature of land use competition, one of the critical issues in the food versus fuel debate is the availability of arable land globally. Rosillo-Calle et al. (2007) argue that adequate land exists for both food and fuel and that the primary problem is a lack of purchasing power amongst the world’s poorer citizens. Dornburg et al. (2008,
52 p. 71) reviewed a number of global studies looking at future land availability for food and fuel and concluded that “under the assumption that food demands of future population are met, most recent studies estimate global biomass potentials of 300 to 800 EJ/yr in 2050”, with at least 80 EJ/yr coming from dedicated energy crops9. This compares with current global bioenergy use from all sources totalling around 50 EJ/yr (Bauen et al. 2009). Hoogwijk, Faaij, de Vries and Turkenburg (2009) found that between 130 and 270 EJ/yr could be produced from energy crops at prices competitive with fossil fuels, using only land that was not needed for food, fodder or forestry. However, these results are highly dependent on the assumptions used for future food demand, yields and costs. Furthermore, the availability of land does not in itself guarantee that production of feedstocks will be allocated to the most appropriate areas or that the benefits and impacts will be distributed equitably.
Concerns about bioenergy land use impacts have led to calls for bioenergy production to be focused on wastes/residues, cellulosic crops or other non-edible crops such as jatropha (Jatropha curcas) and marginal lands that are not required for food production (e.g. Openshaw 2000, Francis, Edinger & Becker 2005, Brown 2008, Eide 2008, Gallagher 2008). Searchinger et al. (2008) argued that biofuel production should be restricted to wastes due to the risk of iLUC emissions, while Gallagher (2008) recommended that future biofuel cropping be directed to “idle land” (land with no current “productive use” or conservation value). While none of the four standards cited in Table 2.2 have adopted these restrictions, the EU and UK have attempted to promote the use of wastes and cellulosic feedstocks by allowing biofuels from these sources to be “double-counted” against biofuel targets (Department for Transport 2012). This means that fuel suppliers can fulfil their mandated obligations to supply biofuels more easily if they use fuels from these sources. However, wastes and cellulosic feedstocks are not completely free from sustainability concerns, as shown by the example of native forest residues in Australia. Similarly, non-edible crops can also pose a threat to local food security if grown on food-producing land (Brittaine & Lutaladio 2010) and land that is classified as “waste land” or “marginal land” may in fact be relied upon by some of the world’s most marginalised people (Gaia Foundation, Biofuelwatch, African Biodiversity Network, Salva La Selva, Watch Indonesia & EcoNexus 2008).
9 1 EJ (exajoule) = 1018 joules
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Reflecting the complexity of food security issues, the UN Energy and RSB standards have opted for flexible prescriptions. UN Energy (2007) recommends a context- specific analytical framework to determine appropriate actions. The Roundtable on Sustainable Biofuels (2010) requires that a risk assessment be undertaken, with biofuel producers required to work with affected communities in food insecure regions to improve food security (e.g. setting aside land, increasing yields). Notably, the RSB standard does not require biofuel producers to ensure food security on a global scale, noting that “voluntary certification alone may not be the best tool to address indirect impacts, since these macro-level impacts are likely to be beyond the control of the individual farmer or biofuels producer seeking certification” (Roundtable on Sustainable Biofuels 2010, p. 4).
2.3.2 Bioenergy policy in Australia
Bioenergy policy in Australia reflects many of the drivers and concerns discussed in section 2.3.1. The main policy goal cited for promoting bioenergy has been greenhouse gas abatement and the major policy instruments used have been mandates, subsidies/tax-breaks and research and development support. The primary instrument used to promote bioenergy for electricity generation is a mandate scheme (often termed a Renewable Portfolio Standard), which has been known variously as the Mandatory Renewable Energy Target (2001-2009), the Renewable Energy Target (2009-2011) and, since 1 January 2011, the Large-scale Renewable Energy Target (LRET). The LRET has a set of targets that progressively rise to 41,000 GWh (gigawatt-hours) of renewable generation per annum by 2020, from sources such as hydro, wind, solar and bioenergy. This compares to a renewable generating capability of 12,200 GWh in 2010 (Office of the Renewable Energy Regulator 2011). Following revisions to the Renewable Energy Target in 2011, small-scale generation from solar, wind and hydro are now covered by a separate Small-scale Renewable Energy Scheme (SRES), which does not include bioenergy. Together, the LRET and SRES are aimed at increasing Australia’s renewable electricity generation to around 20% of total generation by 2020, while ensuring that renewable energy is sourced sustainably (Office of the Renewable Energy Regulator 2011).
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Under the LRET, electricity retailers and other liable entities are required to surrender a specified number of Large-scale Generation Certificates (LGCs) each year, with each LGC representing one megawatt-hour (MWh) of eligible generation. LGCs replaced RECs (Renewable Energy Certificates) as the tradable certificates under the LRET in 2011. Liable entities can create their own LGCs or purchase them from other generators under contract or on the LGC spot market. This market mechanism is designed to promote the least-cost form of renewable energy at any given point in time. As discussed in Chapter 1, bioenergy sources accounted for 18% of all Renewable Energy Certificates (RECs) created between 2001 and 2010 and surrendered by 13 March 2012 (Office of the Renewable Energy Regulator 2012), with the largest bioenergy sources being bagasse from the sugar cane industry (6.6% of all RECs), landfill gas (6.5%), and wood wastes (2.2%). Energy crops have made a negligible contribution to date, making up less than 0.1% of all RECs created between 2001 and 2010.
Feed-in tariffs (FiTs) are an alternative approach to promoting renewable electricity generation. Rather than fixing the quantity of renewable energy (as under the LRET), FiTs fix the price that must be paid to generators. Feed-in-tariffs in Australia are regulated by State and Territory Governments, with most jurisdictions having developed FiTs for small-scale solar (and wind in some cases). Victoria is the only state to offer a FiT for bioenergy, with systems up to 100 kW (kilowatts) eligible to be paid for any electricity exported to the grid (i.e. a “net” FiT) at a tariff that is generally equal to retail electricity prices (Department of Primary Industries 2012). The main advantages of FiTs over mandate schemes such as the LRET are greater price certainty for investors in new technologies and the ability to offer differentiated tariffs for different technologies. For example, FiTs for biomass energy in Germany have been set at differing levels depending on the size of the generator and the feedstocks used (Table 2.4), reflecting a view that certain bioenergy sources need more support during their development phase and certain sources have associated benefits (e.g. landscape preservation or reduced air pollution).
55 Table 2.4: Feed-in tariffs offered for bioenergy in Germany. Source: Schuck (2010). Size Tranches Compensation (€ cents/kWh) 150 kW 11.67 > 150 kW 500 kW 9.18 > 500 kW 5 MW 8.25 > 5 MW 20 MW 7.79 energy crops 4.0 - 7.0 manure 1.0 - 4.0 biomass from land managed Bonus compensation 2.0 for landscape preservation for using: innovative technology 1.0 - 2.0 combined heat and power 3.0 fewer emissions (clean air) 1.0
It is also possible to provide differentiated support for different technologies under electricity mandate schemes. One example is the UK’s electricity mandate (the Renewables Obligation), which employs a system of “banding” that awards fewer than one certificate per MWh to established technologies, such as landfill gas, and more than one certificate per MWh to technologies that are currently less competitive but hold future potential, such as dedicated energy crops (Table 2.5). However, this approach can have unintended consequences if the certificates from all of these sources are traded in a single market. Australia experimented with a form of banding from 2009 to 2010, when large-scale and small-scale generation sources were still covered by a single scheme (the Renewable Energy Target). Because small-scale sources such as residential solar photovoltaics (PV) were unable to compete with cheaper large-scale sources such as wind and landfill gas, the small-scale sources were awarded Solar Credits, which provided five RECs per MWh rather than just one (Department of Climate Change 2009). While this REC “multiplier” provided additional incentives for small-scale generation, it also had the effect of flooding the REC market with “phantom” certificates that did not represent actual generation (Buckman & Diesendorf 2010). This reduced the REC price, which, in turn, reduced the incentive to invest in other forms of renewable energy such as wind and bioenergy. The solution to this
56 problem was the creation of the separate Small-scale Renewable Energy Scheme (SRES) in 2011, which has a fixed certificate price but no fixed target. This allows greater incentives to be provided for small-scale generation without impacting on the viability of large-scale generation (The Parliament of the Commonwealth of Australia 2010).
Table 2.5: UK Renewables Obligation “banding” for bioenergy sources. Source: Department of Energy and Climate Change (2012a). CHP = combined heat and power. Generation type Certificates per MWh x Landfill gas 0.25 x Sewage gas, co-firing of non-energy crop (regular) biomass 0.5 x Co-firing of energy crops x Co-firing of non-energy crop (regular) biomass with CHP 1.0 x The use of fuels made using standard gasification or pyrolysis x Co-firing of energy crops with CHP 1.5 x Dedicated regular biomass x Fuels made using anaerobic digestion x Advanced gasification or pyrolysis x Dedicated biomass burning of energy crops (with or without 2.0 CHP) x Dedicated regular biomass with CHP
Mandate schemes are also commonly used to promote liquid biofuels, with REN21 (2011) listing 36 countries with biofuel mandates globally. NSW is the only Australian state to impose biofuel mandates on wholesale fuel suppliers and retailers under the Biofuels Act 2007 (NSW). As of July 2012, the ethanol mandate was set at 6% of petrol sales by volume (increased from 2% in 2011) and the biodiesel mandate was set at 2% of diesel sales. The benefits cited for promoting biofuels in NSW include that “they’re good for the environment, create jobs in the bush, help our farmers and reduce our reliance on expensive foreign fuel imports” (Department of State and Regional
57 Development 2007). As discussed in section 2.3.1, the RSB standards are being phased in as a sustainability standard under the NSW Biofuels Act (Office of Biofuels 2012b). No time limit has been set for when fuel suppliers will be required to have their biofuels certified under this standard.
The Australian Government also promotes biofuels through the use of subsidies. Domestic ethanol producers currently receive a production subsidy under the Ethanol Production Grants Program (Department of Resources, Energy and Tourism, 2012). Biodiesel (both domestic and imported) is eligible for a subsidy under the Cleaner Fuels Grants Scheme (Australian Taxation Office 2011a). Both of these schemes provide biofuel producers with grants that are equal to the fuel excise of 38.143c/L. This effectively provides a tax break for biofuels and a price advantage over petrol and diesel, which attract fuel excise of 38.143c/L but receive no reimbursements. While the Biofuels Association of Australia has argued that the biofuel industry is not subsidised because it pays excise that is then “granted back”, the Productivity Commission, an advisory body to the Australian Government, takes the view that forgoing government revenue in this manner meets the World Trade Organization’s definition of a subsidy (Productivity Commission 2011b).
Previously planned changes to Australian fuel excise arrangements would have eliminated both biofuel grants programs and instead reduced the excise payable to 12.5c/L for ethanol and 19.2c/L for biodiesel by 2015 (Batten & O’Connell 2007). However, following pressure from the biofuel industry and rural Members of Parliament, legislation was passed in 2011 that extended the existing arrangements until 2021. The exclusion of imported ethanol from the Ethanol Producers Grant Program demonstrates a policy goal of promoting the domestic ethanol industry rather than simply mitigating greenhouse gas emissions at lowest cost. Biofuel policy in other countries has also favoured domestic production, with researchers such as Rubin et al. (2008) and Hausman and Wagner (2009) arguing that US and EU biofuel policies have been used as substitutes for other agricultural policies aimed at boosting farmer incomes (e.g. agricultural subsidies or set-aside policies).
58 Carbon pricing, whether through an emissions trading scheme or a carbon tax, can also promote bioenergy by providing a relative price advantage over fossil fuels. The Australian Government obtained legislative approval in late 2011 for its “Clean Energy Future” carbon pricing mechanism to commence on 1 July 2012. This scheme features an initial 3-year period in which the price of emissions permits is fixed (effectively a carbon tax), before transitioning to an emissions trading scheme with a fixed cap and a market-determined price. The starting price for permits is $23/tCO2-e in 2012-13, rising to $25.40/tCO2-e in 2014-15 (Commonwealth of Australia 2011b). Under this scheme, bioenergy will be treated as carbon neutral. Some downstream emissions (e.g. electricity from fossil fuels used in the processing of feedstocks) will be covered by carbon pricing arrangements and others (e.g. fertiliser used to grow feedstocks) will be excluded from carbon pricing.
Support for research, development and deployment is another means of promoting bioenergy (Batten & O’Connell 2007), with notable Australian Government programs including the Biofuels Capital Grants Program and the Second Generation Biofuels Research and Development Program, which focused on low-cost, non-food feedstocks such as cellulosic ethanol and biodiesel from algae. The Australian Government has recently announced a range of new measures as part of its carbon pricing scheme, including the Australian Renewable Energy Agency to provide grants for early-stage technology development, the Clean Technology Innovation Program to fund proof-of- concept work and early-stage commercialisation and the Clean Energy Finance Corporation to invest in renewable energy projects (Commonwealth of Australia 2011b).
The main policy measures used in Australia to prevent unsustainable bioenergy production have been regulatory restrictions. Most regulations that affect how feedstocks can be produced are not bioenergy-specific, such as laws governing native vegetation clearing, chemical use, air pollution and the operation of industrial facilities. However, some bioenergy-specific regulations have been used to address particular issues in Australia, most notably the use of native forest residues for electricity generation.
59 Restrictions on the use of native forest material for bioenergy have been introduced by both state and Commonwealth governments. Prior to November 2011, the Commonwealth approach was to allow native forest biomass to be counted under the LRET and earn LGCs, but only if the biomass was harvested “primarily for a purpose other than biomass for energy production”10. This policy was opposed by a number of NGOs and the Greens Party, who saw the use of native forest residues for bioenergy as a driver of increased native forest harvesting. Campaigns using terms such as “dead koala RECs” (Klatovsky 2003) created a stigma around RECs/LGCs from wood wastes (whether from native forests or other sources) and this stigma was seen to be depressing the price of these RECs/LGCs relative to other sources (Australian Greenhouse Office 2003). As part of the carbon pricing package, which required support from the Greens Party to pass through parliament, changes were made to the Renewable Energy (Electricity) Regulations 2001 in November 2011 preventing any biomass sourced from a native forest to be used in the creation of LGCs. Biomass from native trees grown in plantations can still be used to create LGCs, falling under the “energy crop” category of the LRET rather than the “wood waste” category (even if energy is only a minor product from the plantation).
NSW also has a ban on the generation of electricity from “native forest bio-material” (bio-material from any Australian native tree). In one sense, this ban is stricter than the Commonwealth ban because it applies to all electricity generation, not just the creation of LGCs. However, it also allows more exemptions, not only for plantation biomass but also for off-site processing wastes (e.g. from sawmills) and small generators (<200kW)11. Sawmill residues have been controversial in NSW, with the NSW Greens Party arguing that the use of sawmill residues for energy could subsidise and entrench existing harvesting (Cubby 2009). Victoria also had a ban on commercial renewable energy production from public native forests, but this was rescinded on 1 January 2010 (Department of Primary Industries 2009). GreenPower, a voluntary green energy scheme run by various State and Territory government agencies, refuses to accredit electricity generated using native forest biomass as a “green” power source (GreenPower, 2010).
10 Section 8(2) of the Renewable Energy (Electricity) Regulations 2001 (as of 13 March 2010). 11 2003 amendment to the Protection of the Environment Operations (General) Regulation 1998 (NSW).
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As discussed in the previous section, policy measures developed overseas are becoming increasingly influential on Australian bioenergy policy. O’Connell et al. (2009a) undertook a comprehensive analysis of recent international developments in the area of bioenergy sustainability policy and outlined a range of future policy options for Australia, including adopting standards that have been developed overseas, seeking to influence international standards under development or developing approaches specific to Australia. The adoption of the RSB standards under the NSW Biofuels Act provides an example of this overseas influence. Australian exporters of biofuels and biomass products may also encounter international sustainability standards, particularly those exporting to Europe such as Plantation Energy, a producer of wood pellets from plantation residues in Western Australia (Energy Global 2010).
2.4 Integrating notions of sustainability across the revegetation, plantation and bioenergy sectors
As highlighted in section 2.3, notions of sustainability around bioenergy generally focus on the positive contribution that bioenergy can make to goals such as climate change mitigation as well as the potential threats it can pose to goals such as forest conservation and food security. It is less common for revegetation goals such as habitat restoration, soil rehabilitation or salinity mitigation to find their way into bioenergy sustainability standards or other policy documents. However, as demonstrated by some of the examples cited in sections 2.1 and 2.2, it is possible for revegetation projects to explicitly consider economic outcomes (e.g. Mansourian 2005, Oviedo 2005) and for commercial plantation projects to explicitly consider environmental enhancement (e.g. Erskine at al. 2005, Sustainable Agriculture Network 2008). Similarly, biomass production systems for bioenergy can be developed with revegetation goals as an integral component.
One of the best-known Australian examples of bioenergy from woody perennials being targeted as a commercial driver for the revegetation of degraded or vulnerable land is the nascent Oil Mallee industry in the wheatbelt of Western Australia (WA). Southwest WA is a major food-producing region with significant ecological values (Mullan
61 2000), but is highly susceptible to dryland salinity as a result of the extensive replacement of deep-rooted native vegetation with shallow-rooted annual grain crops (National Land and Water Resources Audit 2001). Thus, one of the major drivers behind the Oil Mallee industry is to mitigate the impacts of rising saline water tables by planting strips of mallee (eucalypt species featuring a multi-stemmed growth form) within wheat fields (Figure 2.6). The mallee trees’ high level of evapotranspiration and deep roots prevent the saline water table from rising to the surface.
A number of commercial drivers have been explored to encourage further planting of mallee in WA, with bioenergy (in the form of electricity) emerging as a key product option alongside eucalyptus oil (for pharmaceutical or industrial uses), activated carbon (for filtration or purification) and the generation of carbon credits through sequestration (Enecon 2001). The 2009 Oil Mallee Industry Development Plan (URS Australia 2009) also identifies opportunities from emerging technologies, including liquid biofuels (e.g. cellulosic ethanol or bio-crude from thermo-chemical conversion) and biochar, which is a solid co-product of pyrolysis that has shown potential as a soil ameliorant (CSIRO 2011a). Mallee cropping options have also been assessed for NSW (e.g. Abadi et al. 2006, Total Catchment Management Services 2008), albeit to a much lesser extent than for WA. These NSW options are discussed in detail in Chapter 4.
Figure 2.6: The role of mallee tree belts in mitigating dryland salinity in the wheatbelt of Western Australia. Source: Yu, Bartle and Wu (2007).
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Howard and Ozlack (2004) examined policy options for promoting Oil Mallee and other revegetation activities based around woody energy crops, recommending the removal of perverse incentives that subsidise fossil fuels, better integration of energy and natural resource management policy, the creation of a dedicated biomass industry institution, further research and development and promotional activities involving public consultation, information and marketing. Research and development is the main policy instrument that has been used to promote the Oil Mallee industry to date, including funding for projects on mallee productivity (Peck, Sudmeyer, Huxtable, Bartle & Mendham 2012), hydrological impacts (Wildy, Pate & Bartle 2003, Bennett et al. 2011), biodiversity (Smith 2009), integrated processing involving electricity generation (Enecon 2001, Verve Energy 2006) and the development of a prototype mallee harvester (Future Farm Industries 2011).
Simpson et al. (2009) highlight a number of examples from Europe and North America where woody bioenergy crops such as willow (Salix spp) and poplar (Populus spp) have contributed to local environmental enhancements. Recorded benefits include an increase in soil organic matter (through litterfall, root decay and reduced tillage), improved water quality (due to lower fertiliser requirements and filtering of runoff or wastewater) and enhanced biodiversity (habitat for deer, birds and bees). Simpson et al. (2009) also cite the use of bioenergy plantations in Sweden to filter wastewater and sewage and to remove cadmium from contaminated soils. Willow and poplar bioenergy systems are similar to mallee in the sense that they feature shorter rotations than is traditional for plantation forestry and can be harvested by coppicing, which involves cutting the tree back to ground level and allowing it to re-sprout. For this reason, they are often referred to as short rotation coppice (SRC) systems. Dimitriou et al. (2011) reviewed a range of European studies into SRC systems, finding that the establishment of such systems on agricultural land could generally be expected to result in improved groundwater quality, reduced heavy metal concentrations in soils and greater abundance and diversity of birds. However, they also noted that the impact of plantations on other animal types and soil parameters was more mixed, with further research required on appropriate site selection and management strategies.
63 Examples such as Oil Mallee and SRC systems in Europe highlight the need for a notion of sustainability that is capable of encompassing the revegetation, plantation and bioenergy sectors simultaneously. However, significant differences exist in the ways that sustainability issues, goals, benchmarks and policy instruments are framed in each of these sectors, as shown in Table 2.6. While the revegetation sector is primarily based around goals of improving selected environmental values, the plantation and bioenergy sectors feature a combination of policy goals and measures that are designed to promote certain benefits while restricting land use activities that could pose a threat to sustainability. The plantation and bioenergy sectors show significant overlaps in terms of threats to biodiversity, soil and water and human rights, but certain issues such as climate change, energy security and food security are more prominent in the bioenergy sector.
64 Table 2.6: Key sustainability issues, benchmarks and policy instruments for the revegetation, plantation and bioenergy sectors. Revegetation/Restoration Plantation Forestry/Agriculture Bioenergy Key Promote for: Promote for: Restrict to Promote for: Restrict to prevent: Policy prevent: Issues Environmental Economic Environmental Environmental Environmental x biodiversity x development x biodiversity loss x climate change x biodiversity loss x soil & water Social x soil/water mitigation x soil & water x climate change x employment degradation Economic degradation Socio-economic Environmental x carbon stock x energy security x carbon stock loss x community x take pressure loss x development Social development off native Social Social x loss of land rights forests 65 x cost-effectiveness x loss of land x modern energy x loss of worker’s rights services rights x loss of worker x employment x food insecurity rights Economic x unproductive or unviable plantations
Revegetation/Restoration Plantation Forestry/Agriculture Bioenergy Key Enhance current land Enhance Maintain habitat Enhance GHG Maintain Goals/ condition economic & biodiversity, soil, balance & energy environmental & social Bench- Enhance cost- social outcomes water, climate security relative values marks effectiveness of funding Maintain native Enhance in to fossil fuels Enhance GHG balance (e.g. market-based forests limited cases (e.g. Enhance relative to fossil fuels incentives) FSC & SAN rules availability of Maintain production of Enhance social wellbeing on restoration) energy services food (more common in (more common in Enhance social & developing countries) developing economic development countries) Key x Funding x Subsidies or x Regulations x Mandates (for x Standards 66 Policy x Extension tax breaks (e.g. NSW biofuels or x Regulations (e.g. Instru- x Carbon cap & trade (e.g. MIS) Plantations electricity) native forest ments x Biodiversity offsets & x R&D funding Code) x Subsidies or electricity) trading (e.g. NSW x Standards tax breaks x Proposed land use Biobanking) x Carbon cap & restrictions (e.g. trade wastes only, “idle x R&D funding land” only)
Table 2.6 highlights the complex mix of maintenance and enhancement goals found in the plantation and bioenergy sectors. However, complex interactions between these goals can also be found in the revegetation sector. For example, revegetation to create biodiversity corridors may be based on the enhancement of habitat on the local scale, while being about the maintenance of biodiversity on the regional or national scale by facilitating species migration and population mixing. Similarly, revegetation in the form of carbon plantings may be about enhancing carbon sequestration in a narrow sense, while being about maintaining a stable climate in a broader sense. Conversely, goals based around the maintenance of ecosystem services that provide clean water and healthy environments may be a necessary pre-requisite for enhancing social and economic development. Thus, the goals of maintenance and enhancement listed in Table 2.6 are generalisations rather than a full list of goals underlying each sector.
In terms of policy instruments, revegetation usually requires funding, which in Australia is increasingly being distributed through market-based instruments (MBIs) such as bush auctions, carbon offsets and biobanking. For the plantation sector, the instruments most commonly described as “sustainability” policy are regulations and industry standards. Measures to promote plantations, such as tax breaks, are less likely to be framed as sustainability policy, even though economic goals constitute one of the three pillars of sustainability. Bioenergy policies may employ the terms sustainability or sustainable development regardless of whether they are aimed at promoting bioenergy or restricting it. Bioenergy policies are also more likely to include goals and benchmarks relating to GHG savings and competition impacts (e.g. food security, indirect land use change) than policies applied to plantations in general. The bioenergy sector features a number of policy instruments that combine incentives and disincentives (e.g. offering tax breaks but restricting eligibility using sustainability standards).
Another difference between the three sectors is their application of policy principles such as “polluter pays” or “beneficiary pays” (Dovers 2005). In the energy sector, the polluter pays principle can be found in policies that put a price on carbon or set a mandate for electricity or fuel companies to supply or purchase renewable energy. In contrast, the beneficiary pays principle is more common in the revegetation sector,
67 with the government generally expected to pay for revegetation rather than imposing a mandate on landholders to revegetate a portion of their property. Furthermore, carbon pricing schemes are often selective about which polluters have to pay such as the Australian Government’s scheme exempting farmers from paying a carbon price for fertiliser or land clearing emissions but allowing them to earn credits from tree- planting.
A critical decision for policy-makers working across the revegetation, plantation and bioenergy sectors simultaneously is where to target policy measures. For example, targeting incentives at non-commercial revegetation may produce a lower level of adoption than targeting land use options that offer a commercial return, but promoting commercial plantations will not necessarily lead to planting strategies that offer the greatest benefits for biodiversity, soil health or water quality. Policy-makers also need to consider whether sustainability standards or regulations are required for specific products (e.g. biofuels) or whether they should be targeted at production systems more broadly, regardless of the product (e.g. regulations covering land clearing for a variety of purposes).
Bioenergy in particular has been singled out for sector-specific regulations and standards. Eide (2008, p. 17) justifies such an approach by arguing that bioenergy presents an exceptional risk, stating that “production of feedstock for biofuel is by its very nature best suited for large holdings, and it is to an extreme degree a monoculture production”. However, decisions to impose higher standards on bioenergy can also be influenced by higher expectations of what bioenergy must achieve to be considered sustainable. The clearest example of this is the requirement for biofuels to deliver GHG emissions savings relative to fossil fuels under the UK, EU and RSB standards but the lack of any similar benchmarks for other products under the FSC, AFS, SAN or RSPO standards for forestry and agriculture (e.g. timber could be required to achieve lower life-cycle emissions than a comparable building material). In the case of the UK and EU standards, this may be justified on the basis that these standards define which biofuels are considered worthy of policy support, but this is not the case for the RSB standards, which cover biofuels across a range of contexts.
68 The use of forest biomass is another area where bioenergy is held to a higher standard, particularly in Australia, where electricity generation has been singled out as an unacceptable use of forest biomass. The potential scale of a bioenergy industry based on forestry residues is often cited as a reason for this treatment (e.g. Forestmedia 2010), but it is likely that other factors also play a role, including incumbency (e.g. the export woodchip sector may also be criticised by NGOs but is already established) and value-judgments about the relative merits of harvesting forests for timber, paper or energy.
The other major area where bioenergy is often held to a higher standard than other uses of biomass is in relation to competition for land and other resources. While competition impacts, such as reduced food produced or increased GHG emissions from indirect land use change (iLUC), can be caused by a variety of forestry and agricultural products (e.g. timber, cotton, rubber), bioenergy is often singled out as having a special responsibility to avoid these competition impacts. Examples include the requirement under the RSB standards for biofuel producers to enhance local and regional food security (Roundtable on Sustainable Biofuels 2010) and the US EPA’s inclusion of iLUC emissions in their GHG life-cycle assessments (US EPA 2010).
The special responsibility for bioenergy to avoid competition impacts is evident in proposals such as the suggestion of Gallagher (2008) that future biofuel production be directed to “idle land” and the argument made by Searchinger et al. (2008) that biofuel feedstocks should be restricted to wastes only. Figure 2.7 provides a visual representation of the value-systems underlying the proposals of Gallagher (2008) and Searchinger et al. (2008), along with a third example from O'Connell, Keating & Glover (2005), who undertook a bioenergy sustainability scoping study for Australia. O’Connell et al. argued that an order of values exists for biomass use, stating that “the basic energy value of biomass will quite likely be one of the lowest order values” and “a sustainable bioenergy paradigm would suggest we pursue the highest order value of the biomass” (O’Connell et al. 2005, p. 5). They do not provide a definitive value order for all possible uses of biomass, but indicate that timber, primary food, fibre and ecosystem services such as soil remediation would generally rank above energy
69 recovery. The inclusion of ecosystem services makes it clear that the concept of an order of values is based on more than just the market values of biomass products.
Figure 2.7: Value-systems implicit in the approaches of Gallagher (2008), Searchinger et al. (2008) and O’Connell et al. (2005). Solid arrows show where one use is permitted to displace another, while dashed lines show where displacement is not permitted. Note that Gallagher (2008) and Searchinger et al. (2008) present different views on whether food production should be permitted to displace forests.
Both Gallagher and Searchinger et al. argue that energy cropping should not be allowed to displace existing food production. However, a rigid application of this rule could create problems for land use activities that seek to combine revegetation and bioenergy production, such as Oil Mallee in Western Australia. Figure 2.8 demonstrates this by comparing the assumptions underpinning the rules proposed by Gallagher and Searchinger et al. with the assumptions underpinning the development of an Oil Mallee industry in WA. The conversion of small strips within a wheat field to mallee may result in a short-term decline in wheat production due to loss of cropping
70 area, but, if this helps to mitigate dryland salinity, the long-term result may be higher levels of food production than if the area remained completely under wheat. Even the assumption that planting mallee would lead to a short-term reduction in food supply may be overly pessimistic in some cases, as mallee belts can enhance wheat yield by reducing wind impacts (Abadi & Cooper 2004).
Gallagher/Searchinger WA Oil Mallee assumptions assumptions
Bioenergy Bioenergy + other products displaces food displace production food production (partially)
Reduced food supply Short-term + Mitigation of reduction in dryland salinity Higher food prices food supply
Increased hunger & land Greater food supply clearing for agriculture over the long term
Figure 2.8: Comparison of assumptions underlying two different visions of bioenergy. The flowchart on the left represents the assumptions underpinning the recommendations of Gallagher (2008) and Searchinger et al. (2008), while the flowchart on the right represents the assumptions underpinning the development of Oil Mallee in WA.
Given the problems with dryland salinity in Australia, a blanket rule banning bioenergy plantations that displace food production could prove counter-productive in terms of food security, landscape health and even indirect land use change (as wheat production lost to salinity may be replaced by land clearing elsewhere in the world). While there are no plans at present to impose such restrictions in Australia, the global proliferation of bioenergy policy measures and the potential for mallee products such as wood
71 pellets or ethanol to be exported in the future (URS Australia 2009) raises the prospect that differing visions of bioenergy sustainability could increasingly come into conflict.
The conflict highlighted in Figure 2.8 demonstrates the need for comprehensive but context-specific decision-making processes that are able to consider the full range of land use values operating at a variety of scales (e.g. food, fuel, fibre, ecosystem services and social values). O’Connell et al. (2005, p. 5) make it clear that, despite seeing bioenergy as a lower order value of biomass, local priorities should also be considered and acknowledge that “there may be some circumstances where a dedicated energy crop may be desirable”. Flexibility can also be found in the food security requirements of the UN Energy and RSB sustainability criteria, which avoid blanket rules about the displacement of agriculture by biofuel production. Gallagher (2008) suggested that, ideally, addressing indirect impacts would require a global agreement on land use planning and the extension of sustainability standards more broadly across all agriculture and forestry activities. Chapter 3 explores conceptual frameworks that may assist in the development of a comprehensive and context-specific notion of sustainability that can be applied to bioenergy, agroforestry and revegetation.
2.5 Conclusion
The revegetation, plantation and bioenergy sectors explored in this chapter are characterised by differing sustainability issues, goals, benchmarks and policy instruments. Developing a notion of sustainability that can encompass these three sectors simultaneously involves the selection of appropriate elements from each sector and the careful integration of these elements. The revegetation sector is dominated by goals of environmental enhancement and policy measures such as grants and MBIs that seek to incentivise revegetation activities. In contrast, environmental goals in the plantation sector mostly focus on maintenance rather than enhancement and notions of sustainability appear most commonly within restrictive policy measures, such as regulations and industry standards. The bioenergy sector features both maintenance and enhancement goals and presents innovative ways of integrating incentives and disincentives, but also features a number of unresolved issues relating to land use for energy crops.
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It may be possible in some cases to find synergies between the goals and policy measures of the different sectors, such as the promotion of Oil Mallee as an energy crop that can provide both renewable energy and salinity mitigation. However, trade- offs are likely to be required in other cases, such as using land for either food or fuel and designing plantations to maximise either biomass production or biodiversity. As highlighted in section 2.4, such trade-offs will inevitably involve value judgments, raising questions of whose values should be employed (e.g. local community, global community, affected/interested parties), at what scale should trade-offs be made (e.g. global food security vs. local soil protection) and how should the costs and benefits be shared. Key decisions are also required on how policy instruments should be targeted to achieve maximum effectiveness and efficiency.
The following chapter explores a range of conceptual frameworks that can assist with the integration of the various issues, goals, benchmarks and policy instruments across the three sectors and the development of a framework for selecting and implementing integrated sustainability policy.
73 Chapter 3: Conceptual Frameworks
The purpose of this chapter is to evaluate a range of established conceptual frameworks for their potential to help frame a notion of sustainability that can simultaneously encompass revegetation, agroforestry and bioenergy production. Five cross- disciplinary frameworks are introduced and discussed in the following sections: 3.1: Multifunctionality 3.2: Conservation through sustainable use (CSU) 3.3: Adoption of innovations by rural landholders 3.4: Ecological economics 3.5: Resilience within adaptive complex systems
Section 3.6 combines these five conceptual frameworks and attempts to incorporate them into an integrated sustainability policy framework that can be applied to the case studies in Chapters 4-8.
3.1 Multifunctionality
Multifunctionality is a broad concept which, according to the OECD (2001), recognises that agriculture and other land uses involve the joint production of multiple commodity and non-commodity outputs and that some of these non-commodity outputs constitute externalities or public goods. Food, fibre and biofuels are all examples of commodity outputs, while examples of non-commodity outputs include ecosystem services, food security and the viability of rural communities. Multifunctionality has been most prominent as a concept in the agriculture sector, particularly as a focus of trade policy and agricultural subsidy reform (e.g. World Trade Organization 2001, European Commission 2010a). However, similar ideas can also be found in forestry and other sectors, often under terms such as “multiple-use” or “joint production” (OECD 2001). While a truly multifunctional approach might seek to dismantle the boundaries delineating the agriculture, forestry, energy and conservation sectors altogether, discourses on multifunctionality often operate within these traditional boundaries.
74 A multifunctional approach to framing sustainability issues across the bioenergy, plantation and revegetation sectors would avoid defining any land use option in terms of a single output, but rather would recognise the joint production of multiple outputs. Even where the intent of a land manager is heavily focused around one objective (e.g. food production, timber harvest or biodiversity conservation), there are likely to be a variety of non-target outputs such as ecosystem services or social benefits. Where land managers are actively seeking multiple outcomes, the OECD (2001) argues that it may be inappropriate to talk about some outcomes as simply “by-products” or “side- effects”. The Oil Mallee example cited in Chapter 2 demonstrates this clearly, with salinity mitigation, rural viability and maintenance of food production being explicit goals rather than simply by-products of a commodity production system (URS Australia 2009). Similarly, authors such as Dornburg (2004) have advocated a shift away from the idea of single-purpose land uses towards “multifunctional biomass systems” for various material and energy outputs.
Two key elements of multifunctionality are the scale or scales at which outputs are delivered and the extent to which such outputs are connected or joint (OECD 2001). Economic, social and environmental impacts of land use often occur at different spatial and temporal scales and such scale factors are particularly important for non- commodity outputs that cannot be adequately captured in global markets, such as biodiversity conservation, soil and water health, amenity and rural viability. Food security can also be seen as a non-commodity output of agriculture which has local as well as global dimensions (OECD 2001). Local or national food security constitutes a primary goal for multifunctional agriculture in many European countries such as Norway, where it is used to defend agricultural subsidies and trade barriers (Bjørkhauga & Richards 2008).
The joint delivery of outputs is integral to multifunctionality, as it determines the extent to which land managers are able to separate the provision of commodity and non-commodity outputs. Joint delivery differs across production systems, with three main sources identified by the OECD (2001): technical interdependencies (e.g. pest control through cropping patterns), non-allocable inputs (e.g. mutton and wool both produced from sheep) and allocable inputs that are fixed so that the amount allocated
75 to one output affects another (e.g. available farmland being allocated to food or to fuel). The combined impact of joint delivery and overlapping scales means that many outputs cannot simply be separated and addressed at the geographic scale most appropriate (e.g. global food security cannot be managed separately from local provision of ecosystem services). Rather, multiple outputs providing both private and public goods and operating at a variety of scales must be considered simultaneously.
A critical debate around multifunctionality is whether it is simply a characteristic of particular land use systems that needs to be recognised (a “positive” approach) or whether it is a goal to be actively pursued (a “normative” approach) (OECD 2001). The reform of the EU Common Agricultural Policy (CAP) provides an example of a normative approach, with one of the identified objectives being to “secure the enhanced provision of environmental public goods” (European Commission 2010a, p. 7). Conversely, the World Trade Organization (2004, p. 70) demonstrates a positive approach, recognising that “most countries accept that agriculture is not only about producing food and fibre but also has other functions” but not holding a position on whether multifunctionality should be an explicit goal of agriculture.
3.1.1 Multifunctionality in Australia
In Australia, multifunctionality has not been recognised to the same degree as in many European countries, with Australian agricultural policy largely operating under a free- market productivist paradigm rather than the protectionist multifunctional paradigm that has emerged in Europe (Bjørkhauga & Richards 2008). However, Holmes (2006) argues that Australian agriculture has begun to move away from a dominant productivist mentality and is undergoing a “multifunctional rural transition” in which land is no longer valued solely for what it can produce but is increasingly being valued for attributes that he categorises as “consumption” (e.g. amenity or lifestyle values) and “protection” (e.g. biodiversity or scenic beauty). Holmes (2006) and Argent (2002) both emphasise that productivist agricultural goals are still prominent in much of Australia and that the rural transition should not be seen as “post-productivist”, a term that has been used to describe rural land use in the UK.
76 Holmes (2006) regards the main drivers of the multifunctional rural transition in Australia to be agricultural overcapacity, increasing environmental concerns and the emergence of market-driven amenity uses due to higher incomes and mobility. He identifies the following “rural occupance modes” for rural Australia based on the relative dominance of production, consumption or protection goals: - Productivist agricultural (production); - Rural amenity (consumption); - Conservation (protection); - Indigenous (protection); - Small farm or pluriactivity (mix of production and consumption); - Peri-metropolitan (intense contests between production, consumption and protection); and - Marginalised agricultural (potential integration of production and protection).
Holmes (2006) argues that, apart from the indigenous mode, these modes are largely generic for affluent western nations. However, the size and diversity of Australia has allowed them to become more clearly delineated. The productivist mode remains dominant in certain areas with high rainfall, high soil fertility or irrigation, as well across the “agricultural heartland” inland of the major cities. The rural amenity mode forms a zone around major cities (just beyond the peri-metropolitan zone), as well as around prime tourist destinations (often near the coast). The conservation mode has traditionally consisted of rugged or infertile land in high rainfall areas and the arid interior, but declining production in the semi-arid rangelands has added new properties to the conservation estate. Holmes views the rise of a marginalised agricultural mode in these areas (as well as on small farms that are no longer viable) as creating new opportunities, such as further protection, the provision of ecosystem services (e.g. biodiversity, carbon sinks), forestry plantations and tourism.
Within the Australian forestry sector the term multifunctionality is rarely used, but the multiple values and uses that forests can provide are often recognised in policy. Lindenmayer et al. (2006) include the provision of wood and non-wood values alongside the maintenance of ecological processes and functions under their notion of “ecologically sustainable forestry”, while the need to “maintain and protect other forest
77 values” is recognised under the notion of Ecologically Sustainable Forest Management used by the Australian Government (Department of Agriculture Fisheries and Forestry 2007). In contrast to these attempts to promote a multifunctional outlook, Ferguson (2005) argues that a notion of “one-tenure, one-use” has been dominant within Government, NGOs and the media in Australia, making it difficult to better manage the multiple values that forests inevitably provide.
Australian researchers have contributed to the debate around whether multifunctionality should be actively pursued as a goal. Fischer, Brosi, Daily, Ehrlich, Goldman, Goldstein et al. (2008) compare two ends of an agricultural land use spectrum which they define as “land-sparing” (monofunctional) and “wildlife-friendly farming” (multifunctional). Land-sparing is a strategy involving binary course-grained landscapes where land is dedicated to either production or conservation, while wildlife- friendly farming involves heterogeneous fine-grained landscapes that perform multiple functions (Figure 3.1). Fischer et al. (2008) argue that, while both strategies may have strengths for biodiversity conservation (e.g. some species require large blocks of undisturbed habitat while others need mosaics), managers of binary course-grained landscapes should aim to increase their landscape heterogeneity through land use diversification and the establishment of habitat corridors. Brock et al. (2002) make a similar argument that the simplification of agroecosystems for efficiency and specialisation can lead to a loss of resilience due to the exclusion of many species.
Godfray (2011) and Noble (1995) present arguments against the kind of “land-sharing” model promoted by Fischer at al. (2008) and Brock et al. (2002). Godfray (2011) cites data on bird populations from India and Ghana as evidence that land-sparing provides better conservation and food production outcomes in forested tropical regions, while Noble (1995) uses data from Australian forests to make a case that intensive harvesting over a smaller forest area (with the remaining area protected) represents a marginally better strategy for biodiversity than multiple-use over the entire, larger area. While these studies demonstrate that the promotion of multifunctionality may not be the most efficient way to deliver desirable outputs in certain landscapes, their results do not consider other factors such as which landscape type may be more resilient to external shocks or more capable of facilitating adaptation to climate change.
78
Figure 3.1: Conceptual model of land-sparing and wildlife-friendly farming. The three examples highlight the continuum of scales at which biodiversity conservation and agriculture can be integrated. Reproduced from Fischer at al. (2008, p.381)
3.1.2 Multifunctionality versus strict prioritisation of outputs
Chapter 2 highlighted a number of approaches that sought to rank particular land use outputs such as food, bioenergy and biodiversity based on an order of values (O'Connell et al. 2005, Searchinger et al. 2008, Gallagher 2008). Such approaches may be compatible with multifunctionality if they recognise the prevalence of joint outputs and take into account local factors. For example, O’Connell et al. (2005) recognise that locally-significant outputs such as soil remediation may be delivered jointly with commodity outputs such as bioenergy. However, the approaches of Gallagher (2008) and Searchinger et al. (2008) present a vision quite different to that of multifunctionality, by defining land according to its primary output (e.g. food, fibre, conservation or “idle land”) and proposing a common set of land use rules across the globe (e.g. biofuels should not be produced on land currently used for food production). In contrast, a multifunctional approach would recognise that a land use system is defined by a combination of outputs (e.g. food, energy, ecosystem services, rural viability) and that the relative value of these outputs will vary according to local circumstances and priorities.
79 The OECD (2001, p. 17) argues that “spatial and scale differences reduce the usefulness of market and policy approaches that can not be implemented using area specific or local criteria”. Thus, policy approaches that do not take into account local criteria should be treated with caution and land use policy is likely to require a suite of complementary policy instruments that operate across a variety of scales. For example, while some authors have called for a global ban on bioenergy expansion (or global restriction to “idle land”), local stakeholders may determine that a land use system producing a mixture of food, bioenergy, soil conservation and habitat for biodiversity (e.g Oil Mallee in Western Australia) is of greater value than one that specialises in food production alone. However, a multifunctional approach does not mean that local values should automatically prevail over global values. Multifunctionality provides a framework for considering issues of joint delivery and scale in the development of policy, but it does not provide a value system for ranking different outputs across different scales.
3.1.3 Multifunctional policy instruments
Much of the policy development that has occurred to date around multifunctionality has taken place within the context of agricultural trade policy. The European Union, Norway and Japan have been amongst the strongest advocates of multifunctionality and the need to consider “non-trade concerns” such as food security, environmental services and rural viability (World Trade Organization 2001). Under the WTO’s Agreement on Agriculture, direct government payments to landholders are unrestricted (in the so-called “green box”), provided that such payments are not related to the volume of production and do not act as a form of price support (World Trade Organization 1994). The EU is in the process of reforming its Common Agricultural Policy (CAP) to decouple subsidies from commodity production and instead base them on the maintenance of key non-commodity outputs, such as basic income levels, climate change mitigation and other environmental goals (European Commission 2010a).
An example of multifunctional thinking being incorporated into bioenergy policy is Brazil’s national program for biodiesel use and production (PNNB). This program
80 followed on from Brazil’s more well-known ethanol program, PROALCOOL, and employed a similar approach based on a blending mandate for biodiesel (initially at 2% and rising to 5%) and fuel tax exemptions (Romeiro 2006). However, the Brazilian government has also incorporated social objectives into this policy by certifying biodiesel that is produced from feedstocks grown by family farmers under the National Programme for the Strengthening of Family Agriculture (PRONAF) as “Combustível Social”, or social fuel (Romeiro 2006). Social fuels qualify for a 67.9% reduction in fuel tributes (taxes) and this reduction is increased to 100% if the biodiesel feedstocks also come from Brazil’s poorest regions in the north or north-east of the country (Pousa, Santos & Suarez 2007). Romeiro (2006) and Pousa et al. (2007) argue that these incentives have been insufficient to allow small farmers to compete with industrial-scale agriculture (particularly soybean oil), but they do demonstrate how the joint delivery of two outputs (biofuel and social development) can be recognised and promoted in government policy.
While tax breaks have been used in Brazil to provide differentiated incentives, similar opportunities exist with mandates and feed-in tariffs. The EU’s renewable energy directive, discussed in Chapter 2, allows biofuels from wastes and cellulosic energy crops to be “double-counted” towards national targets and mandates, such as the UK’s Renewable Transport Fuels Obligation (RTFO). This is based on the idea that such feedstocks present a lower risk of indirect impacts such as deforestation or food insecurity than crops like corn or oil palm. Chapter 2 also discussed examples from the electricity sector where differentiated support has been provided for renewables, such as “banding” under the UK’s Renewables Obligation, the Solar Credits “multiplier” under Australia’s Renewable Energy Target and the use of bonus rates under Germany’s bioenergy feed-in tariffs.
While the Brazilian biodiesel example clearly employs social goals and the EU’s double-counting for biofuels is aimed at preventing negative land use impacts, the use of banding or differentiated feed-in tariffs for electricity has typically had a different focus. These measures have primarily been used to promote emerging renewable technologies that are more expensive than mature technologies but have strong future potential. For example, the UK introduced banding to its Renewables Obligation in
81 2009 following a determination that the previous technology-neutral approach was only promoting least-cost sources such as onshore wind and hydro (Department of Trade and Industry 2007). As these sources had limitations in terms of future expansion, and there was a need to provide extra support for emerging technologies (Department of Trade and Industry 2007). However, the social or environmental desirability of different technologies can also have an influence on such policies. One of the key limitations cited for onshore wind power in the UK was the long delays in obtaining planning approval (Department of Trade and Industry 2007), which partly reflects concerns about visual and other impacts of wind farms amongst some sectors of UK society. In Germany, local environmental goals have influenced the structure of bioenergy feed-in tariffs, with bonuses awarded to biomass from land managed for landscape preservation and technologies that produce fewer harmful emissions (Schuck 2010).
The idea of structuring renewable energy incentives to preference technologies based on their environmental or social co-benefits is a developing concept and has not been considered in detail for Australia. Further consideration of how such a model could work for both biofuels and electricity generation in the Australian context is provided in Chapter 8. Overall, multifunctionality appears to offer a framework for dealing with situations that lie at the heart of this thesis, where land use systems deliver multiple outputs jointly across a variety of scales. Despite lower levels of recognition of the concept in Australia to date, multifunctionality clearly has relevance for rural land use patterns across many parts of the country (Holmes 2006). A multifunctional approach does not necessarily resolve questions of how to prioritise different outputs, but it can help to understand the interrelationships between these outputs and develop policy approaches that capitalise on the synergies that may exist.
82 3.2 Conservation through sustainable use
Conservation through Sustainable Use (CSU) is a policy approach that seeks to align production and conservation goals in circumstances where the use of biodiversity can provide an incentive for conservation. In some ways, CSU can be seen as a variation of multifunctionality, as it is also based around the idea that certain outputs are delivered jointly. However, it has mostly been employed within the conservation sector and been focused on the sustainable harvesting of biodiversity rather than on agricultural production.
CSU is more specific than the broader concept of “sustainable use” that has been explored extensively within institutions such as the IUCN (International Union for Conservation of Nature), the Convention on Biological Diversity (CBD) and the Convention on International Trade in Endangered Species (CITES). CSU involves more than simply a recognition that sustainable use is preferable to unsustainable use. It also recognises that, in some cases, use may be preferable to no use at all, on account of the incentives for conservation that use can provide. This idea is encapsulated in the following quote from the Addis Ababa Principles and Guidelines for the Sustainable Use of Biodiversity (CBD 2004, p. 7): “encouraging sustainable use can provide incentives to maintain habitats and ecosystems, the species within them, and the genetic variability of the species”
CSU as a term has been used most commonly in Australia, where it has been applied to sustainable use initiatives involving saltwater crocodiles (Webb 2002), kangaroos (Ampt & Baumber 2006) and a variety of other potential industries based on native species (Archer & Beale 2004). Similar initiatives worldwide are often referred to using other terms, such as finding “synergies” between production and biodiversity (e.g. Erskine & Catterall 2004), seeking “win-win” outcomes between forest cover and human well-being (Sunderlin, Angelsen, Belcher, Burgers, Nasi, Santoso et al. 2005), “making the restoration of natural capital profitable” (Pejchar, Goldstein & Daily 2007) and identifying actions that have both private and public net benefits (Pannell 2008). While these other concepts may correspond broadly to CSU, the term is used here to refer specifically to initiatives that meet the following preconditions:
83 1. any harvested components of an ecosystem are sustainably extracted (i.e. not harvested beyond their capacity to be replenished); 2. conservation of one or more elements of an ecosystem constitutes an overarching goal of management, with use representing a means to that end (implied by the term conservation through sustainable use); and 3. the use of these biodiversity components provides an incentive to conserve habitat that may otherwise not be conserved.
These conditions and the boundaries they place around CSU are open to interpretation. Different views are possible on what the primary goal of management should be and the extent to which trade-offs between goals should be allowed. There may also be differing perspectives on what constitutes a sustainable extraction rate or what particular ecosystem components, services or functions need to be maintained. Assumptions are also required regarding what may happen in the absence of use, with such assumptions requiring a certain degree of pragmatism (e.g. without use there would be no incentive to maintain the ecosystem and it is likely to be converted to a more damaging land use) rather than pure idealism (e.g. if current use ceased the area would ideally be protected for its ecological values). Incentives to conserve habitats can result from a variety of commercial and non-commercial use activities, including hunting (for meat, skins or sport), harvesting of forest products, recreation and tourism. The provision of ecosystem services such as clean water, flood mitigation or carbon sequestration may also be seen as the use of an ecosystem and thus could arguably fall under the concept of CSU.
While CSU attempts to harness the incentives that can be provided by the use of ecosystem components, it is important to stress that it is not based around the notion that all functions of an ecosystem can and should be assigned market values. This notion, often applied in the field of environmental economics, has been criticised for its “weak” sustainability principles (e.g. Hamilton 1997). CSU does not justify use activities on the basis that they are the most economically efficient thing to do, but rather based on the capacity of use activities to contribute to conservation goals in a pragmatic manner. Furthermore, CSU does not suggest that only those aspects of ecosystems which can be commercialised should be conserved. In situations where
84 conservation goals do not align with any viable use activity, CSU is unlikely to be the most appropriate framework to employ. It must also be recognised that the commercial use of selected ecosystem components can create incentives to overharvest or simplify ecosystems to provide only the components that are valued by the user (Sunderlin et al. 2005). Thus, CSU initiatives must avoid a simplistic assumption that use will automatically lead to conservation and instead be based on a broader consideration of the full social, economic and environmental impacts of use.
3.2.1 CSU in restoration, revegetation and agroforestry
The relationship between sustainable use and conservation is subject to a diverse range of viewpoints (Cooney 2007). Sustainable use is sometimes viewed narrowly as relating only to “wild living resources” (e.g. IUCN 2000), a term that could exclude replanted ecosystems. In other cases, such as the CBD-sponsored Satoyama Initiative (Nature Conservation Bureau 2009), sustainable use principles are applied to the conservation of “secondary nature” (environments created and managed by local people engaged in farming, forestry or other activities). This initiative is named after the Satoyama Landscape of Japan, a mix of managed forests, rice paddies, irrigation ponds and grasslands that provide crucial habitat for endangered species and valuable ecosystem services. Applying CSU principles to the overlap zone between revegetation and agroforestry requires a broad approach that looks beyond the maintenance of “natural” or “wild” ecosystems to include situations where a secondary ecosystem is being restored or established with the aim of sustainably harvesting from it in the future.
The cork forests of the western Mediterranean provide an example of a CSU strategy being employed in a reforested landscape. Conservation groups such as WWF (2006) have argued in favour of the continued use of cork for wine bottling in order to help maintain the 2.7 million hectares of cork oak forests. The composition of these forests has been shaped by human management over a variety of spatial and temporal scales (Urbieta & Marañón 2008) and their diverse mosaic habitats continue to support endangered species such as the Iberian Lynx, the Iberian Imperial Eagle and the Barbary Deer (WWF 2006). A declining cork industry poses threats including clearing
85 for agriculture and other land uses, forest abandonment, poor forest management and increasing forest fires. The concept of CSU is encapsulated in the following argument: “Because the forests have an economic value to local communities, people care for the forests. This helps maintain their environmental values as well as reducing the risk of fires and desertification.” (WWF 2006, p. 2)
The damar agroforests of Sumatra are another globally-highlighted example of a constructed forest landscape in which ongoing harvest helps to maintain a variety of complementary social, economic and environmental values (Sunderlin et al. 2005). These replanted forest ecosystems are so-named because of the central role of the damar tree (Shorea javanica), which yields a resin used in the production of incense, varnish, paint, and cosmetics (Kusters, Ruiz Perez, De Foresta, Dietz, Ros-Tonen, Belcher et al. 2008). Household surveys in the Krui region of Sumatra undertaken by Kusters et al. (2008) identified pressure to convert damar forests to monocultures of coffee, pepper or oil palm. However, they also found that maintaining damar has its own continuing appeal, partly due to economic attributes such as a consistent low-risk income with low labour requirements and partly due to social factors such as a taboo on clear-cutting damar and a social responsibility to maintain forests planted by forebears. The Indonesian Government has also granted some farmers special usage rights to damar agroforests on state land in order to maintain a buffer zone for the World Heritage-listed Bukit Barisan Selatan National Park (Kusters et al. 2008).
In Australia, commercial eucalypt plantations has been expanding at the same time as calls have grown for extensive revegetation of woodlands to reverse declining biodiversity and other environmental values (e.g. Vesk & Mac Nally 2006, Cork et al. 2006). Research by Loyn et al. (2007) in two regions of Victoria found that mean bird densities were higher on eucalypt plantations established on formerly cleared sites than they were on adjacent cleared farmland. Remnant woodland sites had higher bird densities than plantations overall, although plantations provided important habitat for many bird species that were in decline in woodlands. Such evidence demonstrates the potential value of plantations within a biodiverse vegetation mosaic. In years to come, these plantations could be viewed in a similar light to the cork and damar forests, with conservationists championing the continuation of use activities in order to prevent
86 broadscale conversion to other uses and associated loss of biodiversity. Oil Mallee, discussed in Chapter 2, has also shown the potential for bioenergy to be a key commercial driver for such land use options.
A counter example, where CSU arguments have been misused, is the claim that oil palm plantations in Indonesia contribute to soil, water and biodiversity conservation by providing a way to revegetate areas that have previously been cleared for forestry (US Embassy Jakarta 2005). While it is indeed possible that such plantations may be more environmentally beneficial than leaving these areas deforested, it is also important to consider the broader context in which logging companies and oil palm producers interact. As discussed in Chapter 2, oil palm production has been identified as an ongoing driver of deforestation in southeast Asia and Sheil (2009) cites examples where palm oil companies have been suspected of deliberately lighting fires to degrade forests and where logging companies have used palm oil licences to gain access to timber because they could not obtain logging permits. Plantations can only be considered a true example of CSU once it is shown conclusively that are not contributing to further deforestation.
3.2.2 Key principles and tools for operationalising CSU
The Convention on Biological Diversity (CBD) has provided a vehicle for much of the conceptual work on sustainable use under the banner of the “ecosystem approach”, which promotes the integrated management of land, water and living resources. Table 3.1 shows the twelve ecosystem approach principles endorsed in 2000 under Decision V/6 of the parties to the Convention on Biological Diversity (CBD 2000). These are matched against the fourteen principles of the Addis Ababa Principles and Guidelines for the Sustainable Use of Biodiversity (CBD 2004), which provide more specific guidance on matters of sustainable use. Both sets of principles are broader than the concept of CSU, covering a range of circumstances involving integrated management. However, they highlight a number of policy factors that are relevant to CSU, including usage rights, regulations, distribution of costs and benefits, community participation, communication, sustainability, economic analysis, interdisciplinary approaches and adaptive management.
87 Table 3.1: Ecosystem Approach principles matched to their most closely-related Addis Ababa principles.
Principles of the Ecosystem Approach Specific Guidance provided by Addis (CBD 2000) Ababa principle/s [with number of principle] (CBD 2004)
1. The objectives of management of x Create supportive policies, laws, and land, water and living resources are a institutions at all levels of governance, matter of societal choice. with effective linkages between these levels. [1]
2. Management should be decentralized x Empower and support local users of to the lowest appropriate level. biodiversity to be responsible and accountable for resource use [2] x Ensure that the needs of indigenous and local communities and their contributions to resource conservation and sustainable are reflected in the equitable distribution of benefits. [12]
3. Ecosystem managers should consider the effects (actual or potential) of their activities on adjacent and other ecosystems.
88 Principles of the Ecosystem Approach Specific Guidance provided by Addis (CBD 2000) Ababa principle/s [with number of principle] (CBD 2004)
4. Recognizing potential gains from x Identify and remove perverse incentives management, there is usually a need that undermine conservation and to understand and manage the sustainable use of biodiversity [3] ecosystem in an economic context. x Policies should take into account: Any such ecosystem-management (a) Current and potential values of use; programme should: (b) Intrinsic and other non-economic (a) Reduce those market distortions values; and that adversely affect biological (c) Market forces affecting values. [10] diversity; x Minimise waste and adverse (b) Align incentives to promote environmental impact and optimise biodiversity conservation and benefits from uses. [11] sustainable use; x Internalise the costs of management and (c) Internalize costs and benefits in conservation of biological diversity [13] the given ecosystem to the extent feasible.
5. Conservation of ecosystem structure x Avoid or minimize adverse impacts on and functioning, in order to maintain ecosystems through management goals ecosystem services, should be a and practices [5] priority target of the ecosystem approach.
6. Ecosystems must be managed within the limits of their functioning.
89 Principles of the Ecosystem Approach Specific Guidance provided by Addis (CBD 2000) Ababa principle/s [with number of principle] (CBD 2004)
7. The ecosystem approach should be x Ensure that the spatial and temporal undertaken at the appropriate spatial scale of management is compatible with and temporal scales. the ecological and socio-economic scales of use [7] x Ensure international cooperation where multinational decision-making and coordination are needed. [8]
8. Recognizing the varying temporal scales and lag-effects that characterize ecosystem processes, objectives for ecosystem management should be set for the long term.
9. Management must recognize that x Practice adaptive management based on: change is inevitable. (a) Science and traditional/local knowledge; (b) Iterative, timely and transparent feedback from monitoring of use and impacts; and (c) Adjusting management based on timely feedback from the monitoring procedures [4]
10. The ecosystem approach should seek the appropriate balance between, and integration of, conservation and use of biological diversity.
90 Principles of the Ecosystem Approach Specific Guidance provided by Addis (CBD 2000) Ababa principle/s [with number of principle] (CBD 2004)
11. The ecosystem approach should x Promote and support interdisciplinary consider all forms of relevant research into all aspects of use and information, including scientific and conservation of biological diversity [6] indigenous and local knowledge, x Apply an interdisciplinary, participatory innovations and practices. approach to management and
12. The ecosystem approach should governance [9] involve all relevant sectors of society x Develop and implement education and and scientific disciplines. public awareness programmes on conservation and sustainable use [14]
As with the concept of multifunctionality, the ecosystem approach provides a framework for integrating different economic, social and environmental goals without dictating which goals should be adopted. These goals are considered to be a matter of societal choice (Principle 1). While this has been a source of criticism of the ecosystem approach in some quarters, Sayer and Maginnis (2005) argue that it was never intended to be a management prescription but rather a set of principles outlining desirable attributes for management systems. The ecosystem approach does provide some guidance on what factors should be taken into account in the process of goal-setting and how these factors should be prioritised, particularly through its promotion of local benefits and decentralised management (Principle 2), consideration of impacts on adjacent ecosystems (Principle 3) and maintenance of ecosystem services as a priority target (Principle 5).
The Addis Ababa Principles and Guidelines (CBD 2004) further highlight the rights and needs of local and indigenous people. It is argued that economic benefits from ecosystem use, such as jobs and profits, should be directed at local communities for reasons of both equity (these groups often shoulder significant costs so should receive a share of benefits) and pragmatism (active local engagement and participation can minimise management violations). The assignment of usage rights to local people can
91 also overcome some of the problems commonly associated with the “tragedy of the commons” (Hardin 1968), as reflected in the following statement:
“Resources for which individuals or communities have use, non-use, or transfer rights are usually used more responsibly because they no longer need to maximise benefits before someone else removes the resources” (CBD 2004, p. 9).
Despite the focus on local interests under the ecosystem approach, the parties to the CBD made clear in Decision V/6 that local interests should not automatically prevail but rather should be balanced against the wider public interest. Sayer and Maginnis (2005) also caution against too much of a focus on local interests, citing examples from Australia and the UK where the assigning of rights to private forest-owners has made it difficult for subsequent governments to re-assert the public interest.
Externalities (costs or benefits borne by those external to the management of the system) are a critical issue for CSU initiatives. The ecosystem approach and Addis Ababa Principles require consideration of impacts on adjacent ecosystems, removal of perverse incentives, alignment of incentives for conservation and sustainable use, and internalisation of costs and benefits within the managed ecosystem. However, this does not mean that activities should seek to have no impacts beyond the system being managed. Indeed a CSU approach involves the active promotion of external benefits (e.g. ecosystem services that benefit more than just the direct managers of the ecosystem). Rather, the ecosystem approach aims to ensure that those who benefit from an ecosystem’s conservation also contribute to the costs involved and those who manage the resource are compensated for the benefits they provide to others (Conference of the Parties to the Convention on Biological Diversity 2000).
Payments for ecosystem services, such as the carbon sequestration and habitat provision, are one way of internalising positive externalities. Negative externalities may be minimised by removing perverse subsidies, granting tax breaks for environmental investment or introducing certification schemes that reward managers who have internalised costs (CBD 2004, p. 20). While the Addis Ababa principles recognise the importance of strong regulations on use (e.g. harvest limits or quotas), they also advise the removal of inadequate or unnecessary regulations on the grounds
92 that they can increase costs, foreclose opportunities and encourage unregulated uses (CBD 2004, p. 11). The Addis Ababa principles also advocate adaptive management plans (including monitoring and targeted research), extension activities (e.g. education, demonstration), public participation and awareness-raising and economic valuation studies of environmental services (discussed further in section 3.4).
Overall, the concept of CSU and the policy principles and tools identified under the Addis Ababa principles offer useful guidance for the types of land use options being explored in this thesis. In particular, the focus on harnessing commercial drivers to achieve conservation, the value of local usage rights and the internalisation of externalised costs and benefits are all relevant for the framing of sustainability policy and the selection of policy instruments around bioenergy-based agroforestry.
3.3 Adoption of innovations by rural landholders
In order to understand whether new land use options such as bioenergy-based agroforestry can create incentives for conservation, it is important to understand how land use innovations diffuse and become adopted (or not adopted) by rural landholders. The conceptual frameworks and practical lessons that have emerged from diffusion research over several decades provide valuable insights into which factors may be critical in determining adoption or non-adoption and what policy mechanisms may be effective in promoting adoption (if indeed such a goal is desirable).
3.3.1 Paradigms of diffusion and landholder adoption
A study by Ryan and Gross (1943) into the adoption of hybrid corn in Iowa was highly influential on the development of diffusion research, as it established many of the key methodologies and identified several key factors influencing adoption. Rogers (1962) pioneered a generalised model of innovation diffusion that has achieved widespread currency and has been refined over five editions (up to Rogers 2003). Rogers’ central argument is that the process of diffusion is a general process that can be found within diverse contexts ranging from agriculture to medicine to information technology and that it features the same core elements irrespective of the type of innovation, who the
93 adopters are, or where it takes place. Adoption research cuts across a wide range of disciplines, including sociology, economics, psychology, anthropology, marketing and agriculture (Pannell, Marshall, Barr, Curtis, Vanclay & Wilkinson 2011). A key focus of diffusion research is the effectiveness of interventions by governments, NGOs and/or businesses to promote adoption (e.g. Vanclay 2004, Foxon & Pearson 2008, Pannell & Wilkinson 2009, Low et al. 2010).
A key point made by Rogers (2003), and reinforced in the rural Australian context by authors such as Vanclay (2004) and Pannell et al. (2011), is that adoption is fundamentally a social process. Rogers (2003) highlights a number of examples, from cures for scurvy to the design of keyboards, where technological innovations with clear advantages have failed to be adopted due to socio-cultural factors. Vanclay (2004, p. 213) argues that “agriculture has too long been thought of as a technical issue involving the application of science, and the transference of the outputs of that science via a top-down process of technology transfer”. Pannell et al. (2011) explore a range of social factors that influence adoption, including the personality of the decision maker, their social networks, personal circumstances and family situation. They also make the point that many factors, such as risk, long-term costs and benefits and the value of keeping future options open, can be seen as either economic or social depending on one’s disciplinary perspective.
Figure 3.2 compares two frameworks for the adoption of innovations: x the generalised diffusion model of Rogers (2003); and x the framework outlined by Pannell et al. (2011) for the adoption of conservation practices by rural landholders in the Australian context (revised from Pannell, Marshall, Barr, Curtis, Vanclay & Wilkinson 2006).
While Rogers employs four key elements of diffusion (innovation, communication channels, time and social system), Pannell et al. divide their framework into three key sets of issues (attributes of practices, process of learning and experience and social, cultural and personal influences). Rogers’ “innovation” element largely corresponds to the “attributes of practices” cited by Pannell et al. Similarly, Rogers’ innovation- decision process (under his “time” element) corresponds broadly to the “process of
94 learning and experience” identified by Pannell et al. There are, however, some notable differences, such as the way that Pannell et al. employ a single notion of social, cultural and personal influences that largely combines Rogers’ elements of “communication channels” and “social system”. Furthermore, Rogers considers that the key consideration when categorising adopters is time, (i.e. categories based on the amount of time people take to adopt a new idea). Pannell et al. (2011, p. 18) prefer to deal with landholder differences under social, cultural and personal influences and emphasise that “people who adopt one innovation early are not necessarily early adopters of all innovations”.
Figure 3.2: The key elements of the diffusion of innovations. Elements from Rogers (2003) are compared to the set of issues identified by Pannell et al. (2011).
Rogers (2003) identifies five attributes of an innovation that may influence its adoption: relative advantage, compatibility, complexity, trialability and observability. Pannell et al. (2011) simplify these into only two categories: relative advantage (including compatibility and complexity) and trialability (including observability and complexity). Relative advantage relates to the perceived advantages of an innovation
95 over current practices and includes factors such as economic costs and benefits (short, medium and long-term), risk profile, interaction with government policy, lifestyle impacts, self-image and environmental credibility. Trialability relates not only to how easily a trial can be established, but also how easily results are able to be observed and employed in further decision-making. Both Rogers and Pannell et al. make the point that, when it comes to understanding adoption, what matters most is not an “objective” analysis of the innovation’s attributes by an external party, but rather how the attributes of the innovation are perceived by potential adopters.
The innovation-decision process identified by Rogers and the process of learning and experience identified by Pannell et al. feature a similar progression of stages. The first stage relates to initial knowledge or awareness of an innovation, progressing to a persuasion stage (where an attitude towards an innovation is formed through non-trial evaluation), a decision stage (involving trial evaluation where possible), an implementation stage (if the decision is made to adopt) and, finally, a confirmation stage (involving review and potentially dis-adoption). For any given innovation, different individuals will move through these stages at different rates, with Rogers using this to define five adopter categories: (1) innovators, (2) early adopters, (3) early majority, (4) late majority and (5) laggards.
Drawing on diffusion case studies undertaken over several decades in a range of fields, Rogers’ (2003) argues that the adoption process usually follows a normal, bell-shaped curve (Figure 3.3), with small numbers of adopters at first being joined by increasingly large numbers as a critical mass is reached. Adoption rates then peak and go into decline as the market of potential adopters becomes saturated.
96
Figure 3.3: Generalised model of adoption over time based on Rogers’ five adopter categories. Redrawn from Rogers (2003, p. 281).
Rogers’ classification scheme has achieved widespread use in a number of fields, including agriculture, but it has also attracted criticism. Rogers considers the underlying determinant of his adopter categories to be “innovativeness”, which he defines as “the degree to which an individual (or other unit of adoption) is relatively earlier in adopting new ideas than other members of a system” (Rogers 2003, p. 267). He also outlines “ideal types” for each category based on shared characteristics and values such as venturesome (innovators), respect (early adopters), deliberate (early majority), sceptical (late majority) and traditional (laggards). Pannell et al. (2011) criticise this approach for implying that innovativeness is a characteristic that people apply equally to all innovations. Vanclay (2004) emphasises that farmers often have legitimate reasons for non-adoption and argues that stereotyping particular farmers as recalcitrant laggards can lead to inequitable approaches that place the needs and worldviews of certain farmers above those of others. Rogers (2003, p. 121) acknowledges that the stereotyping of later adopters as uneducated, irrational and/or resistant to change can contribute to an “individual-blame bias” that should be avoided, but he does not regard the use of terms such as “laggard” or the defining of “ideal types” as inherently problematic.
97 Notwithstanding their different approaches to adopter classification, both Rogers and Pannell et al. emphasise that adoption decisions are influenced by a range of social variables, including socioeconomic, personality and communication factors. Rogers (2003) argues that early adopters are more likely to have higher education levels, higher social status and larger farm sizes than later adopters, as well as being more empathic, less dogmatic, more rational, more intelligent, better able to deal with abstract thinking, less risk-averse, less fatalistic, more favourable toward science and more aspirational. He also argues that they are more likely to have greater levels of social participation, greater exposure to communication channels (both mass communication and interpersonal), more contact with change agents, more contact outside the local social system and hold a greater level of opinion leadership within their community. Pannell et al. (2011) cite many of the same factors, but tend to emphasise the complexities surrounding them, for example: - farm size may have an influence on the adoption of cropping practices but not tree-planting; - higher education levels may actually reduce adoption rates in cases where it is prudent to exercise caution; - a higher level of off-farm income may increase financial security but also reduce the time available for innovations that have high labour requirements; - a high level of risk-aversion may reduce adoption rates for innovations that increase risk but increase adoption rates for those that reduce risk; and - levels of trust and respect between farmers and change agents can increase adoption, while ethnic or cultural differences can act as barriers to diffusion.
3.3.2 Policy development and research strategies for rural adoption
The factors and processes described by Rogers (2003) and Pannell et al. (2011) have important implications for the selection and targeting of policy instruments around rural land use innovations such as bioenergy-based agroforestry. However, before selecting policy options, it is necessary to determine whether it is actually socially desirable to promote the innovation in question. Research into the diffusion of innovations often suffers from a pro-innovation bias, whereby researchers start out with the assumption that an innovation should be adopted (Rogers 2003). This can be
98 compounded by source-bias, which is the tendency for researchers to side with those who have introduced them to the case study (often those seeking to promote the innovation in question) and can in turn lead to individual-blame bias, which is the tendency to blame an individual for not adopting rather than to blame the innovation or the system for failing to meet the individual’s needs (Rogers 2003).
With regard to the case studies in this thesis, I need to be aware of my own potential biases resulting from the way I have come to be involved with these issues. The fact that I am actively looking for innovations that can address some of the sustainability issues discussed in Chapter 2 may lead to pro-innovation bias. Also, the fact that I have been introduced to the case study innovations by individuals who are passionate about promoting them may lead to source bias. Table 3.2 lists a number of approaches suggested by Rogers (2003) for overcoming these biases and their implications for this thesis.
Table 3.2: Approaches to address bias in diffusion research. Source: Rogers 2003)
Suggested approach (Rogers 2003) Implications for this thesis
Conduct research during rather than after the Applies to both case studies diffusion process
Undertake a comparative analysis of a successful and Not possible within the scope unsuccessful diffusion process within the same of this thesis and time available community
Acknowledge that rejection of an innovation may be Needs to be acknowledged rational and appropriate before and during case study research
Investigate the broader policy and research context Undertaken in Chapter 2. within which diffusion takes place to increase our Requires consideration in understanding of motivations for adoption Chapters 4-8
Base research on network analysis rather than solely Requires consideration in on the responses of individuals development of methodologies (Chapters 5-7)
99 Suggested approach (Rogers 2003) Implications for this thesis
Guard against accepting without question the Requires consideration in definition of diffusion problems presented by change development of methodologies agents (Chapters 5-7) and analysis (Chapter 8)
Involve all participants in the definition of a Requires consideration in diffusion problem (rather than just change agents) development of methodologies (Chapters 5-7)
Consider social and communication structural Requires consideration in variables, such as who controls the R&D system development of methodologies producing the innovations, which change agency (Chapters 5-7) and analysis diffuses them and for whose benefit (Chapter 8)
Taking into account the strategies for managing bias shown in Table 3.2, this thesis seeks to identify policy options that could be used to promote desirable innovations, while preventing the adoption of innovations with undesirable consequences. Drawing on their experiences with landholder adoption and government investment in environmental management, Pannell et al. (2009) have developed the Investment Framework for Environmental Resources (INFFER). The most relevant component of INFFER for this thesis is the Public: Private Benefits Framework (Pannell 2008), which is designed to assist policy-makers in selecting appropriate policy instruments relating to the adoption of land management actions. Pannell (2008) divides the key policy instruments relating to landholder adoption into five categories:
- Positive incentives to encourage adoption of desirable actions. Examples include subsidies, grants and tax breaks. - Negative incentives (i.e. disincentives) to discourage adoption of undesirable actions. Examples include regulations and taxes. - Extension to provide information that assists landholder decision-making. Examples include education programs, field days and demonstration sites. - Technology change to identify new land management options. Examples include basic research and strategies for development and deployment. - No action (i.e. informed inaction).
100 Under the Public: Private Benefits Framework, the decision to employ a particular policy instrument is based on the relationship between the public net benefit and private net benefit of the action in question. This requires all benefits and costs, both public and private, to be converted to a common unit, such as $/hectare/year. Pannell (2008) outlines the following general rules for policy selection under the Public: Private Benefits Framework:
- Positive incentives should only be used to promote actions with a positive public net benefit and should not be used for any action landholders would undertake anyway (i.e. any actions with a private net benefit) or any action with a private net cost greater than the public net benefit (as the incentives will end up costing more than the public benefit will be worth). - Extension can be used to encourage actions with a positive public net benefit, but should only be used if the action also has a positive private net benefit (otherwise the action will not be attractive to potential adopters). - Disincentives should be used to discourage actions that have a public net cost that outweighs the private net benefit to the individual undertaking them. However, if the private benefit outweighs the public cost, it may be more appropriate to take no action (i.e. allow the action to occur) or use a flexible disincentive (e.g. pollution tax) to pass the costs onto the private individual. - Technology change is an option in cases where current actions offer a public net benefit but carry a private net cost (in particular where the public benefit is not high enough to justify providing incentives). - If an action carries both public and private net costs, it should be unattractive to private landholders and thus no action is likely to be required. However, if misperceptions exist about the true private costs and benefits, extension or disincentives may be required to inform or discourage landholders. - In all cases, the possible policy action should be weighed against the option of undertaking no action (i.e. informed inaction).
Figure 3.4a provides a graphical representation of these general rules. Following these rules, a bioenergy-based agroforestry option that offered a positive net benefit both privately and publicly would fall in the upper right quadrant and would be best promoted through extension (e.g. education or demonstration). A bioenergy-based
101 agroforestry option that offered public benefits (e.g. salinity mitigation) but had a private cost (e.g. lower returns than current land use) would fall in the upper left quadrant, requiring either incentives for adoption or technology change to make it more attractive.
Pannell (2008) also goes beyond the basic policy matrix outlined in Figure 3.4a, taking into account economic factors such as learning costs for new practices, transaction costs in the delivery of incentive programs, lag times before benefits are realised and the scarcity of public funds. Pannell (2008) deals with lag time by applying discount rates to benefits or costs that occur in the future. This reflects the time value of money principle, under which a dollar earned or spent sooner is assumed to be worth more than a dollar later (Peirson, Brown, Easton, Howard & Pinder 2009). Scarcity of public funds is dealt with by assuming that funding will be restricted to projects that can provide a strong benefit: cost ratio. Figure 3.4b shows how the basic framework changes when assumptions relating to each of these factors are incorporated (Pannell 2008). The major effects are an increase in the area of “no action” at the expense of positive incentives, extension and negative incentives, with technology change shifting into a zone of higher public benefit and lower private cost.
102
Figure 3.4: Basic and modified versions of Pannell’s (2008) Public: Private Benefits Framework. Graph (a) represents the basic rules, while (b) shows a modified version incorporating lag time, learning and transaction costs and a benefit: cost ratio 2.
One significant insight arising from Pannell’s framework is that the level of private benefit is just as important an influence on policy choice as the level of public benefit.
103 The level of private benefit influences the likelihood of adoption, as well as whether or not public intervention is justified. The Public: Private Benefits Framework can incorporate a wide range of economic, environmental and social costs and benefits, but it requires them all to be converted to a common unit. Thus, it represents a “weak” sustainability paradigm in which environmental and social values can be traded-off against economic values (Pearce 1993). If $/ha is chosen as the common unit, environmental values may be assigned monetary values using methods such as contingent valuation, which involves surveying potential consumers about their willingness to pay for ecosystem services (Kolstad 2011). Pannell (2008) argues that this is simply a matter of making explicit the ranking processes that decision-makers already employ and that “relatively qualitative ratings” may be used rather than monetary values.
Issues relating to valuation and trade-offs are discussed further in the following section on ecological economics. Section 3.6 revisits the major factors and processes governing landholder adoption of innovations and seeks to incorporate them into an integrated policy framework for application to the case studies.
3.4 Ecological Economics
Ecological economics is an interdisciplinary field which brings together elements of economics, ecology, physics, philosophy and other disciplines12. Ecological economics addresses many of the key issues that are of interest within conventional (neoclassical) economics, such as the allocation of scarce resources to competing ends. However, it rejects many of the precepts that underlie neoclassical economics, with Lawn (2001, p. 5) arguing that neoclassical economists view the economy as “circular, self-feeding and self-renewing” in contrast to the ecological economics view of the economy as an “open subsystem of the larger ecosphere”. Applying an ecological economics approach to the development of bioenergy-based agroforestry has far-reaching implications in terms of goal-setting, managing trade-offs and the selection of policy instruments.
12 Considered to be transdisciplinary rather than interdisciplinary by some (e.g. Costanza et al. 1997a).
104 3.4.1 Fundamentals of ecological economics
While neoclassical economists are primarily concerned with the efficient allocation of scarce resources to competing ends, ecological economists such as Costanza et al. (1997a), Lawn (2001) and Daly and Farley (2003) consider sustainability and equity to be more important than efficiency. The prioritisation of these goals within ecological economics is as follows: 1. A sustainable economic scale; 2. An equitable distribution of wealth and income; and 3. An efficient allocation of resources.
The first goal flows from the basic premise that “the earth has a limited capacity for sustainably supporting people and their artifacts determined by combinations of resource limits and ecological thresholds” (Costanza et al. 1997a, ch. 2, p. 57). Daly and Farley (2003) focus on throughput as the key determinant of a sustainable economic scale. Throughput is the flow of resources from the ecosphere through the economy and back again as wastes, with the ultimate aim being a steady-state economy in which throughput no longer grows and human populations and stocks of capital are kept constant (Daly 1980). Costanza et al. (1997a) argues that the goal should not only relate to an economic scale that is sustainable but also one that is optimal, which is defined as the point where the marginal benefits of any further exchange of ecosystem services for production increases would be outweighed by the costs. Any increase in throughput that occurs beyond the optimal economic scale represents “uneconomic growth”, a concept that is not recognised in neoclassical economics.
The second goal of ecological economics, an equitable distribution of wealth and income, does not imply total equality, but rather that "the difference between rich and poor is limited to what is considered fair and just" (Lawn 2001, p. 104). Daly and Farley (2003) justify this goal with reference to a key concept of neoclassical economics, the law of diminishing marginal utility, which states that a gain is more valuable when one has relatively little than when one already has a lot. Daly and Farley (2003) argue that this law should apply not only to the individual, as it does in neoclassical economics, but also across society as well, meaning that a gain for
105 someone who has relatively little is more valuable to society than a gain for someone who already has a lot. Tools that can be used to promote equity include maximum and minimum limits on wealth and income, welfare payments, redistribution of capital through community-owned businesses and reform of global trade (Lawn 2001, Daly & Farley 2003).
The third goal, efficiency, is important within ecological economics but does not have the overriding dominance that it does in neoclassical economics. Ecological economists recognise the value of competitive markets in the efficient allocation of certain goods and services, but they reject many neoclassical assumptions about markets. These include the assumption that all externalities can be incorporated into market prices, that all public goods can be converted into private goods for trade within markets and that all humans seek to maximise their welfare solely through the accumulation of marketed goods and services (Hamilton 1997). Lawn (2001) argues that the concept of ecological economic efficiency (EEE) is more specific than the conventional notion of efficiency, relating to how efficiently limited means (i.e. resources available within the optimal macroeconomic scale) are allocated towards various competing ends that have been valued and ranked in an equitable manner.
Implementing the goals of ecological economics requires valuation systems that are broader than conventional economic measures such as Gross National Product (GNP), but that still allow comparisons and trade-offs between different forms of capital (e.g. natural and human) and different societal ends (e.g. needs versus wants). Natural capital is an economic metaphor for the stock of physical and biological natural resources (Farley & Gaddis 2007) and can be categorised based on its function as either source (e.g. supplying coal or timber), service (e.g. flood control or amenity) or sink (e.g. sequestering carbon dioxide)13. Ecological economists tend to reject the “weak” sustainability principle that human capital is an appropriate substitute for all natural capital, but they vary in how far they lean towards the “strong” sustainability view that human capital cannot be substituted for natural capital and that the entire
13 Another functional category sometimes used is site (Farley and Gaddis 2007) or Ricardian Land (Daly and Farley 2003), which refers to the functioning of land as a location for incident solar radiation or rainfall but does not include the soil, biota or other attributes of the land.
106 stock of natural capital must be preserved for future generations (Pearce 1993). The concept of “critical natural capital” has emerged as a compromise between these two positions (Brand 2009), representing the portion of natural capital “which is responsible for important environmental functions and which cannot be substituted in the provision of these functions by manufactured capital” (Ekins, Simon, Deutsch, Folke & De Groot 2003, p. 169). Conversely, if natural capital is non-critical, it may be traded off against other forms of capital provided that overall utility is maintained for future generations.
Ecological economists also vary in their views on the use of monetary valuation methods to value natural capital, such as contingent valuation, revealed preferences and replacement valuation. These valuation methods are primarily the tools of environmental economics, which is a branch of neoclassical economics concerned with internalising environmental externalities (Kolstad 2011). However, they have been used by some ecological economists, most notably Costanza et al. (1997b), who combined the results of over 100 published valuation studies covering 17 ecosystem services across 16 biomes to estimate that the total economic value of global ecosystem services at US$16-54 trillion annually (in 1994 US dollars). Such approaches can highlight the neglected value of natural capital, but have been criticised by other ecological economists14. In particular, many ecological economists object to the use of cost-benefit analyses based on monetary valuation to decide when natural capital should be conserved, restored or exchanged for human-made capital. Daly and Farley (2003) and Rees, Farley, Vesely and Groot (2007) put forward a number of reasons for opposing such cost-benefit analyses, including that: x Current market prices may be misleading if they are based on unsustainable levels of production; x Market prices are an undemocratic way of valuing public goods, as they are based on levels of demand that represent preferences weighted by income level; x Reducing non-market goods to a single price involves many hidden assumptions and subjective value-judgments;
14 See Ecological Economics 25 (1) 1998 for critiques of Costanza et al. (1997).
107 x Discount rates typically applied to short-term investment decisions are inappropriate for longer-term decisions about natural capital and for scenarios in which growth in throughput is limited; and x Monetary pricing implies complete substitutability between human and natural capital, which conflicts with the “strong” sustainability principle that the two forms of capital are complementary and have limited substitutability.
There is also debate within ecological economics with regard to valuing competing societal ends (e.g. nutrition, health, shelter, social inclusion). In general, ecological economists object to the neoclassical economics view that all values should be determined subjectively by individuals and instead argue that any meaningful notion of societal welfare or development requires that competing needs and wants be valued and ranked explicitly at a societal level15. Examples of such rankings can be found in alternative economic indices such as the Index of Sustainable Economic Welfare, the Genuine Progress Indicator or the Sustainable Net Benefit index (Lawn 2001). Each of these indicators employ a set of value-judgments to rank and weigh-up factors such as private consumption, health, crime, pollution, levels of inequality, stocks of natural and human capital and services from paid and unpaid labour based on their contribution to human welfare and ecological sustainability. Some ecological economists (e.g. Daly & Farley 2003, Lawn 2001) argue that this valuing and ranking of societal needs and wants can be done in an “objective” manner through the use of ethics16. The notion of objectivity can be problematic as it represents a social construct in itself (Albury 1983). Other authors such as Costanza et al. (1997a) refer instead to the need to replace valuation systems based on current individual preferences (“current value”) with those based on the preferences needed to assure long-term sustainability (“sustainable value”).
15 Lawn (2001) defines development as “an evolutionary process involving the qualitative improvement in the human condition over time” while Daly (2006) emphasises an element of efficiency in his description of development as an increase in utility per unit of throughput. 16 Lawn (2001) and Daly and Farley (2003) argue that ecological economics requires a “dogmatic belief” in objective value in order to rank ends and provide a meaningful measure of development.
108 3.4.2 Implications for policy and research
Ecological economists recommend many of the policy mechanisms that were discussed in Chapter 2, such as taxes, subsidies and market-based instruments, but their recommendations are influenced by the prioritisation of sustainable scale, then equity, then efficiency. A particular policy focus relates to elements of natural capital that produce non-excludable public goods (e.g. clean air, stable climate). Daly and Farley (2003) argue that such goods are likely to be over-used and under-produced by private individuals, as the full costs and/or benefits of such actions are often externalised (i.e. not borne by those causing the impacts and not incorporated into market prices). A number of tools may be used to internalise these “externalities” and prevent the overuse or under-production of public goods. Pigouvian subsidies (named after economist Arthur Pigou) may be used to reward individuals who produce or conserve public goods (e.g. clean air or water), while Pigouvian taxes may be applied to those who use or degrade them (e.g. polluters).
Tradable quota schemes (i.e. cap-and-trade) may be used to place limits on the scale of a particular activity (e.g. greenhouse gases emissions) and allow trading of quotas to distribute the costs efficiently across the economy. Strict regulatory limits can also be used to maintain a sustainable scale of activity, but are seen as less efficient than market-based measures such as cap-and-trade (Daly & Farley 2003).
Following the notion that sustainable scale is a higher priority goal than efficiency, Daly and Farley (2003) argue that tradable quota schemes are preferable to direct taxes or subsidies (e.g. carbon cap-and-trade would be preferable to a carbon tax). This is because tradable quota schemes reduce the risk of overshooting a sustainable scale and instead place the risk onto the permit prices that must be paid by polluters (and ultimately passed on to consumers). In practice, however, regulators and politicians will seek to balance the risk of overshooting pollution targets and the risk of high prices for pollution permits regardless of whether a tax or cap-and-trade approach is taken. These political trade-offs are clearly visible in the Australian Government’s development of a greenhouse gas cap-and-trade scheme, first as the Carbon Pollution Reduction Scheme (Department of Climate Change 2008) and now the Clean Energy
109 Future scheme due to commence in mid-2012 (Commonwealth of Australia 2011b). The planned scheme starts with a fixed-price phase (effectively a carbon tax) before transitioning into a cap-and-trade scheme where permit prices are set by supply and demand. However, the commencement of the cap-and-trade phase does not remove all risk of overshooting pollution goals, as there are exemptions for certain industries and consumers, opportunities to buy credits from other countries and the potential for future legislative changes to the emissions caps. Furthermore, if the chosen tax, subsidy, tradable quota or strict regulatory limit is poorly designed or does not align with public perceptions of fairness and equity, implementation may be more difficult and costly regardless of which option is theoretically most efficient.
Daly and Farley (2003) also make the point that it is often impossible to achieve the combined goals of scale, equity and efficiency using a single tool such as a tax, subsidy or quota. A tax or tradable quota may address scale and efficiency but not equity, while a measure to improve equity such as income redistribution will not in itself lead to a sustainable scale. According to Daly and Farley (2003), achieving all three goals requires an instrument to limit scale (e.g. a tax or quota), an instrument to deliver efficiency (e.g. a competitive market) and a measure to reduce disparities in income and wealth (e.g. welfare payments). This need for multiple tools has relevance for the “food versus fuel” debate, where a single action such as limiting biofuel production through land use restrictions may address scale but not result in the efficient use of land or address equity issues arising from global disparities in wealth and income.
The question of whether monetary valuation should be used to decide when natural capital should be conserved, restored or exchanged for human capital has important implications for this thesis, including the potential use of Pannell’s (2008) Public: Private Benefits Framework discussed in the previous section. Costanza (1997) and Pannell (2008) both make the argument that environmental and social factors are already valued implicitly and weighed-up against economic factors in decision- making, so formal valuation simply makes these processes explicit. However, the use of a common unit of measure for natural and human capital (whether monetary or otherwise) implies substitutability between these two types of capital, a position rejected by proponents of strong sustainability. The concept of critical natural capital,
110 which provides for compromise between positions of weak and strong sustainability, can also provide for compromise between advocates and opponents of monetary valuation.
Farley and Gaddis (2007) argue that when natural capital is relatively abundant, demand for it is elastic (i.e. large changes in its supply do not significantly affect its marginal value17) and decisions to maintain or restore it may appropriately be based on monetary valuation of natural capital. However, if natural capital stocks decline to critical levels (i.e. becomes critical natural capital), Farley and Gaddis argue that monetary valuation is no longer appropriate, as no further loss can be justified under any cost-benefit analysis. Figure 3.5 demonstrates Farley and Gaddis’ (2007) view that the marginal value of natural capital (the cost to society of losing one more unit) rises exponentially as it approaches a point of criticality. At the point of criticality, the marginal value of the natural capital becomes infinite, as it is “absolutely essential and has no substitutes” (Farley and Gaddis 2007, p. 23).
Figure 3.5: Hypothetical supply and demand curves for natural capital stocks. Redrawn from Farley and Gaddis 2007. Marginal value is expressed in terms of value to society rather than in monetary terms.
17 Marginal value refers to the cost to society of losing or gaining one more unit of natural capital.
111 According to Farley and Gaddis (2007), if a component of natural capital falls below the threshold of criticality, it must be restored, with the pertinent question no longer being whether to restore it, but rather how to do so in the most equitable and cost- effective manner. They also define an intermediate zone, where natural capital may be classed as “vulnerable” and demand may be highly inelastic (i.e. small changes in availability may have large effects on the marginal value of what remains). Trade-offs between vulnerable natural capital and other types of capital may be appropriate, but monetary valuation techniques are likely to encounter difficulties due to the non-linear relationship that exists between natural capital stocks and marginal value within this zone.
Pannell’s (2008) Public: Private Benefits Framework presented in section 3.3 is designed to facilitate trade-offs between public and private benefits, including determining when it may be appropriate to allow a loss of public natural capital in exchange for private profit. However, according to authors such as Ekins et al. (2003), Farley and Gaddis (2007) and Brand (2009), such a trade-off is not appropriate in situations where natural capital stocks are at or near critical levels. As such, an alternate version of Pannell’s framework has been developed for this thesis (Figure 3.6), taking into account Farley and Gaddis’ conceptualisation of critical natural capital (CNC).
Figure 3.6 is based on the notion that trade-offs between public and private benefits would no longer be appropriate in cases where stocks of natural capital have reached critical levels. At this point, the conservation and restoration of these stocks would become the over-riding factor in determining public benefit. Hence, the axes in Figure 3.6 are not based on a common unit such as $/ha/year and policy instrument selection is not based on whether private benefits exceed public benefits or vice versa. Rather, the choice of policy is based on two factors:
1. The impact that the activity under consideration is likely to have on critical natural capital (i.e. positive, negative or positive with side-effects); and 2. Thresholds for behavioural change by landholders or other managers of natural capital (e.g. whether or not incentives are required to stimulate action). Following Rogers (2003) and Pannell et al. (2011), these thresholds would
112 differ between landholders and be based on a combination of economic and non-economic factors.
Figure 3.6: Public: Private Benefits Framework adapted for use with CNC. The basic framework from Pannell (2008) has been modified for use in cases where public benefit relates to CNC. The red lines represent thresholds of policy selection.
The main difference between Figure 3.6 and Pannell’s original framework (Figure 3.4a) is the lack of diagonal lines in Figure 3.6, as these would indicate trade-offs between public and private benefits. Where both public net benefits (i.e. impact on critical natural capital) and private net benefits (economic and non-economic) are positive (top right-hand quadrant), adoption can be expected to occur with extension or even no action. However, in some cases, landholders may require a positive incentive to overcome learning costs or lag times and in others there may be side-effects that require targeted negative incentives (i.e. disincentives). Where public benefits are positive but private benefits are negative (top left-hand quadrant), positive incentives would be required (or technology change if considered more cost-effective). Where
113 public net benefits are negative (i.e. a loss of critical natural capital), disincentives may be required to prevent uptake of damaging practices. However, as highlighted by Pannell (2008), such measures are unlikely to be required if private benefits are negative or small relative to learning costs, as this already provides a barrier to uptake.
A critical question for this thesis is when to apply the type of framework advocated by Pannell (2008), based on monetary valuation and trade-offs, or an alternative framework such as that shown in Figure 3.6, based on the notion that critical natural capital has infinite value and no substitutes. This in turn raises the question of how to identify critical natural capital. De Groot (2003) argues that criticality depends on both the importance of the natural capital and the level of threat to which it is exposed. Brand (2009) distinguishes the following “domains” of criticality that have been employed in the literature and considers that natural capital is critical if it applies to at least one of these: 1. Socio-cultural (providing non-materialistic needs such as health and aesthetics) 2. Ecological (criteria such as naturalness, biodiversity, irreversibility or uniqueness) 3. Sustainability (critical to human well-being and unable to be substituted for human capital) 4. Ethical (e.g. responsibility to preserve sentient animals) 5. Economic (high-value needs that can be expressed in monetary terms) 6. Human survival (e.g. a stable climate or protection from floods)
Brand (2009) views criticality as operating in degrees (i.e. some capital is more critical than others). This contrasts with Farley and Gaddis’ (2007) view of critical natural capital as absolutely essential and having infinite value (as there cannot be differing degrees of infinite value), but could be compatible with their notion of vulnerable natural capital (which allows for differing degrees of vulnerability). Brand (2009) argues that the degree of criticality depends upon how significant the natural capital is within a relevant domain, whether it applies to more than one domain and how significant the different domains are considered to be in relation to one another. Each of these factors are subject to value-judgments, making it apparent that the concept of critical natural capital is “by no means rooted solely in the natural sciences but also in
114 the full array of social sciences and the humanities” (Brand 2009, p. 608). There is also enormous uncertainty in our understanding of the relationships between different elements of natural capital and the environment, social and economic outcomes they contribute to. This issue is revisited in section 3.5 in relation to resilience and adaptive management.
One of the most comprehensive approaches to identifying critical natural capital and incorporating it into decision-making is the CRITINC framework developed under a European Union research project (Ekins et al. 2003). This project concluded that it is not possible to identify critical natural capital as particular elements of natural capital, but rather that critical functions are created through the interaction of different elements of natural capital (Ekins 2003). To conserve these critical functions, the key characteristics of each element of natural capital must be conserved, as well as their capacity to interact.
The CRITINC framework involves seven basic steps (Ekins et al. 2003): 1. Identifying and categorising particular environmental functions for investigation. 2. Relating these functions back to the elements of natural capital from which they emanate (climate, geology, vegetation, hydrology etc). 3. Developing impact matrices that explore how human impacts on elements of natural capital (e.g. resource depletion, pollution, ecosystem imbalance) are affecting the functions under investigation. 4. Developing sustainability standards to keep these functions above critical levels. 5. Calculating “sustainability gaps” (or SGAPs), which represent the difference between the current state of the natural capital (or current pressure being placed on it) and the sustainability standard. 6. Describing the social or economic aspirations that are causing threats or pressures and looking for alternative ways of meeting them. 7. Applying a decision-analysis system to give insights into the implications of restoring CNC and closing the SGAP.
115 The CRITINC framework has been applied to a variety of European case studies, including air quality in Milan, river health in the UK and France, German forests, Dutch wetlands and urban development in Sweden (Ekins 2003). The promotion of sustainability standards under the CRITINC framework creates obvious parallels with the standards explored in Chapter 2 in relation to forestry (FSC and AFS), agriculture (SAN and RSPO) and bioenergy production (UK RTFO). One key difference is that the CRITINC standards are not determined at the scale of an individual land- management unit, but rather at the scale of the environmental functions they seek to conserve. This approach has parallels with the concept of multifunctionality, which recognises that a single land unit is capable of simultaneously producing multiple joint outputs that operate on differing scales. Furthermore, CRITINC does not assign responsibility for conservation or restoration of natural capital to individual land managers. Rather, it identifies what degree of conservation or restoration of natural capital is required, what options might be available to achieve this and what the implications are of different courses of action.
The issues identified around critical natural capital are revisited in section 3.6 in pursuit of an integrated framework for use in the case studies.
3.5 Resilience within adaptive complex systems
Over recent decades, the complexity of ecological, social and economic systems has increasingly been recognised through a focus on concepts such as resilience and adaptive capacity. These approaches have significant ramifications for the ways in which concepts such as sustainability, critical natural capital and adaptive management may be employed within the case studies of this thesis. The concepts of resilience and adaptive management first rose to prominence within the field of ecology, where systems approaches began to be employed in the 1970s as an alternative to the dominant paradigms based around stability and linear relationships (e.g. Holling 1973, Holling, Bazykin, Bunnell, Clark, Gallopin, Gross et al. 1978). However, these notions have since been applied to socio-economic systems as well, with resilience (or lack thereof) used to explain events such as the Great Depression and the collapse of the Soviet Union (Levin, Barrett, Aniyar, Baumol, Bliss, Bolin et al. 1998, Berkes 2007).
116 3.5.1 Resilience principles
Holling (1973, pp. 14-15) differentiates between stability, which is the “the ability of a system to return to an equilibrium state after a temporary disturbance”, and resilience, which is “a measure of the persistence of systems and of their ability to absorb change and disturbance and still maintain the same relationships between populations or state variables”. Thus, a system can be highly unstable in that it never seems to return to equilibrium, but highly resilient because it can absorb variability without fundamental relationships breaking down (Holling 1973). These ideas can be seen in the approach taken under the CRITINC framework discussed in the previous section, whereby conserving CNC does not involve maintaining stable quantities of particular elements of natural capital, but rather maintaining the interactions between different elements that create critical functions (Ekins 2003).
The concept of resilience recognises that systems often show complex non-linear relationships, characterised by feedback effects, threshold dynamics and multiple domains of stability. Feedback effects produce non-linear changes by either amplifying the initial disturbance (positive feedback) or reducing it (negative feedback). Threshold effects are also non-linear, with increasing amounts of disturbance able to be absorbed by a system without significant changes in state until a threshold is reached and a fundamental shift occurs. A system may show a high level of stability when disturbances do not exceed threshold levels (i.e. conditions quickly return to an equilibrium after disturbance), but once such thresholds are exceeded the system may switch to an entirely new state with a new domain of stability. Levin et al. (1998) liken this to a ball being pushed up the sides of a valley - when disturbances are small the ball will continually return to the valley floor but if sufficient force is applied the ball will move up the valley side, over the ridge and into the next valley, where it may remain in a stable state until another force of sufficient magnitude is able to shift it.
As an example of a resilient yet unstable ecosystem, Holling (1973) cites the spruce-fir forests of eastern Canada, which feature long periods of increasing tree density (especially of fir) followed by intense but short-lived outbreaks of budworms (which affect fir most severely and reduce densities). Thus, while the tree densities and insect
117 populations in the forests show very little stability (i.e. they don’t hover closely around an equilibrium), the system overall shows enormous resilience (i.e. a persistent long- term relationship between trees and budworms). Freshwater lake systems are also often cited in the resilience literature as they can exhibit multiple stable states with differing degrees of resilience (e.g. Carpenter & Cottingham 1997, Ibelings, Portielje, Lammens, Noordhuis, Berg, Joosse et al. 2007, Brand 2009), switching for example from a state of low turbidity and high vegetation to one of high turbidity and low vegetation.
Gunderson and Holling (2002a) argue that systems with high stability that are resistant to disturbance may in fact have smaller domains of stability and as a result be less resilient to major shocks. Such systems may be able to resist most disturbances, but once they are disturbed they only need to shift a by a small degree to undergo a fundamental change in state. Gunderson and Holling (2002a) sees this process as part of an adaptive cycle, whereby systems build up during an exploitation phase (r) then enter a conservation phase (K), which features high system stability but low resilience. This lack of resilience, combined with some form of disturbance, can in turn lead to a release phase (ȍ), which is then followed by a reorganisation of resources (Į) and a return to the start of the cycle. Figure 3.7 conveys this adaptive cycle graphically, including the way that resilience changes as the cycle progresses.
Figure 3.7: Representations of an adaptive cycle. A 2-dimensional version is shown on the left (Gunderson & Holling 2002b), with 3-dimensional version on the right (Allison & Hobbs. 2004).
118 Holling, Gunderson and Peterson (2002) have coined the term panarchy (from the Greek god Pan representing the unpredictable and elemental forces of nature) to describe the way that adaptive cycles may be nested within one another. Cycles based around smaller scales of time and space can influence those above them through a process of revolt, whereby dynamic change processes such as fire emerge during the release phase (ȍ) of the lower cycle to affect the conservation phase of the cycle above. Conversely, cycles above can influence those below through a process of remember, with qualities of the conservation phase (K) of the above cycle (e.g. seedbanks) passing downwards to a lower cycle which is in a reorganisation phase (Holling et al. 2002). This relationship is represented in Figure 3.8.
Figure 3.8: Nesting of adaptive cycles within the panarchy. Lower cycles can influence those above through a process of revolt and higher cycles can influence those below through a process of remember. Source: Holling et al. (2002).
The concept of resilience within adaptive complex systems has significant implications for notions of sustainability. It is clear that sustainability cannot be equated simply with maintaining stability, as instability may in fact be a pre-requisite for the long-term maintenance of certain system interactions. However, sustainability should also not be equated simply with resilience either. As discussed in Chapter 1, sustainability involves goal-setting, value-judgments and equity considerations. Resilience makes no
119 such distinctions, “preserving ecologically or socially undesirable situations as well as desirable ones” (Levin et al. 1998, p. 225). Indeed, Nadasdy (2007) argues that projects to enhance resilience often fail to ask whether the system they are seeking to maintain is in fact the most desirable one, such as asking marginalised indigenous people to help enhance the resilience of the very systems in which they are marginalised.
Rather than equating sustainability with resilience, Holling et al. (2002) argue that “sustainability is the capacity to create, test and maintain adaptive capacity”. Adaptive capacity is defined by Armitage (2007, p. 67) as "the capability of a system to adapt to change and respond to disturbance yet still retain essential self-organizing structure, function and feedback mechanisms". Armitage cites four dimensions of adaptive capacity: 1) learning to live with uncertainty and change; 2) supporting and promoting diversity (including recognising the importance of redundancy); 3) combining different types of knowledge (e.g. western scientific and local/indigenous); and 4) maintaining opportunities for self-organisation of social, institutional and ecological systems in the direction of sustainability
While enhancing adaptive capacity may enable a system to be more resilient, system actors also have to make a range of value-judgments, such as whether they actually want the system to be resilient, which functions of the system they consider critical and which functions can be foregone as part of a process of adaptation. Taking the global agricultural trade system as an example, different perspectives may exist regarding which functions of the system should be made resilient. The ability of the system to provide basic nutrition for the world’s poor and the ability of the system to provide acceptable incomes for farmers are two such functions that can come into conflict.
Adaptive management, discussed in section 3.2 in relation to conservation through sustainable use (CSU) and the ecosystem approach, is required if one wishes to actively manage for resilience. Adaptive management recognises that uncertainty is pervasive within the natural sciences and that surprises must be expected. Management
120 actions are seen as purposeful experiments to learn about the nature of systems, requiring carefully designed monitoring, review and feedback processes (Stankey, Clark & Bormann 2005). Associated terms include adaptive co-management (e.g Ruitenbeek & Cartier 2001, Berkes 2007), which focuses on cooperation or collaboration with a diverse range of stakeholders, and adaptive governance, which refers to the creation of polycentric institutional structures capable of delivering adaptive management for socio-ecological systems that operate across multiple scales and involve pervasive uncertainty (Olsson, Gunderson, Carpenter, Ryan, Lebel, Folke et al. 2006).
3.5.2 Implications for policy and research
The concepts of resilience, adaptive capacity and panarchies have implications for some of the other frameworks explored in this chapter as well as for the selection of policy instruments. Resilience theory has parallels with the concept of multifunctionality, which also recognises the value of having a diversity of outputs rather than simply focusing on the efficiency of producing a single output such as food or fuel. Simplification within agricultural ecosystems may result in systems that are highly efficient at producing particular outputs such as food or even habitat for threatened species (as argued by Phalan et al. 2011), but may also result in a loss of resilience due to a lack of diversity and redundancy that can be drawn upon in times of stress (Brock et al. 2002).
Resilience theory also has implications for rural adoption, as behavioural change can exhibit the same kind of non-linear system dynamics as ecosystems, featuring shifts between alternate stable land use states such as cropping, grazing or agroforestry. Thus, when assessing private benefits derived from changes in land use practice and weighing these against public benefits, the critical factor to measure may not be the incremental dollar value of such benefits but rather how likely such benefits are to shift a landholder across a tipping point towards the new practice. Such thresholds will vary from landholder to landholder, depending on financial and other circumstances. Similarly, social incentives such as maintaining cultural identity may exhibit tipping points, with values changing as a critical mass of change is reached (e.g. the cultural
121 value attached to being a grazier changing as a critical mass of landholders switch to agroforestry).
Brand (2009) also draws a connection between ecological resilience and the concept of critical natural capital used in ecological economics, suggesting that the focus on thresholds within resilience theory may also be useful in assessing the criticality of natural capital in some (but not all) ecosystems. This builds on the arguments of De Groot (2003) that the level of threat is an important factor in determining criticality. Brand (2009) suggests that the closer a system is to a threshold of change, the greater the risk to which is it exposed. Threshold approaches often seek to identify “slow” variables (e.g. woody plant abundance within a rangeland or nutrient levels in a shallow lake) that exert control over state-switching behaviour. A review of historic disturbances can identify disturbances of concern, which can then be matched to thresholds of concern and in turn to slow variables of concern (Resilience Alliance 2007).
3.6 Development of an integrated sustainability policy framework
The ultimate aim of this chapter is to identify frameworks and methodologies that can be applied to the two case studies in Chapters 4-8. The conceptual frameworks of multifunctionality, conservation through sustainable use (CSU), adoption theory, ecological economics and resilience theory each offer important principles and tools for this case study analysis. However, a unifying sustainability framework is required that is capable of integrating the key issues arising at each case study site and providing recommendations for policy-makers. Three existing sustainability policy frameworks from Dovers (2005), Clark (2002) and Diesendorf (2000) are summarised in Figure 3.9.
122
Dovers (2005) Framework Clark (2002) Framework Diesendorf (2000) Framework
Three Principal Additional Framework for Sustainability Four Basic Stages Dimensions Elements 1. Problem-Framing General Broad Ethical - Respect nature -Define problem s & goals Social Process Standpoint Principles - Respect people Elements Identify the -Topicality & existing policy - Participants - Be precautionary (in policy - Perspectives standpoint of -Systems monitoring participant or process) - Situations -Changes & causes observer Broad - Conserve biodiversity • Coordination - Base values Goals & climate -Risk & uncertainty & integration - Strategies - Conserve critical capital Public Multiple methods 2. Policy-Framing • - Outcomes - Well-being, equity & diversity Used to gather, -Guiding policy principles participation - Effects interpret and -General policy statement • Description & Measurable objectives or indicators communication integrate -Definition of policy goals Decision information • Transparency Process 3. Policy & accountability Sustainable Development Implementation - Intelligence Moral goal Implementation
123 - Promotion guiding problem- -Policy instrument selection (in evaluation) 1. Present a guiding vision, - Prescription solving goals & scenarios -Implementation strategies • Persistence - Invocation - Democracy -Institutional requirements • Purpose 2. Develop sustainability policy - Human rights -Establish compliance • Information- - Application in all sectors, at all levels, & monitoring richness & - Appraisal - Security with all types of instruments - Termination information- 3. Create supportive 4. Policy Monitoring sensitivity & Evaluation environments • Inclusiveness Problem Orientation -Monitoring & data capture • Flexibility - Clarifying goals 4. Strengthen community action -Mandated evaluation & - Describing trends & conditions 5. Develop personal and review process cycle of - Projecting developments organisational skills -Extension, adaptation or learning Inventing, evaluating and selecting cessation of policy/goals - 6. Reorient the system towards alternatives sustainability
Figure 3.9: Comparison of sustainability policy frameworks from Dovers (2005), Clark (2002) and Diesendorf (2000).
Dovers’ (2005) framework for analysing and prescribing sustainability policy attempts to strike a balance between a “rational” approach, being stepwise and scientific, and an “incremental” approach, which involves smaller steps that recognise complexity and political realities. He makes the distinction between a sustainability issue (e.g. climate change, biodiversity loss, erosion) and a policy problem (i.e. how to respond to an identified issue), stating that “issues are for being concerned about and debating, problems are for resolving” (Dovers 2005, pp. 41-42). Dovers’ framework consists of four basic stages: problem-framing, policy-framing, policy implementation and monitoring and evaluation. There are also a number of over-arching general elements that cut across the stages, such as coordination, public participation and flexibility. The four stages are not strictly linear, as the general elements feed into each stage and the whole process is circular, with monitoring and evaluation serving to inform further problem-framing, policy-framing and policy implementation. Through this cyclical arrangement, Dovers’ framework incorporates the principles of adaptive management that feature prominently in the ecosystem approach (section 3.2) and resilience theory (section 3.5).
Clark’s (2002) framework is not arranged according to a set of sequential stages, but nonetheless shares many features with Dovers’ framework. The three principal dimensions of Clark’s framework are social process, decision process and problem orientation, with each dimension consisting of a series of factors that need to be taken into account in policy-making. There are also three additional elements that apply to policy-making and analysis. Firstly, the standpoint of the participant or observer in policy-making must be established. Secondly, multiple methods should be employed in gathering, interpreting and integrating information. Thirdly, an over-arching moral goal should guide problem-solving, based around democracy and human rights.
Diesendorf’s (2000) framework has some elements that are shared with Clark’s framework (such as a set of over-arching ethical principles), some that are shared with Dovers’ (a set of numbered stages that are revisited in a cyclical manner) and some that are common amongst all three (the setting of goals and targets, community participation and analysis of policy alternatives and instruments). Two notable elements of Diesendorf’s framework are the development of an initial vision of desired
124 sustainability outcomes to guide policy-making (step 1) and a focus on re-orienting organisational structures and other institutional factors towards sustainability (steps 3 and 6).
All three frameworks recognise the setting of goals as a key element of sustainability and recognise that different conceptualisations of sustainability will result in different goals. Some elements of goal-setting identified in the different frameworks may be usefully combined, such as Clark’s focus on the standpoint of the participant and Diesendorf’s focus on the development of a guiding vision. For example, I need to recognise that my initial standpoint coming into this thesis has been to view revegetation of degraded or vulnerable landscapes as a high priority and to see bioenergy production as a potential driver of such revegetation. Others may have visions based around different priorities, such as the opportunity to reinvigorate a regional economy, to enhance energy security or to mitigate climate change through the production of renewable energy. While each of these visions may be consistent with sustainable development, recognising the differences between them and understanding where trade-offs may be required is an important step towards the development of policy goals.
While each of the three frameworks shown in Figure 3.9 provides a viable pathway for the development of sustainability policy, a modified policy framework has been developed for use in this thesis. This framework, outlined in Table 3.3, most closely resembles Dovers’ framework, but also incorporates elements of Clark’s and Diesendorf’s frameworks and reflects the key concepts from the five conceptual frameworks explored in this chapter. The most prominent deviations from Dovers’ framework are the creation of a separate stage for policy evaluation (included under policy implementation by Dovers) and the combining of implementation and monitoring into a single stage. These changes have been made to reflect the importance of fully evaluating the likely impacts of policy interventions before deciding on an implementation pathway and the importance of commencing policy implementation and monitoring simultaneously.
125 Table 3.3: Policy framework developed for application to the thesis case studies. Stage Key Elements Relevant Concepts from Conceptual Where Addressed in Thesis Frameworks 1. Problem- - Identify social goals, Multifunctionality – joint delivery of - Chapter 2: Literature Review framing/ topicality of issues, outputs and impacts (global scale) orientation existing conditions, trends, CSU – conservation & use synergies - Chapter 4: Introduction to Case causes & existing policy Adoption - landholder characteristics and Studies (regional scale) - Identify potential synergies motivations - Chapter 5: Social Analysis and trade-offs Ecological economics – trade-offs between - Chapter 6: Economic Analysis - Project potential scenarios natural & human capital require caution - Chapter 7: Environmental Analysis and visions Resilience – feedbacks, thresholds & - Chapter 8: Discussion and Policy 126 - Define policy problems adaptive cycles Development 2. Policy-framing Select: Multifunctionality – policy must include - Chapter 2: Literature Review - policy principles scale-specific or local criteria (global scale) - policy goals CSU - ecosystem approach/Addis Ababa - Chapter 4: Introduction to Case principles Studies (regional scale) Adoption - INFFER policy selection rules - Chapter 8: Discussion and Policy Ecological economics – scale, equity & Development efficiency Resilience - living with uncertainty, valuing diversity & redundancy
Stage Key Elements Relevant Concepts from Conceptual Where Addressed in Thesis Frameworks 3. Policy - Identify policy options Multifunctionality – joint delivery of - Chapter 5: Social Analysis evaluation - Assess policy impacts and outputs and impacts - Chapter 6: Economic Analysis interactions Adoption - relative advantage & trialability Chapter 7: Environmental Analysis - Select policy measures for CSU - ecosystem approach/Addis Ababa - Chapter 8: Discussion and Policy implementation principles Development Ecological economics – consider impacts on critical natural capital, multiple goals require multiple policy measures
127 4. Implementation - Implement policy CSU – manage at appropriate scales, - Chapter 8: Discussion and Policy through measures incorporate multiple types of knowledge Development adaptive - Re-orient Adoption - monitor diffusion of management systems/structures innovations - Identify key parameters Resilience - identify key thresholds and and commence monitoring variables for monitoring - Review & revisit stages 1- 4
Stage 1 of the framework (problem-framing/orientation) is a combination of Dovers’ problem-framing stage and Clark’s problem-orientation dimension, with several elements that also overlap with the early stages of Diesendorf’s framework. Stage 1 involves an assessment of social goals, conditions, trends, causes and existing policy. The emphasis on potential synergies and trade-offs in Table 3.3 is a result of the focus on these interactions under multifunctionality (joint delivery of outputs), CSU (synergies between conservation and use), ecological economics (trade-offs between human and natural capital) and resilience theory (feedbacks, thresholds). Stage 1 also involves identification of potential future scenarios and developments, incorporating Diesendorf’s (2000) focus on having a vision of sustainability. Following Clark (2002), the identification of goals and visions should include the standpoint of the researchers or policy-makers undertaking the assessment. This stage culminates with the definition of policy problems to be resolved in the remaining stages of the framework.
Stage 2 (policy-framing) closely follows Dovers’ policy-framing stage and involves the selection of policy principles and goals. Policy goals are directly related to the policy problems identified in Stage 1. Policy principles, such as inter-generational equity, the precautionary principle and polluter-pays, affect how policies are structured and how the costs, benefits and risks are distributed.
Stage 3 (policy evaluation) involves the identification, assessment and selection of policy options. Policy instruments may be classed according to the institutional structures that they operate under (e.g. statute law, market mechanisms), as preferred by Dovers (2005), or by the direction of change they are designed to promote, as preferred by Pannell (2008) in section 3.3. Table 3.4 compares these two approaches and provides examples of policy instruments for each category. As Pannell’s framework is focused more narrowly on policy intervention to deliver land management change, it does not provide a direct equivalent for some of Dovers’ broader categories relating to institutional change and intergovernmental agreements.
128 Table 3.4: Policy instrument categories from Dovers (2005) and Pannell (2008). Dovers’ (2005) policy Corresponding Examples instrument classes instrument categories from Pannell (2008)
1. Research and x Technology change x Basic research (general) development x Applied research (specific)
2. Creating new or x Extension x Sustainability indicators improving existing x State of the environment communication reporting and information x Community-based monitoring flows
3. Education and x Extension x Education may be public, training targeted or formal x Training (skills development)
4. Consultative x Extension x Mediation, negotiation
5. Agreements and x Intergovernmental agreements conventions x Conventions, treaties
6. Statute law x Disincentives x Prohibit or limit damaging x Incentives practices (disincentive) x Protect property rights (incentive)
7. Common law x Incentives x Lawsuits for negligence, nuisance
8. Covenants on title x Disincentives x Prohibit damaging land use x Incentives options (disincentive) x Provide stewardship payments (incentive)
9. Assessment x Extension x Review of effects procedures x Environmental impact assessment x Life-cycle assessment
129 Dovers’ (2005) policy Corresponding Examples instrument classes instrument categories from Pannell (2008)
10. Self-regulation x Disincentives x Code of practice with penalties x Incentives for non-compliance (disincentive) x Industry standards that facilitate access to new markets (incentive)
11. Community x Extension x Policy development involvement participation x Community management
12. Market x Disincentives x Taxes, charges, fines mechanisms x Incentives (disincentives) x Subsidies (incentives) x Tradable quotas (both)
13. Institutional or x New or revised settings to organisational enable policy implementation change
14. Change other x Remove distorting subsidies or policies conflicting policies
15. Inaction x No action x Informed inaction, with commitment to reconsider over time
Stage 4 (implementation through adaptive management) combines implementation and monitoring under a single stage in order to highlight the importance of commencing these actions simultaneously. It includes the selection of appropriate institutional structures to implement the chosen policy measures and recognises Diesendorf’s (2000) goal of re-orienting the system towards sustainability. Policy review could be separated from the broader concept of adaptive management into a separate sixth stage or viewed as an overarching element along the lines of Diesendorf’s “cycle of learning”.
130 The significance the five conceptual frameworks explored in this chapter varies across the four stages of the policy framework outlines in Table 3.3. Multifunctionality is most relevant to the first three stages, particularly its focus on identifying joint outputs and the principle that policy must recognise the different scales at which outputs are delivered. CSU is relevant to all stages, particularly the principles outlined in the ecosystem approach and Addis Ababa guidelines relating to inclusiveness and equity, integration of economic and environmental goals and adaptive management at appropriate scales. Adoption theory assists with understanding landholder motivations (Stage 1), applying policy development rules (Stage 2), assessing policy tools against adoption factors such as relative advantage and trialability (Stage 3) and monitoring the diffusion of innovations (Stage 4). Ecological economics provides a set of key concepts for Stages 1-3, including the three goals of scale, equity and efficiency and the principle of non-substitutability of critical natural capital. Finally, resilience theory, with its focus on feedbacks, thresholds and adaptive cycles is influential on Stage 1 (identifying trends and interactions), Stage 2 (dealing with uncertainty) and Stage 4 (identifying key variables for monitoring).
Some of the interactions between the different conceptual frameworks also have implications for the policy framework. For example, while ecological economists are often sceptical of trade-offs between natural and human capital, especially where critical natural capital is involved, the INFFER policy selection rules (Pannell 2008) are designed to facilitate such trade-offs. This conflict has implications for the selection of policy principles (Stage 3), the assessment of policy impacts (Stage 4) and the selection of policy instruments (Stage 4).
There is also an important connection between CSU and critical natural capital in relation to policy selection. A CSU approach requires that certain conservation goals be assigned an over-arching priority within a management system so that these goals can then be targeted using an appropriate sustainable use option. The concept of critical natural capital may help to define the circumstances in which it may be justified to prioritise the conservation of certain elements of natural capital. Farley and Gaddis (2007) argue that, when stocks of natural capital fall below a level of criticality, they must be restored and the only consideration should be how to do so in an
131 equitable and cost-effective manner. In cases where natural capital is below a critical level (or even at a “vulnerable” level where its marginal value is high), a CSU approach may provide a cost-effective and equitable option for restoration.
The final column of Table 3.3 highlights how the different stages of the framework align with the structure of this thesis. Chapter 8 is designed to follow the framework in full, drawing on the background information and case study results presented Chapters 1-7. Due to the need for the case studies to obtain multiple types of information simultaneously, Chapters 4-7 do not correspond to individual stages of the framework. Rather, Chapter 4 introduces the two case studies and provides regional baseline information. This feeds into Stages 1 and 2 of the framework and complements the global perspectives presented in Chapter 2. The social, economic and environmental analyses presented in Chapters 5, 6 and 7 are designed to obtain information that is relevant for framing policy problems (Stage 1) as well as evaluating potential policy impacts (Stage 3). Chapter 8 then provides a summary of each stage and presents key recommendations on the selection of policy goals, principles, instruments and implementation strategies. This approach represents a compromise between the idealised order of activities outlined in Table 3.3 and the practicalities of undertaking research within a limited timeframe and budget.
3.7 Conclusion
Each of the five conceptual frameworks discussed in this chapter provide useful guidance for approaching the case studies in Chapters 4-8. Multifunctionality and CSU provide ways of identifying and managing synergies between different goals and policy measures across the revegetation, plantation and bioenergy sectors. Adoption theory assists with understanding the key factors driving landholder decision-making and the policy measures that could support those processes. Ecological economics and resilience theory both help to manage trade-offs within complex systems by identifying priorities, tipping points and critical interactions. As shown in the sustainability policy framework presented in section 3.6, each of the five conceptual frameworks provide valuable guidance on the selection of policy goals, principles and instruments.
132 This chapter also presents some original contributions towards the further development of the five conceptual frameworks and the development of sustainability policy around bioenergy-based revegetation. Section 3.2 takes an expansive approach to the concept of Conservation through Sustainable Use (CSU), moving beyond the maintenance of “wild” or “natural” ecosystems to apply key CSU principles to the establishment of revegetated ecosystems that will be subject to future sustainable harvest. Section 3.4 adapts Pannell’s (2008) Public: Private Benefits Framework for use with the ecological economics concept of Critical Natural Capital (CNC), where trade-offs between natural and human capital may not be appropriate. Section 3.6 presents a modified sustainability policy framework that draws heavily on Dovers (2005) but also includes elements of Clark’s (2002) and Diesendorf’s (2000) frameworks, as well as incorporating elements of the five conceptual frameworks presented in sections 3.1- 3.5.
The following chapter moves from broad-scale frameworks into specific regional issues relating to revegetation, agroforestry and bioenergy at the two case study sites selected for the NSW Central West. This detailed regional focus not only provides an opportunity to identify potential policy solutions for these two sites, but also to test the value of the sustainability policy framework presented in this chapter.
133 Chapter 4: Introduction to Case Studies
The two case studies explored in this thesis are both located in New South Wales (NSW), Australia (Figure 4.1). The first is centred on the town of Condobolin, in the Lachlan Shire, while the second encompasses a larger area around Lithgow, Oberon, Bathurst and Mudgee, known as the NSW Central Tablelands. Both case study sites are commonly included in the broader region known as the NSW Central West.
Figure 4.1: Location of case study sites in NSW.
The proximity of the two sites and their location within the same state results in a number of similarities, including regulatory context, government incentive programs and certain social and environmental issues. However, there are also a number of important differences between the two sites, including topography, climate, land use patterns, industry development, demographics and local environmental priorities. The Central Tablelands is an existing high rainfall plantation forestry area where bioenergy production could provide a new plantation option. In contrast, Condobolin is a lower rainfall wheat-sheep district with no existing plantation sector.
134 Background information is presented for Condobolin and the Central Tablelands in sections 4.1 and 4.2 respectively. These background sections explain the social, environmental and economic context for each case study and the extent of bioenergy development to date. Section 4.3 brings the two case studies back together to explore the specific policy measures affecting revegetation, agroforestry and bioenergy in the NSW Central West. Section 4.4 then defines the research tasks to be undertaken in Chapters 5-7 by identifying an over-arching research goal and a set of key research questions for the case studies.
In relation to the policy framework outlined at the end of Chapter 3, the information provided in this chapter is primarily relevant to Stage 1 (problem-framing/ orientation). In particular, this chapter covers many of the problem-framing elements identified by Dovers (2005), such as social goals, topical sustainability issues, problematic changes and causes, key risks, sources of uncertainty and the policy environment. Some of the material presented is also relevant to Stage 2 (policy-framing), particularly the identification of existing policy goals and principles.
4.1 Background to the Condobolin Case Study
Condobolin lies on the Lachlan River, close to the geographic centre of NSW. It is the administrative centre for the Lachlan Shire, which covers an area of 15,000 square kilometers. As of the 2006 census, Condobolin had a population of 2849, with 6669 people across the Lachlan Shire as a whole (Australian Bureau of Statistics 2010). The district surrounding Condobolin has low relief, with red and brown earths forming the dominant soil type (Abadi et al. 2006). Farming systems have traditionally been based on a combination of dryland cropping of high-protein wheat and sheep grazing for wool. However, crop rotations commonly feature barley as well and there has been a shift towards sheep and cattle for meat production following the removal of the wool floor price in the early 1990s (Patton & Mullen 2001).
Figure 4.2 shows the dominance of cropping and grazing in the district and the highly fragmented nature of the remaining native vegetation. However, the map does not reflect the full complexity of land use allocation in the district, as a range of
135 crop/pasture rotations are employed and land allocation is also influenced by seasonal outlook and market conditions (Patton & Mullen 2001). Some irrigated cropping occurs in areas near the Lachlan River when water allocations are available.
Patton and Mullen (2001) report that farms in the region are generally 90% cleared, with woody vegetation found only in shelterbelts and hilly portions. Many of the larger blocks of native vegetation around Condobolin are State Forests that have been retained for the production of white cypress, Callitris glaucophylla, for which Condobolin is an important milling centre (Forests NSW 2008b). Farm forestry is not common in the Condobolin area, with URS Forestry (2008a) excluding the region from its assessment of farm forestry in Australia and the Natural Resources Commission (2010, p. 12) considering potential agroforestry development in the region to be a “long-term proposition”.
Patton and Mullen (2001) report that farm sizes in the Lachlan Shire averaged around 2500 ha in 1999, with a large difference between the average property size to the east of Condobolin (1500 ha) compared to the west (5000 ha). The NSW Western Division starts about 50 km west of Condobolin, with this boundary traditionally marking a transition from freehold cropping and grazing properties in the east to leasehold lands in the west that are used predominantly for grazing.
136 137
Figure 4.2: Land uses around Condobolin. Source: LUMAP (NSW Government 2007) . The large “urban” block northeast of Condobolin is the Condobolin Agricultural Research Station. The top and left edges of the map mark the western boundary of LUMAP data for NSW.
4.1.1 Economic, social and environmental trends
Condobolin receives a mean annual rainfall of 460 mm, spread fairly evenly throughout the year (Bureau of Meteorology 2012a). Although the summer months receive slighter higher rainfall on average than the winter months, wheat is grown under a winter cropping regime in order to take advantage of the lower evaporation rates and more even rainfall at that time of year. On average, wheat makes up around 80% of the total winter grain harvest by tonnage for the Condobolin district (NSW Trade & Investment 2011). The past decade has seen extensive drought, largely due to El Niño events in 2002/03, 2006/07 and, to a lesser extent, 2009/10 (Bureau of Meteorology 2011a). Annual rainfall was below the long-term average for eight of the nine years between 2001 and 2009, with significant impacts on cropping success (Figure 4.3).
Figure 4.3: Annual rainfall and wheat harvests for the Condobolin district 1993- 2010. Sources: Bureau of Meteorology (2012), NSW Trade & Investment (2011).
Rainfall and wheat-growing conditions improved markedly across the Condobolin district in 2010 and 2011, under the influence of one of the strongest La Niña events on record (Bureau of Meteorology 2011b). As shown in Figure 4.3, both total rainfall and total wheat harvest in 2010 were at their highest levels for at least 18 years. This
138 change in agricultural fortunes is an important factor for the case study research, as stakeholder interviews ranged from December 2009, when the drought was still in full swing, to October 2010, when a bumper crop was widely anticipated. Global wheat prices also increased sharply during 2010, although the benefit for NSW farmers was partly offset by a rising Australian dollar (ABARES 2011), as well as downgrading of wheat quality due to weather damage related to the La Niña conditions (NSW Trade & Investment 2011).
Both the town of Condobolin and the broader Lachlan Shire declined in population by around 7% between the 2001 and 2006 censuses, with the dominance of the primary industry sector (agriculture, forestry and fisheries) also declining, from 38.2% to 35.5% of the shire workforce (Australian Bureau of Statistics 2010). As of 2006, this workforce sector had a median age bracket of 45-54 years and was 75% male (Australian Bureau of Statistics 2010). While farming constitutes the majority of employment in this sector, sawmilling of white cypress and the associated management of State Forests directly employs around 1.3% of Condobolin’s workforce (Natural Resources Commission 2010).
One way to view the land use and demographic trends in the Condobolin region is in relation to Holmes’ (2006) seven land occupation modes described in Chapter 3 (section 3.1.1). The Lachlan Shire fits most closely with Holmes’ “productivist agricultural” mode, whereby production goals dominate over consumption (of land for lifestyle purposes) and protection (of biodiversity or scenic beauty). This is indicated by the relatively high level of employment in agriculture, the distance from major urban centres and the lack of remnant native vegetation. Due to the length of the drought over the past decade, a shift towards a “marginalised agricultural” mode became apparent for some properties around Condobolin, evidenced by low crop harvests, declining population and declining agricultural employment. Holmes argues that such a shift can present opportunities for new multifunctional land uses that combine production and protection goals.
The strong wheat harvest and high prices of 2010-11 interrupts the trend of agricultural marginalisation around Condobolin. However, pressures may re-emerge in coming
139 years, with El Niño conditions forecast for late 2012 under some climate models (Bureau of Meteorology 2012b) and global wheat prices projected to fall in 2012/13 (ABARES 2012). Adding to these pressures are the high Australian dollar, competition for workers with the booming mining sector and the impacts of climate change. Modelling from CSIRO & BOM (2010) indicates that climate change in the NSW Central West, including Condobolin, is likely to bring a reduction in winter rainfall, which is critical to wheat-growing, and an increase in evapotranspiration (Figure 4.4). Projections for the summer months include increases in temperature and evapotranspiration, with a slight increase in rainfall. These projections are based on a range of climate models and a range of emissions scenarios from the Intergovernmental Panel on Climate Change (IPCC) and are thus subject to considerable uncertainty.
Figure 4.4: “Best estimate” (50th percentile) climate change projections for NSW. Projections for rainfall (top) and potential evapotranspiration (bottom) are for winter months relative to a 1990 baseline under the IPCC medium emissions (A1B) scenario. Source: CSIRO and BOM (2010). Condobolin is marked by a dot.
140 The potential impacts of climate change on wheat production in the Condobolin area are uncertain. Wheat yield modelling commissioned for the Garnaut Review, shown in Table 4.1, suggests that wheat yields may rise across much of the eastern Australian wheatbelt by 2030 under climate change, with possible declines thereafter in some locations (Crimp, Howden, Power, Wang & De Voil 2008). However, Condobolin has a lower mean annual rainfall than the nearest locations shown in Table 4.1 (i.e. 460 mm at Condobolin versus 584 mm at Dubbo and 552 mm at Coolamon). This could make Condobolin more susceptible to a loss of winter rainfall.
Table 4.1: Wheat yield change across southeastern Australia under climate change. Cumulative change from 1990 levels under “best-estimate” (50th percentile) model outputs. Source: Garnaut (2008).
Cumulative Yield Change under 3 Climate Change Scenarios (%)
Global mitigation with Global mitigation with No Location CO -e stablised@450ppm CO -e stablised@550ppm mitigation (north to 2 2 south) 2030 2100 2030 2100 2030 2100
Dalby, Qld 1.6 -3.7 4.8 -1.0 8.2 -18.5
Moree, NSW 14.8 10.8 17.7 14.1 20.6 10.9
Dubbo, NSW 4.0 2.3 6.1 6.7 8.1 -5.9
Coolamon, 8.2 7.4 9.9 12.3 11.6 1.9 NSW
Birchip, Vic 6.8 -0.3 10.7 1.5 14.8 -24.1
Climate change modelling by CSIRO (2007) suggests that, under a moderate 2030 climate change scenario, the town of Forbes (100km east of Condobolin) could have a climate similar to that currently found at Warren, 200 km to the northwest. If Condobolin were to experience a similar 200 km shift in climatic zones, it would have a climate similar to that currently found between Nyngan and Cobar, where the
141 wheatbelt gives way to extensive grazing lands. Garnaut (2008, p. 552) suggested that mallee production for bioenergy could be an alternative land use option for areas that are “in the process of conversion out of wheat growing by the warming and drying of southeast Australia”. In addition to the warming and drying trends, an increase in extreme events such as heatwaves, droughts and floods are predicted as climate change progresses (Hennessy et al. 2007). Changes to the amplitude and location of El Niño events have been projected, along with a shift towards a different type of event, the “Modoki El Niño”, an example of which is the 2002-2003 event that caused severe reductions in rainfall across eastern Australia (Richardson, Steffen, Liverman, Barker, Jotzo, Kammen et al. 2011).
Some of the regional environmental issues that are most prominent around Condobolin are soil health, water management and biodiversity conservation. Soil compaction, acidification and sodicity are major soil health concerns (Molino Stewart Pty Ltd 2009), but unlike in the Western Australian wheatbelt, dryland salinity is not a widespread problem around Condobolin. Biodiversity conservation is a key issue due to the high levels of past clearing and low levels of remnant native vegetation. Water supply issues are a major concern and the Condobolin area has been heavily impacted by restricted water releases in recent years. Most notably, the Wyangala Dam upstream on the Lachlan River reached a low of 4.3% of capacity in December 2009 before the drought broke (NSW Government 2010). CSIRO (2007c) warns that climate change is likely to lead to reductions in water availability for irrigation in the Lachlan catchment.
NSW has been divided into thirteen natural resource management (NRM) regions, each of which is managed by a Catchment Management Authority (CMA). The CMAs fall under state government jurisdiction and have responsibility for implementing certain state laws, such as those covering native vegetation clearing. They also receive much of their funding from the Commonwealth for programs to address issues such as soil health, water quality and biodiversity loss. The Condobolin area falls under the jurisdiction of the Lachlan CMA, which also extends to the headwaters of the Lachlan River in the Central Tablelands and to the end of the river at the Great Cumbung Swamp, about 250 km southwest of Condobolin. The Lachlan Catchment Action Plan (Lachlan Catchment Management Authority 2006) contains a number of targets
142 relating to revegetation, with the three most relevant to the Condobolin area shown in Table 4.2.
Table 4.2: NRM targets relating to revegetation under the Lachlan Catchment Action Plan. Source: Lachlan Catchment Management Authority (2006).
Theme Target for 2016 Actions Associated with Target
Biodiversity 20,000 hectares of - Creation of corridors to improve and Native native vegetation connectivity between fragments and Vegetation established through increasing patch size revegetation using - Creation of buffers to patches of high local endemic species conservation value, priority habitats, regional and local corridors and degraded landscapes - Management of revegetated areas for biodiversity conservation under a management agreement
5000 kilometres of - Identification of both regional and local corridor habitat is corridors established and/or - Work with land managers to link remnant protected vegetation by revegetating and/or enhancing the corridors
Land 20,000 ha of actively Stabilisation and rehabilitation of areas of the Management eroding, fragile or catchment identified as severely degraded, severely degraded actively eroding or have a high erosion hazard land are stabilised (actively eroding gullies, fragile soils currently and/or rehabilitated experiencing sheet erosion, areas of salt and sodic scalds and saline discharge sites)
In addition to the targets relating to habitat corridors, buffers and land stabilisation shown in Table 4.2, the Lachlan Catchment Action Plan also has a target that, by 2016, “100,000 hectares of saline hazard landscapes will be improved and maintained using actively growing, diverse, perennial-based vegetation systems” (Lachlan Catchment
143 Management Authority 2006, p. 126). However, this target primarily relates to revegetation in groundwater recharge areas, which are more common in the upper catchment than the area around Condobolin. The Lachlan Catchment Action Plan states that a key goal behind the 5000 km corridor target is facilitating the movement and dispersal of flora and fauna in response to climate change. This theme is revisited in other regional planning documents, including a Natural Resources Commission (2010) assessment of cypress forests in southwestern NSW, which highlights the potential for cypress forests within State Forests and other land tenures to act as the backbone of a regional corridor network that could help species adapt to climate change. The report notes that “there may also be scope to expand the cypress timber industry to private and leasehold land if policy settings can be refined to create appropriate incentives for landholders and managers to invest in agro- and farm-forestry” (Natural Resources Commission 2010, p. 8). CSIRO (2007c) suggests other roles that revegetation could play in climate change adaptation in the Lachlan catchment, including increasing shade for stock and facilitating a change to land uses that are more resistant to heat and drought.
While the current catchment action plan extends to 2016, it was under review at the time this thesis was finalised, with the CMA advising that a revised plan is expected in 2012.
4.1.2 Bioenergy-based land use options for the Condobolin area
The Lachlan Renewable Energy Alliance (LREA) was formed in 2006 by a group of landholders and other interested parties around Condobolin in order to explore the potential for new land use options involving bioenergy production. Poor wheat yields associated with drought and rising production costs were major drivers behind the formation of the group (Total Catchment Management Services 2008). A range of bioenergy options, including ethanol from wheat, were initially considered by the LREA, but the group quickly narrowed their focus to blue mallee (Eucalyptus polybractea), shown growing in Figure 4.5 at West Wyalong, 100 km from Condobolin. Blue mallee occurs naturally across a large portion of western NSW and
144 substantial areas of mallee were cleared in the past to make way for cropping and grazing (Total Catchment Management Services 2008).
Figure 4.5: Blue mallee growing in a plantation at West Wyalong, NSW. Plants are 2-3 m tall approximately 18 months since last harvest. Photo by Alex Baumber, April 2010.
Since 2007, the LREA has assessed the potential for a range of bioenergy products from mallee, along with co-products such as eucalyptus oil and charcoal. While these ideas have been strongly influenced by the experiences of the fledgling Oil Mallee industry in Western Australia (WA), there are also significant differences between the LREA and Oil Mallee approaches. Dryland salinity is not a major focus around Condobolin, with a number of other NRM goals instead driving mallee-based revegetation, including sequestering carbon, stabilising soils, providing habitat for biodiversity and enhancing social resilience (Total Catchment Management Services 2008). The LREA have also focused on block rather than ribbon plantings and shorter harvest cycles than in WA.
A business analysis commissioned by the LREA with the support of the Lachlan Shire Council (Total Catchment Management Services 2008) outlines a vision for over 250
145 million blue mallee trees planted on 67,500 ha of land within a 100km radius of Condobolin by 2019 (i.e. covering 2% of all land within this radius). This approach would involve block plantings of around 4000 trees per hectare, with trees harvested every 12-15 months using a coppicing approach (where trees resprout after harvest from an underground lignotuber). These parameters are largely based on mallee production trials undertaken at the Condobolin Agricultural Research Station since the late 1980s, involving locally-provenanced seedstock as well as seedstock from farther afield (e.g. Milthorpe, Hillan & Nicol 1994, Milthorpe, Brooker, Slee & Nicol 1998). Mallee biomass productivity of 2-3 dry tonnes per hectare per year (t/ha/yr) has been estimated for Condobolin (Total Catchment Management Services 2008), compared with estimates of 5-15 t/ha/yr (dry) for the wheatbelt of WA (URS Australia 2009). Possible reasons for these differences in yields include rainfall levels, soil types, availability of groundwater and planting styles (e.g. blocks at Condobolin vs. ribbons in WA).
An important influence on some LREA members has been the eucalyptus oil production facility operated by GR Davis Pty Ltd near West Wyalong, 100km south of Condobolin. This facility has been producing eucalyptus oil from mallee (both wild stands and plantations) for over 100 years, has experimented with a range of approaches and has participated in production trials run by the Condobolin Agricultural Research Station. While the research station trials focused primarily on plant selection for oil and biomass yield (Milthorpe et al. 1994, Milthorpe et al. 1998), design features such as wider spacings between rows and soil protection using mulch or grass have been trialled at West Wyalong. According to the property manager for GR Davis, these measures have led to improvements in soil health and water infiltration (Andrew Cumming personal communication April 2010).
The product options most extensively explored by the LREA have been wood pellets for electricity or heat and eucalyptus oil for pharmaceuticals or solvents. Assuming average yields of 2.5 t/ha/yr (dry), preliminary economic modelling reported by Total Catchment Management Services (2008) suggests that farmers would need to attract a price of at least $19/t for the biomass and $2/kg for the eucalyptus oil in order to match average 2007 returns from grazing and cropping, estimated at $83/ha/yr. While
146 eucalyptus oil prices were considered to be fairly well-known and a price of $2/kg considered conservative, returns on biomass were much more uncertain due to the challenges involved in accessing wood pellet markets and unpredictable costs for processing and transport.
Wood pellets are used as an energy source for purposes ranging from residential heating to electricity generation and offer advantages over other solid biomass fuels such as low moisture content and relatively high calorific value (Heinimö & Junginger 2009). Total Catchment Management Services (2008) considered the potential production of pellets for export, domestic electricity generation or charcoal production, with trial pellets produced from Condobolin mallee and analysed for calorific value, moisture and ash content. Europe accounts for the majority of global pellet production and consumption, with countries such as Sweden, Denmark, Belgium, the Netherlands, the UK and Italy importing pellets from Canada, the Baltic states and eastern Europe (Heinimö & Junginger 2009). Enecon (2007) modelled the production and export of wood pellets made from mallee biomass at York, Western Australia, concluding that such export may be commercially viable at middle or upper range prices available in
Europe or on the emerging Japanese market.
Since 2008, a sub-group of LREA members have set up a separate corporate structure to commercialise the production of blue mallee. This includes a company called MalleeCondo Pty Ltd, which is tasked with establishing a local mallee industry, and a broader company called True Blue Mallee Pty Ltd, which has responsibility for product development and marketing, as well as identifying opportunities in other regions. The group is yet to establish a commercial plantation, but a seed orchard has been planted on one property and trial harvest of existing mallee stands has occurred on others (Sandy Booth, True Blue Mallee, personal communication Sep 2009-April 2012). This group has moved away from wood pellets to explore compressed wood briquettes. These have been produced on a trial basis and sold under the name BIOBLOXTM through a website and selected retailers in the Blue Mountains, west of Sydney (Figure 4.6). This product is marketed as a “fire extender” for residential wood heaters, having lower moisture content and higher density than regular commercial firewood (True Blue Mallee 2011).
147
Figure 4.6: Image of Fire Extender BIOBLOXTM product and packaging. Source: BIOBLOX website (True Blue Mallee 2011).
Another important development has the commencement of a mallee production trial in March 2010 involving ten landholders around Forbes (100km east of Condobolin). These landholders have been working with Delta Electricity, a major electricity generator in NSW, to grow over 200,000 mallee trees for co-firing with coal (Delta Electricity 2010). This mallee trial forms part of a broader plan to replace 20% of the coal used at the Wallerawang power station, 200km east of Forbes, with biomass from a number of potential sources, including new mallee plantations, existing radiata pine plantations, urban wood waste and invasive native scrub approved for clearing in western NSW (Horner 2010b). While the Forbes trial has recently been reported as moving into a commercial phase (Larkin 2011), Delta Electricity have indicated that a combination of an increased price for Large-scale Generation Certificates (LGCs) and the introduction of carbon pricing is needed to bridge the cost gap of around $55/MWh between coal-fired and biomass-fired generation (Horner 2010a). These policy factors are discussed further in section 4.3.
148 Apart from the exploration of pellets, briquettes and co-firing in the NSW central west, a number of other bioenergy options involving mallee have been explored in Western Australia. Integrated tree processing for electricity, eucalyptus oil and activated carbon (a product used in water filtration and gold recovery) has been modelled (Enecon 2001) and successfully trialled at a demonstration plant (Verve Energy 2006). Options involving liquid biofuel production from cellulosic material have also been considered in WA but not yet trialled. These include ethanol production via complex fermentation pathways and the production of renewable diesel and other fuels through thermo- chemical conversion (gasification or fast pyrolysis) followed by further refinement via processes such as Fischer-Tropsch conversion (Enecon 2007). Aviation biofuels have become a recent focus due to the lack of other renewable alternatives for the aviation sector, with a pilot facility proposed for construction in 2012 by a consortium including Virgin Australia, GE, the Renewable Oil Corporation, Future Farm Industries CRC and Canadian company Dynamotive Energy Systems (GE 2011). A recent analysis of biofuel prospects for aviation found that, although fuel production was technically feasible and biomass resources were substantial, high production costs and competition from the road transport sector could pose challenges for the use of second-generation biofuels in aviation sector in the short-to-medium term (CSIRO 2011b).
A final influence on the LREA and the broader community around Condobolin has been the establishment of mallee carbon sequestration plantings in the district during the 2001-2009 drought period. Most of these plantings were established by the company CO2 Australia in accordance with the rules of the Kyoto Protocol and the NSW Greenhouse Gas Reduction Scheme. These rules are discussed further in section 4.3, but most notably include a requirement that the carbon stock of the mallee plantation is retained for a 100-year period. While these plantings are not available for harvest for bioenergy or any other product, they have been the most prominent example of commercial mallee establishment in the Condobolin area.
My introduction to the Condobolin case study was through Sandy Booth, who is a visiting fellow at the Institute of Environmental Studies, University of New South Wales. Mr Booth is the principal of Total Catchment Management Services Pty Ltd
149 and was lead author of the 2008 business analysis commissioned by the LREA. He is also one of the founders of MalleeCondo Pty Ltd and True Blue Mallee Pty Ltd. This introduction to the case study creates the potential for what Rogers (2003) terms “source-bias”, which is the tendency for researchers to side with those who have introduced them to a case study. Care has been taken to minimise the potential for this bias in the development of case study methodologies in Chapters 5, 6 and 7.
4.2 Central Tablelands Case Study
The Central Tablelands region straddles the Great Dividing Range, which divides the coastal strip of NSW from the western slopes and plains. Dominant land uses include grazing of sheep and cattle, protected area management, exotic softwood plantations and some cropping (Figure 4.7). Native vegetation occupies a larger proportion of the landscape than around Condobolin, with the Greater Blue Mountains World Heritage Area bordering the region to the east. The region’s plantation estate is dominated by Radiata pine (Pinus radiata) and is found mostly within government-owned State Forests, with about 25% of the plantation estate on private land (Forests NSW 2008a). While a small number of farm forestry trials have been undertaken in the region (Allan Wilson, Green Canopies Pty Ltd, personal communication August 2010), URS Forestry (2008a) found that the area of farm forestry in the central and northern tablelands combined was only 2760 ha, less than 10% of the total farm forestry area in NSW.
The boundaries of the Central Tablelands are ambiguous, with some definitions stretching west past Orange (e.g. Bureau of Meteorology 2011c) and others covering only the local government areas (LGAs) that immediately border the Blue Mountains (e.g. Central Tablelands Alliance 2007). For the purposes of this thesis, the case study region has been defined as including the four LGAs shown in Figure 4.7, governed by Oberon Shire Council, Lithgow City Council, Bathurst Regional Council and Midwestern Regional Council.
150
Figure 4.7: Land use in the NSW Central Tablelands. Source: LUMAP (NSW Government 2007). The blank area to the east is a result of LUMAP’s lack of coverage for the Sydney metropolitan area.
4.2.1 Economic, social and environmental trends
Mean annual rainfall in the Central Tablelands (Bureau of Meteorology 2012a) is highest in the southeast (around 900 mm at Lithgow and 850 mm at Oberon) and declines moving northwards (670 mm at Mudgee) and westwards (640 mm at Bathurst). The higher rainfall levels in the southeast are a major reason for the concentration of the existing radiata pine plantations in this area. While the Central Tablelands were affected by the same broad drought patterns that impacted Condobolin from 2001 to 2009, the Central Tablelands spent much less of this period under drought declaration (Industry & Investment NSW 2010). Climate change patterns are
151 projected to be broadly similar to those shown for Condobolin in Figure 4.4, with temperatures increasing in all seasons and rainfall decreasing in winter but increasing slightly in summer (CSIRO & BOM 2010). While there is significant uncertainty associated with translating state-wide climate change projections into more specific regional-scale impacts, CSIRO (2007a, 2007b) warns that by 2030 the Central Tablelands may experience reduced streamflow, shifts in climatic ranges affecting biodiversity and agriculture (particularly wine and fruit production) and increased risks from drought and wildfire.
The population of the four LGAs at the time of the 2006 census was 81,807, with 44% of these people residing in the Bathurst urban area (Australian Bureau of Statistics 2010). The density of the Central Tablelands population (3.94 persons/km2) is much higher than that of the Lachlan Shire around Condobolin (0.45 persons/km2). Also, rather than experiencing a population decline between 2001 and 2006, the four Central Tablelands LGAs recorded combined growth of 1.6%. However, much of this growth was concentrated in the two largest urban centres of Bathurst and Lithgow. If these urban areas are excluded, the smaller towns and rural zones actually show a population decline by 2.4% between 2001 and 2006 (Australian Bureau of Statistics 2010).
While parts of the Central Tablelands may fit under Holmes’ (2006) productivist agricultural mode, the agriculture, forestry and fisheries sector accounted for only 7.2% of employment in 2006. Moreover, the number of people employed in this sector declined by around 12% between 2001 and 2006, compared with an increase in overall employment of 6% (Australian Bureau of Statistics 2010). Employment in the agriculture, forestry and fisheries sector was least prominent in the urbanised LGAs of Bathurst and Lithgow and most prominent in Oberon Shire (17% of all employment), where the major wood processing facilities are located.
The Central Tablelands has shown strong evidence of Holmes’ “multifunctional rural transition” in recent years, with an influx of so-called “rural lifestylers” (also known as “hobby farmers”, “blockies” or “tree-changers”) who are not dependent on the land for their income (Central West Independent Review Panel 2007). The greatest concentrations of rural lifestylers are found around major towns and transport routes to
152 Sydney, with these areas falling under Holmes’ modes of “rural amenity” (dominated by consumption values) or “pluri-activity” (mix of production and consumption values). Some areas in the far east of the region could be classed as “peri-metropolitan” (featuring intense competition between production, consumption and protection) due to their proximity to Sydney and the Greater Blue Mountains World Heritage Area.
Most of the plantations in the Central Tablelands have their origins in the 1960s and 70s, when the NSW Government pursued a policy of clearing “unproductive” native vegetation for the establishment of exotic softwood species (Forests NSW 2008a). Clearing was phased out in the 1980s and plantation establishment on private land was also encouraged. Given that harvest cycles for radiata pine are typically 28-35 years (Forests NSW 2008a), many plantations in the region have been harvested and replanted at least once. The dominant processing site for plantation timber in the region is the Oberon Timber Complex, where sawn timber, particle board and medium- density fibre board (MDF) are produced. However, some timber processing occurs at Bathurst and at locations outside the region. Forests NSW (2008) does not have any native plantations in the region’s State Forests, but some private landholders have engaged in native agroforestry trials (Allan Wilson pers. comm.).
Coal mining is also an important land use in the Central Tablelands, mostly concentrated northeast of a line running between Lithgow and Mudgee (known as the Western Coalfield of NSW). Coal mines in the region supply export markets as well as the Mt Piper and Wallerawang coal-fired power stations west of Lithgow. Expanding coal exploration and production in the Western Coalfield has seen new land purchases by mining companies and has led to some community concerns regarding conflicts with existing farming activities, the contribution of coal to climate change and impacts on communities close to mines, groundwater systems and adjoining conservation areas (Department of Planning 2011).
Environmental issues in the Central Tablelands differ significantly from Condobolin due to higher levels of remnant native vegetation, higher rainfall, greater elevation and relief and differing soil types. Parts of the Central Tablelands have been classified as having high salinity hazard and the dominance of coarse-grained acidic rock types has
153 led to sandy-textured soils which are susceptible to erosion (Central West Catchment Management Authority 2007). Water issues are also quite different to Condobolin, with the tablelands sitting upstream of a number of major dams, including Warragamba Dam supplying Sydney, Burrendong Dam on the Macquarie River and Wyangala Dam that supplies towns including Condobolin on the Lachlan River. Biodiversity issues vary significantly across the region, from the largely-intact Greater Blue Mountains World Heritage Area, listed for its outstanding biodiversity values, to other areas that have been extensively cleared for agriculture or urban development.
The two main Catchment Management Authorities (CMAs) with jurisdiction over the case study area are the Hawkesbury-Nepean and Central West CMAs (Figure 4.8). Lachlan and Hunter-Central Rivers CMAs cover smaller areas away from the major population centres of the tablelands.
Figure 4.8: CMA and LGA boundaries in the Central Tablelands.
154 Both the Hawkesbury-Nepean and Central West CMAs have identified roles for revegetation in reducing groundwater recharge in salinity-prone landscapes and for the protection of low capability land that is not suitable for grazing or cropping. Table 4.3 lists the management targets that have greatest relevance for revegetation with woody perennials under the two catchment action plans for 2006-2016.
Despite the common focus on revegetation, the two CMAs endorse different strategies for achieving it. While the Central West plan emphasises the potential for commercial forestry plantations to play a role in revegetation, the Hawkesbury-Nepean plan focuses on passive regeneration (e.g. fencing out livestock) and the use of locally- provenanced plants. Hawkesbury-Nepean CMA also has more of a focus on the potential for revegetation to enhance habitat corridors and provide buffers for remnant vegetation, with explicit mention made of the role that this could play in assisting species movement in response to climate change. In contrast, the 2006-2016 Central West plan does not mention climate change at all.
In addition to the targets listed in Table 4.3, there are also a number of other targets in each catchment action plan for which revegetation could potentially play a role. These include stabilising and controlling sediment migration along priority watercourses, enhancing and regenerating native riparian vegetation and restoring and enhancing areas of high conservation value (HCV) vegetation. However, it is doubtful that revegetation activities that involve ongoing harvest for bioenergy would be applicable to these targets. A potential conflict is likely to exist between CMA goals of protecting degraded riparian areas and the use of biomass harvesting machinery in such areas. Also, vegetation that is established and managed for ongoing harvest is unlikely to meet the definition of HCV vegetation.
155 Table 4.3: CMA management targets most relevant to revegetation using woody perennials in the Central Tablelands. Sources: Central West Catchment Management Authority (2007) and Hawkesbury-Nepean Catchment Management Authority (2007).
CMA & Target (for 2016 unless otherwise Actions Associated with Target Theme noted) Central Establish and manage large - Strategic placement of West: interception plantings on 30,000 ha interception plantings of Salinity of suitable sites in identified key perennial vegetation in upland landscapes landscapes that exhibit suitable groundwater flow systems Establish and manage for salinity - Establishment of plantations of outcomes 2,000 ha of large forestry native or exotic species (50 to plantings within key saline >500 ha in size) in key upland landscapes sites to control recharge. Increase by 100,000 ha the spatial - Implementation of grazing and area of perennials in identified farming systems that reduce recharge landscapes across the recharge through deep-rooted catchment for optimal water use perennials (trees, shrubs, forbs, grasses) Central 10,000 ha of lands classified as low - Improvement in current West: capability for cropping or grazing management practices, Vegetation purposes are managed primarily for revegetation or rehabilitation conservation of native vegetation - May be suitable for commercial and landscape protection plantations From 2008, new forestry - Location of future forestry plantations are located to achieve plantations in areas that have a optimal contribution to other symbiotic relationship with the catchment targets landscape (including salinity and soil targets)
156 CMA & Target (for 2016 unless otherwise Actions Associated with Target Theme noted) Hawkesbury- 2300 ha of native vegetation have - Priority given to passive Nepean: been established through regeneration and fencing over Biodiversity revegetation to replace native active revegetation with tree- vegetation cleared in each planting landscape - Priority given to locally provenanced seeds/plants The condition of native vegetation - Priority given to Mitchell has been improved by Landscapes >70% cleared, active/passive regeneration of priority fauna habitats and buffers of at least 20 m around high regional biodiversity corridors priority, existing remnants resulting - Investment in buffers that can be in an increase of 360 ha under regenerated naturally active/passive regeneration. Hawkesbury- 20 000 ha of the catchment will be - Exclusion fencing Nepean: protected from soil erosion through - Engineering works Soil and soil conservation works (e.g. Land fencing, gully control, revegetation) Management Salinity - by 2009, recharge sites in - Revegetation of identified saline priority subcatchments have been recharge areas (including identified and by 2016, 2400 ha of integration of this goal into all recharge areas have been treated CMA projects) An additional 20 000 ha of targeted Preservation and revegetation to areas of agricultural land ensure: throughout the catchment is - 90% tree cover on land managed according to its rural land capability class 7 (2nd lowest capability capability class) - 100% vegetation cover on land capability class 8 (lowest capability class)
157 Late in 2011, Central West CMA released a new draft catchment action plan for the period 2011-2021 (Central West Catchment Management Authority 2011). This plan was developed in accordance with the principles of resilience thinking and the INFFER approach, both discussed in Chapter 3. INFFER was used during the planning process to identify over 500 systems and assets within the Central West CMA region, with the new catchment plan designed to target thresholds of potential concern for high risk assets (Central West Catchment Management Authority 2011, p. 20). This approach, which considers both the significance of assets and the risks to which they are exposed, has much in common with the notion of critical natural capital envisioned by De Groot (2003) and Brand (2009) in Chapter 3. Unlike the 2006-2016 plan, climate change features prominently in the revised plan as a key driver of system change.
The revised Central West plan is simpler than the 2006-2016 version, with the number of themes reduced from seven to four (communities, water, biodiversity and land) and the number of management targets reduced from 41 to 10. CMAs have had to become more strategic in the setting of priorities due to a large reduction in base CMA funding that occurred in 2008, shortly after the 2006-2016 Central West plan was finalised (Natural Resources Commission 2009). Commercial plantations are no longer mentioned explicitly in the revised Central West plan, but revegetation in general retains its relevance as a priority action, particularly under the following targets: x B1 (Biodiversity): By 2021, 8-16% of priority vegetation communities are being actively managed to achieve a good condition stable state, increase net extent and, where possible, increase connectivity x B2 (Biodiversity): By 2021, increase the number of management interventions coordinated to improve habitat of native flora and fauna including threatened species to achieve stable state x L1 (Land): By 2021, 9-40% of priority soil landscape systems are being actively managed to maintain good condition or managed to improve condition to be in an ecologically functional and productive alternate state
158 4.2.2 Bioenergy-based land use options for the Central Tablelands
Unlike at Condobolin, the exploration of bioenergy options for the Central Tablelands has not been primarily driven by landholders. Rather, the development of a regional bioenergy industry has been pursued most actively by a combination of research and development bodies, the forestry and energy sectors, catchment management authorities and local councils.
The selection of appropriate plantation species is one research area with important implications for the development of bioenergy-based agroforestry in the Central Tablelands. Booth and Ryan (2008) highlighted a number of native tree species that could have commercial potential in the Central Tablelands, including Tasmanian blue gum (Eucalyptus globulus, especially ssp bicostata), shining gum (E. nitens), spotted gum (Corymbia maculata), sugar gum (E. cladocalyx) and river red gum (E. camaldulensis). Bennell et al. (2009) also identified Tasmanian blue gum, sugar gum and river red gum, along with manna gum (E. viminalis), as promising bioenergy species for lower rainfall environments (including the western part of the Central Tablelands). Stirzaker et al. (2002) provided a climate matrix to assist with the selection of tree species for salinity mitigation. A number of farm forestry trial sites were also established across the Central Tablelands between 1998 and 2001 with the involvement of the Central West CMA (Allan Wilson pers. comm.). These trials included species such as Tasmanian blue gum, shining gum and she-oak (Casuarina spp.), but monitoring and reporting of these trials has been inconsistent.
A review of regional agroforestry prospects around Australia (Polglase et al. 2008) classed most of the Central Tablelands as falling under the “Southern Wet” geoclimatic zone (>550mm rainfall and south of 29º latitude), where E. globulus was modelled as a bioenergy species18. The results of this modelling suggest that, if the opportunity cost of taking land out of current production is taken into account, producing biomass for electricity generation would be profitable only in very limited areas of the Central Tablelands. The modelling suggested that plantations would need to located close to
18 Parts of the region may also fall into the “Southern Dry” zone, where E. cladocalyx was modelled or the East Coast Sub-tropical zone, where E. grandis (flooded gum) was used.
159 bioenergy facilities in order to be profitable, due to high transport costs and low prices for biomass ($21-23 assumed per green tonne). The modelling also showed that integrated production of bioenergy, eucalyptus oil and charcoal could improve profitability compared with bioenergy alone, but the most attractive options financially would be hardwood sawlogs or pulpwood production. Overall, across all of Australia’s National Plantation Inventory regions, Polgalse et al. (2008) gave the Central Tablelands a medium ranking for sawlog and pulpwood production.
Electricity generation from biomass has been explored in the Central Tablelands. As mentioned in section 4.1, Delta Electricity have set a goal of replacing 20% of the coal used at their Wallerawang power station west of Lithgow with around 1.2 million dry tonnes of biomass (Delta Electricity 2010). Co-firing with up to 2% chipped biomass has been achieved routinely and 8% co-firing has been achieved in combustion trials using wood pellets (Horner 2010b). Four main sources of biomass have been explored by Delta Electricity: clean separated wood waste (i.e. recycled timber) from Sydney, local softwood processing wastes, woody weeds (invasive native scrub) from western NSW and plantation mallee biomass from around Forbes (discussed in section 4.1). Notably, while Delta have commenced a plantation trial 200km west of Wallerawang at Forbes, they have not explored new plantations in the Central Tablelands region itself (Horner 2010b). This issue is further addressed in Chapters 5 and 6.
The Central Tablelands case study research presented in this thesis has emerged from a collaborative effort involving the Blue Mountains World Heritage Institute (BMWHI), the Institute of Environmental Studies (IES), the Future of Australia’s Threatened Ecosystems (FATE) Program and the Hawkesbury-Nepean CMA. These groups have been exploring the potential for new land uses that could combine production and conservation along the western edge of the Blue Mountains since around 2004. BMWHI and the IES are based at the University of New South Wales (UNSW), where the FATE Program was also based before moving to the University of Sydney in 2009. I personally have been involved in this research work since 2005, firstly as Project Officer for the FATE Program and then, since 2008, as a PhD candidate. This work has looked at a variety of potential agroforestry products, with bioenergy emerging as a key focus in July 2007, following a meeting hosted by Oberon Shire Council. The
160 strong initial interest by Oberon Council was due to the concentration of existing wood wastes at Oberon’s wood processing facilities and in surrounding softwood plantations.
Following the 2007 Oberon meeting, the idea of a native agroforestry industry that could produce biomass in conjunction with the existing plantations and processing facilities in the region was presented to the Central Tablelands Alliance, consisting of Oberon Shire Council, Lithgow City Council and Mid-Western Regional Council. The Alliance endorsed this vision and agreed to support a research funding proposal to the Bioenergy, Bioproducts and Energy Program of the Rural Industries Research and Development Corporation (RIRDC) in February 2008. RIRDC were unable to fund the project at that time, but subsequently repackaged it for submission in August 2009 to the Forest Industries Climate Change Research Fund (FICCRF), operated by the Australian Government Department of Agriculture, Forestry and Fisheries (DAFF). In April 2010, DAFF and RIRDC approved funding totalling $173,700 for an 18-month research project led by BMWHI, IES and FATE (referred to hereafter as the BMWHI project).
The objective of the BMWHI project was to explore whether bioenergy-based agroforestry could be an appropriate industry for the Central Tablelands. My roles in this project have included drafting the RIRDC and DAFF research proposals and undertaking specific research tasks as a PhD researcher reporting to the principal investigators, John Merson (UNSW) and Peter Ampt (USYD), who are also PhD supervisors. As such, the majority of the Central Tablelands case study research presented in Chapters 5-7 of this thesis has been undertaken as part of the BMWHI project. As my role has included the diffusion of ideas about bioenergy-based agroforestry to stakeholders who had previously given them little or no thought, the potential exists for both “source-bias” and “innovation-bias” (Rogers 2003). The case study methodologies detailed in Chapters 5, 6 and 7 have been developed in a manner that seeks to counteract these potential biases.
The BMWHI project participants also agreed in 2010 to collaborate with two related projects funded under the FICCRF in the Central Tablelands. One project was carried out by Industry and Investment NSW (now NSW Trade and Investment) and explored
161 the use of harvest residues for bioenergy from existing radiata pine plantations at several sites in the Macquarie region of Forests NSW, which broadly overlaps with the region chosen for this case study19. This project involved assessing the nature and quantity of residual biomass, as well as the implications of biomass removal for greenhouse gas emissions and nutrient balance. The second project involved modelling of a regional bioenergy industry for Central NSW by CSIRO Ecosystem Sciences, with a particular focus on the co-firing of biomass with coal for electricity generation. CSIRO’s project boundaries are significantly larger than the case study presented here, encompassing not only the Central Tablelands but also the Central West slopes and plains as far west as Condobolin. Thus, while being mostly relevant to the Central Tablelands case study, the CSIRO project results also have implications for the Condobolin case study.
Two reports have been produced for the BMWHI project, with one released in 2011 (Merson, Ampt, Rammelt & Baumber 2011) and one forthcoming in 2012 (Baumber, Rammelt, Ampt & Merson forthcoming 2012). Final reports for the CSIRO project (Rodriguez, Warden, O’Connell, Almeida, Crawford, Jovanovic et al. 2011c) and Industry and Investment NSW project (Ximenes, Ramos, Bi, Cameron, Singh & Blasi 2012) were also released in late 2011 and early 2012. The results of the CSIRO and Industry and Investment NSW projects were not available at a sufficiently early stage to be used as direct inputs for the case study research presented in this thesis, but their implications for the case study results are discussed in Chapter 6 (economic analysis).
4.3 Regulatory and policy environment
This section expands on discussion of policy measures for revegetation, agroforestry and bioenergy introduced in Chapter 2 by detailing the specific policy measures applicable to the case studies. As both case study sites fall under the same national and state government jurisdictions, most of the regulatory and policy measures affecting the case study sites are the same, particularly in relation to bioenergy production and plantation development. Natural Resource Management (NRM) policy, including
19 Compared to the case study area selected for this thesis, Forests NSW’s Macquarie region extends farther west past Orange and excludes some areas to the north around Mudgee.
162 revegetation, is the greatest area of difference between the two case studies, due to the differences in CMA jurisdiction.
4.3.1 Natural resource management policy
The three main CMAs covering the case study areas employ a number of different policy mechanisms to promote the NRM targets presented in Tables 4.2 and 4.3. Central West CMA (2011) offers a range of incentives for landholders and community groups. Those with most relevance for revegetation include the Small Grants program (up to $2,000 for on-ground works), the Multi-Ecological Community Stewardship program (paying landholders to manage certain vegetation types for conservation) and the Farm Planning program (including a focus on resilience and adaptation to climate change). However, none of these programs specifically target agroforestry or revegetation activities that are undertaken with an intention of future commercial harvest.
The most relevant funding programs offered by the Hawkesbury-Nepean CMA (2008) are the River Health Program, Biodiversity Program and Soil and Land Program. As discussed in section 4.2, the river health program has limited relevance for commercial agroforestry due to its focus on minimising disturbance. The biodiversity program may be relevant, but has a strong focus on local species. The soil and land program covers the establishment of tree lots to improve soil and water quality and the planting of native vegetation in areas that have been treated for soil degradation. The soil and land program is largely implemented through 10-year agreements between landholders and the CMA, offering up to $14,000 for projects.
The Lachlan CMA covers both the Condobolin case study in its lower catchment and the part of the Central Tablelands in its upper catchment. Lachlan CMA (2011) has a focus on extension, including site visits, information and technical support and planning, as well as providing support funds for selected projects. Past projects supported in the Condobolin area include revegetation on Aboriginal land, wind erosion monitoring, removal of willows from riverbanks and incentives to remove invasive native scrub (commonly referred to as “woody weeds”). Projects supported in
163 the upper catchment include riparian rehabilitation, assessment of biodiversity in Travelling Stock Routes, wind erosion monitoring and the development of methodologies to measure carbon sequestration in environmental plantings. No projects specifically aimed at commercial agroforestry have been supported in either part of the catchment (Lachlan CMA 2011).
All three CMAs also play a role in implementing the Native Vegetation Act 2003 (NSW) by assessing applications to clear protected native vegetation. This is done through the use of Property Vegetation Plans (PVPs). PVPs may identify areas of non- protected vegetation that can be cleared without approval (e.g. regrowth), as well as areas where clearing approval is granted on the basis that it would “improve or maintain” environmental outcomes (e.g. invasive native scrub). Clearing that has a negative impact may still be approved if offsets are specified elsewhere in the PVP, such as agreeing not to clear regrowth, reducing stocking rates, weed control or revegetation (NSW Government 2005). Thus, CMAs could also play a role in promoting agroforestry if it is deemed to be an appropriate offset for clearing.
The NSW Government’s Environmental Trust also provides annual restoration and rehabilitation grants to community groups and local governments ranging from $5,000 to $100,000. However, given that direct landholder grants are not available and that recent grants have not included agroforestry or other commercial revegetation activities, the relevance of this program for the case studies is likely to be limited.
The Australian Government provides NRM funding through the Caring for Our Country program, which includes an open call for larger projects ($20,000 to $1 million), an annual round of Community Action Grants for smaller projects ($5,000 to $20,000) and one-off environmental recovery responses (Commonwealth of Australia 2011a). Caring for Our Country also provides base-level funding for regional NRM bodies across Australia (i.e. CMAs in NSW). The drop in the baseline CMA funding discussed in section 4.2 is related to the establishment of Caring for Our Country in 2008, which was part of a shift in the Commonwealth’s NRM funding strategy away from annual allocations towards competitive processes that are also open to non-CMA applicants (Natural Resources Commission 2009).
164
Of the six priority areas for the Caring for Our Country program, revegetation activities are most relevant under Biodiversity and Natural Icons and Sustainable Farm Practices. In particular, targets have been set to “increase by at least 400 000 hectares by June 2013 the area of native habitat and vegetation that is managed to reduce critical threats to biodiversity and enhance the condition, connectivity and resilience of habitats and landscapes” and “to increase by 10 000 the number of farmers adopting management practices to improve soil health by reducing the risk of soil acidification, soil loss through wind and water erosion and/or increasing the carbon content of soils by June 2013” (Commonwealth of Australia 2011a, p. 40 & p. 69). The former target has a focus on threatened species and ecological communities, linking remnant native vegetation and buffering protected areas, while the latter explicitly refers to landscape- scale conservation through agroforestry (Commonwealth of Australia 2011a).
The Australian Government has also recently announced the creation of a new Biodiversity Fund using revenue raised from the planned carbon pricing scheme. As of early 2012, specific project criteria and application procedures were yet to be issued, but the scheme will aim to promote new environmental plantings that create wildlife corridors, increase habitat connectivity and protect riparian areas (Australian Government 2011). Enhancing climate change adaptation by facilitating species movement is a stated aim of the program. It is unclear whether commercially-harvested plantations would be able to meet the requirements of the program.
Market-based instruments (MBIs) that promote carbon sequestration or biodiversity conservation may also have applicability for the case studies. The NSW Greenhouse Gas Abatement Scheme provides a mechanism for plantation managers to generate carbon credits by establishing a sequestration pool. However, this scheme is likely to be overtaken by the Australian Government’s Carbon Farming Initiative as the main incentive scheme for biosequestration. The Carbon Credits (Carbon Farming Initiative) Act 2011 (Cth) allows Australian Carbon Credit Units (ACCUs) to be issued that may be either compliant or non-compliant with the Kyoto Protocol. Kyoto- compliant ACCUs will be able to be sold to Australian or overseas emitters to offset their emissions, while the main market for non-Kyoto ACCUs will be the Carbon
165 Farming Initiative’s non-Kyoto Carbon Fund, worth $250 million over six years from 2012-13 (Commonwealth of Australia 2011b). The Kyoto Protocol only recognises reforestation that is at least 0.2ha in area, has a tree height of at least 2m and has at least 20% canopy cover (Greenhouse Gas Reduction Scheme 2011). Through the use of non-Kyoto ACCUs, the Carbon Farming Initiative is able to provide incentives for revegetation activities that sequester carbon but may not meet the Kyoto requirements, such as narrow bands of mallee integrated into cropping systems (URS Australia 2009).
Under the Carbon Farming Initiative, greenhouse gas abatement must be permanent and additional (i.e. the activity would not have occurred without carbon credits). Flexibility is provided with regard to permanence by allowing landholders to reverse their abatement and relinquish the credits earned (Department of Climate Change and Energy Efficiency 2010). Activities can pass the additionality test if they are not required by law and are considered uncommon in the industry or region in question. The Department of Climate Change and Energy Efficiency (2011b) has proposed using an uncommonness test based on whether less than 5% of landholders in a relevant comparison group currently undertake the activity. Projects that pass the additionality test can be listed as a specified offsets project under the Carbon Credits (Carbon Farming Initiative) Regulations 2011 (Cth), with this list of projects also known as the “positive list”.
Under the inaugural regulations passed in late 2011, the positive list does not cover any tree-planting activities that involve harvesting, except for forestry projects that were previously accredited under the Australian Government’s Greenhouse Friendly initiative, which certified projects for voluntary carbon markets. However, the positive list is expected to grow over time and the Department of Climate Change and Energy Efficiency (2011b) notes that it will investigate mallee plantings that involve harvesting for products such as bioenergy. As discussed in Chapter 2, harvested plantations can provide permanent sequestration if the average amount of stored carbon in trees and soils over successive harvest cycles is higher than the baseline level prior to plantation establishment. Thus, while significant uncertainty remains, the Carbon
166 Farming Initiative may in the future provide an opportunity for mallee growers at Condobolin to earn carbon credits alongside the production of biomass for energy. The situation in the Central Tablelands is less promising for the generation of carbon credits. The Carbon Farming Initiative also has a “negative list” of “excluded offsets projects” under the regulations. This list covers projects that have been deemed to pose a “significant risk to communities or the environment” (Department of Climate Change and Energy Efficiency 2011b, p. 10). The negative list contains a general exclusion on the generation of ACCUs from plantings in areas with greater than 600 mm average annual rainfall (i.e. the vast majority of the Central Tablelands region) unless: - the planting is a permanent environmental planting (i.e. not harvested); - the planting is designed to mitigate dryland salinity; - water entitlements are held for the estimated use of rainfall by the plantation; or - the planting is in an area where it is not possible to obtain water entitlements or where the National Water Commission believes the relevant State and Territory government has adequately addressed the issue of plantation water use.
As discussed in Chapter 2, the justification for this exclusion is that “plantations established in high rainfall areas can have adverse impacts for other water users and environmental flows” (Department of Climate Change and Energy Efficiency 2011, p. 12). Under these rules, commercial plantations in the Central Tablelands could only earn ACCUs if they were covered by water entitlements (with corresponding costs) or be shown to be combating salinity. Such plantations would also need to be first added to the positive list by passing the additionality test (i.e. be practiced by less than 5% of landholders). Regardless of water licensing or salinity benefits, the negative list prevents any plantations funded through a forestry managed investment scheme (MIS) from earning ACCUs. This has been done to ensure that the additive effect of MIS incentives and ACCUs does not lead to plantation development with “adverse impacts on access to agricultural land, communities and employment” (Department of Climate Change and Energy Efficiency 2011, p. 12).
As of January 2012, methodologies have been developed under the Carbon Farming Initiative for permanent environment environmental plantings, but not for tree planting activities that involve harvesting. Methodologies may be developed by the Department
167 or submitted by other stakeholders and require a public comment period prior to approval. In a previous consultation paper, the Department of Climate Change and Energy Efficiency (2010) suggested that biosequestration activities that involve substantial variations in carbon stocks due to harvest cycles or climatic variability may be able to use an “averaging” approach to determine changes in carbon stocks over the long term. It is unclear whether this approach will ultimately be applied under the Carbon Farming Initiative.
The NSW Biobanking scheme is another market-based incentive scheme with relevance for the case study sites. The scheme provides landholders with tradable biodiversity credits if they enter into agreements to enhance and protect biodiversity on their land. These credits can be traded to developers who have been required under their development approval to offset the habitat destruction they will be causing. Plant regeneration is one of the activities that can be used to generate biodiversity credits under the scheme, along with controlling grazing, retaining fallen timber on the ground to provide shelter for small mammals, managing fire and controlling pests and weeds (Department of Environment and Climate Change 2008a). Developers wishing to destroy habitat may be issued with biobanking statements that detail the number and type of credits (i.e. ecosystem or species credits) that must be surrendered to offset their habitat destruction, along with the vegetation types in which those credits can be generated.
While the BioBanking scheme can offer incentives for revegetation activities, the benchmarks that are used for generating credits are typically based on the land’s original vegetation type (listed in the NSW Vegetation Types Database). Thus, the scheme is heavily based around notions of “naturalness” discussed in Chapter 2 and its relevance for commercial agroforestry activities may be limited, even if such activities could be shown to enhance biodiversity outcomes.
4.3.2 Plantations policy
The Plantations and Reafforestation Act 1999 (NSW) sets out the framework for the regulation of plantations in NSW and establishes the Plantations and Reafforestation
168 Code, which contains most of the detailed prescriptions on plantation establishment and management. The Act outlines the following basic categories of plantation operations: - Plantation operations not requiring approval under the Act: These include existing plantations (approved prior to the Act’s commencement), ancillary plantation operations (part of a broader development approved under a separate process) and exempt farm forestry (less than 30ha and requiring no clearing approval). - Complying plantations: These meet all the requirements of the Code and have a relatively simple application and approval process (decisions within 14 days). - Non-complying plantations: These fail to meet one or more aspects of the Code. The applicant must provide a statement of environmental effects and approval will only be granted if non-complying aspects are not considered significant. Decision times are longer (40 days) and conditions may be imposed. - Operations impacting on threatened species: These may be complying or non-complying in other respects. A species impact statement must be provided by the applicant and any approval requires the concurrence of the Director- General of National Parks and Wildlife or the Director of NSW Fisheries.
The Act is designed to provide a streamlined process, such that authorisation of a plantation exempts the authorised activities from various requirements of the Native Vegetation Act 2003, Environmental Planning and Assessment Act 1979, National Parks and Wildlife Act 1974, Threatened Species Conservation Act 1995 and a number of other NSW Acts. It is also designed to provide a guarantee that authorised plantations will be able to be harvested in the future by restricting the circumstances under which an authorisation may be cancelled. Authorisations may be cancelled due to breaches of the Code, breaches of the approval conditions or abandonment of the plantation. The Minister may also cancel an authorisation if it is deemed necessary to protect unique or special wildlife values, but compensation must be paid in such instances. Because exempt farm forestry does not require authorisation, it also does not benefit from these harvest guarantee provisions.
169 In terms of plantation establishment, the Code has requirements for the retention of native vegetation, buffering of waterways and cultural heritage sites, conditions affecting the placement of roads and slope limits for activities such as mounding, ripping and ploughing (taking account of soil type and rainfall erosivity). Buffers of 20 m are required around all rivers and wetlands greater than 0.1 ha. This reduces the potential for plantations to contribute to revegetation in riparian areas, as any trees planted in these buffer zones cannot be harvested. 10 m buffers are required around drainage lines and drainage depressions on some soils, although some low-impact commercial planting is allowed within these buffer zones. Drainage depressions, drainage lines and rivers are defined using the Strahler system, which looks at how many tributaries flow into the drainage feature.
The Code is designed to ensure that plantations are established on “essentially cleared land”, but some removal of native vegetation is allowed. Clearing of isolated trees and woody vegetation patches less than 1ha is permitted, as long as these cleared areas make up no more than 10% of the plantation area. If the proposed plantation area contains any native “habitat trees” (mature trees with diameter at breast height >40cm), an average of one habitat tree per hectare should be retained. However, it is possible to clear habitat trees to levels below this, provided that replacement trees are established elsewhere (10 or 20 new trees are required for each tree removed, depending on its size). Clearing is generally not permitted for: - Patches of woody vegetation greater than 1ha - Native vegetation on rocky outcrops (exposed boulders >70% of surface) - Rainforests - Wetlands - Native grasslands of high conservation value (large, diverse, well-preserved grassland of a type that is poorly conserved across the region) - Any native vegetation types listed under a regional vegetation schedule
Exceptions to the rule preventing clearing within patches greater than 1ha are permitted for irregular projections (if clearing represents less than 10% of the vegetation patch) and regrowth vegetation.
170 The clearing restrictions of the Code have been designed to be broadly consistent with those of the Native Vegetation Act 2003 (NSW), which is aimed at preventing broadscale landclearing in NSW. Section 11 of the Native Vegetation Act reinforces the harvest guarantee provisions of the Plantations and Reafforestation Act by specifying that “the harvesting or other clearing of native vegetation planted for commercial purposes” is a routine agricultural management activity (RAMA) that does not require approval. However, there are some minor differences between the Acts, most notably around the definition of regrowth. The Native Vegetation Act allows clearing of any vegetation that has regrown since 1990 (or since 1983 in the Western Division), while the Code currently permits regrowth to be cleared if it is less than 10 years old or dominated by certain species (mostly wattles or dense stands of small eucalypts)20.
In addition to authorisation for plantation establishment, the Code requires operational plans to be prepared for major harvesting events (>100 trees removed per hectare). Where trees are harvested through coppicing, as is proposed for blue mallee at Condobolin, an operational plan is not required.
As discussed in Chapter 2, investors in Australian plantations are eligible for tax breaks under the rules for forestry Managed Investment Schemes (MIS). MIS is an attractive option for investors on high incomes who wish to reduce their income tax liability in the short-term. MIS investments are tax-deductible in the year they are made. Future returns are taxable at the time of harvest, but are likely to be spread out over a number of years or received at a time when the investor’s income is subject to a lower marginal income tax rate. As of 2009, MIS was responsible for more than 90% of investment in Australian plantation forestry (Plantations2020 2009). The current rules on MIS require that at least 70% of investor contributions be spent on direct forestry costs and that plantations are established within 18 months of a scheme’s commencement21.
20 Detailed in a regional vegetation schedule issued under the Act effective 14 December 2001.
21 Implemented under the Tax Laws Amendment (2007 Measures No. 3) Act 2007
171 If biomass from existing native forests on private land was to be used in conjunction with plantation biomass, approval for harvesting would be required under the Native Vegetation Act 2003 (NSW). The relevant rules for such harvest around Condobolin and the Central Tablelands are set out in the Private Native Forestry Codes of Practice for Northern NSW (Department of Environment and Climate Change 2008e) and Cypress and Western Hardwood Forests (Department of Environment and Climate Change 2008d). The Codes require the approval of a Property Vegetation Plan (PVP) and Forest Operation Plan prior to harvest, with an ultimate benchmark that harvesting must improve or maintain environmental outcomes (i.e. by ensuring regeneration after harvest). As discussed previously, the use of such biomass for electricity generation would face additional restrictions under the Protection of the Environment Operations (General) Regulation 1998 (NSW) and the Renewable Energy (Electricity) Regulations 2001 (Cth).
4.3.3 Bioenergy policy
The most significant bioenergy policy measure affecting the case study sites is the Australian Government’s Renewable Energy Target, particularly the component relating to large-scale generation, the Large-scale Renewable Energy Target (LRET). As discussed in Chapter 2, biomass electricity projects are eligible under the LRET to earn LGCs (Large-scale Generation Certificates). The LRET is a market-based scheme that requires liable parties (usually electricity retailers) to surrender a certain number of LGCs each year, based on their share of the electricity market (Office of the Renewable Energy Regulator 2011). Liable parties can either create LGCs themselves or purchase them from other renewable energy generators on the LGC market.
Prior to 2011, the tradeable certificates were known as RECs (Renewable Energy Certificates) and covered both large-scale and small-scale generation. A REC multiplier, starting at five RECS per MWh rather than one, was applied to small-scale solar, wind and hydro to make these sources more competitive, but these “phantom” RECs were seen to be flooding the REC market and affecting the viability of large- scale projects (Buckman & Diesendorf 2010). This led to small-scale generation sources being moved into their own scheme, the Small-scale Renewable Energy
172 Scheme (SRES), with its own certificates, Small-scale Technology Certificates (STCs). SRES does not presently include bioenergy.
Following the separation of the LRET and SRES, LGC prices were predicted to rise due to the removal of the impact of phantom certificates (EnergyAustralia 2011). LGC spot prices rose from around $30 to $40 per LGC in early 2011, before stabilising at that level over the following 12 months (Green Energy Markets 2012). Horner (2010a) has estimated that it may take three or more years for all phantom certificates to “wash out” of the system, as liable parties are permitted to “bank” certificates for use in later years. Another complicating factor is the existence of long-term bundled contracts under which a renewable energy generator sells both electricity and LGCs to an electricity retailer. ROAM Consulting (2011) argue that these contracts often feature an “effective” LGC price that is much higher than the spot price, calculating this effective price to be $92 per LGC in 2011 compared to a spot price of around $40.
Electricity generation from plantation biomass falls under the “energy crops” category of the LRET, even if bioenergy is only a minor product from the plantation. Prior to the amendment of the Renewable Energy (Electricity) Regulations 2001 (Cth) in 2007, most plantation biomass fell under the category of “wood waste” and was stigmatised by association with wood waste from native forests, including reports that this negative public perception was driving down prices for all RECs in the wood waste category (Australian Greenhouse Office 2003). The criteria for plantation biomass to be classed as an energy crop under the regulations are that it is sourced in accordance with relevant Commonwealth or State planning and approval processes, the plantation is managed under an approved code of practice (or the Australian Forestry Standard as a default) and that the land on which the plantation stands was not cleared after 31 December 1989.
The voluntary renewable energy support scheme, GreenPower, managed by a consortium of State and Territory government agencies also provides a complement to the LRET. Greenpower supports higher prices for renewable energy by requiring electricity retailers to purchase sufficient renewable energy to cover the amount that their GreenPower customers have signed up for. These requirements are in addition to
173 any LRET obligations. Biomass from sustainably managed plantations is an eligible source under Greenpower, provided that native forests were not cleared during establishment (GreenPower, 2010).
Carbon pricing can also impact on the viability of bioenergy by increasing the costs associated with burning fossil fuels. NSW has had an emissions trading scheme since 2003, the Greenhouse Gas Reduction Scheme (GGAS), which creates an effective carbon price through the trading of NSW Greenhouse Abatement Certificates (NGACs). However, this scheme is likely to be terminated or substantially altered once the Australian Government’s national carbon pricing mechanism commences in mid- 2012 (Independent Pricing and Regulatory Tribunal 2011). The national scheme will commence with a 3-year period in which the price for emissions permits is fixed
(effectively a carbon tax), with the permit price starting at $23/tCO2-e in 2012-13 and rising to $25.40/tCO2-e by 2014-15 (Commonwealth of Australia 2011b). The scheme then transitions to a cap-and-trade system, in which the supply of permits is fixed and the price varies according to demand for permits and the marginal cost of abatement. A rising carbon price can be expected to improve the competitiveness of renewable energy over time by increasing the cost of generating electricity from coal and, to a lesser extent, gas. However, this impact is likely to be small during the early years of the scheme, with modelling conducted for the Treasury department by SKM MMA and
ROAM Consulting showing that carbon prices starting at $20-30 per tCO2-e would result in a “relatively small additional increase in renewable generation” by 2020 compared to the impact of the LRET alone (Treasury 2011, p. 105).
A key reason why the carbon price is unlikely to drive additional renewable energy investment in its early years is the inter-relationship between the carbon pricing mechanism and the LRET. Introducing a carbon price into a fossil-fuel dominated electricity market such as Australia’s can be expected to increase wholesale electricity prices, which should make renewable generation more competitive. However, because this rise in wholesale prices will close the gap between the average wholesale electricity price and the long run marginal cost of renewable generation, the LGC price would be expected to fall. This is because, according to economic theory, this gap should be the key determinant of the LGC price (Frontier Economics 2008, ROAM
174 Consulting 2011). Thus, the introduction of a carbon price is likely to cause a commensuurate drop in the LGC price, neutralising the impact of the carbon price on renewable generation. However, the carbon price is likely to become a more significant driver of renewable energy over time, as the generation target for the LRET iis due to stop growing in 2020 and then remain steady until 2030 (Figure 4.9). The rellationship between the carbon price and the LRET and the implications for economic modelling are discussed further in Chapter 6.
Figure 4.9: Change in generation target under the LRET 2011-2030. Datta source: Office of the Renewable Energy Regulator (2011)
If liquid biofuels were to be produced from woody biomass at either case studdy site, they would qualify for the NSW Government’s fuel blending mandates under the Biofuels Act 2007 (NSW). Primary fuel wholesalers in NSW are currently required to ensure that ethanol makes up a minimum of 6% of all petrol sales by volume and biodiesel makes up a minimum of 2% of all diesel sales. Plans to increase the biodiesel mandate to 5% were postponed indefinitely in December 2011 due to a lack of local supply and plans to replace all regular unleaded petrol with E10 (10% ethanol) were cancelled in January 2012 due to concerns that some motorists could experiennce engine damage from E10 and would have to buy more expensive premium fuels (Office of Biofuels 2012a). As discussed in Chapter 2, biofuel suppliers do not currently have to demonstrate compliance with a sustainabilitty standard, but the Roundtable on
175 Sustainable Biofuels standard has been listed under the regulations and is planned to be phased in over an unspecified period of time (Office of Biofuels 2012b).
The main biofuel incentives offered by the Australian Government are the Ethanol Production Grant Program (ethanol) and Cleaner Fuels Grants Scheme (biodiesel and renewable diesel), which were recently extended until 2021. Both of these schemes provide a subsidy of 38.143c/L, effectively making these fuels excise-free and providing a competitive advantage over conventional petrol and diesel. The national carbon pricing scheme will also provide a competitive advantage for liquid biofuels in certain transport applications. Biofuels will be treated as carbon neutral, while an effective carbon price will be imposed on domestic aviation, shipping and rail transport through changes to fuel credits or excise arrangements, with the government intending to extend this to heavy on-road transport by 2014 (Commonwealth of Australia 2011b). No carbon price will apply to household transport or light commercial vehicles. As these forms of transport are more likely to use ethanol rather than biodiesel, ethanol is likely to gain less of a competitive advantage from carbon pricing compared to biodiesel, renewable diesel and renewable jet fuel. Renewable diesel differs from biodiesel in its production process, being refined from a biocrude rather than produced via the transesterification of vegetable oil or animal fat.
Solid biomass fuels such as wood pellets, briquettes or firewood used for industrial or residential heat would not be eligible for Commonwealth or NSW Government incentives. Industry groups representing major users of plantation biomass for industrial heating applications have urged the Australian Government to increase incentives for the use of such fuels (A3P 2010). Liquid or solid fuels that are exported may benefit from subsidies, tax concessions or mandate schemes operating in the importing country, with the European pellet market largely driven by these policies (Sikkema, Steiner, Junginger & Hiegl 2009).
As discussed in Chapter 2, electricity generation using biomass sourced from existing native forests rather than plantations would face significant regulatory barriers. As of November 2011, the definition of wood waste under the Renewable Energy (Electricity) Regulations 2001 (Cth) prevents any biomass sourced from a native forest
176 to be used in the creation of LGCs. These changes were negotiated by the Australian Greens Party as part of the carbon pricing package (Commonwealth of Australia 2011b) and replace the previous rules that permitted native forest residues to be used to earn LGCs if the biomass was harvested primarily for a higher-value purpose such as sawlog or veneer production. The changes have no impact on plantation biomass, which is eligible for the creation of LGCs under the energy crop category.
In NSW, the Protection of the Environment Operations (General) Regulation 1998 (NSW) also restricts the use of native forest biomass. These restrictions are weaker than the new Commonwealth regulations on native forest biomass in that they allow native forest biomass to be used for electricity generation if it is from an off-site processing facility (e.g. a sawmill) or is used for small-scale generation (<250kW capacity). However, the NSW regulations are more limiting in some ways because they apply directly to the generation of electricity rather than simply the creation of LGCs. The NSW regulations use a broad definition of native forest bio-material that covers any bio-material from any native Australian tree, unless grown as part of a plantation. This definition would extend to native regrowth, even if it is classed as invasive native scrub and approved for clearing by the relevant authority. Delta Electricity have considered this source of biomass for their 20% co-firing project for Wallerawang power station (Horner 2010b).
For bioenergy options other than electricity generation, there are no commensurate restrictions on the use of native forest biomass. Transport fuels produced from native forest biomass (e.g. cellulosic ethanol) would still be eligible for the NSW biofuel mandate and the Australian Government’s Ethanol Production Grant. Heating products (e.g. wood pellets, firewood) do not presently receive support regardless of their source.
Bioenergy production using plantation biomass from the case study sites may also be eligible for some of the research and development support programs mentioned in Chapter 2. Funding has already been fully allocated for the Biofuels Capital Grants Program, which aimed to increase supplies of liquid biofuels, and the Second Generation Biofuels Research and Development Program, which covers liquid biofuels
177 from cellulosic and algal feedstocks. However, future funding may be available through the Australian Biofuels Research Institute (ABRI), which was established in 2011 with a focus on reducing the costs of second-generation biofuels. It is planned that ABRI will be absorbed by the new Australian Renewable Energy Agency (ARENA) as part of the Australian Government’s Clean Energy Future program. ARENA has recently launched a $15 million Advanced Biofuels Investment Readiness Program, aimed at pre-commercial demonstration of second-generation biofuels. ARENA is complemented by the Clean Technology Innovation Program, which will fund proof-of-concept work and early-stage commercialisation, and the Clean Energy Finance Corporation, which will invest in renewable energy projects (Commonwealth of Australia 2011b).
Future bioenergy research and development funding may also be available through the Bioenergy, Bioproducts and Energy Program of the Rural Industries Research and Development Corporation (RIRDC), which contributed funding for the Central Tablelands component of this thesis. Examples of other recent bioenergy projects funded by RIRDC include the development of bioenergy sustainability policy (O'Connell et al. 2009a) and biomass co-firing with coal (McEvilly, Abeysuriya & Dix 2011).
4.4 Case Study Goal and Research Questions
As shown in the preceding sections, each of the two case study sites feature a range of NRM issues and goals relating to revegetation and have experienced some degree of industry development in the areas of agroforestry and bioenergy. However, there remains much uncertainty regarding the prospects for further development of these industries, the potential to connect them with NRM objectives and the role that policy could play in these developments. Thus, the research goal for the following three case study chapters is defined as follows:
To assess the potential for new sustainable land use options in the case study regions that involve the production of bioenergy from woody crops and the delivery of regional natural resource management goals.
178 The goal has been deliberately phrased to focus on bioenergy production and NRM delivery, rather than bioenergy production for NRM delivery. This approach reflects the fact that there is much uncertainty about whether synergies between bioenergy production and NRM goals will be found and what the priorities of relevant stakeholders are likely to be. The focus on woody perennial crops does not imply that other bioenergy options, such as grains or grasses, could not play a role in achieving regional NRM goals. Rather, the focus on woody perennials is a result of the following factors: x many of the revegetation strategies identified for the case study regions focus on woody perennial vegetation; x woody energy crops have a track record of delivering NRM benefits in Western Australia and Europe (discussed in Chapter 2); and x preliminary consultations at both case study sites have revealed stakeholder visions based around woody crops (e.g. LREA at Condobolin).
Beneath the broader research goal, a number of more specific research questions are relevant to the case studies:
1. What bioenergy options involving woody energy crops may be viable in the case study regions? 2. What economic and non-economic benefits can woody energy crops provide for landholders in the case study regions? 3. How could the establishment of woody energy crops contribute to regional NRM goals? 4. What barriers exist for the adoption of new land uses involving bioenergy production and the delivery of NRM goals? 5. What policy measures could be employed to promote and guide such land uses and develop a regional bioenergy industry (if this is considered desirable)?
The five research questions form the basis of the social, economic and environmental analyses presented in Chapters 5, 6 and 7. Question 1 expands on the background information presented in this chapter by exploring potential species, product options and plantation designs. Questions 2 looks at the potential benefits of energy cropping, with Question 3 focusing more narrowly on regional NRM goals. Question 4 covers
179 the flipside to Questions 2 and 3, looking at the potential risks that energy cropping could create. Question 5 expands on the policy information presented in section 4.3 by exploring which new policy measures and policy variations could be effective for the case studies. Table 4.4 shows how the five questions are addressed in Chapters 5, 6 and 7.
Table 4.4: Elements of each research question covered in Chapters 5, 6 and 7.
Research Chapter 5 Chapter 6 Chapter 7 Question Social Analysis Economic Analysis Environmental (summarised) Analysis
1. Viable Stakeholder views Economic viability N/A bioenergy on: of: options x Bioenergy x Bioenergy options options x Plantation designs x Plantation designs
2. Economic Stakeholder Economic benefits N/A and non- motivations economic (economic, social & benefits environmental)
3. Contribution Perceived N/A Protection & to regional contribution to NRM enhancement relating NRM goals goals to biodiversity, soils, salinity & climate
4. Barriers to Perceived barriers Economic barriers N/A adoption (economic, social & environmental)
5. Policy Preferred policy Economic impact of N/A measures options policy changes
180 4.5 Conclusion
While neither case study site currently features a significant level of agroforestry activity aimed at either bioenergy production or revegetation, the background information presented in this chapter indicates that opportunities may exist for new land use options that can meet these objectives in an integrated manner. The past and present research and development activities undertaken by such diverse groups as the Condobolin Agricultural Research Station, the LREA, MalleeCondo Pty Ltd, GR Davis Pty Ltd, Delta Electricity, BMWHI, Industry and Investment NSW and CSIRO cover a range of factors that are critical to a future bioenergy industry based on agroforestry. These factors include biomass production rates, market opportunities, plantation management strategies and financial costs and returns. Furthermore, the focus of the relevant NRM agencies on revegetation using woody plants presents potential opportunities to identify synergies between environmental, economic and social objectives. However, the information presented in this chapter also highlights substantial knowledge gaps relating to bioenergy-based agroforestry, including its economic feasibility, social acceptability and environmental impacts.
The two case study sites are relatively close together and fall under the same national and state government jurisdictions, but they also feature a number of differences in terms of climate, land use patterns, social issues, environmental issues and level of experience with bioenergy and plantation forestry. As a result, the case study sites present an opportunity to analyse how these different factors influence the social, economic and environmental feasibility of different bioenergy and agroforestry options. This analysis task is taken up over the following three chapters, which focus on social analysis (Chapter 5), economic analysis (Chapter 6) and environmental analysis (Chapter 7). Chapters 5-7 combine the background information and previous research presented in this chapter with new research tasks in an attempt to fill key knowledge gaps and identify priority areas for future research. These chapters also draw on the existing policy measures presented in this chapter, as well as other international examples cited in Chapters 2 and 3, to assess the potential social, economic and environmental impacts that may result from changes in policy.
181 Chapter 5: Social Analysis
This chapter presents the original social analysis undertaken for the Condobolin and Central Tablelands case studies. As outlined in Chapter 4, the development of bioenergy-based agroforestry at either case study site involves a broad cross-section of stakeholders, including landholders, plantation managers, energy companies, potential investors and government agencies. However, there is little existing information on the attitudes of these stakeholders towards key factors such as plantation location and design, product options and policy interventions. Thus, the methodologies outlined in this chapter are designed to narrow these knowledge gaps and feed into the policy framework outlined in Chapter 3 and employed in Chapter 8. In particular, this chapter identifies key goals, values and perspectives for Stage 1 of the policy framework (problem-framing/orientation) and evaluates attitudes towards a range of policy options for Stage 3 (policy evaluation).
This chapter is divided into separate sections for each case study, with section 5.1 covering the methodology and results for the Condobolin case study and section 5.2 covering the methodology and results for Central Tablelands case study. Section 5.3 provides a comparative discussion of results from both case studies, exploring their implications for each of the five research questions outlined at the end of Chapter 4. Key results from the Condobolin case study have previously been published in the journal Rural Society (Baumber, Merson, Ampt & Diesendorf 2011), while key results from the Central Tablelands case study appear in a project report to the Rural Industries Research and Development Corporation (Merson et al. 2011).
5.1 Condobolin Case Study
Prior to commencing this case study, preliminary investigations were undertaken, including attending a meeting of the Lachlan Renewable Energy Alliance (LREA) at the Condobolin Agricultural Research Station in December 2009 and holding discussions with key informants. I was invited to attend the meeting by Mr Sandy Booth of Total Catchment Management Services Pty Ltd, who is also one of the founders of MalleeCondo Pty Ltd as well as a Research Fellow at the Institute of
182 Environmental Studies, UNSW. I introduced myself to the meeting and explained my connection to Mr Booth, while stressing the independence of my research project. Over the next two days, informal discussions were held with six key stakeholders connected to the LREA, MalleeCondo Pty Ltd, the Condobolin Agricultural Research Station and Lachlan Shire Council. Most of these stakeholders were landholders in the district. These results were used to develop a methodology for a series of semi-structured interviews.
5.1.1 Methodology
A total of nineteen semi-structured interviews were carried out between April and October 2010. All interviews were face-to-face, apart from one, which was undertaken by phone. The interviews ranged from 20 to 75 minutes in length. Interviewees were divided into three basic categories: landholders, government and industry (Table 5.1). Several interviewees fell into more than one category.
Table 5.1: Breakdown of interviewees by category. Landholders Government Industry
x 7 “core” LREA x 3 Industry & Investment x 1 prospective mallee bioenergy landholders NSW (Condobolin producer (MalleeCondo Pty Ltd) x 7 “peripheral” Agricultural Research x 1 electricity company (Delta landholders Station, Plantations Electricity) Unit, State and Regional x 1 mallee eucalyptus oil producer Development) (G.R. Davis Pty Ltd, 100 km x 2 Lachlan Shire Council from Condobolin) (1 employed, 1 elected) x 1 farming industry group x 1 Lachlan CMA representative (Central West employee Farming Systems) x 1 farming services contractor x 1 retailer of rural supplies
Landholders were divided into a “core” group who had been involved with the LREA for a number of years and a “peripheral” group with only minor involvement, such as
183 attending a single meeting or discussing ideas about mallee with LREA members. As shown in Figure 5.1, the properties of interviewed landholders were mostly to the west and north of Condobolin, with the farthest being around 140km away by road.
Figure 5.1: Property locations for interviewed landholders around Condobolin.
As discussed in Chapter 4, the initial introduction to the case study through Sandy Booth creates the potential for “source-bias” (Rogers 2003). Steps were taken to minimise this potential bias during both the interviews and the analysis of results. These steps included: x explaining to interviewees that I was not affiliated with MalleeCondo or the LREA; x using open-ended questions that would allow interviewees to identify issues themselves rather than rely on those cited by advocates of mallee production;
184 x recognising that non-adoption may be a rational and appropriate decision; and x avoiding extrapolation of results beyond the interview group to the broader landholder community around Condobolin.
Landholders were recruited by “snowballing” from core LREA members that were present at a meeting of the LREA on 12 April 2010 at the Condobolin RSL Club. This process was not designed to provide a random sample of landholders in the Condobolin area, but rather to learn about the key issues from those who had spent the most time and effort thinking about them. The early interest shown by the core group does not necessarily mean they would become early adopters of mallee production, as this can be influenced by a range of factors relating to individual circumstances and the nature of the land use option (Pannell et al. 2011). A request was made to Delta Electricity to also interview landholders involved with their mallee production trial around Forbes, but this request was denied.
The interview methodology was approved by the UNSW Human Research Ethics Advisory Panel for Arts, Humanities and Law on 5 March 2010. This approval covered the interview questions (Table 5.2), as well as the information statement and consent form given to each participant prior to interviewing (Appendix A). The consent form advised that the interviews would be recorded (audio only) and that no information that could identify particular interviewees would be published without their permission. Interviewee responses were kept anonymous, with codes used to differentiate interviewee categories (e.g. LH A=Landholder A, LH/G B=Landholder/Government B). Because the interview questions dealt with potential policy changes, government and industry interviewees were asked to express their personal views rather than the official views of their employer.
Table 5.2 lists the questions used in the interviews, with variations and follow-up questions shown in italics. The default questions were aimed at landholders, who made up the majority of interviewees, with modification or omission required for government and industry stakeholders to reflect their differing roles. Some interviewees addressed questions from a purely personal perspective, whereas others considered the ramifications for other stakeholders. As the interviews were semi-
185 structured, some interviewees gave expansive responses, raised additional issues and answered follow-up questions, while others did not address the full set of questions due to a lack of relevance or time constraints.
Table 5.2: Questions used in semi-structured interviews. Variations and follow-up questions are indicated by italics. No. Topic 1 Background: - Age, gender, property size, land use activities (Landholders) - Role of organisation (Industry/Government) 2 Goals: - What are your goals in using your land the way you currently do? What are your goals for the future of your property? (Landholders) - What are the goals of your organisation/business (Industry/Government) 3 Do you have any concerns about the long-term sustainability of: - your land or your current land uses? (Landholders) - current land uses in the district? (Industry/Government) 4 What are the major environmental issues for the region? (All interviewees) 5 Have you (or your organisation) been involved in other types of tree-planting before? 6 Have you experimented with other changes in land use or innovations? (Landholders) 7 What exposure have you had to the idea of growing mallee for bioenergy or other products? (All) 8 Is it something you (or landholders in the district) might be interested in (why or why not)? - Would the net average annual return need to be the same or better than your current land use for you to take it up? (or do you think landholders would need this?) - What return would you need per hectare to take it up? (Landholders) 9 What potential benefits do you think planting mallee could provide? (All - Prompt for different types of benefits if not initially volunteered - economic, environmental and social) 10 What issues could cause difficulties or barriers to getting involved in growing
186 No. Topic mallee? (All) 11 If mallee proves viable, how much land would you think about converting to it? Where on your property would you plant it? (Landholders) 12 Do you feel that you have enough information about land preparation, planting and harvesting for mallee? (Landholders) - Which of these tasks would you want to do yourself? (Landholders) - Is there a need for standards or protocols in any these areas? (All) 13 What kind of support schemes do you think would be most effective in helping landholders take up mallee? (All - prompt with establishment support, market development, price support or payments for ecosystem services such as storing carbon, preventing erosion or conserving biodiversity) 14 How much land would you like to see converted to mallee across the region as a whole? (All) 15 Assuming returns were the same, would it make any difference to you what the mallee ended up being used for, such as bioenergy, eucalyptus oil, timber, woodchips or storing carbon? (All) 16 How do you currently sell your products (e.g. auction, forward contracts)? What approach would you want to see for mallee? (Landholders) 17 What sort of business model would you prefer for growing mallee? (All - interviewer then outlines three different models that emerged in preliminary discussions – a community-based enterprise model, an outside investor model and a carbon rights model)
The first seven interviews were carried out jointly with James Martin, who was assessing landholder involvement in mallee production as part of a Masters of Environmental Management project at UNSW. As such, some interview questions were devised jointly with Mr Martin in order to obtain information relevant to both projects, particularly the questions on previous innovations (Q6), information required for mallee production (Q12) and the methods for selling products (Q16).
Questions 1-4 were focused on landholder characteristics, goals, sustainability and environmental issues. Questions 5-7 were aimed at understanding past practices and
187 exposure to the idea of growing mallee. Questions 8-10 were aimed at understanding the key drivers for, and barriers to, the adoption of mallee cropping. While these questions were influenced by the diffusion/adoption frameworks of Rogers (2003) and Pannell et al. (2011), a full diffusion study was beyond the scope of this research.
Question 8 sought to test the importance of mallee being able to deliver a return that was comparable to current land uses in terms of average net annual return ($/ha/yr). Economic studies often compare the average net return from a proposed land use with that of a current land use, with examples including the analysis of regional agroforestry potential by Polglase et al. (2008), the WA Oil Mallee Industry Development Plan (URS Australia 2009) and the mallee business analysis for Condobolin commissioned by the LREA (Total Catchment Management Services 2008). Other authors, such as Pannell et al. (2011) emphasise that this is only one factor determining the relative advantage of an innovation.
Question 9 on the benefits of growing mallee was deliberately open-ended, with follow-up questions used based on an interviewee’s initial response (e.g. “you mentioned some economic benefits, do you see any social or environmental benefits?”). Responses were recorded both before and after this prompting. While the issue of climate change was raised by most interviewees at some stage, none of the interview questions directly asked about the interviewees’ level of belief in climate change or their concerns about it. This was done to avoid making assumptions and to allow interviewees to express for themselves whether climate change was a significant influence on their decision-making. Despite this attempt to prevent bias, it is possible that some interviewees may have worded their answers cautiously due to the social context of the interviews, which involved young urban-based environmental researchers, often stereotyped as climate change “believers”, interviewing older rural landholders, often stereotyped as climate change “deniers”. In line with Clark’s (2002) view that researchers should recognise their own standpoint in relation to sustainability issues, it should be noted that I personally accept the conclusions of the Intergovernmental Panel on Climate Change (2007) that “warming of the climate system is unequivocal” (p. 30) and that “most of the observed increase in global
188 average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic GHG concentrations” (p. 39).
Question 10 was focused on barriers and was also open-ended to avoid bias. Questions 11, 12, 14 and 15 covered various aspects of plantation design and management, including the amount of potential land conversion (individual properties and district- wide), preferred products and existing knowledge. These questions were designed to explore some of the issues discussed in Chapter 2 regarding competition for land and community attitudes to plantations, which can depend on the amount and quality of land converted and the level of integration with existing agriculture (Williams 2009a).
Questions 16 and 17 focused on different mallee business models identified through the preliminary investigations. Interviewees were presented with two bioenergy production models: a community-based model in which locally-owned businesses would coordinate planting, harvesting and processing (promoted by some LREA members) and an outside-investor model where growers would supply mallee under contract and the investor would take on many costs and risks (influenced by the Delta Electricity trials around Forbes). A third model was also presented based on mallee being planted purely for carbon sequestration (i.e. no harvest), with carbon rights sold to an external company under contract (influenced by the activities of CO2 Australia in the Condobolin area).
Question 13 focused on policy, with four possible support mechanisms for a mallee bioenergy industry being presented to interviewees. These options were: x support with the establishment of mallee plantations (e.g. grants) x market development activities (e.g. research and development of bioenergy products) x measures to support the price of mallee products (e.g. renewable energy mandates, carbon price) x payments for the co-benefits or ecosystem services that could result from planting mallee (e.g. biodiversity, salinity or carbon credits).
189 5.1.2 Results
As the interview questions differed depending of the interviewee’s role, the category is noted for each result (e.g. landholders only, government/industry combined). The number of interviewees responding is also stated for each question (e.g. n=16).
For landholders, the average age was 50 years (n=14) and there were thirteen males and three females (two interviews involved couples). The most common land use was a mixture of dryland cropping and grazing, with two landholders growing irrigated crops as well and two practicing grazing only. The average area of land owned or managed was just over 7,000 ha, with 9 of the 14 landholders saying that the land was their main source of income (two others said it would be if not for the drought). When asked about goals (Q2), 93% of interviewed landholders mentioned making an income from the land and 86% talked about sustainable management or improving land condition over time (n=14).
With regards to the sustainability of current land uses (Q4), 50% of landholders (n=12) said they had no major concerns, 42% raised economic concerns (e.g. declining returns, rising input costs) and 25% raised environmental concerns (e.g. declining rainfall, declining irrigation water availability, excessive chemical use). 58% noted that land management had improved over time. Only one landholder explicitly linked a sustainability concern (declining rainfall) to climate change.
While there were no specific questions on climate change, the issue came up in most interviews (12 of 19). Amongst landholders, only one interviewee clearly self- identified as a believer in climate change and one self-identified as a non-believer. The remaining ten were classed as “ambivalent”, with examples including:
“I guess the fundamental question is do you believe in climate change? I dunno” (LH/G A)
190 “…there’s definitely climate change but whether it’s for the worse or not, whether it’s cyclical. We’re still a young country, we really don’t know. We’re gonna have our droughts and our floods…” (LH F)
“I’m not a firm believer in global warming per se – I’m a firm believer in conserving resources and maintaining the health of our land and all that sort of thing but you know I think weather will change around and we’ve seen this before” (LH A)
Government and industry representatives reinforced the general view of climate change expressed by landholders, with one stating that landholders in the district were “sitting on the fence” and another stating that there was “widespread scepticism”.
64% of landholders (n=14) reported some degree of previous involvement in tree- planting (Q5). As shown in Figure 5.2, this was mostly for non-commercial purposes (windbreaks/shelterbelts or other environmental reasons), although three landholders had experience with producing mallee commercially or as a part of a trial.
Figure 5.2: Landholders reporting previous experience with tree-planting. N/A=not answered.
Landholders identified a range of land use innovations or changes they had adopted in the past (Q6), with the most common being minimum-till cropping, re-establishment of native pastures, changing the balance between grazing and cropping (generally towards grazing), trialling mallee, growing grain crops for fodder and introducing controlled
191 traffic (i.e. GPS-guided) cropping. Many of these practices, along with others such as agistment of stock and seeking off-farm income, were reported to be adaptations to drought or climatic variability.
Responses to Q9 (potential benefits of growing mallee) were classed as economic, social or environmental (Figure 5.3). All interviewees nominated at least one economic benefit of growing mallee (landholders, government and industry combined), with diversifying income streams and reducing income variability the most commonly cited. In contrast, less than a third mentioned social or environmental benefits without prompting (e.g. “you’ve mentioned some economic benefits, what about social or environmental benefits?”). The most common social benefit cited (including after prompting) was jobs or business opportunities for the local community, while windbreaks were the most common environmental benefit cited. Some benefits mentioned in the 2008 business analysis (Total Catchment Management Services 2008) attracted few mentions, including carbon sequestration, biodiversity conservation and salinity mitigation.
Figure 5.3: Number of interviewees citing each type of benefit. Results are for landholders, government and industry combined (n=16). Cross-hatching represents where benefits were only cited after additional prompting.
192 While economic factors represented the greatest perceived benefits of growing mallee, they also represented the greatest perceived barriers (Q10). As shown in Figure 5.4, the most-cited barrier was uncertainty about returns, followed by a lack of investment capital, particularly after years of drought. Follow-up questions revealed that concerns about uncertainty related mostly to mallee product options, market access and prices. In contrast, there was widespread confidence that mallee would grow well in the area and that sufficient knowledge existed within the LREA on how to grow it. The most common social barrier was the risk of future regulatory changes that may inhibit harvest, particularly under the Native Vegetation Act 2003 (NSW). This was classed as a social barrier due to its political nature, but it clearly has economic and environmental dimensions as well. Environmental barriers were the least cited of the three categories, with the risks cited relating to fire, pests and poor survival.
Figure 5.4: Number of interviewees citing each type of barrier. Results are for landholders, government and industry combined (n=17).
Landholders were divided into “core” and “peripheral” groups based on their level of involvement with the LREA. On average, those in the core group cited a greater number of discrete benefits from growing mallee than those in the peripheral group (Figure 5.5). However, those in the core group also cited a greater number of discrete barriers, which may be a reflection of the greater amount of time and thought that the core group members had given to the idea of growing mallee.
193
Figure 5.5: Average number of discrete benefits and barriers cited by landholders. Includes benefits cited only after prompting.
In terms of the economic return required to adopt mallee production (Q8), only 25% of landholders, government and industry interviewees (combined) said that it would need to be the same as, or more than, returns from current land uses (n=16). 50% said mallee would be attractive even if the return was lower than current land uses, citing reasons such as greater consistency of income, ability to use of marginal land, reduced wind erosion and reduced runoff. The remaining 25% said it would depend on factors such as whether it was a small-scale or large-scale change (the latter requiring an equal or greater return) or the personal circumstances of the farmer (e.g. older farmers might take a lesser return if they could reduce their labour input).
Most landholders found it difficult to put a dollar figure on the net annual average return they would require from mallee, with many citing income variability due to drought as a reason. Only two of the landholders who said they would be prepared to accept a lower return than current land uses put forward a figure, with these being $50- 100/ha/yr and $80/ha/yr. Two landholders who said they would need a return that was the same as current land uses or greater nominated a dollar figure, with these being $150-200/ha/yr and $250-370/ha/yr (the latter being on a small irrigated farm). It is difficult to draw conclusions from such a small sample size, but, interestingly, these
194 two pairs of figures fell either side of the figure of $83/ha/yr that was identified by Total Catchment Management Services (2008) as the average return on land in the district in 2008. These figures are discussed further in the economic analysis in Chapter 6.
The amount of land nominated by landholders for potential conversion to mallee (Q11) ranged from 2% to 50% of total land held. A number of landholders broke this down into initial and ultimate amounts (Figure 5.6), emphasising the need to observe results before converting more land. The median amounts nominated were 5% for initial conversion and 9% for ultimate conversion, compared with the 2% average conversion rate envisioned by the 2008 business analysis (Total Catchment Management Services 2008). The land most commonly cited for plantings was marginal or less productive land, closely followed by land that was currently underutilised for cropping due to its size or shape. Landholders from the core group were more likely to focus on block plantings rather than strips and the need to use reasonable quality land to ensure satisfactory yields.
Figure 5.6: Amount of land nominated by landholders for conversion to mallee. Only those landholders providing a response are included.
There was a divergence of views amongst core landholders as to the density of planting. Some landholders suggested densities of around 4000 trees/ha, with rows 1.5- 2.5 m apart, based on research by Milthorpe et al. (1998). Others preferred lower densities of around 3000 trees/ha, with rows 3 m apart, to encourage grass growth
195 between rows. This latter group were influenced by the G.R. Davis eucalyptus oil plantation near West Wyalong.
When asked how much land across the district should be converted to mallee (Q14), 50% (landholders, government and industry combined) said it was up to individual landholders or would be driven by economics (n=12). The remainder suggested figures ranging from 5% to 50% of the landscape, with two landholders mentioning the need to maintain food production as a reason for limiting mallee expansion. When asked what product they would prefer be produced from the mallee, assuming returns were identical (Q15), a majority of interviewees (8 out of 12) felt that it did not matter, while two expressed a preference for renewable energy and two expressed an objection to carbon plantings.
Of the three mallee business models presented in Q17, 60% of interviewees (landholders, government and industry combined) favoured the community-based bioenergy model, in which locally-owned businesses would coordinate planting, harvesting and processing (n=16). 20% of interviewees favoured the model in which an outside investor such as an energy company would contract landholders to produce mallee as a feedstock for bioenergy. The remaining 20% could see benefits from both the community-owned and outside-investor models. The advantages cited for the community model were greater control over the land, higher potential returns (due to taking on greater ownership and risk) and greater flow-on benefits to the community. The outside-investor model was seen to offer lower risk, stable long-term contracts, lower management requirements and access to bigger markets.
No interviewees cited the carbon planting model as their most favoured model. In fact, 75% expressed strong negative views towards carbon plantings, such as:
“You lose control of your land for 99 years.” (LH F)
“It’s inhibitive, it devalues the land.” (LH C)
196 “…has no appeal to me because it’s a one-off payment and you get a negative for the sale of country” (LH E)
“Carbon trading is very political and airy-fairy and you can’t see any result. Too susceptible to political change. Let’s say you lock up a contract for 100 years - governments change and ideas change and it’s too long a timeframe for what’s actually happening on the ground.” (LH D)
“…if it was twice or three times [current returns] or whatever my trigger would be - people sell their souls at a price don’t they? But you would take a lesser price I suppose for renewable energy – being involved in that sort of market.” (LH/G A)
These responses highlight very different attitudes amongst interviewees towards mallee being grown for bioenergy and mallee being grown for carbon only. This issue is discussed further in section 5.3.
The majority of landholders (both core and peripheral) felt that mallee growers should be able to undertake certain activities themselves (Q12), such as ripping and plantation design to minimise costs and ensure that plantations met their needs (e.g. windbreaks, soil protection). However, some landholders saw value in a standardised approach, such as ensuring high survival rates, optimal productivity and access for harvesting. Views on the best methods for selling mallee products (Q16) also reflected a collaborative approach, with the most common suggestion being a growers’ pool that could maximise bargaining power in bioenergy markets while minimising the risk and transaction costs for individual landholders. Long-term contracts were seen to minimise risk but reduce landholder returns, while an auction-style approach was seen to offer greater potential returns but with greater risk.
The final issue addressed in the interviews was the effectiveness of policy options to support landholder entry into a mallee bioenergy industry (Q13). By far, the most favoured of the four options presented (Figure 5.7) was establishment support (n=16, landholders/government/industry combined). Follow-up questions revealed that this
197 need was largely financial, as most interviewees felt that sufficient knowledge on growing mallee existed within the group. Low interest loans were suggested as an establishment support option by several landholders, citing their use with other agricultural activities.
Figure 5.7: Policy options listed as first or equal first by interviewees. Includes all interviewees providing a response (n=16).
While all interviewee groups (landholders, industry and government) preferred establishment support over the other options, the industry and government stakeholders were more likely than landholders to nominate price support and market development. In terms of price support, a boost to the Renewable Energy Target and the introduction of a carbon price were cited as examples. A key reason that was cited for being sceptical towards price support and payments for ecosystem services (especially carbon sequestration) was the risk of future policy change. These issues are discussed further in section 5.3.
198 5.2 Central Tablelands Case Study
The social analysis for the Central Tablelands case study was largely undertaken after the Condobolin social analysis, from August 2010 to February 2011. The methodologies selected differed from those employed at Condobolin for three key reasons discussed in Chapter 4:
1. The Central Tablelands case study covers a larger and more diverse area; 2. The case study does not feature a core landholder group who have begun to explore bioenergy options from agroforestry; and 3. Greater resources were available for the social analysis as a result of funding from the Department of Agriculture, Forestry and Fisheries (DAFF) and the Rural Industries Research and Development Corporation (RIRDC).
For these reasons, the methodologies chosen were a Participatory Rural Appraisal (PRA), followed by a mail survey sent to landholders across the study area. The case study formed part of a larger group project, carried out by a research team consisting of two principal investigators (also thesis supervisors), John Merson (UNSW) and Peter Ampt (The University of Sydney), as well as a project manager, Crelis Rammelt (Blue Mountains World Heritage Institute), and myself. The results of the PRA and survey were published in a project report to RIRDC released in June 2011 (Merson et al. 2011) and were also presented to a stakeholder workshop held in Lithgow in November 2011, alongside the key results of the economic analysis (Chapter 6) and environmental analysis (Chapter 7). This stakeholder workshop helped to inform the discussion and conclusions presented in Chapters 5-7.
While I was involved in all stages of the project, the social analysis tasks for which I had primary responsibility were:
- Drafting the research grant applications to DAFF and RIRDC; - Drafting the initial project plan, budget and timeline; - Drafting questions for the PRA and survey to ensure consistency with thesis research questions and with Condobolin study; - Statistical analysis of survey results using Microsoft ExcelTM;
199 - Drafting the discussion of results, implications and recommendations sections of the June 2011 report; and - Presenting key results to the stakeholder workshop in November 2011.
5.2.1 Methodology
The methodology for the Participatory Rural Appraisal (PRA) was approved by the UNSW Human Research Ethics Advisory Panel for Arts, Humanities and Law on 24 May 2010, with the survey questions approved on 30 November 2010. These approvals covered the information statement and consent form given to each PRA participant (Appendix B), the PRA interview questions (Appendix C) and the landholder questionnaire (Appendix D).
The PRA involved 29 interviews with key informants undertaken by five pairs of interviewers over two days (30-31 August 2010), followed by a workshop in Lithgow on September 1st. The key informants were selected through consultation with the project partners: Hawkesbury Nepean CMA, Central West CMA, Lachlan CMA, Midwestern Regional Council, Lithgow City Council, Bathurst Regional Council and Oberon Shire Council. The location of the interviews are shown in Figure 5.8, with the interviewees consisting of: - 19 Landholders (11 commercial, 3 semi-commercial and 5 small non- commercial) - 6 Industry representatives (forestry, nursery and energy sectors) - 4 Environment group representatives - 3 Landcare coordinators - 3 Government representatives (council, CMA and NSW Government)
200
Figure 5.8: Location of interviews for PRA.
The PRA interview questions (Appendix C) covered many of the same issues as the Condobolin interviews, including background information, land use goals, sustainability concerns, experience with tree-growing, potential benefits and barriers, required level of return, desired level of land conversion and policy preferences. Unlike at Condobolin, where mallee was a clear focus, the Central Tablelands interviews included questions on which tree species might work in the region and whether bioenergy would be a major or minor product from the plantations. Due to the lack of familiarity with the idea of growing trees for bioenergy in the region, interviewees were presented with a “vision” document at the start of each interview (Figure 5.9). This vision was not designed to be overly prescriptive, but to highlight a range of possibilities for the region including plantations based on monocultures or mixed species, strips or blocks, for 100% bioenergy or with co-production with timber,
201 potential integration with other biomass sources (sawmill wastes, rradiata pine residues) and different bioenergy product options (electricity, biofuels).
Figure 5.9: “Vision” document presented at the start of each interview.
The PRA workshop attracted thirrteen attendees, including memberrs of the interview teams, representatives of partner organisations and two local landholders. The low turnout of interviewees meant that the main function of the workshop was to review the key issues identified by the interview teams and identify regional trends.
The results of the PRA, discussed in section 5.2.2, were used to narrow the case study region down to the local government areas (LGAs) of Bathurst, Oberon, Lithgow and Mid-Western, and to divide it into northern, southwestern and souutheastern sub-regions (Figure 5.10). For the purposes of the mail survey, the boundaries of the sub-regions were based on postcodes rather than LGA or CMA boundaries. The westernmost areas covered by the PRA (around Orange, Cowra and Molong) were excluded from the case study in order to make it more manageable and because the PRA iidentified a number
202 of ways in which these areas differed from the core tablelands area, including climate (lower rainfall and differing seasonality), land use (more cropping) and social trends (larger properties, less hobby farmers).
Figure 5.10: Sub-regions selected following PRA. Boundaries based on postcodes.
The landholder survey was sent out to 784 households, with 159 responses received for an overall response rate of 22% (after accounting for 59 surveys returned to sender). The majority of addresses were sourced from mailing lists provided by Hawkesbury- Nepean CMA (295 addresses) and Central West CMA (189 addresses), with these supplemented by sourcing 300 additional addresses at random from a commercial
203 mailing list (first filtered to exclude postcodes outside the region and addresses in the major towns of the region). The address lists were deleted following the mailout. The survey was mailed with a cover letter and an anonymous pre-paid return envelope. The questionnaire (Appendix D) consisted of 25 discrete questions divided into four parts: About yourself and your farm, About agroforestry for bioenergy, Making the vision a reality and About your region. In order to categorise landholders, respondents were asked for details such as their postcode, property size and major land use activities. The survey questions were designed to test assumptions emerging from the PRA and to allow comparison with the results of the Condobolin case study. An additional influence was a recent survey undertaken in the southwest slopes of NSW on landholder attitudes to carbon sequestration plantings, subsequently published in a report to the Cooperative Research Centre for Forestry (Schirmer & Bull 2011). Jacki Schirmer (Australian National University) provided a copy of that questionnaire, allowing some of the questions in our Central Tablelands survey to be designed to facilitate future comparison.
Of the full set of survey questions listed in Appendix D, the most relevant for this thesis are: - What is your experience with tree-planting or tree-cropping? (including details on commercial/non-commercial, aims, success rate and planting design). - Degree of agreement/disagreement with a range of statements regarding potential benefits of agroforestry. - Degree of agreement/disagreement with a range of statements regarding potential barriers to agroforestry. - What annual return would you require in order to consider agroforestry (same as current land uses, less, more or depends)? - What net return (income-expenditure) per hectare would be needed to take it up? - If you were to get involved, how much of your land would you think about turning over to agroforestry? - If you were to get involved, which type of land would you use for agroforestry? - Would you prefer block or strip plantings (block, strip or combination)?
204 - Degree of agreement/disagreement with a range of statements regarding implementation of agroforestry, particularly the location of sites (for growth rate, competing use, environmental benefit) and harvest rotations (1-5 years for bioenergy only, 15-30 years for timber and bioenergy, 70-100 year commitment for carbon sequestration). - Assuming the returns and the impacts on the landscape were the same, would it matter to you what the trees were used for (e.g. bioenergy, timber, woodchips, storing carbon)? - What tree species do you think could work for agoforestry involving bioenergy production in your region? - What kind of support scheme would be most effective in driving uptake? (financial support, knowledge support, research and development, price support or payment for ecosystem services).
The questionnaire also included questions on locations for bioenergy facilities, other sources of biomass that could be combined with agroforestry biomass and new infrastructure that may be required for a regional bioenergy industry involving agroforestry. Some questions attracted less than 159 responses due to respondents skipping questions.
The questions on benefits, barriers, implementation and support schemes asked respondents to indicate their reaction to a series of statements along a five-level Likert scale (Strongly Disagree, Disagree, Undecided, Agree or Strongly Agree). When recording the survey data, these responses were scored from 1 (Strong Disagree) to 5 (Strongly Agree). Respondents who gave no response were excluded from the calculations.
The question on which parts of land would be used for agroforestry employed categories from NSW rural land capability mapping (DIPNR 2004), namely land suitable for regular cultivation, land suitable for grazing with occasional cultivation, land suitable for grazing only, marginal land (rocky/steep with little grazing value) and land set aside for conservation purposes. NSW land capability mapping does not have a category called “marginal land (rocky/steep with little grazing value)”, but this term
205 was chosen as the best description for rural land capability classes 7 and 8, which include, respectively, “steep slopes, shallow soils and/or rock outcrop” and “cliffs, lakes or swamps and other lands unsuitable for agricultural and pastoral production” (Emery 1988). The support scheme question differed from that used in the Condobolin interviews in that the option of “establishment support” was subdivided into “financial support” and “knowledge support”. This approach was taken because the mail survey did not provide the same flexibility to ask follow-up questions as the semi-structured interviews at Condobolin.
Key results from the PRA and survey were presented to a stakeholder workshop held in Lithgow on 14 November 2011. This workshop helped to identify key issues and potential future directions and was influential on the discussion and conclusions sections of this chapter and Chapters 6 and 7. This workshop involved the following participants: x Mary-Rose Townsend, local landholder x Graeme Ross, local landholder x Mitchell Clapham, local landholder x Trevor Evans, local landholder x Vanessa Keyzer, Hawkesbury-Nepean CMA x Casey Proctor, Lachlan CMA x Kieran Hawker, Lachlan CMA x Clare Hamilton, Midwestern Regional Council x Grant F. Christopherson, Coordinator of Central West renewable energy precinct, NSW Office of Environment and Heritage (and landholder) x Stephen Schuck, Bioenergy Australia x Fabiano Ximenes, NSW Trade and Investment (forestry research) x Edward Frater, NSW Trade and Investment (state and regional development) x Sandy Booth, MalleeCondo and Total Catchment Management Service x Ted Hayman, Baradine Biofuels (and landholder at Baradine, northwest NSW) x Debbie Crawford, CSIRO x Tom Jovanovic, CSIRO
206 x Sandra Velarde, PhD Candidate, Australian National University (ANU) x John Merson, UNSW x Peter Ampt, The University of Sydney x Crelis Rammelt, Blue Mountains World Heritage Institute x Sarah Terkes, UNSW x Chanci King, Blue Mountains World Heritage Institute x Alex Baumber, UNSW
5.2.2 Results
As discussed in section 5.2.1 and shown in Figure 5.10, the case study area was broken up into three sub-regions based on the PRA results. Lithgow and Oberon were both placed in the southeastern (SE) sub-region due to similarities including high rainfall, a concentration of existing plantation forestry, high levels of remnant native vegetation and high levels of small non-commercial landholders. The PRA identified a potential opportunity to trial a cooperative agroforestry model in this sub-region, in which small properties would be grouped together and larger properties could contribute their less productive land and/or areas currently used for private softwood plantations. This subregion also features two of the most promising sites for future bioenergy facilities: the Oberon Timber Complex, where sawmill residues provide a complementary source of biomass, and Delta Electricity’s Wallerawang power station northwest of Lithgow, where biomass co-firing has been trialled. However, another issue highlighted in the PRA was that Delta Electricity has elected not to explore energy cropping in the areas close to Wallerawang, instead choosing to go 200 km farther west to the Forbes area, where the cost of land and the value of competing agricultural production is lower.
The southwestern (SW) sub-region is centered around Bathurst, the largest urban area in the case study region. In this sub-region, the PRA identified potential barriers to bioenergy-based agroforestry, including high land values resulting from the proximity to Bathurst and valuable grazing opportunities. However, a high level of past vegetation clearance and a need for windbreaks and salinity mitigation in some areas were highlighted as opportunities for agroforestry that could deliver environmental co-
207 benefits. Transport of biomass to Oberon or Wallerawang was a more common suggestion than the establishment of a bioenergy facility near Bathurst.
For the northern (N) sub-region, which includes Mudgee and Rylstone, the PRA identified four main landholder groups: small non-commercial landholders, innovative commercial farmers, more traditional commercial farmers and mining companies. The first two categories were considered more likely to participate in agroforestry involving bioenergy production, while the traditional commercial farmers were considered less likely. It was reported that mining companies have been purchasing land to act as buffers around mines and that agroforestry could be a low maintenance land use option for such land. No clear location for a bioenergy facility was identified for this sub- region.
The PRA found evidence of past native agroforestry trials in all three sub-regions, but the general perception was that no economically viable model had emerged. Agroforestry based on radiata pine was relatively common in the SE sub-region (including amongst some interviewed landholders) but was seen to pose a range of issues including a long wait for returns, difficulties in managing for premium wood production and difficulties competing with the larger-scale production from government-owned State Forests. A number of interviewees and workshop participants, particularly those with industry or government roles, highlighted the need for macroeconomic drivers for bioenergy, such as a higher price for Renewable Energy Certificates (RECs) and/or a carbon price. Although interviewers specified that the research was focused only on plantations and not native forests, a small number of interviewees suggested that biomass should be removed from areas of native forest and used for bioenergy. The arguments in favour of this were that it could reduce fire risk or improve timber productivity in the forest.
For the mail survey, results were segregated according to sub-region, property size and major land use. Respondents were divided into four landholding size categories: smaller than 40 ha, 40-100 ha, 100-850 ha and larger than 850 ha. These divisions were based on the minimum subdivision sizes permitted in the four LGAs (40 ha in Oberon and Lithgow, 100 ha in Bathurst and Mid-Western) and the minimum viable
208 size for a commercial farm at Oberon (850 ha), as determined by a 2008 land use analysis commissioned by Oberon Council (Insite Economic and Social Planning Pty Ltd 2008). Table 5.3 shows the percentage of respondents in each size class and the breakdown of land area by size class. While the majority of respondents had less than 100 ha, the total land area was dominated by landholders in the >850 ha class.
Table 5.3: Breakdown of survey respondents according to land size class. n=159 Property Size Percentage of survey respondents Percentage of land held Class in each class (note that 4% gave no by survey respondents in property size) each class <40 ha 30% 0.6% 40í100 ha 21% 2.0% 100í850 ha 32% 19% >850 ha 13% 78%
Figure 5.11 shows the major land use activities identified by survey respondents. Two main activities emerged: commercial grazing (listed as a major use by 47% of respondents) and lifestyle/hobby farming (listed by 35%). There was a small degree of overlap between these groups, with 6% listing both activities as a major land use. The next most common major land uses were conservation of remnant native vegetation (18%) and environmental plantings (8%), but most of these respondents also listed either commercial grazing or lifestyle/hobby farming as a major land use. Commercial forestry was selected as a major land use by less than 1% of respondents and as a minor land use by 4%.
209
Figure 5.11: Distribution of major land use amongst survey respondents. n=159
Land use patterns varied by sub-region (Figure 5.12), with commercial graziers being more dominant in the north and lifestylers forming a slight majority in the southwest. The relationship between major land use and property size was even more pronounced (Figure 5.13), with increasing property size associated with an increase in commercial grazing and a decrease in lifestyle/hobby farming.
70% Commercial grazing 60%
Commercial 50% cropping
40% Lifestyle and hobby farming 30% Conservation of 20% remnant native vegetation
10% Environmental plantings
0% SE SW N
Figure 5.12: Distribution of major land use activities by sub-region. n=124
210 100% Commercial 90% grazing
80% Commercial 70% cropping
60% Lifestyle and 50% hobby farming
40% Conservation of 30% remnant native vegetation 20% Environmental 10% plantings
0% <40ha 40-100ha 100-850ha >850ha
Figure 5.13: Distribution of major land use activities by property size. n=152
While the trends shown in Figures 5.12 and 5.13 largely reinforced the PRA findings, the higher proportion of lifestylers in the southwest compared to the southeast was somewhat surprising.
Experience with tree-planting also varied by sub-region, with commercial tree-planting experience much more common in the southeast (26%; n=159) compared with the southwest (2%) and north (3%). This is likely to reflect the concentration of the existing plantation sector in that sub-region. Non-commercial tree planting was also highest in the southeast (87%), although the dominance over the southwest (47%) and north (70%) was not as pronounced. Interestingly, the level of experience with tree- planting did not vary greatly by landholder type, with 21% of commercial graziers and16% of lifestylers having engaged in commercial tree-planting. The figures for non-commercial planting were 84% and 82% respectively.
With regard to the potential benefits of agroforestry, respondents showed higher levels of agreement with statements relating to environmental benefits (mean 3.90 on the Likert scale) than with statements relating to economic benefits (3.69) or social
211 benefits (3.67)22. As shown in Figure 5.14, the four highest-rated statements all related to environmental benefits (windbreaks, wildlife, off-property environmental benefits and salinity). The highest-rated economic benefit from agroforestry was actually an indirect benefit (windbreaks) rather than a more direct economic benefit such as diversifying income streams (fifth overall). All benefit statements had a mean score greater than 3, indicating that the level of agreement with each statement was higher than the level of disagreement.
While Figure 5.14 shows that climate change mitigation and adaptation did not rank as high priorities for agroforestry, this was not due to a lack of belief in human-induced climate change. 53% of respondents agreed or strongly agreed with the statement that “human use of fossil fuels is changing the climate” compared with 18% who disagreed or strongly disagreed. The subset who agreed or strongly agreed with this statement ranked the statements about agroforestry and climate change benefits no differently to the overall group (i.e. mitigation was still the 7th highest-rated benefit and adaptation was 10th).
The pattern of responses to statements regarding barriers to agroforestry (Figure 5.15) is the opposite of the pattern for benefit statements shown in Figure 5.14. Economic barriers attracting the highest level of agreement (3.44 mean score), followed by social barriers (3.23). Environmental barriers had a mean score of 2.89, meaning that, on balance, landholders were disinclined to agree that these were in fact barriers. Overall, 79% of respondents gave a higher average score across all benefits than they did across all barriers (n=153), indicating a positive attitude to agroforestry overall.
22 1= Strongly Disagree, 2= Disagree, 3=Undecided, 4=Agree and 5=Strongly Agree.
212
Figure 5.14: Mean scores for benefits of agroforestry. n=155. Error bars indicate a 95% confidence interval (CI) around the mean. 213
Figure 5.15: Mean scores for agroforestry barriers. n=156. Error bars show 95% CI. Full version of each statement in Appendix D.
The risk of regulatory changes that could prevent future harvest was perceived by survey respondents to be the greatest barrier to agroforestry development in the Central Tablelands. As with the Condobolin case study, this factor was classed as a social barrier, reflecting views expressed in the PRA that such changes (e.g. to the Native Vegetation Act 2003) are often politically motivated and reflect differing social values between urban and rural voters.
When asked “If you were to get involved, how much of your land would you think about turning over to agroforestry?”, 66% of survey respondents (n=159) nominated an area of their land. Both the amount of land and the proportion of land nominated varied by property size class (Figure 5.16). Landholders in the <40 ha, 40-100 ha and 100-850 ha size classes nominated similar proportions of land for conversion (20-30% of the total land held by respondents in those size classes23). However, landholders in the >850 ha class nominated a much lower figure of 2.6%. The overall percentage of land nominated was 7.6%, reflecting the fact that landholders in the >850 ha size class accounted for the majority of all land held by survey respondents. Even though they nominated the lowest proportion of their land, landholders in the 100-850 ha size class emerged as the most significant potential contributors to a regional biomass industry, accounting for 65% of the total land nominated by all respondents.
23 These figures were calculated by adding all land nominated in each size class and dividing by the total land held in that size class. Landholders who did not state a property size were excluded.
214
Figure 5.16: Land nominated for conversion to agroforestry by property size class. Land nominated is shown as a percentage of all land held by survey respondents in each class. n=152
A comparison of the survey data with cadastral (property unit) data provided by the NSW Land and Property Management Authority (LPMA) indicates that large landholdings (>850 ha) may be over-represented in the survey (Table 5.4). Such properties make up 78% of all land in the survey compared with only 28% of all land in the LPMA cadastre. If large landholders with low interest in agroforestry are indeed over-represented in the survey data, it could mean that the overall land conversion figure of 7.6% shown in Figure 5.16 is an under-estimate of true landholder interest. Table 5.4 shows corrected figures, calculated by dividing the LPMA cadastral data into the same size classes as the survey data, after first excluding any properties that were not private rural land24. This was undertaken using the ArcGIS 10 Geographic Information System (GIS) software package. This attempt to correct for the potential survey bias towards large properties delivers a corrected land conversion rate of 19.2%.
24 Areas excluded were: National Parks, Nature Reserves, State Conservation Areas, State Forests, Vacant Crown Land and Reserved Crown Land, plus all land uses classed as urban, transport, power generation or mining and quarrying under NSW LUMAP land use mapping NSW Government (2007).
215 Table 5.4: Overall land conversion rate corrected from survey data. Survey results adjusting based on Land and Property Management Authority (LPMA) cadastral data.
Property size class
<40 ha 40í99 ha 100í850 ha >850 ha All
Proportion of surveyed landholders’ land falling into each size class (%) 0.6 2.0 19.1 78.3 100
Proportion of land falling into each size class according to the LPMA cadastral data (%) 5.5 9.4 57.0 28.1 100
Land conversion rates from survey (% of total land held in each class) 28.4 22.3 26.0 2.6 7.6
Proportion of land potentially converted to agroforestry if the conversion rates for each size class from the survey are applied to the property size distribution found in the cadastral data (%) 19.2
While Table 5.4 indicates that overall landholder conversion rates may be much higher than 7.6%, this figure carries its own sources of error. In particular, the cadastral data is divided into property units based on unique Lot and Deposited Plan numbers rather than according to the owner or manager of the property. Based on anecdotal reports from the PRA, it is quite common for large landholders to hold multiple property units. Such holdings would be classed as large (>850 ha) in the survey but appear as medium (100–850 ha) in the cadastre. If this practice is indeed widespread, it may be more appropriate when analysing cadastral data to apply the low conversion rate assumption of 2.6% (found for large properties in the survey) to medium-sized properties (100-850 ha), rather than the much higher conversion rate of 26% used in Table 5.4. Overall, this means that, while a conversion rate of 7.6% may be an under-estimate of landholder interest, 19.2% is likely to be an over-estimate.
216 In response to the survey question on desired returns from agroforestry, 50% of respondents (n=159) said they would require a greater net average annual return per hectare than their current land use in order to switch, while 19% said they would require the same return. 6% said they would accept a lesser return and 16% chose “depends”, with the degree of environmental co-benefits being the most commonly- cited consideration25. These figures varied by sub-region (Figure 15.17), with landholders in the north more likely to require greater returns and those in the southeast more likely to accept lesser returns. Lifestylers were more than twice as likely as commercial graziers to accept lesser returns (9% vs. 4%) or to select “depends” (24% vs. 11%). The proportion of landholders prepared to accept lesser returns than their current land use was much lower for this case study than amongst the landholders interviewed at Condobolin.
70% % saying same return 60% % saying greater % saying lesser % saying depends 50% not answered
40%
30%
20% % of respodents in sub-region in respodents of % 10%
0% SE SW N
Figure 5.17: Return required from agroforestry relative to current land use, by sub-region. n=159
As with the Condobolin interviews, the majority of respondents were not prepared to nominate a dollar figure for the net average annual return per hectare they would
25 9% of survey respondents gave no answer or said they weren’t interested.
217 require to adopt agroforestry. Only 37% of respondents nominated a figure, with the average being $1043/ha. The sub-regional averages varied from $996/ha in the southeast to $644/ha in the north to $305/ha in the southwest26. Commercial graziers nominated $1365/ha on average compared to $631/ha for lifestylers. These figures are discussed further in the economic analysis in Chapter 6.
When asked which type of land they would use for agroforestry27, survey respondents showed a preference for less productive land (Figure 5.18), with 51% selecting “marginal land (rocky/steep with little grazing value)”, 38% selecting “land suitable for grazing only” and 35% selecting “land suitable for grazing and occasional cultivation” (multiple categories could be selected). In contrast, survey respondents reported that the most widespread land type was “land suitable for regular cultivation”, making up 36% of all land they held. Only 7% of land was reported to be marginal land28. Interestingly, 23% of respondents said they would consider agroforestry on “land set aside for conservation purposes”. This could mean that they see agroforestry and conservation as compatible or that they feel such land should cease to be set aside for conservation.
26 A number of landholders were excluded from the sub-regional analysis due to not providing a postcode. 27 Land types were based on NSW rural land capability classes (DIPNR 2004). “Marginal land (rocky/steep with little grazing value” was used in the survey as a description for rural land capability classes 7 and 8. 28 These figures were calculated by adding up the land listed in each land class by each landholder who responded and dividing this by the total area of land listed by survey respondents.
218
Figure 5.18: Preferred land classes for agroforestry vs. distribution of land classes. The y-axis shows the land classes nominated for conversion to agroforestry by survey respondents, while the x-axis shows the occurrence of each class across all surveyed properties (as reported by survey respondents).
In terms of plantation design and implementation, survey respondents showed more interest in environmental impacts than economic factors. There were higher levels of agreement with statements about locating agroforestry to maximise biodiversity (3.76 mean Likert score) and for erosion or salinity control (3.96) than for statements about choosing sites where growth rates were highest (3.47) or the value of competing land uses was lowest (3.47). A combination of blocks and strips was the most popular design strategy, with 55% of respondents (n=159) preferring this over either blocks alone (preferred by 21%) or strips alone (preferred by 8%). Similarly, mean Likert scores were higher for a combination of tree crop rotations that could produce both timber and bioenergy (3.68) compared to short-rotation only (3.61) or long-rotation only (3.21). The statement that “I would commit to agroforestry for 70-100 years if it
219 meant extra income from carbon credits” attracted an average score of 3.40, indicated more agreement than disagreement (3.60 for lifestylers and 3.28 for commercial graziers).
When asked about potential agroforestry species suitable for the region, the majority of survey respondents were unable to suggest any. From those who did make suggestions, the most commonly cited species (including PRA responses) were: Eucalyptus melliodora (yellow box), E. viminalis (manna gum/ribbon gum), E. globulus (Tasmanian blue gum), E. camaldulensis (river red gum), Acacia spp. (particularly A. dealbata – silver wattle) and Casuarina spp. Although the focus was on native agroforestry, Pinus radiata (radiata pine) received several mentions. 65% of respondents said that it would not matter to them which products were produced from agroforestry, assuming that returns and local environmental impacts were the same. Of the 21% who said that it would matter, the most common comments were against woodchips (10 respondents) and in favour of carbon sequestration (7 respondents).
With regards to policy options to support agroforestry, respondents gave all five options a mean Likert score greater than 3.0, indicating that they were more likely to be effective than ineffective. However, the most preferred option was financial support for upfront establishment, followed by knowledge support, research and development, payment for ecosystem services and, lastly, price support for products harvested (Figure 5.18). Based on the 95% confidence intervals shown in Figure 5.19, the difference between upfront financial support and price support is statistically significant.
220
Figure 5.19: Mean Likert scores for potential agroforestry support schemes. Error bars show 95% confidence intervals.
The order of policy preferences was the same amongst both lifestylers and commercial graziers (Figure 5.20). However, commercial graziers gave higher scores for each support option on average than lifestylers, indicating a greater level of interest in obtaining support overall. The policy preferences expressed were also very similar to those found in the Condobolin interviews, with the implications discussed in section 5.3.
Figure 5.20: Mean Likert scores for potential support schemes by landholder type. Error bars show 95% confidence intervals.
221 5.3 Discussion
This section discusses the results from the two case studies in relation to the five research questions outlined in Chapter 4. While comparisons are made between the two case studies where possible, caution is required due to the differing nature of the two groups, with a small group of interested landholders at Condobolin and a much larger group in the Central Tablelands representing a broader cross-section of landholders.
What bioenergy options involving woody energy crops may be viable in the case study regions?
The Condobolin case study is focused narrowly on the use of blue mallee (E. polybractea), which most interviewees were confident could be grown successfully in the region based on previous trials at the Condobolin Agricultural Research Station and commercial plantations at West Wyalong. Of the species identified in the Central Tablelands interviews and survey, E. viminalis (manna gum), E. camaldulensis (river red gum) and E. globulus (Tasmanian blue gum) have previously been identified as potential bioenergy species due to their high productivity (Bennell et al. 2009) and the former two species are well-suited to the climatic conditions found in the tablelands (Stirzaker et al. 2002). While E. globulus is generally considered more suited to the winter-dominated rainfall regimes of southern Australia, the subspecies E. globulus bicostata is considered a potential plantation species for drier areas with more uniform rainfall (Booth & Ryan 2008). Other species that have been cited in previous studies were not mentioned at all in the PRA or survey, such as E. cladocalyx (sugar gum), cited by Bennell et al. (2009) for bioenergy potential, and E. nitens (shining gum), which showed medium-high productivity in parts of the Central Tablelands in modelling by Booth et al. (2007).
Landholders from both case study sites showed a general lack of concern about which products would be produced from agroforestry, provided that returns were the same. Electricity generation was the most commonly mentioned bioenergy option in interviews at both sites, followed by solid fuels (pellets, briquettes) and liquid fuels (ethanol, bio-crude). With regards to potential processing centres, Condobolin was the
222 main focus for that case study region, while Oberon and Wallerawang were the main sites mentioned in the Central Tablelands. Each of these bioenergy options is assessed further in Chapter 6 (economic analysis).
The median amounts of land nominated for conversion to agroforestry at Condobolin (5% initially, 9% ultimately) were similar to the overall level of land nominated in the Central Tablelands survey (7.6% of total land held). However, while the Condobolin results are more likely to be an over-estimate of landholder interest, due to the interviews being targeted at landholders most interested in mallee, the Central Tablelands results appear to be an under-estimate when compared with cadastral data (due to an over-representation of less interested larger landholders). Further research with larger sample groups and common methodologies would be required to determine which region has a higher level of overall interest in bioenergy-based agroforestry.
In terms of plantation design options, both case studies revealed desires for a combination of blocks and strips, depending on specific landholder circumstances. Low-productivity land was generally preferred for agroforestry, but there was a substantial minority of landholders at both sites who were prepared to consider plantations on moderately productive land. Preferences for using less productive land and only partial conversion to agroforestry are consistent with the plantation strategies found to have higher levels of community acceptance in WA and Tasmania by Williams (2009a, 2009b). The emphasis placed on being able to scale up production over time (particularly at Condobolin) reinforces the arguments of Rogers (2003) and Pannell et al. (2011) that trialability is a key factor in the adoption of innovations.
The Central Tablelands survey revealed a preference for a mixture of species with differing harvest rotations and a mix of blocks and strips. At Condobolin, a number of different plantation styles were proposed, but the focus was on a single tree species, E. polybractea (blue mallee). Row spacing was a key design issue for Condobolin, with some landholders wishing to encourage grass growth between rows to increase rainfall infiltration and others wishing to minimise such growth to prevent competition for resources. Issues relating to land availability, mixed species plantations and mallee row spacings are explored further in Chapter 7 (environmental analysis).
223
What economic and non-economic benefits can woody energy crops provide for landholders in the case study regions?
Perceptions of benefits differed between the case study sites, with the Condobolin group much more likely to cite economic benefits and the Central Tablelands group assigning the highest overall ratings to environmental benefits. In part, this may reflect the fact that the Condobolin group was formed by commercial landholders who were actively looking for new economic opportunities following years of drought, while the Central Tablelands survey group had a higher proportion of landholders who were not dependent on the land for their primary income. Another factor could be the differing degree to which bioenergy-based agroforestry has been explored in each case study region to date, with this idea more likely to be new to landholders in the Central Tablelands.
Results from both case studies cast doubt on the assumption that landholders will always require an average annual return that is at least equivalent to their current land use in order to consider adopting a new innovation such as agroforestry. At Condobolin, only 25% of those interviewed said they would require a return that was greater or the same, while in the Central Tablelands this figure was 69%. While the Condobolin sample group was drawn from those landholders most interested in mallee and is not representative of the broader farming community, these results do highlight the existence of a cohort of landholders at both sites who may be responsive to factors such as environmental co-benefits, reduction of risk profile and compatibility with other land use practices. All of these factors were cited by Pannell et al. (2011) as factors that can contribute to the relative advantage of an innovation alongside relative financial returns. The issue of return relative to current land use is analysed further in Chapter 6 (economic analysis).
Windbreaks/shelterbelts were the most commonly cited environmental benefit from agroforestry at both case study sites. Habitat for biodiversity and salinity mitigation were rated highly in the Central Tablelands, but not at Condobolin. Protecting land from water erosion was a medium-ranked environmental benefit at both sites. The
224 Condobolin sample group showed a strong interest in the potential social benefits from mallee cropping such as providing jobs and revitalising businesses in the town. The Central Tablelands PRA did not reveal the same level of interest in regional job creation, with a range of existing job opportunities cited, including tourism, timber processing, mining services and higher education.
In the Central Tablelands, lifestylers may present a better opportunity than graziers for the adoption of agroforestry that has conservation benefits due to their greater willingness to accept lesser returns and their greater interest in non-economic benefits. However, they may also pose challenges due to the smaller amounts of land they hold and the diversity of environmental goals expressed in the survey.
How could the establishment of woody energy crops contribute to regional NRM goals?
For both case studies, the alignment between landholder objectives and the regional NRM goals cited in Chapter 4 was strongest in relation to landscape protection from wind and water erosion. The greater focus on salinity mitigation amongst landholders in the Central Tablelands corresponds to a greater focus on this issue in the NRM plans that cover this region (Central West Catchment Management Authority 2007, Hawkesbury-Nepean Catchment Management Authority 2007). Restoring habitat for biodiversity attracted greater attention in the Central Tablelands than at Condobolin, despite being a priority in the NRM plans for both areas.
As discussed in Chapter 4, climate change adaptation has increasingly become a regional NRM focus in NSW, with a move towards a planning approach based on ecological resilience. However, climate change adaptation was not mentioned in the Condobolin interviews and rated poorly as a potential benefit from agroforestry in the Central Tablelands. There are a number of possible explanations for this. Landholders may not consider climate change to be a significant risk to them, may not feel that agroforestry is a good climate change adaptation strategy or simply may not have thought about the issue in depth. At Condobolin, many landholders did associate mallee cropping with adaptation to drought and climate variability, just not to climate
225 change per se. This could be related to the general ambivalence towards climate change science. However, in the Central Tablelands, climate change adaptation rated poorly as a driver for agroforestry despite the fact that the majority believed that fossil fuel use is changing the climate. Other benefits with clear implications for climate change adaptation did attract relatively high ratings in the Central Tablelands, such as provision of habitat (which can improve species migration) and protection against erosion (important under more extreme weather events).
The climate change adaptation results may indicate that case study landholders do not have a strong understanding of what may be needed for climate change adaptation or do not view it as a stand-alone issue separate from sustainable land management. Hogan et al. (2011) concluded from a survey of almost 4000 Australian farmers that adaptation actions were not correlated with belief in climate change, but rather with a planned approach to risk management and a broader desire to adopt sustainable practices. For landholders with doubts about climate change science, an effective way to encourage appropriate adaptation may be to focus not on climate change per se but rather on the adoption of sustainable land use practices to manage risk in a variable climate.
Climate change mitigation through agroforestry was viewed more favourably in the Central Tablelands than at Condobolin, as evidenced by the divergent attitudes towards making a 100-year commitment in order to earn carbon credits. However, there has not been as much actual experience with carbon plantings in the Central Tablelands as there has been around Condobolin, where issues such as the loss of flexibility and control over land were presented as major barriers. The negative view of growing mallee for carbon at Condobolin reinforces the argument of Pannell et al. (2011) that flexibility of future land use can be an important factor in determining the relative advantage of an innovation. The preference for a community-based model of bioenergy production from mallee over a carbon planting model involving an external company also reinforces Williams’ (2009a) finding that community attitudes to plantations are often more favourable when plantations are owned by an individual landholder and processing of products occurs within the local community.
226 The question of how agroforestry plantations could contribute to NRM goals relating to biodiversity, salinity, soil protection and climate change is assessed further in Chapter 7 (environmental analysis).
What barriers exist for the adoption of new land uses involving bioenergy production and the delivery of NRM goals?
Both case studies showed a similar pattern, with economic and social barriers outweighing environmental barriers such as fire risk, pest animals and competition for water. Economic barriers such as uncertainty about returns and high investment costs came out ahead of social barriers (especially regulatory change) at Condobolin, while this order was reversed in the Central Tablelands. Pannell et al. (2011) highlight trialability as a vital factor in helping landholders deal with uncertainty. Short rotations for tree crops, which can enhance trialability, were favoured at both sites. Research and development can also assist with trialability. This can be funded either by government, such as the mallee production trials at the Condobolin Agricultural Research Station during the 1990s (Milthorpe et al. 1998), or by industry, such as Delta Electricity’s trials around Forbes (Delta Electricity 2010). The ability to scale up a regional bioenergy industry over time is also important, as it allows landholders to observe results before committing more land.
Concerns about regulatory change at both case study sites are reasonable based on past experience. Although the NSW Plantations and Reafforestation Code has been designed to provide certainty of future harvest, it is still possible that future changes could create additional restrictions for landholders. Furthermore, a number of regulatory changes over the past decade have contributed to this sense of uncertainty, including: x The introduction of the NSW Native Vegetation Act 2003 and its associated rules and definitions around clearing, regrowth and private native forestry. x The 2003 ban on the use of native forest biomass for electricity generation in NSW. x The tightening of forestry MIS tax rules in 2007 and the collapse of MIS companies Timbercorp and Great Southern in 2009 (Williams & Hopkins 2009).
227 x Numerous changes to the Renewable Energy Target (RET) since its introduction in 2001. These include changes to the definitions of “energy crops” in 2007 and “wood wastes” in 2011, REC price volatility related to the Rudd Government’s 2007 decision to expand the target after the Howard Government previously decided not to and the influence of “phantom” RECs from small-scale solar, which were seen to be depressing REC prices before being separated out in 2011 (Buckman & Diesendorf 2010). x The continued uncertainty around a carbon price, including the abandonment of the Carbon Pollution Reduction Scheme (CPRS) in 2010 and the announcement of a fixed-price scheme to commence in 2012, which the federal opposition has threatened to scrap if elected in 2013.
Chapter 6 provides economic analysis concerning product prices, investment costs and uncertainty, while Chapter 8 explores policy measures that could be used to deal with the barriers identified. Other potential barriers require further investigation, particularly because both case studies were heavily focused on landholders. Some local environmental groups interviewed as part of the participatory rural appraisal (PRA) in the Central Tablelands expressed opposition to plantation expansion. Previous experience in other regions such as Tasmania and southwest WA also suggests that opposition to plantations can often emerge from outside the landholder community (Tonts & Schirmer 2005, The Wilderness Society Tasmania 2010). A more comprehensive public participation process is required at both sites before policy directions are finalised.
What policy measures could be employed to promote and guide such land uses and develop a regional bioenergy industry (if this is considered desirable)?
Landholders in both case studies showed similar preferences when asked about potential support measures for bioenergy-based agroforestry. Establishment support was ranked first at both sites, with financial support being a more important consideration than knowledge support. Market development and payments for ecosystem services (e.g. carbon, biodiversity) attracted moderate support at both sites. However, the most notable contrast in each case study was between the strong landholder preference for establishment support and the focus of certain government
228 and industry interviewees on price support mechanisms such as the Renewable Energy Target (RET) and carbon price. Reasons cited by landholders for their scepticism towards price support include the progressive removal of price support for Australian agriculture (e.g. wool floor-price, single export desk for wheat) and the uncertainty surrounding mechanisms such as the RET and carbon price.
Measures such as the RET and carbon price have an important role to play in stimulating demand for bioenergy products, but there is also a clear need to focus on complementary support for upfront establishment, including ways that price support for bioenergy products can be translated into upfront support for landholders. The model employed by Delta Electricity at Forbes provides one such example, whereby Delta covers the costs and risks of plantation establishment and hopefully profits from the generation of renewable energy if the project succeeds (Delta Electricity 2010). An MIS bioenergy scheme is another option, whereby tax deductions for upfront investment could help to offset the risk associated with the wait for returns. Other ideas could be drawn from the solar photovoltaic sector, where householders are able to earn credits upfront at a fixed price under the Small-scale Renewable Energy Scheme (SRES). This allows them to offset the cost of installation without having to take on the risk of future price fluctuations or regulatory changes. These policy options are considered further in Chapter 6 (economic analysis) and Chapter 8 (policy development).
5.4 Conclusion
The results of the social analysis presented in this chapter have important implications for the policy development framework presented in Chapter 8. The goals, priorities, strategies and concerns identified through the interviews, workshops and survey are important for framing policy problems and understanding how landholders and other key stakeholders are likely to respond to policy interventions. The case study results shows that the adoption of bioenergy-based agroforestry has much in common with other agricultural and forestry practices, including the importance of relative advantage and trialability. If support programs are to be successful in promoting landholder adoption, it is essential to consider how these programs can facilitate trialability and
229 ensure that on-ground establishment support is considered rather than relying only on pricing mechanisms such as the RET and carbon price. These issues are incorporated into the policy development and recommendations in Chapter 8.
The case study results highlight that landholders are diverse in terms of property size, land use activities, financial situation, environmental goals and attitude to risk. Furthermore, the case study landholders did not all define relative economic advantage in the same way. When considering a new innovation such as bioenergy-based agroforestry, many were prepared to accept a lower return than they receive for their current land uses. Even where innovations appeared similar, such as growing mallee for bioenergy and growing mallee for carbon sequestration, they were viewed very differently by some case study landholders due to their different impacts on enterprise risk and land use flexibility. These results have implications for the economic analysis of such land use options, which is the focus of the following chapter.
In addition to their economic implications, the results presented in this chapter also have implications for Chapter 7 (environmental analysis). Stakeholders at both sites identified a range of potential environmental benefits that could flow from bioenergy- based agroforestry, but few of these suggestions were based on actual experience with commercial agroforestry. Research is required to better understand the potential environmental impacts of bioenergy-based agroforestry, including whether environmental co-benefits are predominantly private, as may be the case for windbreaks, or whether they could have broader implications, such as salinity mitigation, habitat for biodiversity and carbon sequestration. Further social research is also needed across a diverse range of landholders and other stakeholders at both case study sites to gain further understanding of some of the important issues identified in this chapter, including how trade-offs might be made between factors such as average annual return per hectare, income consistency, land use flexibility and environmental co-benefits. This research could assist with the development of case studies in other parts of Australia, as many of the same issues are likely to emerge in other locations where revegetation, agroforestry and bioenergy intersect.
230 Chapter 6: Economic Analysis
The economic analysis presented in this chapter consists of two main elements: demand-side analysis (section 6.1) and supply-side analysis (section 6.2). The demand- side analysis explores the economic viability of a range of bioenergy product options in order to determine the prices that could be paid to landholders for their biomass. The same set of bioenergy options have been modelled for each case study region, with differences between the two regions such as transport distance also factored into the demand-side modelling. The supply-side analysis involves the calculation of potential net returns from bioenergy-based agroforestry in each case study region and a comparison of these returns to the returns that could be expected from typical agriculture in each region.
The analyses presented in this chapter have primarily been designed to inform two of the five key research questions presented in Chapter 4: Q1: What bioenergy options may be viable in the case study regions? and Q5: What policy measures could be employed to promote and guide such land uses?
The consideration of Q1 also incorporates elements of Q2 (benefits from bioenergy- based agroforestry) and Q4 (barriers to bioenergy-based agroforestry). A range of policy interventions have been factored into the analysis in sections 6.1 and 6.2, drawing on the key policy measures discussed in Chapter 4, including grant programs, carbon pricing, the Renewable Energy Target (RET), fuel excise and tax breaks for Managed Investment Schemes (MIS). Section 6.3 provides a discussion of the results from sections 6.1 and 6.2 and an assessment of their implications for the key research questions. Key results of the analysis for the Central Tablelands case study region have also been provided to the Rural Industries Research and Development Corporation and will be published in a forthcoming report (Baumber, Rammelt, Merson & Ampt forthcoming 2012).
231 6.1 Demand-side Analysis
The aims of the demand-side analysis presented in this section are to determine, for a range of bioenergy options at each case study site: 1. The breakeven price (i.e. maximum price payable before costs start to exceed revenues) that could be paid by a bioenergy facility for each tonne of chipped green biomass delivered to the factory gate; and 2. The biomass scale required for each bioenergy option in green tonnes per year (gt/yr).
A range of different biomass conversion technologies have been considered, with each option assuming a single bioenergy facility at either Condobolin, using mallee biomass, or Oberon, using biomass from native hardwood species. Oberon has been selected as the most appropriate site for the Central Tablelands case study region due to the presence of existing biomass supplies from wood processing that could complement biomass supplies from agroforestry. All costs relating to the construction and operation of a bioenergy facility are considered to be demand-side factors and are included in this section. All costs associated with harvesting, chipping and transporting biomass to the bioenergy facility are included in the supply-side analysis in section 6.2.
The breakeven prices determined through this analysis provide an indication of the economic viability of each bioenergy option. The first test of economic viability is whether a bioenergy option is able to deliver a positive breakeven biomass price, indicating that income from product sales would exceed all capital and operating costs apart from the cost of biomass. The second test of economic viability is whether a bioenergy option can offer a breakeven biomass price that is equal to, or higher than, current biomass prices in the NSW Central West. For this purpose, a biomass price of $35-40 per green tonne (gt) has been used as an indicative market price. This is based on analysis undertaken by Ximenes et al. (2012) of existing markets for plantation biomass in the Central Tablelands, including biomass used for electricity generation at Delta Electricity’s Wallerawang power station.
232 6.1.1 Methodology
Six bioenergy options were analysed across three broad categories: solid fuels, liquid fuels and electricity. The six options were: - Wood pellets for export to either Europe or Japan (solid fuel); - Compressed wood briquettes for Australian residential wood-heaters (solid fuel); - Ethanol produced from cellulosic material via enzymatic conversion for the domestic road transport market (liquid fuel); - Thermochemical conversion of biomass to produce either renewable diesel29 or aviation fuel (liquid fuel); - Electricity generation using biomass only (electricity); and - Electricity generation through the co-firing of biomass at an existing coal-fired power plant (electricity).
These options were selected based on the stakeholder consultation presented in Chapter 5 as well as previous studies exploring bioenergy from plantation biomass in: x high-rainfall regions of Australia (e.g. Forest and Wood Products Australia 2007, Polglase et al. 2008, O'Connell et al. 2009b, Rodriguez et al. 2011a); and x low to medium rainfall regions of Australia (e.g. van Bueren & Vincent 2004, Enecon 2007, Total Catchment Management Services 2008, Bennell et al. 2009).
The six options vary in terms of their level of technological readiness, previous application within Australia and potential market size. The availability and quality of data on production costs and market prices for each bioenergy option is highly variable. These sources of uncertainty are discussed for each bioenergy option.
A basic economic model was created using Microsoft ExcelTM for each bioenergy option, including key factors such as capital costs, operating costs and expected prices for energy products. Costs were based on relevant Australian and international
29 Renewable (or synthetic) diesel differs from biodiesel in that it is refined from a bio-crude rather than being produced through the transesterification of vegetable oil or animal fat.
233 bioenergy studies. In addition to the base case model constructed for each option, sensitivity analyses were undertaken to assess the impacts of changes in key parameters such as production costs, price factors and policy interventions. The policy options selected for modelling were dependant on the nature of the bioenergy option in question and were draw from the range of existing and potential policy measures discussed in Chapters 2, 3 and 4. Costs and prices for each model are reported in Australian dollars (AUD) unless otherwise noted, with July 2011 exchange rates used to convert overseas costs and prices to AUD.
The basic model for each bioenergy option assumed that 100% of biomass was used for bioenergy. Additional modelling was also undertaken to determine the impact of co-producing either eucalyptus oil (Condobolin) or pulpwood for paper (Central Tablelands) alongside bioenergy. Other possible co-products, such as sawlogs, biochar (via pyrolysis) or high-value chemicals (via a biorefinery) were not assessed due to a lack of established markets and/or cost data. Co-generation of electricity and heat was considered under the co-production model for biomass-fired electricity and eucalyptus oil at Condobolin, in which waste heat from electricity generation was assumed to be used for eucalyptus oil distillation.
For all models, it was assumed that green biomass would contain 50% dry matter (DM), following data for blue mallee reported by Total Catchment Management Services (2008) and data for native hardwood species reported by O’Connell et al. (2009b). Another factor made consistent across all models in order to facilitate comparison was the required rate of return on capital investment. The default rate applied was 7.5% per annum over 20 years, unless otherwise noted in the model parameters. This represents a mid-range rate of return compared to other Australian bioenergy studies (Table 6.1).
234 Table 6.1: Required rates of return used in previous Australian bioenergy studies. Source Bioenergy option Rate of Period of Capital return amortisation recovery (%) (years) factor CSIRO (2011c) Biomass electricity 7 30 0.08 Rodriguez et al. Cellulosic ethanol 7.5 30 0.09 (2011a) Graham et al. (2011) Biofuels in 7 15 0.11 aviation Enecon (2007) Wood pellets 10 20 0.12
The selected rate of return produces a capital recovery factor (CRF) of 0.098, meaning that the annual capital costs included in each model are equal to 9.8% of the initial capital investment. CRF was calculated using Equation 6.1 from Enecon (2007).
Where: CRF = capital recovery factor R = required rate of return (%) N = number of years over which return is required
Solid fuels: wood pellet model
The wood pellet model assumed pelletisation of biomass at either Condobolin or Oberon for export to either Europe or Japan. The factory gate price payable for one green tonne (gt) of chipped biomass was determined using Equation 6.2.
235 Where: bp = biomass price payable at factory gate (AUD/gt)
pp = pellet price obtainable on export market (local currency/t)
er = exchange rate (local currency/AUD)
sc = shipping costs for pellets (AUD/t)
hc = port handing costs for pellets (AUD/t)
tc = transport to port costs for pellets (AUD/t)
oc = operating costs (excl. feedstock) for pellet production (AUD/t)
cc = capital costs for pellet production (AUD/t) r = conversion rate (t pellets/gt biomass)
The base case assumed annual pellet production of 50,000 t/yr (e.g.7 t/hr for 24 hours/day, 300 days/yr), which represents medium to large scale production by European standards (Enecon 2007, Nilsson, Bernesson & Hansson 2011). Production costs were based primarily on European and North American data (Table 6.2), as available Australian data tends to relate to plants that are either smaller, such as the 4000 t/yr facility in Woodburn, NSW (Enecon 2007), or larger, such as Plantation Energy’s 250,000 t/yr facility in Albany, WA (Redman 2009).
The base case production costs were set at a conservative level of $75/t of pellets due to a lack of local experience, with the full range of costs from Table 6.2 considered as variations in the sensitivity analysis (i.e. $48-84/t). Costs may decrease with experience or due to local advantages such as being able to dry biomass in the sun. This has been successfully achieved with mallee biomass near Condobolin (Sandy Booth pers. comm.) and Forbes (Larkin 2011) and could avoid gas-fired drying costs that often exceed $30/t in Europe (Enecon 2007).
236 Table 6.2: Pellet production costs from previous studies30.
Study Feedstock Plant Capital Capital Operating Capital + Author/s & capacit invest- cost costs excl. operating location y (t/yr) ment ($ per feedstock costs ($/t) millions) tonne ($/t) ($/t) Thek & Sawdust, Obernberger 25,000 2.75 8 65 73 Austria (2004) WA mallee Not Enecon (2007) using data 50,000 Not stated 84 stated from Europe Forest thinnings Polagye et al. (transport- Not 33,500 15 61 76 (2007) able stated plant), USA Crop Sultana et al. wastes, 44,000 3.17 7 41 48 (2010) Western Canada Energy Nilsson et al. crops & 80,000 8.11 10 43 53 (2011) sawdust, Sweden Energy This study crops, 50,000 6 12 63 75 (base case) NSW
Table 6.3 shows the full set of base case assumptions and variations for the pellet model.
30 CRF of 0.098 applied to capital investment costs where stated. Capital cost annualisation method not stated for Enecon (2007) or Polagye et al. (2007). Exchange rates: 1 AUD=0.74 EUR, 1 AUD=1.08 USD.
237 Table 6.3: Base case pellet production assumptions and variations. Parameter Base case assumptions Variations used in sensitivity analysis Pellet capital + operating 75 $48-84/t costs excl. feedstock ($/t) Pellet transport to port 46 Condobolin-Port costs ($/t)31 Botany 20 Oberon-Port Botany Port handling costs for 13 pellets ($/t)31 Pellet shipping costs 88 (Europe) ($/t)32 47 (Japan) Price received for pellets 127 EUR/t (mid-range Europe: 112-141 EUR/t (CIF, excl. GST/VAT) Europe) Japan: 21,800-40,000 30,900 JPY/t (mid-range JPY/t Japan) Exchange rates 1 AUD = 0.74 EUR 1 AUD = 0.50-0.93 EUR 1 AUD = 87 JPY 1 AUD = 60-100 JPY Conversion rate (t 0.5 pellets/ gt biomass)
Road transport, port handling and shipping costs follow Enecon (2007), with adjustment for export from Port Botany, NSW, rather than Kwinana, WA. Exported pellets were assumed to be used for electricity generation, which offers lower prices than residential heating (Sikkema et al. 2009) but is a growing market that has been successfully targeted by Plantation Energy Pty Ltd operating in WA (Energy Global 2010). Pellet prices used in the model were inclusive of cost, insurance and freight (CIF) and were based on the 2007-2009 price ranges reported for Europe (Sikkema et
31 Enecon (2007). Per km road transport rate for York-Kwinana (134km) applied to Condobolin-Port Botany (471km) and Oberon-Port Botany (205 km). Port Botany handling costs assumed equal to Kwinana. 32 Enecon (2007). Per nautical mile shipping costs (50,000 t shipments) to Rotterdam & Osaka from Kwinana (9573 nm & 4637 nm) applied to Port Botany (11558 nm & 4833 nm).
238 al. 2009, p. 16) and Japan (Asia Biomass Office 2011). The exchange rates used in the sensitivity analysis were those observed between 2001 and 2011, with a 25% increase also considered for AUD:EUR rate due to the Australian dollar being at an all-time high against the Euro in July 2011. The model did not consider the impact that changes in exchange rates may have on costs such as shipping. Also, while overseas pellet demand has been stimulated by renewable energy and carbon pricing policy (Sikkema et al. 2009), the modelling did not consider the impact of policy changes in Europe or Japan.
Solid fuels: briquette model
The briquette production model was much simpler than the pellet model due to the target market being Australian residential wood-heaters. However, the briquette model contained a high degree of uncertainty due to a lack of Australian data or studies. The breakeven biomass price for briquetting was determined using Equation 6.3.
Where: bp = biomass price payable at factory gate (AUD/gt)
qp = briquette price ex factory (AUD/t)
pc = production costs (capital & operating) excl. feedstock (AUD/t) r = conversion rate (t briquettes/gt biomass)
Base case assumptions and variations are listed in Table 6.4 for a plant producing 5000 tonnes of briquettes per year (e.g. 750 kg/hr, 16 hr/day, 312 days/yr). Base case production costs excluding feedstock were assumed to be midway between the cost figures of $41/t estimated by Tabarés (2000) for Spain (1 AUD=0.74 EUR) and $60/t estimated by Felfli, Luengo and Rocha (2005) for Brazil (1 AUD=1.72 BRL)33. Forest and Wood Products Australia (2007) identified briquetting equipment available in Australia with capacities and prices similar to those analysed by Felfli et al. (2005). The sensitivity analysis considered costs ranging from $41/t to $219/t (excluding
33 CRF of 0.098 applied to Felfli’s capital investment costs. Tabarés’ capital investment & CRF not stated.
239 feedstock), with the lower limit based on Tabarés et al. (2000) and the upper limit based on analysis undertaken by Baradine Biofuels, who have assessed the potential production of briquettes from cypress thinnings in northwestern NSW (Ted Hayman personal communication March 2012). The difference between these two estimates highlights the risks involved in applying overseas data to the development of new industries in Australian. Labour costs make up a large proportion of the production costs estimated by Baradine Biofuels (Ted Hayman pers. comm.).
Table 6.4: Base case briquette production assumptions and variations.
Parameter Base case assumptions Variations used in sensitivity analysis
Briquette production costs (capital 50 41-153 + operating) excl. feedstock ($/t)
Briquette price ex factory ($/t) 250 100-384
Conversion rate (t briquettes/ gt 0.5 biomass)
The base case briquette price in Table 6.4 is based on compressed wood briquettes sold in large Australian hardware stores, which were retailing for around $1/kg ($1000/t) in August 2011when sold in 10 kg or 20 kg bags. Following Tabarés’ (2000) assumption that prices double from the factory to wholesale and then again from wholesale to retail, this corresponds to a briquette price ex factory of $250/t. However, the sensitivity analysis also considered the possibility of obtaining a higher price, up to the $384/t maximum price34 estimated by Baradine Biofuels (Ted Hayman pers. comm.). Also, given the potential for increased briquette production to flood the small Australian briquette market (Forest and Wood Products Australia 2007), a lower wholesale price of $100/t ex factory was also analysed. This is similar to the prices reported by Tabarés (2000) for Spain ($95/t) and Felfli et al. (2005) for Brazil ($105/t).
34 Price of $384/t is based on a maximum price of $450/t minus shipping costs of $66/t.
240 Liquid fuels: ethanol model
Ethanol was assumed to be produced via enzymatic conversion of woody biomass at either Condobolin or Oberon, with ethanol being substitutable for unleaded petrol after making allowance for their differing energy densities. As discussed in Chapter 2, the commercial production of cellulosic ethanol is not yet widespread and is subject to considerable uncertainty.
The breakeven biomass price for ethanol production was determined using Equation 6.4. As the model was based on wholesale petrol prices, it does not include fuel retail margins or GST. The Australian wholesale unleaded petrol price (terminal gate price excluding taxes) was determined using Equation 6.5, which includes consideration of the oil price in Singapore (Tapis crude) as well as refining, shipping and wholesaling margins related to the import of Singapore’s benchmark MOPS95 unleaded petrol into Australia. This approach to calculating unleaded petrol prices follows that employed by the Australian Institute of Petroleum (2011).
Where: bp = biomass price payable at factory gate (AUD/gt)
uw = unleaded petrol wholesale price excl. taxes (AUD/L)
ux = unleaded petrol excise (AUD/L)
uc = carbon price on unleaded petrol (AUD/t CO2-e)
ci = carbon intensity of unleaded petrol (t CO2-e/L)
sr = substitution ratio (MJ in 1L ethanol/MJ in 1L unleaded petrol)
ex = net ethanol excise (including producer grant) (AUD/L)
cc = capital costs for ethanol plant (AUD/L)
oc = operating costs (excl. feedstock) for ethanol plant (AUD/L) r = conversion rate (L ethanol/gt biomass)
241 Where: uw = Australian unleaded petrol wholesale price (AUD/L)
tp = Tapis crude price (USD/barrel)
uy = yield of MOPS95 per barrel of oil (L/bbl)
er = exchange rate (USD/AUD)
rm = refining margin (AUD/L)
sm = shipping margin (AUD/L)
wm = wholesaling margin (AUD/L)
Table 6.5 shows the base case assumptions and variations employed in the ethanol model. Ethanol production costs were drawn from an analysis of a 68 ML/yr cellulosic ethanol plant in the Green Triangle region of Victoria and South Australia by Rodriguez et al. (2011a). Unleaded petrol costs were drawn from data published by the Australian Institute of Petroleum (2011) for July 2011.
The sensitivity analysis for ethanol included variations in the exchange rate and Tapis crude price within their observed 2001-2011 ranges. A 25% increase was also considered for the AUD: USD exchange rate due to it being at a near-record high in July 2011. Ethanol was assumed to attract a net excise of zero in the base case due to the Ethanol Production Grants Program discussed in Chapter 4. The sensitivity analysis considered the impact of a rise in net ethanol excise to 12.5c/L, the level that had previously been proposed for 2015 (Batten & O’Connell 2007) prior to the Australian Government deciding to extend the current excise arrangements. The base case assumed that neither petrol nor ethanol was subject to a carbon price, while the sensitivity analysis considered the impact of a carbon price up to $100/t CO2-e on petrol. Ethanol was assumed to be exempt from the carbon price and no analysis was undertaken of possible rises in ethanol production costs due to carbon pricing.
242 Table 6.5: Base case ethanol production assumptions and variations. Parameter Cellulosic ethanol Base case Variations used in assumption sensitivity analysis Ethanol capital costs ($/L)35 0.33 Ethanol operating costs, excluding 0.13 feedstock ($/L)35 Conversion rate (L/gt)36 133 Oil Price - Tapis crude ($/bbl)37 115 20-150 Yield of MOPS95 per barrel of oil 159 (L/bbl) Exchange rate $A1=$US1.08 $A1= $US0.50-1.35 Refining margin on MOPS95 ($/L)37 0.03 Shipping margin for MOPS95 ($/L)37 0.02 Wholesaling margin for MOPS95 ($/L)37 0.09 Excise on petrol ($/L) 0.381 38 Carbon intensity of petrol (t CO2-e/L) 0.00229 Carbon price on petrol emissions ($/t 0 0-100
CO2-e) Substitution ratio (MJ in 1L ethanol/MJ 0.68 in 1L petrol)38 Net excise on ethanol, including 0 0.00-0.125 grants/rebates ($/L)
35 Rodriquez et al. (2011). Capital costs based on $226m for a 68 ML/yr plant with a CRF of 0.098. 36 Conversion rate based on the more conservative estimate of 260L per dry tonne by O’Connell et al. (2009b), rather than the more optimistic estimate of 325 L per dry tonne by Rodriquez et al. (2011). 37 Australian Institute of Petroleum (2011). Oil price for week ending 1 July 2011. Refining, shipping and wholesaling margins based on averages for July 2009-July 2011. 38 National Greenhouse Accounts Factors (Department of Climate Change and Energy Efficiency 2011c).
243 Liquid fuels: renewable diesel/jet fuel model
Renewable diesel differs from biodiesel in that it is refined from a bio-crude rather than being produced from vegetable oil or animal fat through transesterification. A range of thermo-chemical conversion processes, including gasification, pyrolysis or saccharification, can be used to prepare woody biomass feedstocks for further refinement to products such as renewable diesel or jet fuel (CSIRO 2011b). These processes are subject to greater commercial uncertainty than cellulosic ethanol. The chosen pathway for this analysis was gasification followed by Fischer-Tropsch refinement. This was based on the conclusion of Graham et al. (2011) that gasification was the only conversion option for woody biomass with sufficient data for modelling. Production costs were assumed to be the same for either renewable diesel or jet fuel and these products were assumed to be directly substitutable for their non-renewable counterparts (i.e. no difference in energy content or quality).
The breakeven biomass price for the renewable diesel/jet fuel model was determined using Equation 6.6, with base case assumptions and sensitivity ranges listed in Table 6.6.
Where: bp = biomass price payable at factory gate (AUD/gt)
fp = price of competing fuel (including excise) (AUD/L)
uc = carbon price on competing fuel (AUD/t CO2-e)
ci = carbon intensity of competing fuel (t CO2-e/L)
pc = production costs (AUD/L)
ex = excise payable on biofuel (AUD/L) r = conversion rate (L/gt biomass)
244 Table 6.6: Base case renewable diesel/jet fuel assumptions and variations. Parameter Base case Variations used in assumption sensitivity analysis Production costs ($/L)39 0.97 Price of competing fuel ($/L)40 Diesel: 1.20 Jet fuel: 0.85 Carbon price on competing fuel Diesel: 0 Diesel: 0-100
($/t CO2-e) Jet fuel: 0 Jet fuel: 0-100 Carbon intensity of competing Diesel: 0.00255 41 fuel (t CO2-e/L) Jet fuel: 0.00268 Conversion rate (L/gt of 110 biomass)42 Net excise payable on biofuel Ren. diesel: 0 Ren. diesel: 0-0.191 ($/L)43 Ren. jet fuel: 0.03556 Ren. jet fuel: 0-0.03556
The production costs in Table 6.6 were based on the estimates produced by Graham et al. (2011) for a hypothetical 400 ML/yr facility. The price difference between diesel and jet fuel shown in Table 6.6 is primarily due to the much higher rate of excise on diesel ($0.38143/L) compared to jet fuel ($0.03556/L). In addition, the base case assumed that renewable diesel would attract a net excise of zero due to the reimbursement of excise under the Cleaner Fuels Grants Scheme, but that no equivalent scheme would be created for renewable jet fuel. The sensitivity analyses considered the impact of changes to net excise, including:
39 From Graham et al. (2011). Includes $0.78/L capital (based on a CRF of 0.11 rather than 0.098), $0.12/L operating (excl. feedstock) and $0.07/L fuel storage and transportation. 40 Diesel prices for Sydney, July 2011 (Australian Institute of Petroleum 2011), jet fuel prices for March 2010 (Sustainable Aviation Fuel Road Map 2011) 41 Based on National Greenhouse Accounts Factors (Department of Climate Change and Energy Efficiency 2011, p. 16) for diesel oil and kerosene for use as fuel in an aircraft (avtur). 42 Based on an estimate of 220L per tonne of dry matter by Graham et al. (2011). 43 2011 rates (Australian Taxation Office 2011b), previously planned 2015 rate (Batten & O’Connell 2007).
245 x an increase to $0.191/L for renewable diesel based on previously policy proposals for 2015 (Batten & O’Connell 2007); and x the creation of an excise reimbursement scheme for renewable jet fuel that reduced net excise to zero.
No carbon price was assumed for the base case, while the sensitivity analyses considered two scenarios. In one scenario, a carbon price would be applied to both diesel and jet fuel, while in the other, a carbon price would be applied only to jet fuel and not to diesel. The latter scenario is based on the arrangements outlined in the Australian Government’s Clean Energy Future package, whereby a carbon price will be imposed on domestic aviation, but an agreement has yet to be reached on extending the carbon price to heavy road transport (Commonwealth of Australia 2011b). In both scenarios, the renewable forms of these fuels were assumed to be exempt from carbon pricing.
Electricity models
Two electricity models were chosen, based primarily on the leading options identified through the case study interviews and workshops: 1. A small-scale (5 MW) biomass-only plant at Condobolin or Oberon; and 2. Co-firing biomass at a 1000 MW coal-fired power station at Wallerawang, near Lithgow.
The base case model for each option assumed a baseload generation strategy. For the co-firing model, biomass was assumed to replace 3% of the station’s coal use, following McEvilly et al. (2011). In order to facilitate co-firing, pre-processing of biomass was assumed to be required at either Condobolin or Oberon. No pre- processing was assumed to be required for the 5 MW biomass-only option (apart from the chipping of biomass prior to arrival at the factory gate).
Equation 6.7 was used to determine the breakeven biomass price for both options.
246 Where: bp = biomass price payable at factory gate (AUD/gt)
wp = average wholesale price received for electricity (AUD/MWh)
cp = carbon price (AUD/t CO2-e)
wc = change in average wholeseale electricity price received per dollar of carbon price (AUD/MWh)
rp = LGC price for biomass generation
cc = capital costs for biomass generation (AUD/MWh)
oc = operating costs excl. feedstock (AUD/MWh) r = conversion rate (MWh/gt biomass)
pc = biomass pre-processing and transport costs (AUD/gt)
Table 6.7 lists the base case assumptions and sensitivity ranges employed for the two models. Capital and operating costs were much higher for the 5 MW biomass-only model due to the need for new infrastructure rather than modifications to an existing facility. Base case capital costs for the 5 MW biomass-only facility were assumed to be $43/MWh. This was based on a capital cost of $3.5M per MW of capacity (CSIRO 2011c, p. 66), a CRF of 0.098 and 8000 hours of annual operation at full capacity (Stucley et al. 2004, p.170). This level of output corresponds to a capacity factor of 0.91 (i.e. 91% of maximum annual output). These capital costs are mid-range according to estimates from IEA/OECD (2007) for biomass-fired steam turbine or gasification plants (at 1 AUD=1.08 USD).
Operating costs (excluding feedstock) for the 5 MW biomass-only option ($16/MWh) are mid-range compared to estimates from Moon (2011) for a Korean 3 MW gasification plant ($10/MWh) and Stucley et al. (2004) for an Australian 5 MW steam turbine plant ($20/MWh). The sensitivity range for capital and operating costs for the 5 MW model was set at +/-50% of base case costs. This allowed alternative cost estimates to be considered, such as the lower capital cost estimate of $2M per MW of capacity used by Rodriguez, May, Herr and O'Connell (2011b, p. 2595) for a 5MW plant in South Australia or Victoria.
247 Table 6.7: Assumptions used in the electricity generation models. Parameter 5 MW plant 3% co-firing Variations biomass only (1000 MW plant) used in sensitivity analysis Capital costs ($/MWh) 43 1.2144 +/-50% Operating costs excl. 16 0.8144 +/-50% feedstock ($/MWh) LGC Price45 40 40 0-100 Conversion rate (MWh/gt) 0.67546 0.8147 Pre-processing & transport 0 40 +/-33% costs ($/gt)48 Average price obtained for 40 40 40-140 electricity sales ($/MWh)49
Carbon price ($/t CO2-e) 0 0 0-100 Change in electricity price $0.81/MWh $0.81/MWh per 50 due to carbon price per $1/t CO2-e $1/t CO2-e
While the existing 1000 MW Wallerawang Power Station is currently the focus of a biomass co-firing trial (Delta Electricity 2010), data specific to that facility was not available for this modelling exercise. Instead, the main source for cost data on co-firing was a recent study by McEvilly et al. (2011), which analysed 3% biomass co-firing at a 1000 MW plant. The base case co-firing model featured much lower capital and
44 McEvilly et al. (2011). Capital costs=$3m (CRF=0.098), operating costs=$198,000/yr. 45 Average LGC spot price April-June 2011 (Green Energy Markets 2012) 46 16.2GJ/dry tonne (Department of Climate Change and Energy Efficiency 2011c), 12GJ required per MWh@30% efficiency (International Energy Agency 2007), biomass 50% dry matter 47 McEvilly et al. (2011). Biomass used=198,000 green tonnes/yr, biomass generation=244,143 MWh/yr. 48 From pellet model. Pre-processing=$37.50/gt ($75 per t pellets). Transport=19.6c/gt/km (9.8c/t pellet/km) for 309 km (Condobolin-Wallerawang) and 57 km (Oberon-Wallerawang). 49 Treasury (2011, p. 111): $40/MWh = national average wholesale electricity price for 2011. 50 Treasury (2011, p. 110): “Core” scenario for 2012-2017, with a carbon price averaging $22.10/t CO2-e resulting in an average increase of $18/MWh in wholesale electricity prices.
248 operating costs than the biomass-only model, but was assumed to have much higher costs for pre-processing and transport. Biomass was assumed to be pelletised at either Oberon or Condobolin before transport to Wallerawang, with these pre-processing and transport costs drawn from the wood pellet model. The sensitivity range for pre- processing and transport costs was set at +/-33% of base case costs, allowing for consideration of lower-range pelletising costs such as those estimated by Sultana et al. (2010) and Nilsson et al. (2011).
Both base case options assumed baseload generation at an average electricity price of $40/MWh, based on the national average wholesale electricity price for 2011 (Treasury 2011, p. 111). The sensitivity analysis considered average prices up to a maximum of $140/MWh. These higher prices could be achieved through a feed-in tariff on bioenergy introduced by the NSW Government or by following a strategy of generating electricity only during periods of high (peak) demand. As shown in Figure 6.1, NSW wholesale electricity prices are only above average around 5% of the time, but can increase rapidly during these peak periods.
Figure 6.1: Percentiles for the 2010/11 NSW Regional Reference Price (RRP). Source: 30-minute interval price data from AEMO (2011).
249 The maximum electricity price used in the modelling ($140/MWh) was based on price data for the National Electricity Market (NEM) from AEMO (2011) and is approximately equal to the average price that would have been obtained in the 2010/11 financial year by a NSW generator following a strategy of running their plant only 10% of the time, during 30-minute intervals when the Regional Reference Price was above the 90th percentile. For example, a generator following this strategy would have obtained their highest price of $12,136/MWh at 16:00 on 1 February 2011 and their lowest price of $32.48/MWh at 13:30 on 3 March 2011, with an average price of $143.80/MWh across all periods in which they were generating (AEMO 2011).
A peak-only strategy is likely to be viable only for the 5MW biomass-only option and only then if gasification of biomass is employed, as steam turbine generators are difficult to start and stop at short notice. This strategy would also have an impact on capital costs per MWh of output, as the initial capital outlay would need to be recovered from fewer MWh each year.
Table 6.8 shows how capital costs per MWh and prices received per MWh could change for the 5 MW biomass-only model if generation were restricted to peak times only, using the base case capital cost data (from CSIRO 2011c, p. 66) and NSW Regional Reference Price data for 2010/11 (AEMO 2011). These figures were used to undertake an additional analysis of the breakeven biomass price that a 5 MW biomass- only plant would be able to pay if following a peak-only generation strategy. Operating costs per MWh, carbon price and LGC price were assumed to be the same as the base case. The model did not consider cost increases related to the storage of biomass during low price periods or any reductions in capital costs that could be achieved by using larger-scale biomass gasification facilities.
250 Table 6.8: Capital costs and average electricity prices for a peak-only 5 MW biomass plant. Cost source: CSIRO (2011c), price source: AEMO (2011). Strategy: generate Annual Annual capital Capital Average price only when NSW Output costs assuming costs per received RRP is above (MWh) CRF of 0.098 ($) MWh ($) ($/MWh) the… 100th percentile 43,800 1,715,000 39.16 36.54 50th percentile 21,900 1,715,000 78.31 76.37 25th percentile 10,950 1,715,000 156.62 87.08 10th percentile 4,380 1,715,000 391.55 143.80 5th percentile 2,190 1,715,000 783.11 252.48
The two policy factors included in the electricity models were the LGC (Large-scale Generation Certificate) price and the carbon price. LGC prices were set at $40 in the base case based on 2011 spot prices (Green Energy Markets 2012), with the sensitivity analysis considering increases up to $100/LGC. 1 LGC represents 1 MWh of renewable electricity. The carbon price was set at zero for the base case and up to
$100/ t CO2-e for the sensitivity analysis. Although biomass combustion releases small quantities of non-CO2 greenhouse gases (Department of Climate Change and Energy Efficiency 2011c), it was assumed that biomass generation was exempt from carbon pricing.
Modelling of LGC and carbon price impacts was complicated by the interaction between these two factors discussed in Chapter 4. Increases in the wholesale electricity price (from a carbon price or otherwise) can be expected to reduce the LGC price, as the “gap” that needs to be bridged by LGCs will have been reduced. To reflect this interaction, two key assumptions were employed in the carbon price modelling:
1. Wholesale electricity prices were assumed to rise by $0.81/MWh on average
for every $1/t CO2-e increase in the carbon price. This was based on modelling reported by Treasury (2011) for its ‘core’ policy scenario, whereby a carbon
price averaging $22.10/t CO2-e between 2012-2017 was expected to result in an increase of $18/MWh in average wholesale electricity prices.
251 2. Every $1/MWh increase in the average wholesale electricity price was assumed to cause a $1 decrease in the LGC price, down to an LGC price of zero (at which point LGCs would become obsolete)51. This assumption follows Frontier Economics (2008) in its modelling of the interaction between the RET and a carbon price.
Although sufficient for the purposes of this modelling exercise, both assumptions have their limitations. The first assumption is based on modelling of relatively low carbon prices and is likely to break down at higher prices as the “merit order” (i.e. order of dispatching power stations) shifts for generation sources such as coal, gas and renewables (Frontier Economics 2008). For the second assumption, Treasury (2011, p. 105) raises doubts about an exact 1:1 relationship between wholesale prices and LGC prices by predicting that the rise in wholesale prices will be offset by falling LGC prices “to some extent”. The relationship between LGC spot prices and electricity prices is also complicated by the use of long-term contracts that employ “effective” LGC prices that are higher than the spot price (ROAM Consulting 2011, p. 20). Furthermore, the LGC market is still affected by “phantom” credits from small-scale solar generation (Buckman & Diesendorf 2010), which Horner (2010a) argues may take years to “wash out” of the market following the separation of the RET into small- scale and large-scale components in 2011.
Co-production models
Co-production models were developed as a variation to each of the solid fuel, liquid fuel and electricity models. For Condobolin, mallee biomass was assumed to be separated into a leaf fraction for eucalyptus oil distillation and a residual fraction for bioenergy. For the Central Tablelands, the fractions were pulpwood for paper and residual biomass for bioenergy. All facilities, including the biomass separator, bioenergy plant and oil distillery or pulp mill were assumed to be co-located at either
51 The sensitivity analysis for electricity price ($40-140/MWh) assumed no change to the LGC price, as it was based on feed-in tariffs or targeting peak periods rather than a change to the average wholesale price.
252 Condobolin or Oberon. Under the co-production model, the price paid per green tonne of biomass was determined using Equation 6.8.
Where: bo = overall biomass price (AUD/gt) with co-production
fb = biomass fraction (% of green weight) sent to bioenergy facility
bb = biomass price payable if used for bioenergy only (AUD/gt)
fc = biomass fraction (% of green weight) sent to distillery/pulp mill
vc = value of co-products (AUD/gt sent to distillery/pulp mill)
cc = costs of co-production (AUD/gt sent to distillery/pulp mill)
Mallee biomass was assumed to be 65% leaf by green weight, based on estimates from Total Catchment Management Services (2008). For all Condobolin models except for the 5 MW electricity plant, it was assumed that the boilers for distilling eucalyptus oil were heated using the spent leaf material (i.e. residues left after oil extraction and open air drying). These models assumed that the remaining 35% woody fraction was sent to the bioenergy plant. The 5 MW biomass electricity option employed a different set of assumptions. These assumptions followed Enecon (2001) and involved the use of waste hot water from the power plant to run the oil distillery and the use of spent leaf from the distillery as fuel for the power plant. Under these assumptions, the fraction sent to the distillery (fc) is 65% while the fraction sent to the bioenergy plant (fb) is 100% (either directly or as spent leaf).
The baseline value of eucalyptus oil (vc) was assumed to be $175 per green tonne of leaf, based on an oil yield of 25 kg per green tonne of leaf and a baseline oil price of $7/kg. A sensitivity range of $50-300/gt was also analysed, based on an oil price range of $2-12/kg (Total Catchment Management Services 2008). The costs related to the co-
253 52 production of oil (cc) were assumed to be $22.50/gt of leaf ($0.90 per kg of oil ). Yield/price estimates were drawn from Total Catchment Management Services (2008), while costs were based on Abadi et al. (2006) and Enecon (2001).
For the Central Tablelands, the wood fraction to be sold as pulpwood was determined using the relationship shown in Figure 6.2, which was derived by Bennell et al. (2009) from trial and survey data covering eucalypt species with moderately dense leaves across southern Australia. The base case assumed that trees were harvested at age 10, following modelling by Polglase et al. (2008) and Bennell et al. (2009) of pulpwood and bioenergy production in SE Australia. Figure 6.2 shows that trees at age 10 would have a wood fraction of approximately 65% and a residual fraction of approximately 35%. An alternate model was also run assuming a harvest age of 5 years (50% wood fraction, 50% residual biomass). The value of the pulpwood fraction (vc) was assumed to be $55/gt delivered to Oberon, based on market analysis by Ximenes et al. (2012). The need to separate the biomass into pulpwood and residual fractions was assumed to add a cost (cc) of $10/gt, following Bennell et al. (2009).
All co-production models also considered the possibility that the net return from co- production (vc - cc) could be lower than the breakeven biomass price calculated under the individual bioenergy models (bb). If this was the case, then it was assumed that all biomass would be used for bioenergy only and none would be used for eucalyptus oil or pulp.
52 Operating costs = $0.77/kg ($0.85/kg from Abadi et al. (2006) minus harvest costs of $0.08/kg). Capital costs = $0.13/kg ($930,000 handling equipment and $408,000 for distillation equipment from Enecon (2001) for a facility producing 1050 kg/yr of oil, CRF=0.098).
254 Figure 6.2: Relationship between tree age and wood fraction for eucalypt species with moderately dense leaves. Reproduced from Bennell et al. (2009).
6.1.2 Results
Figure 6.3 shows the results of the demand-side modelling for each of the bioenergy options under base case assumptions. The breakeven price that could be paid for each green tonne of biomass delivered to the factory gate ($/gt) is shown on the vertical axis, with the scale of biomass production required for each option (gt/yr) shown on the horizontal axis. With regard to the two tests of economic viability outlined at the start of section 6.1: x All options apart from pellet export to Europe and renewable jet fuel pass the first test of delivering a positive breakeven biomass price under base case assumptions. x Three options pass the second test by delivering a breakeven biomass price greater than $40/gt. These options are briquettes, pellets to Japan (from either Oberon or Condobolin) and ethanol.
255
Figure 6.3: Breakeven biomass price and scale for each demand-side bioenergy model under base case assumptions.
In terms of the scale of biomass use represented by each option, briquette production has the smallest scale in Figure 6.3, followed by the 5 MW biomass-only power plant and then wood pellets. Renewable diesel/jet fuel has the largest scale of the options modelled, with a scale several times larger than the second-largest option, ethanol. Co- firing with coal at a 1000 MW plant at a rate of 3% biomass produces a medium-range scale of around 300,000 gt/yr. The modelling did not consider the option of 20% biomass co-firing, which has been proposed by Delta Electricity (2010) for its 1000 MW plant at Wallerawang. That option would require around 2 million green tonnes of biomass per year, falling between ethanol and renewable diesel in terms of scale. The scale results shown in Figure 6.3 are based on typical facility sizes from previous studies and each option is likely to have a degree of scale flexibility.
The scale of biomass use by a bioenergy facility has a number of implications for the development of a regional agroforestry industry. A small-scale option like briquettes or pellets would require a relatively small number of participating landholders and a relatively low capital investment. These lower barriers to entry could increase the
256 trialability of bioenergy-based agroforestry for landholders in the region. However, small-scale options like briquettes carry a higher risk that landholders will be undercut by cheaper biomass supplies. This is particularly relevant for a region like the Central Tablelands, where existing biomass residues can be found at the Oberon Timber Complex and in government-owned radiata pine plantations. The breakeven biomass prices shown in Figure 6.3 are not guaranteed prices, but rather represent the maximum prices that could be paid for biomass by the different bioenergy facilities. If cheaper biomass sources are available, bioenergy producers will not need to pay the breakeven price.
A large-scale bioenergy option (e.g. liquid fuels or 20% co-firing) would be more likely to exhaust cheaper sources of biomass in the region and require bioenergy producers to pay the breakeven prices shown in Figure 6.3. However, these large-scale bioenergy options also carry significant risks due to their high investment costs and lack of commercially-proven technologies, particularly for liquid fuels. There is also a “chicken-or-egg” dilemma, whereby investors in bioenergy facilities require certainty of supply before investing, but investors in new plantations require certainty of markets before planting. Renewable diesel/jet fuel is a particularly extreme case, as the 400 ML facility assumed in the modelling would require an upfront investment of around $2 billion (Graham et al. 2011) and a biomass supply much larger that all other options shown in Figure 6.3.
With regards to the breakeven biomass prices for each bioenergy option, the solid fuel models produced the highest results, with briquettes and pellet export to Japan both producing a breakeven biomass price of around $100/gt under base case assumptions. However, in addition to the risk of being undercut by cheaper biomass sources, there are other risks associated with these options. The briquette model features considerable uncertainty with regard to Australian production costs and the impact that an increase in production could have on briquette prices in the small Australian market. The sensitivity analysis results for briquettes (Figure 6.4) indicate that an increase in production costs to the level estimated by Baradine Biofuels (Ted Hayman pers. comm.) would reduce the breakeven biomass price to $49/gt. While higher briquette prices could increase the breakeven biomass price to $167/gt, a fall in briquette price to
257 $100/t, similar to levels reported for Spain (Tabarés et al. 2000) and Brazil (Felfli et al. 2005), would lower the breakeven biomass price to $25/gt (assuming base case costs). A combination of the maximum production costs used in the sensitivity analysis ($153/t) and the minimum briquette price ($100/t) results in a negative biomass price of -$27/gt, meaning that landholders would have to pay the briquette plant to take their biomass.
Figure 6.4: Briquette sensitivity analysis results for (a) production costs and (b) briquette price. Base case results shown in red.
For the wood pellet model, an Oberon plant appears slightly more viable than a Condobolin plant, due to shorter transport distances to Port Botany. Japan appears to be a more viable export market than Europe due to its higher prices and shorter shipping distance. Export to Europe delivers a negative biomass price under base case assumptions. However, Japan’s pellet market is smaller than Europe’s, potentially leading to greater volatility, and a declining trend was apparent in pellet prices between 2007 and 2009, which the most recent year for which price data was available (Asia Biomass Office 2011). Plantation Energy has successfully targeted both markets from Western Australia, but considers Japan to be secondary to Europe (Energy Global 2010). Compared with the hypothetical facilities modelled for Condobolin and Oberon, Plantation Energy have shorter transport distances to the nearest port (Albany, WA), shorter shipping distances and a much larger production scale (250,000 t/yr).
258 The sensitivity analysis results for the wood pellet model (Figure 6.5) indicate that breakeven biomass prices at Condobolin and Oberon are particularly sensitive to changes in pellet prices and exchange rates. If Japanese prices are assumed to be “low” (i.e. 2009 levels) rather than “medium” (base case), the model shows that biomass prices would be $30-50/gt rather than $80-100/gt. Conversely, a fall in the Australian dollar back to “low” levels relative to the Euro and Yen (last seen in 2009) would almost double the breakeven biomass price (assuming there were no flow-on effects to shipping or other costs). The model showed less sensitivity to production costs, with a 33% reduction in costs delivering only a 12-14% increase in breakeven biomass prices. If production costs were able to be reduced at Condobolin to $48/t (e.g. through open- air drying of biomass) while remaining at the base case level of $75/t at Oberon, Condobolin would overtake Oberon as the more viable of the two sites.
Figure 6.5: Wood pellet sensitivity analysis results for (a) pellet price, (b) exchange rate and (c) production cost. Base case assumptions indicated by red lines on the x-axis.
After briquettes and pellets, the ethanol model delivered the next-highest breakeven biomass price in Figure 6.3, producing a result of $48/gt under base case assumptions. The sensitivity analysis results for ethanol (Figure 6.6) highlight the susceptibility of ethanol production to global factors such as exchange rate and oil price volatility. A fall in the Australian dollar to $US0.50 (last experienced in 2002) would increase the price of imported oil in the model and cause the breakeven biomass price to more than double. A rise in the price of Tapis crude to $US150/bbl (slightly above the record high of mid-2008) would boost the breakeven biomass price by around 40% above the base case. In contrast, a fall in Tapis crude prices to $US60/bbl (experienced less than
259 six months after the 2008 high) would result in a 60% drop in breakeven biomass price. Biomass price was less sensitive to domestic policy changes, with increases in carbon price and ethanol excise having opposing effects. For example, if net excise on ethanol was to rise to 12.5c/L (as was previously planned for 2015), the model shows that a carbon price of around $80/t CO2-e would need to be applied to unleaded petrol to offset this impact and return the breakeven biomass price to the base case level of $48/gt.
Figure 6.6: Ethanol sensitivity analysis results for (a) oil price, (b) exchange rate, (c) carbon price and (d) ethanol excise. Base case results shown in red.
Renewable diesel delivered a breakeven price of $25/gt under base case assumptions. This was lower than the biomass price for the ethanol model, as well as being lower than the $35-40/gt prevailing price for biomass at Oberon (Ximenes et al. 2012). However, renewable diesel delivered a much higher breakeven price than renewable jet fuel (-$13/gt). This was due to two factors: (1) the much higher rate of excise levied on
260 road transport fuels compared to aviation fuels; and (2) the fact that renewable diesel producers receive a grant covering all excise paid, but the same does not apply to aviation fuels. This result reinforces the conclusion of Graham et al. (2011) that road transport biofuels are likely to be more viable than aviation biofuels unless substantial changes occur in relation to excise rates, biofuel production costs and/or the use of electric vehicles.
The results of the renewable diesel/jet fuel sensitivity analyses are shown in Figures 6.7 and 6.8. The analysis of fuel excise (Figure 6.7) suggests that an increase in net excise on renewable diesel from the current level of zero to 19.1c/L (previously planned for 2015) would lead to a collapse in the breakeven biomass price. For renewable jet fuel, an excise exemption or rebate that reduced net excise to zero would have little impact on the breakeven biomass price due to the low level of excise currently levied on aviation fuels.
Figure 6.7: Renewable diesel/jet fuel sensitivity analysis results for excise rates. Base case results shown in red.
The carbon price analysis for renewable diesel/jet fuel (Figure 6.8) shows that a carbon price of around $40-60/t CO2-e would be required to raise the breakeven biomass price for renewable diesel above $35-40/gt. If a carbon price was applied to jet fuel but not diesel, as is planned under the initial years of the Australian Government’s carbon pricing mechanism (Commonwealth of Australia 2011b), the model shows that the
261 breakeven biomass price for renewable jet fuel would increase from -$17/gt at a carbon price of zero to $12/gt at a carbon price of $100/t CO2-e. However, even at this high carbon price, renewable jet fuel would still fall short of the base case biomass price for renewable diesel due to the fuel excise advantage enjoyed by renewable diesel.
Figure 6.8: Renewable diesel/jet fuel sensitivity analysis results for carbon price. Base case results shown in red.
For the electricity models, the 5 MW biomass-only facility delivered a breakeven biomass price of $14/gt using base case assumptions. The co-firing results were either side of this, delivering $23/gt at Oberon and $11/gt at Condobolin. The breakeven biomass price at Condobolin was lower than Oberon due to the additional transport distance to Wallerawang, where co-firing was assumed to take place. The co-firing results for Oberon are very similar to the results of modelling undertaken independently by the CSIRO (Rodriguez et al. 2011c), which were released after the case study modelling had been completed. The CSIRO study found that a biomass price of up to $48 per dry tonne may be viable for co-firing at Wallerawang. This corresponds to $24 per green tonne if the moisture content is 50%, which is very close to the $23/gt found for the Oberon co-firing option presented here. Some of the
262 CSIRO’s key assumptions were different to the case study modelling for this thesis, with the CSIRO study assuming a higher rate of biomass co-firing (20% instead of 3%), a lower LGC price ($36 instead of $40) and that any pre-processing of biomass would occur at Wallerawang rather than at Oberon.
The sensitivity analysis of electricity costs (Figure 6.9) highlights that the 5 MW biomass-only model is sensitive to changes in capital and operating costs, while the co- firing models are sensitive to changes in pre-processing and transport costs. A reduction in pre-processing costs (e.g. a switch from pelletising to briquetting) could substantially improve the economics of the co-firing option.
Figure 6.9: Electricity sensitivity analysis results for (a) capital and operating costs, and (b) pre-processing and transport costs. Base case assumptions indicated by red lines on the x-axis.
The sensitivity analysis results for the key electricity policy factors of LGC price and carbon price are shown in Figure 6.10. The LGC analysis shows that a 50% increase in LGC price (i.e. from $40 to $60) would approximately double the breakeven biomass price for each electricity option. The same impact could be achieved through the use of a multiplier, whereby biomass electricity was awarded 1.5 LGCs per MWh rather than 1.
263
Figure 6.10: Electricity sensitivity analysis results for (a) LGC price, and (b) carbon price. Base case assumptions indicated by red lines on the x-axis.
The carbon price analysis shows that a carbon price would have no impact until it reaches $49/t CO2-e, due to the assumption that a carbon price would increase wholesale electricity prices but reduce LGC prices simultaneously. Above $49/t CO2-e, the LGC price would reach zero and become irrelevant. As discussed in section 6.1.1, the assumed relationship between carbon price and LGC price has limitations. In reality, LGC prices are likely to be influenced by long-term bundled contracts and the fact that the Large-scale Renewable Energy Target (LRET) will continue to increase up to 2020 and drive further increases in LGC prices at the same time as the carbon price is being progressively increased. However, the model results reinforce the general conclusions of Treasury (2011) that the LRET is likely to remain the main driver of renewable electricity investment during the early years of a carbon price. Modelling commissioned by Treasury suggests that a carbon price introduced in 2011 with an aim of achieving a 5% reduction in 2000 emissions levels by 2020 would not begin to have an additive effect on the level of renewable energy use in Australia until around 2018-2020 (Treasury 2011).
The sensitivity analysis results for electricity price (Figure 6.11) indicate that an increase in the average electricity price received could greatly increase the breakeven price payable for biomass (assuming that capital costs per MWh remain at base case levels). Based on these results, a breakeven biomass price of $35-40/gt (i.e. the
264 prevailing price at Oberon) would be achievable at average electricity prices of $60- 80/MWh (i.e. 50-100% higher than the base case price). The modelling shows that an average price of $140/MWh would deliver a breakeven biomass price of over $80/gt for all three models.
Figure 6.11: Electricity sensitivity analysis results for electricity price. Base case assumption indicated by a red line on the x-axis.
A bioenergy feed-in tariff could provide a mechanism for increasing the average price received for electricity sales while still following a baseload generation strategy. An alternative way to achieve an average electricity sale price of $140/MWh would be to follow a peak-only generation strategy that involved selling power only when the NSW Regional Reference Price was above the 90th percentile, which mostly occurs in summer and winter (Figure 6.12). However, as discussed in section 6.1.1, this would only be viable for a biomass gasification facility and would require capital costs to be recovered from fewer MWh of annual output. Figure 6.13 shows the results of the peak-only variation modelled for the 5 MW plant, in which the electricity price received and the capital cost per MWh were both assumed to rise as generation is increasingly concentrated in peak times. These results show that a peak-only generation strategy would not increase the breakeven biomass price payable for the 5
265 MW model, as capital costs per MWh rose more steeply than the electricity price as generation was increasingly restricted to peak times. Larger-scale gasification facilities (e.g. 150-500 MW) could produce a different result, as their capital costs per MW of capacity can be lower than those employed in the 5 MW model (ACIL Tasman 2009).
Figure 6.12: Periods during 2010/11 in which the NSW Regional Reference Price for electricity was above the 90th percentile. Source: 30-minute interval price data from AEMO (2011). Note the concentration of peak periods in summer and winter.
Figure 6.13: Breakeven biomass price for the 5 MW biomass-only electricity model based on peak-only generation. Each column label refers to a strategy of selling power only when the Regional Reference Price is above the percentile listed.
266 The co-production options involving eucalyptus oil at Condobolin or pulpwood at Oberon produced differing results across the six bioenergy models. Figures 6.14 and 6.15 compare the base case bioenergy-only results (from Figure 6.3) to the co- production results for Condobolin and Oberon. Those options showing negative returns in Figure 6.3 (pellets to Europe, renewable jet fuel and co-firing) have been excluded on the basis that co-production would not be viable (i.e. the biomass fractions for oil or pulp could be sold but the residual biomass would remain unsold).
250 Bioenergy only Oil at $2 Oil at $7 Oil at $12
200
150
100
50
0 Overallprice biomass ($/gt) Pellets to Japan Briquettes Ethanol Ren. diesel 5MW electricity -50
Figure 6.14: Breakeven biomass price under the Condobolin co-production model. Eucalyptus oil prices of $2/kg, $7/kg or $12/kg are shown.
250 Bioenergy only Pulp 50% Pulp 65%
200
150
100
50
0 Overall biomass price ($/gt) Pellets to Japan Briquettes Ethanol Ren. diesel 5MW electricity -50
Figure 6.15: Breakeven biomass price under the Central Tablelands co- production model. Pulpwood fractions of 50% (aged 5 years) or 65% (aged 10 years) are shown.
267 Eucalyptus oil co-production at Condobolin showed a greater impact on overall biomass prices than pulpwood co-production in the Central Tablelands at higher oil prices ($7/kg and $12/kg). However, the impact that co-production at Condobolin would have at the lower oil price of $2/kg was similar to the impact of pulpwood co- production at Oberon. The 5 MW electricity option showed the greatest benefit from co-production. This was because the breakeven biomass price for bioenergy alone was low, making the value of the co-products more significant. The Condobolin co- production option involving eucalyptus oil and 5 MW biomass-fired generation also benefitted from being able to utilise the leaf portion of the biomass twice (firstly for oil extraction and then for electricity generation).
Overall, the demand-side modelling results highlight a number of scenarios in which bioenergy facilities could offer a breakeven biomass price of around $40/gt (i.e. similar to prevailing biomass prices at Oberon). These include: x Briquette production at either site, provided that wholesale briquette prices were at least 50% of the assumed base case price; x Pellet export to Japan from either site, provided that pellet prices were at least equal to the “low” (i.e. 2009) level used in the modelling; x Cellulosic ethanol production at either site using base case assumptions;
x Renewable diesel at either site, if a carbon price of around $50/t CO2-e was imposed on conventional diesel; x Electricity generation from 3% co-firing, if LGC prices were at least 50% higher than 2011 levels for Oberon (i.e. $60/LGC) or at least 100% higher than 2011 levels for Condobolin (i.e. $80/LGC); x Electricity generation from a 5 MW biomass-only gasification plant at either site, if a feed-in tariff of $80/MWh was imposed or if electricity generation was restricted to the top 25% of price periods throughout the year; or x Electricity generation from a 5 MW biomass-only plant at Condobolin, if eucalyptus oil was co-produced for sale at $2.50/kg.
268 6.2 Supply-side analysis
The supply-side analysis presented in this section is based on a “typical” commercial farm at each case study site. It involves comparison between a scenario in which a portion of the farm is converted to agroforestry for bioenergy production and a scenario in which the same area is maintained under typical agricultural production. The farm types and agricultural systems chosen as typical are based on a combination of past studies, government reports and the social analysis presented in Chapter 5. The models also consider a range of policy options discussed in Chapters 4 and 5 that could be introduced at the landholder level (e.g. grants for plantation establishment, payments for carbon sequestration, advancement of LGC payments).
The Condobolin analysis is focused exclusively on blue mallee (Eucalyptus polybractea) while the Central Tablelands analysis considers a range of species options. Each model is based on a single-species monoculture and average climatic conditions. This reflects a lack of available data on mixed-species plantations and on the impacts that climatic variability can have on key parameters such as biomass yield and production costs. In addition, no attempt has been made to incorporate economic values for co-benefits such as soil protection or biodiversity conservation into the models. This is again due to a lack of data on these co-benefits, as well as the issues discussed in Chapter 3 around monetary pricing of environmental assets. Within ecological economics, monetary pricing is considered problematic due to the need to convert a range of non-market goods into a single price, the application of discount rates to natural capital in future years and the implication that natural capital is directly substitutable for other forms of capital.
Chapter 7 (environmental analysis) considers issues relating to the valuation of environmental co-benefits, as well as assessing plantation design factors such as mixed-species approaches and the role of climate change and climate variability.
The supply-side modelling assumes a base case biomass price of $40/gt delivered to the factory gate and employs a sensitivity range of $20-100/gt. The base case price is based on the prevailing price for chipped biomass (non-pulpwood) delivered to
269 Oberon, as reported by Ximenes et al. (2012). The minimum price selected for the supply-side sensitivity analysis ($20/gt) follows Polglase et al. (2008), who assumed biomass prices of $21-23/gt for biomass used in electricity generation. The maximum price of $100/gt corresponds to the highest base case biomass price results from the demand-side modelling (i.e. briquettes and pellets to Japan). As discussed in section 6.1, the supply-side analysis includes all costs associated with harvesting, chipping and transporting biomass to a bioenergy or pre-processing facility in either Condobolin or Oberon.
6.2.1 Methodology
The supply-side analysis for all scenarios is based on a discounted cash flow approach to determine the net present value (NPV) and equivalent annual value (EAV) of each land use option. This approach is based around the time value of money principle (i.e. that a dollar earned or spent sooner is worth more than a dollar earned or spent later). It involves forecasting a series of future net cash flows from an investment and discounting these to their present value, which is today’s value of a future sum (Peirson et al. 2009). NPV represents the difference between the present value of all net cash flows from an investment over a specified period of time and its initial cash outlay and is calculated using Equation 6.9 from Peirson et al. (2009, p. 111).
Where: C0 = initial cash outlay of project
C1 = net cash flow generated by the project in year 1
C2 = net cash flow generated by the project in year 2 etc N = the life of the project (number of years) R = the required rate of return (discount rate)
The choice of discount rate and project life can have a major impact on NPV, especially for an activity such as agroforestry, which can have high upfront costs and
270 long wait times for revenue. The discount rate represents the rate of return that the project needs to generate to justify undertaking it, otherwise the landholder would be better off financially by investing their money elsewhere. The conventional approach is to use the real interest rate, which is the current commercial interest rate minus the rate of inflation (Abadi et al. 2006). Hence, the discount rate used in the supply-side modelling is 6%, based on June 2011 rates for an average commercial agribusiness overdraft of 9.21% per annum (National Farmers Federation 2011) minus inflation of 3.3% (Reserve Bank of Australia 2011). The project life was set at 30 years, which is the median figure used across a range of previous mallee studies from NSW and WA (van Bueren & Vincent 2004, Abadi & Cooper 2004, Abadi et al. 2006, Total Catchment Management Services 2008, URS Australia 2009). This represents a lower rate of return and longer project life than used in the demand-side analysis for capital investment in bioenergy facilities (7.5% over 20 years). This difference is justified on the basis of the social analysis results, which showed that landholders are likely to take a longer-term view of farm viability and be motivated by factors other than simply maximising their return on capital.
For the typical agriculture model at each case study site, it was assumed that no new upfront investment was required (only annual costs such as sowing and animal husbandry). Thus, typical agriculture at each site produced identical net cash flows for all 30 years of the model. In contrast, the agroforestry models feature high upfront investment costs and variable cash flows. To facilitate comparison between these different scenarios, NPV for each scenario was converted into an equivalent annual value (EAV) in $/ha/yr. EAV corresponds to the cash flow (in equal annual payments) that would be required over a period of time equal to the life of the project to provide a present value equal to the NPV of the project (Peirson et al. 2009). For example, a project that requires an upfront investment of $1000 and generates net income of $500 every second year for 10 years would have a variable cash flow. However, its NPV would be equivalent to annual cash flows of $107 per year, assuming a discount rate of 6%. EAV is calculated using Equation 6.10 from Peirson et al. (2009, p. 142).
271 Where: NPV0 = Net Present Value of the project (in today’s dollars) n = the life of the project k = the required rate of return (discount rate)
None of the models include the value of land. Thus, a comparison can be made between agroforestry and typical agriculture at each case study site, but not with the option of selling the land and investing the proceeds elsewhere. All models considered variable costs only (i.e. those that vary proportionally with the area of land used for a given activity). Fixed costs such as utilities, vehicle ownership and general farm labour were excluded, following an assumption that these costs would be the same regardless of the breakdown between cropping, grazing and agroforestry. This assumption is likely to be valid for the agroforestry conversion rates identified in Chapter 5 (i.e. less than 25% of land), but fixed costs may experience more significant changes at higher conversion rates (e.g. reduced need for labour).
Condobolin
The parameters used in the blue mallee production model are shown in Table 6.9. As discussed in section 6.1.2, the base case biomass price was set at $40/gt, with a sensitivity range of $20-100/gt. The production model was based primarily on the business analysis undertaken by Total Catchment Management Services (2008), which assumed block plantings of 4250 mallee trees per hectare. A number of other sources were consulted before selecting base case figures and sensitivity ranges, including results from mallee productions trials at the Condobolin Agricultural Research Station (Milthorpe et al. 1994, Milthorpe et al. 1998), mallee production modelling for the NSW Central West (Kingwell, Hajkowicz, Young, Patton, Trapnell, Edward et al. 2003, Abadi et al. 2006) and mallee production modelling for Western Australia (Abadi & Cooper 2004, van Bueren & Vincent 2004, URS Australia 2009).
272 Table 6.9: Parameters used in the mallee production model for Condobolin. Parameter Base case Source(s) for base Variations used in sensitivity assumption case assumption analysis
Mean annual 5 Total Catchment 4 – (Total Catchment Management biomass yield Management Services 2008) (gt/ha/yr) Services (2008) - 7 – NSW trial average yield expected yield (Milthorpe et al. 1998) 16 – WA estimate (URS Australia 2009)
Biomass price 40 Demand-side 20-100 (demand-side modelling and at factory gate modelling & Polglase et al. 2008) ($/gt) Ximenes et al. (2012)
Harvest Annual, Total Catchment Every 1.5 yrs – NSW (Abadi et al. frequency starting year Management 2006) 3 Services (2008)
Yield for first 20 Total Catchment harvest (% of Management full harvest) Services (2008)
Establishment 2062.50 Total Catchment 0 – 100% cost reduction costs – one-off Management 463 – NSW (Abadi et al. 2006) ($/ha) Services (2008) 1032 – 50% cost reduction 1850 – WA (URS Australia 2009) 3000 – NSW (Kingwell et al. 2003)
Management 20 Abadi et al. (2006) 8 – WA (van Bueren & Vincent costs annual 2004) ($/ha) 60 – WA (URS Australia 2009)
273 Parameter Base case Source(s) for base Variations used in sensitivity assumption case assumption analysis
Harvest costs - 26.29 Total Catchment 10.90 – NSW eucalyptus oil harvest years Management production (Abadi et al. 2006) only ($/ha) Services (2008) 115 ($23/gt@5gt/ha) – WA (van estimate plus Bueren & Vincent 2004) higher diesel price of $2.93/ha
Transport 16.15 Total Catchment 5.10 – 30km average haul WA (URS costs to Management Australia 2009) processing Services (2008) - 11.53 – 50km average haul NSW plant - harvest 70km average haul (Total Catchment Management years only NSW Services 2008) ($/gt)
The base case assumption for biomass yield in Table 6.9 is low compared to estimates for WA, but similar to trial results for Condobolin (Milthorpe et al. 1998). Establishment costs were assumed to be higher than in WA, where planting densities are typically lower (URS Australia 2009). Transport costs estimated by Total Catchment Management Services (2008) are high compared to WA (URS Australia 2009), due both to higher per km rates ($0.23/gt/km compared with $0.17/gt/km) and longer distances.
Harvest costs, including cutting, chipping, on-farm transport and loading, represent one of the greatest uncertainties in the model due to a lack of field data. The base case model assumes costs higher than those estimated by Abadi et al. (2006) for eucalyptus oil production in NSW (which does not require chipping), but substantially lower than costs cited for WA (van Bueren & Vincent 2004, URS Australia 2009), where harvesters are required to handle larger trees. While the development of a cost- effective harvesting system has been one of the greatest impediments to the development of the Oil Mallee industry in WA (URS Australia 2009), a prototype
274 harvester has recently been developed. Future Farm Industries CRC (2011) claims that this harvester is able to halve the current cost of cutting and chipping. The mallee production model did not consider the impact of mallee plantations on neighbouring cropland or pasture. Two main impacts are likely, with mallee plantations having the potential to reduce windspeeds at ground level (thereby reducing moisture loss and erosion) as well as the potential to compete with crops or pasture for sub-soil moisture through lateral root expansion. In modelling WA mallee plantations, Abadi et al. (2004) assumed that mallee plantations would increase crop yields by 2% across a wind-reduction zone measuring 20 tree heights in width while reducing crop yields by 20% across a competition zone measuring two tree heights in width. Under the baseline assumptions of Abadi et al., the two effects would cancel one another out. It is reasonable to expect that mallee plantings in the NSW Central West could provide both wind protection and root zone competition for crops and pasture, but there is a lack of data at present on these impacts and it is unknown whether the net impact on adjacent production areas would be positive or negative.
The parameters used for the typical agricultural production model are shown in Table 6.10. This model was based around Patton and Mullen’s (2001) description of a “representative farm” of 1500 ha east of Condobolin and assumed a combination of cereal cropping and sheep grazing on a seven-year rotation for each paddock. The rotation features three years of cropping (one year of long-fallow wheat, one year of short-fallow wheat, one year of short-fallow barley) and four years of improved pasture (including pasture establishment in the first year). A similar seven-year rotation was employed by Abadi et al. (2006) for a typical farm in the NSW Central West. While the assumed rotation appears appropriate based on previous research, it should be noted that crop and pasture rotations can vary significantly from farm to farm (Patton and Mullen 2001). Drought can also cause disruptions to rotation cycles, as evidenced by a 23% drop in the average area of winter grains harvested for 2001-2009 compared to 1993-2000 (NSW Trade & Investment 2011). Given that 2010 was the first good winter cropping season at Condobolin following extended drought, rotation patterns may take some years to stabilise.
275 Table 6.10: Parameters used in the typical agriculture (1500ha) Condobolin model. Parameter Base case Source(s) for base Sensitivity Source(s) for assumption case assumption range sensitivity range Area under LF wheat: 214 ha Patton & Mullen – – each crop SF wheat: 214 ha (2001). LF= long each year SF barley: 214 ha fallow, SF=short Pasture: 856 ha fallow. (214 ha under establishment, 642 ha maintained) Annual crop LF wheat: 2.4 t/ha Abadi et al. (2006), – – yields SF wheat: 1.6 t/ha NSW Government SF barley: 1.7 t/ha (2011b) Crop prices LF wheat: $305/t NSW Government 50%-125% Patton & SF wheat: $255/t (2011b) of 2011 Mullen (2001), SF barley: $235/t prices Abadi et al. (2006), 25% above 2011 prices Crop costs LF wheat: 318/ha NSW Government – – per hectare SF wheat: $277/ha (2011b) SF barley: $277/ha Pasture est: $173/ha Crop levies 2.05% of crop value NSW Government – – & insurance (combined) (2011b) Livestock 4.0 dry sheep Kingwell et al. 2.1-5.3 Patton & carrying equivalent (DSE) (2003) DSE/ha Mullen (2001), capacity per ha of whole Abadi et al. farm (2006)
276 Parameter Base case Source(s) for base Sensitivity Source(s) for assumption case assumption range sensitivity range Flock size 5455 NSW Government – – (wethers) (2011a) Annual 31,003 kg adult NSW Government – – wool & wool 1373 kg (4- (2011a) adjusted livestock mth-olds) for flock size sales 2160 kg crutch wool 1026 CFA wethers Wool and Adult wool: NSW Government 50%-125% Min: 2001 livestock $6.35/kg (2011a) of 2011 prices (Patton sale prices 4-mth-olds: prices & Mullen $3.37/kg 2001) Crutching: $4.00/kg Max: +25% CFA wethers $124 ea. Annual Replacement NSW Government Replacement – livestock wethers: $87,360 (2011a) adjusted costs vary enterprise (incl. cartage) for flock size. with costs (fees, Wool tax: 2% of Supplementary feed livestock husbandry, sales Sheep fees: level of 11.7 prices above replacement 5% sales kg/head/yr from (50-125%). stock etc) Supplementary Abadi et al. (2006) Supp. feeding: $10,185 feeding costs Other costs: vary with $93,710 grain prices above (50- 125%)
277 For simplicity, it was assumed that any conversion of land to mallee would reduce the area used for each crop/pasture activity in equal measure (i.e. 7 ha converted to mallee would result in 1 ha less of long-fallow wheat, 1 ha less of short-fallow wheat, 1 ha less of short-fallow barley and 4 ha less of pasture). This assumption is more likely to be valid if small blocks or strips are planted across a farm, rather than a single paddock being converted to a block planting.
The typical agriculture model assumed that the land had already been cleared and that appropriate infrastructure such as fencing and drainage were already in place. Crops yields and livestock carrying capacity were based on previous studies in the region. For the sake of simplicity, the sheep enterprise was assumed to be an all-wether merino enterprise producing 20-micron wool according to the farm budget model outlined by Industry and Investment NSW (NSW Government 2011a). Prices and costs were primarily sourced from Industry and Investment NSW gross margin farm budget data (NSW Government 2011a, 2011b), which is provided in full at Appendix E53. The sensitivity analyses considered the impacts of a 50% fall in wool, sheep or grain prices, as well as a 25% increase in prices. At the time of Patton and Mullen’s (2001) analysis of a typical Condobolin farm, grain and wool prices were 40-50% lower than in 2011 and sheep prices were 50-80% lower (depending on age).
Central Tablelands
For the Central Tablelands supply-side modelling, three sites (Oberon, Bathurst and Mudgee) were selected to represent the three subregions identified in Chapter 5 (SE, SW and N respectively). Based on the interview and survey results, the typical agriculture model was based on sheep grazing on improved pasture, while the agroforestry model considered a number of potential native tree species (Table 6.11). The shortlist of agroforestry species was compiled from a combination of the survey and interview results, past agroforestry trial sites identified in the region (Allan Wilson pers. comm.) and previous studies covering the Central Tablelands or adjacent areas
53 As NSW Government (2011b) did not provide costs for short-fallow wheat in the Central West (west), costs were assumed to be the same as short-fallow barley following Patton & Mullen (2001).
278 (Stirzaker et al. 2002, Booth, Jovanovic, Snowdon, Mummery, Battaglia, Sands et al. 2007, Booth & Ryan 2008, Polglase et al. 2008, Bennell et al. 2009).
As highlighted in Table 6.11, the species most commonly cited by landholders did not correspond with those for which productivity data was widely available. The species most commonly identified in the interviews and survey were mostly local species that were known to have good survival rates in non-commercial plantings, such as Eucalyptus viminalis (manna gum) and E. melliodora (yellow box). The species for which most data was available were generally established plantation species that had been produced commercially in other regions, such as E. globulus (Tasmanian blue gum) and E. nitens (shining gum).
Table 6.11: Species shortlisted for the Central Tablelands supply-side modelling.
Species Survey/ Trials/ Data Interviews Studies Eucalyptus viminalis (manna gum) 999 9 E. melliodora (yellow box) 99 E. camaldulensis (river red gum) 99 9 Acacia spp. (esp. silver wattle) 99 9 Casuarina spp 99 9 E. globulus (Tasmanian blue gum) 9 999 999 E. sideroxylon (red ironbark) 9 9 E. nitens (shining gum) 99 99 E. cladocalyx (sugar gum) 99 9 E. grandis (flooded gum) 9 9
Productivity data (Table 6.12) was available for only a handful of species based on modelling undertaken by Booth et al. (2007), Polglase et al. (2008) and Bennell et al. (2009). Additional modelling was undertaken specifically for this thesis using the 3-PG model (Physiological Principles Predicting Growth) developed by Landsberg and
279 Waring (1997)54 and 3-PG calibrations for E. globulus, E. cladocalyx and E. grandis developed by Sands & Landsberg (2002), Paul et al. (2007) and Almeida et al. (2004) respectively.
Table 6.12: Yield estimates for species considered for the agroforestry model.
Species Source Biomass Yield (t DM/ha/yr)
SE SW N
E. globulus or Polglase et al. (2008) – 4-9 E. grandis Pulpwood production model – Southern Wet zone
E. nitens Booth et al. (2007) – growth - 6-12 model for Murray-Darling basin
E. globulus Bennell et al. (2009) - 500mm - 15 mean annual rainfall
E. cladocalyx Bennell et al. (2009) - 500mm - 17 mean annual rainfall
E. viminalis Bennell et al. (2009) - 500mm - 10 mean annual rainfall
E. globulus 3-PG modelling 13 8 7
E. cladocalyx 3-PG modelling 14 9 8
E. grandis 3-PG modelling 7 11 13
Baseline for economic modelling 12 8 8
The 3-PG modelling results shown in Table 6.12 were generated using using 3-PGpjs version 2.5 in Microsoft ExcelTM, assuming the harvest of all above-ground biomass (stem plus foliage) at age 10. The models covered one site in each Central Tablelands
54 The 3-PG version used was 3-PGpjs version 2.5 in Microsoft ExcelTM. Advice on the selection of parameters was provided by Dr Joe Landsberg, one the 3-PG model’s developers.
280 sub-region discussed in Chapter 5, with the selected sites being Oberon (SE), Bathurst (SW) and Mudgee (N). The main inputs required for the 3-PG modelling of the three sites were: x average monthly climatic data, sourced from the Bureau of Meteorology (2012a); x soil type, determined by reviewing surrounding soil profiles in the NSW Natural Resources Atlas (NSW Government 2011c); and x stocking rates (stems/ha), assumed to be 1500 for E. globulus, 1300 for E. cladocalyx and 1250 for E. grandis following Polglase et al. (2008).
The full set of parameters used in the 3-PG modelling is presented in Appendix F.
For the purposes of the supply-side modelling for the Central Tablelands, it was not necessary to select one distinct agroforestry species. Rather, the baseline figures shown in Table 6.12 represent mid-range yields based on the previous studies and 3-PG modelling. The baseline figures most closely resemble the 3-PG model outputs for E. globulus (Tasmanian blue gum) and are midway between the lower estimates of Polglase et al. (2008) and the higher estimates of Bennell et al. (2009).
Fieldwork was also undertaken to determine whether the baseline biomass yields were achievable in the field. This involved visiting three agroforestry trial sites in the Central Tablelands in October 2011. The first site was an E. nitens plantations near Oberon, the second was an E. globulus plantation near Ilford and the third was a hybrid E. globulus x E. grandis plantation near Lue (Figure 6.16). While each plantation was established in 2000, other key parameters such as annual rainfall, soil type, slope and planting density differed between the sites.
281
Figure 6.16: Agroforestry trial sites used to test biomass yield assumptions.
At each field site, measurements were recorded for diameter at breast height (DBH) and tree height across two plots ranging from 800 to 1250 m2. DBH was recorded for every tree within each plot and a representative sample of trees were measured for height. Dr Sebastian Pfautsch of the University of Sydney provided expert advice for this task, while Dr Crelis Rammelt (Institute of Environmental Studies, UNSW) and Chanci King (Blue Mountains World Heritage Institute) also assisted with tree measurements. The DBH measurements were used to calculate total basal area per hectare for each plot, which was compared to the value calculated for basal area per hectare at each site using a 3-PG model for E. globulus 55.
Unlike the 3-PG results shown in Table 6.12, which were based on average monthly climatic conditions, the 3-PG modelling for the three field sites used month-by-month
55 Basal area was used rather than biomass yield to test the 3-PG model as it was not possible to weigh trees or calculate their average density. E. globulus was used for 3-PG modelling at each site as no calibration is currently available for E. nitens or E. globulus x E. grandis.
282 climate data for each location for the period 2000-2011. The climate data for each field site was interpolated from surrounding weather station records using the SILO Data Drill tool hosted by the Queensland Climate Change Centre of Excellence (Queensland Government 2011). Full 3-PG parameters are provided in Appendix F.
Figure 6.17 provides a comparison of the field measurements with the 3-PG model results for the three field sites. While the basal area results recorded at the Oberon field site are very close to the 3-PG predictions, the field results for Ilford and Lue are only around 50% of those predicted by the model.
Figure 6.17: Field site measurements of tree basal area per hectare compared to 3-PG model predictions.
The failure of the 3-PG model to accurately predict growth rates at Ilford and Lue could be due to a number of factors, including: x local soil, landscape or microclimatic conditions that were not fully captured in the model parameters; x the fact that the 3-PG model for E. globulus has been developed primarily from plantation data from winter rainfall regimes south of the Central Tablelands (Sands & Landsberg 2002); and/or
283 x the failure of the 3-PG model to fully predict tree growth under the drought conditions affecting the region between 2002 and 2007. Based on the wide variation between the results of the 3-PG modelling and fieldwork for Ilford and Lue, a sensitivity range of +/-50% of the base case biomass yield assumptions was also modelled for agroforestry in the Central Tablelands. The full range of base case assumptions and sensitivity ranges for each model parameter are shown in Table 6.13. The yield figures shown in Table 6.13 are presented in green tonnes per hectare (gt/ha) and hence are double the yield figures shown in Table 6.12 (as biomass is assumed to be 50% dry matter by weight). While the actual dry matter percentage can vary by species and age, it was assumed that any reduction in green biomass tonnage due to a lower % dry matter would be offset by a higher price per green tonne (as it is the dry matter content that bioenergy producers value). A lower moisture content could also reduce costs such as transport and drying, but this was not directly considered in the modelling.
Many of the cost assumptions shown in Table 6.13 have been drawn from modelling undertaken by Polglase et al. (2008) of a short rotation coppicing system for bioenergy based on E. globulus in Australia’s “Southern Wet” zone (which covers most of the Central Tablelands). Harvesting was assumed to occur every ten years via coppicing, resulting in one set of establishment costs followed by three harvest rotations across the 30 year life of the model. While regrowth after coppicing is likely to be faster than after initial growth (Polglase et al. 2008), the model employs the conservative assumption of identical growth rates in each rotation. Alternative rotation lengths of 5 and 15 years were also modelled, under the assumption that mean annual biomass yield would be unchanged56.
56 3-PG modelling for E. globulus indicated that varying rotation length would have a minor impact on mean annual yield (98-107% of base case) depending on the sub-region.
284 Table 6.13: Parameters used in the agroforestry production model for the Central Tablelands. Parameter Base case Source(s) for Variations used in assumptions base case figure sensitivity analysis
Mean annual SE: 24 gt/ha/yr Table 6.11 +/-50% (Table 6.11) biomass yield SW: 16 gt/ha/yr N: 16 gt/ha/yr
Biomass price $40/gt Demand-side $20-100 (demand-side (factory gate) modelling & modelling and Polglase et Ximenes et al. al. 2008) (2012)
Rotation 10 years Polglase et al. 5-15 years length (2008), Bennell et al. (2009)
Establishment Tree establishment = Polglase et al. $740/ha (Bennell et al. costs (one-off) $1500/ha (2008) 2009) to Post-establishment = $2220/ha (Polglase et al. $150/ha 2008) Roading = $200/ha Total Establishment = $1850/ha
Management $80/ha Polglase et al. $5/ha (Bennell et al. 2009) costs (every (2008) to $80/ha (Polglase et al. year) 2008)
Harvest costs $14/gt Polglase et al. $10/gt (Bennell et al. (harvest years (2008) 2009) to $30/gt (Polglase only) et al. 2008)
285 Parameter Base case Source(s) for Variations used in assumptions base case figure sensitivity analysis
Average SE: 50 km Average SE: 50 km (to Oberon) transport SW: 90 km distance by road SW: 60 km (to Bathurst) distance N: 180 km to Oberon from N: 60 km (to Mudgee) each sub-region (private rural land only)
Transport $0.12/gt/km Polglase et al. $0.05/gt/km (Bennell et al. costs to (2008) 2009) to processing $0.23/gt/km (Total plant (harvest Catchment Management years only) Services 2008)
Sensitivity analyses were undertaken for establishment, management and harvest costs based on estimates from Polglase et al. (2008) and Bennell et al. (2009), which suggest that costs will tend to increase with rainfall and the value of products (e.g. costs for pulpwood are higher than bioenergy). The base case assumptions for transport costs, drawn from Polglase et al. (2008), are similar to those used by Rodriguez et al. (2011) for pulpwood, lower than those used by Total Catchment Management Services (2008) for mallee biomass and higher than those used by Bennell et al. (2009) for various biomass types. Average transport distances for the base case were based on a single processing facility in Oberon, while a variation was also modelled in which facilities were assumed to be established at Bathurst and Mudgee as well. Plantations were assumed to be spread evenly across all private rural land in each sub-region (i.e. excluding urban areas, National Parks, State Forests and other crown land). A tortuosity factor (ratio of road distance to straight line distance) of 2 was applied to locations in the SE sub-region and 1.5 to locations in the SW and N sub-regions, based on transport distance calculations made using Google Maps Australia (Google 2011).
The parameters selected for the Central Tablelands typical agricultural model are shown in Table 6.14. Carrying capacity in dry sheep equivalent per hectare (DSE/ha)
286 was based on “typical” tablelands grazing properties for Bathurst, Oberon and Mudgee published by the NSW Land and Property Management Authority (2010). As at Condobolin, the sheep enterprise at each site was assumed to be all-wether 20-micron merino, drawing on gross margin data from Industry and Investment NSW (NSW Government 2011a). As with the Condobolin model, it was assumed that no new infrastructure was required.
Table 6.14: Typical agriculture parameters used in the Central Tablelands model.
Parameter Oberon Bathurst Mudgee Source Sensitivity base case base case base case range
Property size 191 ha 683 ha 943 ha Land and – Property Livestock 12.6 4.5 DSE/ha 3.4 DSE/ha 50%-150% Manage- carrying DSE/ha of base case ment capacity Authority (2010)
Flock size 2182 2818 2909 NSW – (wethers) Government (2011a)
Annual wool 12,401 kg 16,019 kg 15,535 kg NSW – & livestock adult wool adult wool adult wool Government sales 549 kg (4- 709 kg (4- 732 kg (4- (2011a) mth-olds) mth-olds) mth-olds) adjusted for flock size 864 kg 1116 kg 1152 kg crutch wool crutch wool crutch wool
410 CFA 530 CFA 547 CFA wethers wethers wethers
287 Parameter Oberon Bathurst Mudgee Source Sensitivity base case base case base case range
Wool and Adult wool: $6.35/kg NSW 33%-125% livestock sale Government of 2011 4-mth-old wool: $3.37/kg prices (2011a) prices Crutching wool: $4.00/kg
CFA wethers: $124 ea.
Annual Replace- Replace- Replace- NSW Replace- livestock ment ment ment Government ment wether enterprise wethers: wethers: wethers: (2011a) cost varies costs (fees, $34,944 $45,136 $46,592 adjusted for with husbandry, (incl. (incl. (incl. flock size. livestock replacement cartage) cartage) cartage) price above stock etc) (33-125%) Wool tax: Wool tax: Wool tax: 2% of sales 2% of sales 2% of sales
Sheep sales Sheep sales Sheep sales commiss- commiss- commiss- ion: 5% of ion: 5% of ion: 5% of sales sales sales
Supp. Supp. Supp. feeding: feeding: feeding: $4501 $5813 $6001
Other costs: Other costs: Other costs: $33,924 $59,694 $70,774
288 Policy analysis for supply-side modelling
Following the calculation of returns from agroforestry and typical agriculture for each each case study model, a range of policy options targeted at the landholder level were also analysed. These included assistance with establishment costs, payments for sequestered carbon and the allocation of LGCs to landholders in advance of actual generation. Assistance with establishment costs and payments for sequestered carbon were raised regularly during landholder consultation at both case study sites. The LGC advancement option was not raised during the social analysis, but could provide a potential solution to landholder concerns about future regulatory change and uncertainty of returns in the LGC market. A precedent exists with small-scale solar photovoltaic (PV) generation under the Australian Government’s Small-scale Renewable Energy Scheme, whereby home-owners are able to receive credits upfront for the expected generation of their rooftop units over a lifetime of up to 15 years (Office of the Renewable Energy Regulator 2011).
Three schemes for establishment support were considered. The first assumed that a government agency would provide a grant for half of the base case establishment costs. The second option was a low-interest loan from government, with capital assumed to be provided at the Reserve Bank of Australia’s June 2011 cash rate of 4.75% (Reserve Bank of Australia 2011). This was assumed to reduce the discount rate applied across the life of the project from 6% to 1.5% p.a. (i.e. 4.75% minus the inflation rate at 3.3%). The third option assumed that establishment and management costs were provided through a Managed Investment Scheme (MIS). For this option, it was assumed that an investor in the highest marginal income tax bracket (45%) paid for all establishment and annual management costs and was able to claim these in non-harvest years as a tax deduction, effectively meaning that the Australian Government was covering 45% of these costs. However, it was also assumed that 30% of funds invested in the MIS would be used for costs not directly related to plantation establishment. This is in line with the ATO ruling on MIS expenditure discussed in Chapter 4 and has the effect of increasing the overall cost of establishment and management (including direct and indirect costs) to 143% of the base case assumption. These factors were
289 represented in the MIS model by multiplying base case establishment costs and management costs (in non-harvest years only) by 1.43 and then by 0.55.
Three carbon sequestration options were considered. The first two assumed that credits were only available for above-ground biomass, with carbon prices set at $25 and $50/t
CO2-e. The third option assumed that credits were available for below-ground carbon as well, with the carbon price set at $25/t CO2-e. For above-ground carbon, credits were assumed to be awarded based on the average amount of above-ground biomass present over the life of the plantation. This was assumed to be 50% of the biomass present at the time of harvest or 2.5 gt/ha at Condobolin, 120 gt/ha in the SE sub- region of the Central Tablelands, and 80 gt/ha in the SW and N sub-regions.
Below-ground biomass was based on a static rather than average figure, as it is not removed at harvest time. Below-ground biomass for Condobolin was assumed to be 3.1 gt/ha, which is 62% of above-ground biomass at the time of each harvest, following estimates from Polglase et al. (2008, p. 49) for mallee at 500 mm mean annual rainfall. The Central Tablelands figures were based on the ratio of root biomass to stem and foliage biomass at age 10 (i.e. time of harvest) from the 3-PG modelling of E. globulus
(0.33 in SE, 0.46 in SW, 0.49 in N). All green biomass figures were converted to CO2- equivalent figures by multiplying them first by 0.25, based on a 50% moisture content and 50% carbon content by dry weight (Harper, Smettem & Tomlinson 2005), and then by 3.67, based on the molecular weight of CO2 (Liew 2009). It was assumed that carbon payments would be made as a one-off payment at the start of the project and there were no transaction costs associated with verification or trading.
Two LGC advancement options were considered, with one advancing ten years’ worth of LGCs to landholders at the time of plantation establishment and one advancing thirty years’ worth of LGCs. These models employed the assumption that each green tonne of biomass would produce $27 worth of LGCs. This was based on the 5 MW biomass generation model from section 6.1, which assumed 0.675 MWh/gt and an LGC price of $40. All LGCs that could be created from harvested biomass over a period of either ten years or thirty years were assumed to be granted to the landholder at the start of the project and sold immediately for $40 each. To account for this
290 upfront payment, $27 was deducted from the base case price paid for each tonne of biomass at the time of harvest, reducing it from $40/gt to $13/gt. No transaction costs were included in the model.
6.6.2 Results
Condobolin
The mallee agroforestry model for Condobolin produced a negative return under base case assumptions, with an EAV of -$89/ha/yr. This result indicates that income from the sale of biomass would not recoup the costs for establishment, management, harvesting and transport to a local bioenergy facility. In contrast, the typical agriculture model produced a positive EAV of $161/ha/yr. This figure is higher than the $83/ha/yr estimated by Total Catchment Management Services (2008) and the $103/ha/yr estimated by Abadi et al. (2006) for conventional agriculture around Condobolin, most likely due to higher commodity prices in 2011.
The sensitivity analysis for the mallee agroforestry model showed that variations in key assumptions can have substantial imapcts on EAV. Figure 6.18 shows the impact of varying the assumptions used for (a) biomass price, (b) biomass yield, (c) establishment costs, (d) annual management costs, (e), harvest costs and (f) transport costs. The factors producing the greatest impact on EAV are biomass price, biomass yield, establishment costs and transport costs. EAV becomes positive at a biomass price of around $60/gt and approaches the return offered by conventional agriculture (base case) at around $95/gt. For biomass yield, the model suggests that 16 gt/ha/yr would be required for the EAV of mallee cropping to match that of typical agriculture. Such yields have been estimated for narrow mallee strips in WA (URS Australia 2009), but they are more than twice as high as yields considered “optimistic” for the Condobolin area (i.e. 6 gt/ha/yr) by Total Catchment Management Services (2008).
291
Figure 6.18: Sensitivity analysis results for mallee biomass production. Base case results shown in red. EAV for typical agriculture (base case) was $161/ha/yr.
292 The model results also show that a positive EAV could be achieved if establishment costs were to be reduced from the base case level of $2063/ha to the $463/ha estimated by Abadi et al. (2006) for the NSW Central West. However, even with establishment costs of zero, EAV remains well below that of typical agriculture. A reduction in base case transport costs by around two-thirds would reduce losses by more than 50%, but would not in itself lead to a positive EAV.
Figures 6.18 (d) and 6.18 (e) highlight the risk of further declines in EAV from higher management and harvest costs. However, the higher-range costs used in these sensitivity analyses relate to very different production systems than are proposed for Condobolin, with larger trees and narrower strips of mallee (van Bueren & Vincent 2004, URS Australia 2009). A change in harvest frequency from annual to once every 18 months was also modelled. This produced a slightly improved EAV (-$78/ha/yr), but only if there is assumed to be no change to harvest costs ($/ha) or the growth rate of mallee.
The sensitivity analysis undertaken for the typical agriculture model for Condobolin also highlighted a number of key factors that can influence EAV. Figure 6.19 shows the sensitivity analysis results for (a) grain prices, (b) wool prices, (c) sheep prices (d) combined grain, wool and sheep prices, and (e) carrying capacity. The EAV for typical agriculture shows greatest sensitivity to grain prices, with a 50% fall in grain price producing a 64% fall in EAV. Wool prices have a moderate effect on EAV and sheep prices have little impact, as the assumed sheep enterprise was primarily for wool rather than meat production.
A simultaneous drop in grain, wool and sheep prices to 50% of their 2011 levels (i.e. similar prices to 2001) produces a negative EAV of -$24/ha/yr. While mixed cropping and grazing at these price levels still outperforms the base case mallee scenario, the modelling highlights that low prices for grain, wool and sheep, together with rising prices for mallee biomass (and/or falling costs) could produce a scenario in which mallee cropping offers better financial returns than cropping and grazing.
293
Figure 6.19: Sensitivity analysis results for the Condobolin typical agriculture model. Base case results shown in red.
294 Central Tablelands
Table 6.15 compares the base case EAV results from agroforestry in each of the three sub-regions with the base case EAV results for typical agriculture. These results indicate that, with a single bioenergy facility in Oberon, only the SE sub-region would generate a positive EAV. Furthermore, even in the SE sub-region, the EAV from agroforestry would be well below the EAV for sheep grazing. With facilities at Bathurst and Mudgee as well, all sub-regions produce a positive EAV for agroforestry, albeit at levels that are substantially lower than the EAVs for grazing.
Table 6.15: Comparison between base case EAV for agroforestry and sheep grazing in the Central Tablelands. Sub- EAV for EAV for agroforestry – EAV for typical region agroforestry – Oberon, Bathurst & agriculture – sheep Oberon facility only Mudgee facilities grazing ($/ha/yr) ($/ha/yr) ($/ha/yr) SE $106 $106 $300 SW -$37 $14 $85 N -$190 $7 $54
The SE sub-region has a number of advantages for agroforestry. If the sole bioenergy facility is assumed to be at Oberon, the SE has a distinct transport advantage. It also has an advantage in terms of biomass yield due to higher rainfall levels. However, the higher rainfall also increases carrying capacity for sheep grazing, making it difficult for agroforestry to compete on a purely financial basis under base case assumptions.
The sensitivity analysis for agroforestry in the Central Tablelands showed that biomass price had the greatest impact on EAV across the range of values modelled (Figure 6.20). Assuming a single facility at Oberon, the biomass price required to make agroforestry competitive with typical agriculture would be $51/gt in the SE, $50/gt in the SW and $60/gt in the North. If facilities were located in Bathurst and Mudgee as well, the model shows that agroforestry in those sub-regions would become competitive with typical agriculture at biomass prices of $46/gt (SW) and $44/gt (N).
295 These prices represent a relatively small increase in biomass price above the base case assumption of $40/gt. This suggests that bioenergy-based agroforestry is much closer to be financially competitive with typical agriculture in the Central Tablelands than it is at Condobolin.
Figure 6.20: Sensitivity analysis results for biomass price in the Central Tablelands. Graph (a) assumes a single facility at Oberon, while (b) assumes three separate facilities. Base case biomass price is indicated by the red line on the x-axis. The coloured lines on the y-axis indicate the base case EAV for typical agriculture in each sub-region.
Figure 6.21 shows the results of the agroforestry sensitivity analysis for the remaining parameters modelled (assuming a single Oberon facility). After biomass price, the model showed the greatest sensitivity to biomass yield. This was particularly evident in the SE sub-region, where a 50% yield reduction would result in a negative EAV. Given that the tree measurements for Lue and Ilford (discussed in section 6.1.1) showed results that were around 50% lower than the 3-PG estimates for those sites, lower-than- expected yields represents a major risk for agroforestry in the Central Tablelands.
The modelling showed that changes to harvest costs had the greatest impact in the SE sub-region, while transport cost reductions had the greatest impact in the North due to the longer distances involved. A reduction in harvest frequency from 10 years to 5 years produced a 50% increase in EAV in the SE as a result of income being obtained earlier (assuming that growth rates and harvest costs per green tonne were unaffected).
296 Figure 6.21: Central Tablelands agroforestry sensitivity analysis results. Graph (a) shows biomass yield, (b) harvest frequency, (c) establishment costs, (d) annual management costs, (e) harvest costs and (f) transport costs. All assume a single facility at Oberon. The red line on the x-axis indicates the base case assumption for each parameter.
297 The typical agriculture model for the Central Tablelands showed high sensitivity to wool prices and low sensitivity to sheep prices (Figure 6.22), similar to Condobolin. The Oberon model (SE) showed a greater sensitivity to declining wool prices than Bathurst (SW) or Mudgee (N), but it still produced higher EAVs than the other two sites under all scenarios. The model results show that, if wool prices were to fall to around 55-60% of base case prices (i.e. similar to 2001 prices), typical agriculture would deliver similar returns to agroforestry in each sub-region (assuming three separate facilities). A drop in carrying capacity to around 45% of the base case level would also produce an EAV similar to agroforestry in the SE sub-region. However, land with lower carrying capacity (e.g. “marginal” land) is likely to also produce lower biomass yields from agroforestry.
Figure 6.22: Sensitivity analyses for typical agriculture in the Central Tablelands. The red line on the x-axis indicates the base case assumption for each parameter.
298 Policy analysis
The results of the policy analysis for Condobolin are shown in Figure 6.23. The 30- year LGC advancement option had the greatest impact on the EAV of mallee cropping and was the only policy option capable of turning the negative base case EAV into a positive value (albeit still well below the EAV for typical agriculture). While the ten- year LGC advancement option produced less than one-sixth of the benefit of the 30- year scheme, it is a much more realistic option, given that the LRET scheme is due to be phased out between 2020 and 2030 (Office of the Renewable Energy Regulator 2011). The option of Government support for 50% of establishment costs was marginally more beneficial than the option of a low interest loan. Both of these options were substantially more beneficial than the MIS option, largely due to the increased overheads assumed for MIS investment diluting the benefit provided by the tax breaks. While the three carbon schemes delivered minimal benefit to the project EAV, including below-ground carbon had more than twice the impact on EAV of including above-ground carbon only (at a carbon price of $25/t CO2-e).
Figure 6.23: Impact of policy options on mallee agroforestry EAV at Condobolin. AG = above ground, BG = below ground. EAV for typical agriculture was $161/ha.
299 The policy analysis produced some quite different results for the Central Tablelands (Figure 6.24) compared to Condobolin. While the 30-year LGC advancement option had the greatest impact on EAV at both sites, the scale of this impact was much greater in the Central Tablelands. The carbon credit schemes also had a much greater impact than at Condobolin, with a $50 carbon price (on above-ground carbon only) boosting the EAV for agroforestry above that of typical agriculture in all three sub-regions. The greater impact of the carbon options in the Central Tablelands was mostly due to the longer wait between harvests, which increased the average amount of carbon sequestered over time. The higher growth rates in the Central Tablelands also contributed to this impact. The 50% establishment support option had a similar impact on EAV in the Central Tablelands and Condobolin in absolute terms (i.e. adding around $60-80 to EAV). However, the stronger performance of the other policy measures in the Central Tablelands reduced the relative impact of this option. The low- interest loan option had a greater impact on EAV in the tablelands compared with Condobolin due to the longer wait for returns.
Figure 6.24: Impact of policy options on agroforestry EAV in the Central Tablelands. The coloured lines on the y-axis indicate the change in EAV required to match typical agriculture in each sub-region (assuming a single facility at Oberon).
300 6.3 Discussion
What bioenergy options involving woody energy crops may be viable in the case study regions (including consideration of economic benefits and barriers)?
The economic modelling results presented in this chapter suggest that, under base case assumptions, agroforestry for bioenergy would not be competitive with typical agriculture on a purely financial basis at either case study site. The differential between agroforestry and typical agriculture was larger for Condobolin than for the Central Tablelands. However, the Central Tablelands features greater uncertainty regarding biomass yields, as demonstrated by the results of tree measurements in the field. The base case modelling indicated that, in addition to being uncompetitive with typical agriculture, agroforestry at Condobolin would actually represent a loss-making venture. The same result was also found for agroforestry in the SW and North sub- regions of the Central Tablelands if biomass had to be transported to Oberon.
While the base case results showed that agroforestry was uncompetitive with typical agriculture, the sensitivity analysis results showed that agroforestry could become competitive if there were increases in biomass prices, falls in biomass production costs, falls in grain or wool prices and/or policy support for landholders investing in agroforestry. The extent to which biomass prices would need to increase above the base case assumption of $40/gt in order to make agroforestry competitive with typical agriculture was much lower for the Central Tablelands (10-50% above base case) compared with Condobolin (140%). In order for mallee production at Condobolin to reach parity with typical agriculture, there would most likely need to be a combination of moderate increases in biomass price (e.g. 50% above base case) along with substantial declines in grain and wool prices (e.g. to 2001 levels). Reductions in costs for mallee establishment, harvest and transport could also play an important role.
Based on the demand-side analysis, solid fuel options (briquettes for domestic use or pellets for export to Japan) appear to offer the best opportunity to achieve the biomass price levels required at Condobolin for parity with cropping and grazing. However, each of these options have risks. Briquettes present risks such as uncertain costs and
301 the potential to flood the small domestic market. Pellets carry risks associated with changes in the exchange rate and overseas policy decisions that could influence demand and prices. In addition to the risks related to individual small-scale technologies, there is also a risk that the breakeven biomass prices calculated in the modelling will not translate into high biomass prices being paid to landholders due to competition from cheaper biomass sources, such as residues from sawmilling and forest harvesting. Landholders may be able to attract higher prices in the early stages of a regional bioenergy industry, especially if they are co-owners of a briquette or pellet facility, but mallee biomass may be out-competed as the industry matures and logistical pathways develop for cheaper biomass sources. Co-production modelling showed that producing eucalyptus oil alongside bioenergy could improve the financial performance of mallee cropping, but this option also present a risk of falling prices due to over-supply.
For the Central Tablelands, the modelling results showed that the biomass prices required for parity with typical agriculture may be achievable with larger-scale bioenergy facilities producing liquid fuels or electricity. For these larger-scale options, the presence of other biomass sources (e.g. sawmill residues at Oberon) may actually be an advantage for agroforesters rather than a threat. The presence of existing biomass sources increases the chances of a facility being built, as such facilities require large guaranteed biomass supplies, which new plantations alone may be unable to provide. In addition, larger facilities are likely to exhaust cheaper sources of biomass more quickly, requiring operators to increase their prices over time to attract biomass from new dedicated plantations.
The issues relating to existing residues and new dedicated bioenergy plantations are clearly highlighted in the results of biomass supply modelling for the Wallerawang power station undertaken as part of the CSIRO’s Central NSW project discussed in Chapter 4 (Rodriguez et al. 2011c). Cost-supply modelling by the CSIRO (Figure 6.25) suggests that sawmill residues are likely to be the lowest-cost biomass sources available for use at Wallerawang, followed by forest residues, but also that these sources are limited. According to Figure 6.25, once biomass demand exceeds around 250,000 dry tonnes (i.e. the scale of the ethanol plant modelled in this chapter),
302 biomass from dedicated energy plantations would be required, with a commensurate jump in the price that a bioenergy facility would need to pay for biomass. Thhe results from Rodriguez et al. (2011c) also suggest tthat mallee eucalypts within 80 kiilometers of Wallerawang could be a potential agroforestry option, which differs from tthe approach taken in this thesis of limiting thee modelling of mallee production to the area further west around Condobolin and Forbes.
Figure 6.25: Cost-supply curve for potential biomass sources for co-firinng at Wallerawang, NSW. Reproduced from Rodriguez et al. (2011c).
The case study modelling also suggests that small-scale electricity generation could provide a competitive bioenergy option at either case study site if a feed-in tariff is introduced that raises the prices received for bioelectricity. A strategy of geneerating electricity only during peak times using biomass gasification could also yield a higher average ellectricity price. However, the modelling for the 5 MW biomass-only option suggested that the higher electricity prices available at peak times may not be enough to compensate for the higher capital recoverry costs per MWh associated with a peak- only strategy. It is possible that larger-scale gasification technology may offer lower capital coosts per MW of capacity than those assumed in the modelling (ACIL Tasman
303 2009), which could enhance the viability of a peak-only generation strategy. Moreover, such a strategy could have benefits for the renewable electricity sector more broadly, as power from gasified biomass could help to balance out periods of low output from solar or wind generators. Elliston, Diesendorf and MacGill (2012) envisaged such a role for biomass gasification in their simulation of 100% renewable electricity for Australia’s National Electricity Market.
Finally, it is important to remember that the viability of bioenergy-based agroforestry cannot be determined solely by its ability to deliver a return that is competitive with typical agriculture. The social analysis presented in Chapter 5 showed that a substantial proportion of the landholders interviewed or surveyed at each case study site would be prepared to consider agroforestry that offered a lower return than their current land use, provided that it offered other benefits, such as enhanced economic resilience or environmental co-benefits. In addition, there were also a number of landholders, particularly in the Central Tablelands survey, who would require more than their current returns in order to take on a risky and complex land use option such as bioenergy-based agroforestry.
Economic valuation of environment co-benefits has not been included in the modelling presented in this Chapter, but could represent a future research opportunity for the case study sites. This would require careful consideration of appropriate valuation methodologies, the selection of discount rates and the substitutability of different types of capital, especially where critical natural capital is concerned.
What policy measures could be employed to promote and guide agroforestry land uses and develop a regional bioenergy industry?
From a policy perspective, the demand-side modelling results indicate that two of the most effective measures for enabling bioenergy producers to increase the prices they could pay for biomass would be the introduction of a carbon price on petrol and diesel or an increase in LGC prices. The former approach would benefit ethanol and renewable diesel, while the latter would benefit bioelectricity. Under the Australian Government’s current plans for carbon pricing, light vehicles will be exempt, but
304 diesel use by heavy on-road vehicles may be included from 2014-15 (Treasury 2011). LGC prices are predicted to rise as targets increase up to 2020 and “phantom” certificates from small-scale sources disappear from the market (EnergyAustralia 2011). Assuming no carbon price, ROAM Consulting (2011) has forecast a 2020 LGC price of $73 (if no change is made to shortfall charges) or $107 (if the shortfall charge is increased). The modelling in this chapter indicated that an LGC price of $100 would make agroforestry to supply a 5 MW biomass-fired plant competitive with typical agriculture in the Central Tablelands, but not at Condobolin. If the carbon price proceeds as currently planned, LGC prices can be expected to be lower than they would be with no carbon price (as discussed in section 6.1.1), but the net effect for bioenergy projects should be neutral or slightly positive.
In terms of policy measures targeted at the landholder level, establishment support in the form of grants or low-interest loans appeared to be the most promising option for Condobolin, while payments for carbon sequestration appeared more promising for the Central Tablelands. This pattern also matches the social analysis results presented in Chapter 5, whereby carbon sequestration was viewed much more positively in the Central Tablelands than at Condobolin. Advancement of LGCs also offered strong financial benefits in the modelling, but only if a large advancement period was used, such as 30 years. Such a large advancement period is unrealistic given the remaining life of the LRET scheme (ending in 2030). There are also likely to be significant difficulties in ensuring that biomass that had been planted for bioenergy and awarded LGCs in advance was ultimately used for that purpose. This issue is discussed further in Chapter 8.
It is also possible to compare the relative impact of the leading demand-side and supply-side policy measures identified in this chapter to determine which policy measures would have the greatest impact on overall project EAV. This comparison is presented in Table 6.16. The supply-side results used for this comparison are simply a reproduction of the results shown in Figures 6.23 and 6.24. All supply-side models assume a biomass price of $40/gt and do not require that particular bioenergy option is specified. To determine the impact of demand-side policy interventions on EAV, the breakeven biomass price before and after the policy intervention have been used as
305 inputs to the supply-side agroforestry models for Condobolin and the Central Tablelands (SE sub-region only).
For the analysis of demand-side policy interventions in Table 6.16, only liquid fuels and electricity have been included, as the solid fuel models did not include any policy parameters. The policy interventions selected are: x a carbon price of $50 (i.e. around double the 2012 starting price); x an LGC price of $80 (i.e. double the 2011 price); or x a feed-in tariff (FiT) set at $80/MWh (i.e. double the Australian average wholesale electricity price in 2011).
An LGC price of $80 and a feed-in tariff of $80/MWh have the same effect on the electricity options in Table 6.16, as they both add additional revenue of $40 for every MWh of electricity generation. The same effect could also be achieved by awarding two $40 LGCs per MWh for bioenergy-based agroforestry.
In general, the results in Table 6.16 indicate that demand-side interventions would have a greater impact on project EAV than supply-side interventions. The greatest impact on EAV results from a doubling of the LGC price or electricity price. This result contrasts with the preference of most landholders interviewed or surveyed as part of the social analysis in Chapter 5 for support with establishment costs over demand- side interventions such as price support. However, the results shown in Table 6.16 support the views of a number of industry and government stakeholders that the Renewable Energy Target and carbon price are likely to be the key policy drivers for bioenergy-based agroforestry.
306 Table 6.16: Comparative impact of demand-side and supply-side policy interventions on project EAV at each case study site. Supply-side or Policy option Breakeven biomass EAV at Condobolin ($/ha/yr) EAV in SE sub-region of demand-side selected for analysis price ($/gt) Central Tablelands ($/ha/yr) (bioenergy use before after before after EAV change before after EAV change stated for policy policy policy policy from policy policy policy from policy demand-side) option option option option intervention option option intervention Carbon $25 AG only 40 40 -89 -85 4 106 306 6 Supply-side Carbon $50 AG only 40 40 -89 -81 8 106 506 206 options Carbon $25 AG+BG 40 40 -89 -80 9 106 438 138 (no particular 50% establishment 40 40 -89 -14 75 106 173 67 bioenergy use costs specified) 10-year LGC 40 40 -89 -65 24 106 314 14 advancement
307 Ethanol Carbon price $50 47.57 57.97 -56 -10 46 244 433 189 Renewable Carbon price $50 25.30 39.33 -154 -92 62 -162 94 256 diesel 5 MW biomass LGC price $80 or 14.23 41.23 -203 -84 119 -363 129 492 electricity FiT $80/MWh 3% co-firing at LGC price $80 or 10.60 43.04 -219 -76 143 - - - Condobolin FiT $80/MWh 3% co-firing at LGC price $80 or 22.95 55.39 - - - -204 386 590 Oberon FiT $80/MWh LGC = Large-scale Generation Certificate, FiT = feed-in tariff, AG = above-ground, BG = below-ground.
While Table 6.16 shows greater impacts from demand-side policy interventions, supply-side options may also have an important role to play. In particular, the results show that providing 50% of establishment costs at Condobolin or enabling agroforestry in the Central Tablelands to earn carbon credits could have a significant impact on the EAV of agroforestry in these locations. These options also have the advantage of being provided to landholders upfront rather than after harvesting and bioenergy production has taken place. This upfront cash flow reduces risks for landholders and helps to overcome barriers related to a lack of capital to invest in agroforestry. Furthermore, the demand-side results in Table 6.16 assume that there are no transaction costs and that all additional income resulting from the policy intervention would flow through to landholders. In reality, energy companies, plantation managers and brokers would all require a cut of any income generated from carbon credits or LGCs. Overall, these factors suggest there may be a role for both demand-side and supply-side policy interventions. Further consideration is given to the most appropriate of policy interventions in Chapter 8.
6.4 Conclusion
The results presented in this chapter highlight significant challenges in achieving widespread adoption of bioenergy-based agroforestry at either case study site based on current conditions. This is particularly the case for Condobolin, given low returns from mallee cropping and high wheat and wool prices at present. However, the modelling also showed that the current poor performance of agroforestry relative to typical agriculture could change if shifts are observed in key commodity and energy markets or if policy measures to promote bioenergy and agroforestry are applied strategically in each case study region.
One of the key factors identified in this chapter is a lack of detailed data on emerging bioenergy options and innovative agroforestry approaches that may be suited to the case study sites. New data for bioenergy production systems relating to costs, prices and capabilities could help to reduce the areas of uncertainty in the demand-side analysis, particularly in relation to options such as briquetting, biomass co-firing and thermo-chemical conversion for renewable diesel or jet fuel. Similarly, new data on
308 mixed-species plantations, the use of marginal land for agroforestry and the impacts of agroforestry on neighbouring land uses would help to tailor the economic analysis contained in this chapter to specific circumstances, rather than being restricted to a broad-scale monoculture model of plantation forestry.
When considering the economic analysis results presented in this chapter, it is important to remember that a significant proportion of landholders consulted through the social analysis indicated that the returns they would require from agroforestry may be different to what they would require from existing land uses. Thus, when taken in isolation, the results outlined in this chapter are not capable of fully describing the circumstances in which agroforestry for bioenergy would be viable. These results only describe the circumstances in which bioenergy-based agroforestry would be financially competitive with typical agriculture, and only then within the constraints of the assumptions used.
Some of the reasons cited by landholders in the social analysis for accepting lesser returns from agroforestry are analysed further in Chapter 7, including co-benefits related to landscape health, biodiversity and the management of environmental risks. Economic valuation of environmental co-benefits represents a potential area for future economic analysis in the case study regions. This would require a range of additional data on the impacts of agroforestry and could be facilitated through the use of tools such as the INFFER framework of Pannell et al. (2009) discussed in Chapter 3. However, any such analysis must consider the concerns about monetary valuation raised by ecological economists such as Farley and Gaddis (2007). These issues are discussed further in Chapters 7 and 8.
309 Chapter 7: Environmental Analysis
This chapter addresses the third research question identified at the end of Chapter 3, regarding the contribution that bioenergy-based agroforestry could make to regional NRM goals at the case study sites. Sections 7.1-7.3 present the original research tasks undertaken in relation to this question. These are divided into environmental protection requirements (7.1), environmental enhancement opportunities (7.2) and landscape function (7.3). Section 7.4 provides a discussion of these results, with a particular focus on further research needs relating to factors such as biodiversity, hydrology and climate change. While the primary focus of this chapter is on the third research question set for the case studies (contribution to NRM goals), it also covers elements of the second research question (potential benefits from agroforestry) and the fifth research question (policy impacts).
The methodologies presented in this chapter have been selected to focus on the key environmental issues identified for the case study sites in Chapter 4 (introduction to case study regions) and Chapter 5 (social analysis). The separation of the chapter into environmental protection (7.1) and environmental enhancement (7.2) reflects the division discussed in Chapter 2, whereby sustainability in the plantation sector is commonly based on benchmarks of environmental protection or maintenance, while sustainability in the revegetation sector is usually based on benchmarks of environmental enhancement. Combining these different benchmarks is one of the major challenges that arises when integrating notions of sustainability from the revegetation, plantation and bioenergy sectors.
The primary methodology employed in sections 7.1 and 7.2 is GIS (Geographical Information System) analysis, undertaken using the ArcGISTM software package (versions 9.3 and 10). For this GIS analysis, the Central Tablelands study region has been defined as the Bathurst, Oberon, Mid-Western and Lithgow local government areas (LGAs) plus a 5 km buffer. The Condobolin study region has been defined as all areas within a 100 km radius of Condobolin, following the approach of Total Catchment Management Services (2008). The focus of analysis within these regions is
310 further restricted to cover only private rural land (Figure 7.1), which is defined as all land except for: x land classed as National Park, Nature Reserve, State Conservation Area, State Forest, vacant crown land or reserved crown land under the National Public and Aboriginal Lands (NPAL) digital dataset (Geoscience Australia 2004); and x land classed as urban, transport, power generation or mining and quarrying under NSW LUMAP land use mapping (NSW Government 2007).
Overall, private rural land makes up 3.03 million ha in the Condobolin study region (96% of all land) and 1.65 million ha in the Central Tablelands study region (66% of all land)57. Some of the land excluded from analysis could play a role in the supply of biomass for a regional bioenergy industry (e.g. State Forests, mining land). However, the social and economic data presented in Chapters 5 and 6, and any assumptions derived from this data, are primarily relevant for private rural land.
The level of analysis undertaken in sections 7.1 and 7.2 is more detailed for the Central Tablelands than for Condobolin, due to the additional funding provided by RIRDC/DAFF and the additional data provided by project partners, particularly Hawkesbury-Nepean and Central West CMAs and Bathurst and Mid-Western councils. As part of the team project funded by RIRDC/DAFF, Alex Gold (Institute of Environmental Studies, UNSW) undertook some of the processing tasks for the Central Tablelands spatial data.
Key results presented for the Central Tablelands in sections 7.1 and 7.2 have also been published in a report to the Rural Industries Research and Development Corporation (Merson et al. 2011).
57 Due to limitations in LUMAP coverage, a small amount of land classed as private rural land to the north and west of Condobolin may contain urban, transport, power generation or mining land uses. Based on data for the area covered by LUMAP, this error is estimated to represent less than 1% of the total study area.
311 312
Figure 7.1: Private rural land in the case study regions. The Condobolin region is shown on the left and the Central Tablelands on the right.
7.1 Environmental protection requirements
As discussed in Chapter 4, plantation establishment in NSW must comply with a range of government policy measures aimed at maintaining environmental values. The aim of this section is to understand how these policies could influence the spatial development of a regional bioenergy industry based on agroforestry in each case study region. The most relevant environmental protection instruments are those operating under NSW state law, particularly the NSW Plantations and Reafforestation Code, the National Parks and Wildlife Act 1974 (NSW) and the Local Environmental Plans (LEPs) for the relevant Local Government Areas (LGAs). As discussed in Chapter 4, the Plantations and Reafforestation Code forms part of an integrated approvals process for plantations that takes into account the requirements of other regulatory instruments, including the Native Vegetation Act 2003 (NSW).
7.1.1 Methodology
In order to assess the impacts of different levels of plantation establishment, three land conversion scenarios (low, medium and high) were developed for each case study region (Table 7.1). These scenarios were based on the survey and interview results presented in Chapter 5 and the figures employed in Chapter 6 for biomass yield and scale of different bioenergy options58. The bioenergy production options listed in Table 7.1 for each scenario are indicative only, as other sources of biomass (e.g. sawmill residues) have not been considered and each bioenergy system has a degree of flexibility around its scale of operation. As in Chapter 6, the Central Tablelands analysis considers the option of having three separate bioenergy plants (e.g. Oberon, Bathurst and Mudgee).
58 Despite not being modelled in Chapter 6 a 20% co-firing option based on a 1000 MW power plant has been included in Table 7.1 due to this option being considered by Delta Electricity (2010).
313 Table 7.1: Land conversion scenarios used to analyse environmental restrictions.
Condobolin Central Tablelands Low Medium High Low Medium High
Conversion rate for private rural 2.2 5.0 9.25 1.8 7.6 19.2 land (%)
Land converted to agroforestry 67,500 151,400 280,100 29,800 125,700 317,500 (ha)
Biomass production rate 5 5 5 20 20 20 (gt/ha/yr)
Total biomass 1.4 2.5 337,500 757,000 595,000 6.4 million produced (gt/yr) million million
Bioenergy Co-firing Renewable option with Ethanol Co- Co- @20% diesel closest scale (pellets firing firing (ethanol if (co-firing from Chapter 6 Ethanol if split @3% @20% split @20% if (assuming no across 3 biomass biomass across 3 split across other biomass plants) plants) 3 plants) sources)
While each of the scenarios presented in Table 7.1 represents a plausible outcome given certain pre-requisites such as the economic viability of bioenergy production, insufficient evidence exists at present to determine which scenarios are more likely than others. The low scenario for Condobolin is based on the 67,500 ha of mallee plantings envisioned in the business analysis prepared by Total Catchment Management Services (2008), which equates to 2.2% of all rural private land within 100 km of Condobolin. The medium scenario is based on the median percentage of land nominated by interviewees in Chapter 5 for initial conversion to mallee (5.0%), while the high scenario is based on the median value for ultimate land conversion
314 amongst interviewees (9.25%). Given that interviewees were selected based on their level of exposure to the idea of growing mallee, it is unsurprising that the land conversion rates they nominated are higher than those assumed by Total Catchment Management Services (2008) for all landholders.
The three scenarios for the Central Tablelands are based on the survey results discussed in Chapter 5. This survey was designed to reach a more representative sample of landholders than the Condobolin interviews. The medium scenario is based on the overall level of land nominated for conversion to agroforestry by survey respondents (i.e. total land nominated divided by total land held by all respondents). The high scenario is also based on the survey results, but corrected for the apparent over-representation of large landholders compared to the digital cadastral layer from the NSW Land and Property Management Authority (see Chapter 5, section 5.2.2). Each of these scenarios has different sources of uncertainty, such as the over- representation of less interested landholders with larger holdings in the medium scenario and difficulties accounting for landholders who hold multiple property units in the high scenario. The low scenario has been set based on the assumption that the only landholders converting to agroforestry would be those who indicated in the survey that they would be prepared to accept a return that was the same as, or less than, the return from their current land use.
In order to compare land requirements under the different scenarios with land availability under environmental policy constraints, a range of areas across each case study region were classed as “restricted” for plantation establishment (Table 7.2). Wherever restrictions on plantations were ambiguous, conservative interpretations were applied. For example, while the Plantations and Reafforestation Code has different buffer requirements for wetlands, rivers, drainage lines and drainage depressions (defined using the Strahler scale), the maximum buffer of 20 m was applied to all wetlands and watercourses contained in the relevant GIS layers. Similarly, while the Code allows native woody vegetation to be cleared in some circumstances (e.g. regrowth, irregular projections), all areas of woody native vegetation in the relevant GIS layer were classed as restricted. For the relevant LEPs, Appendix G provides a full list of zones classed as restricted for plantation activities.
315 Digital zoning maps were unavailable for some LEPs (Oberon, Lachlan, Forbes, Parkes and Bland), but this is unlikely to have a significant impact on the mapping of restricted land, as the zones restricted for plantation activities under these LEPs (e.g. national parks, schools, industrial land) are unlikely to occur on private rural land.
Table 7.2: Policy sources used to identify areas with plantation restrictions.
Policy source GIS data used Areas classed as restricted
National Parks and National Public and All National Parks, Nature Wildlife Act 1974 Aboriginal Lands Reserves and State (NSW) (Geoscience Australia 2004) Conservation Areas
LEPs for Bathurst, Digital zoning layers All LEP zones where forestry Oberon, Lithgow, Mid- supplied by Bathurst, or plantation activities are Western, Lachlan, Lithgow and Mid-western listed as “prohibited” or “not Forbes, Parkes & Bland councils usually consistent with the LGAs (NSW objectives of the zone” Government 2011d)
NSW Plantations and TOPO 250K series 3 All areas within 20 m of a Reafforestation Code – (Geoscience Australia 2006) watercourse watercourse buffers
NSW Plantations and Wetlands of NSW All areas within 20 m of a Reafforestation Code – (Department of wetland wetland buffers Environment and Conservation 2005)
NSW Plantations and NSW Interim Native All areas classed as “most Reafforestation Code – Vegetation Extent v1 likely” or “likely” to consist native vegetation (Department of of woody native vegetation clearing Environment and Climate Change 2008c)
After excluded areas of rural private land classed as restricted in Table 7.2, the remaining land area in each case study region was compared to the amount of land required under the various scenarios listed in Table 7.1. Further analysis was also
316 undertaken for the Central Tablelands, involving a comparison between land availability within each rural land capability class (DIPNR 2004) and landholder preferences for locating plantations as indicated in the survey. GIS analysis was used to calculate the area of private rural land within each land capability class in the Central Tablelands, as well as the area of land available within each capability class after policy restrictions on plantation establishment had been applied.
7.1.2 Results
Figure 7.2 shows the areas in the Condobolin and Central Tablelands case study regions where plantation development would be restricted by the policy measures considered in Table 7.2. Overall, plantation establishment would be restricted on 14 % of the private rural land in the Condobolin study region and 39% of the private rural land in the Central Tablelands study region. The higher level of restriction in the Central Tablelands is primarily due to the greater coverage of woody native vegetation, particularly across the central corridor and southern fringe.
Compared to Condobolin, the Central Tablelands has a lower availability of unrestricted land. In addition, the social analysis suggests higher land conversion rates for the Central Tablelands and the economic analysis suggests a narrower gap between bioenergy-based agroforestry and typical agriculture than at Condobolin. Together, these factors suggest that the Central Tablelands study region may be more likely to experience conflicts between plantation establishment and other land use objectives than the Condobolin study region. For example, the high scenario for the Central Tablelands would involve almost 20% of private rural land being converted to agroforestry, which equates to around one third of the private rural land that is not covered by woody native vegetation, riparian zones or other restricted areas. In comparison, the high scenario for land conversion at Condobolin (9.25% of all private rural land) could be comfortably accommodated within the 86% of private rural land on which plantations would not face significant restrictions.
317
318
Figure 7.2: Areas where plantation establishment is likely to restricted by policy measures. Condobolin study region is shown on the left and the Central Tablelands study region on the right.
The results of the land capability analysis for the Central Tablelands (Table 7.3) also highlight the potential for land use competition in the region. While the most prevalent land class in the region is “land capable of grazing with occasional cultivation”, the land class most commonly nominated for conversion to agroforestry in the survey (by 51% of respondents) was “marginal land (rocky/steep with little grazing value)”. The term “marginal land” was used as a proxy in the survey for rural land capability classes 7 and 8. As shown in Table 7.3, these classes make up only 25% of private rural land in the study region and much of this is covered by woody native vegetation where clearing for plantation establishment is heavily restricted. When these restricted areas are excluded, the remaining area of unrestricted marginal land is equal to only 10% of the total private rural land in the study region. If the level of land conversion for agroforestry in the Central Tablelands reached the level envisioned by the high scenario (around 20%), the availability of marginal land would be insufficient, requiring plantation establishment on higher capability land. This could potentially lead to the type of land use conflict seen in other parts of Australia where rapid plantation expansion has occurred (e.g. Tonts & Schirmer 2005, Parsons et al. 2007, The Wilderness Society Tasmania 2010).
Another potential source of conflict is the view expressed by 23% of survey respondents that plantation establishment would be appropriate on land set aside for conservation. As discussed in Chapter 5, this could indicate either that these landholders see agroforestry as compatible with conservation goals or that they feel such areas should no longer be conserved. Either way, opposing views are likely to exist within the broader community, with some anti-plantation views expressed by participants in the participatory rural appraisal and landholder survey.
319 Table 7.3: Landholder preferences compared with land availability in the Central Tablelands. Land capability class descriptions follow those used in the survey, with corresponding class numbers taken from DIPNR (2004). Survey respondents were able to nominate more than one land class of land for conversion to agroforestry.
Land Land Land Marginal Land set suitable for suitable for suitable land aside for regular grazing & for (class 7-8) conservation cultivation occasional grazing purposes (no (class 1-3) cultivation only corresponding (class 4-5) (class 6) class)59 Survey respondents nominating each 13 35 38 51 23 land class for agroforestry (%) Proportion of land in each land class as reported 36 27 26 7 4 by survey respondents (%) Proportion of land in each land class from GIS 10 40 24 25 0 (% of total private rural land) Proportion of total unrestricted private rural land falling within each land class 9 31 12 10 0 (% of total unrestricted private rural land)
The analysis of land capability data for the Central Tablelands contains some uncertainties. It is unclear whether surveyed landholders were using the same
59 The GIS layer for NSW land capability mapping (DIPNR 2004) classes some land based on its conservation status rather than using classes 1-8, but only for crown land (e.g. National Parks).
320 definitions for their land as DIPNR’s (2004) land capability mapping. Table 7.3 shows that surveyed landholders reported much higher levels of cultivatable land and lower levels of marginal land on their properties compared to DIPNR’s mapping for the region. This could mean that the sample group had more productive land than the regional average or that survey respondents were defining their land differently to DIPNR (2004). It is also unclear whether landholders who nominated marginal land for agroforestry were fully aware of the restrictions on clearing native vegetation for plantation establishment. Clarification of these issues may help to enhance understanding of where plantation development is most likely to occur and where conflicts may arise between landholder preferences, environmental protection regulations and community attitudes.
7.2 Environmental enhancement opportunities
The spatial analysis presented in section 7.1 highlights areas where plantations could be established without posing a threat to existing native vegetation, protected areas or riparian zones. However, as discussed in Chapter 2, maintaining environmental values in the face of threats is only one element of a holistic notion of sustainable development. While regulations and sustainability standards in the plantation sector often focus on the maintenance of environmental values (e.g. Forest Stewardship Council 2002, Australian Forestry Standard Limited 2007), the focus of sustainability in the revegetation sector is generally based on the enhancement of environmental values.
As discussed in Chapter 4, the Lachlan, Central West and Hawkesbury-Nepean Catchment Management Authorities (CMAs) each have a range of targets relating to revegetation. These targets primarily focus on the establishment of corridors and buffers for biodiversity, the protection of soils and landscapes against erosion and the reduction of groundwater recharge in landscapes that are prone to dryland salinity. As such, the aim of this section is to identify priority areas or “hotspots” where plantations may help to achieve these goals. As with section 7.1, more detailed analysis was possible for the Central Tablelands due to the associated research project funded by DAFF/RIRDC and supported by the CMAs and councils in the region.
321
7.2.1 Methodology
The methodology for identifying potential vegetation corridors and buffering sites (Figure 7.3) was primarily based on visual interpretation of the continuity of woody native vegetation contained in the NSW Interim Native Vegetation Extent v1 GIS layer (Department of Environment and Climate Change 2008c). For Condobolin, the identification of biodiversity corridors followed on from similar work undertaken by the Natural Resources Commission (2010, p. 170) in its assessment of the role of cypress forests in providing habitat linkages in south-western NSW. Other potential corridors were added to those mapped by the Natural Resources Commission (NRC). The NRC assessment did not extend to the Central Tablelands, but alternative data was available in the form of landscape mapping based on the Mitchell Landscape classification scheme (Department of Environment and Climate Change 2008b). Using this GIS layer, provided by the Hawkesbury-Nepean CMA, Mitchell Landscapes that have been more than 70% cleared since European settlement were identified as high priority landscapes for connection and buffering.
As shown in Figure 7.3, different approaches were used for the two case studies due to the differences in remnant native vegetation in each region. Narrow corridors were employed around Condobolin, reflecting the fact that levels of remnant vegetation in the landscape are very low and much of what remains is arranged in a linear fashion along waterways and travelling stock routes. Wider corridors and buffers were mapped in the Central Tablelands to capture the large but fragmented areas of native vegetation that remain. Some areas with high levels of past clearing were not chosen as priority target areas, such as the area immediately surrounding Bathurst, where very low levels of existing native woody vegetation would make it challenging to achieve regional linkages.
322 323
Figure 7.3: Potential revegetation corridors for biodiversity in the case study regions. Left: Condobolin, Right: Central Tablelands.
Target areas for revegetation to protect soils and landscapes from erosion and degradation were identified using a number of GIS layers. Firstly, for each case study region, a comparison was made between rural land capability mapping (DIPNR 2004) and NSW LUMAP land use mapping (NSW Government 2007) to identify areas where current land uses may be in conflict with land capability recommendations. This exercise involved identifying any land within rural land capability classes 7 or 8 that were being used for grazing, cropping or horticulture according to LUMAP (Figure 7.4). These areas were classed as land capability hotspots on the basis that class 7 land is “best suited to tree cover only” and class 8 land is “unsuitable for agriculture” (Hawkesbury-Nepean Catchment Management Authority 2007, p. 120).
Each of the three relevant CMAs has targets designed to ensure that land is used within its capability. Hawkesbury-Nepean CMA (2007, p.122) identified grazing on land with a capability class of 7 as the most significant use of land outside of its capability in that CMA region, while Central West CMA (2007, p. 61) states that commercial plantations may be suitable on land classified as having low capability for cropping and grazing (i.e. land classes 7 and 8). For the Condobolin case study, limitations in LUMAP extent meant that the analysis had to be limited to the south-eastern half of the case study region only.
324 325
Figure 7.4: Land capability hotspots for the case study regions. Left: Condobolin (SE portion only), Right: Central Tablelands.
For the Central Tablelands, “environmentally sensitive areas” mapping produced by the Central West CMA was provided by Bathurst and Mid-western regional councils. This mapping highlights land with high erosion rates and land affected by dryland salinity in the western and northern parts of the study region (Figure 7.5). This erosion and salinity data was not available for the area covered by Hawkesbury-Nepean CMA or for the Condobolin case study. Salinity-affected land does not form a concentrated hotspot, but is scattered across the northwestern part of the Central Tablelands study region.
Figure 7.5: Central Tablelands hotspots for erosion (left) & dryland salinity (right).
Following the determination of environmental hotspots for Condobolin and the Central Tablelands, these potential target areas were compared to the mapping of restricted and unrestricted areas presented in section 7.1. For the Central Tablelands, it was also possible to make further comparisons with the distribution of land capability classes (DIPNR 2004) and the distribution of property size (using cadastral data provided by the NSW Land and Property Management Authority). The purpose of these comparisons was to determine the degree to which potential hotspot areas are likely to align with:
326 x land availability for plantation establishment (after considering exclusions due to environmental regulations); and x landholder preferences revealed through the Central Tablelands survey data, such as the use of marginal land for plantations and higher levels of interest in agroforestry amongst smaller landholders.
7.2.2 Results
Figure 7.6 combines the biodiversity and land capability hotspots for the Condobolin region. Areas of overlap between these criteria are concentrated along the Lachlan River and in a zone approximately 50-100km north-east of Condobolin. There may also be other areas where these issues align in the northwestern half of the study area where the LUMAP land use mapping does not currently extend.
Figure 7.6: Biodiversity and land capability hotspots for the Condobolin region.
327 Figure 7.7 combines the biodiversity, land capability, erosion and salinity hotspots for the Central Tablelands. The greatest overlap of hotspots occurs in the area between Mudgee and Bathurst, with smaller areas of overlap evident in a corridor running east- west between Lithgow and Oberon and along the southwestern fringe of the study region.
Figure 7.7: Overlap between environmental hotspots in the Central Tablelands.
After this analysis was completed, the Central West CMA released a revised catchment action plan (Central West Catchment Management Authority 2011). This presents an opportunity to compare the hotspots mapped in Figure 7.7 with the landscape priorities identified by the Central West CMA. The CMA’s priority areas (Figure 7.8) fall under the categories of wetland, soil and vegetation and were identified through using the INFFER approach discussed in Chapter 3 (Pannell et al. 2009). The land capability and erosion hotspots identified north of Bathurst in Figure 7.7 align with high soil priority
328 areas in Figure 7.8. The area northeast of Oberon also shows up as both a biodiversity hotspot in Figure 7.7 and an area of very high vegetation priority in Figure 7.8.
Figure 7.8: Landscape priorities in the tablelands portion of the Central West CMA region. Reproduced from Central West Catchment Management Authority (2011).
Figure 7.9 compares the environmental hotspots at each case study site with the availability of private rural land after accounting for regulatory restrictions.
329
Figure 7.9: Environmental hotspots compared with available private rural land. Top: Condobolin, Bottom: Central Tablelands.
Figure 7.9 reveals significant scope to locate new plantations in hotspot areas, particularly in the Condobolin region. For the Central Tablelands, the pattern is more mixed, with some hotspots in areas with ample available land (e.g. biodiversity and
330 salinity hotspots in the northwest) and others featuring a much smaller proportion of available land (e.g. some of the hotspots in the central area and the far southwest).
Figure 7.10 analyses these issues further for the Central Tablelands, comparing environmental hotspots to land capability and property size distribution. This analysis highlights the need for different strategies in different parts of the region. For example, the area between Bathurst and Mudgee features overlapping environmental hotspots, as well as consisting mostly of low capability land, the land class most preferred for plantations in the survey. However, this area also has the highest concentration of large large properties, with these landholders showing the least interest in agroforestry in the survey. In contrast, the area north of Mudgee has many small landholders, but is dominated by land suitable for cultivation, where agoforestry may be less able to compete financially and is more likely to create conflicts around the loss of productive land. The south-eastern corridor between Oberon and Lithgow features an alignment of hotspots, consists mostly of lower capability land and has mostly small-to-medium sized properties. However, experiences from other agroforestry/revegetation programs such as the Community Rainforest Reforestation Program in North Queensland (discussed in Chapter 2) suggest that small, non-commercial landholders can present challenges such as having different goals to policy-makers and failing to undertake the management activities necessary for commercial production.
The analysis presented in this section highlights a number of potential target areas for revegetation in the two case study regions. Further target areas could also be identified through the use of the INFFER system (Pannell et al. 2009), as has been done by the Central West Catchment Management Authority (2011) in its new catchment action plan, or through the use of tools for identifying critical natural capital, such as CRITINC (Ekins et al. 2003). However, it cannot be assumed that plantation establishment in these areas will automatically lead to environmental enhancements such as habitat provision, erosion control or salinity mitigation. Plantation design factors are also critical, including species selection, land preparation, tree spacing, harvest regimes and integration with other land uses. These design issues are discussed further in sections 7.3 (landscape function) and 7.4 (biodiversity, water use and climate change).
331 332
Figure 7.10: Environmental hotspots compared with land capability (right) and property size (left) in the Central Tablelands. Only unrestricted areas of rural private land are shown. Land capability data from DIPNR (2004). Cadastral data supplied by LPMA.
7.3 Landscape function
Landscape function refers to the manner in which ecological and physical processes interact within a landscape unit, including the growth patterns of vegetation, the cycling of nutrients between plants and soils and the transfer of resources into and out of the system. The approach employed in this section is based on the trigger-transfer- reserve-pulse framework described by Ludwig and Tongway (2003) and shown in Figure 7.11. This framework emphasises the importance of triggers such as rainfall events in driving pulses of vegetation growth, the role of water and wind as agents for the transfer of resources (both within the system and to and from the system) and the role of soil and vegetation patches in providing reserves of nutrients, moisture and seeds.
Figure 7.11: The trigger-transfer-reserve-pulse framework. Reproduced from Ludwig and Tongway (2003, p. 4).
While Ludwig and Tongway’s (2003) framework was initially developed for rangeland ecosystems, the general processes and interactions have relevance beyond these areas.
333 Landscape Function Analysis (LFA) was developed at CSIRO Sustainable Ecosystems (Tongway & Hindley 2004) and incorporates principles from the trigger-transfer- reserve-pulse framework into a rapid assessment tool for a diverse range of landscapes. I completed an LFA training course in 2006 and have since used LFA in environments ranging from the Blue Mountains (Merson, Attwater, Booth, Mulley, Ampt, Wildman et al. 2009) to the rangelands north of Broken Hill (Ampt & Baumber 2010).
The LFA methodology is based on the organisation of the landscape into patches, where resources accumulate, and inter-patches, where resources are mobile (Figure 7.12). Patches may be formed by trees, grasses, shrubs, logs or other structures that impede the movement of soil and litter. The scale at which this patch/inter-patch pattern occurs is dictated by factors such as climate, slope, soil type, grazing pressure and human landscaping (e.g. contour banks). In high rainfall grassland environments, patches are likely to occupy most or even all of the landscape, while in arid environments the ratio of patch to inter-patch area is generally low (Tongway & Hindley 2004).
Figure 7.12: Division of a hypothetical LFA transect into patches and inter- patches. Reproduced from Tongway and Hindley (2004, p. 38).
In addition to recording landscape organisation, LFA also involves an assessment of soil surface indicators within landscape patches and inter-patches. These indicators
334 cover factors such as rainsplash protection, perennial vegetation cover, litter ccover, soil type and evidence of erosion and deposition. When combined with appropriate weightings, the indicator scores produce three soil surface indices for the surveyed landscape (Figure 7.13), namely stability (degree of resistance to erosive forces), infiltration (capacity for water to penetrate tthe soil surface) and nutrient cycliing (retention and breakdown of nutrients within the landscape). As concerns about erosion, runoff and soil degradation were commonly cited in Chapter 5 as reasons for interest in agroforestry at both case study sites, LFA offers a relatively fast and simple method for assessing the impacts of plantattion establishment on the landscappe.
Figure 7.13: Contribution of soil surface indicators to indices for stability, infiltration and nutrient cyclingn . Reproduced from Ampt and Baumber (20010, p. 46).
335 7.3.1 Methodology
Sites were selected for LFA transects in each case study region from amongst the properties visited as part of the social analysis. One site was selected in the Condobolin case study region, while three sites were selected in the Central Tablelands (Figure 7.14). LFA transects were undertaken in August 2011 (Condobolin) and October 2011 (Central Tablelands). The LFA procedure followed at each site is that detailed on pages 25-50 of Tongway and Hindley’s (2004) LFA manual, including site description, site characterisation (division into patches and inter-patches) and recording of soil surface indicators for each patch and inter-patch type.
The study site selected for the Condobolin case study region site was the Mt Mulga property operated by G.R. Davis eucalyptus oil producers, near West Wyalong (480 mm average annual rainfall). Although this site is approximately 100 km south of Condobolin, it was selected due to the presence of blue mallee plantations dating back more than 25 years, as well as natural mallee stands that have been harvested for over 100 years. In addition, plantation design and management styles have varied over time, with the plantation manager (Andrew Cummin pers. comm.) believing that that the newer style of plantations established at Mt Mulga were delivering improved water infiltration, biomass yield and soil health compared to the older style of plantations. The newer plantations feature wider row spacings designed to encourage grass cover, while the older plantations were established with narrower row spacings and a focus on weed control. Thus, an LFA monitoring methodology was developed to test the hypothesis that wider row spacings could improve soil health and water infiltration, as well as to compare the mallee plantations to other land uses on the property.
336
Figure 7.14: Locations of LFA sites for (a) Condobolin and (b) Central Tablelands.
337 Six land management units were selected for analysis at Mt Mulga (Table 7.4), with two transects undertaken within each land unit. All units were located on gentle slopes and had the same soil type (sandy clay loam). Four mallee units were selected, each having been harvested by coppicing within the past 12-18 months, but featuring different plantation design and management strategies. Two newer-style plantations with wider spacings (6-7 years old) were selected, one where grass growth had been encouraged between rows and one where mallee leaf residues (after oil extraction and drying) had been laid down as mulch. One 25-year-old plantation with older-style narrow spacing was selected, along with one natural mallee stand that had been harvested for over 100 years. For comparison with other land uses, a pasture unit and a remnant native vegetation unit adjacent to the newer (6-7 year old) mallee plantations were chosen. It was not possible to measure a pasture unit that was subject to regular grazing, with the selected pasture unit managed by slashing rather than grazing. It was also not possible to compare the mallee plantations to an area used for the cropping of wheat or other cereals.
The sites selected for LFA in the Central Tablelands were near Oberon, Ilford and Lue. These were the same three sites that were used to verify the plantation modelling results in Chapter 6 and are managed by three of the landholders involved in the Participatory Rural Appraisal in Chapter 5. As shown in Table 7.5, each of the three sites features a native plantation with trees around 11 years of age. In addition, two of the three sites (Ilford and Lue) also feature an adjacent pasture unit managed for cattle grazing during this period. A single LFA transect was undertaken within each of the three plantation units, as well as within the pasture units at Ilford and Lue. The Ilford plantation was located upslope of the adjacent pasture and had been specifically sited there to provide protection for the steepest part of the slope. The Lue plantation was downslope of the pasture and had not been designed to serve any environmental objective (nor had the Oberon plantation).
338 Table 7.4: Land management units for Condobolin case study LFA site (Mt Mulga). Unit name Details (as of August 2011) Image 3 m Row spacing: 3 m mulched Tree spacing within rows: ~1 m Establishment year: ~2005 Last harvest: 15-18 months ago Height: 1.5-2 m Treatment: Mulch (spent mallee leaf) spread post-harvest at 10-12 tonnes/ha. 3 m grassed Row spacing: 3 m Tree spacing within rows: ~1 m Establishment year: 2004-2005 Last harvest: ~18 months ago Height: 1.8-2.5 m Treatment: Grass growth encouraged before and after tree planting. 1.5 m old- Row spacing: 1.5 m style Tree spacing within rows: ~1 m Establishment year: ~1985 Last harvest: 12-18 months ago Height: 1.2-1.8 m Treatment: Weed spraying undertaken in early years of plantation. Old natural Natural mallee stand, harvested for over 100 years (40 by mechanical harvest). Last harvest: ~18 months ago. Tree density: Not measured, but much lower than in planted areas. Height: 1-1.5 m
Pasture 30 m wide strip of native grasses growing between mallee plantation and road. Treatment: Not regularly grazed, but recently slashed (grass cuttings present on surface).
Native Remnant native vegetation adjacent to vegetation mallee plantation (3 m grassed unit). Canopy: Mixed eucalypts. Mid-storey: Acacias, cypress, some mallee. Groundcover: Tussock grasses, lomandra & fallen timber.
339 Table 7.5: Site/unit descriptions for Central Tablelands case study LFA sites. Site Unit details (as of October 2011) Image Oberon - Species: Eucalyptus nitens (shining hobby gum) farm 2 Establishment year: 2000 km east Mean annual rainfall: of - 800 mm (1889-2010) Oberon - 672 mm (2000-2010) Topography: mid-slope, moderate gradient Management: Pruning to 4m, no thinning, no grazing Adjacent land uses: remnant native vegetation, other plantation (newer) LFA comparison: none
Ilford - Species: Eucalyptus globulus cattle (Tasmanian blue gum) property Establishment year: 2000 10 km Mean annual rainfall: north of - 679 mm (1889-2010) Ilford - 681 mm (2000-2010) Topography: upper slope, steep to moderate gradient Management: no grazing, no thinning, no pruning Adjacent land uses: Cattle grazing on improved pasture LFA comparison: Pasture below plantation (mid-slope) Lue - Species: E. globulus x E. grandis cattle (blue gum x flooded gum) property Establishment year: 2000 2 km Mean annual rainfall: south of - 676 mm (1889-2010) Lue - 717 mm (2000-2010) Topography: lower slope, low gradient Management: no grazing, no thinning, no pruning Adjacent land uses: Cattle grazing on improved pasture LFA comparison: Pasture above plantation (mid-slope)
340 7.3.2 Results
Results for the stability, infiltration and nutrient cycling indices at Mt Mulga (Condobolin case study) are shown in Figure 7.15. The old natural mallee stand showed the lowest scores across all three indices, followed by the old-style (1.5 m) plantations. The newer-style (3 m) plantations achieved the highest scores for nutrient cycling and infiltration, with the pasture site showing the highest score for stability.
Figure 7.15: LFA results for Mt Mulga (Condobolin case study) +/- standard error.
341 While the stability scores for the old natural mallee stand and the 1.5 m plantation were significantly lower than the other land units, the standard error bars shown in Figure 7.15 indicate that was no statistically significant difference between the stability results for the two 3 m plantations, the pasture unit and the native vegetation unit. For infiltration and nutrient cycling, the two 3 m plantations and the pasture unit had significantly higher scores than the other units, while the 3 m mulched unit had significantly higher scores than the pasture unit under both indices.
Overall, the mulched 3 m plantation appears to have the best landscape function, closely followed by the grassed 3 m plantation (no statistically significant difference for any of the three indices). The spreading of mulch provided greater consistency in the litter scores for the 3 m mulched site compared to the somewhat patchy grass cover in the 3 m grassed site. The pasture site also had high levels of litter cover, but most of this came from recent slashing activity. These litter scores are unlikely to be matched in a grazed pasture system, where grass would be removed by livestock rather than accumulating as litter.
For the old natural mallee stand and the old-style (1.5 m) plantation, a lack of litter cover, presence of hard soil crusts and evidence of sheet erosion were major contributing factors to the low scores for stability, infiltration and nutrient cycling (Figure 7.16).
Figure 7.16: Land units showing hard soils and a lack of litter cover at Mt Mulga. Left: Old-style 1.5 m plantation, Right: Old natural mallee stand.
342 The LFA results for Mt Mulga highlight the importance of plantation design and management in determining whether mallee plantations are likely to have a positive or negative impact on landscape function. The Mt Mulga results indicate that the conversion of native pasture or even remnant native woodland to mallee plantation has the potential to improve landscape function if the plantations are managed in a way that incorporates mulch or grass cover. However, the older mallee units (1.5 m and old natural) performed poorly in comparison to both the native pasture and remnant native vegetation units.
The impact of wider row spacing in promoting grass growth was identified by the plantation manager at Mt Mulga as a key factor in improving water infiltration (Andrew Cumming pers. comm.). The row spacings advocated by Mallee Condo Pty Ltd, 2.4 m with every seventh row skipped (Sandy Booth pers. comm.), fall in between the 1.5 m and 3 m row spacings observed at Mt Mulga. Other factors may also play a role in landscape function, including the fact that the older mallee sites at Mt Mulga had experienced a much higher level of machinery use over a number of decades and herbicides had been used to eradicate weeds in the early years of the 1.5 m plantation. Care must also be taken in extending these results to other locations and land types with different characteristics. Future LFA research could focus on other soil types in the Condobolin region and comparisons between mallee plantations, grazed pastures and cropping land.
The Central Tablelands LFA results are shown in Figure 7.17. The Oberon plantation produced the highest score for stability, but performed worse than the other plantation sites for infiltration and nutrient cycling. The plantation and pasture units at Ilford produced very similar results for all three indices. At Lue, significant differences were observed between the plantation and pasture units for all three indices, with the plantation recording higher scores for infiltration and nutrient cycling and the pasture recording a higher score for stability. The Lue plantation had higher litter scores than the adjacent pasture unit, as well as softer soil crusts and greater surface roughness (due to the ripping and mounding for tree planting), but it lacked the perennial ground cover found in the pasture unit and showed some evidence of soil movement along the edges of the rows.
343
Figure 7.17: LFA results for the Central Tablelands case study sites.
The higher overall LFA scores for the Lue plantation compared to the pasture unit above it are not surprising, given that the pasture unit was on a slightly steeper gradient and there was a further 100-200 metres of pasture above the transect from which runoff could accumulate. Evidence of runoff in the pasture unit was visible in the form of litter bands that had accumulated as patches every 1-3 m down the slope. In contrast, the plantation unit at Lue showed no evidence of downslope movement of litter, with
344 leaves and tree branches appearing to have remained where they fell or moved only short distances from the mounded tree rows into the adjacent troughs. This bank-trough pattern along the contour of a slope (Figure 7.18) is commonly employed in the rehabilitation of minesites and other degraded land to prevent the build-up of run-off and to ensure that litter, soil and other resources are retained within the landscape unit (Tongway & Hindley 2004).
Figure 7.18: Bank-trough micro-catchment. Commonly used in rehabilitation of minesites and other degraded areas. Reproduced from Tongway & Hindley (2004, p. 35).
The plantation units at Oberon and Ilford also featured the bank-trough pattern shown in Figure 7.18. Notably, the plantation and pasture units at the Ilford site produced very similar LFA results despite the plantation at this site being located upslope of the pasture and on a steeper gradient. The Lue results provide preliminary evidence that plantations located at the base of a sloping pasture may be able to slow down the movement of water, litter and soil that may build up on the pasture above, while the Ilford results suggest that plantations located on the upper part of a slope may be able to prevent runoff from accumulating and carrying soil and litter into the pasture below. These outcomes, if able to be replicated more broadly, could help to contribute to some of the regional NRM targets identified in Chapter 4, including:
345 x 20,000 ha of actively eroding, fragile or severely degraded land are stabilised and/or rehabilitated (Lachlan Catchment Management Authority 2006); x 10,000 ha of lands classified as low capability for cropping or grazing purposes are managed primarily for conservation of native vegetation and landscape protection (Central West Catchment Management Authority 2007); and x 20 000 ha of the catchment will be protected from soil erosion as a result of repairing the catchment by soil conservation works such as fencing, gully control structures, revegetation and other treatments (Hawkesbury-Nepean Catchment Management Authority 2007)
Further research is required to test the hypotheses presented above, including LFA monitoring of plantation and pasture units combined in different ways across a range of slope positions (upper, mid and lower slope) and soil types. The stage of plantation development may also be significant and a comprehensive research program would require monitoring before and after plantation establishment as well as before and after harvesting. This fieldwork did not identify any significant threats to soil health from plantation establishment at the three Central Tablelands sites, but such threats may occur in other locations. The NSW Plantations and Reafforestation Code places restrictions on ripping and mounding on steeper slopes with highly erodible soils due to concerns that soil disturbance may threaten vulnerable sites. Further research should also focus on plantation impacts on “marginal land” (rural land capability classes 7 & 8), which was raised as a concern by some participants at the November 2011 workshop. Another consideration for future research is the degree to which benefits from soil protection are private (on-farm) or public (off-farm). The gathering of data on private and public benefits could facilitate the application of the INFFER Public: Private Benefits Framework (Pannell 2008) to regional policy development.
Overall, the results of the LFA monitoring for the Condobolin and Central Tablelands case study sites highlight the potential for plantations to enhance or maintain landscape function at these sites when they are appropriately integrated into the landscape and managed to optimise stability, infiltration and nutrient cycling. However, this analysis has also revealed evidence of plantation systems in the Condobolin case study area that have lower function that nearby pasture or native vegetation due to a lack of ground
346 cover or physical disturbance. The results presented here highlight promising areas for future research but fall short of providing a detailed guide for predicting the impacts of plantation establishment on landscape function.
7.4 Discussion of results and identification of future research needs
The results of the GIS analysis and LFA fieldwork highlight potential opportunities for bioenergy-based agroforestry to enhance the sustainability and resilience of land use systems within the case study regions. However, they provide only preliminary evidence that agroforestry may be able to contribute to the regional NRM goals presented in Chapter 4. The LFA results for both case study sites suggest that agroforestry systems may provide better landscape function than other land uses, but they also highlight potential risks from agroforestry systems that fail to provide adequate ground cover. Similarly, the GIS analysis identified areas where land capability may be better suited to tree-based activities than to current land uses, but was not able to assess the full impacts of tree planting, management and harvesting on these vulnerable landscapes.
In relation to biodiversity and salinity, the GIS analysis has helped to identify hotspots for action and to link these with potential agroforestry strategies emerging from the social analysis in Chapter 5. However, due to limitations of time, resources and specialised skills, it was not possible to undertake fieldwork assessing the potential contribution of plantation-based land uses to habitat provision and salinity mitigation. Similarly, the contribution of plantations to climate change mitigation and adaptation was beyond the scope of the GIS analysis and fieldwork undertaken. These aspects of agroforestry represent important areas for future research, with the following three subsections discussing the key considerations for biodiversity (7.4.1), hydrology (7.4.2) and climate change (7.4.3).
7.4.1 Biodiversity
As highlighted in the GIS analysis in section 7.2, the potential value of agroforestry for biodiversity conservation is likely to vary across the case study regions. Furthermore,
347 the biodiversity value of plantations will be influenced by design factors such as species selection, proximity to other vegetation types and regimes for harvesting and management. While direct measurement of biodiversity impacts within plantations has not been possible for this thesis, a number of previous studies have investigated these issues. Relevant field studies include coverage of southern NSW (Lindenmayer, McIntyre & Fischer 2003), Victoria (Forrester, Bauhus & Cowie 2005, Loyn et al. 2007), North Queensland (Kanowski, Catterall & Wardell-Johnson 2005b) and Western Australia (Smith 2009). There are also a number of broader reviews covering the general principles of plantation design, including those of Paltridge (2002), Lindenmayer and Hobbs (2004), Lamb et al. (2005), Forrester, Bauhus, Cowie and Vanclay (2006), Dickinson, Bristow and Huth (2008), and Felton, Knight, Wood, Zammit and Lindenmayer (2010).
A number of studies have shown that plantations can provide habitat value when established on previously cleared land. For example, Loyn (2007) found that, while the mean abundance of forest and woodland birds in Victorian eucalypt plantations was lower than in native forest, it was higher than on cleared farmland. Similarly, Smith (2009) found that habitat quality scores for Oil Mallee plantations in Western Australia were lower than for remnant native woodland, but higher than for adjacent crop/pasture land. Felton et al. (2010) undertook a review of 36 global studies of plantation and pasture biodiversity, finding that plantations showed significantly higher species richness for birds and reptiles/amphibians and higher abundance for mammals compared to pasture lands that lacked remnant vegetation. However, they also emphasised that the biodiversity benefits of plantations should not be generalised, as they did not find significant differences in relation to plants or invertebrates and their comparisons only included pasture sites without remnant vegetation.
A key plantation design issue relating to biodiversity is the selection of commercial tree species. Paltridge (2002) argues that, in the Australian context, eucalypts will generally have greater value for biodiversity than exotic pinus spp. and mixed-species plantations are likely to provide better habitat value than monocultures. Most plantations established in Australia are monocultures, as mixed species plantations are considered more expensive to establish, manage and harvest (Dickinson et al. 2008).
348 Mixed species plantations are more common amongst small landholders who value non-commercial outcomes (Dickinson et al. 2008), a pattern that was supported by the survey findings for the Central Tablelands case study.
There are relatively few studies with relevance for the NSW Central West that have attempted to directly measure the biodiversity impacts of using a mix of species rather than a monoculture. Smith ‘s (2009) study of Oil Mallee strips within wheat fields in Western Australia involved a comparison with mixed species revegetation (Figure 7.19), finding little difference in abundance of small vertebrates between the two revegetation strategies. However, Smith did identify proximity to native vegetation as an important factor, with Oil Mallee plantings farther than 200 m from remnant woodland containing fewer species.
Figure 7.19: Biodiversity monitoring results for Western Australian oil mallee. Source: Smith (2009). Species monitoring was not undertaken for the crop/pasture site.
Kanowski et al. (2005b) compared biodiversity outcomes for monocultures of hoop pine, mixed-species cabinet timber plantations, restoration plantings and mature rainforest sites in North Queensland, finding no significant difference in bird species richness between the mixed-species and monocultural plantations (Figure 7.20). Catterall et al. (2005) further reinforce this ambiguity around mixed-species plantations, suggesting that they may have a role to play in enhancing biodiversity, but only if other factors are also considered such as site heterogeneity and proximity to intact native vegetation.
349
Figure 7.20: Rainforest bird monitoring results for North Queensland. Reproduced from Kanowski et al. (2005b). Cabinet timber plantations featured a mix of commercial species while hoop pine plantations were all monocultures.
Species diversity, site heterogeneity and proximity to native vegetation have been all identified by Lindenmayer and Hobbs (2004) as key plantation design principles for promoting biodiversity. Their design principles (Table 7.6) focus on both environmental maintenance and environmental enhancement. Many of the maintenance principles (e.g. protecting remnant vegetation) also appear in the NSW Plantations and Reafforestation Code and industry standards discussed in Chapter 2 (e.g. FSC, AFS and SAN). Many of the enhancement principles such as establishing vegetation mosaics, integrating plantations alongside remnant forests and maintaining stand age diversity have been recommended in other studies (e.g. Lindenmayer 2002, Catterall et al. 2005, Kanowski, Catterall, Proctor, Reis, Tucker & Wardell-Johnson 2005a). The focus of Lindenmayer and Hobbs (2004) on creating connections and vegetation mosaics also reflects the multifunctional “wildlife-friendly farming” approach of Fischer et al. (2008) discussed in Chapter 3.
350 Table 7.6: Principles for enhancing wildlife conservation in Australian plantations. Summarised from Lindenmayer and Hobbs (2004). Category Principle Details General Habitat suitability All organisms require access to suitable principles habitat Non-replaceability Replacement of native vegetation by plantations is negative for fauna conservation Landscape- Landscape heterogeneity Diverse age classes and spatial level juxtaposition of stand ages/types should be principles maintained Patch size of remnant Patches of remnant vegetation within native vegetation within plantations should be retained, with larger plantations patches having higher priority Riparian areas Riparian areas should be retained as (or restored to) native vegetation cover Connectivity Physical links between patches should not be severed Adjacency and Conservation value of plantations is likely landscape context to be greater if close to native vegetation Stand-level Plant species diversity Plant diversity (particularly understorey principles vegetation) should be maintained Stand structure Structural elements such as logs and windrows should be retained Stand age Some older stands of trees should be maintained for habitat value
Many of the principles listed in Table 7.6 are likely to increase operating costs for plantation managers. Maintaining a mixture of species or age classes, integrating plantations into mosaics alongside native vegetation and retaining structural elements such as logs are all likely to reduce the efficiency of management and harvesting practices. Dickinson et al. (2008) argue that the low returns from eucalypt plantations often make it hard to justify practices that increase management costs, such as using a mixture of species. Incorporating these design elements is likely to be even more challenging for a low value product such as bioenergy.
In some cases, using a mixture of species can increase biomass yield (Lamb et al. 2005, Kelty 2006). Examples include where the different species use resources differently (e.g. soil moisture or sunlight), where one species provides resources for
351 another (e.g. nitrogen fixation) or where the mixture of species reduces pest damage. Dickinson et al. (2008) argues that these outcomes are difficult to achieve using a mixture of eucalypts, which tend to monopolise resources. Forrester et al. (2005) found that mixing Acacia mearnsii (a nitrogen-fixing species) with Eucalyptus globulus in a 50:50 ratio in eastern Victoria resulted in a doubling of biomass production compared with E. globulus alone. This result was attributed to A. mearnsii fixing nitrogen to the soil, increasing phosphorus cycling through high litterfall and developing a canopy below that of E. globulus (Forrester et al. 2005). Furthermore, Forrester et al. (2006) reviewed 18 global trials in which eucalypts were mixed with nitrogen-fixing species, concluding that mixed-species plantations significantly outperformed monocultures in about half of the studies, while in no study did monocultures outperform mixed-species in a statistically significant manner.
Nichols et al. (2006) argue that mixed-species plantations are likely to require a yield premium of around 10% to offset their additional costs, a level that was greatly exceeded in the study of e. globulus and a. mearnsii by Forrester et al. (2005). However, Lamb et al. (2005) emphasise the distinction between ecological productivity (biomass) and commercial productivity (profit), as the value of products may differ between the species used. This is less likely to be a concern when producing bioenergy rather than high-value timber, but differences in biomass attributes could affect economic factors such as biofuel yield or processing costs. Plantations with a diversity of species or age classes may also help to minimise risk by providing products for different markets or allowing different harvest frequencies (e.g. short- rotation trees generating cash flow while longer-rotation trees mature). In cases where synergies cannot be found between biodiversity and economic outcomes, Dickinson et al. (2008) suggest a range of policy measures to offset the additional costs and facilitate trade-offs. These recommendations cover many of the policy measures analysed in this thesis, including capitalising on the non-commercial motivations of landholders, providing financial incentives (e.g. grants, tax breaks), tightening regulations on plantation establishment or using certification schemes to provide a market advantage.
352 Based on this analysis, the following research questions emerge as future priorities for the Condobolin and Central Tablelands case study areas: - What is the impact on biodiversity of using a mixture of plantation species rather than a monoculture? - What is the impact on biodiversity of maintaining understorey vegetation (e.g. grass cover between mallee rows at Condobolin)? - Can mixed-species plantations increase biomass productivity and profitability (particularly the use of eucalypts and nitrogen-fixing species in the Central Tablelands)? - What is the impact on biodiversity of factors such as proximity to native vegetation, stand age and landscape hetereogeneity? - What is the impact on plantation costs and profitability of factors such as proximity to native vegetation, stand age and landscape hetereogeneity? - Can biodiversity impacts be valued in economic terms, for inclusion further economic and policy analysis using tools such as INFFER (Pannell et al. 2009)?
7.4.2 Hydrology
The establishment of plantations may have positive, negative or neutral impacts on environmental values that are linked to hydrology. While plantations generally use more water than land uses involving pasture or crops, the level of water use and the impact on streamflow can vary substantially depending on factors such as the proportion of a catchment that is reforested, the location of plantations within a catchment, the design of plantations (e.g. strips vs. blocks) and management practices such as thinning (Prosser & Polglase 2006, Parsons et al. 2007). Furthermore, the impacts that plantation water use may have on important environmental values can be variable. For example, in some cases, plantation expansion can reduce water availability for both irrigators and environmental flows and allow salt levels in rivers to rise. In other cases, plantations may reduce salinity risks by reducing groundwater recharge. Parsons et al. (2007) cite southeastern South Australia as an example of the former, where a rapid expansion of blue gum plantations has led in competition for
353 water, and southwestern Western Australia as an example of the latter, where reforestation has helped to combat dryland salinity in a number of catchments.
Plantation expansion was highlighted in a 2006 CSIRO report (Dijk, Evans, Hairsine, Khan, Nathan, Paydar et al. 2006) as a major potential threat to water resources in the Murray-Darling basin, where both case studies are situated. The report highlighted a need for greater planning around reforestation across the basin, including not only large-scale commercial plantations, but also smaller-scale forms of agroforestry, environmental plantings and regrowth resulting from the exclusion of stock. Vertessy et al. (2003) highlight various planning strategies that can be employed to minimise the impact of plantations on water yield, including restricting plantations to less than 20% of the landscape, avoiding drainage lines and key runoff-generating sites, and ensuring a mix of stand ages within a catchment.
Planning around plantation water use falls under a broader framework for water reform that includes the National Water Initiative. This initiative has been established by the Council of Australian Governments (COAG), a collaborative body representing the Commonwealth as well as all State and Territory governments in Australia. The Murray-Darling Basin Authority is also vital in this area due to its responsibility for developing a basin plan that covers the highly controversial area of water rights and allocations.
Modelling by Dowling et al. (2004) shows the importance of the higher-rainfall upland areas in the south and east of the Murray-Darling basin such as the Central Tablelands, both in terms of water yield and the generation of salt. Modelling of an extreme 100% reforestation scenario by Dowling et al. (2004) shows that many of the areas where reforestation could contribute to reducing salt load overlap with areas where loss of water yield from reforestation would be highest. This further emphasises the need for locally-specific land use planning and targeted policy measures around plantation expansion. The Condobolin area is likely to be less important than the Central Tablelands in reducing salt load due to lower rainfall and the presence of regional rather than local groundwater flow systems. However, Figure 7.21 highlights some
354 areas near Condobolin where reforestation could contribute to significant reductions in salt generation.
Figure 7.21: Impacts of a change from current vegetation cover to 100% tree cover in the Murray-Darling basin. Left: impact on water yield, Right: impact on salt generation 15 years after planting. Reproduced from Dowling et al. (2004), with Condobolin marked by a dot and the Central Tablelands by a circle.
Issues around competition for water may be resolved by expanding water licensing systems normally used for irrigators and other extractive water users to rain-fed land uses such as plantation forestry. This approach has been taken under the Carbon Farming Initiative, with commercial plantations in areas with more than 600 mm long- term average annual rainfall being required to hold water access entitlements in order to be eligible for carbon credits. Plantations in such areas must hold water entitlements equivalent to 90% of the expected water use levels shown in Table 7.7. Under this system, Condobolin would be exempt from water licensing requirements (less than 600 mm rainfall), but the vast majority of the Central Tablelands would be covered. Exemptions to water licensing requirements are made for non-commercial environmental plantings (i.e. non-harvested), plantings that contribute to the mitigation of dryland salinity (whether for commercial harvest or not) and regions where it is not
355 possible to obtain a water access entitlement. The Carbon Farming Initiative administrator may also grant an exemption if advised by a relevant state or territory agency and other relevant experts that “there is no material impact on water availability, or on the reliability of existing water entitlements, in or near the project area, for the duration of the project”60.
Table 7.7: Water use offsets for plantations under the Carbon Farming Initiative. Rainfall zone (mm/year) Offset factor (ML of water per hectare) 600-700 0.9 700-800 1.2 800-900 1.5 900-1000 1.8 >1000 2.1
The approach taken in the Carbon Farming Initiative provides a template that could be adopted in other approvals processes for commercial plantations. It facilitates trade- offs between different water users (via trading of water rights), as well as between different environmental objectives relating to carbon sequestration, biodiversity and salinity mitigation. However, it also highlights the need for further research to gather specific local knowledge on the impacts of plantations on water yields and salinity. The Department of Climate Change and Energy Efficiency (2011d) has published a set of salinity guidelines to assist with the dryland salinity exemption from water licensing requirements. These guidelines permit three sources of evidence to be used to show that a plantation’s location and topography will contribute to the mitigation of dryland salinity:
1. A current regional Natural Resource Management (NRM) plan. This is the most straightforward option if the regional NRM plan contains this information. 2. Salinity risk maps and other supporting information. This is most relevant where a regional NRM plan does not contain the necessary information. 3. Direct measurements or monitoring information from the project area/s.
60 Carbon Credits (Carbon Farming Initiative) Regulations 2011 (Cth) s3.37 (8)(b)
356 For each of these options, the proponent must provide proof that their evidence has been been verified by either the relevant regional body (i.e. a CMA in NSW) or a Registered Greenhouse and Energy Auditor. Thus, CMAs have been assigned the role of certifying revegetation projects as contributing to the mitigation of dryland salinity in their region.
Of all the potential environmental benefits of commercial agroforestry discussed in this chapter, mitigation of dryland salinity features the greatest degree of past research work and policy support. As discussed in Chapter 4, the Lachlan, Central West and Hawkesbury-Nepean catchment plans all contain goals relating to revegetation in salinity-prone areas, with the Central West plan specifically mentioning the role that commercial plantations could play in achieving this.
A number of approaches for regional assessment of salinity mitigation strategies have been developed. The Commercial Environmental Forestry program, a 2003-2007 collaboration between CSIRO, DAFF, the Victorian Department of Primary Industries and a number of regional bodies, explored the potential for large-scale commercial plantations in landscapes prone to stream salinity in case study regions in Victoria and WA (Polglase 2007). Key outputs from this program include the Scenario Planning and Investment Framework (SPIF), a GIS-based scenario planning tool, and FLUSH-3-PG, which combines tree growth modelling based on 3-PG with modelling of water use and water flows at the hillslope level. An alternative approach is Hydrogeological- Landscape (HGL) mapping that can be used to identify priority areas for salinity mitigation and other environmental objectives (Geoscience Australia 2010). The Central West catchment has been used as a pilot region for the development of HGL mapping, with application to other regions being considered (Geoscience Australia 2010).
While revegetation has a clear role to play in the mitigation of dryland salinity, careful consideration is required of both the environmental and economic impacts of revegetation before deciding if policy intervention is justified. For example, Pannell et al. (2001) argue that many salinity problems in Western Australia result from local groundwater flow systems that vary in size, shape and geological structure. This runs
357 counter to the common perception that groundwater systems are interconnected and require common action across multiple properties. Bennett et al. (2011) found that mallee belts can cause significant reductions in groundwater recharge, but they also forecast that the area ultimately protected from dryland salinity by mallee plantings was likely to be no greater than the area occupied by the mallee trees. This highlights the role that commercial returns from salinity plantings may play in determing whether the combined public and private benefits of revegetation justify policy intervention.
Overall, salinity mitigation represents one of the most promising avenues for harnessing the economic driver of commercial agroforestry to deliver multifunctional environmental benefits. However, further research is needed that considers local salinity factors and other hydrological impacts, such as a loss of water yield for downstream users. Tools such as SPIF, FLUSH-3-PG and HGL mapping could provide useful frameworks for further research into these issues in the Central Tablelands and, to a lesser extent, around Condobolin. In terms of policy-making, a useful tool for considering hydrological impacts may be the INFFER framework that was discussed in Chapter 3 (Pannell et al. 2009) and has been used to identify key assets in the Central West CMA area (Central West Catchment Management Authority 2011). In particular, INFFER provides a framework for weighing up public and private benefits and determing when policy intervention may be appropriate, with the case study sites potentially offering suitable locations to trial this framework once further data has been collected.
7.4.3 Climate change
The climate change implications of bioenergy-based agroforestry include both mitigation and adaptation. Mitigation could result from the substitution of fossil fuels with bioenergy, as well as the sequestration of carbon in plantations. As these actions affect atmospheric greenhouse gas concentrations at the global rather than regional scale, climate change mitigation does not appear as a regional NRM goal in any of the CMA plans discussed in Chapter 4. Conversely, climate change adaptation is very much a regional issue, with revegetation activities potentially impacting on species migration, soil protection against extreme rainfall events and fire risk. Climate change
358 adaptation features prominently in the Hawkesbury-Nepean and Lachlan catchment action plans for 2006-2016, and in the revised Central West catchment action plan for 2011-2021. With regards to climate change mitigation, the impacts of different bioenergy systems can vary greatly, depending on:
x the energy source being displaced (e.g. coal, gas, oil); x the level of process emissions involved in sourcing the biomass (e.g. fertiliser, transport, processing); and x the impact that the establishment of energy crops has on carbon stores in vegetation and soils.
As this thesis is primarily concerned with regional NRM issues, a full greenhouse gas life-cycle assessment of each bioenergy option discussed in Chapter 6 is beyond the scope of the case study research. However, some general rules about the climate change mitigation potential of different bioenergy systems can be drawn from previous studies. These general rules are employed in Table 7.8, which provides a qualitative assessment of the bioenergy options discussed in Chapter 6.
The general rules used in Table 7.8 are primarily sourced from a study of the energy balance of mallee bioenergy in WA by Wu, Fu, Giles and Bartle (2007), a study of potential biomass energy options for Queensland by O'Connell et al. (2009b) and a European Union report into biomass energy sustainability requirements (European Commission 2010b). The European Commission report classes briquette and pellet production as a single category, with default emissions (excluding land use change) ranging from 2 g CO2-e per MJ of energy produced (European forest residues processed using wood fuel) to 40 g CO2-e per MJ of energy produced (tropical short- rotation forestry processed using natural gas). O’Connell et al. (2009b) found that greenhouse gas abatement from the use of forest residues and energy crops for bioenergy in Queensland would be greatest for electricity, followed by renewable diesel (via Fischer-Tropsch conversion) and then ethanol from cellulosic feedstocks. The differences between these three technologies are largely due to the conversion processes involved and the type of fuel that can be replaced by the bioenergy (e.g. coal, diesel or petrol).
359 Table 7.8: Qualitative assessment of climate change mitigation impacts. The bioenergy options included are those presented in Chapter 6.
Bioenergy Risk to Emissions benefit Emissions from Emissions from option carbon from substitution growing and transport of stores (substituted fuel processing biomass (from type in brackets) biomass (process clearing) fuel in brackets) Pellet export Low High (coal Low (wood) or Medium from Oberon assumed) medium (gas) (shipping) Pellet export Low High (coal Low (wood) or High (road & from Condobolin assumed) medium (gas) shipping) Briquettes for Low Low (firewood) Low (wood) or Low (local use) home heating medium (gas) or medium (national use) Co-firing w/ coal Low High (coal) Low (wood) or Low medium (gas) Biomass-only Low High (coal) or Low Low electricity medium (gas) Ethanol Low Medium (petrol) Medium Low Renewable diesel Low Medium-high Low Low (diesel) Renewable jet Low Medium-high (jet Low Low fuel fuel)
Each bioenergy option in Table 7.8 has a low risk of reducing carbon stores through land clearing due to the restrictions imposed by the NSW Plantations and Reafforestation Code and the Native Vegetation Act 2003 (NSW). In fact, if bioenergy plantations are established on previously cleared land with low carbon levels, they are likely to increase overall levels of carbon sequestration. The Department of Climate Change and Energy Efficiency (2011b) have indicated that mallee cropping for energy and other products is being investigated as a potential sequestration activity under the Carbon Farming Initiative, but methodologies are yet to be developed for such activities. Further research in the NSW Central West could aim to test whether the bioenergy options shown in Table 7.8 would indeed deliver the levels of greenhouse gas abatement indicated by previous studies in other locations.
360 In terms of climate change adaptation, future research in the NSW Central West should be integrated with research into biodiversity and landscape function, as climate change is likely to act as a stress multiplier for these factors. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change highlighted the limited capacity of Australia’s natural systems to adapt to higher temperatures, changes in rainfall and an increase in extreme events, due to high levels of habitat fragmentation (Hennessy et al. 2007). When considering the future research topics suggested in this chapter for landscape function (section 7.3), biodiversity (7.4.1) and hydrology (7.4.2), a key focus also needs to be on the potential for climate change to alter key variables, such as rainfall patterns, temperature, species interactions and rates of infiltration/runoff.
Climate change is also likely to impact on the viability of different plantation species at the case study sites. Figure 7.22 shows the results of a simple modelling exercise using the 3-PG models used to estimate biomass yields for the Central Tablelands in Chapter 6. To assess some of the impacts of climate change, the baseline model parameters were altered to reflect changes in temperature and rainfall based on data produced by CSIRO and BOM (2010) for three emissions scenarios used by the Intergovernmental Panel on Climate Change (2007)61. Adjustments were made to the baseline parameters for temperature, rainfall, solar radiation and frost days in each season, based on the “best estimate” (50th percentile) projections for the year 2070 from CSIRO and BOM (2010).
The results of the plantation modelling show a general pattern of declining biomass yield as atmospheric CO2 concentrations increase. However, they also highlight that the relative impact is likely to be different for different species and locations. In the case of Eucalyptus grandis (flooded gum) at Oberon and Bathurst, the 3-PG results suggest that climate change could have a positive impact on biomass yield. However, it should also be remembered that, for two of the three field sites reported in Chapter 6, the 3-PG model provided a poor prediction of species growth under current climatic conditions. The incorporation of climate change projections further compounds the uncertainties present in the 3-PG models for these species and locations. Other factors
61 The three emissions scenarios used were B1 (lowest), A1B (medium) and A1FI (highest). Full model parameters are listed in Appendix F.
361 not included in the results shown in Figure 7.22 include the impacts of climate change on drought patterns and the impact of increased atmospheric CO2 levels on species growth rates.
Figure 7.22: Impacts of climate change on biomass yield for four plantation species by 2070. Results are based on above-ground biomass at age 10 in dry tonnes from 3-PG modelling. B1 is the lowest emissions scenario, A1B is medium and A1FI is the highest.
362 Another factor that is likely to be affected by climate change is fire. Fire risk was not perceived to be a major barrier to agroforestry development by landholders at either case study site. However, CSIRO (2007a) has highlighted fire as a potential risk for plantation forestry in the Central Tablelands under climate change projections and the issue of fire risk has emerged as a key community concern in some parts of southern Australia where plantation forestry has undergone rapid expansion (Geddes 2006, Hirst 2007). GHD (2011) recently completed a research project looking at these impacts in partnership with Australian Forest Growers and the Australian Plantation Products and Paper Industry Council. The project used the Central Tablelands as one of six case study sites and was funded under the Forest Industries Climate Change Research Fund, the same program that funded the Central Tablelands research reported in this thesis. GHD (2011) concluded that bushfire risk to plantation forests was likely to increase in the Central Tablelands under climate change projections of higher temperatures, lower rainfall and more days of extreme fire danger. They recommended a landscape-scale approach to climate change adaptation, including tree pruning and maintenance of fire breaks within plantation areas, fuel hazard reduction in native forest areas adjacent to plantations and strengthening of existing systems for fire detection and suppression. The continued population growth of the Central Tablelands was identified as both a strength and a weakness. Higher populations may allow volunteer fire brigades to be maintained, but “tree-changers” can increase fire risks by increasing the amount of native vegetation across the landscape whilst being inexperienced at bushfire management.
A key question regarding plantations and fire is whether plantation expansion increases fire risk across a region. Geddes (2006) analysed 30 fires in hardwood plantations across six regions of Australia (mainly Tasmanian blue gum plantations). This study found that the plantation areas affected by fire were generally small and the rates of spread were lower in plantations of native species than they were in grassland, pine plantations and native forest. In particular, Geddes found that young plantations on former agricultural land had low fuel loads and may be able to slow the movement of a wildfire on extreme forest fire days. The Forest Industry Council (2007) also argues that well-planned and well-managed plantations generally reduce the fire risk for surrounding landscapes.
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Plantation fire risk may be higher where plantations are older (more fallen leaves and branches), second-rotation (fuel remaining from earlier rotation) or if a shrubby understorey is able to develop (Geddes 2006, Hirst 2007). However, while such factors may increase fire risk, they can also increase biodiversity value. Lindenmayer and Hobbs (2004) recommended that older trees be retained, understorey plants be encouraged and woody debris be left in place in order to enhance wildlife conservation in Australian plantations. These conflicting objectives indicate that trade-offs are likely to be required between reducing fire risk and enhancing biodiversity. Locating plantations next to remnant native forest to enhance connectivity is also likely to simultaneously increase the mobility of both wildlife and wildfire. Such trade-offs may be largely unavoidable, but further research into the effects of plantation expansion on both biodiversity and fire risk could help plantation managers and policy-makers to balance these objectives in an informed manner. Any such research needs to consider the impacts of climate change.
7.5 Conclusion
The results and analysis presented in this chapter provide some indications that agroforestry systems, including those for bioenergy, may be able to contribute to regional NRM goals. However, insufficient evidence exists at present to justify the widespread promotion of bioenergy-based agroforestry in order to achieve these NRM goals. Encouraging the widespread establishment of bioenergy plantations before impacts are fully understood could lead to negative impacts from inappropriate plantation design and management. Key target areas for further research include the impacts of plantation establishment and harvesting on marginal (i.e. low capability) land, appropriate plantation designs to provide habitat for biodiversity, localised salinity impacts of plantations and plantation species performance under climate change projections. Further research is also needed into the potential risks that plantations could present, particularly for soil health and bushfires.
Soil protection and salinity mitigation appear to be two of the most promising avenues for linking agroforestry to regional NRM goals. LFA results obtained from both case
364 study sites provide preliminary evidence that commercial plantations could improve key soil attributes such as infiltration and nutrient cycling compared to other land uses. No direct salinity results were obtained in this study, but research in other areas has identified a role for revegetation in reducing groundwater recharge, with this strategy being endorsed in catchment action plans by the Lachlan, Hawkesbury-Nepean and Central West CMAs. Commercial agroforestry may be able to make a contribution to the conservation of biodiversity, but this remains subject to widespread uncertainty. It is unlikely that the kinds of monocultural and homogeneous plantations assessed in this chapter would be able to contribute to CMA biodiversity targets, as such targets usually require that local endemic species are used (e.g. Lachlan and Hawkesbury- Nepean CMAs) or that management is “primarily” for conservation (e.g. Central West CMAs).
Another target area for future research is the extent to which environmental costs and benefits are experienced privately (i.e. on property) versus publically (i.e. off property). The INFFER tool discussed in Chapter 3 could assist with this task, particularly through its Public: Private Benefits Framework (Pannell 2008). INFFER has been employed recently by the Central West CMA to identify key assets with high environmental, social or economic values, but this has not been done for the remainder of the Central Tablelands region or for the Condobolin area. Key advantages of the INFFER approach are that it employs an extensive community consultation process, delivers a detailed summary of each asset and provides a framework for incorporating these assets into policy-making. CRITINC is another tool discussed in Chapter 3 that could be used to identify critical natural capital in line with the principles of ecological economics. The use of tools such as INFFER and CRITINC is beyond the scope of this thesis due to limitations of time, data and the specialised skills required, but these tools could provide a framework for planning future research into the environmental impacts of bioenergy-based agroforestry in the case study regions.
The high levels of uncertainty surrounding NRM benefits in the case study regions have important implications for the development of sustainability policy relating to bioenergy-based agroforestry. As discussed in Chapter 1, the precautionary principle requires that measures to protect against severe or irreversible impacts be put in place
365 where scientific uncertainty about such impacts exists. Another strategy for dealing with uncertainty is adaptive management, which features heavily in the ecosystem approach and resilience theory discussed in Chapter 3. These implications for policy development are discussed further in the following chapter, which draws on the results of three case study analysis chapters (5, 6 and 7) and applies the policy framework outlined in Chapter 3 to develop recommendations for sustainability policy around bioenergy-based agroforestry.
366 Chapter 8: Policy Development and Recommendations
The social, economic and environmental analyses presented in Chapters 5, 6 and 7 underscore the complexity of issues surrounding the establishment of a bioenergy- based agroforestry industry at either of the case study sites. While the case study analyses have highlighted a range of potential synergies between bioenergy production, landholder goals and regional NRM targets, they have also highlighted the uncertainty that surrounds such land use options and the need for trade-offs between environmental, social and economic objectives. The aim of this chapter is to cut through this complexity to identify feasible policy pathways to address key knowledge gaps and trial land use activities that could address multiple objectives at the case study sites. This includes consideration of the possibility that the best way forward may be to keep policies unchanged.
This chapter is structured according to the policy framework outlined in Chapter 3. The five stages of the framework, shown in Table 8.1, are based on the policy frameworks of Dovers (2005), Clark (2002) and Diesendorf (2000) and incorporate key concepts from multifunctionality, conservation through sustainable use (CSU), adoption theory, ecological economics and resilience theory. Section 8.1 of this chapter covers problem- framing/orientation (Stage 1), 8.2 covers policy-framing (Stage 2), 8.3 policy evaluation (Stage 3) and 8.4 implementation (Stage 4). The largest of these sections is 8.3 (policy evaluation), which includes a detailed analysis of a range of different policy options. Recommendations are provided on the selection of policy goals and principles in section 8.2, on the selection of policy instruments in section 8.3 and on strategies for implementation and monitoring in section 8.4. These recommendations are aimed specifically at the case study regions, but have implications for other parts of NSW, other states of Australia and, potentially, for other countries around the world.
367 Table 8.1: Sustainability policy framework developed in Chapter 3.
Stage Key Elements 1. Problem-framing/orientation - Identify social goals, topicality of issues, existing (section 8.1) conditions, trends, causes & existing policy - Identify potential synergies and trade-offs - Project potential scenarios and developments - Define policy problems
2. Policy-framing Select: (section 8.2) - policy principles - policy goals 3. Policy evaluation - Identify policy options (section 8.3) - Assess policy impacts and interactions - Select policy measures for implementation 4. Implementation through - Implement policy measures adaptive management - Re-orient systems/structures (section 8.4) - Identify key parameters and commence monitoring - Review & revisit Stages 1-4
8.1 Problem-framing/orientation
Following Dovers’ (2005) concept of problem-framing, this section focuses on identifying key issues, analysing conditions and trends, identifying causes and defining policy problems to be resolved. As in Chapter 3, the terminology used is based on the idea that “issues are for being concerned about and debating, problems are for resolving” (Dovers 2005, pp. 41-42). Section 8.1.1 reviews the major issues and social goals relating to bioenergy-based agroforestry across multiple scales. Section 8.1.2 looks at current trends and attempts to map out plausible future scenarios for the case study regions. Section 8.1.3 defines the key policy problems to be resolved in the remaining stages of the policy framework.
8.1.1 Issues, goals, synergies and trade-offs
The topicality of different sustainability issues varies across geographic scales and stakeholder groups. Figure 8.1 illustrates some of these differences by matching key sustainability goals for the revegetation, plantation and bioenergy sectors to the issues
368 and scales that are most applicable. This draws on the discussion of sustainability issues at the global and national scales in Chapter 2 and at the case study scale in Chapters 4-7.
Environmental issues such as biodiversity conservation and climate change are topical at all scales, but the emphasis can vary. While global biodiversity conservation goals are often focused on maintaining habitats, the case study analysis showed a strong focus on habitat enhancement. Similarly, for soil and water health, enhancement goals are more prominent at the local rather than global scale. Climate change goals also vary, with mitigation policy dominating at the global and national scales and adaptation being primarily a regional-scale issue. However, as discussed in Chapter 5, case study landholders tended to focus more on climate change mitigation (e.g. renewable energy, sequestration) than on adaptation. This may be due to the dominance of mitigation strategies in public discourse (e.g. carbon tax debate) and a tendency for farmers to view adaptation as part of a broader notion of sustainable farming rather than as a stand-alone issue (Hogan et al. 2011).
With respect to socio-economic issues, a strong growth focus is evident in many national-scale policies for renewable energy and plantations (e.g. Treasury 2011, Plantations2020 2002). However, for case study landholders, goals such as maintaining livelihoods, staying on the land and increasing farming resilience were cited more often than growth or expansion. Some landholders did mention the need for continued productivity increases or diversification, but this was generally viewed more as a response to changing global conditions (e.g. high Australian dollar, high input costs) than as an end in itself. Some social issues, such as land rights and job creation are topical from the global scale through to the landholder scale. However, the nature of these issues varies significantly. While land rights goals contained in global sustainability standards usually focus on land being seized for production purposes, case study landholders were more concerned about their land use rights being removed by governments in the name of conservation (e.g. restrictions on land clearing). Similarly, the goal of maintaining food production is common at the global scale, but was outweighed at the case study scale by a view that farmers have the right to decide what they produce from their land.
369 370
Figure 8.1: Major goals and issues identified in this research. Key sustainability issues are shown on the y-axis, with their scale shown on the x-axis). Red arrows show potential synergies, blue arrows show trade-offs and purple arrows show mixed synergies/trade-offs.
Figure 8.1 also identifies a number of potential synergies and trade-offs between goals that could influence the development of policy around bioenergy-based agroforestry. These are labelled S1 to S5 for potential synergies, T1 to T3 for likely trade-offs and S/T1 to S/T6 for relationships that could produce either synergies or trade-offs in different circumstances.
The key synergies identified are: S1. Maintaining climate stability and maintaining species/habitats: The loss of forests and other habitats is a major contributor to climate change. S2. Expanding renewable energy and maintaining secure energy supplies: Energy security is a driver of renewable energy, especially biofuels. S3. Adapting to climate change and maintaining economic resilience: Future resilience requires successful adaptation to climate change. S4. Maintaining economic resilience and providing local jobs: Local job provision is a key component of economic resilience. S5. Maintaining economic resilience and maintaining land use flexibility: Case study landholders saw land use flexibility as critical to their adaptive capacity.
The potential trade-offs identified are: T1. Expanding energy plantations and maintaining land use flexibility: Plantations have a longer rotation length than cropping or grazing rotations. T2. Establishing carbon plantings and maintaining land use flexibility: The 100 year commitment for carbon plantings was a major barrier at Condobolin, but Central Tablelands landholders were more willing to consider this trade-off. T3. Maintaining food production and maintaining land use rights/flexibility: Land use restrictions to protect food production could reduce the land use options available to landholders (e.g. energy cropping, plantation forestry).
The relationships that could produce either synergies or trade-offs are: S/T1. Maintaining climate stability and expanding renewable energy: Bioenergy can replace fossil fuels, but climate change mitigation benefits may be eroded if emissions-intensive processes are employed (e.g. deforestation, fertiliser use).
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S/T2. Expanding plantations and expanding renewable energy: The case study results highlight the potential for bioenergy to be a viable plantation product under certain conditions, but demand for biomass from other plantation sectors (e.g. timber, paper) could prevent an expansion of energy cropping. S/T3. Expanding plantations and maintaining climate stability: Plantations can increase carbon sequestration and help to maintain climate stability, but not if forests are not cleared for establishment. S/T4. Adapting to climate change and enhancing habitat connectivity: Connected habitats facilitate species migration, but if landholders lose all income from such land they may consider this to be a poor adaptation strategy. S/T5. Expanding energy plantations and enhancing habitat connectivity, erosion control and salinity mitigation: The case study results show that plantations may be able to contribute to these goals, but poor plantation design and management could have negative impacts on existing habitat, marginal land and fragile soils. S/T6. Expanding energy plantations and maintaining food production: Loss of food production due to plantation expansion is topical at a global scale as well as in some regions of Australia. However, carefully integrated plantations may be able to enhance food production in some cases (e.g. Oil Mallee in WA)
8.1.2 Scenarios for bioenergy-based agroforestry at the case study sites
The case study results highlight a range of potential scenarios for combining the different goals outlined in section 8.1.1. However, following Clark’s (2002) argument that researchers should explicitly acknowledge their own standpoint and Rogers’ (2003) prescriptions for dealing with bias in diffusion research, it is important for me to first acknowledge that my own vision has shifted during the course of this research. Initially, my focus was on the revegetation of degraded or vulnerable landscapes, with bioenergy production viewed as a means to this end. However, my exposure to different stakeholder perspectives and increased understanding of the broader policy and research context has led to other goals being elevated in my vision of sustainability. I no longer view energy cropping as simply a means of revegetating landscapes, but also recognise its implications for other goals, particularly enhancing
372 the socio-economic resilience of farming systems and mitigating climate change through the provision of renewable energy.
For the Condobolin case study, the dominant vision of a regional bioenergy industry revolves around blue mallee (Eucalyptus polybractea) integrated into existing cropping and grazing mosaics. Within this vision, there are a number of key design features that require further consideration, including: - Whether mallee should be located on marginal land, where competing use value is lower, or higher-quality land, where biomass production may be higher; - Whether mallee should be planted in large dedicated blocks, which may be more accessible for a regional bioenergy industry, or smaller strips, which may be easier to integrate into existing farming operations; - The positive and negative effects of mallee on adjacent crops, including wind protection and competition for water; and - Location and design factors of plantations to maximise environmental benefits versus economic return.
Row spacing and the role of groundcover emerged as key design issues at Condobolin, with the landscape function analysis (LFA) results in Chapter 7 highlighting the potential for mallee plantings to either enhance or degrade soil health depending on how they are established and managed. These structural attributes are also important for biodiversity conservation, with Lindenmayer and Hobbs (2004) recommending that plantations be designed to retain existing habitat elements (e.g. paddock trees, fallen logs), be located close to existing native vegetation and be managed to create a diversity of ages and structural characteristics. Based on results from Western Australia (Smith 2009), mallee plantings may provide some habitat value, but many of the attributes suggested by Lindenmayer and Hobbs (2004) would require a major trade-off in harvest efficiency due to reduced accessibility and uniformity of plantations.
The economic analysis in Chapter 6 indicates that mallee cropping at Condobolin would struggle to compete financially with typical cropping and grazing under base
373 case assumptions. For mallee cropping to be competitive, there would need to be a substantial rise in biomass prices, a fall in mallee production costs or a decline in returns from cropping and grazing. However, there was also a common view amongst interviewed landholders that mallee is a complement to existing land uses rather than a direct substitute. The most common vision espoused by interviewees was one in which a small portion of a property (5-15%) would be converted to mallee, with plantings located to minimise the loss of existing production and maximise co-benefits such as soil protection and shelter for livestock. Furthermore, expectations were generally not that returns from mallee would be higher than for existing land uses, but that mallee could help to reduce risk by providing a more consistent return and increasing the diversity of commodities produced.
While landholders may not require mallee to deliver the same returns as cropping or grazing, it would still need to cover its establishment and harvesting costs, something the economic analysis in Chapter 6 showed it would struggle to do under base case assumptions. Small-scale bioenergy options involving briquettes or pellets may be one way of achieving higher biomass prices, while also providing opportunities for landholders to scale up production over time and pursue a community ownership model. However, these options carry risks such as the saturation of the small Australian briquette market, price volatility in overseas pellet markets or being undercut by cheaper biomass sources.
Delta Electricity’s (2010) vision for co-firing mallee at Wallerawang power station offers a lower-risk way for landholders to trial mallee production, but would be less likely to deliver community ownership or high biomass prices. Liquid biofuels could offer returns higher than co-firing but lower than pellet export, but would require a very large scale of production. This creates a “chicken-or-egg” dilemma, in which either landholders or bioenergy producers would need to make a large, risky investment based on a technology that is yet to be proven commercially in Australia. Small-scale electricity generation could represent a means of delivering the higher biomass prices needed for mallee to deliver a positive return, but would require a feed- in tariff to guarantee electricity prices or reduced capital costs if a peak-only generation strategy is followed.
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Overall, a plausible scenario for the Condobolin region could feature the following:
1. Initial mallee establishment by a small group of landholders on up to 5% of their land. This would most likely require some form of financial assistance and a focus on landholders with a strong interest in the potential co-benefits of mallee cropping. 2. Initial production of briquettes for domestic markets, with expansion into pellets for overseas markets or niche electricity supply as production expands and commercial partnerships are developed. Co- firing at a major power station could also occur if sufficient landholders are attracted to this low-risk, low-return model and there is a rise in the price of LGCs (Large-scale Generation Certificates) and/or a feed-in tariff is introduced. 3. Active adaptive management to assess different planting locations and design factors, such as row spacing, proximity to native vegetation and the use of marginal land. 4. Possible future expansion into large-scale electricity or liquid fuel production if biomass prices rise and technologies become more certain.
A viable scenario for the Central Tablelands could look somewhat different to Condobolin, due to the division between larger and smaller landholders in the region, the greater uncertainty about plantation species and the presence of an existing plantation and wood processing sector. The social analysis suggested that larger landholders (>850 ha) were more commercially-oriented and more likely to require a return from agroforestry that was competitive with grazing. Small landholders (<100 ha) tended to be less reliant on the land for income, more likely to accept a lower return from agroforesty and more interested in environmental co-benefits such as windbreaks, habitat for biodiversity and salinity mitigation. Potential energy crops include established plantation species such as Tasmanian blue gum (Eucalyptus globulus) or shining gum (E. nitens) and more uncertain species such as manna gum (E. viminalis), sugar gum (E. cladocalyx) or silver wattle (Acacia dealbata). Opportunities also exist to explore alternate subspecies (e.g. E. globulus bicostata),
375 hybrids (e.g. E. globulus x E. grandis) or to design plantations with a mixture of species (e.g. acacias and eucalypts). A key barrier for species selection is a lack of species growth data for the region and for non-conventional plantation designs.
Based on the economic analysis in Chapter 6, the Central Tablelands appears closer than Condobolin to achieving returns from bioenergy-based agroforestry that are competitive with typical agriculture. The presence of biomass residues from existing wood processing in the Central Tablelands could also help to address the “chicken-or- egg” problem around bioenergy investment by allowing larger-scale options such as liquid fuels or co-firing to commence without a massive new investment in agroforestry. The opportunity for landholders to observe a functioning regional biomass market before committing to agroforestry could also increase trialability. However, the presence of cheap biomass wastes from wood processing may make it harder for biomass from agroforestry to compete, unless landholders were engaged in co-production (e.g. timber and bioenergy) or the scale of bioenergy production was sufficient to exhaust all existing biomass residues in the region. Small-scale options such as pellets or niche electricity generation may be a viable investment for an energy company, but these options are more likely to be based on existing biomass residues than on new purpose-grown biomass.
Reflecting these different characteristics, a plausible scenario could involve:
1. Initial development of a bioenergy facility at Oberon or Wallerawang, producing electricity or liquid fuels from existing biomass residues. 2. Establishment of native agroforestry by small landholders around Oberon and Lithgow interested in environmental co-benefits and prepared to accept lower returns for their biomass. The costs of managing the many small landholders in this area may be higher but transport costs should be lower. 3. Possible expansion onto larger landholdings in the west and north of the case study region once landholders have observed the successful development of bioenergy and native agroforestry in the southeast. Necessary pre-requisites would be a rise in biomass prices (e.g. from
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existing residues being exhausted) and/or new facilities in Bathurst or Mudgee to reduce transport costs. The scenarios presented above are unlikely to occur without significant changes to key economic conditions and/or targeted policy intervention. In the absence of such changes, the most likely scenario for each case study region is the continuation of existing trends, such as the increasing intersection of production, lifestyle and conservation values in the Central Tablelands and the fluctuation of the Condobolin region between Holmes’ (2006) “productivist” and “marginalised agriculture” modes depending on prevailing climatic and market conditions. Under this scenario, natural resource management policies are likely to continue to focus on revegetation as a solution to biodiversity loss, salinity and erosion, but it is questionable whether sufficient incentives for revegetation would exist to combat these problems, especially if they are further exacerbated by climate change.
8.1.3 Policy problems for the case study sites
Dovers (2005) classifies policy problems according to a hierarchy of macro, meso and micro problems. Macro-problems are based on broad sustainability issues, such as biodiversity conservation and climate change. Beneath these sit a range of meso- problems, such as maintaining existing habitats or enhancing connectivity. These in turn are underlain by micro-problems, such as uncertainty about local habitat needs or a lack of a clear framework for trading carbon from plantations. It is these micro- problems that are of most interest for the development of policy solutions for the case study regions. Table 8.2 applies Dovers’ (2005) problem hierarchy to the case studies in order to identify the key micro-problems to be targeted in Stages 2-4 of the policy development framework.
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Table 8.2: Policy problems to be resolved for the case studies.
Macro-problems Meso-problems Micro-problems Conserving - Improving habitat - Agroforestry/revegetation not biodiversity connectivity competitive with cropping or grazing - Ensuring habitat value of plantations - No incentive to locate plantations in - Maintaining areas of greatest need existing native - Uncertainty about habitat value of vegetation plantations - Measures to improve habitat value can increase costs - Plantation expansion can pose a threat to existing habitats Enhancing soil - Reducing soil - Agroforestry/revegetation not health erosion competitive with cropping or grazing - Reducing dryland salinity - No incentive to locate plantations in - Increasing soil areas of greatest need carbon and nutrient - Uncertainty about soil impacts of cycling plantations (especially on marginal land) Mitigating climate - Enhancing carbon - Lack of a clear pathway to earn change sequestration carbon credits from plantations - Reducing fossil fuel use - Bioenergy from plantations not - Protecting existing competitive with fossil fuels (in carbon stocks absence of high carbon price) - Some bioenergy production systems may have poor carbon balance and may sequester less than land uses they replace. Enhancing system - Maintaining and - Uncertainty about agroforestry yields, resilience enhancing costs, returns and risk sustainable land use options - Lack of landholder awareness about - Enhancing adaptive climate change adaptation capacity - Some plantation options may reduce - Maintaining food land use flexibility (especially those security involving carbon sequestration) - Increasing - Plantation expansion can pose a threat functional to food production biodiversity
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The micro-problems outlined in Table 8.2 fall under four broad themes. The first theme is the lack of economic competitiveness for activities that combine agroforestry, bioenergy and revegetation. The second theme relates to policy gaps such as the lack of incentives to locate plantations in areas of greatest need. The third theme is the uncertainty surrounding the impacts that plantations may have on biodiversity, soils and livelihoods and the lack of awareness around issues such as climate change adaptation. The fourth theme is the risk that plantation-based bioenergy systems may have negative impacts on existing habitats, marginal land, climate change (through poor carbon balance), land use flexibility and food production. These four themes have important implications for the identification of appropriate policy principles, goals and instruments in sections 8.2 and 8.3.
8.2 Policy-framing
Policy-framing provides a critical link between the policy problems identified in Stage 1 of the framework (section 8.1) and the selection and evaluation of policy instruments in Stage 3 (section 8.3). Policy-framing involves the selection of policy principles, the development of a policy statement and the definition of measurable policy goals (Dovers 2005). This section provides recommendations covering each of these elements.
8.2.1 Policy principles
Table 8.3 shows the policy principles that are recommended for application to the policy problem themes identified in section 8.1.3. To avoid unnecessary complexity, the recommended policy principles are applied to the four policy problem themes discussed in section 8.1.3 rather than to each individual micro-problem.
The policy principles shown in Table 8.3 come from three main sources. Firstly, Dovers (2005) provides a list of guiding principles for sustainability policy, including factors such as precaution, public participation and integration of knowledge. Secondly, the conceptual frameworks of multifunctionality, conservation through sustainable use (CSU), adoption theory, ecological economics and resilience theory
379 discussed in Chapter 3 each include key principles relating to policy development. Thirdly, the social analysis presented in Chapter 5 provides guidance on how different policy measures are likely be perceived by landholders and other key stakeholders in the case study regions. While the views of local stakeholders should not necessary over-ride other priorities, policy measures stand a higher chance of success if they align with local stakeholders’ perceptions of fairness and efficacy.
Table 8.3: Recommended policy principles. Policy Problem Policy principles Source Themes Lack of Favour sustainable use of renewable Dovers (2005) economic resources over non-renewable resources competitiveness Use incentives to promote actions where net Adoption theory for agroforestry public benefits exceed private costs (Pannell 2008) and bioenergy Consider technology change where an action Adoption theory has net public benefits but high private costs (Pannell 2008) Internalise public benefits provided by CSU, Dovers private actors (e.g. beneficiary pays) (2005) Land use options supported by subsidies are Social analysis vulnerable to future policy changes Upfront support is less risky than future Social analysis support Lack of Ensure integration of ecological, economic Dovers (2005) incentives and and social goals in policy frameworks and frameworks institutional structures Align incentives between conservation and CSU use Ensure that policy measures include local Multifunctionality, criteria and management is decentralised to CSU, Social the lowest possible level analysis
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Policy Problem Policy principles Source Themes Ensure benefit-sharing is equitable, CSU, Dovers considering local stakeholders, marginalised (2005), Social groups and inter-generational equity analysis Priorities for policy-setting: 1. Sustainable Ecological scale, 2. Equity and 3. Efficiency economics Scale, equity and efficiency each need to be Ecological targeted with a separate policy measure economics Where natural capital stocks fall below Ecological critical levels they must be restored economics Uncertainty and Apply the precautionary principle Dovers (2005) lack of Learn to live with uncertainty, promote Resilience theory, awareness diversity and value redundancy Social analysis Maintain opportunities for self-organisation Resilience theory Combine different types of knowledge Dovers (2005), (scientific, local, indigenous) CSU, Resilience Enable public participation and education, Dovers (2005), including marginalised stakeholders CSU Threats from Assess sustainability impacts of policy Dovers (2005) plantation actions expansion Internalise costs relating to public goods CSU, Dovers (e.g. polluter pays) (2005) Disincentives (e.g. regulations, taxes) should Adoption theory be used where actions have net public costs (Pannell 2008) that exceed private benefits Critical natural capital should not be traded- Ecological off against human capital economics
In addressing the lack of economic competitiveness of agroforestry and bioenergy at the case study sites, broad principles are offered by Dovers (2005) and under the
381 concept of Conservation through Sustainable Use (particularly the ecosystem approach discussed in Chapter 3). These broad principles include the need to favour renewable resource use over non-renewables and the need to ensure that any public benefits are internalised when making comparisons between different land uses and energy sources. More specific policy principles are provided by Pannell et al. (2008) on the use of incentives where public benefits exceed private costs and the promotion of technology change where public benefits exist but private costs are high. The social analysis in Chapter 5 highlighted landholder resistance towards land use options that are viable only with perpetual subsidies and a preference for upfront rather than future support due to the latter being vulnerable to future policy and economic changes.
The lack of incentives and frameworks for targeting agroforestry towards the delivery of environmental co-benefits requires consideration of CSU principles such as managing according to local criteria and equitable benefit-sharing. Ecological economics also provides a number of relevant principles, including the prioritisation of sustainable scale over equity and efficiency, the need for separate policy measures to address each of these goals and the importance of protecting and restoring critical natural capital.
Dovers (2005) suggests a range of policy principles for dealing with problems related to uncertainty, including the application of the precautionary principle, the integration of different types of knowledge and the importance of public participation. The precautionary principle, as defined under the EPBC Act in Chapter 1, states that lack of full scientific certainty should not be used as a reason for postponing measures to prevent environmental degradation if there are threats of serious or irreversible environmental damage. Resilience theory also has a strong focus on uncertainty, with Armitage (2007) arguing that adaptive capacity depends on learning to live with uncertainty, valuing diversity and redundancy and maintaining opportunities for self- organisation of social, institutional and ecological systems.
The final theme, ensuring that bioenergy-based agroforestry does not have perverse outcomes on environmental and social values, requires policy principles such as the assessment of policy impacts (from Dovers 2005), the internalisation of costs relating
382 to public goods (from the ecosystem approach) and the use of disincentives where actions have public costs that exceed private benefits (Pannell 2008). Ecological economics places great importance on maintaining critical natural capital, which Farley and Gaddis (2007) argue has infinite marginal value and cannot be traded-off against other forms of capital using monetary valuation techniques.
8.2.2 Policy goals for the case study sites
Policy goals should be detailed and measurable in order to facilitate policy evaluation as part of an adaptive management cycle (Dovers 2005). However, it is difficult to develop detailed goals for the case studies due to the high levels of uncertainty regarding the impacts of bioenergy-based agroforestry and the fact that this policy framework forms part of a PhD thesis rather than a policy statement from a Government agency with clear lines of authority and responsibility. Dovers recognises that goal-setting can be challenging in cases where uncertainty makes it difficult to define desirable states or outcomes. In such cases, he recommends an approach based on further public participation and adaptive cycles of implementation and review to refine goals over time. Following this approach, the goals outlined in Table 8.4 represent tentative goals that are predominantly process-oriented rather than outcome- oriented. These goals would need to be further refined through the process of trial implementation and review (section 8.4). The goals are arranged according to the same four themes used to categorise policy principles.
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Table 8.4: Recommended policy goals.
Policy Problem Policy Goals Themes
Lack of Increase adoption of agroforestry activities that contribute to economic revegetation objectives without posing undesirable threats competitiveness Incentivise the replacement of greenhouse-intensive energy for agroforestry sources with low emissions technologies including bioenergy and bioenergy Internalise costs relating to land degradation and climate change within responsible industries
Support research and development into biomass production systems and bioenergy from plantation biomass
Lack of Incentivise agroforestry options that provide biodiversity and/or incentives and soil benefits over land uses that do not provide such benefits frameworks Incentivise agroforestry options that sequester carbon over land uses that do not
Uncertainty and Support research and development into the impacts of different lack of agroforestry systems on biodiversity, soils and climate change awareness Protect vulnerable habitats and landscapes against agroforestry activities with uncertain impacts
Increase public awareness regarding climate change adaptation
Ensure public participation in refining policy goals and selecting policy actions
Threats from Create disincentives for agroforestry activities that threaten plantation existing habitats or degrade soils expansion Impose limits on total levels of rural resource use (particularly land and water), with different allocations for food and non-food production (including agroforestry)
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The goals listed in Table 8.4 cover the creation of incentives for beneficial forms of bioenergy-based agroforestry, disincentives to protect against developments which pose significant risks, research and development to increase knowledge around these land use options and public participation to inform key stakeholders and ensure their views are taken into account. While there remains much uncertainty about the role that agroforestry might play in improving habitat connectivity, controlling erosion or mitigating salinity in the case study regions, the environmental analysis presented in Chapter 7 shows sufficient potential to justify a tentative goal around the adoption of beneficial forms of agroforestry. Achieving this goal requires the creation of incentives for agroforestry activities that provide environmental benefits and disincentives for activities that present threats. It is not possible at this stage to set adoption targets for agroforestry or to specify the exact form that such plantations should take. Similarly, while targets have been set for overall renewable energy development under the Renewable Energy Target, it would be premature to set specific targets for bioenergy from agroforestry.
Due to the widespread uncertainty around the impacts of bioenergy-based agroforestry, furthering knowledge through research, development and deployment represents a key policy goal. This relates to the economics of agroforestry and bioenergy as well as to the impacts of agroforestry on biodiversity, soils and climate. Strategic actions to promote public awareness and public participation can play a role in addressing uncertainty and refining policy goals. Due to the uncertainty of agroforestry impacts, particularly on marginal land, precautionary measures are required to protect existing habitats and soils. The final goal listed in Table 8.4 is designed to reduce conflicts such as food versus fuel and draws on the principle of ecological economics that we should first set a sustainable scale of resource use and then allocate resources to deliver equity and efficiency. However, this goal does not imply that land should be allocated exclusively to food, fuel or another use. Instead, a key focus should be the integrated use of land to deliver commodity outputs alongside conservation goals (i.e. multifunctional land uses).
Some of the goals listed in Table 8.4 can be found in existing policy measures, such as the promotion of bioenergy under the Large-scale Renewable Energy Target (LRET),
385 the protection of habitat under the Native Vegetation Act 2003 (NSW) and government support for research and development around plantation-based bioenergy systems. However, other goals have not been incorporated into any existing policy measures and there is a lack of integration between the goals that do exist due to the traditional separation of revegetation, plantation and bioenergy policy. Section 8.3 evaluates existing and potential policy measures that could address the goals identified in Table 8.4.
8.3 Policy Evaluation
This stage of the framework is where specific policy instruments are identified, assessed and selected. The policy instruments explored in this section were introduced in Chapters 2 and 3, with specific policy measures relevant to the case study sites discussed in Chapter 4 and potential variations considered in Chapters 5-7.
8.3.1 Identification of policy options for the case study sites
As discussed in Chapter 3, Dovers (2005) uses institutional arrangements to divide policy instruments into fifteen categories, such as statute law, self-regulation and market mechanisms. Pannell (2008) employs a simpler categorisation based primarily on whether policy is designed to encourage or discourage change. While Pannell’s framework has the advantage of simplicity, it lacks a category based around changes to broader policy and institutional structures, such as intergovernmental cooperation and agency responsibilities. Thus, a hybrid approach has been used here to categorise the existing and potential policy instruments discussed in preceding chapters (Table 8.5). It features Pannell’s categories of incentives, disincentives, extension, technology change and no action, with an additional category for broader institutional measures.
For the existing policy instruments listed in Table 8.5, the relevant jurisdiction is noted, with international measures included only if they could have a direct impact on the case studies through trade in biomass products (e.g. sustainability standards) or international agreements (e.g. Kyoto Protocol).
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Table 8.5: Existing and potential policy instruments relating to revegetation, agroforestry and bioenergy at the case study sites.
Policy Existing or planned policy Potential policy instruments for instrument instruments (Int=International, introduction to case study sites category Aust=Australia-wide, NSW) Incentives x Grants for revegetation activities x Subsidies for multifunctional land (e.g. tax (Aust & NSW) uses (e.g. agriculture in EU) breaks, x Sequestration credits for x Extension of carbon credits to subsidies or environmental plantings, mallee commercial plantations mandates to plantings & salinity plantings x Extension of NSW Biobanking promote under Carbon Farming Initiative scheme to agroforestry adoption of (Aust) bioenergy, x Creation of a mandate scheme for x MIS tax breaks for plantation agroforestry or industrial heat from biomass establishment (Aust) revegetation) x Feed-in-tariffs for bioenergy x LRET – energy crops eligible for x Rewarding social/environmental target (Aust) outcomes through bioenergy x Greenpower voluntary scheme – incentives (e.g. biodiesel in Brazil, energy crops eligible (Aust) electricity in Germany) x Carbon pricing on fossil fuels, x Multipliers or banding for but not on bioenergy renewable energy certificates (e.g. x Biofuel mandates (NSW) UK sources receive between 0.25 x Excise tax rebates for biofuels and 4 certificates per MWh) (Aust) x Providing renewable energy x Overseas incentives for wood certificates upfront (e.g. solar PV pellet use (Int) in Australia) Disincentives x Native Vegetation Act (NSW) x Regulations restricting liquid (e.g. taxes or x Plantations & Reafforestation biofuels from native forest regulations to Code (NSW) biomass discourage x Local Environmental Plan (LEP) x Regulations restricting use of adoption of restrictions for plantations (NSW) agricultural land for biofuels (e.g. bioenergy- Eide 2008, Searchinger 2008) x Carbon price on certain emission based land sources x Meta-standard approach to uses with integrate existing forestry and x Restrictions on carbon credits for unsustainable agriculture standards into biofuel high-rainfall plantations (Aust) impacts) sustainability standards (e.g. UK) x Restrictions on generating electricity & LGCs from native x Integrated land use planning to forest biomass (NSW & Aust) resolve food vs fuel issues (Gallagher 2008) x Sustainability standards for x Expansion of carbon price to forestry products (Int & Aust) fertiliser use and off-road transport x Biofuel sustainability standards fuels (Int & NSW)
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Policy Existing or planned policy Potential policy instruments for instrument instruments (Int=International, introduction to case study sites category Aust=Australia-wide, NSW) Extension x CMA extension covering x Education and awareness (e.g. education revegetation & sustainable land campaigns for climate change to encourage management (NSW) adaptation desirable x Plantation sector extension, e.g. x Extension programs highlighting actions and Plantations2020 (Aust) role of agroforestry for salinity, discourage x Bioenergy sector extension, e.g. habitat and soil protection undesirable Renewable Energy Coordinators x Extension covering economics of actions) (NSW), Bioenergy Australia bioenergy-based agroforestry (Aust) Technology x Incentives for renewable energy x Active adaptive management of change (e.g. innovation through LRET and agroforestry to better understand: R&D measures carbon pricing (Aust) - biomass yields to promote the x Biofuels Capital Grants Scheme - habitat and soil impacts development & Second Generation Biofuels - carbon sequestration of desirable Research and Development x Feed-in tariffs or Renewable forms of Program (Aust) Energy Target multipliers to bioenergy- x Clean Technology Innovation encourage further R&D into based Program & Clean Energy Finance plantation-based bioenergy agroforestry) Corporation (Aust) x RIRDC and Joint Venture Agroforestry Program (Aust) x Research & development into biomass jet fuel (Aust & Int) Broader x Kyoto protocol (Int) x Establish cross-sectoral institutional x Clean Energy Future program institutions spanning revegetation, measures (Aust) plantations and bioenergy sectors (e.g. legal and x Division in the roles of the x Establish cross-juridictional institutional Commonwealth and states under institutions integrating state and structures) Australian constitution federal policy x Joint Commonwealth/state responsibilities for CMAs No action x Circumstances where policy x Informed inaction instruments listed above do not x Temporary inaction while further apply information is gathered
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Existing measures shown in Table 8.5 that operate at the state or national level include revegetation grants, carbon sequestration credits, renewable energy certificates (i.e. LGCs for bioenergy), managed investment schemes (MIS), biofuel mandates and land use planning laws. The potential policy measures shown in Table 8.5 are mostly variations on existing measures that could help to align them with the key concepts discussed in Chapter 3, such as the promotion of multifunctional land uses through targeted subsidies or renewable energy certificate multipliers, integrated land use planning that better reflects the ecosystem approach and adaptive management in line with resilience thinking. The policy measures outlined in Table 8.5 are discussed further in section 8.3.2, where their social, economic and environmental suitability for the case study sites is assessed.
8.3.2 Assessment of policy instruments for the case study sites
The assessment of policy instruments in this section considers not only which policy measures are likely to be effective, but also how they could be implemented. This draws on a range of policy selection criteria nominated by Dovers (2005), which are divided evenly into effectiveness criteria and implementation criteria (Table 8.6). These criteria are also revisited in relation to the selection of policy options in section 8.3.3.
Table 8.6: Selection criteria for policy implementation from Dovers (2005).
Effectiveness criteria Implementation criteria Information requirements Equity implications Dependability Cost Corrective versus antidotal focus Social/political feasibility Systemic potential Institutional feasibility Flexibility in space and time Monitoring requirements Efficiency Enforcement/avoidability Complexity and cross-sectoral influence Communicability
Due to the high level of uncertainty surrounding not only the impacts of bioenergy- based agroforestry but also the impacts that policy changes may have, it is prudent to follow an adaptive management approach, whereby policy interventions are seen as 389 deliberate experiments to increase knowledge (Stankey et al. 2005). Some policy options, such as revegetation grants, lend themselves to trial implementation in a small area, for a limited period of time or with a limited set of actors. Other options, such as changes to rules around the Large-scale Renewable Energy Target (LRET), have impacts that are too pervasive for small-scale trials and instead require further research and consultation to identify likely impacts prior to full implementation. Similarly, policy changes that could result in serious or irreversible environmental impacts require protective measures to guard against such impacts, in line with the precautionary principle.
Incentives
The economic analysis in Chapter 6 showed that upfront financial support for tree planting and other establishment costs could be one of the most effective policy options for improving the competitiveness of agroforestry. The social analysis in Chapter 5 also showed this form of support to be preferred by landholders at both case study sites. Upfront establishment support represents a lower risk option for landholders compared to support provided at the time of harvest (e.g. price support), which can be subject to political and economic uncertainty. Also, by contributing to investment costs, it can help to overcome a major barrier identified by landholders, particularly at Condobolin. Such support can be provided in a variety of forms. Cash grants and the provision of materials (e.g. fencing, seedlings) are methods commonly employed for revegetation projects funded by CMAs, the Australian Government’s Caring for Our Country Program or its new Biodiversity Fund. Low interest loans were also cited by landholders who had experience with them in relation to agricultural development. The economic analysis suggested that low-interest loans could have a substantial impact on net project returns over a 30-year project life. Managed investment schemes (MIS) can deliver a government subsidy in the form of tax breaks for plantation establishment, but did not rate highly either socially or economically in the case study analyses. Integrating environmental objectives into what is already a complex set of MIS tax rules could also prove challenging.
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The Queensland Community Rainforest Reforestation Program, discussed in Chapter 2, provides some lessons around upfront support for integrated plantation/revegetation activities. In particular, such support can create a risk of landholders accepting free seedlings and other support for environmental reasons without committing to long- term commercial management (Vize et al. 2005). Such an outcome may result in some environmental gains, but would fail to capitalise on the CSU (conservation through sustainable use) principle that an alignment of environmental and economic objectives can lead to more widespread adoption. This risk could be addressed by requiring some financial contribution from landholders or evidence of business planning. Trial implementation could allow the mix of incentives to be varied over time in response to stakeholder feedback, to determine which types of agroforestry were capable of delivering the best environmental outcomes and to test whether greater integration of economic and environmental objectives can result in higher rates of revegetation and greater cost-effectiveness. Such trials could also assess the suitability of tools such as the INFFER Public: Private Benefits Framework developed by Pannell (2008) and the CRITINC tool for identifying critical natural capital (Ekins et al. 2003).
Payments for ecosystem services are another class of policy instrument that can provide incentives for conservation, with carbon sequestration being the tradable credits option explored in most detail for the case studies. The case study analysis showed a major disparity between landholder attitudes towards carbon sequestration at the two case study sites. While landholders interviewed at Condobolin were strongly opposed to carbon plantings due to concerns over loss of land use flexibility and impacts on land value, surveyed Central Tablelands landholders were generally willing to consider committing to agroforestry for 70-100 years in return for carbon credits. The economic analysis also indicated that carbon credits could make a greater contribution to the viability of agroforestry in the Central Tablelands compared with Condobolin. However, the Australian Government’s Carbon Farming Initiative makes it difficult for commercial plantations to earn carbon credits in the Central Tablelands, with such activities yet to be assessed against the additionality requirements, no approved methodologies for calculating credits from commercial plantations and a requirement for water licensing in areas with more than 600 mm annual rainfall.
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Changes could be made to the Carbon Farming Initiative to increase incentives for integrated agroforestry, such as exemptions from water licensing for plantations that meet environmental goals, greater institutional support for agroforestry and flexibility around the 100-year commitment. The Carbon Farming Initiative already exempts plantings from water licensing requirements if they are commercial plantings that can be shown to mitigate salinity or non-commercial plantings that provide habitat. These exemptions could be extended to commercial plantings that provide habitat and soil protection benefits. Also, if water licensing for commercial plantations is considered necessary to prevent negative impacts on other water users, as is argued by the Department of Climate Change and Energy Efficiency (2011b), these rules should not be restricted to regulations covering carbon sequestration, but be made consistent across all plantation policies, including the Plantations2020 strategy, MIS taxation policy, the NSW Plantations and Reafforestation Code and the Australian Forestry Standard.
Institutional support for carbon sequestration in commercial plantations could be provided through guidelines on how integrated agroforestry could meet additionality requirements and the development of methodologies for calculating carbon sequestration. These changes are likely to require additional research and consultation. In terms of flexibility around the 100-year commitment to maintaining carbon stocks, the Carbon Credits (Carbon Farming Initiative) Act 2011 (Cth) currently allows for carbon stocks to be reduced or eliminated through land use change provided that the project proponent relinquishes a sufficient number of credits to account for the credits they were originally awarded. While this allows landholders to change their land use activities in the future, there is a risk that the cost of buying back credits could be much higher than the income they received at the time of planting. An alternative option would be to set a maximum buyback price set at the time of establishment (e.g. original value of carbon credits adjusted using the consumer price index). This would create more certainty for landholders, especially if accompanied by extension activities to ensure that landholders were fully aware of their rights and responsibilities around carbon trading. However, this could have significant consequences for other stakeholders and the broader carbon market that would need to be fully analysed prior to any policy change.
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The other relevant policy option involving payments for ecosystem services is the NSW Biobanking scheme, whereby developers can offset destructive activities by paying landholders elsewhere to undertake conservation actions. Biodiversity impacts do not lend themselves to substitution to the same extent as carbon credits, as the biodiversity value of revegetated sites is highly dependent on location, species choice and structural characteristics (Lindenmayer & Hobbs 2004). Given the level of habitat fragmentation and climate change risks facing Australia’s biodiversity, it may be prudent to follow an ecological economics approach that treats remnant habitat as critical or vulnerable natural capital for which trade-offs are not appropriate. A government payment scheme that simply rewards landholders for biodiversity benefits from plantations but without employing tradeable credits aspect would be more consistent with such an approach, but it may be more challenging to achieve politically due to the lack of the self-funding mechanism that is inherent to tradeable credits schemes such as Biobanking.
As discussed in Chapter 4, there are a range of NSW and Australian Government policy measures that provide incentives for bioenergy, including the Large-scale Renewable Energy Target (LRET), biofuel mandates and biofuel excise rebates. The introduction of a carbon price in 2012 will also provide an additional driver for bioenergy by making emissions-intensive activities more costly. In addition, overseas policies could have an impact on Australian bioenergy producers, such as incentives that increase demand for wood pellets or biofuels. However, none of these policy measures are aimed specifically at bioenergy from plantation biomass, and none contain provisions that favour bioenergy that contributes to revegetation objectives. The LRET directs investment to the lowest-cost renewable energy technologies and biofuel mandates in NSW differentiate only between fuel types (i.e. ethanol and biodiesel) but not between feedstocks.
If bioenergy from certain forms of agroforestry can be shown to provide greater public benefit than other types of renewable energy due to biodiversity, salinity, soil or climate impacts, bioenergy from these sources could be preferenced through the use of differentiated incentives. A number of these options were discussed in relation to multifunctionality in Chapter 3. For liquid biofuels, tax breaks can be structured to
393 preference feedstocks with desirable co-benefits, as has been done for biodiesel in Brazil (Pousa et al. 2007). Alternatively, mandate schemes can be structured to place extra weight on desirable feedstocks, such as the double-counting approach that has been implemented in the UK under the EU renewable energy directive (Department for Transport 2012). For electricity generation, differentiated incentives can be provided through the use of multipliers or banding for renewable energy certificates (e.g. UK) or feed-in tariffs that offer a range of different rates and bonuses (e.g. Germany).
In relation to liquid biofuels from woody biomass, a key challenge around providing additional incentives through the fuel excise system is that net excise for biofuels in Australia is already zero (i.e. excise is reimbursed through grants to producers). This would mean that any further support would represent not just foregone revenue, but an additional government subsidy, which could be politically difficult to achieve. The Australian Government is proposing to make changes to the fuel excise and tax credit system in order to impose an “equivalent carbon price” on fuel uses such as domestic aviation, rail transport and, if it is possible to achieve political agreement, heavy on- road transport (Commonwealth of Australia 2011b, p. xiii). It may be prudent to delay any further changes to fuel excise until there is greater clarity around the carbon pricing implications for the fuel excise system.
Another challenge for liquid biofuels is the pre-commercial status of second-generation biofuel technologies. This makes it difficult to determine the most appropriate level at which to set additional subsidies or multipliers. Given this uncertainty, an adaptive management approach could be trialled under the NSW biofuel mandate scheme. This could be similar to the EU’s double-counting system for biofuels from wastes and cellulosic feedstocks, with the level of multipliers adjusted over time in response to changes in the biofuel industry. Following the idea of a “social fuel” in Brazil (Pousa et al. 2007), fuels made from feedstocks that can be shown to enhance biodiversity, salinity or soil protection could receive an “environmental fuel” label and fuels that enhance the resilience of rural communities could receive a “social fuel” label. Fuels with both labels could receive a higher multiplier as a result (e.g. double-counted if one label held, triple-counted if both labels held).
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For electricity, a multiplier system could be introduced to the LRET to encourage bioenergy feedstocks with environmental or social co-benefits. The economic analysis in Chapter 6 indicated that increasing the price of Large-scale Generation Certificates (LGCs) or awarding more than one LGC per MWh of electricity may be effective ways in enhancing the viability of bioenergy-based agroforestry in the NSW Central West. However, Australia does not have a comprehensive certificate multiplier or banding system such as that used in the UK. Certificate multipliers have a chequered past in Australia, with the Solar Credits multiplier being criticised for flooding the market with “phantom” certificates (Buckman & Diesendorf 2010) and ultimately leading to the splitting of the Renewable Energy Target into the LRET (Large-scale Renewable Energy Target) and SRES (Small-scale Renewable Energy Scheme) in 2011.
While the history of multipliers and “phantom” certificates in Australia could make it difficult to add a new multiplier to the LRET, the SRES could provide an opportunity to trial such an approach. The SRES does not currently cover bioenergy, but it provides a fixed price for Small-scale Technology Certificates (STCs) created from small-scale solar, wind and hydro. It also has a multiplier in place already, albeit one that is due to be phased out in 2013. A fixed price for certificates could reduce risks for investors in energy crops and a multiplier could help to make energy cropping competitive with typical agriculture. A policy trial that extended the SRES to energy crops would require changes to legislation and eligibility rules, as the SRES was originally designed for small-scale solar, wind and hydro only. If medium or large bioenergy facilities were to be included under the SRES, changes would need to made to the annual calculation of the Small-scale Technology Percentage, which determines how many STCs must be purchased by liable energy companies (Office of the Renewable Energy Regulator 2011). Changes to existing timeframes may also be required, as the SRES multipliers are due to be phased out in 2013 and the Renewable Energy Target as a whole is planned to stop increasing by 2020 (Department of Climate Change and Energy Efficiency 2012).
Another of the economic policy factors modelled in Chapter 6 was the awarding of renewable energy certificates from plantation biomass at the time of establishment rather than the time of harvest. This change would fit well with the addition of biomass
395 from energy crops to the SRES, as this scheme already provides upfront certificates for solar, wind and hydro (Office of the Renewable Energy Regulator 2011). However, the primary difficulty for energy cropping would be ensuring that biomass was actually used for its intended purpose and that the level of generation was in line with expectations. One solution could be to allow plantation managers to surrender the certificates they had initially been awarded if the required generation did not eventuate, similar to the relinquishment provisions of the Carbon Farming Initiative. This could, however, create a financial liability for plantation managers if they were unable to sell their biomass for energy at the time of harvest and had to purchase certificates at much higher prices than their original sale price. Possible risk mitigation strategies could include the pooling of risk across a group of plantations or risk-sharing agreements between plantation managers and the energy companies that they intend to sell their biomass to.
Feed-in tariffs are another option for providing differentiated incentives in the electricity sector, but they also have a chequered past in NSW. A solar feed-in tariff was introduced in NSW in 2009 at a very generous rate of $0.60/kWh before being dramatically cut to $0.20/kWh in April 2011. Adding to the uncertainty was a threat, later withdrawn, to retroactively reduce tariffs for participants who had signed up at the original higher rate (Solar Choice 2011). There has also been a lack of focus on bioenergy under feed-in tariffs in Australia and a tendency to focus mainly on small- scale generation. However, if these barriers can be overcome, feed-in tariffs could be the ideal mechanism for introducing differentiated support for bioenergy in NSW. Unlike the use of multipliers under a tradeable certificate scheme such as LRET, feed- in tariffs allow fixed prices to be set separately for each production system, avoiding the problem of one technology affecting the incentives available for others. The economic analysis in Chapter 6 suggested that electricity prices of $60-140/MWh (compared to a baseline assumption of $40/MWh) would be needed to make bioenergy-based agroforestry competitive with typical agriculture, with the exact price required varying by technology and location.
Another incentive that could be provided for woody energy crops is the creation of a mandate scheme for industrial heat from biomass. The UK has a mandate scheme for
396 biomass heat (Department of Energy and Climate Change 2011) and major users of wood waste have lobbied for a similar scheme in Australia (A3P 2010). An alternative option would be to extend the Renewable Energy Target (i.e. LRET or SRES) to cover such activities. The previous inclusion of solar hot water heaters under the Renewable Energy Target shows that it is possible for such schemes to include non-electricity sources. However, the inclusion of solar water heaters has been criticised for distorting the certificate market (Buckman & Diesendorf 2010) and a separate biomass heat scheme would help to avoid this impact. As there is no renewable heat mandate at present, the use of multipliers or banding for energy crops could be incorporated from the start of the scheme.
In terms of the costs of different policy options, the Commonwealth Government would bear the cost of biofuel subsidies or tax breaks, while the additional costs associated with feed-in-tariffs or mandates for biofuels, electricity or heat would be borne by energy suppliers and, ultimately, their consumer base. Following the polluter- pays principle, passing costs onto energy suppliers would be justifiable where the environmental and social goals of the policy measure were related to climate change, as the electricity and road transport sectors are major sources of Australia’s greenhouse gas emissions (Commonwealth of Australia 2011b). Benefits that could quality as climate change adaptation include habitat provision to facilitate species migration, soil protection against an increase in extreme rainfall events or socio-economic adaptation of rural communities. Salinity mitigation has less of a connection to climate change, but could represent a more sensible starting point for the trialling of multifunctional policy measures due to the knowledge that has already been gained through projects such as Oil Mallee in WA and the development of mechanisms for verifying the salinity benefits of plantations under the Carbon Farming Initiative. For any trial, there would need to be a mechanism by which agroforestry activities could be certified as providing the desired benefits, with Catchment Management Authorities having the capacity to contribute to this in NSW.
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Disincentives
Most of the disincentive measures with relevance for bioenergy-based agroforestry in NSW are regulatory restrictions relating to native vegetation, land use planning and forestry, although pricing mechanisms for water and greenhouse gas emissions also provide disincentives for wasteful or environmentally-damaging activities. A key issue for regulatory restrictions is how they should be targeted. While some measures may cover a broad range of land uses or production systems, others may be targeted at a single land use or product, such as bioenergy. For example, the Native Vegetation Act 2003 (NSW) is targeted at the land use level and applies broadly across many different activities (e.g. clearing for agriculture, forestry or urban development). The NSW Plantations and Reafforestation Code is also targeted at the land use level, but applies only to plantation-based activities. Sustainability standards are generally targeted at the product level and may cover a wide variety of products (e.g. Forestry Stewardship Council, Sustainable Agriculture Network) or only specific products (e.g. Roundtable on Sustainable Biofuels, Roundtable on Sustainable Palm Oil). Restrictions on generating electricity from native forest biomass under the Protection of the Environment Operations (General) Regulation 1998 (NSW) are another example of restrictions covering only one product.
A general principle followed in this chapter is that regulatory restrictions should be applied broadly across all production systems (e.g. food, fuel, fibre), unless a particular product poses a unique threat or has specific characteristics that require targeted regulations. While bioenergy-based agroforestry could pose threats such as land clearing, land degradation and land use competition, it is not unique in posing these threats. For example, electricity generation from native forest biomass has been banned in NSW, but many NGOs argue that woodchip export poses a similar threat (e.g. The Wilderness Society 2011, Australian Conservation Foundation 2011). Furthermore, technological advances around second-generation biofuels could create a new source of demand for forest biomass in coming years. Thus, it may be more appropriate to address concerns about over-harvesting of forests at the forest management level rather than at the product level.
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In relation to competition for land, there is no convincing argument for imposing restrictions on bioenergy-based land uses alone, as other activities such as plantation forestry, cotton-growing, mining and urban expansion can also have indirect impacts on food production and prices. Rosillo-Calle et al. (2007 p. xx) argue for an integrated approach, stating that:
"Large-scale energy plantations require that a country or region has a policy on how to use its land. Such a policy would go far beyond energy to include policies on food production and prices, land reform, food exports and imports, tourism and the environment".
Gallagher (2008), reporting on the indirect impacts of biofuels to the UK Government, argues that a global land use planning agreement would be the “optimum solution” to ensure that bioenergy production is directed to areas where it is most appropriate. While such an agreement is likely to remain an elusive goal at the global level, it may be possible at the state or national scale, with one model being the Strategic Regional Land Use planning process that has recently commenced in NSW. This process involves preparing regional plans that identify strategic agricultural land across NSW (Figure 8.2). The main purpose of this planning process has been to identify areas that could be at risk from mining or coal seam gas development, with the NSW Government proposing that any such activities within 2 km of strategic agricultural land undergo assessment by an independent panel (Department of Planning and Infrastructure 2012).
While the focus of Strategic Regional Land Use planning in NSW is currently on mining and coal seam gas, and some groups have rejected the proposed protections as inadequate (e.g. NSW Farmers’ Association 2012), the broad framework could form the basis of an integrated planning approach that ensures adequate food production while still allowing for the development of new industries such as bioenergy-based agroforestry. Any such planning would need to ensure that it did not preclude integrated land use options, such as mallee belts within wheat fields, or options that might displace agriculture in the short-term but protect it in the long-term (e.g. through salinity mitigation).
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Figure 8.2: Strategic agricultural land (SAL) identified in the New England and Northwest region of NSW. Source: Department of Planning and Infrastructure (2012).
Competition for resources is not restricted to land, with water use being a key issue for bioenergy plantations. As discussed in relation to incentives, the Carbon Farming Initiative imposes water licensing requirements on commercially-harvested plantations to prevent negative impacts on other water users, but waives this requirement for plantings that provide biodiversity or salinity benefits. This principle could be extended beyond carbon sequestration to cover all plantations, with the Plantations and Reafforestation Code being the most effective mechanism for achieving this in NSW. Plantations could be required to hold water licences for their estimated use of incident rainfall unless they offer environmental benefits such as salinity mitigation, soil protection or habitat for biodiversity. Unlike under the Carbon Farming Initiative, these exemptions should be available to both commercial and non-commercial plantations, based on an assessment of their likely impacts on a landscape scale. This would represent a trade-off approach, whereby a certain level of biodiversity, salinity or soil benefit would be considered sufficient to outweigh the loss of water to downstream users or environmental flows.
For plantation-based bioenergy feedstocks that are produced and used within NSW, policy instruments such as the Plantations and Reafforestation Code, the Environmental Planning and Assessment Act 1979 (NSW) and the Strategic Regional Land Use planning process present the most appropriate mechanisms for achieving sustainable production. However, where biomass feedstocks are exported (e.g. to Europe) or imported (e.g. to meet the NSW biofuel mandate), international 400 sustainability standards may be required to mitigate threatening processes. Such standards can create a disincentive for unsustainable production, by making it difficult for uncertified feedstocks to access bioenergy markets. In such cases, it would appear prudent to adopt internationally-recognised standards rather than develop new standards, as has occurred with the adoption of Roundtable on Sustainable Biofuels standards under the NSW Biofuels Act. Exceptions may be required in cases where international standards have been developed without taking into account important factors relevant to Australia, such as the need to revegetate areas of farmland to mitigate dryland salinity.
Before international sustainability standards are applied to Australian bioenergy policies, an assessment should be undertaken that compares the risk of contributing to unsustainable practices to the regulatory burden that would be imposed on producers. For liquid biofuels, the high level of international trade makes the adoption of international standards a sensible option. However, it is much less likely that biomass feedstocks would be imported to produce electricity under the Large-scale Renewable Energy Target (LRET). As such, the adoption of international standards under the Renewable Energy (Electricity) Regulations 2001 (Cth) may be unnecessarily burdensome compared to the current rules requiring energy crops to be sourced in accordance with relevant Commonwealth or state planning and approval processes and be managed under an approved code of practice (with the Australian Forestry Standard listed as a default).
One aspect of international sustainability standards that could be incorporated into eligibility rules for bioelectricity under the LRET are greenhouse gas benchmarks. This has occurred in the UK, where biomass electricity is required to deliver life-cycle greenhouse gas savings of at least 60% compared to fossil fuel generation (Department of Energy and Climate Change 2012b). However, given the additional burden that this would create for bioenergy producers and the fact that almost all of Australia’s bioelectricity is sourced from wastes or residues at present, further research into typical greenhouse gas balances is needed before such a change could be justified.
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The introduction of carbon pricing in July 2012 will create a disincentive for some bioenergy production processes that involve high life-cycle emissions, such as energy- intensive processing that uses electricity or gas (e.g. wood pellets). However, other activities are excluded from carbon pricing, such as fertiliser application and off-road fuel use (Commonwealth of Australia 2011b). Including these agricultural activities under an emissions trading scheme poses a number of challenges, including a lack of cost-effective estimation and monitoring techniques, the need to include thousands of small agricultural emitters and the political challenges involved with imposing a new tax on Australian agriculture (Saddler & King 2008). The Australian Government has instead opted to provide incentives for emissions reductions in agriculture through its $429 million Carbon Farming Futures program (Commonwealth of Australia 2011b). Saddler and King (2008) endorse such a use of incentives to manage agricultural emissions, along with levies on emissions-intensive practices and accreditation standards for agriculture. Accreditation standards could include life-cycle emissions criteria similar to the Roundtable on Sustainable Biofuels standards. Off-road fuel use is one area where a levy could be applied through the fuel excise system to capture emissions from tractors and harvesters.
Extension
Extension measures relevant to the case studies fall into the three broad categories of revegetation, plantations and bioenergy. Catchment Management Authorities (CMAs) have the greatest involvement in extension for revegetation, but have relatively little involvement with agroforestry and even less with bioenergy. Plantation extension activities are largely carried out by plantation companies or by government-industry collaborations such as Plantations2020 and Forest and Wood Products Australia. Bioenergy extension occurs through the peak Australian industry body, Bioenergy Australia, as well as through specific government measures, such as the system of Renewable Energy Coordinators in NSW, which cover six Renewable Energy Precincts across the state (Office of Environment and Heritage 2011).
The integration of revegetation, plantation and bioenergy extension systems is an important pre-requisite for widespread adoption of bioenergy-based agroforestry.
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However, given the major uncertainties that exist with regard to both environmental and economic impacts, it may be premature to commence extension services aimed specifically at bioenergy-based agroforestry. Rather, a more appropriate first step would be to improve communication and information exchange between the government agencies and industry bodies involved in extension across the different sectors. A dedicated forum for collaboration between the different sectors could help to set research priorities and disseminate results amongst key parties. It could also help to break down cultural barriers that may exist, given the divergent agendas of these stakeholder groups at present.
As adoption of bioenergy-based agroforestry increases in the NSW Central West, a regional association along the lines of the Oil Mallee Association in WA, which has a grower base of over 1200 (URS Australia 2009), may be an appropriate vehicle for sharing information, developing industry strategies and participating in research. The Oil Mallee Association, along with the Forest Products Commission of WA, commissioned the 2009 Oil Mallee Industry Development Plan, which lists a number of extension activities, including conferences, education, development of a quality management system and collaborations with regional natural resource management agencies (URS Australia 2009). The Lachlan Renewable Energy Alliance at Condobolin could form the basis of a similar group, but currently suffers from a lack of actual mallee growers and the decision by some of its most active members to form a separate company, MalleeCondo Pty Ltd. There were mixed views in the Condobolin interviews on this development, with some stakeholders seeing the formation of MalleeCondo as a necessary step in the development of a viable industry and others seeing it as a barrier to the free flow of information.
Aside from new, integrative approaches to extension, the case study research identified a number of gaps in existing extension services that could be addressed. One such gap relates to field trials for agroforestry in the Central Tablelands, where sites were set up between 1998 and 2002 but results have not been reliably recorded or distributed. There are also gaps in the NSW Renewable Energy Precinct system, with no precinct covering the Forbes-Condobolin area (Office of Environment and Heritage 2011)
403 despite the fact that MalleeCondo and Delta Electricity are both pursuing bioenergy projects in this region.
Another gap identified in the case study research relates to awareness and understanding around climate change adaption. Hogan et al. (2011) also found that, across Australia, most farmers are yet to adapt their farming practices to a changing climate, with extension having an important role to play in this area. The Department of Climate Change (2010) identifies agriculture as a national priority action area for climate change adaptation and the Department of Agriculture, Fisheries and Forestry (2009, p. 2) has endorsed an extension-based approach that focuses on “providing fundamental information and knowledge, and the decision support tools that will allow farmers and rural industries to manage the risks of climate change”. However, Pannell (2010) suggests that the nature of climate change as slow, highly uncertain and spatially heterogeneous makes it unlikely that extension will produce effective adaptation, with technology change and market reform suggested as alternatives. Scepticism about human-induced climate change in places such as Condobolin could also create resistance around extension projects that are labelled as “climate change adaptation”. A more prudent approach may be to focus on enhancing adaptive capacity more generally, including the ability to adapt to climate variability and shifts in global commodity markets. Based on landholder responses at Condobolin, diversification into mallee-based agroforestry may be seen as a useful risk management strategy that enhances adaptive capacity.
Technology change
Following Pannell (2008), technology change covers policy measures relating to research, development and demonstration aimed at facilitating changes in land management. For the case studies, this covers both bioenergy technology and agroforestry systems. Government support may involve direct agency involvement (e.g. NSW Forests), research grants (e.g. Clean Technology Innovation Program) or indirect incentives, such as the use of carbon pricing to stimulate private investment in research and development. The LRET scheme is designed to support only the least-cost forms of renewable energy at any given point in time, which provides little incentive
404 for research into emerging technologies that may have large future potential but high costs in the short-term (Buckman & Diesendorf 2010). Purpose-grown biomass for bioenergy clearly falls into the high cost/ high potential category, with Figure 8.3 showing how coppiced eucalypt plantations could represent the largest source of biomass for bioenergy in Australia, but have current costs that are substantially higher than for sugarcane bagasse, forest residues or crop stubble.
As discussed under incentives, feed-in tariffs and renewable energy certificate multipliers can be used to incentivise the development of technologies that are not presently least-cost (Buckman & Diesendorf 2010). Thus, apart from their use in promoting multifunctional outputs, these measures could also be used to promote industry investment in research, development and deployment.
Figure 8.3: Cost-supply curve for renewable jet fuel from a range of biomass types. Reproduced from Graham et al. (2011, p. 13)
Research into agroforestry productivity could be funded through existing programs such as Forest and Wood Products Australia and the Rural Industries Research and Development Corporation. Research into the biodiversity, salinity and soil impacts of agroforestry could be funded by existing institutions, such as CMAs or the Caring for Our Country Program. New arrangements under the Australian Government’s Clean Energy Future Program could also fund relevant research and development, but may
405 need to be broadened in scope. The Biodiversity Fund is currently restricted to environmental plantings rather than biodiversity in commercial plantations, the Carbon Farming Futures initiative is focused on soil carbon and the Regional NRM Planning and Climate Change Fund does not mention agroforestry at present (Commonwealth of Australia 2011b).
Broader Institutional Measures
The most significant influence on institutional arrangements affecting bioenergy-based agroforestry in Australia is the division of responsibilities between the Commonwealth and the states. While the Commonwealth has greater financial resources and is able to implement overarching schemes such as the LRET and carbon pricing, the states are generally responsible for regulating energy and land use issues. International agreements such as the Kyoto Protocol also play an important role in setting general policy directions at the national level.
Institutional changes that could assist the development of bioenergy-based agroforestry include enhanced integration across both sectoral and jurisdictional boundaries. The CMAs are a good example of cross-jurisdictional integration, as they receive a substantial portion of their funding, as well as broad policy directions, from the Commonwealth, but are administered by the states, who provide their regulatory powers. CMAs would be well-placed to expand this integrative role around bioenergy- based agroforestry, including certifying plantation sites that contribute to biodiversity, soil protection or salinity mitigation. The involvement of CMAs in plantations policy would also require cross-sectoral cooperation with the Plantations Unit of NSW Trade and Investment, who implement the Plantations and Reafforestation Code. If food security and land use competition issues were to be implemented through a land use planning mechanism, there would need to be enhanced cooperation between CMAs, local councils, the NSW Department of Planning and Infrastructure (responsible for land use planning), the NSW Department of Trade and Investment (responsible for plantations and agriculture) and the Australian Government Department of Climate Change and Energy Efficiency, which oversees the carbon pricing and Carbon Farming Initiative regulations.
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Given the level of cross-jurisdictional integration required to further develop bioenergy-based agroforestry, the Council of Australian Governments (COAG) may be an appropriate vehicle for coordinating new Commonwealth-state arrangements. This could potentially include a new intergovernmental agreement and be linked to the cross-sectoral forum proposed under extension through the inclusion of key landholder groups and industry stakeholders.
No action
Pannell (2008) argues that informed inaction may be an appropriate policy response where: x desirable actions are likely to be adopted without intervention; x undesirable actions are unlikely to be adopted without intervention; or where x the level of public benefit relative to private benefit does not justify intervention
For most of the policy options discussed in this section, current knowledge does not yet justify broad-scale policy intervention, but it also does not yet justify a choice of informed inaction. As policy interventions could have positive or negative effects (e.g. agroforestry could lead to either soil protection or erosion), a precautionary approach is required that delays broad-scale policy intervention until further knowledge is gathered. Adaptive management trials may be used to gather further knowledge while protecting against broad-scale risks. Once further knowledge is obtained, bioenergy- based agroforestry activities can be assessed against Pannell’s three criteria listed above and informed inaction may be selected as a policy choice. Pannell’s (2008) Public: Private Benefits Framework could help to determine whether policy interventions are justified once further trial data has been gathered. However, such policy trials also need to consider whether the environmental benefits delivered by bioenergy-based agroforestry can be appropriately valued in monetary terms, especially if they impact on critical natural capital.
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8.3.3 Selection of policy instruments
The assessment in section 8.3.2 demonstrates that the selection of policy instruments involves more than simple “yes-or-no” decisions. The selection process also involves consideration of whether policy options are ready for immediate implementation, are suited to an adaptive management trial or require further information before a final decision can be made. As such, the recommendations on policy selection presented in this section have been divided into the following four categories:
1. Full implementation: Implementation is warranted based on current knowledge regarding policy effectiveness and ease of implementation 2. Trial implementation: Policy shows promise but full impacts are uncertain or implementation strategies require further development 3. Delay pending further research: Policy shows promise but also poses systemic risks, with a high level of uncertainty 4. No action under current conditions: Policy measure is considered unlikely to contribute to policy goals under current conditions, but should be subject to review as part of an adaptive management process
The policy recommendations for each category are presented in Tables 8.7 to 8.10. These recommendations reflect the assessment of each policy option in section 8.3.2. The tables also identify the key strengths and weaknesses for each option, based on Dovers’ (2005) criteria for implementation and effectiveness.
The policy measures recommended for full implementation (Table 8.7) mostly involve minor changes to existing policies and measures to enhance knowledge and public participation. It is recommended that broad-based land use and plantation regulations be used to protect against environmental threats from energy plantations if and when they expand across NSW. These are considered preferable to bioenergy-specific regulations, as energy cropping does not present a unique threat with regard to land clearing or degradation. Other recommendations are to close gaps in existing extension and research programs to ensure that bioenergy-based agroforestry is considered. These include an audit of previous agroforestry trials in the Central Tablelands, the creation of a NSW Renewable Energy Precinct for Condobolin, an increased focus on
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ways that plantations can help to meet CMA targets and the expansion of programs such as Caring for Our Country and the Biodiversity Fund to provide support for multifunctional plantations. The final recommendation is for a cross-sectoral and cross- jurisdictional forum to further the development of bioenergy-based agroforestry.
Table 8.7: Policy measures recommended for full implementation.
Policy option Policy Type Strengths Weaknesses
Employ broad land use regulations Disincentives Institutional Avoidability, (e.g. Native Vegetation Act) and feasibility, inflexibility, plantations-specific regulations (e.g. equity, complexity, Plantations and Reafforestation systemic monitoring Code) to prevent environmental potential threats from energy plantations.
Address gaps in extension programs: Extension Low Cost, - Audit of past agroforestry trials in complexity, information the Central Tablelands. communicabi needs - Create NSW Renewable Energy lity, equity, Precinct for Condobolin. institutional - CMA guidance on using feasibility plantations to meet NRM targets.
Expand NRM funding programs Technology Equity, Institutional such as Caring for Our Country and change, systemic feasibility, the Biodiversity Fund to incorporate extension and potential cost, commercial plantations with incentives complexity environmental benefits.
Establish a cross-sectoral and cross- Broader Institutional Political jurisdictional forum for bioenergy- institutional feasibility, feasibility based agroforestry to enhance measures, equity, integrated extension and R&D, extension and communicabi potentially linked to the Council of technology lity, systemic Australian Governments (COAG). change potential
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The policy measures recommended for trial implementation (Table 8.8) all show potential for widespread future adoption, but feature high levels of uncertainty and complexity. Incentive programs involving grants or low interest loans represent the simplest option for promoting multifunctional plantations, but would still require trials to better understand the impacts of different plantation types, to develop monitoring regimes and to determine which incentives are likely to be most effective. Similarly, most of the renewable energy incentives discussed in section 8.3.2 would require trials, including the use of multipliers or banding under the NSW biofuel mandates or SRES, differentiated feed-in tariffs for energy crops, upfront provision of renewable energy certificates for energy crops and the creation of a mandate scheme for biomass heat.
The use of renewable energy incentives to promote multifunctional plantations is a new concept for Australia and poses challenges around complexity, information needs and institutional capacity. Multipliers and feed-in tariffs lend themselves to an adaptive management approach, as feedstock eligibility rules and incentive levels can be altered over time as knowledge advances. Despite a lack of second-generation biofuels on the market, multipliers could also be trialled under the NSW biofuel mandates, starting with first-generation biofuels that provide high greenhouse gas savings or other benefits.
As shown in Table 8.8, water use, land use competition and climate change are other policy areas that could benefit from adaptive management trials. The Carbon Farming Initiative and NSW Plantations and Reafforestation Code provide avenues for the development of water licensing rules, including exemptions based on soil, salinity or biodiversity benefits. Strategic Regional Land Use planning in NSW offers a framework for managing land use competition, with its regional nature lending itself to a trial around the integration of energy cropping with existing agriculture. Greenhouse gas emissions from agriculture and forestry could be addressed through an adaptive mix of incentives and levies, rather than the inclusion of these activities under an emissions trading scheme. Finally, trials are recommended that explore how climate change adaptation could be enhanced through a focus on climate variability and broader land use resilience.
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Table 8.8: Policy measures recommended for trial implementation.
Policy option Policy Type Strengths Weaknesses
Trial incentive programs aimed at Incentives Social Cost, efficiency, encouraging multifunctional feasibility, information needs, plantations using a mix of cash grants, equity, monitoring low interest loans and measures to complexity ensure business planning. (i.e. low)
Trial the use of multipliers/banding Incentives Flexibility, Complexity, (e.g. double-counting) for efficiency, information needs, “environmental fuels” and “social equity institutional fuels” under the NSW mandates for feasibility, ethanol and biodiesel. dependability
Amend SRES to trial multipliers for Incentives Flexibility, Information needs, energy crops with environmental or efficiency, institutional social benefits, using salinity equity feasibility, mitigation initially and expanding to complexity, cost climate change adaptation.
Trial differentiated feed-in tariffs for Incentives Efficiency, Institutional energy crops with environmental or and equity feasibility, social benefits, using salinity technology complexity, mitigation initially and expanding to change information needs, climate change adaptation. dependability, cost
Trial upfront renewable energy Incentives Flexibility, Complexity, certificates for multifunctional dependability institutional plantations, with risk mitigation feasibility measures (e.g. buyback).
Introduce a biomass heat mandate, Incentives Equity, Complexity, with multipliers/banding for energy flexibility, institutional crops with environmental or social systemic feasibility benefits. potential
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Policy option Policy Type Strengths Weaknesses
Carbon Farming Initiative: Extend Incentives Equity, Complexity, water licensing exemptions to and extension systemic information needs, commercial plantations with potential, monitoring biodiversity and soil benefits. Also institutional develop methodologies and feasibility guidelines.
Require water licensing for all new Disincentives Equity, Complexity, plantations under NSW Plantations flexibility information needs, and Reafforestation Code, with monitoring exemptions for plantations with biodiversity, soil or salinity benefits.
Adapt the Strategic Regional Land Disincentives Systemic Complexity, Use planning framework in NSW to potential & information needs, ensure food security. This should equity (if all monitoring, consider all land uses (not just land uses), institutional restrictions on energy crops), flexibility & feasibility, social integrated land uses (e.g. Oil Mallee) efficiency (if feasibility and long-term impacts. quotas/offsets used)
Trial a mix of incentives and levies to Incentives Equity, Cost, social reduce emissions in agriculture and and efficiency, feasibility, forestry production (e.g. fertiliser and disincentives political information needs fuel use) through Carbon Farming feasibility Futures and the fuel excise system.
Focus research and extension aimed Technology Flexibility, Complexity, at climate change adaptation towards change and social information needs broader goals relating to climate extension feasibility variability and land use resilience.
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Each trial suggested in Table 8.8 needs to include mechanisms for assessing cost- effectiveness and efficiency. The INFFER system, developed by Pannell et al. (2009), could provide a useful framework for measuring the cost-effectiveness of different approaches and has been used in the development of the Central West CMA’s new catchment plan (Central West Catchment Management Authority 2011). However, other approaches could also be considered, such as the CRITINC framework (Ekins et al. 2003) based on the identification and monitoring of critical natural capital.
Table 8.9 shows policy measures that are recommended for delay pending further research. This category includes measures that show some promise, but could also pose systemic risks that require further analysis or would be premature due to a lack of development around energy cropping in NSW. Providing additional subsidies for biofuels from multifunctional plantations would be premature due to the fact that excise on biofuels is already zero, commercially-viable second-generation fuels are currently lacking and there is ongoing uncertainty around future excise rates. Setting a maximum buyback price for carbon sequestration could provide greater flexibility for landholders, but would also have implications for carbon markets in Australian and internationally. Similarly, the imposition of international sustainability standards on biomass electricity would impose a substantial burden on bioenergy producers without clear evidence that current production poses risks such as poor greenhouse gas balance or negative land use impacts.
The last two measures listed in Table 8.9 relate to extension for multifunctional plantations. The creation of specific extension services for such plantations would be premature, given the level of uncertainty around species, markets and environmental impacts. Similarly, a regional growers association in the Central West is premature due to the lack of growers. However, this situation could change with an increased adoption and knowledge around energy cropping, particularly if governments implement some of the research and extension measures recommended for full implementation and adaptive management measures recommended for trial implementation.
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Table 8.9: Policy measures recommended for delay pending further research.
Policy option Policy Type Strengths Weaknesses
Provide additional subsidies Incentives Efficiency, Cost, political for biofuels certified as a equity feasibility, “social fuel” or “environmental complexity fuel” through the fuel excise system.
Carbon Farming Initiative: Set Incentives Flexibility, Equity, maximum buyback price for social complexity, carbon credits to lower feasibility systemic risks landholder risk and increase flexibility.
Apply international Disincentives Equity, Cost, information sustainability standards (or institutional needs, aspects such as GHG savings feasibility, complexity, benchmarks) to biomass flexibility monitoring, electricity under LRET. systemic risks
Establish extension services Extension Institutional Complexity, aimed at increasing adoption of and social information needs bioenergy-based agroforestry. feasibility, flexibility
Establish regional growers Extension Equity, Social feasibility, association for NSW Central communicabi dependability West. lity, systemic potential
The final category, no action under current conditions, includes measures that are unlikely to be effective or would pose major implementation difficulties (Table 8.10). The development of Managed Investment Schemes (MIS) specifically for bioenergy plantations is not justified, as MIS showed a relatively small benefit in the economic analysis, was seen as risky by some stakeholders and bioenergy plantations would
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qualify for existing MIS arrangements anyway. Biobanking is not considered appropriate for commercial plantations due to the trade-offs required between remnant native vegetation and less complex plantation habitat.
Table 8.10: Policy measures recommended for no action under current conditions.
Policy option Policy Type Strengths Weaknesses
Develop and promote a Managed Incentives Institutional Social Investment Scheme (MIS) feasibility feasibility, framework aimed specifically at dependability bioenergy plantations.
Biodiversity credits made available Incentives Efficiency Complexity, to multifunctional commercial information plantations under the NSW needs, equity Biobanking scheme.
Extend carbon price to emissions Disincentives Equity, Cost, sources in the agriculture and efficiency complexity, forestry sectors. information needs political feasibility
Develop new biofuel/bioenergy Disincentives Social Complexity, standards to prevent inappropriate feasibility enforcement development of energy plantations information in NSW. needs, equity
The inclusion of agricultural emissions under an emissions trading scheme has been listed in Table 8.10 due to the challenges discussed previously, with these emissions dealt with instead through the recommendation to trial a mix of incentives and levies to reduce emissions. Lastly, it is not considered necessary to develop new sustainability standards for biofuels or bioenergy in NSW, as most sustainability risks are already dealt with through existing regulations and international standards are available if
415 import or export is a concern (e.g. adoption of Roundtable on Sustainable Biofuels standard for NSW biofuel mandates).
8.4 Implementation through adaptive management
This stage of the policy framework differs from that of Dovers (2005) in that it combines the implementation of selected policy measures with the implementation of associated monitoring regimes. The need for these two processes to be undertaken in parallel and feed into review is highlighted in Figure 8.4. These processes feed into a review process that is a key part of the adaptive management cycle and may result in changes to implementation and monitoring, as well as revisiting earlier stages of the framework.
Figure 8.4: Processes involved in Stage 4 of the policy framework. 416
Before the policy measures recommended in section 8.3 can be implemented, consideration must be given to appropriate legal and institutional structures, the engagement of key stakeholders in participatory processes and the development of monitoring and review mechanisms. As argued by Diesendorf (2002), this should include a comprehensive effort to reorient the system toward sustainability. The primary focus of this section is on the recommended policy measures that would require the most substantial legal or institutional changes. The implementation strategies discussed here have greatest relevance for Australian Government and NSW Government agencies, as well as CMAs and local government in the NSW Central West. However, there is also a role for environmental and community NGOs and industry organisations, particularly in relation to public participation, extension and research and development.
8.4.1 Policy measures recommended for full implementation
Most of the policy measures recommended for full implementation in section 8.3 already have appropriate institutional and legal structures in place. Some potential areas for improvement include consistency of land use planning across local government and CMA boundaries, as well as more streamlined approval processes for agroforestry. There is a strong argument for further streamlining of approvals under the Plantations and Reafforestation Act 1999 (NSW) for landholders engaging in coppicing (e.g. mallee cropping) on existing farmland, as such activities are unlikely to involve new clearing and coppicing is already exempt from having to submit operational plans for harvesting activities. Such streamlining could also help landholders to view mallee as another cropping option rather than a forestry option involving unfamiliar regulatory requirements.
The recommendation for a cross-sectoral and cross-jurisdictional body to integrate bioenergy, revegetation and plantations policy could be addressed under the auspices of the Council of Australian Governments (COAG). The specific gaps around extension and research highlighted in section 8.3 could be addressed through:
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x The Australian Government Department of Sustainability, Environment, Water, Population and Communities: Inclusion of commercial plantations under the Caring for our Country Program and the Biodiversity Fund; x NSW Trade and Investment: Formation of a renewable energy precinct for the Forbes-Condobolin area and auditing of past agroforestry trials in the Central Tablelands; and x Central West, Lachlan and Hawkesbury-Nepean CMAs: Guidance on aligning plantation development with regional natural resource management objectives.
Monitoring in these instances should focus on the degree to which barriers to agroforestry have been removed and knowledge around agroforestry has increased. Social analysis tools such as interviews and surveys would be appropriate. Environmental monitoring to better understand the impacts of agroforestry is primarily an issue for the next section (measures recommended for trial implementation).
8.4.2 Policy measures recommended for trial implementation
Policy options recommended for trial implementation should be carried out as active adaptive management experiments. Trials could restricted either by geographical area, by participants or by eligible activities. The NSW Central West offers a number of advantages as a trial site due its diversity of landholder types, environmental targets, land use activities, rainfall zones and existing policy measures. However, for some policy options, trials may be more appropriate in areas where bioenergy-based agroforestry is more advanced, such as the wheatbelt of Western Australia, with knowledge then used to develop policy for emerging areas such as the NSW Central West.
Geographically-restricted trials would be appropriate for cash grants and low interest loans aimed at multifunctional plantations. The use of a single CMA area would allow environmental monitoring parameters to be drawn from an existing catchment action plan. To test the hypothesis that conservation through sustainable use can deliver cost- effective restoration of selected ecosystem attributes, non-commercial revegetation projects should be funded and monitored alongside projects involving commercial
418 plantations. The INFFER tool developed by Pannell et al. (2009), including the Public: Private Benefits Framework (Pannell 2008), could assist with this task. INFFER has recently been used to identify key assets by the Central West Catchment Management Authority (2011), making this region a leading candidate for policy trials. However, alternative mechanisms may be required where critical natural capital is involved, as trade-offs between natural and human capital may not be appropriate in such circumsances. Tools such as CRITINC (Ekins et al. 2003) may be able to assist with this task.
A single CMA or Local Government Area would represent an appropriate scale for trials related to Strategic Regional Land Use planning and water licensing for plantations. Collaboration with state and Commonwealth agencies would be required, as CMAs and local councils do not possess regulatory powers over water allocations and have limited control over regional land use planning. While measures to protect food security should ultimately consider all possible land uses in a region, a trial may be more manageable if it begins with a small number of land uses, such as mining, plantations and carbon plantings. Key parameters for monitoring include the degree of change in land use as well as the perceptions of key stakeholders with regards to fairness, transaction costs and impacts on land use flexibility.
Changes to state or federal renewable energy incentives programs would be harder to trial on a regional basis. Experimental economics may provide tools to increase understanding around the behaviour of landholders, plantation managers and energy companies. Trials could also focus on a limited set of eligible feedstocks to avoid major disruptions to markets for biofuels or renewable energy certificates. Multipliers for liquid biofuels (e.g. double-counting) could be trialled under the NSW biofuel mandates, starting with first generation fuels that provide local environmental or social benefits, before expanding to second-generation fuels from agroforestry as they enter the market. Such changes would require amendments to the Biofuels Act 2007 (NSW) and accompanying regulations.
The Australian Government’s Small-scale Renewable Energy Scheme (SRES) provides a better avenue than the Large-scale Renewable Energy Target (LRET) for
419 trialling measures such as multipliers that reward multifunctional plantations or upfront renewable energy certificates that improve plantation viability. This is because the SRES already uses multipliers for small-scale solar, wind and hydro generation and provides credits in advance of actual generation (Office of the Renewable Energy Regulator 2011). It also has a fixed price of $40 for its certificates (Small-scale Technology Certificates or STCs), which avoids the issue of “phantom” generation from a multiplier driving down certificate prices and affecting the viability of other generation sources (Buckman & Diesendorf 2010). Multifunctional bioenergy systems that are fairly well understood, such as Oil Mallee in WA, could be the first to be rewarded with a credit multiplier, followed by other plantation systems as knowledge increases. Any trial of upfront certificates would need to consider provisions for the relinquishing of credits should biomass not be used for bioenergy after harvest.
The major legislative changes that would be required to add multipliers for energy crops under SRES would be to the Renewable Energy (Electricity) Act 2000 (Cth) and the accompanying Renewable Energy (Electricity) Regulations 2001(Cth). Currently, multiplier rates and their expiry dates are specified in the Act, while eligible small- scale generation units are defined by the regulations (currently hydro, wind and solar only). To facilitate trialling of differentiated multipliers in an adaptive fashion, it may be prudent to use the regulations to set multiplier rates rather than the Act, as future amendment of the Act would be more complicated. As well as making bioenergy an eligible generation source under the SRES, consideration would also need to be given to the maximum size of eligible generation units. Changes of this nature would require extensive consultation.
Feed-in tariffs for bioenergy would require implementation at a state level, requiring new legislation and extensive consultation to avoid the boom-bust situation that occurred with the solar feed-in tariff in NSW (Solar Choice 2011). A mandate for renewable heat would be best implemented at the Commonwealth level as a complement to the Renewable Energy Target for electricity.
Any measure to incentivise multifunctional plantations, whether it involves grants, multipliers or feed-in tariffs, would require a certification system to identify those
420 plantations that provide the desired benefits. CMAs, or equivalent regional bodies in other states, would be a sensible choice to administer such a scheme, as they have considerable expertise arising from their existing roles in assessing grant applications and land use plans (e.g. Property Vegetation Plans in NSW). They have already been assigned a similar role in verifying salinity benefits under the Carbon Farming Initiative (Department of Climate Change and Energy Efficiency 2011d). A single CMA could form the basis for a certification trial, with an initial focus on environmental benefits that are relatively well understood, such as mitigation of dryland salinity. Such a certification scheme would be unlike most existing certification schemes for forestry and agriculture, as it would focus on enhancing rather than simply maintaining environmental values.
The other measures recommended for trial implementation in section 8.3 are a mix of incentives and levies for agricultural emissions and new ways to promote climate change adaptation by focusing on climate variability and resilience more broadly. CMAs such as Central West Catchment Management Authority (2011) have already begun to focus on climate change adaptation in this manner and to trial new measures aimed at increasing adaptive capacity. The most appropriate forum to further consider agricultural emissions such as off-road fuel use and fertiliser application is the Multi- Party Climate Change Committee within the Australia Federal Parliament (Commonwealth of Australia 2011b).
8.4.3 Policy measures recommended for delay pending further research
While policies in this category are not recommended for immediate implementation, active monitoring and targeted research are critical to reduce uncertainties. Some of the measures discussed already would be helpful in this regard, such as the establishment of a cross-sectoral research and development body, the inclusion of research into multifunctional plantations under existing grants programs and the auditing of past agroforestry trials in the Central Tablelands. Additionally, monitoring of the diffusion of bioenergy-based agroforestry would be required to determine when targeted extension measures such as a regional growers group may be appropriate.
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With regards to biofuel excise for “environmental fuels” or “social fuels”, two implementation strategies are possible. One involves increasing subsidies under the Ethanol Producers Grant Program and Cleaner Fuels Grants Scheme, while the other involves a comprehensive overhaul of the fuel excise system to provide differentiated excise rates based on energy content of fuels, greenhouse gas emissions and additional environmental or social benefits. This would require extensive consultation, economic modelling and political negotiation. Similarly, amendments to the Carbon Farming Initiative to set a maximum buyback price for sequestration credits would require consultation, modelling of the potential impacts for the Australian carbon market and analysis of implications for global trade in carbon credits.
The application of sustainability standards to the Renewable Energy Target would be relatively easy for energy crops. The regulations already allow the Australian Forestry Standard to be used to demonstrate sustainable plantation management and other standards could be added, such as those of the Forest Stewardship Council. However, as these forestry standards do not include any greenhouse gas benchmarks, an additional requirement may need to be set under the regulations (e.g. 50% emissions savings compared to fossil fuel). Monitoring of the feedstocks currently used for bioenergy in Australia would be required to determine when such changes may be justified.
8.4.4 Policy measures recommended for no action under current conditions
Policies included in this category are considered unlikely to be the most effective or efficient ways of achieving the policy goals outlined in section 8.2. As such, no implementation strategies or targeted monitoring measures are proposed. However, these policy measures should be reconsidered as part of a formal policy review process and potentially moved into a different category as knowledge increases or conditions change.
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8.5 Conclusion
This chapter has demonstrated the applicability of the policy framework developed in Chapter 3 for the case study sites analysed in Chapters 4-7. In addition, many of the recommendations made in this chapter have implications for bioenergy-based agroforestry in other regions of NSW, other states of Australia and, possibly, other countries. The framework itself has the versatility to be applied to a range of different land use options and sustainability issues in different contexts.
While the case study analysis in Chapters 4-7 showed that bioenergy-based agroforestry has the potential to contribute to social and environmental goals in the NSW Central West, a precautionary approach is required due to a combination of pervasive uncertainty, risks of negative plantation impacts and the wide-ranging implications of many policy interventions. As such, very few of the policy measures assessed in this chapter have been recommended for full implementation. Those measures that are recommended for full implementation relate to the protection of important environmental values from inappropriate plantation development, participatory processes for the development of bioenergy-based agroforestry and addressing key gaps in research and extension.
Following an adaptive management and governance approach, several policy options have been recommended for trial implementation. These include covering water licensing and land use planning, which have been recommended in response to the global concerns about competition for land and water between energy crops and other land uses discussed in Chapter 2. Trials have also been recommended to incorporate environmental and social co-benefits into renewable energy incentive programs. This approach represents a novel use of such policy tools in Australia and is aimed at encouraging bioenergy producers to go beyond compliance with government regulations and industry standards. This recognises that sustainability is not just about mitigating threats, but is also about promoting positive change. These policy recommendations draw heavily on the conceptual frameworks discussed in Chapter 3, particularly multifunctionality, conservation through sustainable use and ecological
423 economics. The NSW Central West has many characteristics that make it an appropriate location to trial such measures before they are applied more broadly. As important as it is to identify new policy options that may help to shift rural land use systems towards sustainability, it is equally important to highlight areas where policy intervention is not justified. This may be due to a lack of knowledge, risks of negative impacts or evidence that measures are likely to be ineffective or overly expensive. It is considered unlikely that bioenergy-based agroforestry could be linked effectively to the NSW Biobanking scheme or that new sustainability standards for bioenergy would provide more effective protection of environmental values in NSW than existing policy options. Other measures have been recommended for delay pending further research, particularly extension measures aimed at promoting bioenergy-based agroforestry in the NSW Central West.
While the case study analysis did not show sufficient justification for widespread promotion of energy cropping at present, continued research and policy trials are justified based on the potential for environmental enhancement and the likelihood of future changes in technology and market conditions. Furthermore, the sustainability policy framework followed in this chapter has demonstrated its value as an effective tool for identifying goals, trends and scenarios relating to policy problems, evaluating and selecting policy solutions and developing implementation strategies.
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Chapter 9: Conclusion
Agroforestry for the production of bioenergy remains a potential rather than proven land use option for the NSW Central West, with further research required to establish whether such activities could contribute to regional NRM objectives. However, the case study analysis presented in this thesis provides sufficient preliminary evidence of potential economic, social and environmental benefits to justify further research and policy development in this area. The case study results suggest that bioenergy-based agroforestry could be economically viable under certain conditions and that environmental enhancement could be achieved through appropriate plantation design that incorporates knowledge of how the local ecosystem functions. The case studies also identified a cohort of landholders at both Condobolin and the Central Tablelands who would be interested in bioenergy-based agroforestry that delivered such benefits. While these results provide cause for cautious optimism about future developments in this field, viable agroforestry systems that provide both bioenergy and revegetation outcomes may take many years to emerge, if at all.
As discussed in Chapter 1, Diesendorf (2000, p. 23) defines sustainable development as “types of economic and social development that protect and enhance the natural environment and social equity”. The case study analyses presented in this thesis indicate that bioenergy-based agroforestry in the NSW Central West could, under the right conditions, satisfy Diesendorf’s definition of sustainable development. In order to achieve this, agroforestry systems would need to enhance key environmental values while protecting against environmental risks such as land clearing and exposure of soil to erosive forces. Social equity could be enhanced through agroforestry systems that increase farmers’ economic resilience, provide local jobs and assist with adaptation to climate change, but careful management is also required around competition for land and water resources.
The research presented in this thesis fits within a broader global context in which the goals that underlie bioenergy, agroforestry and revegetation activities can both align and conflict. As discussed in Chapter 2, bioenergy use has been expanding for reasons of energy security and climate change mitigation, but has brought with it a range of
425 social and environmental threats. Many of these threats have also emerged around other forms of plantation development and there have been attempts to develop integrated agroforestry solutions that can maintain and enhance environmental values. This overlap zone between agroforestry and revegetation is a complex area for policy development, as notions of plantation sustainability are generally dominated by ideas of protecting or maintaining key environmental values in the face of threats, while notions of sustainability around revegetation are dominated by environmental enhancement. Combining these two conceptualisations of sustainability is challenging in itself, but the complexity of this task is increased considerably by the addition of bioenergy, which elucidates widely divergent visions of both a renewable resource that enhances sustainability and a rapacious consumer of land that leads to deforestation, dispossession and food insecurity.
Assessing sustainability at the intersection of the revegetation, plantation and bioenergy sectors inevitably requires value-judgments and trade-offs. The social analysis for the two case studies (Chapter 5) highlighted a generally positive view of bioenergy-based agroforestry amongst Condobolin and Central Tablelands landholders. Global concerns around bioenergy, such as deforestation, dispossession or food insecurity did not emerge as major concerns in the case study regions. A goal of protecting food production was expressed by a minority of landholders, but the dominant view, even amongst landholders who were sceptical about bioenergy plantations for other reasons, was that they would not pose major threats at conversion rates of around 5-20% of private farm land. Similarly, concerns about deforestation from bioenergy in Australia tend to focus on the use of native forest residues rather than on energy crops (e.g. The Wilderness Society 2003). However, other types of plantations in Australia have generated concerns around competition for land (e.g. Tonts & Schirmer 2005) and water (e.g. Carbon Farming Initiative). Such concerns may emerge only after plantation development becomes widespread, highlighting the fact that these issues require careful monitoring as expansion occurs.
The two case studies analysed in this thesis suggest that some key factors influencing the development of bioenergy-based agroforestry may be common across regions, while others will vary. The social analysis at both sites confirmed many of the
426 stakeholder views reported in other studies (e.g. Tonts & Schirmer 2005, Williams 2009a, 2009b), including preferences for plantations that occupy only part of a property, are owned by farmers, contribute to environmental objectives and involve local processing and job creation. However, the key barriers were different for the two case study sites, with Condobolin landholders more likely to cite economic factors and Central Tablelands landholders more likely to cite risk of regulatory change. Landholders in NSW have faced significant regulatory change in the past decade through the implementation of the Native Vegetation Act 2003 (NSW). Entering the plantation and bioenergy sectors has the potential to expose them to further regulatory uncertainty, as evidenced by the numerous changes that have been made in Australia to tax rules for forestry Managed Investment Schemes, restrictions on the use of native forest biomass for bioenergy, incentives programs for renewable energy and frameworks for carbon pricing.
The economic analysis in Chapter 6 reinforced many of the concerns identified by landholders around agroforestry, including concerns about the substantial capital investment required and uncertainty about the biomass markets that may be available at the time of harvest. Economic modelling indicated that bioenergy-based agroforestry would not be competitive with typical agriculture at either case study site under the baseline assumptions. However, there were a range of circumstances under which it could be viable. One strategy could revolve around small-scale bioenergy options, such as briquettes, pellets or peak-only electricity generation. These options showed higher returns in the economic modelling and offer advantages of low upfront investment costs and greater trialability. Another potential strategy involves large-scale bioenergy, such as liquid fuels or co-firing with coal. These options could consume existing biomass residues, create demand for purpose-grown biomass, drive prices upwards and increase the likelihood of agroforestry being competitive with typical agriculture. From a landholder perspective, a small-scale strategy is likely to be more effective where landholders are closely involved in the development and ownership of the industry, such as at Condobolin. A large-scale strategy may be the better option for landholders in the Central Tablelands, where there are large existing supplies of cheap biomass and the industry is more likely to be driven by energy companies and wood producers rather than landholders.
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The results of the economic analysis suggest that bioenergy-based agroforestry is closer to being competitive with typical agriculture in the Central Tablelands than it is at Condobolin. The Condobolin model was based exclusively on the coppicing of blue mallee (Eucalytpus polybractea) on 1-2 year harvest cycles, while the Central Tablelands model considered a range of species, including Tasmanian blue gum (E. globulus), sugar gum (E. cladocalyx), flooded gum (E. grandis) and manna gum (E. viminalis) on 5-10 year harvest cycles. The higher predicted biomass yields in the Central Tablelands provide greater revenue and make it easier to recoup establishment costs, which are estimated to be similar between the two sites. However, the Central Tablelands model also carries risks due to the lack of long-term studies on native agroforestry in the region, with the tree measurement field results in Chapter 6 highlighting the risk that actual tree growth may fall well short of model predictions.
Apart from the opportunities that may arise from experimentation with different bioenergy products and silvicultural systems, bioenergy-based agroforestry could also be viable at the case study sites if prices decline for wheat and wool or if adoption efforts are focused on landholders who do not require returns commensurate with typical agriculture. Landholders who said they would accept returns for agroforestry that were lower than those for typical agriculture, or said “depends”, made up 75% of those interviewed at Condobolin and 22% of survey respondents in the Central Tablelands. The reasons cited by these landholders include lower income variability for agroforestry (particularly mallee cropping), environmental co-benefits and the ability to utilise marginal land. Further research is required to determine how widespread these attitudes are, how trade-offs between environmental and economic values would be handled and the extent to which the benefits delivered would represent public, as opposed to private, goods.
The environmental benefits from agroforestry that were most commonly cited in the social analysis were windbreaks (ranked first at both sites), followed by erosion control, habitat for biodiversity, salinity mitigation and carbon sequestration. Windbreaks may be an important private benefit that drives adoption of agroforestry, but the environmental analysis in Chapter 7 suggests that mitigation of dryland salinity,
428 erosion control and carbon sequestration are likely to be the leading public benefits. The fieldwork involving Landscape Function Analysis (LFA) revealed preliminary evidence that appropriate plantation location and design may be able to enhance key soil health factors such as infiltration and nutrient cycling. Salinity mitigation involving commercial plantations was not directly measured for this thesis, but has been the focus of other research work (e.g. Polglase 2007, Central West Catchment Management Authority 2007). Biodiversity conservation appears to be a more speculative option at present, but benefits could be achieved with careful consideration of plantation design factors such as connectivity, proximity to intact vegetation and maintenance of structural diversity (Lindenmayer & Hobbs 2004, Catterall et al. 2005).
Apart from presenting new information on bioenergy-based agroforestry at the case study sites, this thesis also sought to develop and test a framework for the development of sustainability policy. This framework, outlined in Chapter 3 and applied to the case studies in Chapter 8, draws heavily on previous frameworks developed by Dovers (2005), Clark (2002) and Diesendorf (2000). The framework has proved capable of integrating issues across the revegetation, plantation and bioenergy sectors at the regional scale through the identification of goals, exploration of trends and scenarios, selection of policy principles, evaluation of policy options and planning of implementation strategies.
The successful application of the framework to the case studies highlights its potential for further use in other regions where complex issues require integration across multiple sectors. It has also shown how the concepts of multifunctionality, conservation through sustainable use (CSU), adoption theory, ecological economics and resilience thinking can be integrated and pushed beyond their traditional boundaries. This thesis has demonstrated the relevance of multifunctionality for plantation forestry and has shown how these principles can be incorporated into renewable energy policy. It has also shown that CSU principles can be applied not only to “natural” or “wild” ecosystems, but also to cases where vegetation is being established for a combination of commercial and environmental reasons. The relationship between public and private benefits has been critical to the development of policy aimed at landholder adoption. Lastly, the interconnections between the
429 ecological economics notion of critical natural capital and resilience concepts such as thresholds and feedbacks have been influential on the adaptive management approach followed in Chapter 8.
In accordance with the finding that bioenergy-based agroforestry at the case study sites shows potential, but is highly uncertain and subject to significant risks, the key recommendations of this thesis follow an adaptive management approach. This entails few immediate policy changes and relies instead on a number of trials to evaluate the effectiveness of potential policy options. The policy measures recommended for full implementation in Chapter 8 primarily relate to the protection of important environmental values, the collection of new information and the expansion of extension services and participatory processes for key stakeholders. This represents a policy approach that is consistent with the precautionary principle, whereby measures to protect against serious or irreversible harm are required while more speculative opportunities for social, economic and environmental enhancement are explored.
The policy measures recommended for trial implementation in Chapter 8 involve some simple measures aimed at supporting landholders with plantation establishment and more complex measures that involve the adaptation of existing renewable energy incentives to promote multifunctional outcomes. Establishment support, including cash grants and low interest loans, were the most preferred type of policy intervention amongst landholders at both case study sites. Bioenergy incentive schemes, such as the Renewable Energy Target and biofuel mandates, were highlighted more by government and industry representatives than by landholders. While grant schemes may be the simplest and most stable option for landholders, they lack the self-funding characteristics of biofuel mandates or tradable renewable energy certificates and the ability to harness the power of markets to promote efficiency.
The incorporation of local environmental and social co-benefits into renewable energy incentive programs is an idea that has not previously been tested in Australia and has few precedents around the world. In theory, the use of market-based schemes, such as the Renewable Energy Target, could increase efficiency and cost-effectiveness of revegetation activities, but strict verification processes and close monitoring is
430 required. Transaction costs, barriers to entry and the behaviour of key market players could all have a bearing on whether theorised efficiency gains are achieved. Also, while grants or subsidies would most likely be paid by government (beneficiary pays), schemes such as the Renewable Energy Target and NSW biofuel mandates impose costs on the energy industry and ultimately on energy consumers. Opposition to these costs may emerge if the environmental or social objectives appear unrelated to energy use. Thus, a focus on climate change adaptation may be the best way to ensure that the polluter-pays principle is followed, including goals such as connecting habitat, protecting soils against extreme events and increasing the resilience of vulnerable rural communities.
Other measures recommended for trial implementation relate to land use planning and water licensing and are aimed at preventing plantations from causing negative competition impacts. As bioenergy is not alone in contributing to land use competition, a comprehensive planning approach is preferable to measures aimed only at bioenergy, such as regulations or standards restricting bioenergy production to wastes or “idle land” (e.g. Gallagher 2008). Rural land use competition issues have emerged in many regions of Australia as a result of non-bioenergy land uses such as pulpwood plantations (Tonts & Schirmer 2005) and coal and gas development (Department of Planning 2011). The NSW Central West could provide an appropriate setting for regional trials of planning approaches to address these issues, due to its diversity of land use activities, including grazing, cropping, lifestyle/hobby farming, plantation forestry, mining and conservation.
A common theme across all the policy measures recommended in Chapter 8 for either full implementation, trial implementation or delay pending further research is the need for more information on the social, environmental and economic impacts of bioenergy- based agroforestry. The case study research identified a number of key information gaps, which are also likely to exist in other regions. There is a lack of data on the impacts of different forms of agroforestry on key environmental parameters such as biodiversity, salinity, soil erosion and wind speed. Further social data is needed on the attitudes of landholder groups and other stakeholders not reached by the case study research presented here. Economic data around bioenergy and agroforestry is
431 constantly shifting as technologies and markets develop. The adaptive management approach advocated in Chapter 8 is designed to continually improve knowledge in strategic areas while undertaking deliberate policy experiments.
My own journey through this thesis has resulted in significant changes to the way I view sustainability issues arising at the intersection of the revegetation, plantation and bioenergy sectors. As mentioned in Chapter 8, I began with a vision of revegetation as the greatest priority and bioenergy-based agroforestry as a means to that end, heavily influenced by the concept of conservation through sustainable use (CSU). However, by considering in Chapters 2 and 3 the broader context in which these issues reside and undertaking in Chapters 4-7 a wide range of case study analyses, my views have shifted. Other questions have become increasingly important to me, such as how to meet rising demand for energy without exacerbating climate change, how to successfully integrate bioenergy production into rural landscapes alongside the production of food and how to increase socio-economic resilience in regional communities that are subject to ongoing changes in demographics, market conditions and climate. The policy goals, principles and actions recommended in this thesis have been developed to reflect the diversity of social goals identified through the case study research, but they inevitably reflect my own perspectives on how these goals should be prioritised and integrated.
The case study results presented in this thesis may lead some to question whether bioenergy-based agroforestry will ultimately play a significant role in the revegetation of Australia’s degraded and vulnerable rural landscapes, much less a role in meeting the world’s growing demand for energy. Certainly, if economic and social conditions were to remain unchanged, it is hard to see a major expansion of bioenergy-based agroforestry in the NSW Central West. However, these conditions are not static. Australia, and the world more broadly, is rapidly increasing its demand for energy. Bioenergy technologies are advancing in key areas such as second-generation biofuels and electricity generation through gasification. Australia’s plantation estate continues to expand, with new knowledge and efficiencies being gained through experience with short-rotation tree cropping. As the effects of climate change increase, concerns around habitat connectivity and soil protection are likely to grow, along with efforts to reduce
432 or offset greenhouse gas emissions. All of these trends point to a future in which bioenergy, agroforestry and revegetation will increasingly interact in Australia’s rural landscapes and policy frameworks to handle these interactions will be required. This thesis has contributed to the development of such frameworks by outlining a range of scenarios, policy options and information needs, along with a set of recommendations for incorporating these factors into regional adaptive management processes.
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479 Appendix A: Participant Consent Form - Condobolin
Approval No 10 014
PARTICIPANT INFORMATION STATEMENT AND CONSENT FORM
Project title: Mallee plantings for bioenergy: A sustainable land use option for the Condobolin region?
Participant selection and purpose of study You are invited to participate in a study of the viability of commercial plantings of mallee for bioenergy around Condobolin. We hope to learn more about the potentiial costs and benefits of mallee land uses and the barriers to their uptake. You were selected as a possible participant in this study because we want to hear from a various range of stakeholders who may have different perspectives on commercial mallee plantings.
Description of study and risks If you decide to participate, we will conduct an interview with you using a prepared set of questions and also leaving time for additional questions if necessary. You may be contacted later for a follow-up interview or telephone conversation. We will do oour utmost to minimise inconvenience when scheduling and conducting interviews. We will endeavour to schedule the interviews when it is most convenient for you. The interviews shouuld take between 20-30 minutes. With your permission, the interviews will be recorded for transcription purposes (audio only).
Confidentiality Any information that is published from this study will bee provided in such a way that you cannot be identified. Any information that could be identified with you will remain confidential and will be disclosed only with your explicit permission,, except as required by law. If you choose to participate in this research by signing this document, the results will be published in a PhD thesis and possibly future research publicattions (journal articles, conference presentations).
Complaints Complaints may be directed to the Ethics Secretariat, The University of New South Wales, SYDNEY 2052 AUSTRALIA (phone 9385 4234, fax 9385 6648, email [email protected]). Any complaint you make will be investigated promptly and you will be informed out the outcome.
Feedback to participants Upon completion of the thesis or research publication, you will be notifified and you can request to be sent an electronic copy of the thesis/article.
480
Your consent Your decision whether or not to participate will not prejudice your future relations with the University of New South Wales. If you decide to participate, you are free to withdraw your consent and to discontinue participation at any time without prejudice.
If you have any questions, please feel free to ask. If you have any additional questions later, Alex Baumber (PhD candidate, Environmental Policy and Management Program), 0432250548 will be happy to answer them. You will be given a copy of this form to keep.
481
PARTICIPANT INFORMATION STATEMENT AND CONSENT FORM (continued) Mallee plantings for bioenergy: A sustainable land use option for the Condobolin region?
You are making a decision whether or not to participate. Your signature indicates that, having read the information provided above, you have decided to participate.
…………………………………………………… .……………………………………………………. Signature of Research Participant Signature of Witness
…………………………………………………… .……………………………………………………. (Please PRINT name) (Please PRINT name)
…………………………………………………… .……………………………………………………. Date Nature of Witness
REVOCATION OF CONSENT Mallee plantings for bioenergy: A sustainable land use option for the Condobolin region?
I hereby wish to WITHDRAW my consent to participate in the research proposal described above and understand that such withdrawal WILL NOT jeopardise any treatment or my relationship with The University of New South Wales.
…………………………………………………… .……………………………………………………. Signature Date
…………………………………………………… Please PRINT Name
The section for Revocation of Consent should be forwarded to Alex Baumber, Institute of Environmental Studies, Vallentine Annexe UNSW Sydney 2052
482
Appendix B: Participant Consent Form – Central Tablelands
Approvall No 10 014
PARTICIPANT INFORMATION STATEMENT AND CONSENT FORM
Project title: Assessing the potential for new bioenergy agroforestry crops in the NSW central tablelands
Participant selection and purpose of study You are invited to participate in a study of the potential for growing new agroforesttrry crops for bioenergy in the NSW central tablelands. We hope to learn more about the potentiaal costs and benefits of such tree cropping opportunities and the barriers to their uptake. You weere selected as a possible participant in this study because we want to hear from a various range of stakeholders who may have different perspectives on agroforestry and bioenergy.
Description of study and risks If you decide to participate, we will conduct an interview with you using a prepared set of questions aand also leaving time for additional questions if necessary. You may be contacted later for a follow-up interview or telephone coonversation. We will do our utmost tto minimise inconvenience when scheduling and conducting interviews. We will endeavour to schedule the interviews when it is most convenient for you. The interviews should take about 1 to 1.5 hours. With your permission, the interviews will be reecorded for transcription purposes (audio only).
Confidentiality Any information that is published from this study will be provided in such a waay that you cannot be identified. Any information that could be identified with you will remain confidential and will be disclosed only with your explicit permission, except as rrequired by law. If you choose to participate in this research by signing this document, the results will be published in a research report, a PhD thesis and future research publications (journal articles, conference presentations).
Complaints Complaints may be directed to the Ethics Secretariat, The University of New South Wales, SYDNEY 2052 AUSTRALIA (phone 9385 4234, fax 9385 6648, email [email protected]). Any complaint you make will be investigated promptly and you will be informed out the outcome.
Feedback to participants Upon completion of the thesis or research publiication, you will be notified and you can request to be sent an electronic copy of the thesis/articlee.
483
Your consent Your decision whether or not to participate will not prejudice your future relations with the University of New South Wales. If you decide to participate, you are free to withdraw your consent and to discontinue participation at any time without prejudice.
If you have any questions, please feel free to ask. If you have any additional questions later, John Merson (Director, Institute of Environmental Studies, UNSW), 02 9385 4973 will be happy to answer them. You will be given a copy of this form to keep.
484
PARTICIPANT INFORMATION STATEMENT AND CONSENT FORM (continued) Assessing the potential for new bioenergy agroforestry crops in the NSW central tablelands
You are making a decision whether or not to participate. Your signature indicates that, having read the information provided above, you have decided to participate.
…………………………………………………… .……………………………………………………. Signature of Research Participant Signature of Witness
…………………………………………………… .……………………………………………………. (Please PRINT name) (Please PRINT name)
…………………………………………………… .……………………………………………………. Date Nature of Witness
REVOCATION OF CONSENT Assessing the potential for new bioenergy agroforestry crops in the NSW central tablelands
I hereby wish to WITHDRAW my consent to participate in the research proposal described above and understand that such withdrawal WILL NOT jeopardise any treatment or my relationship with The University of New South Wales.
…………………………………………………… .……………………………………………………. Signature Date
…………………………………………………… Please PRINT Name
The section for Revocation of Consent should be forwarded to A/Prof John Merson, Institute of Environmental Studies, Vallentine Annexe UNSW Sydney 2052
485
Appendix C: PRA Interview Sheet – Central Tablelands Aim
Interview questions have been identified based on their potential to: - obtain background information on the informant and/or the district - facilitate learning from past experiences with growing trees, processing tree products or producing energy - gather data that can be used in further analysis - test assumptions (of the research team or of previous research) - identify incentives and barriers for the uptake of bioenergy-based agroforestry - test key informant’s responses to possible visions, actions or policy measures
Method
The interviews will be semi-structured and will take 1-1.5 hours each (check time of the next appointment). Make sure that teams don’t forget to take notes. Begin with: - Tell the interviewee how much time it might take. Ask if it is ok, and let them know they can skip over questions if they don’t feel they have much to say on them. - Give a bit of background on the project (this can be brief as it has already been done to some extent over the phone and the vision will be presented during the interview) - Present and sign Information Consent form.
Questions
Question Sub-group/s Comments
1. About you
Can you tell me a bit about yourself, such as Landholders and Wording may your age, property (business) size, farming business owners vary depending (business) activities, history on the land (in the on nature of business), dependency on land (business) for business/land
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Question Sub-group/s Comments income? use
Why do you own land? How do you use it? What Landholders is the future of how you use your land? What would you like to be able to do with it?
Can you tell me a bit about your organisation’s Govt, community role in the Central Tablelands region and the role groups you perform in the organisation?
What concerns, if any, do you have about the Landholders, Prompt with long-term sustainability of your land/business? business owners examples if need be (climate, regulations, market prices, etc)
What is your experience or exposure to growing All trees – planted or through natural regeneration, both for commercial and non-commercial reasons?
2. About the district
What do you feel are the major environmental All issues in the region?
What do you feel are the major social and All economic issues in the region?
How important is plantation and farm forestry in All the area? How important is tree growing in the
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Question Sub-group/s Comments future?
What do you think needs to happen to improve All the region?
3. Vision for bioenergy-based agroforestry
Interview team will first outline a possible scenario based around plantations of native trees, managed to produce bioenergy and other products and targeted at providing a variety of environmental and social benefits.
Each team will use the script and images to outline this vision.
Do you have any immediate responses to the All scenario?
Are there any potential benefits you can see in All Could prompt the vision we’ve outlined? with “environmental, social or economic benefits”
Are there any potential threats or risks you can All see in the vision we’ve outlined?
What potential barriers could you see for All landholders or industry in getting involved?
If you were interested in taking this up, would Landholders you require the same average annual return as your current land use? Do you have any thoughts on what net return you’d need per hectare per year to take it up?
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Question Sub-group/s Comments
If you were to get involved, how much of your Landholders land would you think about turning over to agroforestry? Which parts of your land would you use and what sort of plantation designs would you prefer (block plantings, belts along fence lines or contours etc)? What would you need to know to make these kinds of decisions
If it were to be successful, how much land would All you like to see converted over to these plantations across the region as a whole? (Is there any amount you think would be too much or any areas where you wouldn’t want to see plantations?)
How do you think bioenergy would fit into an All agroforestry system – for example, would it be the primary product from tree-cropping, a co- product alongside other products or just be produced from the wastes left over from higher- value products?
Assuming the returns and the impacts on the All landscape were the same, would it matter to you what the trees were used for – timber, woodchips, bionergy or anything else?
3. Making the vision a reality
What tree species do you think could work for All bioenergy production in this area? (If they name some, ask: do you know what planting times and
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Question Sub-group/s Comments rotation lengths would be required for these species?)
What kind of support scheme do you think All Prompt with would be most effective in driving uptake? For examples example: - establishment support
- price support for the products or
- payments for ecosystem services such as carbon, biodiversity, salinity
Are there are any other types of biomass that Landholders already exist on your property or in the region that could also be used for a regional bioenergy industry (e.g. existing forestry residues, crop stubble)? If so: - what price would you need to make it worthwhile to collect and sell your biomass sources? - what other markets exist for this biomass at present
What locations in the Central Tablelands do you All think might be good for bioenergy facilities (either power generation or processing into liquid biofuels)?
What existing infrastructure do you think could All be used for this new industry and what new infrastructure would be needed?
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Appendix D: Central Tablelands Landholder Survey
Part 1. About yourself and your farm
What is your gender? Male Female
What is your age? Under 30 30 to 49 50 to 64 65 and over
What area of land do you currently own or manage? Land owned: Acres or Hectares Other land managed: Acres or Hectares
What is the postcode for your property?
What are your current land-uses? Please tick the appropriate box or boxes. You can tick as many as is relevant to your situation. No use Major use Minor use
Commercial Cropping Commercial Horticulture Commercial Forestry Commercial Grazing Intensive animal production (feedlot, kennels, etc) Commercial, not production (B&B, farm stay, etc) Mining and quarrying Lifestyle and hobby farming Conservation of remnant native vegetation Environmental plantings (e.g. revegetated corridors) Indigenous land Other (please specify): Other (please specify):
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What is the productive capability of your land (both owned and managed)? Please estimate the percentage of your land in each category below: Capability Percentage Suitable for regular cultivation Suitable for grazing with occasional cultivation Suitable for grazing only Marginal land (rocky/steep with little grazing value) Land set aside for conservation purposes Other (please specify): Total 100%
To what extent do you agree or disagree with the following statements? Please tick the box that best describes your reaction to each statement. Agree Disagree Undecided Strongly agree Strongly disagree
Farmers have to prioritise making an economic return over improving environmental outcomes Farmers have a responsibility to manage their land to provide benefits for the wider community Farmers should be paid to manage their land to provide benefits for the wider community Human use of fossil fuels is changing the climate The science behind climate change is doubtful Good agricultural land should grow food, not trees Tree planting is more acceptable on marginal land Planting trees should involve native rather than exotic trees
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What is your experience with tree-planting or tree-cropping? I have planted trees for commercial purposes (including trials) What were the aims? Please tick all that How much grew How did you plant the area? apply. successfully? Please tick all that apply. Producing commercial timber None A few scattered trees Trialling timber species Some Long strips of trees Carbon sequestration Most Blocks of trees < 1ha Other (please specify): Blocks of trees > 1ha
I have planted trees for non-commercial purposes What were the aims? Please tick all that How much grew How did you plant the area? apply. successfully? Please tick all that apply. Rehabilitating degraded land None A few scattered trees Improving my property’s looks Some Long strips of trees Increasing birds and animals Most Blocks of trees < 1ha Reducing salinity Blocks of trees > 1ha Other (please specify):
Have you received government funding to help cover the costs of any of these tree plantings, or free materials (e.g. seedlings)? Yes No
Were any of these trees planted and managed by someone other than yourself (e.g. a revegetation or forestry organisation)? Yes No
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Part 2. About agroforestry for bioenergy
The following questions relate to the potential for commercial agroforestry in the region with bioenergy as one of the products produced in the form of either heat or electricity from woody biomass. Bioenergy could be the major product or only produced from wastes and off-cuts. The plantations could be single species or multi- species. They could be short-rotation (harvested every 1-5 years) or longer-rotation (15-30 years). A number of possible species and plantation designs could be used. Incentives could be put in place to overcome some of the obstacles.
To what extent do you agree or disagree with the following statements? Please tick the box that best describes your reaction to each statement.
Agree Disagree Undecided
Agroforestry… Strongly agree Strongly disagree
… protects land and water from erosion … protects land against salinity … has environmental benefits beyond my property … attracts wildlife and birds … improves how my property looks … increases the value of the farm … provides windbreaks and shelter for stock … creates a legacy for my (grand)children … diversifies farm business … acts as a form of superannuation … stores carbon to mitigate climate change … helps adapt to climate change impacts
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What barriers do you see for greater uptake of agroforestry? Please tick the box that best describes your reaction to each statement. Agree Disagree Undecided Strongly agree Strongly disagree
Current land uses offer better returns than agroforestry. The wait for returns from agroforestry is too long. Regulatory changes could prevent future harvest. The capital cost for agroforestry is too high. Agroforestry involves considerable ongoing management. Agroforestry has a negative impact on water availability. I’ve had negative experiences with commercial agroforestry. Agroforestry reduces flexibility for future land use. The labour requirements for agroforestry are too high. Markets and future prices for bioenergy or timber products are too uncertain. I don’t know enough about appropriate species. I don’t have the necessary machinery or expertise on how to grow trees. The risk of pest or disease damage is too high. Agroforestry increases fire risks. Land is unsuitable for commercial plantations. Trees do not establish well here. I don’t like the look or aesthetics of plantations. I already have enough trees on my property. Any other barriers (please describe):
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Part 3. Making the vision a reality
What annual return would you require in order to consider agroforestry? Please tick the appropriate box: The same return as your current land use A greater return than your current land use A lesser return than your current land use It depends (please explain factors)
What net return (income-expenditure) per hectare would be needed to take it up? AU$ per hectare.
If you were to get involved, how much of your land would you think about turning over to agroforestry? Acres or Hectares
If you were to get involved, which parts of your land would you use? Please tick one or more boxes below: Land suitable for regular cultivation Land suitable for grazing and occasional cultivation Land suitable for grazing only Marginal land (rocky/steep with little grazing value) Land set aside for conservation purposes
Would you prefer block or strip plantings? Please tick the appropriate box: Block plantings Strip plantings A combination of both
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How would you implement agroforestry on your property? Please tick the box that best describes your reaction to each statement. Agree Disagree Undecided Strongly agree Strongly disagree
I would select sites where growth-rates of the trees would be highest. I would select sites where the value of my existing use is lowest. I would select sites where access for harvesting is easiest. I would select sites where agroforestry adds value to existing land use (e.g. reduce erosion, salinity). I would select sites where biodiversity benefits were greatest. I would prefer a longer rotation (15-30 years) for higher value products, such as timber. I would prefer a shorter rotation (1-5 years) for lower value products, such as bioenergy. I would prefer a mix of trees with different rotations - some for bioenergy and some for timber. I would commit to agroforestry for 70-100 years if it meant extra income from carbon credits. Other (please specify): Other (please specify):
Assuming the returns and the impacts on the landscape were the same, would it matter to you what the trees were used for (e.g. bioenergy, timber, woodchips, storing carbon)? Yes No If yes, why?
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What kind of support scheme would be most effective in driving uptake? Please tick the box that best describes your reaction to each statement. Agree Disagree Undecided Strongly agree Strongly disagree
Financial support for upfront establishment would be most effective. Price support for products would be most effective. Payments for ecosystem services (e.g. carbon, biodiversity, salinity) would be most effective. Knowledge support for plantation establishment and management would be most effective. Research and development support for bioenergy products would be most effective. Other (please specify): Other (please specify):
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Part 4. About your region
What tree species do you think could work for agoforestry involving bioenergy production in your region?
Do you think that any other sources of biomass in the region could also be used for a bioenergy industry? Yes No If yes, what sources: Residues from existing plantation forestry Residues from native forest harvesting Crop stubble Other (please specify):
What locations in the Central Tablelands do you think might be good for bioenergy facilities (either power generation or processing into biofuels)?
What new infrastructure do you think would be needed for this potential new industry?
Thank you for taking the time to complete this questionnaire. If you wish to add any further comments, please do so below.
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Appendix E: NSW Government Gross Margin Data
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Appendix F: 3-PG Modelling Parameters
Table F-1 lists the species parameters used in 3-PG v2.5 (excel) andTable F-2 lists the site parameters used for the regional estimates (monthly averages) and fieldsite groundtruthing (month-by-month recorded data) in Chapter 6. Table F-3 lists the climate change modifications made to the regional estimates (monthly averages) for the climate change analysis in Chapter 7.
Table F-1: Species parameters used in 3-PG modelling Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx Biomass partitioning and turnover Allometric relationships & partitioning Foliage:stem partitioning ratio @ D=2 cm pFS2 - 1 1 0.7 Foliage:stem partitioning ratio @ D=20 cm pFS20 - 0.15 0.15 0.1 Constant in the stem mass v. diam. relationship aS - 0.095 0.074 0.045 Power in the stem mass v. diam. relationship nS - 2.4 2.68 2.812 Maximum fraction of NPP to roots pRx - 0.8 0.8 0.6 Minimum fraction pRn - 0.25 0.25 0.1
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx of NPP to roots Litterfall & root turnover Maximum litterfall rate gammaFx 1/month 0.027 0.008 0.13 Litterfall rate at t = 0 gammaF0 1/month 0.001 0.001 0.00169 Age at which litterfall rate has median value tgammaF months 12 12 13 Average monthly root turnover rate gammaR 1/month 0.015 0.015 0.025 NPP & conductance modifiers Temperature modifier (fT) Minimum temperature for growth Tmin deg. C 8.5 8 8 Optimum temperature for growth Topt deg. C 16 20 25 Maximum temperature for growth Tmax deg. C 40 40 36 Frost modifier (fFRost) Days production lost per frost day kF days 0 1 1
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx Soil water modifier (fSW) Moisture ratio deficit for f = 0.5 SWconst - 0.7 0.7 0.7 Power of moisture ratio deficit SWpower - 9 9 9 Fertitlity effects Value of 'm' when FR = 0 m0 - 0 0 0 Value of 'fNutr' when FR = 0 fN0 - 1 1 0.6 Power of (1-FR) in 'fNutr' fNn - 0 0 1 Age modifier (fAge) Maximum stand age used in age modifier MaxAge years 50 50 50 Power of relative age in function for fAge nAge - 4 4 4 Relative age to give fAge = 0.5 rAge - 0.95 0.95 0.95 Stem mortality & self-thinning Mortality rate for large t gammaNx %/year 0 0 0 Seedling mortality rate (t = 0) gammaN0 %/year 0 0 0 Age at which tgammaN years 0 0 0
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx mortality rate has median value Shape of mortality response ngammaN - 1 1 1 Max. stem mass per tree @ 1000 trees/hectare wSx1000 kg/tree 300 300 180 Power in self- thinning rule thinPower - 1.5 1.5 1.5 Fraction mean single-tree foliage biomass lost per dead tree mF - 0 0 0 Fraction mean single-tree root biomass lost per dead tree mR - 0.2 0.2 0.2 Fraction mean single-tree stem biomass lost per dead tree mS - 0.2 0.2 0.2 Canopy structure and processes Specific leaf area Specific leaf area at age 0 SLA0 m2/kg 11 4.72 10.5 Specific leaf area for mature leaves SLA1 m2/kg 4 4.72 8 Age at which specific leaf area = tSLA years 2.5 2.5 2.5
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx (SLA0+SLA1)/2 Light interception Extinction coefficient for absorption of PAR by canopy k - 0.5 0.5 0.5 Age at canopy fullCanAg cover e years 0 0 0 Maximum proportion of rainfall evaporated MaxIntcpt from canopy n - 0.15 0.15 0.15 LAI for maximum LAImaxIn rainfall interception tcptn - 0 0 0 Production and respiration Canopy quantum molC/m efficiency alpha olPAR 0.06 0.07 0.068 Ratio NPP/GPP Y - 0.47 0.47 0.47 Conductance Maximum canopy conductance MaxCond m/s 0.02 0.02 0.021 LAI for maximum canopy conductance LAIgcx - 3.33 3.33 3.33 Defines stomatal CoeffCon response to VPD d 1/mBar 0.05 0.05 0.05 Canopy boundary layer conductance BLcond m/s 0.2 0.2 0.2 Wood and stand
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx properties Branch and bark fraction (fracBB) Branch and bark fraction at age 0 fracBB0 - 0.75 0.63 0.3 Branch and bark fraction for mature stands fracBB1 - 0.15 0.42 0.12 Age at which fracBB = (fracBB0+fracBB1) /2 tBB years 2 7 2 Basic Density Minimum basic density - for young trees rhoMin t/m3 0.450 0.6 0.48 Maximum basic density - for older trees rhoMax t/m3 0.450 0.82 0.52 Age at which rho = (rhoMin+rhoMax)/ 2 tRho years 4 4 4 Stem height Constant in the stem height relationship aH - 0 0 0 Power of DBH in the stem height relationship nHB - 0 0 0 Power of stocking nHN - 0 0 0
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Meaning/ E. E. Name Units E. grandis comments globulus cladocalyx in the stem height relationship Stem volume Constant in the stem volume relationship aV - 0 0 0 Power of DBH in the stem volume relationship nVB - 0 0 0 Power of stocking in the stem volume relationship nVN - 0 0 0 Conversion factors Intercept of net v. solar radiation relationship Qa W/m2 -90 -90 -90 Slope of net v. solar radiation relationship Qb - 0.8 0.8 0.8 Molecular weight gDM/m of dry matter gDM_mol ol 24 24 24 Conversion of solar molPAR_ radiation to PAR MJ mol/MJ 2.3 2.3 2.3
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Table F-2: Site parameters used in 3-PG modelling Average Yield Model Field Sites SE SW N Oberon1 Oberon2 Ilford1 Ilford2 Lue1 Lue2 Latitude -33.67 -33.43 -32.6 -33.7 -33.7 -32.85 -32.85 -32.65 -32.65 FR 1 1 1 1 1 1 1 1 1 Soil class CL CL SL SL SL SL SL CL CL Max ASW 300 300 300 300 300 300 300 300 300 Min ASW 0 0 0 0 0 0 0 0 0 Date planted 1988/4 1988/4 1988/4 2000/9 2000/9 2000/9 2000/9 2000/9 2000/9 518 End age 30 30 30 11 11 11 11 11 11 Initial WF 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 Initial WR 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 Initial WS 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 Initial ASW 300 300 300 300 300 300 300 300 300 Initial stocking 1500 1500 1500 1010 990 851 463 344 640 Average monthly conditions for Oberon (Springbank), Bathurst Ag Station & Interpolated climate data from SILO database Climate data Mudgee (George St) (www.longpaddock.qld.gov.au/silo/) www.bom.gov.au/climate/averages
Table F-3: Climate change parameters for 2070 used in 3-PG climate change modelling
Temperature Rainfall (% Solar Radiation Rain Days – over 0 (degrees change change from (% change from mm (change in Frost Days – below 2 degrees from long-term long-term long-term days from long- minimum (% change from long- average) average) average) term average) term average)
A1 A1 A1F A1F B1 B A1FI B1 B I B1 A1B A1FI B1 A1B I B1 A1B A1FI Summer (Dec-Feb) 2 2.5 4 2 2 5 0 0 0 0 0 0 -17 -17 -17 519 Autumn (Mar-May) 2 2.5 4 -5 -5 -10 0 0 0 0 0 0 -17 -17 -17 Winter (Jun-Aug) 1.5 2.5 3 -10 -20 -20 3 4 6 0 0 0 -17 -17 -17 Spring (Sep-Nov) 2 3 4 -15 -20 -20 1 1 2 0 0 0 -17 -17 -17
Appendix G: Treatment of plantation forestry under local environmental plans
Plantation forestry is classed as “restricted” if such activities constitute development that is “prohibited” or “not usually consistent with the objectives of the zone”. Plantation forestry is classed as “permitted” if such activities constitute development that may be carried out either without development consent or with development consent. LEPs include amendments made prior to 21 January 2011.
Bathurst Interim LEP 2005 Zone Permitted/Restricted Zone No 1 (a) (Inner Rural Zone) Permitted Zone No 1 (b) (Market Garden Zone) Permitted Zone No 1 (c) (Rural Residential Zone) Restricted Zone No 1 (d) (Rural Special Purposes Permitted Zone) Zone No 1 (e) (Outer Rural Zone) Permitted Zone No 1 (f) (Special Rural Small Restricted Holdings Zone) Zone No 2 (a) (Residential Zone) Permitted Zone No 2 (v) (Village Zone) Restricted Zone No 3 (a) (General Business Zone) Permitted Zone No 3 (b) (Service Business Zone) Permitted Zone No 4 (a) (Industrial Zone) Restricted Zone No 5 (a) (Special Uses—Public Restricted Purposes Zone) Zone No 6 (a) (Local Recreation Zone) Permitted Zone No 6 (b) (Regional Recreation Zone) Permitted
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Lithgow LEP 1994 Zone Permitted/Restricted Zone No 1 (a) Rural (General) Permitted Zone No 1 (c) Rural (Small holdings) Permitted Zone No 1 (d) Rural (Future urban) Permitted Zone No 1 (e) Outer Rural Permitted Zone No 1 (f) Rural (Forestry) Permitted Zone No 2 (a) Residential Restricted Zone No 2 (v) Village Permitted Zone No 3 Business Restricted Zone No 4 Industrial Restricted Zone No 6 Open space Restricted Zone No 8 National Parks and Nature Restricted Reserves
Mid Western Interim LEP 2008 Zone Permitted/Restricted Low Density Residential Restricted Medium Density Residential Restricted Rural Residential Restricted Village Restricted Agriculture Permitted Intensive Agriculture Permitted Rural Small Holdings Permitted Investigation Permitted Neighbourhood Business Restricted Mixed Use Restricted Commercial Core Restricted Light Industrial Permitted General Industrial Permitted
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Special Uses Restricted Infrastructure Restricted Local Open Space—Public Restricted Local Open Space—Private Restricted Natural Areas Restricted Conservation Permitted
Rylstone LEP 1996 Zone Permitted/Restricted Zone No 1 (a) General Rural Permitted Zone No 1 (c) Rural Small Holdings- Rural Permitted Residential Zone No 1 (c1) Rural Small Holdings- Permitted Rural Retreat Zone No 2 (v) Village or Urban Permitted Zone No 4 (a) Industrial Restricted Zone No 7 (a) Environmental Protection Permitted (Recreation) Zone No 7 (c) Water Catchment Permitted Zone No 8 (a) National Park Restricted
Oberon LEP 1998 Zone Permitted/Restricted Zone No 1 (a) Rural ‘A’ Zone Permitted Zone No 1 (c) Rural ‘C’ Zone Permitted Zone No 1 (d) Non Urban ‘D’ Zone – Restricted Jenolan Caves Reserve Zone No 1 (e) Rural ‘E’ Zone Permitted Zone No 2 (v) Village Zone Permitted Zone No 8 National Parks Zone Restricted
522
Lachlan LEP 1991 Zone Permitted/Restricted Zone No 1 (a) Rural Agriculture Zone Permitted Zone No 1 (c) Rural Small Holdings Zone Permitted Zone No 1 (f) Forests Permitted Zone No 2 (v) Village or Urban Zone Permitted
Forbes LEP 1986 Zone Permitted/Restricted Zone No 1 (a) Rural Zone Permitted Zone No 1 (c) Rural Residential Zone Permitted Zone No 2 (a) Residential Zone Restricted Zone No 2 (b) Special Home Activities Permitted Zone No 2 (v) Village Zone Permitted Zone No 3 (a) Business Zone Permitted Zone No 4 (a) Industrial Zone Permitted Zone No 5 (a) Special Uses (Schools etc) Restricted Zone No 5 (b) Special Uses (Railways) Restricted Zone No 6 (a) Public Open Space Restricted Zone No 6 (b) Private Open Space (Private Restricted Recreation Zone) Zone No 7 Flood Way Restricted
Parkes LEP 1990 Zone Permitted/Restricted Zone No 1 (a) Rural “A” Zone Permitted Zone No 1 (c) Rural Small Holdings Zone Permitted Zone No 1 (f) Rural (Forestry) Zone Permitted Zone No 2 (v) Village or Urban Zone Permitted
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Zone No 4 Industrial Zone Permitted Zone No 4 (a) Industrial “Hub” Zone Permitted Zone No 5 (b) Special Uses (Railways) Restricted Zone No 6 Open Space Permitted Zone No 6 (b) Service Corridor Restricted Zone No 8 National Parks and Nature Restricted Reserves Zone
Bland LEP 1993 Zone Permitted/Restricted Zone No 1 (a) General Rural Zone Permitted Zone No 1 (c) Rural Small Holdings Zone Permitted Zone No 1 (f) Rural (Forestry) Permitted Zone No 2 (v) Village or Urban Zone Permitted
524