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Shifting cultivation in the upland secondary forests of the Philippines: Biodiversity and carbon stock assessment, and ecosystem services trade-offs in land-use decisions Sharif Ahmed Mukul BSc (Hons I), MSc in Forestry, Shahjalal University of Science and Technology MSc in Tropical Forestry and Management, Technische Universität Dresden MSc in Agricultural Development, University of Copenhagen

A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2015 School of Agriculture and Food Sciences Abstract Secondary forest comprises a large area in the tropical region, and it has increasingly believed that the future of tropical forests depends on the effective management of such second growth forests largely modified by human activity. In tropical secondary forests, shifting cultivation, swidden or slash-and-burn is a major land-use that has been attributed to causing large scale deforestation and forest degradation. This view has been embedded in many policy documents, although there are conflicting views within the literature as to the impact of shifting cultivation on secondary forest dynamics. This is largely due to the complex nature of this land-use that makes any generalisation difficult. In the Philippines – a country overwhelmed with rich biodiversity and species endemism, shifting cultivation is locally known as kaingin and represents a dominant land-use in upland rural areas. Although not officially recognised, it has a major contribution to the livelihoods and food security of smallholder rural farmers. After post–logging secondary forests, post–kaingin secondary forests also form the largest group of secondary forests in the Philippines. This thesis based on an empirical study where secondary forest dynamics after shifting cultivation were investigated in an upland area in the Leyte Island, the Philippines. Chapter 2 of my thesis is a synthesis that reports, spatial and temporal distribution of research on shifting cultivation using a systematic literature search protocol, and the key findings of research in conservation biology, plant ecology, soil nutrients and chemistry, and soil physics and hydrology. A bias towards research on anthropology and/or human ecology was found with most research reported from tropical Asia-Pacific region. A great variation in findings on selected forest/environmental parameters was also evident. In Chapter 3, I report a field study where tree diversity, species composition and forest structure and their recovery in secondary forests after shifting cultivation was investigated along a fallow/shifting cultivation land-use gradient. Twenty-five individual sites representing four different fallow categories and old-growth forest as control were surveyed. Tree species richness was significantly higher in the oldest fallow sites while other diversity and forest structure indices were higher in the old-growth forest sites. A homogeneous species composition was found in older fallow sites and in old-growth forest. It was found that secondary forests disturbed by shifting cultivation recovers rapidly in terms of species richness and abundance, and that patch size is a strong predictor of this recovery. Uncertainties in the aboveground biomass carbon in degraded secondary forests after shifting cultivation are one of the main issues hindering its inclusion in the current REDD+ negotiations. In Chapter 4, the distribution and recovery of biomass carbon along a fallow gradient were reported from my study sites. It was found that aboveground total biomass carbon and living ii woody biomass carbon was significantly higher in the old-growth forest sites while coarse dead wood biomass carbon was high in the new fallow sites. The high level of dead wood biomass carbon in new fallow sites was due mainly to high levels of coarse dead wood remaining as an artefact of clearing. Relatively higher biomass carbon recovery in oldest fallow sites than other fallow category with patch size again as an influential factor in explaining the variation in biomass carbon recovery in regenerating secondary forests after shifting cultivation was evident. Shifting cultivation has been linked to an adverse impact on soil carbon and nutrients in the tropical region, albeit different conclusions from the studies. In Chapter 5, the distributions and recovery of soil organic carbon, soil nitrogen, phosphorus and potassium in relation to shifting cultivation use in regenerating secondary forests were examined. Limited influence of shifting cultivation on soil carbon, nitrogen and phosphorus were found, although soil K recovery was low across the sites. Multivariate analysis revealed patch size together with slope and fallow age important in explaining the variation in soil carbon and nutrient recovery in different site categories and soil depths. It has commonly believed that tropical landscapes after shifting cultivation are not suitable for biodiversity and carbon benefits. Drawing on my present study in the Philippines in Chapter 6, I demonstrate that regenerating secondary forests following shifting cultivation have the potential for inclusion in programs on forest conservation under REDD+ and CDM. I argue that regenerating secondary forests after shifting cultivation can be a cost-effective conservation, restoration and forest management option not only in the Philippines but also in other countries where shifting cultivation is prevalent. Overall, my thesis highlights the key biophysical and some policy aspects of shifting cultivation on tropical secondary forest dynamics. My results indicate that regenerating forests after shifting cultivation can act as a low-cost refuge for biodiversity conservation and an important source and sink of carbon that increases with abandonment age. A better understanding of the forest dynamics associated with shifting cultivation land-use, however, is important for the future of tropical forest management and conservation.

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Declaration by author

This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my research higher degree candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis.

Publications during candidature

Peer reviewed papers – lead author

Mukul, S.A., Herbohn, J., Firn, J. (in review) High resilience of tropical forest diversity and structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science. Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. (in review) Soil carbon and nutrients status in relation to shifting cultivation in regenerating secondary forests in the Philippines uplands. Land Degradation & Development. Mukul, S.A., Herbohn, J., Firn, J. (in press) Co-benefits of biodiversity and carbon from regenerating secondary forests in the Philippines uplands: Implications for forest landscape restoration. Biotropica. Mukul, S.A., Herbohn, J., Firn, J. (2016) Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports 6: 22483. Mukul, S.A., Herbohn, J. (2016) The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy 55: 167-177. Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B., Khan, N.A. (2015) Role of non-timber forest products in sustaining forest-based livelihoods and rural households’ resilience capacity in and around protected area: a Bangladesh study. Journal of Environmental Planning and Management DOI: 10.1080/09640568.2015.1035774. Mukul, S.A., Herbohn, J., Rashid, A.Z.M.M., Uddin, M.B. (2014) Comparing the effectiveness of forest law enforcement and economic incentive to prevent illegal logging in Bangladesh. International Forestry Review 16: 363-375. Mukul, S.A., Biswas, S.R., Rashid, A.Z.M.M., Miah, M.D., Uddin, M.B., Kabir, M.E., Khan, N.A., Alamgir, M., Sohel, M.S.I., Chowdhury, M.S.H., Rana, M.P., Khan, M.A.S.A., Rahman, S.A., Hoque, M.A. (2014) A new estimate of carbon in Bangladesh forest ecosystems, with their spatial distribution and REDD+ implication. International Journal of Research on Land- use Sustainability 1: 33-40. Mukul, S.A., Tito, M.R., Munim, S.A. (2014) Can homegardens help save forests in Bangladesh? Domestic biomass fuel consumption patterns and implications for forest conservation in south-central Bangladesh. International Journal of Research on Land-use Sustainability 1: 18-25.

Mukul, S.A., Rana, M.P. (2013) The trade of Bamboo (Graminae) and its secondary products in a regional market of southern Bangladesh: status and socio-economic significance. International Journal of Biodiversity Science, Ecosystem Services & Management 9: 146-154. Mukul, S.A., Rashid, A.Z.M.M., Quazi, S.A., Uddin, M.B., Fox, J. (2012) Local peoples' response to co-management in protected areas: A case study from Satchari National Park, Bangladesh. Forests, Trees and Livelihoods 21: 16-29. Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B. (2012) The role of spiritual beliefs in conserving wildlife species in religious shrines of Bangladesh. Biodiversity 13: 108-114.

Peer reviewed papers – co-author

Pavel, M.A.A., Mukul, S.A.*, Uddin, M.B., Harada, K., Khan, M.A.S.A. (in press) Effects of stand characteristics on tree species richness in and around a conservation area of northeast Bangladesh. Journal of Mountain Science DOI: 10.1007/s11629-015-3501-2. Sohel, M.S.I., Mukul, S.A., Burkhard, B. (2015) Landscape’s capacities to supply ecosystem services in Bangladesh: A mapping assessment for Lawachara National Park. Ecosystem Services 12: 128-135. Alamgir, M., Mukul, S.A.*, Turton, S. (2015) Modelling spatial distribution of critically endangered Asian elephant and Hoolock gibbon in Bangladesh forest ecosystems under a changing climate. Applied Geography 60: 10-19. Sohel, M.S.I., Mukul, S.A., Chicharo, L. (2015) A new ecohydrological approach for ecosystem service provisions and sustainable management of aquatic ecosystems in Bangladesh. Ecohydrology & Hydrobiology 15: 1-12. Chowdhury, M.S.H., Gudmundsson, C., Izumiyama, S., Koike, M., Nazia, N., Rana, M.P., Mukul, S.A., Muhammed, N., Redowan, M. (2014) Community attitudes toward forest conservation programs through collaborative protected area management in Bangladesh. Environment, Development and Sustainability 16: 1235-1252. Rashid, A.Z.M.M., Tunon, H., Khan, N.A., Mukul, S.A. (2014) Commercial cultivation by farmers of medicinal plants in northern Bangladesh. European Journal of Environmental Sciences 4: 60-68. Uddin, M.B., Steinbauer, M.J., Jentsch, A., Mukul, S.A.*, Beierkuhnlein, C. (2013) Do environmental attributes, disturbances, and protection regimes determine the distribution of exotic plant species in Bangladesh forest ecosystem? Forest Ecology and Management 303: 72-80.

Rashid, A.Z.M.M., Craig, D., Mukul, S.A., Khan, N.A. (2013) A journey towards shared governance: status and prospects of collaborative management in the protected areas of Bangladesh. Journal of Forestry Research 24: 599 -605. Al-Mamun, M., Poostforush, M., Mukul, S.A., Parvez, M.K., Subhan, M.A. (2013) Biosorption of As(III) from aqueous solution by Acacia auriculiformis leaves. Scientia Iranica 20: 1871- 1880. Al-Mamun, M., Poostforush, M., Mukul, S.A., Subhan, M.A. (2013) Isotherm and Kinetics of As(III) Uptake from Aqueous Solution by Cinnamomum zeylanicum. Research Journal of Chemical Sciences 3: 34-41. Uddin, M.B., Mukul, S.A.*, Hossain, M.K. (2012) Effects of organic manure on seedling growth and nodulation capabilities of five popular leguminous agroforestry tree components of Bangladesh. Journal of Forest Science 28: 212 -219. Uddin, M.B., Mukul, S.A.* (2012) Ethnomedicianl knowledge of Khasia tribe in Sylhet region, Bangladesh. Indian Journal of Tropical Biodiversity 20: 69-76. * where corresponding author.

Book chapters

Mukul, S.A., Byg, A., Herbohn, J. (in press) Shifting away from swidden? Factors affecting swidden transition in central hill districts of Nepal. In: Cairns, M. (ed) Shifting cultivation policy: trying to get it right, Routledge, London. Mukul, S.A. (2014) Biodiversity conservation and ecosystem functions of traditional agroforestry systems: case study from three tribal communities in and around Lawachara National Park. In: Chowdhury, M.S.H. (ed) Forest conservation in protected areas of Bangladesh: policy and community development perspectives (World Forests Series, Vol. 20), Springer, Switzerland, pp. 171-179.

Conference abstracts

Mukul, S.A., Herbohn, J. (2015) A novel carbon payment scheme for improved livelihoods and better management of swidden fallow secondary forests in the developing tropics, (oral presentation), 1st Annual FLARE (Forests & Livelihoods: Assessment, Research, and Engagement) Network Conference, 27-30 November, Paris, France. Mukul, S.A., Herbohn, J., Firn, J. (2015) Co-benefits of biodiversity and carbon from degraded secondary forests following shifting cultivation in the Philippines: implications for forest vii

restoration and community development, (oral presentation), Small-scale and community forestry and changing nature of forest landscapes, 11-15 October 2015, Sunshine Coast. Mukul, S.A., Herbohn, J. (2015) Divergent estimates of biomass carbon in Southeast Asian rain forests: a Philippines study, (oral presentation), ATBC 2015: resilience of island systems in context of climate change, 12-16 July 2015, Hawaii, USA. Mukul, S.A., Herbohn, J., Firn, J. (2015) Rapid recovery of tree diversity over forest structure in post-kaingin secondary forests in the Philippines, (poster presentation), Student Conference on Conservation Science 2015 (SCCS - Australia), 19-29 January 2015, Brisbane. Mukul, S.A., Herbohn, J. (2014) Biodiversity and ecosystem carbon budget in the upland landscapes following shifting cultivation by small-holder kaingin farmers in the Philippines, (oral presentation), 2014 IUFRO World Congress - sustaining forests, sustaining people, the role of research, 5-11 October 2014, Salt Lake City, USA. Mukul, S.A., Herbohn, J., Firn, J. (2014) Neglecting conservation value of degraded tropical landscapes? tree diversity following shifting cultivation in the upland Philippines (oral presentation), ATBC 2014 - the future of tropical biology and conservation, 20-24 July 2014, Cairns. Mukul, S.A., Herbohn, J. (2013) The future of reforestation programs in the tropical developing countries: insights from the Philippines, (oral presentation), American Geophysical Union Fall Meeting, 9-13 December 2013, San Francisco, USA. Mukul, S.A., Gregorio, N., Baynes, J., Herbohn, J. (2013) The future of reforestation programs in tropical developing countries: insights from the Philippines, (oral presentation), The Australia New Zealand Society for Ecological Economics (ANZSEE) Conference: opportunities for the critical decade, enhancing well-being within planetary boundaries, 11-14 November 2013, Canberra. Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B., Herbohn, J. (2013) Efficacy of forest law enforcement and incentive based conservation to prevent illegal logging in developing countries: experience from Bangladesh, (oral presentation), Earth System Governance Tokyo Conference: complex architectures, multiple agents, 28-31 January 2013, Tokyo, Japan. Mukul, S.A., Herbohn, J. (2012) Linking ethics, ecology and the economics in land-use decisions: towards and integrated approach for global sustainability, (oral presentation), World Conference on Natural Resource Modelling, 9-12 July 2012, Brisbane. Mukul, S.A., Byg, A. (2012) Swidden cultivation in the central hills of Nepal: local perceptions and factors affecting change, (poster presentation), Planet under Pressure – new knowledge towards solutions, 26-29 March 2012, London, UK.

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Publications included in this thesis

I have chosen to incorporate five publications into my thesis as per UQ policy (PPL 4.60.07 Alternative Thesis Format Options). This section details each publication, where it appears in the thesis and contributions to the authorship as per the requirements in the UQ Authorship Policy (PPL 4.20.04 Authorship).

Mukul, S.A., Herbohn, J. (2016) The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy 55: 167-177. – incorporated as Chapter 2. Contributor Statement of contribution Author SA Mukul (Candidate) Conceptualised the framework (90%), and wrote and edited the paper (80%) Author J Herbohn Conceptualised the framework (10%), and wrote and edited the paper (20%)

Mukul, S.A., Herbohn, J., Firn, J. (in review) High resilience of tropical forest diversity and structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science. – incorporated as Chapter 3. Contributor Statement of contribution Author SA Mukul (Candidate) Conceptualised the study (90%), designed and conducted the fieldwork (100%), wrote and edited the paper (80%) Author J Herbohn Conceptualised the framework (5%), and wrote and edited the paper (10%) Author J Firn Conceptualised the framework (5%), and wrote and edited the paper (10%)

Mukul, S.A., Herbohn, J., Firn, J. (2016) Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports 6: 22483. – incorporated as Chapter 4. Contributor Statement of contribution Author SA Mukul (Candidate) Conceptualised the study (90%), designed and conducted the fieldwork (100%), wrote and edited the paper (80%) Author J Herbohn Conceptualised the framework (5%), and wrote and edited the paper (10%) Author J Firn Conceptualised the framework (5%), and wrote and edited the paper (10%)

Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. (in review) Soil carbon and nutrients status in relation to shifting cultivation in regenerating secondary forests in the Philippines uplands. Land Degradation & Development. – incorporated as Chapter 5. Contributor Statement of contribution Author SA Mukul (Candidate) Conceptualised the framework (90%), study design and analyse (100%), wrote and edited the paper (80%) Author J Herbohn Conceptualised the framework (5%), and wrote and edited the paper (5%) Author J Firn Conceptualised the framework (5%), and wrote and edited the paper (5%) Author A Almendras-Ferraren Wrote and edited the paper (5%) Author R Congdon Wrote and edited the paper (5%)

Mukul, S.A., Herbohn, J., Firn, J. (in press) Co-benefits of biodiversity and carbon from regenerating secondary forests in the Philippines uplands: Implications for forest landscape restoration. Biotropica. – incorporated as Chapter 6. Contributor Statement of contribution Author SA Mukul (Candidate) Conceptualised the framework (90%), study design and analyse (90%), wrote and edited the paper (80%) Author J Herbohn Conceptualised the framework (5%), study design and analyse (10%), and wrote and edited the paper (10%) Author J Firn Conceptualised the framework (5%), and wrote and edited the paper (10%)

Contributions by others to the thesis

Along with my principal supervisor Professor John Herbohn and co-supervisor Associate Professor Jennifer Firn, Professor Angela Ferraren and Dr Robert Congdon provided inputs in the Chapter 6. Dr Jefferson Fox provided thoughtful comments on an earlier draft of the Chapter 2, and Professors Robin Chazdon and David Lamb provided comments on earlier drafts of the Chapter 3 and 4 of this thesis.

Chapter 1and 7, the overall thesis introduction and overall conclusion, were written by myself with editorial input from my principal supervisor, Professor John Herbohn.

All other significant contribution and inputs by others are provided above for each published, accepted and submitted papers that are currently under consideration for publication.

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Statement of parts of the thesis submitted to qualify for the award of another degree

None.

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Acknowledgements

I am very much grateful to my principal advisor, Professor John Herbohn (UQ/USC) and co- advisor, Associate Professor Jennifer Firn (QUT) for their valuable guidance, feedback and suggestions which made this work possible. I would also like to thank Drs Nestor Gregorio (USC), Arturo Pasa (VSU) and VSU-ACIAR field staffs in the Philippines, particularly – Nayar Adanarg, Val Solano, Jun Ray and Cris Solano for their heartiest cooperation during my fieldwork in the Philippines. Thanks also due to Professors Angela Ferraen (VSU) and Robert Congdon (JCU) for the lab facility in the Philippines, and Ofelia Manarnguit, Jertz Escala for assistance in laboratory analysis. The valuable suggestions and feedback provided by Professors Robin Chazdon (UConn), David Lamb (UQ/USC), L.A. Bruinjeel (VU Amsterdam), Susanne Schimdt (UQ), Vera Lex Engel (UNESP), Stephen Harrison (UQ/USC), Jerry Vanclay (SCU), Associate Professors Wolfram Dressler (U Melbourne), Drs Jefferson Fox (EWC), Jack Baynes (USC), Paul Dargusch (UQ), John Meadows (USC) at different stages of this project was very helpful. During my several visits and stay in the Philippines from 2012 (June) and 2013 (February, June-October) several co-workers, including – Jun Zhang, Jarrah Wills and Chloe Gudmundsson who were working at the same time for their graduate projects made my stay and work there very enjoyable, together with other VSU-ACIAR project staffs – Ian Kim Gahoy, Mayet Avela, Rogelio Tripoli, Nova Parcia and Jufamar Fernandez. Thanks also to Shawkat Sohel for his help in part of thesis formatting. Throughout my doctoral training and study period at UQ my parents and younger brother inspired and motivated me a lot to reach my desired destination. This work is being made possible by a scholarship support (International Postgraduate Research Scholarship) from the Australian Government, with additional funding towards field activity from the Australian Centre for International Agricultural Research (ACIAR- ASEM/2010/50).

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Dedication

This thesis is dedicated to the memory of my father Mostaque Ahmed (1955-2016) who left us on January 17, 2016.

Keywords tropical forest, kaingin, deforestation, biodiversity conservation, forest carbon stock, land-use change, REDD+, reforestation, Southeast Asia

Australian and New Zealand Standard Research Classifications (ANZSRC) ANZSRC code: 050205, Environmental Management, 60% ANZSRC code: 050209, Natural Resource Management, 20% ANZSRC code: 070504, Forestry Management and Environment, 20%

Fields of Research (FoR) Classification FoR code: 0502, Environmental Science and Management, 90% FoR code: 1605, Policy and Administration, 10%

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Table of Contents

Chapter 1. Introduction 1 1.1 Background 1 1.2 Research problem and the research questions 3 1.3 Justification of this research 6 1.4 Methodology 8 1.5 Limitations and challenges 10 1.6 Overview of this thesis 10 1.7 References 11

Chapter 2. The impacts of shifting cultivation on secondary forests dynamics in tropics: 16 a synthesis of the key findings and spatio temporal distribution of research 2.1 Abstract 16 2.2 Introduction 17 2.3 Methodology 18 2.3.1 Document search for systematic map 18 2.3.2 Document characterization 19 2.3.3 Document selection for meta-analysis 19 2.3.4 Data interpretation and analysis 20 2.4 Results and discussions 20 2.4.1 Spatio-temporal dynamics of research on shifting cultivation 20 i. Spatial distribution of research on shifting cultivation 20 ii. Temporal pattern of research on shifting cultivation 22 2.4.2 Impacts of shifting cultivation on tropical forest dynamics 22 i. Plant ecology 26 ii. Conservation biology 27 iii. Soil nutrients and chemistry 28 iv. Soil physics and hydrology 29 2.5 Conclusions 29 2.6 Additional information 30 2.7 References 30

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Chapter 3. High resilience of tropical forest diversity and structure after shifting 43 cultivation in the Philippines uplands 3.1 Abstract 43 3.2 Introduction 43 3.3 Materials and methods 45 3.3.1 Study area 45 3.3.2 Site selection criteria 47 3.3.3 Sampling protocol and vegetation survey 47 3.3.4 Site environmental parameters 48 3.3.5 Diversity and forest structure indices 49 3.3.6 Species composition and similarities 49 3.3.7 Recovery of tree species diversity and forest structure 50 3.3.8 Data analysis 50 3.4 Results 51 3.4.1 Species and characteristics 51 3.4.2 Biodiversity and forest structure in regenerating secondary forests 52 3.4.3 Species composition in regenerating secondary forests after shifting cultivation 53 3.4.4 Tree diversity and forest structure recovery along a shifting cultivation fallow 55 gradient 3.4.5 Environmental controls on the recovery of secondary forest diversity and structure 56 3.5 Discussion 58 3.5.1 Biodiversity conservation and secondary forest development after shifting 58 cultivation 3.5.2 Controls of site environmental conditions in forest recovery after shifting cultivation 60 3.5.3 Implications for conservation and forest landscape management 61 3.6 Conclusions 61 3.7 Additional information 62 3.8 References 62

Chapter 4. Tropical secondary forests regenerating after shifting cultivation in the 76 Philippines uplands are important carbon sinks 4.1 Abstract 76 4.2 Introduction 76 4.3 Methods 78

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4.3.1 Study area 78 4.3.2 Site selection 79 4.3.3 Biomass inventory 80 4.3.4 Biomass calculation in forest ecosystems 81 4.3.5 Estimating carbon in aboveground forest biomass 82 4.3.6 Estimating the recovery of biomass carbon in forests 83 4.3.7 Statistical analysis 83 4.4 Results 84 4.4.1 Distribution of biomass carbon in fallow secondary forests 84 4.4.2 Recovery of biomass carbon in fallow secondary forests 88 4.4.3 Factors influencing the recovery of aboveground biomass carbon in fallow secondary 89 forests 4.5 Discussion 91 4.5.1 Biomass carbon distribution in tropical fallow secondary forests 91 4.5.2 Factors influencing the biomass carbon recovery in fallow secondary forests 92 4.5.3 Forest management and landscape restoration implications 94 4.6 Conclusions 94 4.7 Additional information 95 4.8 References 95

Chapter 5. Soil carbon and nutrients status in relation to shifting cultivation in 102 regenerating secondary forests in the Philippines uplands 5.1 Abstract 102 5.2 Introduction 102 5.3 Materials and methods 104 5.3.1 Study location 104 5.3.2 Site selection and characteristics 104 5.3.3 Soil sample collection 106 5.3.4 Soil sample processing 105 5.3.5 Statistical analysis 107 5.4 Results 108 5.4.1 Soil carbon and nutrients concentrations across a fallow gradient 108 5.4.2 Availability of soil carbon and nutrients along a fallow age gradient 110 5.4.3 Environmental controls on soil carbon and nutrients in fallow sites 112

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5.5 Discussion 114 5.5.1 Variability in soil carbon and nutrients in fallow secondary forests 114 5.5.2 Influence of site environmental factors on soil carbon and nutrients 114 5.6 Conclusions 115 5.7 Additional information 116 5.8 References 116

Chapter 6. Co-benefits of biodiversity and carbon from regenerating secondary forests 123 in the Philippines uplands: implications for forest landscape restoration 6.1 Abstract 123 6.2 Introduction 123 6.3 Methods 125 6.3.1 Background of the area 125 6.3.2 Study site selection 127 6.3.3 Data collection 127 6.3.4 Data interpretation and analysis 127 6.4 Results 128 6.4.1 Biodiversity and carbon co-benefits from regenerating secondary forests 128 6.4.2 Biodiversity and carbon trade-offs in the upland land-use of Philippines 129 6.5 Discussion and implications 130 6.6 References 132

Chapter 7. General conclusions 138 7.1 The context 138 7.2 A synthesis of the impacts of shifting cultivation on tropical forests dynamics 138 7.3 The impact of shifting cultivation on biodiversity, species composition and forest 139 structure 7.4 Aboveground biomass carbon dynamics in regenerating tropical secondary forests 139 7.5 Soil carbon and nutrients in regenerating secondary forests after shifting cultivation 140 7.6 Opportunities for biodiversity and carbon benefits from fallow secondary forests 140 7.7 Implications of this research 140 7.8 References 141

Annexes Annex 2.1. Summary of studies used in meta-analysis on impacts of shifting cultivation on 39 forest dynamics. Annex 3.1. List of tree species recorded from the sites in Gaas on Leyte Island, the 71 Philippines. Annex 4.1. Summary of aboveground biomass carbon distribution in our study sites on 101 Leyte Island, the Philippines.

Appendices 143 Supplmentary Figure 2.1. Country-wise distribution of research on shifting cultivation. 143 Supplementary Table 3.1. Different measures for diversity and forest structure used in 144 the present study. Supplementary Table 3.2. Pearson correlation between site environmental attributes. 145 Supplementary Figure 3.1. Importance value of species across the sites of different 146 fallow categories and in control old-growth forest. Supplementary Figure 3.2. nMDS of richness and abundance of species of global 147 conservation concern using Bray-Curtis distance. Supplementary Figure 3.3. nMDS of richness and abundance of species of local 148 conservation concern using Bray-Curtis distance. Supplementary Table 4.1. Site environmental attributes. 149 Supplementary Table 4.2. Wood density and characteristics of species recorded from the 150 sites on Leyte Island, the Philippines. Supplementary Table 4.3. Organic carbon contents in litter and undergrowth samples 154 from the study sites on Leyte island, the Philippines. Supplementary Table 4.4. Organic carbon contents in dead wood samples from the study 155 sites in Leyte Island, the Philippines. Supplementary Table 4.5. Pearson correlation between site environmental attributes. 156 Supplementary Table 4.6. Biomass carbon distribution in living woody species in our 157 study sites on Leyte island, the Philippines. Supplementary Figure 4.1. Relative contribution of living stems of different diameter 162 class in living woody biomass carbon (LWBC). Supplementary Figure 4.2. Relative contribution of living stems of different height class 163 in living woody biomass carbon (LWBC). Supplementary Table 5.1. Pearson’s correlation between site environmental attributes. 164

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Supplementary Figure 5.1. Percentage concentrations of soil organic carbon and soil 165 nutrients on Leyte Island, the Philippines.

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List of Figures

Figure 1.1. Conceptual framework of this thesis project. 4 Figure 1.2. The background, importance and potential implications of this project. 7 Figure 1.3. Outline of the chapters in this thesis. 11 Figure 2.1. Summary of literature used for systematic map and meta-analysis. 21 Figure 2.2. Geographical distribution of the studies on shifting cultivation by country. 23 Figure 2.3. Temporal changes in research focus between 1950-2014. 24 Figure 2.4. Reported effect of shifting cultivation on (a) major forest characteristics; (b) 25 selected wildlife selected taxa, (c) major soil nutrients and (d) soil physical and hydraulic properties. Figure 3.1. Map showing location of the study area on Leyte Island, and the study sites 46 plotted in a Google Earth map showing the location of the 25 sites. Figure 3.2. Distribution and characteristics of species in different fallow categories and in 51 old-growth forest on Leyte Island, the Philippines. Figure 3.3. Within and between variations of tree diversity and forest structure indices across 52 the sites on Leyte Island, the Philippines. Figure 3.4. nMDS of species richness and abundance using Bray-Curtis distance. 55 Figure 3.5. Recovery of tree diversity and forest structure in relation to old-growth forest on 56 Leyte Island, the Philippines. Figure 4.1. Map of the Philippines, with location map of Barangay Gaas on Leyte Island and 79 our study sites in Gaas. Figure 4.2. Distribution of aboveground biomass carbon in our study sites on Leyte Island, 85 the Philippines. Figure 4.3. Relative contribution of different source to the total aboveground biomass carbon 86 stock in our sites on Leyte Island, the Philippines. Figure 4.4. Relative importance of different successional species groups in living woody 87 biomass carbon (LWBC); and species of different origin in LWBC. Figure 4.5. Relative importance of coarse dead wood of different stand form in coarse dead 87 wood biomass carbon (CDWBC); and dead woods of different degradation status in CDWBC. Figure 4.6. Distribution of aboveground biomass carbon in fallow secondary forest sites in 89 relation to the old-growth forests on Leyte Island, the Philippines. Figure 5.1. Location map of the study area on Leyte Island, and the study sites plotted on a 105

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Google earthTM map. Figure 5.2. The relative contribution of soil organic carbon and nutrients at different soil 110 depths in our sites on Leyte Island, the Philippines. Figure 5.3. Soil carbon and nutrients in relation to control old-growth forests at our study 111 sites on Leyte Island, the Philippines. Figure 6.1. Major land-use/land-cover in the Philippines with the location of Leyte Island 125 indicated, and some common land-use in the upland areas after shifting cultivation use. Figure 6.2. Tree biodiversity in regenerating forest after shifting cultivation in the Philippines 128 uplands. Figure 6.3. Above ground biomass carbon in regenerating forest following shifting 128 cultivation in the upland Philippines.

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List of Tables

Table 1.1. Summary of the samples and measurements taken from the study sites in the 8 Philippines. Table 1.2. Research matrix used for this project. 9 Table 2.1. Example of documents under different subject focus. 19 Table 3.1. Environmental attributes of our fallow sites and old-growth forest on Leyte Island, 49 the Philippines. Table 3.2. Top ten species with highest importance value in sites of different fallow 53 categories and in old-growth forest on Leyte Island, the Philippines. Table 3.3. Summary of mixed effect models obtained using package MuMin. 57 Table 3.4. The relative importance of site environmental attributes in the final LMEM. 58 Table 4.1. Summary of LMEM between site biomass recovery with environmental attributes 90 obtained using the package MuMin. Table 4.2. The relative importance of site environmental attributes in the final LMEM. 90 Table 5.1. Environmental attributes of the study sites on Leyte Island, the Philippines. 106 Table 5.2. Concentrations of soil organic carbon and nutrients across the sites of different 109 fallow categories and old-growth forest on Leyte Island, the Philippines. Table 5.3. Summary of LMEM between soil carbon and nutrient recovery with 112 environmental attributes obtained using the package. Table 5.4. The relative importance of site environmental attributes in the final LMEM. 113 Table 6.1. Biodiversity and aboveground carbon stocks in common upland land-cover/use in 131 the Philippines uplands.

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List of Abbreviations

AGB Aboveground Biomass CBNRM Community Based Natural Resource Management CDM Clean Development Mechanism DENR Department of Environment and Natural Resources IPCC Intergovernmental Panel on Climate Change IUCN International Union for Conservation of Nature NGP National Greening Program REDD+ Reducing Emissions from Deforestation and Forest Degradation SOC Soil Organic Carbon

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CHAPTER 1: INTRODUCTION

1.1 Background Tropical forests provide services that are essential for society and human wellbeing, including biodiversity, timber, water, and carbon sequestration (Lewis et al., 2015). The future capability of forests to provide these ecosystem services is determined by changes in land-use, socio-economic context, biodiversity and climate (Trumbore et al., 2015; Malhi et al., 2014; Metzger et al., 2006). In tropical secondary forests, shifting cultivation, also termed as swidden or slash-and-burn agriculture, is one of the dominant land-uses in upland areas, and has long been considered as one of the main drivers of deforestation and forest degradation (Ziegler et al., 2011; Mertz et al., 2009; Fox et al., 2000). Shifting cultivation was the dominant form of agriculture in most tropical areas until the end of the 20th century, when the political and economic integration at many geographic locations promoted more intensive agriculture (Lawrence et al., 2010; Fox et al., 2009). A large proportion of tropical secondary forests have been subjected to shifting cultivation (Angelsen, 1995), and in many parts of the tropics this practice is now evolving into other more intensive land-uses like rubber, oil palm plantations and sedentary agriculture etc. (see Mukul and Herbohn, 2016; Fox et al., 2014; van Vliet et al., 2012; Padoch et al., 2007; Mertz et al., 2009). In recent years, while shifting cultivation has declined, in many developing countries, it still remains a major means of livelihoods and food security of poorest people living in rural remote landscapes (Parrota et al., 2012; van Vliet et al., 2012; Cramb et al., 2009).

Shifting cultivation typically involves the clearing of the forest by a combination of cutting and subsequent burning of vegetation; the cleared area is then used for cultivation of agricultural crops which was formerly forested land for two to three years (Cairns, 2015). Shifting cultivation farmers then move to another piece of land allowing former land a fallow period to regenerate naturally (Fox et al., 2000). In mountainous areas in many countries of mainland Southeast Asia, shifting cultivation system is still essential for livelihoods and food security (Ziegler et al., 2012; Brunn et al., 2009). Without sufficient empirically based evidence, for decades policy makers and some scientists have believed that shifting cultivation is environmentally unsustainable and one of the major reasons of land degradation (Mertz et al., 2012, 2009; Ziegler et al., 2011; Bruun et al., 2009; Fox et al., 2009).

The Philippines have experienced one of the highest rates of deforestation in Southeast Asia (Lasco and Pullhin, 2009; Chokkalingam et al., 2006). The Philippines is also one of the first countries to 1 introduce massive reforestation programs to restore its degraded forests, landscapes and associated environmental parameters in upland areas (Chokkalingam et al., 2006). The country is one of the ‘hottest of the biodiversity hotspots’, endowed with a vast variety of endemic flora and fauna, many of which are currently under different level of threats (Sodhi et al., 2010; Suarez and Sajise, 2010; Posa et al., 2008). Until the early colonizers arrived in the country in the 16th century, about 90 percent of the Philippines were covered with dipterocarp rich rainforests, which have now reduced to less than 24 percent (Lasco and Pullhin, 2000). Characteristically, upland rural areas in the Philippines are less developed, inhabited by smallholder poor farmers who rely on neighbouring forests for sustaining livelihoods (Herbohn et al., 2014; Le et al., 2014). The majority of the smallholder farmers in rural, remote upland areas practice shifting cultivation, locally termed as kaingin (Lawrence, 1997; Kummer, 1992). Since the Spanish colonial period (i.e. AD1565-AD 1898) major forestry policies in the Philippines tried to impose restriction on this land use practice, assuming a negative impact on upland forests and environment (Suarez and Sajise, 2010). Major reforestation projects in the Philippines also ignored this major land-use, with still very limited understanding the consequences of kaingin on the local environment (Suarez and Sajise, 2010). In upland areas, smallholder kaingin farmers are also vulnerable to environmental changes due to their dependence on forests with very limited access to other natural resources, and kaingin will continue to form an important land-use in the country until greater access to state regulated forestry and other land-use programs, and economic development will take place (Mukul and Herbohn, 2013; Harrison et al., 2004).

Lack of knowledge on biodiversity and biomass carbon and their recovery in shifting cultivation landscapes is one of the major constraints to incorporating this land-use in global voluntary carbon markets under REDD+ (Reducing Emissions from Deforestation and Forest Degradation) and CDM (Clean Development Mechanism) (Parrota et al., 2012; Mertz et al., 2012, Mertz, 2009; Ziegler et al., 2012). Recently, Martin et al. (2013) and Bonner et al. (2013) in their meta-analyses found that secondary forests after disturbances can act as a low-cost measure for conserving biodiversity and forest biomass carbon and hold great potentials for tropical forest restoration. In the Philippines, post-kaingin secondary forests, due to their vast area also have the potentials for carbon / biodiversity offset projects under REDD+ and CDM, and to attract funds to protect and conserve country’s forests with greater community involvement (Lasco and Pulhin, 2003; Lasco et al., 2001). Such project and activities however require better understanding of the biodiversity and carbon dynamics associated with related land-use(s) (Budiharta et al., 2014; Niels et al., 2002).

In case of the shifting cultivation there has been a great variability among findings from studies focusing on ecology and successional development of forests, with studies finding different fallow lengths are required for forest to return its earlier condition, with also different level of impacts on forests and related environmental parameters (Mukul and Herbohn, 2016; Bruun et al., 2009). Against theses backdrops, my thesis sheds light on secondary forest dynamics after shifting cultivation in the Philippines uplands, with this research having important implications for land-use policy and development in the country.

1.2 Research problem and the research questions I hypothesized that secondary forests after shifting cultivation involves major trade-offs in biodiversity and carbon storage when considering potential competing land-uses like natural regeneration, reforestation (native vs. exotic, single vs. mixed species, etc.), invasion by grasslands or conversion to sedentary agricultural field. The conceptual framework of this hypothesis is outlined in Figure 1.1. In my thesis I only considered natural regeneration due to time constraints. To test the hypothesis and to address the existing gaps and inconsistency in research findings (on shifting cultivation) the following research problem was developed.

Research problem:

To what extent do tree diversity, species composition, forest structure, biomass carbon and

soil nutrients recover following shifting cultivation, and what are the implications for land-

use policy development?

Since shifting cultivation is not only a dominant land-use in the tropics, but also a survival strategy for millions of marginal and rural people dwelling in either upland hilly or mountainous areas (van Vliet et al., 2012), the research problem has implications not only in the Philippines but in other developing countries where shifting cultivation is common. Again, in the upland Philippines, a large-scale donor funded reforestation programs known as – National Greening Program (NGP) currently being implemented, which has the objective to restore 1.5 million hectares of degraded upland forests by 2016 (Le et al., 2014).

Understanding biodiversity and carbon stock and any recognized pattern in recovery after kaingin is important to realize any opportunities the large amount of secondary forests in the upland areas may

Primary Forest Features Features *Remote area *Indigenous communities *Proper area/closer to road networks *Low population pressure *Immigration/Migrants from lowlands *Emigration for better livelihood *High population pressure Slash-and-burn/ *Land scarcity Forest degradation

Traditional Shifting Cultivation Intensive Shifting Cultivation

/ Carbon Loss Carbon / Long fallow period Fallow cycle Short fallow period Fallow cycle

Fallow Land Fallow Land

Biodiversity Intact forest patches

Intact forest Disturbance/ Natural Reforestation/ Settlement Invasion succession Restoration

Grass Land Secondary Forest Planted Forest Agricultural Crop Field

Whole landscape Disturbed forest patches Degraded landscape/forests Biodiversity / Carbon Trade-offs

Figure 1.1. Conceptual framework of this thesis project. 4 have for REDD+ or other CDM, which may also complement or boost the current NGP or any other projects in the future on upland secondary forests.

Other than the literature review, synthesis and gap analysis that comprise the second chapter of this thesis, four research questions were constructed to address the research problem stated above. The first research question aimed to examine the conservation value of secondary forests regenerating after shifting cultivation in the Philippines upland.

Research question 1: To what extent regenerating kaingin fallow forests complement the old-growth forest in

terms of biodiversity and forest structure?

General background and context of this research question is discussed in later part of this thesis. The second research question investigated the aboveground carbon stock in secondary forests regenerating after shifting cultivation and the patterns and determinants of biomass recovery.

Research question 2:

What are the aboveground carbon stocks in secondary forests after shifting cultivation, and

how is biomass carbon is allocated in different forest biomass components?

The third research question concerned with soil carbon and nutrients in relation to kaingin land-use and to see how these may recover in regenerating secondary forests. The question was:

Research question 3: What is the status of soil carbon and nutrients in regenerating secondary forests after kaingin, and how do different environmental attributes affect soil carbon and nutrients recovery?

For research question 4, I performed a biodiversity and carbon trade-off analysis using data from this study and information available from literatures on biodiversity and carbon dynamics in other land-use(s) that may replace fallow areas after kaingin in the upland Philippines. The study has implications for land-use policy, forest restoration and community development through REDD+ and other possible CDM projects in the Philippines uplands.

Research question 4: What is the possible ecosystem service benefits and trade-offs associated with regenerating secondary forests after kaingin when compared with other competing land-use(s), and what implications it has on land-use and policy development in the Philippines?

1.3 Justification of this research This study provides a better understanding of the biodiversity, aboveground forest biomass carbon, soil carbon and nutrient stocks in fallow forests and their recovery in relation to old-growth forests that never been used for shifting cultivation or logging. These are important for forest management, restoration and conservation not only in the Philippines but in other countries where shifting cultivation is common.

Forest structure and composition in the tropics change persistently as a result of human use, disturbances, and as a natural pathway of succession (Chazdon, 2014, 2003; Gardner et al., 2009). In tropical regions, secondary forests formed following shifting cultivation and other disturbances are rapidly becoming a dominant forest type (Chazdon, 2014; Chokkalingam and Perera, 2001; Hughes et al., 1999). Although controversial, shifting cultivation is still a dominant land-use in the tropical forest-agriculture frontier (van Vliet et al., 2012; Piotto et al., 2009). Lack of reliable information regarding biodiversity and carbon dynamics associated with shifting cultivation land- use is however hindering its inclusion in ongoing REDD+ and CDM negotiations (Mertz et al., 2012; Ziegler et al., 2012). It is however clear that in tropical region regenerating secondary forests after shifting is important carbon sinks (Mukul et al., 2016).

In the Philippines, shifting cultivation is blamed for majority of country’s deforestation, in the upland areas (Kummer, 1992) with limited ecological studies (see Kellman, 1970). In most of the previous and ongoing reforestation programs (e.g. NGP) this traditional land-use, however, has simply been overlooked without any further attempt to understand the ecological and/or socio- economic dimensions associated with it. The current study will provide information to help explain some of the important aspects of this ‘black-box’, and the findings have potential application by policy makers and reforestation agencies to better recognize this land-use. Figure 1.2 below summarizes the background, importance and implications of this thesis project.

CONTEXT Socio-economic and policy related 1. a common upland land-use practice;

2. connected to food-security; APPROACHES 3. controversial land-use/ sustainability; 1. empirical evidence from a case study area; 4. with potentials for REDD+/carbon forestry 2. vegetation survey for biodiversity, above ground biomass and carbon; Scientific 3. soil samples and below ground organic 1. biomass and carbon recovery issues; carbon 2. suitable fallow length/cycles;

IMPLICAIONS Scientific 5. knowledge on biomass and carbon stock in fallow OUTCOMES 1. state of art and knowledge about one of the kaingin/shifting cultivation areas in upland Philippines; 6. recovery rate of biomass and carbon after severe most common land-use in the upland disturbance by kaingin practice; Philippines; 7. determining an optimal fallow length; 2. biomass and carbon stocks in relation to land- use history/ intensity of use; Policy related 3. recovery of biomass and carbon stock in 1. framing policy based on field evidence; relation to land- use history and intensity 2. scenario-development/comparison with existing plantation focused forestry; 3. search for potential carbon-forestry/reward packages to ensure long term sustainability and financing of upland development programs.

Figure 1.2. The background, importance and potential implications of this project.

1.4 Methodology This thesis is based on an empirical study from Leyte Island, Visayas region, the Philippines. Vegetation survey, biomass inventory and soil sampling was undertaken in post- kaingin secondary forests and in old-growth forests with no prior history of kaingin use. Altogether 100 transects (50 m x 5 m size) established in 25 sites belonging to four fallow categories (e.g. fallow for less than 5 years, fallow between 6-10 years, fallow between 11-20 years, 21-30 years old fallow) and control old-growth forest sites was used. Table 1.1 shows the samples and/or measurements taken from each site/transects other than site environmental information (e.g. elevation, slope, leaf area index, distance from nearest control forest site etc.) collected during this doctoral thesis project. Table1.2 presents the research matrix with brief summary of methodology against each research objective/question. Further details of the area, methodology and instruments used for sample collection and analysis are described in the following chapters of this thesis.

Table 1.1. Summary of the samples and measurements taken from the study sites in the Philippines.

Sample/Item Number (N) Measurement/Analysis/Data Remark Standing live tree 2918 dbh, height, species identity (≥5 cm dbh) Tree fern 184 dbh, height Abaca (Musa textilis) 124 Dead tree 1281 dbh, height/length, degradation (≥5 cm dbh) status Tree wood core sample 844 Wood density Not used here Dead wood sample 20 Organic Carbon (OC %) (4 category x 5 replicates) Undergrowth biomass 100 Dry biomass sample (fresh) Organic Carbon (OC %) Litter and woody debris 100 Dry biomass sample Organic Carbon (OC %) Soil core sample (5 cm3) 900 Soil Organic Carbon (SOC) Incomplete (3 position x 3 Soil Nitrogen (N) (3 soil depth – 0-5 cm, 6- depth x 100 Soil Phosphorus (P) (samples are 15 cm, 16-30 cm); transect) Soil Potassium (K) being Fine root biomass and OC% processed) (3 transect position – Soil pH outer edge, centre, inner Soil moisture content edge) Soil bulk density

Table 1.2. Research matrix used for this project.

Specific objective Research question Data required Data collection method To measure tree diversity To what extent regenerating kaingin - tree (≥5 cm) dbh; Vegetation survey in 25 sites and forest structure in fallow forests complement old-growth - tree (≥5 cm) height; covering 100 transects in both fallow shifting cultivation forest in terms of biodiversity and forest - tree (≥5 cm) identity; fallow shifting cultivation area landscape structure? - site characters; and in control old-growth forest. - site leaf area index To measure aboveground What are the aboveground carbon stocks - live tree (≥5 cm) dbh and height; Biomass inventory and biomass carbon stocks in in regenerating secondary forests after - dead tree (≥5 cm) application of appropriate fallow shifting cultivation shifting cultivation, and how is biomass dbh/circumference and allometric models. area and in control old- carbon is allocated in different forest height/length; wood samples; growth forest. biomass components? - dbh and height of tree ferns and Abaca (≥5 cm); - undergrowths, leaf litter and woody debris biomass; To understand the status of What is the status of soil carbon and - soil organic carbon; Soil sample collection from soil carbon and nutrients in nutrients in regenerating secondary - soil nitrogen; different depths and laboratory relation to shifting forests after kaingin, and how do - soil phosphorus; analysis in VSU-ACIAR cultivation in regenerating different environmental attributes affect - soil potassium; Analytical Chemistry Laboratory. secondary forests. the recovery of soil carbon and - site characteristics; nutrients? To understand the potential What is the possible ecosystem service - land-use type; Primary and secondary data from biodiversity and carbon benefits and trade-offs associated with - tree biodiversity; present project and available trade-offs associated with regenerating secondary forests after - aboveground carbon stock; secondary data from peer- regenerating forests after kaingin when compared with other - carbon sequestration potential. reviewed publications. shifting cultivation and competing land-use(s), and what other possible land-uses. implications it has on land-use and policy development?

1.5 Limitations and challenges Against the hypothesis presented in the Figure 1.1, this project was limited to only the traditional less intensive shifting cultivation landscapes that represent the general shifting cultivation systems common in much of the tropics. Time and resources limited the extension of the study to include other land-use(s) that may also replace shifting cultivation area. A major challenge was to adjust to a new environment and get acquainted with local culture and systems. Security issues related to unauthorized militant groups in the upland area also influenced my study at least once. Heavy rainfall and extreme weather also restricted my access to the study sites on several occasions. Since shifting cultivation still an unrecognised land-use in the Philippines, it was difficult to get the trust of the local smallholders and landowners regarding land-use and history. Species identification was another challenge but greatly facilitated by local botanists. The enormity of the field samples and the subsequent processing and analysis was challenging. The analysis of samples was further affected by typhoon Haiyan which devastated the Leyte Island in November 2013, the area where I worked and based at until October 2013. Visayas State University (VSU), where my samples were stored was severely damaged and lost power for over 3 months, and the laboratory (VSU-ACIAR Analytical Chemistry Laboratory) where my samples were being analaysed was out of operation for more than four months. This resulted in a substantial delay in the analysis of my soil and plant samples. Finally, due to time limitations it was also not possible to analyse and use some of the field data that I collected (e.g. own wood density data, fine root biomass etc.), and include few others manuscripts from this project that are currently on the very early stage of development.

1.6 Overview of this thesis This thesis comprises 7 chapters. Throughout this thesis kaingin and shifting cultivation has been used simultaneously and synonymously. Chapter 2 is a synthesis that reports, spatial and temporal distribution of previous research on shifting cultivation using a systematic literature search protocol, and the key findings of research on some of the selected aspects. Chapter 3 reports a vegetation survey where tree diversity, species composition and forest structure and their recovery in secondary forests after shifting cultivation was investigated along a fallow/shifting cultivation land-use gradient. In Chapter 4, the distribution and recovery of biomass carbon along a fallow gradient were reported. In Chapter 5, the status of soil organic carbon, nitrogen, phosphorus and potassium in relation to shifting cultivation land-use and their recovery of were investigated. Drawing on the previous chapters and present study in Chapter 6, I demonstrate that regenerating secondary forests following shifting cultivation have the potential for inclusion in programs on

10 forest conservation under REDD+ and CDM. Chapter 7 is the general conclusions. Figure 1.3 below provides the outline of this thesis.

CHAPTER 1: General Introduction and background

CHAPTER 2: Systematic map and literature synthesis

CHAPTER 3: CHAPTER 4: CHAPTER 5: Biodiversity Aboveground carbon Soil carbon & nutrients

Tree species diversity, Distribution and Soil organic carbon, soil composition, forest recovery of AGB nitrogen, phosphorus structure, and their carbon in the case and potassium recovery along a fallow study sites, with distribution up to 30 cm age and environmental environmental and site soil depth and their gradient. factors that influence recovery along a fallow the recovery gradient.

CHAPTER 6: Broader study implication using the empirical case study.

CHAPTER 7: General conclusions Summary conclusions of all the thesis chapters with implications and priorities for future research.

Figure 1.3. Outline of the chapters in this thesis.

1.7 References Angelsen, A., 1995. Shifting cultivation and “deforestation”: a study from Indonesia. World Development, 23, 1713-1729.

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Mertz, O., Müller, D., Sikor, T., Hett, C., Heinimann, A., Castella, J.C., Lestrelin, G., Ryan, C.M., Reay, D.S., Schmidt-Vogt, D., Danielsen, F., Theilade, I., van Noordwijk, M., Verchot, L.V., Burgess, N.D., Berry, N.J., Pham, T.T., Messerli, P., Xu, J., Fensholt, R., Hostert, P., Pflugmacher, D., Bruun, T.B., de Neergaard, A., Dons, K., Dewi, S., Rutishauser, E., Sun, Z., 2012. The forgotten D: challenges of addressing forest degradation in complex mosaic landscapes under REDD+. Danish Journal of Geography, 112, 63-76. Mertz, O., Padoch, C., Fox, J., Cramb, R.A., Leisz, S.J., Nguyen, T.L., Tran, D.V., 2009. Swidden change in Southeast Asia: Understanding causes and consequences. Human Ecology, 37, 259- 264. Metzger, M.J., Rounsvell, M.D.A., Acosta-Michlik, L., Leemans, R., Schroter, D., 2006. The vulnerability of ecosystem services to land-use change. Agriculture, Ecosystems & Environment, 114, 69-85. Mukul, S.A., Herbohn, J., 2013. The future of reforestation programs in the tropical developing countries: insights from the Philippines. 2013 American Geophysical Union (AGU)’s Fall Meeting Book of Abstract (Abstract 1050). Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy, 55, 167-177. Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6, 22483. Niles, J.O., Brown, S., Pretty, J., Ball, A.S., Fay, J., 2002. Potential carbon mitigation and income in developing countries from changes in use and management of agricultural and forest lands. Philosophical Transactions of the Royal Society of London A 360: 1621-1639. Padoch, C., Coffey, K., Mertz, O., Lesiz, S.J., Fox, J., Wadley, R.L., 2007. The demise of swidden in Southeast Asia? Local realities and regional ambiguities. Danish Journal of Geography, 107, 29-41. Parrotta, J.A., Wildburger, C., Mansourian, S. (eds.), 2012. Understanding relationships between biodiversity, carbon, forests and people: The key to achieving REDD+ objectives, A global assessment report. Global Expert Panel on Biodiversity, Forest Management, and REDD+, World Series Volume 31. International Union of Forest Research Organizations (IUFRO), Vienna, Austria. Piotto, D., Montagnini, F., Thomas, W., Ashton, M., Oliver, C., 2009. Forest recovery after swidden cultivation across a 40-year chronosequence in the Atlantic forest of southern Bahia, Brazil. Plant Ecology, 205, 261-272.

Posa, M.R., Diesmos, A.C., Sodhi, N.S., Brooks, T.M., 2008. Hope for threatened tropical biodiversity: lessons from the Philippines. BioScience, 58, 231-240. Sodhi, N.S., Koh, L.P., Clements, R., Wanger, T.C., Hill, J.K., Hamer, K.C., Clough, Y., Tscharntke, T., Posa, M.R.C., Lee, T.M., 2010. Conserving Southeast Asian forest biodiversity in human-modified landscapes. Biological Conservation, 143, 2375–2384. Suarez, R.K., Sajise, P.E., 2010. Deforestation, swidden agriculture and Philippine biodiversity. Philippine Science Letters, 3, 91-99. Trumbore, S., Brando, P., Hartmann, H., 2015. Forest health and global change. Science, 349, 814- 818. van Vliet, N., Mertz, O., Heinimann, A., Langanke, T., Pascual, U., Schmook, B., Adams, C., Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.-C., Jørgensen, L., BirchThomsen, T., Hett, C., Bech-Bruun, T., Ickowitz, A., Vu, K.C., Yasuyuki, K., Fox, J., Padoch, C., Dressler, W., Ziegler, A.D., 2012. Trends, drivers and impacts of changes in swidden cultivation in tropical forest-agriculture frontiers: a global assessment. Global Environmental Change, 22, 418–429. Ziegler, A.D., Fox, J. M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Bruun, T.B., Vien, T.D., 2011. Recognizing contemporary roles of swidden agriculture in transforming landscapes of Southeast Asia. Conservation Biology, 25, 846-848. Ziegler, A.D., Phelps, J., Yuen, J.Q., Webb, E.L., Lawrence, D., Fox, J.M., Bruun, T.B., Leisz, S.J., Ryan, C.M., Padoch, C., Koh, L.P., 2012. Carbon outcomes of major land-cover transitions in SE Asia: great uncertainties and REDD+ policy implications. Global Change Biology, 18, 3087-3099.

CHAPTER 2: THE IMPACTS OF SHIFTING CULTIVATION ON SECONDARY FORESTS DYNAMICS IN TROPICS: A SYNTHESIS OF THE KEY FINDINGS AND SPATIO TEMPORAL DISTRIBUTION OF RESEARCH

May cite as – Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy, 55, 167–177.

2.1 Abstract Shifting cultivation has been attributed to causing large-scale deforestation and forest degradation in tropical forest-agriculture frontiers. This view has been embedded in many policy documents in the tropics, although, there are conflicting views within the literature as to the impacts of shifting cultivation. In part, this may be due to the complex nature of this land use making generalisations challenging. Here we provided a systematic map of research conducted on shifting cultivation in the tropics. We first developed a literature search protocol using ISI Web of Science that identified 401 documents which met the search criteria. The spatial and temporal distribution of research related to shifting cultivation was mapped according to research focus. We then conducted a meta-analysis of studies (n = 73) that focused on forest dynamics following shifting cultivation. A bias in research on anthropology/ human ecology was evident, with most research reported from the tropical Asia Pacific region (215 studies). Other key research foci were – soil nutrients and chemistry (72 studies), plant ecology (62 studies), agricultural production/ management (57 studies), agroforestry (35 studies), geography/land-use transitions (26 studies). Our meta-analysis revealed a great variability in findings on selected forest and environmental parameters from the studies examined. Studies on ecology were mainly concentrated on plant diversity and successional development, while conservation biology related studies were focused on birds. Limited impacts of shifting cultivation on some soil essential nutrients were also apparent. Apart from the intensity of past usage site spatial attributes seems critical for the successful development fallow landscapes to secondary forests. It is clear that further research is needed to help ascertain the environmental consequences of this traditional land-use on tropical forests. Scientists and policy makers also need to be cautious when making generalisations about the impacts of shifting cultivation and to the both the social and environmental context in which shifting cultivation is being undertaken.

Key-words: deforestation; secondary forest; agriculture; environmental consequence; conservation.

2.2 Introduction Shifting cultivation, swidden or slash-and-burn is a widespread land-use common in the tropical forest agriculture frontier, and has formed the basis of land uses, livelihoods and customs in upland areas for centuries (Dressler et al., 2015; van Vliet et al., 2012; Mertz et al., 2009a; Metzger, 2003). While reliable information on the number of people who engaged in shifting cultivation is unavailable, Mertz et al. (2009b) has estimated about 14-34 million people alone from tropical Asia depend on shifting cultivation. In tropical regions, it has also been estimated that shifting cultivation is responsible for as much as 60 percent of the total deforestation and is considered as a prominent source of greenhouse gas emissions (Davidson et al., 2008; Geist and Lambin, 2002). At the same time, however, this traditional land-use practice remains central to the livelihoods, culture and food security of millions of people in tropical region (Dalle et al., 2011). In tropical developing countries, the practice of shifting cultivation is sometimes synonymous with poverty and low productivity of land (Schroth et al., 2004). In recent years, the extent of land under shifting cultivation and the people who depend on it for livelihoods and food security has been declining due to rapid urbanization and economic development in some countries (van Vliet et al., 2012; Mertz et al., 2009a). In many parts of South and Southeast Asia, local and regional land-use and development policies have been developed to reduce shifting cultivation due to a perceived negative impact on environment (van Vliet et al., 2012; Fox et al., 2009). There is, however, growing recognition from scientists of the importance of this traditional land-use to smallholder’s livelihoods and food security (Fox et al., 2009; Mertz et al., 2009b; Ziegler et al., 2011). At the same time, controversies still persist among policy makers and the scientific community on the suitability of this traditional land-use from environmental and conservation perspectives (Bruun et al., 2009; Lawrence et al., 2010).

Shifting cultivation is still a dominant land-use/practice in countries rich in biodiversity and forest cover, and many of these countries also has some of the highest rates of deforestation (Baccini et al., 2012). Understanding shifting cultivation is therefore critical for sustainable forest management, biodiversity conservation, and proper land-use and development planning in tropical regions (DeFries and Rosenzweig, 2010). The issues associated with shifting cultivation however, are complex, and involve the intersection of socio-economic, environmental and policy issues. In recent years evidence-based science has been embraced by scientific communities as a desirable approach to design appropriate environmental policies (Lele and Kurien, 2011). In this paper, we review and analyze empirical research on shifting cultivation following a protocol. Our focus was on the spatio- temporal patterns of research on shifting cultivation across the tropics in order to identify research trends and gaps in research. We then performed a meta-analysis of literature that focused on forest 17 dynamics following shifting cultivation with emphasis on the effect of shifting cultivation on key forest and environmental parameters including - plant ecology, conservation biology, soil nutrients and chemistry, and soil physics and hydrology. We finally presented a meta analysis where selected environmental attributes were compared with primary forests and/or other tree based land- use/cover. The drivers of change of shifting cultivation in tropics, with related livelihoods and environmental consequences have been reviewed by van Vliet et al. (2012) based on an analysis of the literature between 2000 and 2010. We extend that analysis to include papers published from 1950 to 2014. Importantly, our study builds on van Vliet et al. (2012) by providing more detailed analysis of the dynamics of tropical secondary forests after shifting cultivation, and factors that may influence the recovery of such landscapes. Our paper provides a general overview of the research on shifting cultivation, gaps in research and secondary forest dynamics after shifting cultivation. Uncovering such issues with greater certainty is useful for both conservation and management of declining tropical forests.

2.3 Methodology 2.3.1 Document search for systematic map We searched the relevant literature using the ISI Web of Science (WoS, Thomson Reuters) database (Web of Science, 2014). WoS was selected as it is one of the most powerful, comprehensive, and widely used search engine for the analysis of interdisciplinary and peer- reviewed literature (Jasco, 2005). There are many terms that have been used locally to explain shifting cultivation (e.g. jhum in Bangladesh and parts of India, kaingin in the Philippines, bhasme in Nepal, ladang in Indonesia, conuco in Venezuela, tavy in Madagascar etc). However, shifting cultivation, swidden and slash-and-burn are the most commonly used and generally accepted terms that have been used to delineate this land-use (Mertz et al., 2009a). In our literature search we used a combination of those keywords using the search term - (shifting cultivation or swidden or (‘slash- and- burn’) in the title. Our review was limited to peer-reviewed articles published between January 1950 to January 2014.

Our search initially yielded 551 documents of which 460 were relevant to our study (Supplementary material 1). All 460 retrieved documents were then reviewed based on their title and abstract to evaluate their suitability for inclusion in the final review. We considered only the articles that reported empirical studies from tropical countries. We then excluded any review, meta-analysis, methodological paper, and paper from outside the tropics (Figure 2.1). This resulted in a list of 401 articles that met our final selection criteria.

2.3.2 Document characterzization We classified the documents according to their main research subject focus (Table 2.1) as interpreted through their title, abstract and corresponding journal title and classification. Documents were classified into the following subject categories: (i) agricultural production/management; (ii) agroforestry; (iii) anthropology/human ecology; (iv) conservation biology; (v) geography/land-use transitions; (vi) plant ecology; (vii) soil nutrients and chemistry; (viii) soil physics and hydrology; and (ix) others. The year of the publication and geographic location of the research (i.e. country/region) were noted for each document.

Table 2.1. Example of documents under different subject focus.

Subject/Topic Example Agricultural production/ agricultural crop yield, weed management etc. Management Agroforestry agro-biodiversity, cultural management, non-timber forest products (NTFPs), and NTFPs domestication Anthropology/ Human ecology socio-political issues related to shifting cultivation, indigenous knowledge, history, perceptions and attitudes on shifting cultivation etc. Conservation biology wildlife diversity and assemblage in shifting cultivation landscapes. Geography/ Land-use transitions spatial land-use/cover change analysis, land-use change dynamics etc. Plant ecology plant biodiversity, plant succession, biomass and species recovery, soil seed bank etc. Soil nutrients and chemistry soil nutrients, soil organic carbon, and other chemical properties of soil. Soil physics and hydrology soil erosion, soil infiltration capacity, soil particle stability etc. Others documents other than the above research focus, e.g. trace gas emissions from shifting cultivation.

2.3.3 Document selection for meta-analysis The main emphasis of our meta-analysis was on the secondary forest dynamics following shifting cultivation and the impacts of shifting cultivation on forest characteristics considering primary or undisturbed forest as control. Therefore, articles from subject foci – plant ecology, conservation biology, soil nutrients and chemistry, and soil physics and hydrology have been included. Since we focused on forest dynamics following shifting cultivation we restricted our

19 analysis only to articles that presented a comparison of the related parameters with undisturbed forests (i.e. primary or secondary forest without prior history of shifting cultivation). Seventy three articles met our final selection criteria for that meta-analysis, comprising 34 studies on plant ecology, 14 studies on conservation biology, 17 studies on soil nutrients and chemistry, and 8 studies on soil physics and hydrology.

2.3.4 Data interpretation and analysis For our systematic map we compared the number of research studies on different subjects, conducted in different time span as well as in different geographic regions. We performed Student’s t-tests with p-value (one-tailed) to see any significant difference in number of research studies on shifting cultivation during different time period as well as in different tropical regions. All statistical analyses were implemented using MS Excel and R statistical package (version 3.1.0; R Development Core Team, 2012). For mapping spatial distribution of research on shifting cultivation, we used the package ‘rworldmap’ (South, 2011).

2.4 Results and discussions 2.4.1 Spatio-temporal dynamics of research on shifting cultivation i. Spatial distribution of research on shifting cultivation Our study revealed spatial heterogeneity and biases in research focus, as well as a high degree of variability in the number of research studies across tropical countries and regions. Altogether 412 studies from 45 countries representing three tropical regions (i.e. tropical Asia and the Pacific; Africa and tropical America) were covered by the retrieved documents (n = 401). The geographic distributions of the studies are shown in Figure 2. Of these studies, 215 (52.2%) were from tropical Asia and the Pacific, 131 (31.8%) from tropical America and the Caribbean, and 66 (16%) were from Africa. A small number of articles (n=9) reported empirical studies from more than one country. The largest number of studies was reported from India (n=58, 14%), followed by Brazil (n=43, 10.4%), Mexico (n=38, 9.2%), Indonesia, and Lao PDR (n=32, 7.8%) (see - Supplementary Figure 2.1) and coincide within tropical countries where deforestation rates are relatively high (see Baccini et al., 2012).

When considering the geographic focus, most research took place in tropical Asia and the Pacific region (t = 3.18; p < 0.05). Significantly more research was conducted on anthropology and human ecology issues (t = 4.35; p ≤ 0.01) with the majority of these studies being conducted in the Asia and the Pacific region (56 studies, 26%) region and in tropical America (32 studies, 24.4%). Plant ecology related studies were the most common in Africa (n=16, 24.2%) and in tropical America

ISI Web of Science

Search term: (shifting cultivation or swidden or (slash and burn)) Range: January 1950 to January 2014 Document type: Peer reviewed article

551 Documents

Not relevant Included (n = 460)

Excluded (n = 91)

Review/Meta-analysis/Methods Case study (n = 401)

Excluded (n = 59)

Agricultural production/Management management (n = 57) Agroforestry (n = 35)

Anthropology/Human ecology (n = 101)

Conservation biology (n = 14) Conservation biology (n = 24)

Geography/Land-use transition (n = 26)

Plant ecology (n =34) Plant ecology (n = 62)

Soil nutrients & chemistry (n = 17) Soil nutrients & chemistry (n = 72)

Soil physics & hydrology (n = 8) Soil physics & hydrology (n = 20)

Others (n = 4)

Meta-analysis Systematic map

Figure 2.1. Summary of literature used for systematic map and meta-analysis.

(n=25, 19%). Research on soil nutrients and chemistry was prominent (n=46, 21.4%) in the Asia- Pacific region (Figure 2.2).

ii. Temporal pattern of research on shifting cultivation The majority of research related to shifting cultivation has been published since 2001 (t = 2.1; p = 0.52), with the major foci being on anthropology/human ecology (22%), plant ecology (20.7%), and soil nutrients and chemistry (14.2%). The majority of the research was on soil physics and hydrology (80%), geography/land-use transitions (73%) and plant ecology (72.6%) has occurred since 2001. Figure 2.3 illustrates the changes in research focus in the retrieved documents between 1950 and 2014.

Research on anthropology and human ecology was prominent (n = 101) throughout almost the entire period except during 1981-1990. Research on agricultural production/management (n = 17) and soil nutrients and chemistry (n=16) was also prominent after anthropology/ human ecology during 1981–1990. During 1991–2000 soil nutrients and chemistry was a major focus of the researchers (n=23). In recent years, research on the environmental impacts of shifting cultivation (e.g. soil physics and hydrology, plant ecology etc) have received more attention.

A similar pattern is also common in case of geography and land-use transition research which may be attributed to the rapid advancement and access to spatial information technologies (for example: satellite imagery and advanced methods to monitor changes in shifting cultivation landscapes).

2.4.2 Impacts of shifting cultivation on tropical forest dynamics In tropical forested landscapes shifting cultivation has long been considered environmentally harmful and unsustainable (see - van Vilet et al., 2012; Ziegler et al., 2011, 2009; Bruun et al., 2009). However, what is often overlooked is that in many cases alternative land-uses to shifting cultivation fallow forests may have potentially greater negative impacts (Dressler et al., 2015; Vongvisouk et al., 2014). However, there are only a few studies that have investigated the change in environmental values of these alternative land-uses that may replace fallow secondary forests. From these studies, there is a growing evidence that the expansion of monoculture tree crops like rubber and oil palm in many parts of tropical Asia, which has replaced traditional shifting cultivations systems, has resulted in increased deforestation, biodiversity loss and deterioration of other related environmental parameters (Ahrends et al., 2015; Bruun et al., 2013; van Vliet et al., 2012).

Figure 2.2. Geogrpahical distribution of the studies on shifting cultivation by country.

100% 0 0 1 31 3 16 90% 2 16 23 31 80% 1 70% 0 10 7 45 60% 3 6 7 2 5 14 50% 6 19 16 40% 24

48 30% 5 11 20% 0 18 17 10% 2 1 14 24 0% 1950-1970 1971-1980 1981-1990 1991-2000 2001-2014

Agricultural production/ Management Agroforestry Anthroplogy/ Human ecology Geography/ Land-use transitions Conservation biology Plant ecology Soil nutrients and chemistry Soil physics and hydrology Others

250

16 200

150 45 studies

14 of 100 19 3 23

Number 1 7 48 16 6 50 10 5 23 24 16 18 5 11 2 17 14 24 0 17 6 1950-1970 1971-1980 1981-1990 1991-2000 2001-2014 Agricultural production/ Management Agroforestry Anthroplogy/ Human ecology Geography/ Land-use transitions Conservation biology Plant ecology Soil nutrients and chemistry Soil physics and hydrology Others

Figure 2.3. Temporal changes in research focus between 1950-2014 (top: percentage; below: number)

Our meta-analysis revealed that there is a high degree of variability with respect to the impacts that shifting cultivation has on forest characteristics, wildlife, soil nutrients, and soil physical and

24 hydraulic properties (Annex 2.1). Interestingly, most of the studies used a chrnosequence approach for monitoring change in different forest attributes in secondary fallow forest following the shifting cultivation (Annex 2.1). Figure 2.4 presents the key insights of the retrieved documents with quantitative data (n=73). Albeit a diverse research focus, a contrasting effect of shifting cultivation in forest characteristics is evident from the literature. It is important to notice here that our comparison was limited to only fallow forests and primary or old-growth forests without any history of shifting cultivation. Due to limited data we were unable to include other possible land-use/cover changes that may also replace fallow shifting cultivation landscape in tropics with potentially greater harmful effects. Details of the changes in forest characteristics, and their recovery pattern and determinants are discussed hereafter as per subject foci.

Figure 2.4. Reported effect of shifting cultivation on (a) major forest characteristics; (b) selected wildlife selected taxa, (c) major soil nutrients and (d) soil physical and hydraulic properties.

(Note: this is based on comparison with primary or old-growth secondary forests without any history of shifting cultivation, and doesn’t not include other possible potentially more harmful land- use/cover changes that may also replace fallow shifting cultivation landscapes).

i. Plant ecology Our meta-analysis of studies on plant ecology revealed a general negative impact of shifting cultivation on plant diversity and species composition (see Ding et al., 2012; Do et al., 2011; Castro-Luna et al., 2011; Figure 2.4a). Interestingly, studies that focused on early successional stage following shifting cultivation found minor effect of shifting cultivation on plant diversity indices (e.g. Phongoudome et al., 2013; d'Oliveira et al., 2011; Raharimalala et al., 2010). A conspicuous negative impact of shifting cultivation on plant diversity compared to undisturbed forest was reported by Ding et al. (2012), Wilde et al. (2012), Do et al. (2011) and Castro-Luna et al. (2011) respectively from tropical China, Madagascar, Vietnam and Mexico. Species richness, however, did not differ significantly between undisturbed forests and secondary forests that have been subjected to shifting cultivation (Klanderud et al., 2010). Some studies found traditional forest management practices like logging less harmful than shifting cultivation when considering species diversity and composition (e.g. Ding et al., 2012).

Both fallow age and intensity of previous use influence the recovery of species composition and diversity after shifting cultivation (Ding et al., 2012; Schmook, 2010; N’Dja and Decocq, 2008). Young fallow areas have less diversity of species, but that diversity recovers quickly (Schmook, 2010). Similarly, it was found that, plant diversity recovered rapidly following shifting cultivation in Mexico, with continuous accumulation with age (Read and Lawrence, 2003). In Madagascar woody species become prominent in fallow secondary forests after about ten years (Rahamiralala et al., 2010; Klanderud et al., 2010). In such circumstances, an active management strategy may be necessary to restore mature-forest species in fallow secondary forest (Bonilla-Moheno et al., 2010). It may however take around 60 years to achieve biodiversity of an old growth forest in such landscape (Do et al., 2010). Interestingly, when considering the factors that influences species diversity and composition, it was found that, soil type did not influence species diversity in the fallow secondary forests (N’Dja and Decocq, 2008).

Compared to species diversity, forest structure is slow to recover following shifting cultivation. For example, Piotto et al. (2009), found that it may take as long as 40 years to recover the structure of an old-growth forest after they have been used for shifting cultivation in Brazil. It has also been found in Cameroon that forest structure is much slower to recover in fallow secondary forests following shifting cultivation compared with logged forests i.e. 30 to 60 years compared to five to 14 years respectively (Gemerden et al., 2003) However, recovery of some specific stand structure parameters, such as stand density, can be rapid in young fallow areas (Phongoudome et al., 2013).

Biomass recovery follows a similar trend to the recovery of species diversity, with a rapid initial recovery phase which subsequently slows. Biomass accumulation increases with abandonment age (Raharimalala et al., 2012). Both above and below ground biomass recovers rapidly at early successional stage with an estimated accumulation rate between 7.5 to 15.0 Mg ha−1 year−1 (Kenzo et al., 2010). Similarly, Gehring et al. (2005) found that biomass recovery is rapid in the early successional stages, with about 50 percent of the biomass recovering within 25 years after last use. Read and Lawrence (2003) from Mexico reported that recovery of biomass may take as long as 55 to 95 years after shifting cultivation. Similarly, Do et al. (2010) found in Vietnam that it may take about 60 years to achieve 80 percent biomass of an undisturbed forest. Substantial recovery of biomass has been found in Brazil following repeated fire events, with recovery to pre-fire aboveground biomass level within 30 years (d’Oliveira et al., 2011).

Burning following initial clearing has been found to have a positive influence on biomass accumulation in fallow secondary forests in the early successional stage (d’Oliveira et al., 2011; Kenzo et al., 2010; Tschakert et al., 2007). The rate of recovery of biomass is also affected by intensity and number of prior shifting cultivation cycles. For example, Lawrence (2005) found that the rate of biomass accumulation declines by about 10 percent with each subsequent shifting cultivation cycle.

In fallow secondary forests seed is crucial for species recovery and regeneration (Vieira and Proctor, 2007), and distance from intact forests or from forests that provide regular seed sources can also influence the recovery of species diversity (Sovu et al., 2009; Wangpakapattanawong et al., 2010). Lawrence et al. (2005), for instance, reported that seed rain declined with increasing distance from the undisturbed forest. Interestingly, the largest seed banks were found in young fallow areas in the Brazilian Amazon (Vieira and Proctor, 2007).

ii. Conservation biology Most studies on conservation biology reported a negative impact of shifting cultivation on selected animal taxa (Figure 2.4b). Our analysis however does not include exotic or monoculture planatations established in fallow secondary forests that have sometimes been found more harmful for local fauna (Ahrends et al., 2015). The majority of the studies (n=7) were, limited to bird diversity and abundance in fallow secondary forests. In India, it has been found that bird diversity and abundance increase with an increase in the fallow age (Raman et al., 1998), although undisturbed forests remain as the main habitat of specialized forest birds (Raman, 2001; Bowman et al., 1990). Intensity of past shifting cultivation use greatly influences the diversity of birds in fallow 27 secondary forest in tropical China (Zhijuna and Young, 2003). The diversity and abundance of large frugivores (i.e. birds that feed on large fruits) also increases with the increase in fallow age (Schulze et al., 2000).

Shifting cultivation also been found to have a negative (but minor) impact on small mammal diversity and abundance in Peru (Naughton-Treves et al., 2003), and Zaire (Wilkie and Finn, 1990), with hunting intensity having a much greater influence (Naughton-Treves et al., 2003). Other lower taxa animal appear to recover quickly after shifting cultivation, with their composition and richness being greatly influenced by the alteration of forest structure (Yoshima et al., 2013).

iii. Soil nutrients and chemistry Studies on soil nutrients and chemistry have reported a mixed effect of shifting cultivation on associated soil parameters (Figure 2.4c). Generally, shifting cultivation involves burning of forest vegetation, and it is quite likely that it increases the amount of organic matter in soil via ash (Tanaka et al., 2001; Giardina et al., 2000; Adedeji, 1984). Soil nutrient losses can be potentially higher following shifting cultivation due increased soil run-off associated with forest clearing and site spatial characteristics like slope (Rodenburg et al., 2003; Brand and Pfund, 1998). In Mexico, Giardina et al. (2000) found that, apart from ash, heating of soil during the burning of forests also acts as an important mechanism of nutrient release in the soil. Interestingly, Osman et al. (2013) found that, soil organic carbon (SOC) was greater in fallow secondary forests than in adjacent natural forests in Bangladesh. In Thailand, Tanaka et al. (2001) found that, while burning increases (SOC), it also results in a decrease in microbial biomass C in soil. In contrast, a 32% decrease in SOC due to combustion has been reported in Mexico (Garcia-Oliva et al., 1999). Some other land- uses like oil palm plantations may have however even more detrimental effect than shifting cultivation when considering soil C (Brunn et al., 2013).

Other nutrients, including soil available nitrogen (N), phosphorus (P) and potassium (K) also exhibit mixed effects following shifting cultivation. For instance, in China, Yang et al. (2003) found that fire reduced the total N and P in soil by about 20% and 10% respectively, while K was increased. Similarly, Brand and Pfund (1998) have reported a positive effect of shifting cultivation on soil available P and K in a 5 year old fallow secondary forest, but negative impact on Ca and Mg available in soil. In contrast, in Nigeria, Adedeji (1984) found that, soil K and N decreased rapidly after clearing for shifting cultivation, and in a 6 year old fallow forest the soil nutrient levels were still far below those found in in a nearby undisturbed forest.

A long fallow period appears to be important to restore the essential soil nutrients (Funakawa et al., 2009). For instance, in Madagascar, Rahamiralala et al. (2010) found that it may take about 20 years to restore soil nutrients after shifting cultivation. Intensity of past use (i.e. number of fallow cycles) does not appear to influence soil P, at least in Indonesia (Lawrence and Schlesinger, 2001).

iv. Soil physics and hydrology Studies on soil physics and hydrology reported mostly negative impacts of shifting cultivation on associated soil attributes in fallow secondary forests (Figure 2.4d). In most cases, subsequent fire resulted in disruption to soil physical and hydraulic properties (Hattori et al., 2005; Garcia-Oliva et al., 1999). Clearing and burning of forest at the initial stage of shifting cultivation cause increased soil run-off (Rodenburg et al., 2003). Dung et al. (2008) found significant increases in soil erosion and runoff compared to undisturbed forest in Vietnam. Gafur et al. (2003, 2004) also found a considerable amount of soil loss (3 Mg ha−1 y−1) through runoff due to shifting cultivation in forests of Bangladesh. In contrast, Osman et al. (2013) however, did not found any considerable effect of shifting cultivation on soil physical properties including – water holding capacity, bulk density, moisture content and particle density.

In Malaysia (Hattori et al., 2005) and Thailand (Grange and Kansuntisukmongkol, 2004) it has been found that shifting cultivation accelerates soil erosion and deteriorates soil hydrological properties in regenerating fallow secondary forests. Soil loss decreased exponentially from burned to early stage of secondary forest development following the shifting cultivation (Thomaz, 2013). However, Grange and Kansuntisukmongkol (2003) did not find any detrimental effect of fallow length on soil physical attributes after shifting cultivation.

2.5 Conclusions In tropical forested landscapes shifting cultivation is still a dominant land-use, although in recent years, both the intensity and extent of shifting cultivation have changed in many countries (van Vliet et al. 2012, 2013). Our systematic map revealed a large spatio-temporal variability and gaps in research on shifting cultivation across the tropics. There is great variability in the numbers and focus of research studies dealing with various aspects of shifting cultivation. Most research has been on anthropology and human ecology issues. In contrast, research on environmental consequences is still limited, and only gaining wider attention from researchers in the recent years.

Due to its complex nature, diverse focus, and differences in the context, it is difficult to generalize the findings of research on shifting cultivation systems. Our meta-analysis on the impacts of 29 shifting cultivation on forest dynamics and related bio-physical and environmental parameters revealed great variability in research findings. There were a relatively large number of studies on plant ecology and fewer studies on soil physics and hydrology. A limited number of studies on environmental consequences of other land use/covers that are common after shifting cultivation in tropics was also evident. Plant diversity and composition was the most common aspects of plant ecology research while conservation biology related research were mainly focused on bird diversity. A limited impact of shifting cultivation on some soil essential nutrients were also evident from our meta-analysis. Apart from fallow length and intensity of previous use, site spatial attributes like slope, nearness to natural forests and permanent seed/dispersal source also seems critical for successful development of fallow secondary forests.

The sustainability of shifting cultivation systems continues to be debated in many tropical countries, and it is clear that this traditional practice will reamain an important land-use and subsistence strategy in those countries many years ahead (Lawrence et al., 2010; Neergard et al., 2008). In developing tropical countries, shifting cultivation is still seen as a threat to the natural forest (Hett et al., 2013), and has been widely promoted as a practice having a detrimental impact to the environment (Neergard et al., 2008; Fox et al., 2000). However, when discussing shifting cultivation, scientists and policy makers should also consider alternative land-uses with potentially greater negative impacts, like sedentary agriculture, commercially driven large scale plantations or monocultures (Dressler et al., 2015). Policy makers also need be cautious while designing policies, with careful consideration to the small-holder farmers to whom shifting cultivation is still the mainstay of livelihoods and food security.

2.6 Additional information Supplementary Figure 2.1 related to this chapter/manuscript is provided at the end of this thesis under the section – Appendices.

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Annex 2.1. Summary of studies used in meta-analysis on impacts of shifting cultivation on forest dynamics. Primary area Source Country Forest type Study approach* Specific focus Environmental Reference land- consequence** use*** Conservation Yoshima et al., 2013 Malaysia Humid forest Comparison Invertebrate diversity Minor Undisturbed biology/zoology forest**** (n=14) Matsumoto et al., 2009 Malaysia Humid forest Chronosequnce, 2- Ant diversity Negative Undisturbed forest 20 yr Borges, 2007 Brazil Humid forest Chronosequnce, 4- Bird diversity Negative Undisturbed forest 35 yr Gathrone-Hardy et al., Indonesia Humid forest Chronosequence, 2- Termites activity Negative Undisturbed forest 2006 60 yr Naugton-Treves et al., Peru Humid forest Comparison Mammalian diversity Minor Undisturbed forest 2003 Zhijuna and Young, China Comparison Bird diversity Negative Undisturbed forest 2003 Anderson, 2001 Honduras Humid forest Comparison Bird diversity Negative Undisturbed forest Raman, 2001 India Dry forest Chronosequnce, 1- Bird diversity Negative Undisturbed forest 100 yr Schulze et al., 2000 Guatemala Humid forest Comparison Bat diversity Negative Undisturbed forest Raman et al., 1998 India Dry forest Chronosequnce, 1- Bird diversity Negative Undisturbed forest 100 yr Raman, 1996 India Dry forest Comparison Primate/squirrel Negative Undisturbed forest abundance Bowman et al., 1990 Papua New Humid forest Chronosequence Bird/butterflies/reptile Negative Undisturbed forest Guinea diversity Wilkie and Finn, 1990 Zaire Humid forest Comparison Mammalian diversity Minor Undisturbed forest Mishra and India Dry forest Chronosequnce, 1- Nematode abundance Negative Undisturbed forest Ramakrishnan, 1988 15 yr Plant ecology Phongoudome et al., Lao PDR Humid forest Chronosequence Plant diversity, forest Minor Undisturbed forest, (n=34) 2013 structure Logged forest Raharimalala et al., Madagascar Humid forest Chronosequence Forest biomass Negative Undisturbed forest 2012 Wilde et al., 2012 Madagascar Humid forest Chronosequence Plant diversity Negative Undisturbed forest Ding et al., 2012 China Humid forest Chronosequence Plant diversity Negative Undisturbed forest, Logged forest d’Oliveira et al., 2011 Brazil Humid forest Long term Forest biomass Minor Undisturbed forest monitoring Do et al., 2011 Vietnam Humid forest Chronosequence Plant diversity Negative Undisturbed forest Castro-Luna et al., Mexico Dry forest Chronosequence Plant diversity Negative Undisturbed forest, 2011 Logged forest 39

Bonilla-Moheno et al., Mexico Dry forest Chronosequence Seedling survival Negative Undisturbed forest 2010 5-15 yr Rahamiralala et al., Madagascar Humid forest Chronosequence, Plant diversity Minor Undisturbed forest 2010 upto 40 years Wangpakapattanawong Thailand Humid forest Chronosequence, 1- Plant diversity/ Minor Undisturbed forest et al., 2010 6 yr succession Schmook, 2010 Mexico Dry forest Chronosequence Plant diversity/ Negative Undisturbed forest succession Kenzo et al., 2010 Malaysia Humid forest Long term Forest biomass Positive Undisturbed forest monitoring Do et al., 2010 Vietnam Humid forest Chronosequence, 1- Plant diversity, Forest Negative Undisturbed forest 26 yr biomass Klanderud et al., 2010 Madagascar Humid forest Chronosequence Plant diversity Negative Undisturbed forest Lawrence et al., 2010 Mexico/Indonesia Dry/Humid Long term Forest biomass Negative Undisturbed forest forest monitoring Piotto et al., 2009 Brazil Humid forest Chronosequence, Plant diversity, Forest Minor Undisturbed forest 10-40 yr structure Sovu et al., 2009 Lao PDR Humid forest Chronosequence, 1- Species diversity, Negative Undisturbed forest 20 yr Forest structure Eaton and Lawrence, Mexico Dry forest Chronosequence, 2- Forest biomass Negative Undisturbed forest 2009 25 yr N’Dja and Decocq, Ivory Coast Humid forest Chronosequence, 1- Plant diversity Minor Undisturbed forest, 2008 30 yr Logged forest Gehring et al., 2008 Brazil Humid forest Chronosequence, 2- Plant diversity Negative Undisturbed forest 25 yr Ochoa-Gaona et al., Mexico Dry forest Chronosequence Plant diversity Negative Undisturbed forest 2007 Vieira and Proctor, Brazil Humid forest Chronosequence, 5- Soil seed Positive Undisturbed forest 2007 20 yr bank/succession Lawrence et al., 2005 Indonesia Humid forest Chronosequence, 9- Plant diversity Negative Undisturbed forest 12 yr Gehring et al., 2005 Brazil Humid forest Chronosequence, 2- Plant diversity, Forest Negative Undisturbed forest 25 yr biomass Lawrence, 2005 Indonesia Humid forest 10-200 yrs Forest biomass Negative Undisturbed forest Lawrence, 2004 Indonesia Humid forest 9-12 Plant diversity Negative Undisturbed forest Kupfer et al., 2004 Belize Dry forest Chronosequence, 1- Plant diversity/ Negative Undisturbed forest 10 yr Succession Metzger, 2003 Brazil Humid forest Chronosequence, 4- Plant diversity/ Negative Undisturbed forest 10 yr Succession Gemerden et al., 2003 Cameroon Humid forest Chronosequence, Plant diversity Negative Undisturbed forest, 40

10-60 yr Logged forest Read and Lawrence, Mexico Dry forest Chronosequence, 2- Forest biomass Negative Undisturbed forest 2003 25 Lawrence and Foster, Mexico Dry forest Chronosequence, 2- Forest biomass Negative Undisturbed forest 2002 25 Miller and Kauffman, Mexico Dry forest Chronosequence; 2- Plant diversity/ Negative Undisturbed forest 1998a 19 yr Succession Miller and Kauffman, Mexico Dry forest Comparison Plant diversity Negative Undisturbed forest 1998b Kotto-Same et al., 1998 Cameroon Chronosequence, 4- Forest biomass/ Negative Undisturbed forest, 70 yr carbon Cacao plantation Soil nutrient and Bruun et al., 2013 Malaysia Humid forest Comparison SOC Negative Undisturbed forest, chemistry Oil palm plantation (n=17) Osman et al., 2013 Bangladesh Humid forest Chronosequence, 1- SOC, N, P, K SOC (+) Undisturbed forest 3 yr Negative Lima et al., 2011 Brazil Humid forest Chronosequence SOC, N Negative Undisturbed forest, Agroforests Rahamiralala et al., Madagascar Humid forest Chronosequence SOC, N Minor Undisturbed forest 2010 Eaton and Lawrence, Mexico Dry forest Chronosequence, 2- SOC Negative Undisturbed forest 2009 25 yr Funakawa et al., 2009 Indonesia Humid forest Comparison SOC Negative Undisturbed forest Neergaard et al., 2008 Malaysia Humid forest Comparison SOC Minor Undisturbed forest, Pepper plantation Rodenburg et al., 2003 Indonesia Humid forest Comparison P Negative Rubber agroforest Gafur et al., 2003 Bangladesh Humid forest Comparison SOM Negative Agroforests Borggaard et al., 2003 Bangladesh Humid forest Comparison SOC, N, K Negative Agroforests Yang et al., 2003 China Comparison N, P, K Negative Undisturbed forest Lawrence and Indonesia Humid forest Chronosequence, P Minor Undisturbed forest Schlesinger, 2001 200 yr Giardina et al., 2000 Mexico Dry forest Comparison N, P, K Positive Undisturbed forest Garcia-Oliva et al., Mexico Dry forest Chronosequence, 1- SOC Negative Undisturbed forest 1999 10 yr Brand and Pfund, 1998 Madagascar Humid forest Comparison P, K, Ca, Mg Mixed Undisturbed forest (P,K+) Salcedo et al., 1997 Brazil Humid forest Comparison SOC Minor Undisturbed forest Adedeji, 1984 Nigeria Chronosequence, 16 N, P, K Negative Undisturbed forest yr Soil physics and Thomaz, 2013 Brazil Humid forest na Soil erosion Negative Undisturbed forest hydrology Osman et al., 2013 Bangladesh Humid forest Comparison Bulk density, water Negative Undisturbed forest (n=8) holding capacity 41

Lestrelin et al., 2012 Lao PDR Humid forest na Soil erosion Negative Undisturbed forest Dung et al., 2008 Vietnam Humid forest na Soil erosion Negative Undisturbed forest Neergaard et al., 2008 Malaysia Humid forest Comparison Soil erosion Minor Undisturbed forest, Pepper plantation Hattori et al., 2005 Malaysia Humid forest Comparison Soil structure Negative Undisturbed forest Gafur et al., 2004 Bangladesh Humid forest Comparison Soil structure Negative Undisturbed forest Grange and Thailand Humid forest Chronosequence, 10 Soil structure, water Minor Undisturbed forest Kansuntisumkmongkol, yr holding capacity 2003 *where, chronsequence studies used secondary forests of different ages that have been previously used for shifting cultivation (and abandoned); comparison studies used only one age (specified or unspecified) of secondary forests (abandoned after shifting cultivation), and long term monitoring studies used the same fallow secondary forest sites for subesequnt investigation over a long period of time; **when refering e to a environmental consequence we consider the specific focus of that study and used undisturbed forests for any comparison; ***our reference land-use for the comparisons were primarily based on forests, either logged or unlogged, and/or other tree based land-uses when available, e.g. cacao/rubber agroforests; we did not include any agricultural land-use in the analysis; **** undisturbed forests includes primary or secondary forests that has never been used for shifting cutivation.

CHAPTER 3: HIGH RESILIENCE OF TROPICAL FOREST DIVERSITY AND STRUCTURE AFTER SHIFTING CULTIVATION IN THE PHILIPPINES UPLANDS

May cite as – Mukul, S.A., Herbohn, J., Firn, J. In review. High resilience of tropical forest diversity and structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science.

3.1 Abstract Shifting cultivation is a widespread land-use in the tropics that is considered a major threat to rain forests diversity and structure. Despite its extent in the tropical region and critical role in forest quality, few studies have attempted to quantify the resilience or recovery capacity of fallow secondary forests after shifting cultivation. We investigated the impact of shifting cultivation on secondary forest dynamics in an upland area of the Philippines - a global biodiversity hot spot and megadiverse country. Species diversity and forests structure parameters were measured at 25 sites along a fallow gradient. Species composition and reassembly pattern in relation to the old-growth forest was also examined. Our study finds high conservation values of secondary forests after shifting cultivation in the area. Species richness was significantly higher in the oldest fallow sites, while Shannon’s diversity index, species evenness, stem number, basal area and leaf area index were higher in the old-growth forest followed by oldest fallow sites. A homogeneous species composition pattern was found in our fallow secondary forests and control old-growth forest. Our results indicate that regenerating secondary forests disturbed by shifting cultivation can exhibit high resilience and may recover rapidly after five years and that patch size is a strong predictor of this recovery. Although recovery of forest structure was not as rapid as tree diversity, our older fallow sites demonstrated comparable numbers of species as the old-growth forest which are either endemic to the Philippines or entails special conservation needs. Our findings suggest that novel and emerging ecosystems like regenerating tropical fallow secondary forests are of high conservation significance with their important role as a refuge for threatened tropical forest biodiversity.

Key-words: forest conservation; kaingin; Southeast Asia; reforestation; forest restoration.

3.2 Introduction A large area of tropical forests has been modified by human activity, mainly logging and shifting cultivation, and the future of forest management in this region relies on the effective 43 management of such human-modified landscapes (Ghazoul et al., 2015; Putz and Romero, 2014; Gardner et al., 2009; Chazdon, 2008). In this region, secondary or second growth forests have become a key concern of the scientists and policy makers in recent years due to their potentials to offset the unprecedented loss of tropical forest biodiversity (Chazdon, 2014, 2003; Pichancourt et al., 2014; Laurance, 2007; Brook et al., 2006; Wright and Muller-Landau, 2006). It is also increasingly acknowledged that regenerating secondary forests in tropics can provide as much environmental benefit as the primary forests although the role they have played in biodiversity conservation remained still largely unexplored (Bonner et al., 2013; Sang et al., 2013; Chazdon et al., 2009; Norden et al., 2009; Erskine et al., 2006).

In Southeast Asia, shifting cultivation or slash-and-burn agriculture has been considered as a primary agent of forest degradation and deforestation for many years (Ziegler et al., 2011; Achard et al., 2002; Geist and Lambin, 2002; Angelsen, 1995). Shifting cultivation is a dominant land-use in this region with deforestation rate remains still amongst highest in the tropics (Dalle et al., 2011; Sodhi et al., 2010; Achard et al., 2002). In recent years, although the extent of land under shifting cultivation has declined in many countries (van Vliet et al., 2012), this traditional land-use still form a central part of the livelihoods of millions of upland rural people in Southeast Asia (Dalle et al., 2011). At the same time, large controversies persist among policy makers and scientific community on the impact of shifting cultivation on forest dynamics both from management and conservation perspectives (Ziegler et al., 2011; Lawrence et al., 2010; Bruun et al., 2009).

The general negative view of shifting cultivation on forest diversity and structure is mainly due to its comparison with primary or less disturbed forests (see - Ding et al., 2012; Do et al., 2011; Castro-Luna et al., 2011; Klanderud et al., 2010). Such comparison is unrealistic for some other land-uses that are currently replacing the tropical rainforests, like oil palm or rubber plantation is environmentally more detrimental than shifting cultivation (Fox et al., 2014; Bruun et al., 2013). Recovering fallow secondary forests after shifting cultivation in this region also never gained as attention as the logged tropical forests here, although together they are the largest contributor of forest degradation (Houghton et al., 2012; Houghton, 2012). Due to the dynamic nature of fallow landscapes, differences in management and site spatial heterogeneity, research on the impact of shifting cultivation in secondary forest dynamics has always been challenging (Mukul and Herbohn, 2016). The intensity of past usage consistently found important in determining the capacity of degraded tropical to recover in terms of species diversity and forest structure, although a large variation exists in the recovery of different forest attributes and time required for their recovery (Lawrence et al., 2010; Lawrence, 2004). It took, at least, ten years to woody species become 44 prominent in secondary forests following shifting cultivation (Raharimalala et al., 2010) and 60 years to achieve biodiversity of an old-growth forest (Do et al., 2010). Recovery of specific stand structure indices, such as stand density, can be rapid in young fallow areas (Phongoudome et al., 2013) although recovery of the other forest structure parameter may take as long as 40 years (Piotto et al., 2009). In both cases an active forest management strategy found useful to restore forest tree diversity and structure (Bonilla-Moheno and Hol, 2010).

The resilience of forest ecosystems depends on the rate at which they recover from disturbances both biotic and abiotic (Isbell et al., 2015; Wilson et al., 2015). We investigated the recovery of species diversity, composition and forest structure along a shifting cultivation-fallow gradient in an upland secondary forest in the Philippines – a global biodiversity hotspot and a megadiversity country (Posa et al., 2008; Myers et al., 2000). We also examined the factors that may expedite the recovery process in such altered ecosystems. The Philippines maintain about 5% of the world’s plant diversity with high level of species endemism (Lasco et al., 2013; Sodhi et al., 2010; Kummer and Turner, 1994). The forest cover in the country has declined from 50% in 1950 to 24% in 2004 (Lasco and Pullhin, 2009), with the majority of the remaining forests severely degraded (Chokkalingam et al., 2006). Shifting cultivation, locally known as kaingin, is a common, yet controversial land-use in the country (Saurez and Sajise, 2010). Kaingin has also been blamed for much of the country’s deforestation and forest degradation, and not a recognized land-use in government policies (Lasco et al., 2013, 2009; Kummer, 1992). After post logging secondary forest, post-kaingin secondary forest, however, represents the second largest group of secondary forests in the Philippines (Lasco et al., 2001).

While shifting cultivation is declining in many Southeast Asian countries (see - van Vliet et al., 2012; Mertz et al., 2009), secondary forests regenerating after shifting cultivation becoming more common in this region (Mertz et al., 2009; Chokkalingam and Perera, 2001). Understanding biodiversity patterns in such landscape is, therefore, essential for the establishment of science - based conservation strategies that could potentially support policy-making for better forest and landscape management and restoration (Trimble and van Aarde, 2012; Schroth et al., 2004). Our study, hence useful not only to recognize the resilience capacity of tropical secondary forests after shifting cultivation but also to fully understand the future potential of tropical forests to support biodiversity and aid forest restoration and management.

3.3 Materials and methods 3.3.1 Study area 45

We conducted our study in Barangay1 Gaas in Ormoc city – located in the west part of the Leyte Island in the Philippines. The island is eighth largest in the country with an area nearly about 800,000 ha. Geographically, Leyte is situated between 124017/ and 125018/ East longitude and between 9055/ and 11048/ North latitude (Figure 3.1). Forest cover on the island is about 10%, although the once dipterocarp rich rainforests of the island are now represented by patches of old- growth and secondary forests intermixed with coconut (Cocos nucifera) and abaca (Musa textilis) plantations (Asio et al., 1998). The relatively flat lowlands of the island are used for agricultural production, mainly corn (Zea mays), rice (Oryza sativa) and sweet potato (Ipomea batatas) (Asio et al., 1998). There have been many attempts at to support reforestation in Leyte and there are numerous smallholder and community forests scattered across the island, including ‘rainforestation plantings’ designed to reduced kaingin activity in the Philippines (see - Herbohn et al., 2014; Nguyen et al., 2014).

Figure 3.1. Map showing location of the study area on Leyte Island (left), and the study sites (right) plotted in a Google Earth map showing the location of the 25 sites.

1 Barangay (Brgy. in short) is the smallest administrative unit in the Philippines and is the native Filipino term for a village. 46

Leyte has a ‘type IV’ climate based on the Coronas Classification of Climate (Navarrete et al., 2013). According to Aurelio (2000) the whole island is formed from tectonic movement and plate convergence that started during the Tertiary and Quaternary age (Asio et al., 1998). The island enjoys relatively even distribution of rainfall throughout the year with an annual rainfall of about 4,000 mm (Jahn and Asio, 2001). Although there is no distinct dry season, between March and May the area experiences its lowest monthly rainfall (Jahn and Asio, 2001). Mean annual temperature is 280C which remains relatively constant throughout the year (Navarrete et al., 2013). Relative humidity ranges between 75 to 80 percent during the dry and the wettest months (Kolb, 2003).

3.3.2 Site selection criteria Olofson (1980) has categorized the kaingin systems in the Philippines into three distinct types based on the sites where they have been practiced, these are: i) the tubigan system, ii) the katihan system and iii) the dahilig system. The tubigan and katihan systems take place in lower elevation or in gently sloping land with limited facilities of irrigation, whereas the dahilig system is widely practiced in profoundly forested areas and in steeper slopes (Olofson, 1980). For the present study, we sampled only from the dahilig system as it is comparable to the most common form of shifting cultivation available in Southeast Asian rain forests.

We purposively chose Brgy. Gaas (hereafter Gaas only) for our study. It is situated in a relatively higher elevational range with low population density and high vegetation cover which is essentials for the regeneration of kaingin fallow secondary forests (Chokkalingam et al., 2006). Smallholder farmers living in the area usually grow abaca or coconut in their kaingin fallow land in order to receive some cash benefits during the time of abandonment. Our study was, however, confined to the areas where farmers planted only abaca since coconut plantations generally lead more intensive land-management and as such secondary regrowth generally does not result.

3.3.3 Sampling protocol and vegetation survey Chronosequence studies (i.e. space for time) are popular as an alternative to long-term ecological research and have widely been used to investigate successional trends in tropical forests (Norden et al., 2015; Pickett, 1989). We categorized our sites into four different fallow categories; i.e. fallow less than (or equal to) 5 year old (SA0-5), hereafter referred to as new, 6-10 year old fallow (SA6-10) hereafter referred to as young, 11-20 year old fallow (SA11-20) hereafter referred to as middle-aged, and 21-30 year old fallow (SA21-30), hereafter referred to as oldest. Additionally, old-growth forest (SF) without any history of major disturbances (i.e kaingin and logging) located close to the fallow sites was sampled as our control. Our control old-growth forest 47 sites may have experienced little anthropogenic disturbance like much of the tropical forest, e.g. source of wild edible fruits and game for meat, therefore for the clarity of the discussion were not considered as the intact or primary forest.

Vegetation survey was undertaken from May to October 2013. We established 25 sites (5 categories x 5 sites) in fallow areas and in old-growth forest representing a total sample area of 2.5 ha. In the case of fallow secondary forests, we sampled from the sites that were at least 1 ha in size (Piotto et al., 2009). We followed a modified Gentry plot approach for our vegetation survey (Gentry, 1982), as it is the most efficient method of providing accurate estimates of tree diversity at the landscape level (Baraloto et al., 2103). Four transects of 50 m x 5 m size (parallel to each other and with a minimum of 5 m distance from each other) were established at each of our 25 sites. We recorded diameter of each tree ≥5 cm at diameter at breast height (dbh) using a diameter tape. There were no standing trees in two of our new fallow sites.

All trees were identified to the species level and named with the help of a local expert from Visyas State University (VSU). Drawing upon the description in published literature and from the web, additional information like the biogeographic origin (endemic, native or exotic), successional guild (pioneer, secondary, and climax), and conservation status of the species as per the World Conservation Union (IUCN, 2013) and local lists maintained by Philippines’ Department of Environment and Natural Resources (DENR, 2007) were noted. For botanical description of species we followed Roskov et al. (2013). In the case of unknown species we used the most common Filipino name of that species.

3.3.4 Site environmental parameters Both fallow age and fallow cycles are known to influence vegetation and soil parameters and their recovery (Klanderud et al., 2010; Lawrence, 2005). Here we are only able to consider fallow age and not fallow cycles because reliable information was not available from the landowner. Other site attributes collected were - geographic position and altitude of the site, distance from the nearest control old-growth forest, patch size, slope and soil organic carbon (SOC %). We used a digital plant canopy imager (Model: CID Bio-Science, CI-110/120) for leaf area index (LAI) measurement and a hand-held global positioning system (Model: Garmin eTrex) for site altitude. Table 3.1 shows the summary of attributes recorded.

Table 3.1. Environmental attributes of our fallow sites and old-growth forest on Leyte Island, the Philippines. Site Fallow category Old-growth F -value attributes ≤5 year 6-10 year 11-20 year 21-30 year forest 6-10 year 0-5 year Elevation 600.8 549.0 567.2 574.8 512.4 2.18 (m asl) ±22.19 ±72.41 ±49.24 ±35.35 ±54.77 Slope 33 ±5.7 32.4 ±9.4 32.6 ±9.2 38.2 ±7.98 36.4 ±9.71 0.47 (degree) Patch area 1.16 ±0.21 1.14 ±0.13 1.34 ±0.24 1.14 ±0.22 na - (ha) Distance 290 ±74.16 540 ±114.01 162 ±198.17 256 ±153.88 0 11.97* (m) SOCǂ (%) 6.17 ±0.68 6.54 ±2.05 5.21 ±0.69 6.79 ±1.92 4.77 ±1.11 1.87 *F-value significant at p <0.01 level as indicated from ANOVA ǂSource: Mukul et al. (in review).

3.3.5 Diversity and forest structure indices Species diversity was described in terms of species richness (S), Shannon-Wiener’s diversity index (H) and species evenness index (J). Shannon’s diversity index and species evenness index were calculated as described in Magurran (2004) while species richness was the number of unique tree species per site (see also – Supplementary Table 3.1). We used stem number (N), basal area (B), and LAI as the measure of forest structure. Both, stem number and basal area (m2) were expressed per site (0.1 ha) basis. Stem density or number was the number of tree individuals (≥5 cm dbh) per site while basal area (m2) was the total cross-sectional area of all stems (≥5 cm dbh) in each site. LAI was measured as the ratio between total leaf area and ground area as described in Watson (1947).

3.3.6 Species composition and similarities We used importance value (IV) index to compare tree species dominance pattern in each fallow secondary forests and in control old-growth forest (Newton, 2007). IV was the sum of relative density, relative dominance, and relative frequency of species (Curtis and Cottam, 1962). Permutational multivariate analysis of variance (PERMANOVA) was also performed to test whether species composition differed among different site categories, and a non-metric multi dimensional scaling (nNMDS) to check species compositional similarities between different fallow categories and old-growth forest.

3.3.7 Recovery of tree species diversity and forest structure Recovery of the tree species diversity and forest structure were compared with the old- growth forest. Our recovery represents how efficiently secondary forests may complement the old- growth control forest. We, therefore, calculated recovery as the percentage of tree diversity and forest structure relative to old-growth forest using the following equation.

R =( Xfallow / Xs) × 100

where is the measure of a diversity and/or forest structure parameter of fallow site, and Xs is the mean of corresponding biodiversity and/or forest structure parameter in control old-growth forest sites.

3.3.8 Data analysis Statistical analysis was performed using ‘R’ Statistical package (version 3.0.1; R Development Core Team, 2014). Analysis of variance (ANOVA) and Tukey’s post-hoc test was performed to test for significant differences between the variables. We used ‘Biodiversity R’ (version 2.4-1; Kindt and Coe, 2005) and ‘vegan’ (version 2.0-10; Oksanen et al., 2010) for calculating species richness and other biodiversity indices. For PERMANOVA and nMDS we used Bray-Curtis similarity metric with 1000 iterations, starting with a random configuration (Valencia et al., 2014), using the package ‘vegan’ (Oksanen et al., 2010).

Linear mixed-effect models (hereafter refer to as LMEM) were developed to examine the effect of fallow age and site environmental attributes (see Table 3.1) on tree diversity and forest structure recovery, using the package ‘nlme’ (Pinheiro et al., 2011). In our LMEM, fallow age (FA), slope (SL), distance from nearest old-growth forest (DIS), patch size (PS) and soil organic carbon (SOC) were used as explanatory variables (i.e. fixed factors), and site diversity (i.e. species richness, Shannon’s index, Species evenness) and forest structure indices (i.e. stem number, basal area, LAI) was the response variable. We used sites nested in fallow categories as the random effect in our models. Due to its collinearity with other explanatory variable ‘elevation’ was excluded from final LMEM (Supplementary Table 3.2). We considered Akaike Information Criterion corrected for small sample sizes (AICc) for the selection of our top models, where the best models had the lowest AICc scores (Johnson and Omland, 2004). For our model selection and to evaluate the contribution different fixed effects had on explaining the variation in the response variables we used R-package ‘MuMin’ (Bartoń, 2011). We considered models within four AICc units to be competing models (Grueber et al., 2011).

3.4 Results 3.4.1 Species and characteristics Altogether, we censused 2918 tree individuals belonging to 131 species, 86 genera and 46 families in our 25 sites on Leyte Island, the Philippines (Annex 3.1). There were six species that were unidentified comprising 0.02% of total individuals. Among the species, 14 belonged to the family Moraceae, followed by Dipterocarpaceae (10 species), Phyllanthaceae (8 species), Fabaceae (6 species), Euphorbiaceae, Lamiaceae (5 species) and Rubiaceae (5 species). At the landscape level, 106 species were recorded alone from our oldest fallow sites, followed by 11-20 years old fallow sites (95 species), and 79 species from the old-growth forest. We found 40 species that were endemic to the Philippines. The highest number (37) of endemic species was recorded from the oldest fallow sites, followed by in 11-20 year old fallow sites (30 species), young fallow sites (29 species) and in old-growth forest (27 species). Six exotic species were also recorded from the sites, although there were no exotic species in the old-growth forest and in young fallow secondary forest. The highest number of pioneer (49), secondary (46) and climax (11) species were recorded from the oldest fallow sites (Figure 3.2). We found nine tree species that are critically endangered globally (as per IUCN Red List) in our oldest fallow sites, and eight species in young fallow sites and our middle-aged secondary forest sites (Figure 3.2).

Figure 3.2. Distribution and characteristics of species in different fallow categories and in old- growth forest on Leyte Island, the Philippines. 51

3.4.2 Biodiversity and forest structure in regenerating secondary forests Tree diversity and forest structure were varied significantly across our sites on Leyte Island, the Philippines. This was the case whether these attributes were measured as species richness

(F4=30.79, p<0.01), Shannon’s diversity index (F4=12.39, p<0.01), species evenness (F4=1.66, p<0.05), stem number (F4=54.1, p<0.01), basal area (F4=12.51, p<0.01) and in LAI (F4=26.48, p<0.01). Post-hoc analysis using Tukey’s HSD showed species richness significantly higher (p<0.01) in oldest fallow secondary forest followed by old-growth forest (45.2 ±4.21) and in the middle-aged forest (39.2 ±9.52) (Figure 3.3). Both Shannon’s diversity index (3.37±0.11), species evenness (0.88±0.02), stem number (145.8 ±16.53), tree basal area (7.81±2.23), and LAI were significantly (p<0.001) higher in the old-growth forest.

Figure 3.3. Within and between variations of tree diversity (left) and forest structure (right) indices across the sites on Leyte Island, the Philippines. Note the differences in scale on Y axes.

3.4.3 Species composition in regenerating secondary forests after shifting cultivation Climax species had the highest IV in all fallow categories and in the old-growth forest except in the case of young fallow sites (Table 3.2). Shorea polysperma showed the highest IV (44.34) in new fallow sites, where in young fallow secondary forest Lithocarpus llanosil had the highest IV (15.4). Parashorea malannoan had the highest IV both in old-growth forest (53.07), middle-aged secondary forest (22.90) and in the oldest fallow secondary forest (24.63) (Supplementary Figure 3.1).

We found a homogeneous pattern of species richness and abundance in our ordination. In nMDS, species richness and abundance in secondary forests were clustered against our old-growth forest. There was no distinct pattern in secondary fallow forests and control old-growth forest as in our ordination all sites were spread out (Figure 3.4). The stress value of nMDS using species richness and abundance was respectively 12.16 and 13.61. It was the same case for the species of global and local conservation concerns (Supplementary Figure 3.2, 3.3). PERMANOVA using site category as our main effect, however, showed a significant difference (F4 = 1.88; p < 0.001) in species composition across our sites. Tukey’s HSD also confirmed significantly different species composition between old-growth forest with new fallow (p < 0.001), young fallow (p < 0.05) and middle-aged fallow secondary forest sites (p < 0.05).

Table 3.2. Top ten species with highest importance value in sites of different fallow categories and in old-growth forest on Leyte Island, the Philippines. Site Species Relative Relative Relative IV category density frequency dominanc e New fallow Shorea polysperma 3.71 3.33 37.30 44.34 Parashorea malaanonan* 7.41 3.33 23.30 34.04 Pterocarpus indicus 14.82 6.67 8.47 29.95 Calophyllum lancifolium 3.71 3.33 7.34 14.37 Siyao 1.85 3.33 9.12 14.30 Polyscias nodosa** 3.71 6.67 0.65 11.02 Ficus minahassae 7.41 3.33 0.23 10.97 Lithocarpus llanosii** 3.71 3.33 3.17 10.20 Shorea contorta 3.71 3.33 2.85 9.88 Piper anduncum 5.56 3.33 0.16 9.05 Young Lithocarpus llanosii** 2.39 1.56 11.39 15.34 fallow Polyscias nodosa** 7.15 2.08 3.90 13.13 Caryota cumingii*** 6.03 1.56 4.30 11.89

Ficus gul 5.75 2.61 3.23 11.58 Radermachera pinnate 3.93 2.08 4.50 10.51 Leucosyke capitellata 6.45 1.56 2.12 10.13 Ormosia calavensis 4.77 1.56 3.29 9.62 Parashorea malaanonan* 1.54 2.61 4.85 8.10 Horsfieldia costulata** 4.63 2.08 1.80 8.51 Bischofia javanica** 3.37 2.08 2.93 8.38 Middle-aged Parashorea malaanonan* 2.70 2.04 18.16 22.90 fallow Polyscias nodosa** 11.79 2.55 4.33 18.67 Shorea contorta 2.27 2.04 9.47 13.78 Leucosyke capitellata 8.52 2.55 1.78 12.85 Lithocarpus llanosii** 3.98 2.04 6.43 12.45 Bischofia javanica** 2.84 1.02 6.34 10.20 Horsfieldia costulata** 5.12 2.04 2.19 9.34 Ficus balete 1.42 1.02 6.68 9.12 Ficus minahassae 2.13 1.53 5.17 8.83 Radermachera pinnate 3.41 2.04 2.30 7.75 Oldest fallow Parashorea malaanonan* 4.46 2.18 17.99 24.63 Polyscias nodosa** 13.51 2.18 5.80 21.50 Shorea polysperma 1.95 1.31 10.03 13.29 Calophyllum blancoi 3.07 2.18 7.97 13.22 Lithocarpus llanosii** 3.76 1.75 5.74 11.25 Bischofia javanica** 3.62 1.75 4.47 9.84 Ficus gul 4.46 1.75 1.43 7.63 Horsfieldia costulata** 3.62 2.18 1.51 7.31 Caryota cumingii *** 3.62 1.75 1.42 6.78 Ormosia calavensis 2.65 1.75 1.67 6.07 Old-growth Parashorea malaanonan* 8.37 2.21 42.49 53.07 forest Bischofia javanica** 7.96 2.21 5.96 16.13 Caryota cumingii*** 11.39 2.21 1.50 15.10 Shorea guiso 4.25 2.21 2.85 9.32 Horsfieldia costulata** 5.21 2.21 1.74 9.16 Ficus balete 0.55 0.89 5.83 7.27 Petersianthus quadrialatus 1.10 1.33 4.61 7.04 Calophyllum blancoi 1.24 1.77 3.99 7.00 Canarium luzonicum 3.84 2.21 0.79 6.85 Palaquium luzoniense 2.20 2.21 2.19 6.60 Where: * - species common across all site categories, ** - species common across at least four site categories, and *** - species common acroos at least three site categories.

Figure 3.4. nMDS of species richness (stress=12.16) and abundance (stress=13.61) using Bray- Curtis distance.

3.4.4 Tree diversity and forest structure recovery along a shifting cultivation fallow gradient The recovery of tree diversity and forest structure with respect to the old-growth forest were significantly different across our secondary forest sites as measured by species richness (F3 = 17.39; p < 0.00), Shannon’s index (F3 = 9.52; p < 0.001), stem number (F3 = 36.06; p < 0.00) and LAI (F3 = 16.28; p < 0.00). There were, however, no significant differences in the recovery of species evenness (F3 = 2.43; p = 0.10) and basal area (F3 = 2.34; p < 0.11) across our sites (Figure 3.5). Recovery of tree diversity in terms of species richness (101.33±13.13) and Shannon’s diversity index (98.87±4.78) was highest in the 21-30 year old fallow sites. Recovery of forest structure parameters, including stem number (98.49±3.05) and basal area (50.15±17.80) was also highest in the oldest fallow sites. Our post-hoc analysis using Tukey’s HSD revealed significantly low (p < 0.05) recovery of species richness, Shannon’s index, stem number and LAI in the new fallow sites compared to sites of other fallow categories.

Figure 3.5. Recovery of tree diversity (left) and forest structure (right) in relation to old-growth forest on Leyte Island, the Philippines. Note the differences in scales on Y axes.

3.4.5 Environmental controls on the recovery of secondary forest diversity and structure Our multiple candidates LMEM models explained the differences in species diversity and forest structure recovery in tropical secondary forests after shifting cultivation (Table 3.3). For all response variables, models that included patch size explained as much variation as other more complex models that included interactions (as all models within ∆AICc= 4 were considered equivalent) (Table 3.4). Other than patch size, soil organic carbon and fallow age were also found to

56 explain variation in the recovery of different biodiversity and forest structure parameters. Distance from old-growth control forest was not retained in any of the best-fit candidate models.

Table 3.3. Summary of mixed effect models (within ∆ AICc = 4) obtained using package MuMin (Bartoń, 2011). Where, S= species richness, H= Shannon’s index, J= species evenness, N= stem number, BA= basal area, LAI= leaf area index, FA = fallow age, DIS= distance from the nearest control forest, SL= slope, PS= patch size, SOC= soil organic carbon. Response variables Site environmental attribute DF LL AICc ∆ AICc Weight FA DIS SL PS SOC S X X 6 -69.93 159.50 0.0 0.36 X 5 -72.59 160.19 0.69 0.26 X X 6 -70.52 160.68 1.18 0.20 X X X 7 -67.85 160.9 1.4 0.18 H X 5 -65.48 145.96 0.0 0.39 X X 6 -63.67 146.97 1.02 0.23 X X 6 -63.68 146.99 1.03 0.23 X X X 7 -61.84 148.89 2.93 0.09 X X 6 -64.98 149.6 3.64 0.06 J X X 6 -49.31 118.26 0.0 0.57 X 5 -51.9 118.8 0.55 0.43 N X X 6 -68.1 155.83 0.0 0.29 X X X 7 -65.69 156.58 0.76 0.2 X X 6 -68.83 156.91 1.08 0.17 X 5 -71.06 157.12 1.3 0.15 X X 6 -69.53 158.7 2.87 0.07 X 5 -71.94 158.89 3.06 0.06 X X 6 -69.69 159.01 3.19 0.06 BA X X 6 -69.76 159.17 0.0 0.18 X 5 -72.27 159.53 0.37 0.15 X X 6 -70.05 159.73 0.56 0.14 X X X 7 -67.37 159.94 0.77 0.12 X X X 7 -67.39 159.99 0.82 0.12 X X 6 -70.36 160.35 1.19 0.1 X X X 7 -68.22 161.65 2.48 0.05 X X 6 -71.26 162.16 2.99 0.04 X X 6 -71.47 162.57 3.41 0.03 X X X X 8 -65.3 162.6 3.43 0.03 X 5 -73.91 162.82 3.65 0.03 LAI X 5 -70.67 156.35 0.0 0.35 X X 6 -68.72 157.07 0.72 0.25 X X 6 -68.72 157.08 0.74 0.24 X X X 7 -66.76 158.71 2.37 0.11 X X 6 -70.31 160.25 3.9 0.05 57

*DF- degree of freedom, LL- log likelihood, AICc - Akaike information criterion corrected for small sample size.

Table 3.4. The relative importance of site environmental attributes in the final LMEM. Where, S= species richness, H= Shannon’s index, J= species evenness, N= stem number, BA= basal area, LAI= leaf area index, FA= fallow age, PS=patch size, SL= slope, DIS= distance from the nearest control forest, SOC= soil organic carbon. Site indices Site environmental attribute* Number FA PS DIS SL SOC of models S 0.54 (2) 1.0 (4) - - 0.38 (2) 4 H 0.32 (2) 1.0 (5) - 0.06 (1) 0.32 (2) 5 J - 1.0 (2) - - 0.57 (1) 2 N 0.44 (3) 0.87 (5) - 0.06 (1) 0.62 (4) 7 BA 0.49 (6) 0.9 (8) - 0.35 (5) 0.45 (6) 11 LAI 0.35 (2) 1.0 (5) - 0.05 (1) 0.35 (2) 5 *values in the parenthesis indicates the number of models containing respective explanatory variable.

3.5 Discussion 3.5.1 Biodiversity conservation and secondary forest development after shifting cultivation Our study revealed rapid recovery and high resilience of regenerating secondary forests after disturbed by shifting cultivation and their importance in species conservation at the landscape level. Recovery of tree diversity was more rapid than forest structure in the area. Although, there was a substantial decrease in biodiversity in the first five years, but our older fallow sites exhibited similar levels of biodiversity and were similar to old-growth forest. The measures of biodiversity we used (species richness, Shannon’s index and species evenness) and chronosequence approach have been widely used to investigate the successional development of forests after disturbances (Mukul and Herbohn, 2016; Norden et al., 2015; Baraloto et al., 2013). We found that Shannon’s index and species evenness index were higher in old-growth forest and species richness was higher in the oldest fallow sites. Recently abandoned fallow areas represented by our new fallow sites demonstrated a very distinct pattern of species diversity compared to the other much older fallow categories in our study. A similar observation was made by Klanderud et al. (2010) in Madagascar who found subsequent shrub dominance after the abandonment of shifting cultivation inhibiting tree diversity in the area. Young fallow areas have less diversity of adult tree species (Schmook, 2010; Miller and Kaffman, 1998), and woody species become prominent in secondary fallow forests after about ten years (Klanderud et al., 2010; Rahamiralala et al., 2010; Gemerden et al., 2003). Some

58 studies suggest that secondary forest, for example, after selective logging, can exhibit better forest structure in terms of basal area than undisturbed forest (e.g. Ding et al., 2012; Castro-Luna et al., 2011), although the conservation value of such landscapes are not always high when considering the diversity of forest specialist species (Mo et al., 2011; Fredericksen and Mostacedo, 2000). In our study, however, we found a reasonably greater forest structure in the old-growth forest. Despite the comparable species richness and abundance in older fallow sites and in old-growth forest, tree basal area was significantly higher in the old-growth forest which may be attributed by the presence of large diameter and canopy trees in relatively undisturbed forests (Mo et al., 2011).

Despite a relatively homogeneous species composition our new fallow sites showed limited overlaps in species composition within the old-growth forest and older fallow secondary forests. Species composition and reassembly regarded as key aspects of forest recovery study after disturbances (Valencia et al., 2014; Slik et al., 2008), and several studies reported that similarity between undisturbed forests and fallow regenerating fallow forests increase with an increase in the abandonment age (see – Norden et al., 2009; Piotto et al., 2009; Lawrence, 2004). In our nMDS ordination, two of the new fallow sites were wholly spread out, which may be a consequence of the intensity of past usage represented by fallow cycles that were not incorporated in our analysis. Interestingly, when considering IV of species on our sites, some dipterocarp species (e.g. Parashorea malaanoan) were found dominant across all sites which may be also attributed to remnant large canopy trees not interfering during agricultural use of the sites (Hager et al., 2014; Dawson et al., 2013).

Recovery of species richness and Shannon’s index was rapid in older fallow sites, although there was no significant difference in the recovery of species evenness. Recovery of stem density increased gradually with the fallow age. Recovery of stand basal area was distinct across the sites and was more inclined to our older fallow sites, an indication of more large and mature trees in those sites. In tropical forests the degree to which a forest recovered after disturbance is uncertain (Ding et al., 2012), although it is acknowledged that tropical forests after disturbances can recover in terms of species richness and stand structure (see – Letcher and Chazdon, 2009; Cannon et al., 1998). Unlike Martin et al., (2013), Letcher and Chazdon (2009) and Slik et al., (2008), who found rapid recovery of forest structure parameters over diversity during secondary forest succession, we found rapid recovery of forest tree diversity in our study sites.

3.5.2 Controls of site environmental conditions in forest recovery after shifting cultivation Patch size influences the recovery of species diversity and composition in our sites, and patch size on its own was found to have similar explanatory power for recovery of forest diversity and structure to more complicated models that include interactions of fallow age, slope and soil organic carbon. Echeverría et al. (2007) also found patch size as the single most important factor influencing both species composition and stand structure in terms of basal area and stem density. Both fallow age and fallow cycles influence the intensity of past forest use (Schmook, 2010; Lawrence, 2004), although, in our analysis, we only included the fallow age (as the cycle was not known). Biodiversity recovery in tropical disturbed secondary forests may depend on the remaining forest cover (Arroyo-Rodriguez et al., 2008), although the intensity of past use is a stronger predictor of forest recovery than edaphic environmental variables, highlighting the importance of humans in shaping tropical forest dynamics (Mukul et al., 2016; Ding et al., 2012; Castro-Luna et al., 2011; Klanderud et al., 2010).

While our study was limited to only soil organic carbon, which is an important indicator of soil fertility, our findings support those of Paoli et al. (2008) who found soil nutrients positively influence the recovery of forest structure parameters like basal area. We, however, found no significant effect of distance from the nearest old-growth forest on the recovery of any of the parameters studied in this study. Studies on secondary forest dynamics have demonstrated that diversity of woody species increases gradually with time, although the rate of recovery differs depending on site geographic location and associated environmental parameters (see - Ehrlen and Morris, 2015; Chazdon, 2014; Martin et al., 2013; Uddin et al., 2013; Klanderud et al., 2010; Lawrence et al., 2010; Piotto et al., 2009; Sovu et al., 2009; Read and Lawrence, 2003; Thompson et al., 2002). Previous studies (e.g. Ding et al., 2012; Schmook, 2010; N’Dja and Decocq, 2008) have reported that secondary forests may require different durations to attain the diversity and structure of an undisturbed forest after they have been abandoned. Fallow age however, did not affect the recovery of forest diversity measures when a common species pool occurs across the sites (Sovu et al., 2009). Slope of the stand was found to influence the stem number where highest stem density can be found in the down-slope and vice versa (Ding et al., 2006). Connectivity to primary forests increases forest regeneration by influencing natural processes like pollination and seed dispersal (Hager et al., 2014; Echeverria et al., 2007) although in our study it was not important. A declining trend in species richness with increasing distance to primary forest edge, however, may found (Sovu et al., 2009).

3.5.3 Implications for conservation and forest landscape management Our study confirms that regenerating tropical forests have the ability to recover after shifting cultivation, although site factors (patch size in our case) may be important during this recovery process. Throughout the tropics, secondary forests are expanding dramatically, and in many countries, they have already exceeded the total area covered by remaining primary or old-growth forests (McNamara et al., 2012; FAO, 2005; Chazdon et al., 2003). Those forests emerged after deliberate human use, and interventions are increasingly considered as a novel and/or emerging ecosystem with a different structure and species composition than previous land-use/cover (Hobbs et al., 2009; 2006). The successful maintenance of tree diversity in such novel ecosystems offers important synergies for conservation, as high plant diversity is associated with higher wildlife diversity (Koh and Ghazoul, 2010; Chazdon et al., 2009). In the case of the Philippines, secondary forest covers a large area and represent a highly dynamic ecosystem, making biodiversity conservation a daunting challenge in the country (Posa et al., 2008; Lasco et al., 2001).

We found that old kaingin fallow areas can also support relatively high numbers of rare and endangered species and thus can play an important role in their conservation. This is contrary to previous views that fallow landscapes are unfavorable for the maintenance forest biodiversity (see - Mo et al., 2011; Gemerden et al., 2003). The population status of rare and endemic species are highly relevant to the prioritization of conservation efforts globally (Peque and Holscher, 2014; Kier et al., 2009). Tropical forest-agriculture frontiers also provide important clues for conservation in complex, heterogeneous landscapes (Kumaraswamy and Kunte, 2013). We found that the number of endemics, climax and red-listed species was greater in relatively oldest fallow secondary forests. A number of dipeterocarp species, including Hopea philippinensis, Shorea polysperma, Shorea contorta – that are equally important for conservation both globally and locally, were shared among secondary forests of different fallow categories and in old-growth forest, indicates high conservation potential of such landscapes.

3.6 Conclusions It is clear that regenerating forests after shifting cultivation have the potentials to offset the tropical forests and biodiversity loss and have high resilience or recovering capacity. In the study species composition in secondary forests with fallow age more than five years were similar to the less disturbed old-growth forest, indicating a continious accumulation of species richness and abundance with fallow age. Recovery of tree diversity was rapid compared to the forest structure, and in all cases, young fallow secondary forest showed a divergent pattern of forest structure and diversity than that of our older fallow secondary forest categories. Although shifting cultivation has 61 a negative reputation for degradation and loss of tropical rainforests, little attention has been paid to study secondary forest dynamics in such complex landscapes. Our study indicates that novel ecosystems such as tropical fallow secondary forests that arise after deliberate human intervention exhibits high resilience and can act as a low-cost refuge for biodiversity conservation. Such landscape can also serve as a low restoration measure in tropical developing countries where shifting cultivation is common.

3.7 Additional information Supplementary Tables 3.1, 3.2, and Supplementary Figures 3.1, 3.2, 3.3, related to this chapter/manuscript is provided at the end of this thesis under the section – Appendices.

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Annex 3.1. List of tree species recorded from the sites in Gaas on Leyte Island, the Philippines.

Family Botanical name1 Local name Abundance Origin2 Conservation status Successional ≤ 5 year 6-10 year 11-20 year 21-30 year Old-growth IUCN3 DENR4 guild5 fallow fallow fallow fallow forest Alangiaceae Alangium javanicum (Bl.) Wang Putian - 4 3 3 5 Native LR NA Secondary Anacardiaceae Dracontomelon dao (Blanco) Merr. & Dao - 2 3 1 2 Native NA V Secondary Rolfe Dracontomelon edule (Blanco) Skeels. Lamio - 2 1 1 Native NA V Secondary

Annonaceae Cananga odorata (Lam.) Hook. f. & Ilang-ilang - 1 - - - Native NA NA Secondary Thomson Polyalthia oblongifolia Burck Lapnisan - 6 2 6 1 Native NA NA Secondary Polyalthia flava Yellow - 7 4 1 8 Endemic NA NA Secondary lanutan Apocynaceae Alstonia macrophylla G. Don Batino - 5 4 5 - Native LR NA Pioneer Alstonia parvifolia Merr. Batino-liitan - - 3 - - Endemic NA NA Pioneer Wrightia pubescens R.Br. Lanete 1 9 13 9 2 Native NA NA Pioneer Kibatalia gitingensis (Elmer) Woodson Laneteng- - 1 1 17 8 Endemic V CE Secondary gubat Araliaceae Arthrophyllum cenabrei Merr. Bingliu - - 9 - - Endemic NA NA Pioneer Polyscias nodosa (Blume) Seem. Malapapaya 2 51 83 97 14 Native NA NA Pioneer Arecaceae Areca cathecu L Bunga - - 5 8 - Native NA NA Secondary Cocos nucifera L. Coconut - - - 5 - Native NA NA Pioneer Caryota cumingii Lodd. ex Mart. Pugahan - 43 25 26 83 Native NA NA Pioneer Heterospathe elata Scheff. Sagisi - 6 6 2 15 Native NA NA Pioneer Bignoniaceae Radermachera pinnate (Blanco) Seem. Banai-Banai 2 28 24 11 2 Native NA NA Secondary

Burseraceae Canarium hirsutum Milipili - - 2 6 1 Native NA NA Secondary Canarium calophyllum Perkins. Pagsahingin- 1 11 10 8 12 Native NA NA Secondary bulog Canarium luzonicum (Blume) A.Gray Piling-liitan - 2 3 6 28 Endemic V NA Pioneer

Calophyllaceae Calophyllum lancifolium Elmer. Bitanghol- 2 3 - 2 - Native NA NA Secondary sibat Cannabaceae Trema orientalis (L.) Bl. Anabiong 1 - - - 2 Native NA NA Pioneer Celtis philippensis Blanco Malaikmo - - - 1 4 Native NA NA Secondary Casuarinaceae Casuarina equisetifolia L. Agoho 1 - 1 - - Exotic NA NA Pioneer Gymnostoma rumphianum (Miq.) Mountain 1 - - 1 - Native NA NA Secondary L.A.S. Johnson agoho Clusiaceae Calophyllum blancoi Planch. & Triana Bitanghol - 7 7 22 9 Native NA NA Secondary

Combretaceae Terminalia microcarpa Decne. Kalumpit - - 2 - - Native NA NA Secondary Cycadaceae Cycas circinalis L. Pitogo - - 1 - - Native E NA Pioneer Datiscaceae Octomeles sumatrana Miq. Binuang - - - 1 - Native LR NA Secondary Dilleniaceae Dillenia indica L. Handapara - 2 - 4 - Native NA NA Secondary Dillenia philippinensis Rolfe Katmon - 2 6 5 6 Endemic V NA Secondary Dipterocarpaceae Shorea almon Foxw. Almon - 2 - 3 Endemic CE V Climax Parashorea malaanonan (Blanco) Bagtikan 4 11 19 32 61 Native NA NA Climax Merr. 71

Dipterocarpus eurynchus Miq. Basilanapiton - - 1 - - Endemic CE E Secondary g Hopea philippinensis Dyer Gisok-gisok - 7 3 2 20 Endemic CE CE Pioneer Shorea guiso (Blanco) Blume Guijo - 15 8 4 31 Native CE NA Pioneer Shorea palosapis (Blanco) Merr. Mayapis - 3 9 5 12 Endemic CE NA Climax Anisoptera thurifera Palosapis - - - 1 - Native NA NA Secondary Shorea polysperma (Blanco) Merr. Tangile 2 6 8 14 5 Endemic CE V Climax Shorea contorta Vidal White lauan 2 5 16 6 4 Endemic CE V Climax Hopea malibato Yakal-kaliot - - - 1 - Native CE CE Climax Ebenaceae Diospyros pilosanthera Blanco Bolong-eta - 1 4 9 3 Native NA E Secondary Diospyros blancoi A.DC. Kamagong - 1 3 - 1 Native V CE Climax Euphorbiaceae Neotrewia cumingii (Müll.Arg.) Pax & Apanang - 3 3 2 4 Native NA NA Pioneer K.Hoffm. Mallotus philippensis (Lam.) Müll.Arg. Banato - 2 - - - Native NA NA Secondary

Macaranga tanarius (L.) Müll.Arg. Binunga - 5 4 2 7 Native NA NA Pioneer Macaranga bicolor Muell. -Arg. Hamindang - 9 1 8 5 Endemic V NA Pioneer Mallotus ricinoides (Pers.) Müll.Arg. Hinlaumo 1 5 12 5 - Native NA NA Pioneer

Fabaceae Ormosia calavensis Blanco Bahai - 34 3 19 2 Endemic NA NA Climax Albizia falcataria (L.) Fosberg. Falcata - 5 6 - Exotic NA NA Secondary Leucaena leucaephala (Lam.) de Wit. Ipil-ipil - - 7 3 - Exotic NA NA Pioneer

Pterocarpus indicus Willd. Narra 8 - - - - Native V NA Secondary Albizia saponaria(Lour.) Blume ex Salingkugi - 4 - 3 8 Native NA NA Secondary Miq. Senna siamea (Lam.) Irwin et Barneby Thailand - - 2 1 - Native NA NA Secondary shower Fagaceae Lithocarpus llanosii (A.DC.) Rehder Ulaian 2 17 28 27 16 Native NA NA Pioneer Hypericaceae Cratoxylum celebicum Bl. Paguriagon - 4 2 11 4 Native NA NA Secondary Lamiaceae Vitex quinata (Lour.) F. N. Williams Kalipapa - - 1 - 10 Native NA NA Pioneer

Vitex turczaninowii (Turcz.) Merr. Lingo-lingo - - - - 1 Endemic NA NA Secondary Premna cumingiana Schauer Magilik 1 - - - 2 Native NA NA Secondary Tectona grandis L. f. Teak - - - 1 - Exotic NA NA Pioneer Callicarpa elegans Hayek Tigau-ganda - - - 2 - Endemic NA NA Pioneer Lauraceae Cinnamomum cebuense Kostermans Kaningag - 2 2 2 - Endemic CE NA Pioneer Litsea perrottetii (Bl.) Villar. Marang - 5 2 8 4 Native NA NA Secondary Neolitsea vidalii Merr. Puso-puso - 7 3 6 Endemic V NA Secondary Lecythidaceae Barringtonia racemosa Spreng. Putat - 3 4 6 11 Native NA NA Pioneer Petersianthus quadrialatus (Merr.) Toog - - - 1 8 Endemic NA NA Pioneer Merr. Malvaceae Diplodiscus paniculatus Turcz. Balobo - 9 5 7 5 Endemic V NA Secondary Pterospermum obliquum Blanco Kulatingan - - - 1 2 Endemic NA NA Pioneer Melastomataceae Astronia cumingiana S.Vidal Badling - 4 8 7 3 Native CE NA Pioneer Meliaceae Dysoxylum decandrum Merrill. Igyo - 2 3 2 6 Native NA NA Pioneer Toona philippinensis Elmer. Lanigpa - 1 3 5 4 Native NA NA Pioneer Dysoxylum cumingianum C. DC. Tara-tara - 4 6 13 10 Native NA NA Pioneer Moraceae Artocarpus blancoi (Elmer) Merr. Antipolo 1 6 5 4 7 Endemic V NA Pioneer Artocarpus ovatus Blanco Anubing - - - 2 - Endemic NA NA Pioneer 72

Ficus irisana Elmer. Aplas - 5 9 7 1 Native NA NA Pioneer Ficus balete Merr. Balete 1 9 10 - 4 Native NA NA Pioneer Ficus gul K. Schum. & Lauterb. Butli 3 41 19 32 18 Native NA NA Secondary Ficus minahassae (Teijsm. & De Hagimit 4 19 15 4 4 Native NA NA Secondary Vriese) Miq. Ficus septica Burm. f. Hauili 2 3 18 - Native NA NA Secondary Ficus ulmifolia Lam. Is-is - 3 1 2 1 Endemic V NA Pioneer Ficus callosa Willd. Kalukoi - - 2 1 - Native NA NA Pioneer Ficus magnoliifolia Blume Kanapai - 6 2 1 - Native NA NA Secondary Ficus odorata (Blanco) Merr. Pakiling - 1 1 5 - Endemic NA NA Climax Ficus vrieseana Miq. Tagitig - - - 1 1 Native NA NA Secondary Ficus nota Merr. Tibig 1 21 17 2 7 Native NA NA Pioneer Ficus ampelas Burm. f Upling-gubat 12 1 - 6 Native NA NA Pioneer Myricaceae Myrica javanica Reinw. ex Bl. Hindang 1 - - - 3 Native NA NA Secondary Myristicaceae Knema mindanaensis (Warb.) comb. Bunod - 1 3 5 - Endemic NA NA Secondary nov. Parartocarpus venenosus (Zoll. & Malanangka 1 2 2 2 4 Native NA NA Pioneer Morr.) Becc. ssp. papuanus (Becc.) Jarr. Horsfieldia costulata (Miq.) Warb. Yabnob - 33 36 26 38 Native NA NA Pioneer Myrsinaceae Ardisia pyramidalis (Cav.) Pers. ex A. Aunasin - 8 6 4 12 Native NA NA Secondary DC. Myrtaceae Syzygium surigaense (Merr.) Merr. Kagagko - - - 2 3 Endemic NA NA Secondary Syzygium crassilimbum (Merr.) Merr. Kaitatanag - 1 1 2 - Endemic NA NA Secondary

Syzygium gigantifolium (Merr.) Merr. Malatalisai - 4 4 4 Endemic NA NA Secondary

Syzygium hutchinsonii (C.B.Robinson) Malatambis 1 10 11 12 5 Endemic NA NA Secondary Merr. Xanthostemon verdugonianus Naves Mangkono - - - 2 2 Endemic V NA Pioneer

Olacaceae Strombosia philippinensis (Baill.) Rolfe Tamayuan - 12 14 14 16 Endemic NA NA Secondary

Pandanaceae Pandanus radicans Blanco Ulangong- - - - 2 - Endemic NA NA Pioneer ugatan Phyllanthaceae Securinega fIexuosa (Muell. -Arg.) Anislag - 6 4 6 - Endemic NA NA Pioneer Antidesma ghaesembilla Gaertn. Binayuyu - 13 - 3 3 Native NA NA Climax Glochidion camiguinense Merr. Bunot-Bunot - 8 3 10 2 Endemic NA NA Pioneer Glochidion album (Blanco) Boerl. Malabagang - 1 1 2 3 Native NA NA Pioneer Breynia rhamnoides Müll.Arg. Matang-hipon - 3 2 2 - Native NA NA Pioneer Cleistanthus venosus C.B. Rob. Sarimisim - 2 1 - Endemic NA NA Secondary Bridelia penangiana Hook.f.Bridelia Subiang - 3 1 1 8 Native NA NA Secondary insulana Hance

Bischofia javanica Blume Tuai - 24 20 26 58 Native NA NA Secondary Piperaceae Piper anduncum L. Spiked pepper 3 - 3 1 5 Native NA NA Pioneer Rhizophoraceae Carallia brachiata (Lour.) Merr. Bakauan- - 4 2 1 1 Native NA NA Secondary gubat Rubiaceae Neonauclea formicaria (Elmer) Merr. Hambabalud - 6 7 7 2 Endemic NA NA Pioneer

Mussaenda philippica A.Rich. Kahoi-dalaga 1 1 - - - Native NA E Secondary Neonauclea bartlingii (DC.) Merr. Lisak - 1 6 4 5 Endemic NA NA Secondary Canthium fenicis (Merr.) Merr. Mapugahan - 2 - 4 - Endemic NA NA Pioneer Canthium monstrosum (A. Rich.) Merr. Tadiang- - 4 1 1 - Native NA NA Pioneer anuang Rutaceae Melicope triphylla (Lam.) Merr. Matang-arau - 4 4 3 1 Endemic NA NA Pioneer Sapindaceae Nephelium lappaceum Rambutan - - 1 - - Native LR NA Pioneer Sapotaceae Planchonella nitida (Blume) Dubard. Duklitan - - 1 9 - Exotic NA NA Secondary

Palaquium luzoniense (Fern.-Vill.) Nato - 11 2 8 16 Endemic V V Secondary Vidal Sterculiaceae Pterospermum diversifolium Bl. Bayok - - 4 1 1 Native NA NA Pioneer Tiliaceae Trichospermum involucratum (Merr.) Langosig - - 1 - - Endemic NA NA Pioneer Elmer Urticaceae Leucosyke capitellata (Pair.) Wedd. Alagasi 3 46 60 5 7 Native NA NA Pioneer Pipturus arborescens (Link) C. B. Rob. Dalunot - - 1 8 - Native NA NA Pioneer

Dendrocnide stimulans (L. f) Chew Lingaton - - - 1 - Native NA NA Pioneer Verbenaceae Premna odorata Blanco Alagau 1 - 2 - - Native NA NA Secondary Premna stellate Merr. Manaba - - 1 - - Native NA NA Secondary Vitaceae Leea aculeata Bl. Amamali - 1 3 - 5 Native NA NA Pioneer Unknown Anungo - 8 2 4 18 - - Secondary Nandamai - - - 1 - - - Pioneer Pandukaki - - - 1 - - - Pioneer Pegonngon - - - 1 - - - Secondary Poelig - 13 1 1 - - Pioneer Siyao 1 - - - - - Pioneer 1whenever possible species name was followed as per Species 2000 & ITIS Catalogue of Life, 2014 Annual Checklist (available online at: www.catalogueoflife.org/annual-checklist/2014/). 2where Endemic - refers to a species found only in the Philippines, Native – refers to a species naturally occurring in the Philippines and Exotic – refers to a species that has been introduced in the Philippines. 3as per IUCN Red List of Threatened Species (available online at: http://www.iucnredlist.org), where: CE or Critically endangered – refers to a species or subspecies facing extremely high risk of extinction in the wild in the immediate future. Endangered - refers to a species or subspecies that is not critically endangered but whose survival in the wild is unlikely if the causal factors continue operating. V or Vulnerable - refers to a species or subspecies that is not critically endangered nor endangered but is under threat from adverse factors throughout its range and is likely to move to the endangered category in the future. LR or Lower risk – refers to a species that has been evaluated, but does not satisfy the criteria for any of the categories Critically Endangered, Endangered or Vulnerable. NA or Not available/Not assessed – refers to a species that has not yet been assessed against the criteria. 4as per DENR Adminsitrative Order No. 2007.01, where:

CE or Critically endangered - refers to a species or subspecies facing extremely high risk of extinction in the wild in the immediate future. This shall include varieties, I formae or other infraspecific categories; E or Endangered - refers to a species or subspecies that is not critically endangered but whose survival in the wild is unlikely if the causal factors continue operating. This shall include varieties, formag or other infraspecific categories; V or Vulnerable - refers to a species or subspecies that is not critically endangered nor endangered but is under threat from adverse factors throughout its range and is likely to move to the endangered category in the future. This shall include varieties, formae or other infraspecific categories; 5based on experts opinion from the Philippines.

CHAPTER 4: TROPICAL SECONDARY FORESTS REGENERATING AFTER SHIFTING CULTIVATION IN THE PHILIPPINES UPLANDS ARE IMPORTANT CARBON SINKS

May cite as – Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6, 22483.

4.1 Abstract In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin secondary forests in an upland area in the Philippines. We found significantly higher carbon in the aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood biomass carbon was higher in the young fallow secondary forest. Aboveground total biomass carbon in our new, young, moderately aged and oldest fallow sites were 160.3 Mg ha-1, 101.09 Mg ha-1, 122.41 Mg ha-1, and 132.54 Mg ha-1 respectively compared to 321.29 Mg ha-1 in old-growth forest. The high level of aboveground biomass carbon in new fallow sites was due mainly to high levels of coarse dead wood remaining as an artefact of clearing. For young through to the oldest fallow sites, there was a progressive recovery of biomass carbon evident. Multivariate analysis indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in secondary forests after shifting cultivation. Our study indicates secondary forests after shifting cultivation are substantial carbon sinks and that this capacity to store carbon increases with abandonment age. Large trees contribute most to aboveground biomass, with one species, Parashorea malaanonan, contributing 33.2% to the overall living wood biomass across the sites. A better understanding of the relative contribution of different biomass sources in aboveground total forest biomass, however, is necessary to fully capture the value of such landscapes from forest management, restoration and conservation perspectives.

Key-words: biomass carbon; regenarating forest; shifting agriculture; REDD+; Southeast Asia.

4.2 Introduction Secondary forests comprise more than half of the total forest area in tropical regions and are the dominant forest type (FAO, 2010). In the tropics, secondary forests also represent a major 76 global carbon sink that rapidly accumulates carbon in aboveground biomass (Pan etal., 2011; Eaton and Lawrence, 2009; Malhi et al., 2006). Because they cover a large area in the tropics, accurate estimates of carbon in secondary forests are critical for quantifying the global carbon balance as well as for the successful implementation of climate change mitigation projects (Chave et al., 2014). However, there remains a high level of uncertainty in tropical forest carbon accounting, firstly due to the unknown amount of deforestation and forest degradation (Malhi, 2010), and secondly due to a limited number of field studies that have estimated standing biomass in secondary forests (Chave et al., 2005). In fact, globally tropical deforestation and forest degradation accounts for approximately 15-35% of anthropogenic carbon emissions (DeFries et al., 2002), and reversing this trend has a clearly recognized potential for recovering the stocks of forest biomass carbon and for other forest conservation outcomes (Houghton, 2012).

Shifting cultivation or ‘slash-and-burn agriculture’ is a traditional land-use practice in tropical forested landscapes, and is a dominant land-use in rural upland areas in the developing countries (Mertz et al., 2009). In the tropics, shifting cultivation has also been seen as the primary source of deforestation and forest degradation for many years (Lawrence et al., 2010; Fox et al., 2009). Historically, shifting cultivation has been viewed negatively as contributing to many forms of environmental degradation, including loss of biodiversity and biomass carbon in forests (van Vliet et al., 2012). Accordingly, throughout much of the tropics, governments have developed policies to control or reduce the practice of shifting cultivation by smallholder rural farmers (Fox et al., 2009).

In Southeast Asia, secondary forests constitute around 63% of the total forest area (Koh, 2007), with an estimated 14-34 million people dependent on shifting cultivation for their livelihoods (Mertz et al., 2009). The extent of land under shifting cultivation however has declined in recent years due to government policies restricting shifting cultivaton and economic factors that promoted other land- use systems (van Vliet et al., 2012; Fox et al., 2009). Consequently, in many parts of this region regenerating secondary forests following shifting cultivation are becoming prominent (Pelletier et al., 2012; Lawrence et al., 2010; Mertz et al., 2009). Due to the dynamic nature of the landscape, shifting cultivation and its changes over time have been very difficult to delineate using satellite based earth observation systems (Houghton, 2012; Pelletier et al., 2012). In Southeast Asia there is also a lack of spatially explicit knowledge of the forest biomass carbon stocks and carbon dynamics associated with shifting cultivation landscapes. This has limited the inclusion of these landscapes in current negotiations on Reducing Emissions from Deforestation and Forest Degradation (REDD+) in the region to achieve the dual objectives of community development and forest conservation (Ziegler et al., 2012). 77

In this paper, we report aboveground biomass carbon distribution along a fallow gradient in an upland secondary forest of the Philippines after shifting cultivation. The Philippines, is both a mega-diverse country and a global biodiversity hotspot, placing it amongst the top priority countries for global conservation (Posa et al., 2008; Myers et al., 2000). As in other parts of the developing tropics, shifting cultivation, known as kaingin in the Philippines, is a common and controversial land-use in the country (Saurez and Sajise, 2010). In fact, secondary forests developed after shifting cultivation forms the second largest group of forest in the country after post logging secondary forests (Lasco et al., 2001). In this paper we also investigate the determinants of biomass carbon recovery in fallow secondary forests, which remain largely overlooked throughout the tropics (Taylor et al., 2015; Malhi et al., 2006). We believe the present study helps address the existing gaps in knowledge on biomass carbon changes and recovery after forest degradation in Southeast Asia which is still largely biased towards the neotropics (see - Ngo et al., 2013, Saner et al., 2012, Kenzo et al., 2010 for example). The study is one of the first attempts to systematically assess the carbon in secondary forests associated with slash-and-burn fallows; and will thus substantially improve our understanding of the role that such landscapes play as a sink of atmospheric carbon for both the Philippnes and other tropical developing countries.

4.3 Methods 4.3.1 Study area The study was conducted in Barangay (the smallest administrative unit and native Filipino term for village) Gaas on Leyte Island, the Philippines (Figure 4.1). Leyte is the eighth largest island in the Philippines, and our study site was located on the western side of the island. Geographically, Leyte is located between 124017/ and 125018/ East longitude and between 9055/ and 11048/ North latitude, and covers an area of about 800,000 ha. Forest cover on the island is about 10%, although the once dipterocarp-rich rainforests now comprise mainly patches of old-growth and primary forests, and coconut (Cocos nucifera) and Abaca (Musa textilis) plantations (Asio et al., 1998). The relatively flat lowlands of the island are being used for agricultural crop production, especially rice (Oryza sativa) and corn (Zea mays) (Asio et al., 1998).

Figure 4.1. Map of the Philippines (a), with location map of Barangay Gaas on Leyte Island (b) and our study sites in Gaas (c). Spatial position of the site locations were plotted in global geo-political boundary available from Esri (http://www.arcgis.com/) using ArcMap (version 10.3) software.

Leyte Island was formed from tectonic movement and plate convergence which started during the tertiary and quaternary age (Aurelio, 2000; Asio et al., 1998). Based on the Coronas Classification of Climate, Leyte has a ‘type IV’ climate with two distinct season (Navarrete et al., 2013). The area enjoys a relatively even distribution of rainfall throughout the year with annual rainfall totalling approximately 4,000 mm (Jahn and Asio et al., 2001). Mean annual temperature is 280C which remains constant throughout the year (Navarrete et al., 2013). Relative humidity ranges between 75 to 80 percent during the dry and the wettest months (Kolb, 2003). The soil in our study area in Gaas was an Andisol type which possesses a markedly higher soil organic carbon content than rest of the islands (Navarrete et al., 2013).

4.3.2 Site selection We chose Barangy Gaas (also refer to as Gaas) purposively. This area of Leyte is situated in a comparatively high altitudinal range and compared to other parts of the island it has a relatively greater extent of undisturbed forests. It also has a low population density. These critieria are prerequisites for the kaingin fallow to regrow as secondary forests (Chokkalingam et al., 2006). For

79 our study we consider only the dahilig kaingin system which is identical to the most common practice of shifting cultivation in the tropics (see Olofson (1980) for details of the Philippines kaingin systems). Smallholder farmers living in the area usually grow Abaca or coconut in their fallow kaingin area in order to receive financial benefits during the time of abandonment. Our study was however confined to the areas where farmers cultivated only Abaca since coconut plantations generally involve more intensified land-management during the fallow periods and this is not conducive for secondary forest development.

4.3.3 Biomass Inventory A series of extensive field surveys were undertaken at the sites between May and October 2013. For the biomass inventory we followed a modified Gentry plot approach (Gentry, 1982). This method has been reported as the most efficient for monitoring secondary forest development in tropical regions (Baraloto et al., 2013). We categorized our sites into four different fallow categories; i.e. less than 5 year old fallow (SA0-5), also referred to as new, 6-10 year old fallow (SA6-10) also referred to as young, 11-20 year old fallow (SA11-20) also referred to as middle- aged, and 21-30 year old fallow (SA21-30) also refered to as oldest. We limited our study to fallow forest sites that were at least 1 ha in size (Piotto et al., 2009). Additionally, we sampled old-growth forest (SF) as control forest sites. These forests had no history of kaingin and logging and were located close to our fallow sites. Our control forest sites were structurally and floristically similar to primary forests although they may have undergone a limited level of anthropogenic use (e.g. source of firewood, wild fruits etc.) like most of the forest in the tropical forest-agriculture frontiers.

We identified a total of 25 sites (four fallow categories + old-growth forest x five replicates). Both the fallow age and fallow cycles have been reported to influence the biomass dynamics in secondary forests (Eaton and Lawrence, 2009). In our study we were only able to consider the fallow age and not the fallow cycles due to a lack of reliable information about past site history. At each site, four transects of 50 m x 5 m were established parallel to each other and with a minimum of 5 m distance between transects, representing a total area of 0.1 ha per site. For standing live trees and palms ≥5 cm diameter at breast height (dbh) we recorded diameter and height of each individuals at 1.3 m from the ground or above stem abnormalities (e.g. buttresses, stilt roots etc.). All individuals were identified to the species level and named with the help of a local expert from Visyas State University (VSU). In the case of unknown species we used the most common Filipino name for that species. We also measured all tree ferns and Abaca ≥5 cm dbh in our transects as other living biomass because they represent a major component of secondary forest succession in post-kaingin secondary forests in the Philippines (Suarez and Sajise, 2010). Lianas were not 80 included in our study. For measuring the dbh of individual tree stems we used diameter tapes. We used a hypsometer for tree height measurements, although the closely-structured canopy in tropical forests sometimes made it difficult to measure tree heights with a high reliability.

Since slashing and burning is a common practice in shifting cultivation landscapes, coarse dead wood biomass in the form of felled, degraded and burnt trees comprise a significant part of the total aboveground biomass in such areas (Pelletier et al., 2012; Mertz et al., 2009). Consequently we censused all dead, cut and burnt trees ≥5 cm at dbh that fell within in our transects. For each individual stem, we recorded whether it was standing or downed (i.e. fallen), and the degradation staus, categorized as – freshly cut, moderately decomposed, highly decomposed and burnt (Ngo et al., 2013). For litter and undergrowth (i.e. seedlings, saplings, shrubs and herbaceous plants) we followed a destructive sampling approach. A 1 m x 1 m rectangular plot was laid in the centre of each of our 100 transects distributed in 25 sites, and all litter and undergrowth samples were collected and weighed in the plot using a measuring balance.

Additionally, for each site we recorded the site geographic position, elevation (E), distance from the nearest control forest (D), patch size (PS), slope (SL), leaf area index (LAI) and soil organic carbon (SOC) as a percentage. We used a digital plant canopy imager (Model: CID Bio-Science, CI- 110/120) for measuring leaf area index and a hand-held global positioning system (Model: Garmin eTrex) for elevation (Supplementary Table 4.1).

4.3.4 Biomass calculation in forest ecosystems There is no allometric equation which is specifically developed for the secondary forests in the Philippines (Lasco et al., 2004), Consequently we used the generic allometric model develeoped by Chave et al. (2014).

AGB = 0.0673 x (ρD2H)0.976

Where, AGB or aboveground dry biomass is in kg, D is the dbh in cm, H is the height of the tree and/or palm in m and ρ is the species specific wood density (g cm-3). This model performed better than the widely accepted previous model by Chave et al., (2005), and performed well across all forest types and bioclimatic conditions (Chave et al., 2014). The inclusion of tree height in this model provides more reliable estimates of biomass, compared to the pervious models that used only diameter in the model (Chave et al., 2014; Hunter et al., 2013). Moreover, this model is based on 58 global sites distributed across the tropics where the previous model was based on 27 global sites 81

(Chave et al., 2014, 2005). For species specific wood density we used the World Agroforestry Centre’s wood density database where wood density was the ratio of dry mass to the green volume (World Agroforestry Centre, 2014) (Supplementary Table 4.2). In the case of unknown species or where wood density was not available, we took the mean wood density of the genus as a substitute (Saner et al., 2012).

For tree ferns and Abaca we used the following allometric models developed by Stanley et al. (2010) and Armecin and Coseco (2012) respectively.

AGB = 1135.3D - 4814.5 AGB = 5.1164 / (1+1343.02e-0.1550D) where AGB for ferns and Abaca is respectively in g and kg, and D is the diameter of individuals in cm.

The volume of coarse woody debris per area was calculated from transect data, and we used the following equation to obtain the volume of individual stems that fell within or intersected our transects.

V = π2D2 / 8L

Where, V is the volume per stem, L is the total length of the stem (of coarse woody debris) that fell within or intersected our transects in m and D is the diameter of coarse woody debris. Wood density was determined locally by the water displacement method taking representative samples (n = 5) for each of the four wood degradation status (i.e. freshly cut, moderately decomposed, highly decomposed and burnt), and were 0.48 g cm-3, 0.35 g cm-3, 0.25 g cm-3 and 0.19 g cm-3 respectively for our freshly cut, moderately decomposed, highly decomposed and burnt wood samples (Delaney et al., 1998). All biomass measurements were first made at the site level (Mg), and then converted to a per hectare (ha) value after correcting plot size or transect length for the slope (Pelletier et al., 2012).

4.3.5 Estimating carbon in aboveground forest biomass In our study total aboveground biomass carbon (AGTBC) is the sum of aboveground living woody (tree and palms) biomass carbon (LWBC), other living biomass carbon (OLBC) measured for tree ferns and Abaca, coarse dead wood biomass carbon (CDWBC), undergrowth biomass carbon 82

(UBC), and litter biomass carbon (LBC). To convert the aboveground biomass of trees we assumed that 50% of the dry mass was carbon (Brown, 1997). Studies at nearby sites with similar forest types have found average carbon content close to 50% (Saner et al., 2012; Kenzo et al., 2010; Lasco et al., 2004). For tree ferns and Abaca, carbon content was assumed to be 50% and 47.3% respectively by total dry biomass after Armecin and Coseco (2012) and Beets et al. (2012).

Measuring of the dry biomass litter and undergrowth samples was undertaken in the VSU-ACIAR Analytical Chemistry Laboratory. The samples were air dried at room temperature and then grinded using an electric grinder. The samples were then oven dried at 70oC for 24 hours and weighed. A representative subsample from each of the litter and undergrowth samples was analysed for estimating the carbon content (% C‐Heanes) (Supplementary Table 4.3). In the case of coarse woody debris we took 5 subsamples from each of the degradation states as mentioned earlier, and the carbon content was measured locally in the laboratory (Supplementary Table 4.4).

4.3.6 Estimating the recovery of biomass carbon in forests We compared the recovery of biomass carbon in different aboveground components with that of the control old-growth forests. We combined both tree fern and Abaca as other living biomass carbon (OLBC) during the analysis due to their relatively low contribution to AGTBC. Recovery (R) was expressed as a percentage (%) of biomass carbon using the following equation.

R =( Xfallow / Xs) × 100

where 푋fallow is the measure of biomass carbon in a fallow site, and 푋s is the mean of corresponding biomass carbon in a similar ecosystem in the control old-growth forest.

4.3.7 Statistical analysis We performed both the analysis of variance (ANOVA) and Tukey’s post-hoc test to test any significant difference between the variables. We developed linear mixed-effect models (also refered to as LMEM) to examine the effect of fallow age and selected site attributes (see Supplementary Table 4.1) on recovery of biomass carbon, using the package ‘nlme’. In our LMEM, fallow age (FA), slope (SL), distance from the nearest control forest (DIS), patch size (PS), leaf area index (LAI) and soil organic carbon (SOC) were used as explanatory variables (i.e. fixed factors), and biomass carbon in different forest strata was the response variable. We used sites nested in fallow categories as the random effect in our models. Due to their high collinearity with other explanatory variables, ‘elevation’ and ‘LAI’ were excluded from the final LMEM (Supplementary Table 4.5). 83

All analyses were performed using ‘R’ Statistical package (version 3.0.1). We considered Akaike Information Criterion corrected for small sample sizes (AICc) for the selection of our top models, where the best models had the lowest AICc scores. We used the R-package ‘MuMin’for our model selection, to evaluate the contribution different fixed effects had on explaining the variabiont in the response variables (Bartoń, 2011). We considered models within four AICc units to be equivalent models (Grueber et al., 2011).

4.4 Results 4.4.1 Distribution of biomass carbon in fallow secondary forests We measured the biomass of 2918 living tree stems (representing 131 species), 184 tree ferns and 124 Abaca plants (Musa textilis, a species of banana native to the Philippines) in our study sites covering a total sample area of 2.5 ha. Tree ferns and Abaca are characteristic species in fallow secondary forests in the area and we include them due to their common occurrence in our study sites. Within our transects we also encountered 1281 pieces of dead woody debris that met the criteria for inclusion for biomass measurement. Using existing allometric models our study thus across all sites finds 328.2 Mg C in the living woody biomass (LWBC), 1.18 Mg C in other living biomass (OLBC; i.e. tree fern and Abaca), 88.83 Mg C in coarse dead wood biomass (CDWBC) and 0.02 Mg C in undergrowth (UBC) and litter biomass (LBC). Aboveground total biomass carbon

(AGTBC) was significantly (F4 = 6.07, p < 0.01) higher in old-growth forest than the secondary forests of all fallow categories. We found that, carbon in both living woody biomass and coarse dead wood biomass varied significantly (F4 = 9.54, p < 0.01) across the sites of different kaingin history as expressed by their fallow age (i.e. post kaingin period) and in our control old-growth forest (Annex 4.1). There were however no significant differences among the sites when we considered the carbon stored in other living biomass and in undergrowth and litter biomass (Figure 4.2). Our post-hoc analysis using Tukey’s HSD revealed significantly higher (321.29 ± 130.96 Mg C; p < 0.01) aboveground total biomass carbon in old-growth forest followed by our new (i.e. SA 0- 5) and oldest (i.e SA 21-30) kaingin fallow sites. LWBC was also significantly higher (316.96 ± 130.63 Mg C; p < 0.01) in old-growth forest sites accounting for 98.65% of the AGTBC, whilst CDWBC was highest (126.65 ± 22.58 Mg C; p < 0.01) in our new kaingin fallow sites with an estimated 79% contribution to the AGTBC (Figure 4.3).

Figure 4.2. Distribution of aboveground biomass carbon (Mg ha-1) in our study sites on Leyte Island, the Philippines. Each bar indicates upper, lower and median values of biomass carbon allocation, and standard deviation of C allocation under corresponding site category. Note the differences in the Y axis.

Parashorea malaanonan had the highest contribution (33.23%) to the overall LWBC, and had relatively greater contribution to all of our fallow sites and old-growth forest. Other than P.

85 malaanonan, Lithocarpus llanosii, Ficus balete and Shorea contorta contributed respectively 6.39%, 5.32% and 3.89% to the overall LWBC (see Supplementary Table 4.6). In old-growth forest Calophyllum blancoi (5.69%), Petersianthus quadrialatus (5.26%) and Bischofia javanica (4.79%) were other major sources of biomass carbon in living woody stems. When considering species successional guild, climax species were the highest contributers (48.93%; p < 0.01) to LWBC in old-growth forest sites followed by the oldest kangin fallow sites (i.e. SA 21-30) (Figure 4.4). Similarly , the contribution of native species to LWBC was also significantly higher in the old- growth forest (80.81%; p < 0.01) (Figure 4.4). As expected, large diameter stems had the greatest contribution to the LWBC in our fallow sites, and a significantly high contribution in the old-growth forest (43.28%; p < 0.01) (Supplementary Figure 4.1). It was a similar case when considering stem heights, where woody stems attaining heights between 30-50 m constituted about 30.11% of the LWBC, which was a significantly higher (p < 0.01) contribution than other height classes (Supplementary Figure 4.2). In the case of OLBC as measured for tree fern and Abaca, we found no significant difference in biomass carbon allocation across the sites.

Figure 4.3. Relative contribution of different source to the total aboveground biomass carbon stock in our sites on Leyte Island, the Philippines.

In the case of CDWBC, carbon stored in standing dead wood was significantly higher (p < 0.01) in our new fallow sites contributing about 85.49% to the CDWBC (Figure 4.5). There were no significant differences in the carbon stored in downed dead wood in our sites of different fallow categories. Post hoc analysis however revealed significantly different (p < 0.05) carbon in downed 86 dead wood in new fallow sites and old-growth forest. In new fallow sites the amount of carbon stored in the freshly cut wood was also highest (91.03%; p < 0.01), and there were no significant differences in carbon stored in moderately decomposed, highly decomposed and burnt dead wood in different fallow sites and in old-growth forest (Figure 4.5). Similarly, we found no significant difference in biomass carbon in litter and undergrowth between our fallow secondary forest sites and in old-growth forest.

Figure 4.4. Relative importance of different successional species groups in living woody biomass carbon (LWBC) (left); and species of different origin in LWBC. Values in the bars indicate absolute contribution (Mg C ha-1) to LWBC of individual category.

Figure 4.5. Relative importance of coarse dead wood of different stand form in coarse dead wood biomass carbon (CDWBC) (left); and dead woods of different degradation status in CDWBC (right). Values in the bars indicate absolute contribution (Mg C ha-1) to CDWBC of individual category.

4.4.2 Recovery of biomass carbon in fallow secondary forests When compared with old-growth forests used as our control, overall we found that AGTBC was highest (49.89 ±17.39) in the new (i.e. SA 0-5) fallow sites, followed by our oldest fallow sites (41.25 ±17.76), middle-aged (i.e. SA 11-20) sites (38.10 ±23.33), and in the young (i.e. SA 6-10) sites (31.46 ±17.42). The high amount of AGTBC in our new fallow sites was mainly driven by the large amount of CDWBC remaining in the sites after being cleared and/or used for kaingin. Although there was no significant difference, the recovery of LWBC was highest in the oldest fallow sites (37.86%), followed by the middle-aged sites (35.28%), young fallow sites (23.4%) and the new fallow sites (10.54%) (Figure 4.6). There was no significant difference in the recovery of OLBC (in tree fern and Abaca) across our sites, except in the case of new kaingin fallow sites and young fallow sites where it was significantly different (p < 0.05). The amount of CDWBC in relation to that in the control old-growth forest sites was significantly different (F3 = 47.42, p < 0.01) across the fallow categories, and was significantly higher in the new kaingin fallow sites (i.e. SA 0-5). In fallow secondary forests, woody debris is ultimately lost from the ecosystem with the increasing fallow age but at the same time the regrowth of vegetation offsets the large loss in dead wood in the area. There was however no significant difference in the recovery of undergrowth and litter biomass carbon (ULBC) across our fallow sites (of different age categories) compared with the control old-growth forest.

Figure 4.6. Distribution of aboveground biomass carbon in fallow secondary forest sites in relation to the old-growth forests on Leyte Island, the Philippines. Each bar indicates upper, lower and median values of biomass carbon recovery, and standard deviation of C recovery under corresponding site category. Note the differences in the Y axis.

4.4.3 Factors influencing the recovery of aboveground biomass carbon in fallow secondary forests Patch size was found to consistently explain the variation in the response variables (i.e. percentage recovery of living woody biomass carbon, LWBC; other living biomass carbon, OLBC; coarse dead wood biomass carbon, CDWBC; and undergrowth and litter biomass carbon, ULBC). It also explained the similar amount of variation (models within ∆AIC = 4 are considered equivalent) found in other complex models with more interactions among explanatory variables (Table 4.1; Table 4.2). Soil organic carbon, fallow age and the slope of a site were also important in explaining the variation in the recovery of different parameters investigated. Distance from the control forest sites was not retained in any of the best fit candidate models.

Table 4.1. Summary of LMEM between site biomass recovery with environmental attributes obtained using the package MuMin (Bartoń 2011). Where, LWBC = living woody biomass carbon, OLBC = other living biomass carbon, CDWBC = coarse dead wood biomass carbon, ULBC = undergrowth and litter biomass carbon, FA = fallow age, DIS = distance (from the nearest control forest site), SL = slope, PS = patch size, SOC = soil organic carbon. Parameter Explanatory variable DF LL AICc ∆ AICc Weight FA DIS SL PS SOC LWBC X X 6 -68.93 157.51 0.00 0.31 X 5 -71.81 158.62 1.12 0.18 X X 6 -69.88 159.40 1.90 0.12 X X X 7 -67.14 159.48 1.98 0.11 X X X 7 -67.50 160.20 2.70 0.08 X X X 7 -67.52 160.25 2.74 0.08 X X 6 -70.34 160.31 2.81 0.08 X 5 -73.04 161.07 3.57 0.05 OLBC X X X X 8 -121.09 271.28 0.00 0.47 X X X 7 -124.55 272.44 1.16 0.27 X X X 7 -124.90 273.12 1.85 0.19 X X 6 -128.31 275.08 3.80 0.07 CDWBC X X X X 8 -127.61 284.31 0.00 0.76 X X X 7 -131.62 286.57 2.26 0.24 ULBC X X X 7 -92.14 207.62 0.00 0.55 X X 6 -95.83 210.13 2.51 0.16 X X X X 8 -90.61 210.32 2.70 0.14 X X X 7 -94.08 211.50 3.89 0.08 X X 6 -96.57 211.60 3.98 0.07 *DF— Degree of Freedom, LL— Log Likelihood, AIC—Akaike Information Criterion corrected for small sample size; **Values in the bold indicate the most influential model describing the variation in biosmass carbon recovery.

Table 4.2. The relative importance of site environmental attributes in the final LMEM. Where, LWBC = living woody biomass carbon, OLBC = other living biomass carbon, CDWBC = coarse dead wood biomass carbon, ULBC = undergrowth and litter biomass carbon, FA = fallow age, DIS = distance (from the nearest control forest site), SL = slope, PS = patch size, SOC = soil organic carbon. Parameter Explanatory variable* Number of FA DIS SL PS SOC models LWBC 0.27 (3) - 0.28 (3) 0.95 (7) 0.55 (4) 8 OLBC 0.74 (2) - 0.66 (2) 1.0 (4) 1.0 (4) 4 CDWBC 1.0 (2) - 0.76 (1) 1.0 (2) 1.0 (2) 2 ULBC 0.77 (3) - 0.22 (2) 1.0 (5) 0.93 (4) 5 *Values in the parenthesis indicate the number of models containing respective explanatory variable. 90

4.5 Discussion 4.5.1 Biomass carbon distribution in tropical fallow secondary forests We show that secondary forests after shifting cultivation are significant sinks for above ground carbon. We also show the relatively greater contribution of older fallow areas over young fallow areas as a carbon sink after being used for shifting cultivation in the upland Philippines. In this area, carbon stored in old-growth forests, oldest fallow areas and moderately-aged fallow areas were 321.29 (±130.96) Mg ha-1, 132.54 (±57.07) Mg ha-1 and 122.41 (±74.95) Mg ha-1 respectively, which is comparable to the carbon pools reported from other forests in the Philippines (Lasco and Pulhin., 2009; Lasco et al., 2006, 2004). These studies found carbon stored in aboveground biomass ranged between 117.9-305.5 Mg ha-1. This estimate is also greater than the upland forests that were selectively logged (Lasco et al., 2006).

The allometric models and sampling approach used may introduce errors in the estimates of carbon, and thus both may have substantial influences on the results of groundbased forest carbon estimates (see - Chave et al., 2005; Ketterings et al., 2001; Brown, 1997). Locally developed and calibrated allometeric models have the potential to minimize this uncertainty in tropical forest carbon accounting (Chave et al., 2005). In our study, we used the most recent allometric model developed by Chave et al. (2014) for estimating living woody biomass in tropical forests. Studies on biomass dynamics and forest carbon stocks are biased towards the neotropics, with very limited systematic inventory reported so far from Southeast Asian secondary forests (e.g. Ngo et al., 2013; Saner et al., 2012; Kenzo et al., 2010). The model developed by Chave et al. (2014) is reported to underestimate the aboveground living biomass by 20% when observed biomass exceeded 30 Mg for individual stems, although this trend disappears when a stem’s biomass is between 10-30 Mg (Chave et al., 2014). We found that stem density was not the main factor in determining carbon stored in living woody biomass, but diameter and height of individual stems had a better ability to control biomass carbon distribution in forests which is consistent with the observations made by Rozendaal and Chazdon (2015), Marin-Spiotta et al. (2007), Lasco et al. (2006), and Lawrence (2005) respectively in the Costa Rica, Puerto Rico, Philippines and Indonesia. We also found that, in old-growth forests and in older fallow secondary forests climax species contributed the most in terms of aboveground living woody biomass carbon, which is also in accordance with the finding of Rozendaal and Chazdon (2015). This may reflect the persistence of mature remnant trees in fallow forest when converted from old-growth stands (Lawrence, 2005). For example, in all of our fallow sites and old-growth forest Parashorea malaanonan consistently made the highest contribution to living woody biomass. In contrast, McNamar et al. (2012) have found limited difference in the occurrence of old-growth forest specialist species in secondary forests with different disturbance 91 history in Lao PDR, and argued that it may due to the high resilience capacity of certain species and their quick resprouting ability.

In young kaingin fallow areas the ‘other living standing biomass’ (i.e. tree ferns and Abaca in the present study) and coarse dead biomass constitute a major part of the aboveground biomass carbon. This depicts a very different composition in landscape scale total aboveground biomass carbon than that of old-growth forest and older kaingin fallow areas. This is largely due to the long disturbance (and use) history and the large remaining amount of dead wood on sites after being used for shifting cultivation (Eaton and Lawrence, 2009). However, Orihuela-Belmonte et al. (2013) have found that in Mexico coarse dead wood biomass carbon is higher in older fallow areas and also significantly different across sites of different fallow age. Similar to our findings, Pelletier et al. (2012) also reported that aboveground forest biomass carbon is not very different between old-growth forest and older fallow areas, but is different between young fallow areas and old-growth forest.

4.5.2 Factors influencing the biomass carbon recovery in fallow secondary forests Recovery of aboveground living tree biomass carbon was highest in the oldest fallow sites and lowest in the new kaingin fallow areas, although living tree biomass is the first pool to be affected when forests are converted for shifting cultivation use. Coarse dead biomass carbon was high in the new kaingin fallow sites compared to the control old-growth forest site, reflecting the high amount of coarse dead wood in new and relatively young kaingin fallow sites remaining after clearing these areas. Other living biomass carbon was highest in the young kaingin fallow areas representing the dynamic nature of such landscapes, where undergrowth and litter biomass carbon is found to increase gradually from new to oldest kaingin fallow sites. Several studies have found that aboveground biomass carbon recovers rapidly during early successional years after abandonment, followed by a relatively slow recovery rate after reaching a peak or intermediate stage (Raharimalala et al., 2012; Kenzo et al., 2010; Letcher and Chazdon, 2009; Lawrence, 2005). Such recovery may take place at a rate of between 3.75-9.4 Mg C ha−1 year−1 and may take as long as 55- 95 years (Kenzo et al., 2010; Read and Lawrence, 2003; Kotto-Same et al., 1998). In tropical old- growth forests, annual rates of biomass carbon change are typically lower than forests that have been subject to different levels of anthropogenic disturbance (Valencia et al., 2009), and in such forests the biomass carbon accumulation rates also decrease with an increasing stand age after reaching an intermediate age (Rozendaal and Chazdon, 2015; Martin-Spiotta et al., 2007).

We found that biomass carbon recovery was constrained mainly by landscape patchiness. In our LMEM patch size showed a consistent control in determining the recovery of biomass carbon at 92 different aboveground levels. In tropical forests, environmental determinants of such recovery as well as its magnitude are still poorly quantified (Taylor et al., 2015; Malhi et al., 2006). Changes in biomass carbon are also driven by the growth and mortality of trees, although such changes are difficult to monitor and require long-term monitoring (Lasky et al., 2014). It is however clear from our study that aboveground living tree biomass is the most vulnerable carbon pool in tropical secondary forests. A similar observation is also made by Kotto-Same et al. (1998). Other environmental factors that also influence the variation in recovery rates are soil organic carbon, fallow age and slope of a site. Distance from the nearest control old-growth forest was found to be unimportant in our LMEM. In the case of other living biomass carbon and coarse dead wood biomass carbon recovery, there was no notable pattern in the LMEM, which may be attributed to the fact that these components have the smallest contribution to our old-growth forest total aboveground biomass carbon.

Chronosequence studies are a widely used approach to investigate secondary forest and successional developments after disturbances (Mukul and Herbohn, 2016; Rozendaal and Chazdon, 2015; Blanc et al., 2009). Both fallow age and fallow cycles offers an indication of previous forest use (Lawrence, 2005), although the present study was limited to only fallow age as the number of cycles was unknown. We found that recovery of standing living woody biomass carbon was distinct across sites of different categories and was superior in older kaingin fallow sites. In young fallow areas, although the number of stumps was higher, biomass carbon recovery was higher in sites with larger diameter trees as also mentioned by Rozendaal and Chazdon (2015). Many environmental factors influence secondary forest recovery after disturbances (Martin et al., 2013; Lawrence et al., 2010), and studies have demonstrated different recovery rates depending on the site’s geographic position together with biotic and abiotic attributes (Lawrence et al., 2010; Piotto et al., 2009; Read and Lawrence, 2003).

Biomass accumulation specifies the carbon stored in aboveground biomass, and was reported to be declining by 9.3% with each fallow cycle in Indonesia (Hulvey et al., 2013; Lawrence et al., 2010; Lawrence, 2005). This decline was mainly driven by the density and biomass of woody stems >10 cm dbh as well as soil phosphorus availability (Lawrence, 2005). Burning also has a positive influence on biomass carbon accumulation in fallow secondary forests (Kenzo et al., 2010; d’Oliviera et al., 2011). Recovery may also depend on remaining forest cover in a landscape, although intensity of past land-use rather than edaphic variables is the strongest predictor of biomass recovery (Castro-Luna et al., 2011). Rapid biomass recovery during secondary forest succession was also reported by Letcher and Chazdon (2015) and Martin et al. (2013). 93

4.5.3 Forest management and landscape restoration implications In tropical forests, aboveground biomass carbon dynamics are important in net primary productivity, and regardless their large contribution to the global carbon balance, uncertainty yet remains regarding their quantitative contribution to the atmospheric carbon cycle (Chave et al., 2005; Clark et al., 2001). In Southeast Asia there are large areas of secondary forest as a result of past anthropogenic disturbances. The existing carbon measurement uncertainties create critical data gaps that limit our understanding of the important role of these forests as sources and sinks of terrestrial carbon (Ziegler et al., 2012). In recent years, it is also increasingly recognized that although undervalued, tropical secondary forests can provide the same important ecosystem goods and services as primary or old-growth forests (Bonner et al., 2013; Martin-Spiotta et al., 2007; Chazdon, 2003). In tropical regions deforestation has been a large contributor of greenhouse gas emissions, and reversing these trends with suitable land-use(s) has a clearly recognized potential for recovering biomass carbon stock in forests (Budiharta et al., 2014; Houghton, 2012). Compared to other climate mitigation options, regenerating secondary forests offers a low-cost approach to reducing greenhouse gas emissions in the tropics, although a greater understanding of and capability to quantify carbon dynamics in such novel and emerging ecosystems is necessary at landscape scales (Bonner et al., 2013). For instance, in many tropical countries monocultures have been preferred for reforestation, but our study along with others suggest that considerable net primary productivity and carbon storage could be achieved if more species diversity is secured in tropical landscapes (Pichancourt et al., 2014). Current remote sensing based techniques using satellite imagery offer promise for estimation of ecosystem carbon exchange in complex forested landscapes, although large variability exists depending on forest conditions and landscape type (Tang et al., 2013, 2012). A combination of field-based inventory and remote sensing techniques can be used to reduce such variability and to cover large areas of tropical forests (Pelletier et al., 2012).

4.6 Conclusions Our results highlight that the secondary forests regenerating following shifting cultivation are important carbon sinks in tropical ecosystems. Allowing development of such secondary regrowth has clear potential for carbon storage in the aboveground forest biomass. Biomass carbon distribution differs across sites with different land-use histories, and a large amount of carbon is stored in living woody biomass in older fallow areas indicating the dynamic nature of the landscape and succesional development towards undisturbed forests. In young fallow areas, large amounts of carbon are stored in coarse dead wood material which ultimately provided inputs to the soil for 94 biomass accumulation in living trees. We found that patch size is an important factor in biomass carbon recovery together with soil organic carbon, fallow age and the slope of a site, and after thirty years a site may achieve more than 40% of the biomass carbon found in old-growth forest without any history of major disturbances. The extensive deforestation and forest degradation in tropical regions caused by shifting cultivation and other land-uses is being blamed for biodiversity loss and global warming. We found that regenerating secondary forests have the potential to mitigate the impacts of such deforestation and forest degradation and to contribute to global carbon sequestration. However, it remains necessary to determine exactly where in the aboveground forest biomass the carbon is being sequestered (e.g. in the present study, we found that coarse woody debris in new kaingin fallow sites has the highest contribution to aboveground total biomass carbon, and in oldest kaingin fallow sites living woody biomass carbon had the highest contribution).

4.7 Additional information Supplementary Tables 4.1, 4.2, 4.3, 4.4, 4.5,4.6, and Supplementary Figures 4.1,4.2, related to this chapter/manuscript is provided at the end of this thesis under the section – Appendices.

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Annex 4.1. Summary (mean ± SE) of aboveground biomass carbon (Mg ha-1) distribution in our study sites on Leyte Island, the Philippines. Where, LWBC = living woody biomass carbon, OLBC = other living biomass carbon , CDWBC = coarse dead wood biomass carbon, UBC = undergrowth biomass carbon, LBC = litter biomass carbon , AGTBC = aboveground total biomass carbon. Parameter Fallow category Old-growth forest ≤ 5 year 6-10 year 11-20 year 21-30 year LWBC 33.42 (±55.25) 74.18 (±54.15) 111.81 (±74.65) 120.02 (±52.05) 316.96 (±130.63)* Pioneer 4.09 (±5.31) 37.30 (±43.85) 29.32 (±20.78) 24.57 (±6.54) 87.58 (±45.63) Secondary 6.75 (±7.97) 20.13 (±6.28) 33.65 (±22.4) 45.03 (±18.78) 74.31 (±36.66) Climax 22.57 (±49.0) 16.75 (±12.27) 48.85 (±55.56) 50.42 (±35.68) 155.07 (±84.03)* Native 17.63 (±23.35) 60.32 (±42.23) 78.17 (±52.47) 75.79 (±33.68) 256.14 (±108.27)* Endemic 15.43 (±32.71) 14.50 (±12.03) 33.24 (±28.13) 41.66 (±30.67) 60.83 (±31.7) Exotic 0.35 (±0.79) 0 0.4 (±0.61) 2.57 (±5.14) 0 OLBC 0.09 (±0.17) 1.45 (±1.34) 0.40 (±0.27) 0.34 (±0.37) 0.21 (±0.30) Tree fern 0.08 (±0.17) 1.41 (±1.33) 0.32 (±0.31) 0.23 (±0.25) 0.21 (±0.30) Abaca 0.01 (±0.02) 0.04 (±0.05) 0.08 (±0.06) 0.11 (±0.14) 0 CDWBC 126.65 (±22.58)* 25.26 (±25.0) 9.95 (±4.97) 11.87 (±12.57) 3.91 (±1.17) Standing 108.28 (±19.46)* 18.21 (±24.74) 2.53 (±1.07) 4.47 (±5.74) 0.31 (±0.25) Downed 18.37 (±11.70) 7.05 (±5.68) 7.42 (±5.49) 7.40 (±7.33) 3.60 (±1.07) Freshly cut 115.29 (±22.2)* 2.06 (±2.77) 0.27 (±0.28) 1.13 (±1.85) 0 Moderately degraded 7.85 (±7.69) 17.20 (±25.39) 4.69 (±3.68) 6.72 (±8.45) 0.3 (±0.21) Highly degraded 3.04 (±3.56) 5.93 (±4.47) 4.97 (±3.76) 4.0 (±4.5) 3.57 (±1.23) Burnt 0.47 (±1.01) 0.08 (±0.13) 0.02 (±0.05) 0.01 (±0.02) 0.04 (±0.09) UBC 0.08 (±0.06) 0.10 (±0.03) 0.12 (±0.04) 0.15 (±0.08) 0.11 (±0.04) LBC 0.07 (±0.04) 0.09 (±0.03) 0.13 (±0.09) 0.17 (±0.10) 0.10 (±0.02) AGTBC 160.3 (±55.86) 101.09 (±55.98) 122.41 (±74.95) 132.54 (±57.07) 321.29 (±130.96)* *Values are significantly different at p < 0.01 level.

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CHAPTER 5: SOIL CARBON AND NUTRIENTS STATUS IN RELATION TO SHIFTING CULTIVATION IN REGENERATING SECONDARY FORESTS IN THE PHILIPPINES UPLANDS

May cite as – Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. In review. Soil carbon and nutrients status in relation to shifting cultivation in regenerating secondary forests in the Philippines uplands. Land Degradation & Development.

5.1 Abstract Shifting cultivation is a dominant land-use in tropical forest-agriculture frontier that is associated with much of the environmental degradation in Southeast Asia. We examined the distribution and availability of key soil parameters –i.e. soil organic carbon (SOC), total nitrogen (N), phosphorus (P) and potassium (K), in relation to shifting cultivation in the upland Philippines. Soil samples were collected along a fallow gradient from regenerating secondary forests on Leyte Island. The effect of site environmental attributes on the availability (in relation to the old-growth forest) of soil carbon and nutrients was investigated using linear mixed-effect models (LMEM). We found relatively higher concentrations of soil carbon and P in the oldest fallow sites and higher N concentration at the youngest fallow sites. Soil K was consistently lower in all of our fallow sites, although soil C and other nutrients were relatively lower in our control old-growth forest sites. We found no significant difference in carbon and nutrients within sites of different fallow categories and soil depths, except in the case of soil K where it was highest in our control old-growth forest sites. Patch size together with slope and fallow age were the most influential factors in explaining the availability of soil carbon and nutrients in tropical secondary forests after shifting cultivation use. Our study suggests that shifting cultivation may not be as detrimental to soil quality at least on the soil type and climate we studied. Further studies are also required to fully understand the long- term effect of shifting cultivation in tropical forest landscapes.

Key-words: soil quality; degradation; disturbance; resilience; restoration; kaingin.

5.2 Introduction Shifting cultivation, swidden or slash-and-burn agriculture is a common land-use in tropical forests and has long been a major source of forest degradation (Ziegler et al., 2011; Mertz et al., 2009a). Generally, shifting cultivation involves slashing and burning of forest vegetation before or at the onset of the monsoon to release nutrients locked in plant biomass; the sites are then cultivated and harvested over several years before they are left fallow to allow growth of secondary forest 102

(Fox et al., 2000). Much of the forest in the tropics has been subjected to shifting cultivation, and this is a major contribution to the livelihoods and food security of smallholder rural upland farmers (Dressler et al., 2015; Chazdon, 2014; van Vliet et al., 2012). Although reliable statistics about the extent of land under shifting cultivation are not available, Mertz et al., (2009b) reported that there are an estimated 14–34 million people dependent on shifting cultivation in tropical Asia. In the last few decades, a rapid transformation of shifting cultivation landscapes has taken place in Southeast Asia, mainly driven by rapid urbanization, and the changing land-use policies and focus of governments (van Vliet et al., 2012; Fox et al., 2009). Another threat to forest in the Southeast Asia is posed by large-scale plantations of commercial and perennial crops including rubber and oil palm (Ahrends et al., 2015; van Vliet et al., 2012), yet shifting cultivation regarded as a major cause of the region’s environmental and forest degradation (Mukul and Herbohn 2016; Hett et al., 2012; Ziegler et al., 2011).

Soil quality is one of the key environmental attributes that is influenced by shifting cultivation and is likely to be affected by any changes in shifting cultivation practices (Paudel et al., 2015; Bruun et al., 2013, 2009; Lawrence et al., 2010; Kotto-Same et al., 1998). Soil quality is defined here as the capacity of the soil to support forest growth without causing degradation of the soil or to the environment (Lal, 1997). Soil quality is also closely linked to soil resilience which refers to the ability of the soil to restore its functions following disturbances (Estes et al., 2011; Lal, 1997). The ecological aspects of shifting cultivation, however, are much more complex than is often presented in the literature, and the transformations of shifting cultivation landscapes to other land-uses have a wide range of environmental consequences, both at the local and global level (Mukul and Herbohn, 2016; van Vliet et al., 2012; Bruun et al., 2009). For instance, the transition of shifting cultivation landscapes to sedentary agriculture will bring a substantial reduction in the above and below ground carbon stocks compared to the transition of shifting cultivation landscapes to secondary forests (Bruun et al., 2009).

In the tropics, the effects of anthropogenic forest disturbances, including the impacts of shifting cultivation, on soil carbon and essential nutrients are still unclear, and characterized by data scarcity and inconclusiveness (see – Paudel et al., 2015; Sang et al., 2013; Bruun et al., 2009; Richards et al., 2007). Consequently, we investigate the effect of shifting cultivation on key soil quality indicators namely – soil organic carbon (SOC), total nitrogen (N), phosphorus (P) and potassium (K) in an upland area of the Philippines (Sharma et al., 2005). In the Philippines shifting cultivation is locally known as kaingin and represents a dominant land-use in the upland areas (Saurej and Sajise, 2010). After logged forests, post kaingin forests constitute the largest group of secondary 103 forests in the country (Chokkalingam et al., 2006, 2001). Our specific research objectives were to determine the concentrations of selected soil parameters (SOC, N, P and K) in post kaingin secondary forests of the country along a fallow gradient, and to identify the effect of site environmental attributes on the recovery of key soil quality indicators investigated. Understanding changes in soil carbon and nutrient availability between secondary forests after shifting cultivation has wider implications for forest management and restoration in the tropics (Locatelli et al., 2015; Smith et al., 2015; Bonner et al., 2013; Sang et al., 2013; Bruun et al., 2009).

5.3 Materials and methods 5.3.1 Study location In the Philippines, 53% of the total land area is considered as forest land based on the national land classification system. Another 47% lands are regarded as alienable and disposable land, with slope less than 18% and are not required for forest purposes (Carating et al., 2014). About 23% of the total land area of the country is classified as upland with altitude ranging between 100-500 m asl (Carating et al., 2014). Our study was conducted in an upland area situated on the western side of the island of Leyte (Figure 5.1), which is the eighth largest in the country and located between 124017/ and 125018/ East longitude and between 9055/ and 11048/ North latitude. Forests cover only about 10% of the island’s 800,000 ha area (Asio et al., 1998). The once dipterocarp rich rainforests of the island are now dominated by patches of old-growth forest, coconut plantations, Abaca (a fiber yielding species from the Musaceae) and fast growing timber species (Asio et al., 1998).

Leyte has a ‘type IV’ climate, according to the Coronas Climate Classification with two distinct seasons – monsoon and dry seasons (Navarrete et al., 2013). Annual rainfall of the study area is about 4,000 mm with a mean annual temperature of about 280C that varies little throughout the year (Navarrete et al., 2013; Jahn and Asio, 2001). Relative humidity ranges between 75 to 80 percent (Kolb, 2003). The soil of our study area is an Andisol and possessed markedly higher concentrations of organic carbon than on the other islands with the Andisol soil type (Navarrete et al., 2013).

5.3.2 Site selection and characteristics We purposively selected Barangay (administrative entity, similar to a village) Gaas (hereafter Gaas only) on Leyte Island because the area has relatively low population density with some undisturbed forests, which is the prerequisite for the development of second growth forests in tropics (Chokkalingam et al., 2006). The kaingin system of the Philippines can be divided into three 104 distinct categories based on slope and access to irrigation facility, these are: i) the tubigan system ii) the katihan system and iii) the dahilig system (Olofson, 1980). Both, the tubigan and katihan systems take places in lower elevation or gently sloping areas with limited facilities for irrigation;, whereas, the dahilig system is more common in the forested areas with steeper slopes (Olofson, 1980). We focused, however, only to the dahilig system because it is the most common form of shifting cultivation in Southeast Asia (Olofson, 1980).

Figure 5.1. Location map of the study area on Leyte Island (left), and the study sites (right) plotted on a Google earthTM map.

Altogether 25 sites (5 categories x 5 replicates) were established in the area. We took samples from four different fallow categories, i.e. less than (or equal to) 5 years old fallow (SA0-5, also referred to as new sites), 6-10 years old fallow (SA6-10, also referred to as young sites), 11-20 years old fallow (SA11-20, referred to as middle-aged sites), and 21-30 years old fallow (SA21-30, also referred to as oldest sites), and from old-growth forests as our control or standard (SF). Our old- growth forests are similar to the primary forests in terms of structure and floristic composition, ever been used for kaingin and/or logging, however, may experience limited level of anthropogenic disturbance like fruit or fuelwood collection. We took samples only from sites that were 1 ha or more in size (Piotto et al., 2009). The age of the site was confirmed by asking the landowner/farmer (Lawrence, 2004). A detailed vegetation survey was conducted at each site and all 105 trees all trees ≥5 cm dbh were identified and measured for related parameters. To measure sites elevation, distance from nearby control secondary forest and geographic position, we used a hand- held global positioning system (Model: Garmin eTrex). We used a digital plant canopy imager (Model: CID Bio-Science, CI-110/120) for measuring leaf area index. Summaries of our site environmental attributes are presented in Table 5.1.

Table 5.1. Environmental attributes of the study sites on Leyte Island, the Philippines. where EL= site elevation (m ASL), SL = slope (°), PS = patch size (ha), DIS = distance (from the nearest control forest site, m), N = tree species richness (no of unique species, site-1), A = tree species abundance (no of individuals, site-1), BA = tree basal area (m2 site-1), LAI = leaf area index (m2 site-1) (Mukul et al. In review). Site Site environmental attribute category EL SL PS DIS N A BA LAI SA0-5 600.8 33.0 1.16 290.0 6.0 10.8 0.89 1.33 (±22.19) (±5.7) (±0.21) (±74.16) (±7.38) (±13.52) (±1.32) (±0.57) SA6-10 549.0 32.4 1.14 540.0 38.4 142.6 2.8 5.7 (±72.41) (±9.4) (±0.13) (±114.02) (±4.83) (±20.5) (±0.81) (±0.96) SA11-20 567.2 32.6 1.34 162.0 39.2 140.8 3.85 5.14 (±49.24) (±9.21) (±0.24) (±198.17) (±9.52) (±26.94) (±1.86) (±1.01) SA21-30 574.8 38.2 1.14 256.0 45.8 143.6 3.92 5.3 (±35.35) (±7.98) (±0.22) (±153.88) (±5.93) (±4.45) (±1.39) (±0.69) SF 512.4 36.4 NA** NA** 45.2 145.8 7.81 6.08 (±54.77) (±9.71) (±4.21) (±16.53) (±2.23) (±0.86) *values in the parenthesis indicate standard deviation of means. ** not applicable for old-growth forest sites.

5.3.3 Soil sample collection Four transects of 50 m x 5m were established within each of the 25 sites. Within each site, transects were spaced at least 5 m apart, parallel to each other and running from the boundary to the centre of the site. Along each transect soil samples were collected from the beginning (0 m), centre (25 m) and end of transect (50 m). Samples from the top 30 cm of topsoil were obtained. Topsoil profile is widely reported to be most affected by land use/cover change (Sang et al., 2013; Bruun et al., 2009; Batjes, 1996); and the top 30 cm of soil is also the standard depth recognized by FAO and approved by IPCC for the global voluntary carbon markets (FAO, 2006). We collected soil core (5cm3) samples from three different depths, i.e. 0-5cm (also referred to as the top soil layer), 6- 15cm (the middle soil layer) and 16-30cm (the bottom soil layer) using a standard soil auger (Manufacturer: AMS Inc., USA). Altogether 900 core samples were collected from 100 transects distributed over the 25 sites. Samples were placed in plastic bags and labeled in the field before further processing in the laboratory. 106

5.3.4 Soil sample processing All analyses were performed in the VSU-ACIAR Analytical Chemistry Laboratory at Visayas State University in the Philippines. Samples were air dried at room temperature prior to being passed through a 2 mm sieve to remove rocks, pebbles and plant material (e.g. roots, litter). We used a homogenized composite sample (n= 3) pooled for the same soil depth for each transect. Altogether there were 300 composite samples from our 900 core samples that were used for laboratory analysis to determine SOC, N, P and K. Subsamples were used for oven drying (105oC for 48 hours) and all calculations are reported on an oven dry weight basis.

For SOC (% C‐Heanes) we oxidized the composite soil samples for each transect by heating with

H2SO4 in the presence of dichromate (Congdon, 2012). Unlike the traditional Walkley-Black method, external heating ensures complete oxidation and more reliable estimate of SOC (Krishan et al., 2009; Rayment and Higginson, 1992). Soil N and P were determined colorimetrically following the single digestion method of Anderson and Ingram (1989), while soil total K was quantified using an atomic absorption spectrophotometer. The recovery of soil parameter is expressed as the percentage of respective soil parameter in our control old-growth forest sites.

5.3.5 Statistical analysis We performed analysis of variance (ANOVA) and Tukey’s post-hoc analysis to test for significant differences among variables. We developed linear mixed-effect models (hereafter refer to as LMEM) to identify the effect of selected site environmental attributes on the availability of SOC, N, P and K in relation to our control old-growth forests using the package ‘nlme’ (Pinheiro et al., 2011). For LMEM along with fallow age (FA), we first considered eight environmental variables as our explanatory variables (i.e. fixed factors) – elevation (EL), slope (SL), patch size (PS), distance from the nearest control forest site (DIS), tree species richness (≥5 cm dbh) (N), tree species abundance (≥5 cm dbh), basal area (≥5 cm dbh) and leaf area index (LAI) (Table 5.1). Tree species richness, abundance, basal area and leaf area index were expressed per site (i.e. 0.1 ha area) basis. After a Pearson’s correlation test we however, found only five site environmental variables, i.e. fallow age, elevation, slope, patch size and leaf area index, suitable for our final LMEM (Supplementary Table 5.1). We used sites nested in fallow categories as the random effect in our LMEM with SOC, N, P, and K at different soil depths as the response variable. All statistical analyses were performed using the ‘R’ Statistical Package (version 3.0.1; R Development Core Team, 2012). We considered Akaike Information Criterion corrected for small sample sizes (AICc) for the selection of our top models. Only models within four AICc units were considered as 107 competing models in the present study (Grueber et al., 2011). We used the package ‘MuMin’ for our model selections and to evaluate the contribution that different fixed effects had on explaining the variation in the response variables (Bartoń, 2011).

5.4 Results 5.4.1 Soil carbon and nutrients concentrations across a fallow gradient We found higher SOC concentrations in all soil depths in our oldest fallow sites (SA21-30) followed by young fallow sites (SA6-10) and in new fallow sites (SA0-5) (Table 5.2). A similar pattern was found at all soil depths examined (i.e. 0-5 cm, 6-15 cm and 16-30 cm). The differences in SOC distribution was not significant in the case of the top soil layer (i.e. 0-5 cm), whilst in the middle (6-15 cm) and bottom (16-30 cm) soil layers were significantly (p<0.05) different across the sites (Figure 2). Tukey’s post-hoc analysis also revealed significantly (p<0.05) higher SOC concentrations in our middle and bottom soil layer in the oldest fallow sites followed by young and new kaingin fallow sites. The relative contribution of the SOC (at the different soil depths) to total SOC stock, however, varied varied across the sites of different fallow categories and forest, with relatively higher SOC concentrations in the top soil layers (i.e. 0-5 cm) in our control forest sites (49.8%) followed by the middle aged sites (48.98%) (Figure 5.3). In the case of the oldest fallow secondary forest sites the relative contribution of SOC in the bottom layer was comparatively higher (27.1%) than all other site categories.

Interestingly soil total N concentrations were highest in the new kaingin fallow sites and in the top layer of the soil that we investigated (see Table 5.2). We found no significant difference in the soil N distribution between different site categories and soil depths as indicated by ANOVA. The relative contribution of soil N present in the top layer of soil to total N stock was higher (54.1%) in our control forest sites followed by young fallow sites (48.4%).

Similar to SOC and N there was no significant difference in total P concentrations in our study sites distributed across different fallow categories and secondary forest without any history of kaingin (Supplementary Figure 5.1). The concentrations of soil P were, however, higher in the oldest fallow sites and in the top soil layer of all our site categories although the differences were not statistically significant using ANOVA (Table 5.2). The relative importance of soil P at different soil depths varied across the sites, and in the secondary forest sites, soil P in the top soil layer had the highest contribution (50.5%) to the total soil P stock identified at the three different depths (Figure 5.3).

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Soil total K concentration was highest in old-growth forest sites at all soil depths followed by young fallow sites and middle-aged sites (Table 5.2). We found significantly higher (F4= 3.16, p<0.05) soil K concentrations in the top layer of soil of our old-growth forest sites using ANOVA and

Tukey’s post-hoc analysis. The difference was, however, not significant in the middle (F4= 2.15, p=0.11) and bottom (F4= 1.73, p=0.18) soil layers.

Table 5.2. Concentrations of soil organic carbon and nutrients across the sites of different fallow categories and old-growth forest on Leyte Island, the Philippines. Soil parameter Soil depth Site category SA0-5 SA6-10 SA11-20 SA21-30 SF SOC 0-5 cm 61.66 65.36 52.06 67.88 47.47 (mg C g-1) (±6.82) (±20.53) (±6.9) (±19.18) (±11.09) 6-15 cm 36.81 36.58 29.23 46.81 25.44 (±6.89) (±15.15) (±3.6) (±17.31) (±5.1) 15-30 cm 29.96 32.97 24.99 42.56 22.68 (±6.66) (±13.78) (±3.73) (±16.67) (±5.38) Total N 0-5 cm 4.33 3.53 3.46 3.36 3.4 (mg N g-1) (±0.77) (±1.17) (±1.14) (±1.02) (±0.5) 6-15 cm 2.67 1.88 2.22 2.21 1.68 (±1.17) (±0.85) (±1.6) (±0.89) (±0.43) 15-30 cm 2.46 1.89 1.51 1.86 1.22 (±1.28) (±0.69) (±1.15) (±1.11) (±0.53) Total P 0-5 cm 0.51 0.53 0.49 0.61 0.49 (mg P g-1) (±0.09) (±0.11) (±0.1) (±0.14) (±0.13) 6-15 cm 0.34 0.4 0.34 0.4 0.28 (±0.14) (±0.1) (±0.09) (±0.14) (±0.14) 15-30 cm 0.30 0.33 0.23 0.34 0.2 (±0.13) (±0.09) (±0.07) (±0.18) (±0.12) K 0-5 cm 1.02 1.88 1.52 1.3 3.18 (mg K g-1) (±0.22) (±1.23) (±0.99) (±0.76) (±1.58) 6-15 cm 0.86 1.81 1.51 0.9 2.45 (±0.26) (±1.29) (±1.18) (±0.48) (±1.35) 15-30 cm 0.89 1.76 1.54 0.91 2.3 (±0.31) (±1.3) (±1.24) (±0.53) (±1.24) *Values in the parentheses indicate the standard deviations of means under respective categories.

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Figure 5.2. The relative contribution of soil organic carbon and nutrients at different soil depths in our sites on Leyte Island, the Philippines. The Y axis here indicates the percentage (%) contribution to the total soil carbon and nutrient pools at the three soil depths studied. The values within the bars are the mean concentrations (mg g-1) of the soil parameters for the respective depths and site categories.

5.4.2 Availability of soil carbon and nutrients along a fallow age gradient We found high SOC, soil N and soil P recovery in our fallow sites when compared with the control old-growth forests (Figure 5.3). In most cases the recovery was higher in young fallow sites and in oldest fallow sites. Among the soil nutrients soil K recovery was lowest across all site categories. The pattern of soil K recovery was different to soil carbon and N and P, with relatively higher recovery in middle-aged sites. Interestingly soil K recovery was lowest in the oldest fallow sites. Despite relatively higher variability within the sites in recovery of carbon and nutrients, there 110 was no significant difference between sites (of different fallow categories) in the recovery of selected soil parameters.

Figure 5.3. Soil carbon and nutrients in relation to control old-growth forests at our study sites on Leyte Island, the Philippines. Note that different scales are used on the Y axes.

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5.4.2 Environmental controls on soil carbon and nutrients in fallow sites

We found patch size (PS) explained the highest amount of variation in soil carbon and nutrients availability (i.e. dependent variables) in regenerating secondary forests in relation to the control old-growth forests (Table 5.3). Other site factors important in explaining the variations were slope (SL) and fallow age (FA). There was no influence of the distance from nearby secondary forest (DIS) to the recovery of the soil carbon and nutrients across our sites. Patch size was found to be consistently important in explaining the variation in recovery for all the soil parameters and soil depths we examined (Table 5.4). In the case of soil P recovery we also found that the slope of the sites was equally important in explaining the variation as the patch size.

Table 5.3. Summary of LMEM between soil carbon and nutrient recovery with environmental attributes obtained using the package MuMin (Bartoń 2011). Where, FA = fallow age, DIS = distance (from the nearest control forest site), SL = slope, PS = patch size. Soil Soil depth Explanatory DF LL AICc ∆ AICc Weight parameter (cm) variable FA DIS SL PS SOC 0-5 X X 6 -86.12 190.71 0.0 0.47 X 5 -88.43 191.15 0.44 0.37 X X 6 -87.80 194.05 3.34 0.09 X X X 7 -85.54 194.42 3.71 0.07 6-15 X X 6 -93.6 205.65 0.0 0.44 X 5 -96.3 206.88 1.23 0.24 X X 6 -94.56 207.58 1.93 0.17 X X X 7 -92.25 207.83 2.18 0.15 16-30 X X 6 -95.67 209.79 0.0 0.42 X 5 -98.48 211.25 1.46 0.20 X X X 7 -94.01 211.36 1.57 0.19 X X 6 -96.47 211.39 1.6 0.19 Total N 0-15 X 5 -88.43 191.14 0.0 0.42 X X 6 -86.93 192.31 1.17 0.24 X X 6 -87.07 192.6 1.46 0.20 X X X 7 -85.01 193.35 2.21 0.14 6-15 X 5 -101.9 218.08 0.0 0.40 X X 6 -100.1 218.71 0.63 0.29 X X 6 -100.5 219.53 1.44 0.19 X X X 7 -98.65 220.64 2.56 0.11 16-30 X 5 -106.9 228.03 0.0 0.30 X X 6 -104.9 228.29 0.27 0.26 X X 6 -104.9 228.36 0.33 0.25

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X X X 7 -102.8 229.0 0.97 0.18 Total P 0-5 X X 6 -80.12 178.7 0.0 0.51 X 5 -82.76 179.8 1.1 0.30 X X 6 -81.67 181.8 3.09 0.11 X X X 7 -79.55 182.42 3.72 0.08 6-15 X 5 -93.35 200.98 0.0 0.42 X X 6 -91.42 201.3 0.32 0.36 X X 6 -92.33 203.12 2.14 0.14 X X X 7 -90.51 204.35 3.37 0.08 16-30 X X 6 -98.21 214.89 0.0 0.45 X 5 -100.8 215.81 0.92 0.28 X X X 7 -96.90 217.13 2.24 0.15 X X 6 -99.47 217.41 2.52 0.13 K 0-5 X X 6 -82.95 184.37 0.0 0.76 X X X 7 -82.20 187.73 3.36 0.14 X 5 -87.04 188.36 3.99 0.10 6-15 X X 6 -88.49 195.44 0.0 0.82 X X X 7 -87.57 198.47 3.03 0.18 16-30 X X 6 -89.94 198.35 0.0 0.82 X X X 7 -89.02 201.37 3.02 0.18 *DF— Degree of Freedom, LL— Log Likelihood, AIC—Akaike Information Criterion corrected for small sample size; **Values in the bold indicate the most influential model describing the variation in biomass carbon recovery.

Table 5.4. The relative importance of site environmental attributes in the final LMEM. Where, FA = fallow age, DIS = distance (from the nearest control forest site), SL = slope, PS = patch size. Soil Soil depth Explanatory variable* Number of parameter (cm) FA DIS SL PS models SOC 0-5 0.16 (2) - 0.54 (2) 1.0 (4) 4 6-15 0.32 (2) - 0.59 (2) 1.0 (4) 4 16-30 0.38 (2) - 0.61 (2) 1.0 (4) 4 Total N 0-5 0.34 (2) - 0.37 (2) 1.0 (4) 4 6-15 0.31 (2) - 0.40 (2) 1.0 (4) 4 16-30 0.45 (2) - 0.44 (2) 1.0 (4) 4 Total P 0-5 0.19 (2) - 0.59 (2) 1.0 (4) 4 6-15 0.22 (2) - 0.44 (2) 1.0 (4) 4 16-30 0.27 (2) - 0.59 (2) 1.0 (4) 4 K 0-5 0.14 (1) - 0.90 (2) 1.0 (3) 3 6-15 0.18 (1) - 1.0 (2) 1.0 (2) 2 16-30 0.18 (1) - 1.0 (2) 1.0 (2) 2 *Values in the parenthesis indicate the number of models containing respective explanatory variable. 113

5.5 Discussion 5.5.1 Variability in soil carbon and nutrients in fallow secondary forests We did not find a clear or consistent influence of shifting cultivation land-use on the stocks of soil organic carbon, N, and P in regenerating secondary forests in the upland Philippines, with relatively greater influence on soil K concentrations. The higher levels of soil organic carbon and nutrients (i.e. N and P) in young fallow sites could be due to the initial release of carbon and nutrients from plant materials to soil following burning (see- Tanaka et al., 2001; Giardina et al., 2000). Heating of soil during burning acts as an important mechanism of nutrient release and the initial burning associated with shifting cultivation is reported to increase SOC by addition of organic matter in soil via ash (Tanaka et al., 2001). Burning can also result in losses of soil available N due to increased volatilization, although, the losses of soil P to atmosphere due to volatilization is relatively low (Romanyá et al., 2001; Giardina et al., 2000). In shifting cultivation landscapes burning also results in a decrease in microbial activity and associated biomass in soil at the initial stage that may negatively influence organic carbon in soil (Tanaka et al., 2001).

The relatively lower concentration of SOC and P at our middle-aged sites (i.e. SA11-20) could be due to increasing nutrient uptake by regenerating vegetation during successional development. Similarly, relatively greater concentrations of soil carbon, N, and P in our oldest fallow sites (SA21- 30) could be due to higher litterfall, litter decomposition and microbial activity in sites (Lange et al., 2015; Paudel et al., 2015; Sayer et al., 2011). Positive effects of shifting cultivation on soil available P and K in secondary forest have been reported by Brand and Pfund (1998). In contrast to our findings, Garcia-Oliva et al. (1999), however, in Mexico found a 32% initial decrease in SOC stock due to fire and combustion, and Yang et al. (2003) found a reduction in soil available N and P after shifting cultivation use. Soil K was consistently low at all our sites and fallow categories, although Yang et al. (2003) reported an increase in soil K after fire and shifting cultivation use at sites in China. Other than combustion during the burning of vegetation, soil runoff associated with forest clearing during shifting cultivation also reported to causes nutrient losses in shifting cultivation landscape (Rodenburg et al., 2003; Brand and Pfund, 1998). Such generalisations might, however, underestimate the fact that in the tropics, smallholder farmers usually select sites with greater soil fertility for shifting cultivation use (Mertz et al., 2008).

5.5.2 Influence of site environmental factors on soil carbon and nutrients We found that site environmental parameters, mainly patch size, have the greatest influence on the recovery of SOC, soil total N and P; and we have found that the same factors influence aboveground biomass carbon and forest structure recovery in regenerating secondary forests after 114 shifting cultivation (see Mukul et al., 2016; Mukul et al., Under review). As mentioned earlier the higher levels of soil carbon and nutrients in our fallow sites could be also due to the initial release of carbon and nutrients following burning, and may not represent the actual recovery in young fallow sites. In the case of soil K, both patch size and slope were found to be equally important for its recovery. However, patch size was found to be the most important factor as models within ∆AICc=4 are considered as equivalent and explain the same amount of variation as other more complex models incorporating more interactions of variables (Bartoń, 2011). Due to a lack of information about past fallow cycles, we did not take account of this in our analysis. It is thus unclear what impact past fallow cycles may have had on the results. The effect of land-use and site environmental attributes on soil carbon and nutrients is evident from many studies (see- Fernandez- Romero, 2014; Parras-Alcantara et al., 2013; Hatter et al., 2010; Neill et al., 1997; van Noordwijk et al., 1997). A long fallow period is critical to restoring essential soil nutrients, and it may take as long as 20 years to restore soil nutrients to a level similar to a secondary forest (Rahamiralala et al., 2010; Funakawa et al., 2009). In an Indonesian study, the number of fallow cycles did not influence soil nutrients, like soil P, although the presence of deep and fine root systems in soil was found to be more important than fire history in recovery of soil P (Lawrence and Schlesinger, 2001). A similar observation was also made by Bruun et al. (2009) where they found higher growth of pioneer species in fallows due to their shallow root systems and ability to take up nutrients from the top layer. Forest structure and species composition may also influence the dynamics of soil carbon and nutrients and vice-versa (Raich et al., 2014; Paoli et al., 2008; Firn et al., 2007; Lawrence et al., 2005). Furthermore, spatial heterogeneity in soil in terms of texture, clay mineralogy and site topography and climate may vary and can also override the effects of other environmental factors (Nottingham et al. 2015; Bruun et al., 2006).

5.6 Conclusions Our study finds that shifting cultivation may not be as detrimental to soil quality at least on the soil type and climate we studied as suggested in the literature, and that geographic and site specific conditions may be important in determining the impact that shifting cultivation has on soil properties. The concentrations of soil carbon, N and P were significantly higher in the young fallow secondary forests, while soil K concentration was lower compared to old-growth forest. We also found greater availability in the soil stocks of SOC, soil N and P in tropical secondary forests compared to old-growth forests after shifting cultivation use. In young fallow areas, this may be attributed to the release of nutrients from slashing and burning of plant biomass available in sites. Patch size together with the slope (of the site) and fallow age were significant explanatory factors associated with the recovery process. 115

In tropical regions shifting cultivation is still a dominant land-use and likely to contribute to the food security and livelihoods of smallholder farmers in upland areas for many years ahead. The traditional view of shifting cultivation as environmentally detrimental in terms of its impacts on soil is not well established (Murty et al., 2002). A better understanding of this issue, with systematic and long-term studies, is important for the restoration and management of tropical secondary forests not only after the shifting cultivation but also after other disturbances.

5.7 Additional information Supplementary Table 5.1 and Figure 5.1, related to this chapter/manuscript are provided at the end of this thesis under the section – Appendices.

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CHAPTER 6: CO-BENEFITS OF BIODIVERSITY AND CARBON FROM REGENERATING SECONDARY FORESTS IN THE PHILIPPINES UPLANDS: IMPLICATIONS FOR FOREST LANDSCAPE RESTORATION

May cite as – Mukul, S.A., Herbohn, J., Firn, J. In press. Co-benefits of biodiversity and carbon from regenerating secondary forests in the Philippines uplands: implications for forest landscape restoration. Biotropica.

6.1 Abstract Shifting cultivation is a widespread land-use in tropical forested areas, and often regarded as the major driver of forest degradation by policy makers. The secondary fallow forests regrowing after shifting cultivation are generally not viewed as suitable targets for biodiversity conservation and carbon retention. Drawing upon an empirical study in the Philippines and other relevant case studies, we demonstrate that recovering secondary forests following shifting cultivation have high potentials for biodiversity and carbon conservation in upland rural areas of the Philippines – a global hotspot of biodiversity and deforestation. We compare the potential biodiversity and carbon sequestration observed in regenerating forests with other land-uses that may replace the fallow areas after shifting cultivation. We argue that regenerating tropical forests can be used as a cost-effective management and restoration strategy in countries where they are common and where forest is an integral part of rural people’s livelihoods. We discuss the issues and potential mechanisms through which such dynamic land-use can be incorporated into development projects that are currently being used for financing sustainable management, conservation and restoration of tropical forests.

Key-words: forest degradation; restoration; reforestation; community forestry; REDD+.

6.2 Introduction Deforestation and forest degradation are among the major threats to forests and biodiversity in Southeast Asia (Sodhi et al., 2010; Achard et al., 2002). Shifting cultivation, also known as swidden agriculture or slash-and-burn has long been seen as the primary agents of deforestation and forest degradation in this region (Ziegler et al., 2011; Angelsen, 1995). In this region shifting cultivation has been practised for centuries and supports an estimated 14-34 million people (Dressler et al., 2015; Mertz et al., 2009). As a consequence, secondary forests regrowing after shifting cultivation are rapidly becoming a prominent forest type in Southeast Asia where secondary forests regrowing both after shifting cultivation, logging and other disturbance constitute about 63%

123 of the total forest cover (Kettle et al., 2010, Koh, 2007; Chokkalingam et al., 2001; de Jong et al., 2001).

The Philippines is both a biodiversity hotspot and a megadiverse country (Posa et al., 2008; Myers et al., 2000), and is among the top priority countries for conservation (Conservation International, 2013). The country has experienced one of the highest rates of deforestation in Southeast Asia, and was one of the first countries to introduce massive reforestation and forest restoration programs to address the country’s rapid forest loss (Pulhin et al., 2007; Chokkalingam et al., 2006). The National Greening Program (NGP) – the most recent reforestation initiative in the country - has an aim to reforest 1.5 million hectares of degraded upland areas by 2016. The success of such efforts are still uncertain, as they are likely to be influenced by many factors and past reforestation programs in the Philippines have had only limited success (see – Le et al., 2014, 2015; Herbohn et al., 2014, Nguyen et al., 2014).

Shifting cultivation, locally called as kaingin, contributes to the livelihoods of many marginal upland farmers in remote rural areas in the Philippines (Lawrence, 1997; Kummer, 1992). In the country at least three and five million people largely depend on kaingin for their subsistence (Mertz et al., 2009). Major forestry policies in the Philippines, however, have attempted to impose restrictions on this land-use, based on the assumption that it has detrimental environmental impacts (Saurez and Sajise, 2010). Although, the Philippines is one of the pioneers in large-scale restoration and reforestation activities, access by smallholder and subsistence farmers to such efforts remains very limited (Pulhin et al., 2007, Harrison et al., 2004). It is likely that kanigin will continue to form an important land-use in the country’s rural, remote areas until greater access to such state regulated reforestation programs will be secured to local communities under community based forest management (CBFM) and other participatory schemes (Pulhin et al., 2007).

Due to its dynamic nature in tropical forested region, it is always difficult to generalize the environmental outcomes of shifting cultivation both during and after the practice (Mukul and Herbohn, 2016). Based on an empirical study in the Philippines here we present evidence that fallow secondary forest after shifting cultivation can provide biodiversity and carbon co-benefits, and could potentially be used as a cost effective forest management and reforestation measure. We also draw upon results from other relevant studies focusing on alternative land-uses, namely plantations of fast growing timber species (Swietenia macrophylla, Acacia sp.), oil palm, and grassland areas and agricultural production (rice) in upland areas to perform a biodiversity and carbon trade-off analysis. We discuss how the biodiversity and carbon co-benefits from 124 regenerating fallow forests could be integrated in ongoing forest conservation measures like Payment for Environmental Services (PES), Reducing Emissions from Deforestation and Forest Degradation (REDD+) and Clean Development Mechanism (CDM) projects. We also emphasized on measures that are essential for success of such efforts with an aim to forest landscape restoration and local development.

6.3 Methods 6.3.1 Background of the area The Philippines archipelago is comprised of 7,107 islands, with a total land area of about 30 million ha (Chokkalingam et al., 2006). The country is divided into 17 regions covering 81 provinces, 118 cities, 1,520 municipalities and 41,995 Barangay (the smallest administrative entity in the country, similar to a village). The climate of the country is tropical humid in general (Kummer, 1992). Based on the national land classification system the Philippines has 53% forest lands (all areas with a slope about 18% irrespective of whether they are covered in forest) and 47% alienable and disposable lands (i.e. lands not classified as forestland and with slopes less than 18%) (Jahn and Asio, 2001; Figure 6.1).

Upland areas in the Philippines are important for three main reasons. Firstly, most of the remaining forests are located in the uplands; secondly, upland areas have been subject to intensified human use since the Second World War; and thirdly, land degradation in the uplands is severe and widespread (Cramb, 1998). At the same time, a great deal of uncertainty exists regarding recovery of biodiversity and carbon stocks in degraded upland secondary forests after different levels of disturbance and human use.

Our empirical study was based in the Leyte Island, the eighth largest island in the country. Leyte has a forest cover of about 10%, although the once extensive dipterocarp rain forests are now mainly patches of disturbed old-growth forests. The island covers an area of about 800,000 ha, and is located between 124017/ and 125018/ East longitude and between 9055/ and 11048/ North latitude. According to Corona’s Classification of Climate Leyte has a ‘type IV’ climate (Navarrete et al., 2013). The Island enjoys relatively even distribution of rainfall throughout the year with annual rainfall totalling about 4,000 mm (Jahn and Asio, 2001). Mean annual temperature is 280C, which remains constant throughout the year (Navarrete et al., 2013).

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Figure 6.1. Major land-use/land-cover in the Philippines (left) (Source: Manuel 2014) with the location of Leyte Island indicated, and some common land-use in the upland areas after shifting cultivation use (clockwise from top-left: regenerating forest dominated by seedlings and undergrowth, secondary forest dominated by tree ferns, coconut plantation in grassland, abaca (Musa textilis) field, Acacia plantation in upland forest invaded by grassland, old coconut plantation within secondary forest) (Photo credits: S.A. Mukul).

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6.3.2 Study site selection The sites for our empirical study were located in Barangay Gaas. The area was selected purposively as it is situated in the comparatively high altitudinal range (450 - 650 m asl) in the island with relatively greater extent of undisturbed forests and with low population density. Both of these factors favour the natural regeneration in the kaingin fallow forests (Chokkalingam et al., 2006). Smallholder farmers living in the area usually grow abaca (Musa textillis, a species of banana native to the Philippines and harvested for fibre) or coconut in their fallow kaingin area in order to receive financial benefits during the time of abandonment. We confined our study to the areas where farmers cultivated only abaca, since coconut plantations generally involve more intensified land-management during the fallow periods and does not favour secondary forest development.

6.3.3 Data collection A series of extensive field surveys were undertaken in our sites in Barangay Gaas between May and October 2013. We categorized our sites into four different fallow categories; i.e. new fallows (i.e. less than 5 year old fallow), young fallows (i.e. 6-10 year old fallow), middle-aged fallows (i.e. 11-20 year old fallow), and oldest fallows (21-30 year old fallow). We sampled five sites from each category, and all sites were at least 1 ha in size. Within each site four transects of 50m x 5m were established and we identified and measured the dbh (diameter at breast height) and height of all trees that were at least 5 cm dbh. We also quantified the biomass of dead wood and other non woody vegetation. More information about the survey design and data collection methods can be found at Mukul et al., (in press). Additionally, we sampled old-growth forests as our control site. Our control old-growth forests sites were structurally and floristically similar to intact primary forests and had never been logged or used for kaingin. As with almost all forests in the Philippines they may however have experienced limited anthropogenic disturbances (e.g. firewood, wild fruit collection).

6.3.4 Data interpretation and analysis Species richness or the number of unique species in each land-use/cover was used as a measure of diversity in the study. We used the mean species number recorded from each fallow category and from our control old-growth forest. Above ground biomass (Mg) was calculated on a per hectare (ha) basis. We used the generic allometric model developed by Chave et al. (2014) for measuring biomass in standing live trees (≥ 5cm dbh).

AGB = 0.0673 × (ρD2H)0.976 127

Where, AGB is the aboveground biomass in kg, D is the dbh, H is the height of the tree and ρ is the species specific wood density (g cm-3). We assume carbon content is 50% of the dry plant biomass (Brown, 1997). For species specific wood density we used the World Agroforestry Centre’s wood density database (World Agroforestry Centre, 2014). Others biomass in undergrowth, litter, dead wood and in other non-woody plants was measured using standard procedures (see Mukul et al., in press for details).

We used descriptive statistics for data interpretation and analysis. Biodiversity and carbon trade- offs was expressed as the additionality (∆), and was calculated as below (Maron et al., 2013):

∆ Additionality = Biodiversity/Carbon in control forest sites - Biodiversity/Carbon in other land use/cover reported from the Philippines.

Where, additionality (∆) could be either positive, where + value indicates biodiversity/carbon gain and a negative value indicates biodiversity/carbon loss.

6.4 Results 6.4.1 Biodiversity and carbon co-benefits from regenerating secondary forests Tree diversity in terms of species richness was higher in the oldest fallow sites in our study area in Gaas, followed by in middle-aged sites and in young fallow sites. Other indicators of biodiversity like the number of locally endemic species (i.e. species that are not found outside of the Philippines) were higher in the relatively older fallow sites (Figure 6.2). The number of critically endangered species globally as listed in the IUCN Red List, and locally endangered species listed by the Philippines’ Department of Environment and Natural Resources (DENR) was, however occur on all fallow sites except for the new fallow sites (see Figure 6.2). Aboveground biomass carbon was substantially higher in the old-growth forests compared to sites of all fallow categories. The relative contribution of biomass carbon in live trees and in other above ground biomass is shown in Figure 6.3. Biomass in other categories composed mostly by the deadwoods which was substantially higher in the new fallow sites and vice versa.

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120 10 9 100 8 80 7 6 60 5 4 40 3 20 2 1 0 0 New fallows Young Middle-aged Oldest Old-growth New fallows Young Middle-aged Oldest Old-growth fallows fallows fallows forest fallows fallows fallows forest Number of species Endemic species Critically endangered (Global) Critically endangered (Local)

Figure 6.2. Tree biodiversity in regenerating forest after shifting cultivation in the Philippines uplands.

350

300

250

1 200 -

150 Mg ha Mg 100

0 New fallows Young fallows Middle-aged Oldest fallows Old-growth fallows forest AGB (live tree) AGB (others)

Figure 6.3. Above ground biomass carbon in regenerating forest following shifting cultivation in the upland Philippines.

6.4.2 Biodiversity and carbon trade-offs in the upland land-use of Philippines In Table 6.1 we present the potential trade-offs between biodiversity and carbon associated with shifting cultivation fallow secondary forests and other common upland land-use that may replace the regenerating forest after being abandoned or if the land converted to permanent and more intensive sedentary agricultural field or used for plantation and/or reforestation using single species or mixed species. Our old-growth control forest always provided the highest benefits in terms of carbon in aboveground forest biomass. The Swietenia macrophylla plantation had the nearest carbon stock to our old-growth forest sites, followed by kaingin fallow sites. The biodiversity and/or conservation importance of the Swietenia macrophylla plantation was however very low compared to kaingin fallow secondary forests of different fallow age and other tree based land-use/cover that has been examined (Table 6.1). Only fallow secondary forest had the potential to provide relatively similar biodiversity and carbon benefits compared to our old-growth control 129 forests. As expected, agricultural use (e.g. rice paddy in this case) and plantations of commercially important species such as oil palm and fast growing exotic Acacia species had also the lowest conservation and carbon importance in the upland Philippines when compared with secondary forests or fallow secondary forests after shifting cultivation (Table 6.1).

6.5 Discussion and implications Our results clearly show that secondary forest regrowing after shifting cultivation can support both substantial biodiversity and carbon benefits when compared with the old-growth forest. While other land-uses may also have greater value in terms of carbon storage and sequestration in tropical countries (see - Chazdon, 2014; Erskine et al., 2006), the conservation value of such land-use is not always comparable to the old-growth forests or to the regenerating fallow sites used in our study. Moreover, the costs and labour involved in plantation establishment and management are also prerequisites for the long term success and continuation of these projects (Gregorio et al., 2015). Our findings are consistent with the findings of Evans et al. (2015) and Gilroy et al. (2014) that show the high potential of post-agricultural forest regeneration for providing biodiversity and carbon co-benefits. We also find that, natural regeneration of shifting cultivation fallows is a highly cost effective restoration measure when considering the costs of plantation establishment and management in degraded landscapes in the area.

The extensive deforestation and degradation of tropical forests is a significant contributor to the loss of biodiversity and to carbon emissions that cause global warming (Budiharta et al., 2014). In tropical regions, uncertainties in biomass carbon, their distribution and recovery are one of the main constraints in inclusion of secondary forests degraded by shifting cultivation to emerging global voluntary carbon market (Ziegler et al., 2012; Mertz, 2009). Here we consider the potential of alternative land-use(s) that may also replace fallow shifting cultivation landscapes in the tropics.

Presently, global forest carbon credits are valued at over US$100 billion/year, and are an emerging, growing sector (Petrokofsky et al., 2011). In 2012, the price of sequestered carbon in the internationally recognized market was averaged US$9.20 per tonne (i.e. Mg), although in recent years there has been a decline in that price (US$3.8 per tonne in 2014) mainly due to fail in legislation to ratify another phase of the Kyoto Protocol (Hamrick, 2015; Peters-Stanley and Yin, 2013). The prospect of inclusion of regenerating secondary forests in emerging global carbon markets, however largely depends on the reliable estimates of carbon together with biodiversity benefits of a particular land-use (Evans et al., 2015; Law et al., 2015; Maron et al., 2013).

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Table 6.1. Biodiversity and aboveground carbon stocks in common upland land-cover/use in the Philippines uplands. Land-use Biodiversity1 Carbon2 Additionality3(∆) Age4 C sequestration Source (Mg ha-1) ∆ Biodiversity ∆ Carbon (Mg ha-1) Old-growth forest 79 321.3 - - - NA Mukul et al. (2016), Post-kangin forest Mukul et al. (In New fallow 28 160.3 -51 -160.9 5 - review) Young fallow 84 101.1 +5 -220.2 10 - As above Middle-aged 95 122.4 +16 -198.9 20 - As above Oldest fallow 106 132.5 +27 -188.8 30 - As above As above Dipterocarp forest NA 221 - -100.3 NA - Lasco & Pulhin (2009) Grasslands - Imperata sp. 0 8.5 -79 -312.8 1 0* Lasco & Pulhin (2009) Sacharrum sp. 0 13.1 -79 -308.2 1 0 * Lasco & Pulhin (2009) Plantations - Swietenia 1 264 -78 -57.3 NA - Racelis et al. (2008) macrophylla Acacia sp. 1 81 -78 -240.3 NA - Lasco & Pulhin (2009) Oil palm 1 55 -78 -266.3 9 6.1 Pulhin et al. (2014) Rice paddy 0 3.1 -79 -318.2 1 0* Lasco & Pulhin (2009) 1 here we only consider the main and/or characteristics plant diversity of a particular land-use; 2 aboveground carbon in forest biomass; 3 the difference, either positive or negative between control old-growth forest and respective land-use; 4 stand age; *no sequestration due to regular harvest; NA – not available.

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Globally policy makers recently collectively committed to the Bonn Challenge, an initiative to restore 150 million hectares of degraded forests by 2020 and 350 million hectares by 2030 (Locatelli et al., 2015). Our trade-off analysis found that regenerating secondary forests after shifting cultivation can be a cost-effective restoration approach in the Philippines, and are likely to play a similar role in other tropical developing countries with comparatively similar socio-political and environmental contexts. Due to limited information and data available on belowground biomass/carbon we did not include belowground carbon in our comparisons. A recent study suggested that carbon estimates without belowground biomass in tropical fallow secondary forests may underestimate the carbon content by up to 30% (McNicol et al., 2015).

Deforestation in tropics is a large contributor to the global CO2 emissions, and reversing this trend therefore has an obvious potential for recovering carbon, biodiversity and mitigate climate change (Gibbs et al., 2007; Houghton, 2012). Because of diverse stakeholder needs, managing tropical forest is complex and challenging (Yasmi et al., 2012). In tropical forest regions, particularly in South and Southeast Asia, involving local communities offers potential benefits for forest conservation (Robinson et al., 2014, Bowler et al., 2012, Balooni and Inoue, 2007). Globally, PES programs like REDD+ and CDM are increasingly gaining wider recognition for their prospects for protecting tropical forest and improving the standards of living of smallholders by giving them access to forest management, monitoring and benefits from carbon trading. The number of CDM projects with afforestation and/or reforestation objectives however remains still very limited (Thomas et al., 2010).

Forest conservation in the Philippines has clearly visible benefits to local livelihoods and climate change mitigation (see Lasco et al., 2013, 2011, Sheeran, 2006). Due to their extent and distribution, regeneration in shifting cultivation fallows in the Philippines offers great prospects for REDD+ and CDM. It is however critical to involve local community members in such activities with clearly defined rights and responsibilities. Improvement of environmental governance by legal and regulatory reform, better land tenure, land allocation and management, law enforcement and monitoring however, crucial for the successful implementation and involvement of local people in forest management in the country (see – Mukul et al., 2014; Chazdon, 2013; Grabowski and Chazdon, 2012).

6.6 References

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Achard, F., Eva, H.D., Stibig, H.J., Mayaux, P., Gallego, J., Richards, T., Malingreau, J.P., 2002. Determination of deforestation rates of the world’s humid tropical forests. Science, 297, 999- 1002. Angelsen, A., 1995. Shifting cultivation and “deforestation”: A study from Indonesia. World Development, 23, 1713-1729. Balooni, K., Inoue, M., 2007. Decentralized forest management in South and Southeast Asia. Journal of Forestry, 105, 414-420. Bowler, D.E., Buyung-Ali, L.M., Healey, J.R., Jones, J.P.G., Knight, T.M., Pullin, A.S., 2012. Does community forest management provide global environmental benefits and improve local welfare? Frontiers in Ecology and the Environment, 10, 29–36. Brown, S., 1997. Estimating biomass and biomass change of tropical forests: A primer. FAO Forestry Paper 134. Food and Agriculture Organization of the United Nations (FAO), Rome, Italy. Budiharta, S., Meijaard, E., Erskine, P.D., Rondinini, C., Pacifici, M., Wilson, K.A., 2014. Restoring degraded tropical forests for carbon and biodiversity. Environmental Research Letters, 9, 114020. Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M.S., et al., 2014. Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology, 20, 3177-3190. Chazdon, R.L., 2013. Making tropical succession and landscape reforestation successful. Journal of Sustainable Forestry, 32, 649-658. Chazdon, R.L., 2014. Second growth: The promise of tropical forest regeneration in an age of deforestation. University of Chicago Press, Chicago, IL. Chokkalingam, U., Bhat, D.M., von Gemmingen, G., 2001. Secondary forests associated with the rehabilitation of degraded lands in tropical Asia: a synthesis. Journal of Tropical Forest Science, 13, 816-831. Chokkalingam, U., Carandang, A.P., Pulhin, J.M., Lasco, R.D., Peras, R.J.J., Toma, T. (eds.), 2006. One century of forest rehabilitation in the Philippines: Approaches, outcomes and lessons. Centre for International Forestry Research (CIFOR), Bogor, Indonesia. Conservation International, 2013. Biological diversity in the Philippines. Retrieved from http://www.eoearth.org/view/article/150648. Cramb, R., 1998. Environment and development in the Philippine uplands: the problem of agricultural land degradation. Asian Studies Review, 22, 289-308. de Jong, W., Chokkalingam, U., Perera, G.A.D., 2001. The evolution of swidden fallow secondary forests in Asia. Journal of Tropical Forest Science, 13, 800-815. 133

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Maron, M., Rhodes, J.R., Gibbons, P., 2013. Calculating the benefit of conservation actions. Conservation Letter, 6, 359-367. McNicol, I.M., Berrya, N.J., Bruun, T.B., Hergoualch, K., Mertz, O., de Neergaard, A., Ryan, C.M., 2015. Development of allometric models for above and belowground biomass in swidden cultivation fallows of Northern Laos. Forest Ecology and Management, 357, 104-116. Mertz, O., 2009. Trends of shifting cultivation and the REDD mechanism. Current Opinion in Environmental Sustainability, 1, 156–160. Mertz, O., Leisz, O., Heinimann, A., Rerkasem, K., Thiha, Dressler, W., Pham, V.C., Vu, K.C., Schimdt-Vogt, D., Colfer, C.J.P., Epprecht, M., Padoch, C., Potter, L., 2009. Who counts? Demography of Swidden cultivators in Southeast Asia. Human Ecology, 37, 281–289. Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy, 55, 167-177. Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6, 22483. Mukul, S.A., Herbohn, J., Firn, J., in review. High resilience of tropical forest diversity and structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science. Mukul, S.A., Herbohn, J., Rashid, A.Z.M.M., Uddin,M.B. 2014. Comparing the effectiveness of forest law enforcement and economic incentive to prevent illegal logging in Bangladesh. International Forestry Review, 16, 363-375. Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B., Kent, J., 2000. Biodiversity hotspots for conservation priorities. Nature, 403, 853-858. Navarrete, I.A., Tsutsuki, K., Asio, V.B., 2013. Characteristics and fertility constraints of degraded soils in Leyte, Philippines. Archives of Agronomy and Soil Science, 59, 625–639. Nguyen, H., Lamb, D., Herbohn, J., Firn, J., 2014. Designing Mixed Species Tree Plantations for the Tropics: Balancing Ecological Attributes of Species with Landholder Preferences in the Philippines. PLoS ONE, 9, e95267. Peters-Stanley, M., Yin, D. 2013. Maneuvering the Mosaic: State of the voluntary carbon markets 2013. Forest Trends, Washington, DC and Bloomberge New Energy Finance,New York. Petrokofsky, G.,Holmgren, P., Brown, N.D., 2011. Reliable forest carbon monitoring – systematic reviews as a tool for validating the knowledge base. International Forestry Review, 13, 56-66. Posa, M.R., Diesmos, A.C., Sodhi, N.S., Brooks, T.M., 2008. Hope for threatened tropical biodiversity: lessons from the Philippines. BioScience, 58, 231-240. Pulhin, F.B., Lasco, R.D., Urquiola, J.P. 2014. Carbon sequestration potential of Oil palm in Bohol, Philippines. Ecosystems & Development Journal, 4, 14-19. 136

Pulhin, J.M., Inoue, M., Enters, T., 2007. Three decades of community-based forest management in the Philippines: Emerging lessons for sustainable and equitable forest management. International Forestry Review, 9, 865-883. Racelis, E.L., Carandang, W.M., Lasco, R.D., Racelis, D.A., Castillo, A.S.A., Pulhin, J.M., 2008. Assessing the carbon budgets of large leaf mahogany (Swietenia macrophylla King) and Dipterocarp plantations in the Mt. Makiling Forest Reserve, Philippines. Journal of Environmental Science and Management, 11, 40-55. Robinson, B.E., Holland, M.B., Naughton-Treves, L., 2014. Does secure land tenure save forests? A meta-analysis of the relationship between land tenure and tropical deforestation. Global Environmental Change, 29, 281–293. Sheeran, K.A., 2006. Forest conservation in the Philippines: A cost effective approach to mitigating climate change? Ecological Economics, 58, 338-349. Sodhi, N.S., Koh, L.P., Clements, R., Wanger, T.C., Hill, J.K., Hamer, K.C., Clough, Y., Tscharntke, T., Posa, M.R.C., Lee, T.M., 2010. Conserving Southeast Asian forest biodiversity in human-modified landscapes. Biological Conservation, 143, 2375–2384. Suarez, R.K., Sajise, P.E., 2010. Deforestation, swidden agriculture and Philippine biodiversity. Philippine Science Letters, 3, 91-99. Thomas, S., Dargusch, P., Harrison, S., Herbohn, J., 2010. Why are there so few afforestation and reforestation Clean Development Mechanism projects? Land Use Policy, 27, 880-887. World Agroforestry Centre, 2014. Wood density database. Available at: http://www.worldagroforestry.org/regions/Southeast_asia/resources/db/wd (Date of access: 14/11/2014). Yasmi, Y., Kelley, L., Murdiyarso, D., Patel, T., 2012. The struggle over Asia’s forests: an overview of forest conflict and potential implications for REDD+. International Forestry Review, 14, 99-109. Ziegler, A.D., Phelps, J., Yuen, J.Q., Webb, E.L., Lawrence, D., Fox, J.M., Bruun, T.B., Leisz, S.J., Ryan, C.M., Padoch, C., Koh, L.P., 2012. Carbon outcomes of major land-cover transitions in SE Asia: great uncertainties and REDD+ policy implications. Global Change Biology, 18, 3087-3099. Ziegler, A.D., Fox, J.M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Brunn, T.B., Vien, T.D., 2011. Recognizing contemporary roles of swidden agriculture in transforming landscapes of Southeast Asia. Conservation Biology, 25, 846-848.

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CHAPTER 7: GENERAL CONCLUSIONS

7.1 The context In tropical regions regenerating secondary forests are expanding dramatically, and in many countries, they have already exceeded the total area covered by remaining primary forests (Chazdon 2014; McNamara et al., 2012). Much of these secondary forests emerged after different levels of human interventions and use (Lawrence and Vandecar, 2015), and is increasingly considered as a novel or emerging ecosystem with characteristics that are not common elsewhere (Chazdon, 2014; Hobbs et al., 2009). Successful restoration and management of such novel ecosystems offer important synergies for conservation and development (Locatelli et al., 2015; Chazdon et al., 2009). In the upland Philippines, secondary forests comprise a large area with ecosystems that are highly dynamic, making forest management and conservation challenging (Posa et al., 2008; Lasco et al., 2001). Shifting cultivation or kaingin has been around a long time in the country (Kummer, 1992) with perceived negative impacts on forests and environment, and no or limited conservation significance in the country (Suarez and Sajise, 2010). The various chapters contained within this thesis addressed the impacts of shifting cultivation in the Philippines uplands. The results are important for understanding the impact of this land use in the Philippines and more broadly in the tropics, and also have important policy implications. The key conclusions from this study are discussed hereafter.

7.2 A synthesis of the impacts of shifting cultivation on tropical forests dynamics Chapter 2 in this thesis presented a synthesis paper based on systematic literature review (see also - Mukul and Herbohn, 2016). Emphasis was given on identifying any geographical and/or subject/research focus bias that exists in research on shifting cultivation, with forest and environmental aspects in secondary forests after shifting cultivation. The purpose of this study was to better understand the ecological factors that may influence the recovery of such complex landscape into secondary forest with environmental values similar to secondary or undisturbed forest that never used for shifting cultivation. There was a bias towards research on anthropology and/or human ecology with most research reported from tropical Asia Pacific region was evident. There was also a great variation in the findings on selected environmental research aspects related to secondary forest dynamics including conservation biology, plant ecology, soil nutrients and chemistry and soil physics and hydrology.

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7.3 The impact of shifting cultivation on biodiversity, species composition and forest structure The empirical part of this thesis study suggests that tropical secondary forests have the ability to recover after shifting cultivation, although site factors matter during the recovery process. It was found that old kaingin fallow areas can support relatively high numbers of rare and endangered species and thus also play an important role in conservation. A number of dipterocarp species, including endemic Hopea philippinensis, Shorea polysperma, Shorea contorta, were shared across the fallow sites of different categories and in control old-growth forest. It was found that initially there is a substantial decrease in biodiversity in the first five years, but the older fallow sites can exhibit similar levels of biodiversity as to the old-growth forest without any history of major disturbance. It was found that biodiversity indices used in the study, including –Shannon’s index and species evenness index were higher in the old-growth forest while species richness was higher in the oldest fallow sites. Recently abandoned new fallow areas demonstrated a very distinct pattern of species diversity compared to the other older fallow categories in our study. A homogeneous species composition between the older fallow sites/categories and old-growth forest was also evident. Recovery of species richness and Shannon’s index in older fallow sites were rapid, although there was no significant difference in the recovery of species evenness across the sites. Recovery of stem density also increased gradually with fallow age. Recovery of stand basal area was distinct across the sites and was higher in the relatively older fallow sites indicating the presence of larger and mature trees in those sites. Patch size was found to influence the recovery of species diversity, composition, and forest structure in regenerating secondary forests after shifting cultivation.

7.4 Aboveground biomass carbon dynamics in regenerating tropical secondary forests Overall, it was found that, tropical regenerating forests after shifting cultivation contribute significant amounts to aboveground carbon. A relatively larger contribution of older fallow areas compared to that of young fallow areas was found in the upland Philippines forests (see also – Mukul et al., 2016). Carbon stored in control old-growth forest, oldest fallow areas and moderately- aged fallow areas were 321.3 (±130.9) Mg ha-1, 132.5 (±57.1) Mg ha-1, 122.4 (±74.9) Mg ha-1 respectively. In young kaingin fallow areas, other living standing biomass (represented here by tree ferns and Abaca, a relative of the banana) and coarse dead wood biomass constitute a major part of the aboveground biomass carbon, depicting a different composition in landscape level total aboveground biomass carbon storage in the area. Recovery of aboveground living woody biomass carbon was highest in the oldest fallow sites and lowest in the new kaingin fallow sites. In new

139 kaingin fallow areas, the high level of aboveground biomass carbon was mainly due to high levels of coarse dead wood remaining as an artefact of forest clearing. Carbon stored in other living biomass was highest in young kaingin fallow areas, where undergrowth and litter biomass carbon was found to increase gradually from new to old kaingin fallow sites. It was again found that biomass carbon recovery was constrained mainly by landscape patchiness, with patch size exhibiting a significant influence on the recovery of biomass carbon at different aboveground carbon pool.

7.5 Soil carbon and nutrients in regenerating secondary forests after shifting cultivation The study found limited influence of shifting cultivation on soil organic carbon, soil nitrogen, and phosphorus availability in regenerating secondary forests. A reduced stock of soil available potassium was however found. Site environmental factors like patch size, had the greatest control on the recovery of the pool of soil carbon, soil nitrogen and soil phosphorus. In case of soil potassium in middle (i.e. 6-15 cm) and bottom (i.e. 16-30 cm) soil layer, slope was also found equally important together with patch size in the recovery of potassium in the soil.

7.6 Opportunities for biodiversity and carbon benefits from fallow secondary forests Uncertainties in the biodiversity and carbon dynamics associated with shifting cultivation- fallow secondary forests are one of the main issues hindering its inclusion in major developments in tropical forest conservation using REDD+ and other CDM options. Drawing on the empirical finding from the Philippines upland it was demonstrated that regenerating secondary forests after shifting cultivation have the potentials for inclusion in programs on forest conservation like REDD+ and CDM (see also- Mukul et al., in press).

7.7 Implications of this research The challenge of translating science into policy is a common problem for many applied disciplines including forestry and environmental science (Cook et al., 2013; Bilotta et al., 2014). Evidence-based science provides scientific and other relevant communities like policy makers, an overview of relevant and trustworthy guidelines that are pertinent to informed decision making (Pullin and Knight, 2009). The finding of this research emphasized the importance of Southeast Asian rainforests after major anthropogenic disturbances like shifting cultivation in the context of biodiversity conservation, and carbon and soil quality management. The results conclude that regenerating secondary forests after shifting cultivation can act as a cost-effective conservation, restoration, and forest management option not only in the Philippines but also in other developing

140 countries where the practice of shifting cultivation is common among smallholder rural and upland farmers.

7.8 References Bilotta, G.S., Milner, A.M., Boyd, I., 2014. On the use of systematic reviews to inform environmental policies. Environmental Science & Policy, 42, 67-77. Budiharta, S., Meijaard, E., Erskine, P.D., Rondinini, C., Pacifici, M., Wilson, K.A., 2014. Restoring degraded tropical forests for carbon and biodiversity. Environmental Research Letters, 9, 114020. Chazdon, R.L., 2014. Second growth: The promise of tropical forest regeneration in an age of deforestation. University of Chicago Press, Chicago, IL. Chazdon, R.L., Peres, C.A., Dent, D., Sheil, D., Lugo, A.E., Lamb, D., Stork, N.E., Miller, S.E., 2009. The Potential for species conservation in tropical secondary forests. Conservation Biology, 23, 1406–1417. Cook, C.N., Possingham, H.P., Fuller, R.A., 2013. Contribution of systematic reviews to management decisions. Conservation Biology, 27, 902-915. Hobbs, R.J., Higgs, E., Harris, J.A., 2009. Novel ecosystems: implications for conservation and restoration. Trends in Ecology and Evolution, 24, 599-605. Kummer, D.M., 1992. Upland agriculture, the land frontier and forest decline in the Philippines. Agroforestry Systems, 18, 31-46. Lasco, R.D., Visco, R.G., Pulhin, J.M., 2001. Secondary forests in the Philippines: formation and transformation in the 20th century. Journal of Tropical Forest Science, 13, 652–670. Lawrence, D., Vandecar, K., 2015. Effects of tropical deforestation on climate and agriculture. Nature Climate Change, 5, 27-36. Locatelli, B., Catterall, C.P., Imbach, P., Kumar, C., Lasco, R., Marín-Spiotta, E., Mercer, B., Powers, J.S., Schwartz, N., Uriarte, M., 2015. Tropical reforestation and climate change: beyond carbon. Restoration Ecology, 23, 337-343. McNamara, S., Erskine, P.D., Lamb, D., Chantalangsy, L., Boyle, S., 2012. Primary tree species diversity in secondary fallow forests of Laos. Forest Ecology and Management, 281, 93–99. Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6, 22483. Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of research. Environmental Science & Policy, 55, 167-177.

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Mukul, S.A., Herbohn, J., Firn, J., In press. Co-benefits of biodiversity and carbon from regenerating secondary forests following shifting cultivation in the upland Philippines: implications for forest landscape restoration. Biotropica. Posa, M.R., Diesmos, A.C., Sodhi, N.S., Brooks, T.M., 2008. Hope for threatened tropical biodiversity: lessons from the Philippines. BioScience, 58, 231-240. Pullin, A.S., Knight, T.M., 2009. Doing more good than harm – building and evidence-base for conservation and environmental management. Biological Conservation, 142, 931-934. Suarez, R.K., Sajise, P.E., 2010. Deforestation, swidden agriculture and Philippine biodiversity. Philippine Science Letters, 3, 91-99.

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APPENDICES

Supplmentary Figure 2.1. Country-wise distribution of research on shifting cultivation.

Zambia Zaire Vietnam Venezuela Tonga Thailand Tanzania Suriname Sudan Sri Lanka South Africa Solomon Islands Sierra Leone São Tomé Philippines Peru Paraguay Papua New Guinea Panama Nigeria Nicaragua Mexico Malaysia Madagascar Liberia Lao PDR Ivory Coast Indonesia India Honduras Guinea Guatemala French Guiana Egypt Ecuador Costa Rica Colombia China Cameroon Burkina Faso Brazil Bolivia Bhutan Belize Bangladesh 0 10 20 30 40 50 60 70

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Supplementary Table 3.1. Different measures for diversity and forest structure used in the present study. Parameter Indices Description Biodiversity Species richness (S) Number of unique species 푠 Shannon-Wiener’s Index (H) 퐻 = − ∑푖=1 푝ᵢ(푙푛 푝ᵢ) , Species Evenness Index (J) J= H/ln(S) Forest structure Stem number (N) Number of individuals Basal area (BA) 퐵 = ∑ 0.00007854 푋 DBH2 Leaf Area Index (LAI) Total leaf area/ground area

*where‘S’ is the number of species; ‘N’ is the total number of trees, ‘푝푖’is the proportion of a particular species, and DBH is the diameter at breast height of trees expressed in cm.

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Supplementary Table 3.2. Pearson correlation between site environmnetal attributes. Fallow age Elevation Slope Patch size Distance SOC Fallow age 1 -0.09 0.25 0.07 -0.35 0.05 Elevation -0.09 1 0.52* -0.03 -0.117 0.53* Slope 0.25 0.52* 1 -0.16 0.065 0.43 Patch size 0.07 -0.01 -0.16 1 -0.085 -0.33 Distance -0.35 -0.12 0.07 -0.09 1 -0.01 SOC 0.05 0.53* 0.43 -0.325 -0.005 1 * Correlations significant at p<0.05 level.

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Supplementary Figure 3.1. Importance value of species across the sites of different fallow categories and in control old-growth forest.

Old-growth forest

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Supplementary Figure 3.2. nMDS of richness (stress=11.33) and abundance (stress=13.03) of species of global (as per IUCN Red List) conservation concern using Bray-Curtis distance.

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Supplementary Figure 3.3. nMDS of richness (stress=19.07) and abundance (stress=19.57) of species of local (as per DENR) conservation concern using Bray-Curtis distance.

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Supplementary Table 4.1. Site environmental attributes, mean±SE. Where, EL = elevation, SL = slope, PS = patch size, DIS = distance (from the nearest control forest site), LAI = leaf area index, SOC = soil organic carbon. Site attributes Fallow category Old-growth (unit) ≤5 year 6-10 year 11-20 year 21-30 year forest EL 600.8 549.0 567.2 574.8 512.4 (masl) (±22.19) (±72.41) (±49.24) (±35.35) (±54.77) SL 33 32.4 32.6 38.2 36.4 (degree) (±5.7) (±9.4) (±9.2) (±7.98) (±9.71) PS 1.16 1.14 1.34 1.14 na (ha) (±0.21) (±0.13) (±0.24) (±0.22) DIS 290 540 162 256 na (m) (±74.16) (±114.01) (±198.17) (±153.88) LAI 1.33 5.70 5.14 5.33 6.08 (%) (±0.57) (±0.96) (±1.01) (±0.69) (±0.86) SOC 6.17 6.54 5.21 6.79 4.77 (%) (±0.68) (±2.05) (±0.69) (±1.92) (±1.11) Values in the parenthesis indicates the standarard deviation; na – not available.

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Supplementary Table 4.2. Wood density and characteristics of species recorded from the sites on Leyte Island, the Philippines. Botanical name Local name Origin1 Successional Wood density3 guild2 (gm cm-3) Alangium javanicum (Bl.) Wang Putian Native Secondary 0.78 Dracontomelon dao (Blanco) Merr. & Dao Native Secondary 0.63 Rolfe Dracontomelon edule (Blanco) Skeels. Lamio Native Secondary 0.55 Cananga odorata (Lam.) Hook. f. & Ilang-ilang Native Secondary 0.35 Thomson Polyalthia oblongifolia Burck Lapnisan Native Secondary 0.56 Polyalthia flava Yellow lanutan Endemic Secondary 0.51 Alstonia macrophylla G. Don Batino Native Pioneer 0.56 Alstonia parvifolia Merr. Batino-liitan Endemic Pioneer 0.46 Wrightia pubescens R.Br. Lanete Native Pioneer 0.53 Kibatalia gitingensis (Elmer) Woodson Laneteng-gubat Endemic Secondary 0.46 Arthrophyllum cenabrei Merr. Bingliu Endemic Pioneer 0.41 Polyscias nodosa (Blume) Seem. Malapapaya Native Pioneer 0.37 Areca cathecu L Bunga Native Secondary 0.62 Cocos nucifera L. Coconut Native Pioneer 0.62 Caryota cumingii Lodd. ex Mart. Pugahan Native Pioneer 0.62 Heterospathe elata Scheff. Sagisi Native Pioneer 0.62 Radermachera pinnate (Blanco) Seem. Banai-Banai Native Secondary 0.52 Canarium hirsutum Milipili Native Secondary 0.57 Canarium calophyllum Perkins. Pagsahingin- Native Secondary 0.57 bulog Canarium luzonicum (Blume) A.Gray Piling-liitan Endemic Pioneer 0.43 Calophyllum lancifolium Elmer. Bitanghol-sibat Native Secondary 0.61 Trema orientalis (L.) Bl. Anabiong Native Pioneer 0.36 Celtis philippensis Blanco Malaikmo Native Secondary 0.72 Casuarina equisetifolia L. Agoho Exotic Pioneer 0.92 Gymnostoma rumphianum (Miq.) L.A.S. Mountain Native Secondary 1.0 Johnson agoho Calophyllum blancoi Planch. & Triana Bitanghol Native Secondary 0.53 Terminalia microcarpa Decne. Kalumpit Native Secondary 0.57 Cycas circinalis L. Pitogo Native Pioneer 0.57 Octomeles sumatrana Miq. Binuang Native Secondary 0.32 Dillenia indica L. Handapara Native Secondary 0.65 Dillenia philippinensis Rolfe Katmon Endemic Secondary 0.67 Shorea almon Foxw. Almon Endemic Climax 0.44 Parashorea malaanonan (Blanco) Merr. Bagtikan Native Climax 0.47 Dipterocarpus eurynchus Miq. Basilanapitong Endemic Secondary 0.72 Hopea philippinensis Dyer Gisok-gisok Endemic Pioneer 0.75 Shorea guiso (Blanco) Blume Guijo Native Pioneer 0.77 Shorea palosapis (Blanco) Merr. Mayapis Endemic Climax 0.42 Anisoptera thurifera Palosapis Native Secondary 0.65 Shorea polysperma (Blanco) Merr. Tangile Endemic Climax 0.56 Shorea contorta Vidal White lauan Endemic Climax 0.48 Hopea malibato Yakal-kaliot Native Climax 1.0 Diospyros pilosanthera Blanco Bolong-eta Native Secondary 0.75

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Diospyros blancoi A.DC. Kamagong Native Climax 0.9 Neotrewia cumingii (Müll.Arg.) Pax & Apanang Native Pioneer 0.55 K.Hoffm. Mallotus philippensis (Lam.) Müll.Arg. Banato Native Secondary 0.68 Macaranga tanarius (L.) Müll.Arg. Binunga Native Pioneer 0.48 Macaranga bicolor Muell. -Arg. Hamindang Endemic Pioneer 0.30 Mallotus ricinoides (Pers.) Müll.Arg. Hinlaumo Native Pioneer 0.42 Ormosia calavensis Blanco Bahai Endemic Climax 0.50 Albizia falcataria (L.) Fosberg. Falcata Exotic Secondary 0.31 Leucaena leucaephala (Lam.) de Wit. Ipil-ipil Exotic Pioneer 0.64 Pterocarpus indicus Willd. Narra Native Secondary 0.74 Albizia saponaria(Lour.) Blume ex Miq. Salingkugi Native Secondary 0.66 Senna siamea (Lam.) Irwin et Barneby Thailand Native Secondary 0.68 shower Lithocarpus llanosii (A.DC.) Rehder Ulaian Native Pioneer 0.71 Cratoxylum celebicum Bl. Paguriagon Native Secondary 0.60 Vitex quinata (Lour.) F. N. Williams Kalipapa Native Pioneer 0.50 Vitex turczaninowii (Turcz.) Merr. Lingo-lingo Endemic Secondary 0.64 Premna cumingiana Schauer Magilik Native Secondary 0.66 Tectona grandis L. f. Teak Exotic Pioneer 0.61 Callicarpa elegans Hayek Tigau-ganda Endemic Pioneer 0.40 Cinnamomum cebuense Kostermans Kaningag Endemic Pioneer 0.50 Litsea perrottetii (Bl.) Villar. Marang Native Secondary 0.49 Neolitsea vidalii Merr. Puso-puso Endemic Secondary 0.59 Barringtonia racemosa Spreng. Putat Native Pioneer 0.50 Petersianthus quadrialatus (Merr.) Merr. Toog Endemic Pioneer 0.59 Diplodiscus paniculatus Turcz. Balobo Endemic Secondary 0.63 Pterospermum obliquum Blanco Kulatingan Endemic Pioneer 0.52 Astronia cumingiana S.Vidal Badling Native Pioneer 0.56 Dysoxylum decandrum Merrill. Igyo Native Pioneer 0.58 Toona philippinensis Elmer. Lanigpa Native Pioneer 0.42 Dysoxylum cumingianum C. DC. Tara-tara Native Pioneer 0.64 Artocarpus blancoi (Elmer) Merr. Antipolo Endemic Pioneer 0.60 Artocarpus ovatus Blanco Anubing Endemic Pioneer 0.69 Ficus irisana Elmer. Aplas Native Pioneer 0.44 Ficus balete Merr. Balete Native Pioneer 0.65 Ficus gul K. Schum. & Lauterb. Butli Native Secondary 0.44 Ficus minahassae (Teijsm. & De Vriese) Hagimit Native Secondary 0.38 Miq. Ficus septica Burm. f. Hauili Native Secondary 0.44 Ficus ulmifolia Lam. Is-is Endemic Pioneer 0.44 Ficus callosa Willd. Kalukoi Native Pioneer 0.33 Ficus magnoliifolia Blume Kanapai Native Secondary 0.44 Ficus odorata (Blanco) Merr. Pakiling Endemic Climax 0.44 Ficus vrieseana Miq. Tagitig Native Secondary 0.44 Ficus nota Merr. Tibig Native Pioneer 0.44 Ficus ampelas Burm. f Upling-gubat Native Pioneer 0.33 Myrica javanica Reinw. ex Bl. Hindang Native Secondary 0.62 Knema mindanaensis (Warb.) comb. nov. Bunod Endemic Secondary 0.58 Parartocarpus venenosus (Zoll. & Morr.) Malanangka Native Pioneer 0.42 Becc. ssp. papuanus (Becc.) Jarr.

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Horsfieldia costulata (Miq.) Warb. Yabnob Native Pioneer 0.49 Ardisia pyramidalis (Cav.) Pers. ex A. Aunasin Native Secondary 0.58 DC. Syzygium surigaense (Merr.) Merr. Kagagko Endemic Secondary 0.71 Syzygium crassilimbum (Merr.) Merr. Kaitatanag Endemic Secondary 0.71 Syzygium gigantifolium (Merr.) Merr. Malatalisai Endemic Secondary 0.71 Syzygium hutchinsonii (C.B.Robinson) Malatambis Endemic Secondary 0.71 Merr. Xanthostemon verdugonianus Naves Mangkono Endemic Pioneer 1.05 Strombosia philippinensis (Baill.) Rolfe Tamayuan Endemic Secondary 0.75 Pandanus radicans Blanco Ulangong- Endemic Pioneer 0.33 ugatan Securinega fIexuosa (Muell. -Arg.) Anislag Endemic Pioneer 0.77 Antidesma ghaesembilla Gaertn. Binayuyu Native Climax 0.63 Glochidion camiguinense Merr. Bunot-Bunot Endemic Pioneer 0.61 Glochidion album (Blanco) Boerl. Malabagang Native Pioneer 0.61 Breynia rhamnoides Müll.Arg. Matang-hipon Native Pioneer 0.77 Cleistanthus venosus C.B. Rob. Sarimisim Endemic Secondary 0.67 Bridelia penangiana Hook.f.Bridelia Subiang Native Secondary 0.54 insulana Hance Bischofia javanica Blume Tuai Native Secondary 0.64 Piper anduncum L. Spiked pepper Native Pioneer 0.39 Carallia brachiata (Lour.) Merr. Bakauan-gubat Native Secondary 0.70 Neonauclea formicaria (Elmer) Merr. Hambabalud Endemic Pioneer 0.74 Mussaenda philippica A.Rich. Kahoi-dalaga Native Secondary 0.64 Neonauclea bartlingii (DC.) Merr. Lisak Endemic Secondary 0.74 Canthium fenicis (Merr.) Merr. Mapugahan Endemic Pioneer 0.64 Canthium monstrosum (A. Rich.) Merr. Tadiang-anuang Native Pioneer 0.43 Melicope triphylla (Lam.) Merr. Matang-arau Endemic Pioneer 0.38 Nephelium lappaceum Rambutan Native Pioneer 0.77 Planchonella nitida (Blume) Dubard. Duklitan Exotic Secondary 0.61 Palaquium luzoniense (Fern.-Vill.) Vidal Nato Endemic Secondary 0.71 Pterospermum diversifolium Bl. Bayok Native Pioneer 0.58 Trichospermum involucratum (Merr.) Langosig Endemic Pioneer 0.33 Elmer Leucosyke capitellata (Pair.) Wedd. Alagasi Native Pioneer 0.44 Pipturus arborescens (Link) C. B. Rob. Dalunot Native Pioneer 0.39 Dendrocnide stimulans (L. f) Chew Lingaton Native Pioneer 0.21 Premna odorata Blanco Alagau Native Secondary 0.66 Premna stellate Merr. Manaba Native Secondary 0.66 Leea aculeata Bl. Amamali Native Pioneer 0.57 Unknown Anungo - Secondary 0.57 Unknown Nandamai - Pioneer 0.57 Unknown Pandukaki - Pioneer 0.57 Unknown Pegonngon - Secondary 0.57 Unknown Poelig - Pioneer 0.57 Unknown Siyao - Pioneer 0.57 1where Native – refers to a species naturally occurring in the Philippines, Endemic - refers to a species found only in the Philippines and Exotic – refers to a species that has been introduced in the Philippines.

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2based on experts opinion from the Philippines; where pioneer species generally refers to the early colonizer species with high light demanding and first growing nature, secondary are the intermediary group of species with moderate light demand and growth, and climax species are the characteristics species of a forest ecosystem that are common in the old growth forest, and are shade tolerant. 1meadian wood density value retrieved from the World Agroforestry Centre Wood Density Database on 2014 (http://www.worldagroforestry.org/regions/southeast_asia/resources/db/wd).

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Supplementary Table 4.3. Organic carbon contents in litter and undergrowth samples from the study sites on Leyte island, the Philippines. Site category Carbon (%) in dry biomass* Litter Undergrowth SA0-5 39.56 (±2.52) 37.74 (±3.91) SA6-10 41.17 (±5.49) 39.53 (±3.19) SA11-20 41.46 (±2.13) 44.04 (±1.85) SA21-30 43.45 (±2.57) 44.14 (±1.10) SF 40.37 (±1.73) 42.57 (±1.70) *values in the parenthesis indicate the standard deviation of means.

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Supplementary Table 4.4. Organic carbon contents in dead wood samples from the study sites on Leyte Island, the Philippines. Wood degradation status Carbon (%) in dry biomass* Freshly cut 43.60 (±0.93) Moderately decomposed 40.54 (±2.32) Highly decomposed 41.98 (±1.98) Burnt 46.95 (±0.48) *values in the parenthesis indicate the standard deviation of means.

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Supplementary Table 4.5. Pearson correlation between site environmental attributes. Fallow age Elevation Slope Patch Distance LAI SOC size Fallow age 1 -0.09 0.25 0.07 -0.35 0.57** 0.05 Elevation -0.09 1 0.52* -0.003 -0.12 -0.41 0.53* Slope 0.25 0.52* 1 -0.16 0.07 0.02 0.43 Patch size 0.07 -0.003 -0.16 1 -0.09 -0.04 -0.33 Distance -0.35 -0.12 0.07 -0.09 1 0.22 -0.01 LAI 0.57** -0.41 0.02 -0.04 0.22 1 -0.01 SOC 0.05 0.53* 0.43 -0.33 -0.01 -0.01 1 *Correlations significant at p<0.05 level; **Correlations significant at p<0.01 level.

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Supplementary Table 4.6. Biomass carbon (Mg C) distribution in living woody species (LWBC) in our study sites on Leyte island, the Philippines. Botanical name All sites Site category SA0-5 SA6-10 SA11-20 SA21-30 SF Alangium javanicum (Bl.) Wang 6.21 (1.95%)* 0 (0) 0.91 (2.45%) 0.97 (1.74%) 2.9 (4.83%) 1.43 (0.90%) Albizia falcataria (L.) Fosberg. 0.08 (0.03%) 0 (0) 0 (0) 0.01(0.02%) 0.07 (0.1%2) 0 (0) Albizia saponaria(Lour.) Blume ex Miq. 0.45 (0.14%) 0 (0) 0.02 (0.05%) 0 (0) 0.02 (0.04%) 0.41 (0.26%) Alstonia macrophylla G. Don 0.15 (0.05%) 0 (0) 0.03 (0.07%) 0.07 (0.13%) 0.05 (0.08%) 0 (0) Alstonia parvifolia Merr. 0.01 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0) 0 (0) Anisoptera thurifera 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) Antidesma ghaesembilla Gaertn. 1.63 (0.51%) 0 (0) 1.17 (3.16%) 0 (0) 0.29 (0.48%) 0.17 (0.11%) Ardisia pyramidalis (Cav.) Pers. ex A. DC. 1.60 (0.50%) 0 (0) 0.65 (1.76%) 0.27 (0.49%) 0.09 (0.15%) 0.58 (0.37%) Areca cathecu L 0.15 (0.05%) 0 (0) 0 (0) 0.06 (0.11%) 0.09 (0.15%) 0 (0) Arthrophyllum cenabrei Merr. 0.09 (0.03%) 0 (0) 0 (0) 0.09 (0.16%) 0 (0) 0 (0) Artocarpus blancoi (Elmer) Merr. 2.09 (0.65%) 0 (0.02%) 0.18 (0.48%) 0.37 (0.65%) 0.02 (0.03%) 1.52 (0.96%) Artocarpus ovatus Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) Astronia cumingiana S.Vidal 0.28 (0.09%) 0 (0) 0.02 (0.06%) 0.05 (0.09%) 0.14 (0.24%) 0.05 (0.03%) Barringtonia racemosa Spreng. 1.55 (0.49%) 0 (0) 0.09 (0.25%) 0.20 (0.36%) 0.42 (0.70%) 0.84 (0.53%) Bischofia javanica Blume 15.86 (4.97%) 0 (0) 1.02 (2.74%) 4.38 (7.83%) 2.86 (4.77%) 7.60 (4.79%) Breynia rhamnoides Müll.Arg. 0.29 (0.09%) 0 (0) 0.17 (0.46%) 0.08 (0.14%) 0.04 (0.07%) 0 (0) Bridelia penangiana Hook.f.Bridelia insulana Hance 1.05 (0.33%) 0 (0) 0.06 (0.16%) 0.01 (0.02%) 0 (0.01%) 0.98 (0.62%) Callicarpa elegans Hayek 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) Calophyllum blancoi Planch. & Triana 13.53 (4.24%) 0 (0) 0.24 (0.64%) 0.84 (1.50%) 3.43 (5.72%) 9.02 (5.69%) Calophyllum lancifolium Elmer. 1.39 (0.43%) 1.35 (8.08%) 0.01 (0.03%) 0 (0) 0.02 (0.04%) 0 (0) Cananga odorata (Lam.) Hook. f. & Thomson 0.06 (0.02%) 0 (0) 0.06 (0.15%) 0 (0) 0 (0) 0 (0) Canarium calophyllum Perkins. 0.81 (0.25%) 0.01 (0.06%) 0.11 (0.30%) 0.21 (0.37%) 0.13 (0.22%) 0.36 (0.23%) Canarium hirsutum 0.09 (0.03%) 0 (0) 0 (0) 0.03 (0.05%) 0.05 (0.08%) 0.02 (0.01%) Canarium luzonicum (Blume) A.Gray 0.62 (0.19%) 0 (0) 0.04 (0.11%) 0.03 (0.05%) 0.12 (0.20%) 0.43 (0.27%) Canthium fenicis (Merr.) Merr. 0.31 (0.10%) 0 (0) 0.17 (0.47%) 0 (0) 0.13 (0.22%) 0 (0) Canthium monstrosum (A. Rich.) Merr. 0.16 (0.05%) 0 (0) 0.15 (0.40%) 0.01 (0.02%) 0 (0) 0 (0) Carallia brachiata (Lour.) Merr. 0.20 (0.06%) 0 (0) 0.06 (0.15%) 0.01 (0.02%) 0.04 (0.07%) 0.09 (0.06%) Caryota cumingii Lodd. ex Mart. 3.03 (0.95%) 0 (0) 0.87 (2.37%) 0.43 (0.77%) 0.45 (0.74%) 1.29 (0.81%)

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Casuarina equisetifolia L. 0.18 (0.06%) 0.18 (1.06%) 0 (0) 0.01 (0.01%) 0 (0) 0 (0) Celtis philippensis Blanco 0.78 (0.25%) 0 (0) 0 (0) 0 (0) 0.02 (0.03%) 0.77 (0.48%) Cinnamomum cebuense Kostermans 1.12 (0.35%) 0 (0) 0.05 (0.13%) 0.98 (1.75%) 0.09 (0.15%) 0 (0) Cleistanthus venosus C.B. Rob. 0.02 (0.01%) 0 (0) 0.01 (0.02%) 0 (0) 0.02 (0.03%) 0 (0) Cocos nucifera L. 0.02 (0.01%) 0 (0) 0 (0) 0 (0) 0.02 (0.04%) 0 (0) Cratoxylum celebicum Bl. 1.24 (0.39%) 0 (0) 0.07 (0.18%) 0.01 (0.02%) 1.06 (1.77%) 0.10 (0.06%) Cycas circinalis L. 0.06 (0.02%) 0 (0) 0 (0) 0.06 (0.10%) 0 (0) 0 (0) Dendrocnide stimulans (L. f) Chew 0 (0) 0 (0) 0 (0) 0 (0) 0 (0.01%) 0 (0) Dillenia indica L. 0.02 (0.01%) 0 (0) 0.01 (0.02%) 0 (0) 0.01 (0.02%) 0 (0) Dillenia philippinensis Rolfe 0.52 (0.16%) 0 (0) 0.02 (0.06%) 0.06 (0.10%) 0.22 (0.37%) 0.22 (0.14%) Diospyros blancoi A.DC. 1.67 (0.52%) 0 (0) 0.01 (0.02%) 1.64 (2.93%) 0 (0) 0.03 (0.02%) Diospyros pilosanthera Blanco 1.69 (0.53%) 0 (0) 0.01 (0.02%) 1.04 (1.86%) 0.53 (0.89%) 0.11 (0.07%) Diplodiscus paniculatus Turcz. 2.86 (0.90%) 0 (0) 1.24 (3.36%) 0.23 (0.41%) 0.81 (1.34%) 0.58 (0.36%) Dipterocarpus eurynchus Miq. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0) 0 (0) Dracontomelon dao (Blanco) Merr. & Rolfe 1.13 (0.36%) 0 (0) 0.01 (0.02%) 0.61 (1.08%) 0.04 (0.07%) 0.48 (0.30%) Dracontomelon edule (Blanco) Skeels. 0.36 (0.11%) 0 (0) 0 (0) 0.02 (0.04%) 0.02 (0.03%) 0.31 (0.20%) Dysoxylum cumingianum C. DC. 2.01 (0.63%) 0 (0) 0.15 (0.39%) 0.21 (0.37%) 0.16 (0.26%) 1.50 (0.95%) Dysoxylum decandrum Merrill. 1.89 (0.59%) 0 (0) 0.01 (0.01%) 0.07 (0.13%) 0.16 (0.27%) 1.65 (1.04%) Ficus ampelas Burm. f 1.11 (0.35%) 0 (0) 0.13 (0.35%) 0 (0.01%) 0 (0) 0.98 (0.62%) Ficus balete Merr. 16.97 (5.32%) 0 (0.01%) 0.53 (1.43%) 2.75 (4.91%) 0 (0) 13.69 (8.64%) Ficus callosa Willd. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0.01%) 0 (0) Ficus gul K. Schum. & Lauterb. 1.03 (0.32%) 0.01 (0.03%) 0.47 (1.25%) 0.13 (0.24%) 0.27 (0.45%) 0.15 (0.10%) Ficus irisana Elmer. 0.21 (0.06%) 0 (0) 0.07 (0.20%) 0.10 (0.18%) 0.03 (0.05%) 0 (0) Ficus magnoliifolia Blume 0.58 (0.18%) 0 (0) 0.53 (1.44%) 0.04 (0.08%) 0.01 (0.01%) 0 (0) Ficus minahassae (Teijsm. & De Vriese) Miq. 1.72 (0.54%) 0.01 (0.04%) 0.50 (1.34%) 1.09 (1.94%) 0.02 (0.03%) 0.11 (0.07%) Ficus nota Merr. 0.36 (0.11%) 0 (0.01%) 0.24 (0.63%) 0.05 (0.09%) 0.01 (0.01%) 0.06 (0.04%) Ficus odorata (Blanco) Merr. 0.11 (0.04%) 0 (0) 0.09 (0.25%) 0 (0.01%) 0.02 (0.03%) 0 (0) Ficus septica Burm. f. 0.56 (0.18%) 0 (0.03%) 0.49 (1.33%) 0.07 (0.12%) 0 (0) 0 (0) Ficus ulmifolia Lam. 0.12 (0.04%) 0 (0) 0.04 (0.12%) 0 (0.01%) 0.06 (0.10%) 0 (0) Ficus vrieseana Miq. 0.15 (0.05%) 0 (0) 0 (0) 0 (0) 0 (0) 0.15 (0.09%) Glochidion album (Blanco) Boerl. 0.26 (0.08%) 0 (0) 0.02 (0.06%) 0 (0.01%) 0.01 (0.02%) 0.22 (0.14%) Glochidion camiguinense Merr. 1.07 (0.34%) 0 (0) 0.22 (0.59%) 0.02 (0.04%) 0.09 (0.16%) 0.74 (0.47%) Gymnostoma rumphianum (Miq.) L.A.S. Johnson 1.18 (0.37%) 0 (0) 0.38 (1.02%) 0 (0) 0.81 (1.34%) 0 (0) Heterospathe elata Scheff. 0.34 (0.11%) 0 (0) 0.03 (0.09%) 0.03 (0.05%) 0 (0.01%) 0.28 (0.18%)

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Hopea malibato 0 (0) 0 (0) 0 (0) 0 (0) 0 (0.01%) 0 (0) Hopea philippinensis Dyer 3.12 (0.98%) 0 (0) 0.43 (1.16%) 0.22 (0.40%) 0.08 (0.13%) 2.40 (1.51%) Horsfieldia costulata (Miq.) Warb. 2.81 (0.88%) 0 (0) 0.34 (0.91%) 0.68 (1.22%) 0.50 (0.83%) 1.29 (0.82%) Kibatalia gitingensis (Elmer) Woodson 1.87 (0.58%) 0 (0) 0.01 (0.02%) 0.74 (1.33%) 0.89 (1.47%) 0.23 (0.15%) Knema mindanaensis (Warb.) comb. nov. 0.56 (0.18%) 0 (0) 0.07 (0.18%) 0.02 (0.03%) 0.48 (0.80%) 0 (0) Leea aculeata Bl. 0.05 (0.02%) 0 (0) 0 (0.01%) 0.02 (0.03%) 0 (0) 0.04 (0.02%) Leucaena leucaephala (Lam.) de Wit. 0.16 (0.05%) 0 (0) 0 (0) 0.15 (0.27%) 0.01 (0.02) % 0 (0) Leucosyke capitellata (Pair.) Wedd. 0.69 (0.22%) 0 (0.03%) 0.30 (0.81%) 0.32 (0.57%) 0.02 (0.03%) 0.05 (0.03%) Lithocarpus llanosii (A.DC.) Rehder 20.40 (6.39%) 0.60 (3.56%) 9.60 (25.87%) 4.62 (8.26%) 4.84 (8.06%) 0.75 (0.48%) Litsea perrottetii (Bl.) Villar. 0.38 (0.12%) 0 (0) 0.11 (0.30%) 0.08 (0.14%) 0.18 (0.30%) 0.01 (0.01%) Macaranga bicolor Muell. -Arg. 0.19 (0.06%) 0 (0) 0.14 (0.37%) 0 (0) 0.04 (0.06%) 0.02 (0.01%) Macaranga tanarius (L.) Müll.Arg. 0.81 (0.25%) 0 (0) 0.63 (1.69%) 0.04 (0.07%) 0.04 (0.06%) 0.10 (0.06%) Mallotus philippensis (Lam.) Müll.Arg. 0.03 (0.01%) 0 (0) 0.03 (0.08%) 0 (0) 0 (0) 0 (0) Mallotus ricinoides (Pers.) Müll.Arg. 0.31 (0.10%) 0 (0.01%) 0.06 (0.16%) 0.15 (0.27%) 0.10 (0.17%) 0 (0) Melicope triphylla (Lam.) Merr. 0.09 (0.03%) 0 (0) 0.02 (0.04%) 0.03 (0.06%) 0.04 (0.06%) 0 (0) Mussaenda philippica A.Rich. 0.01 (0) 0 (0.02%) 0.01 (0.02%) 0 (0) 0 (0) 0 (0) Myrica javanica Reinw. ex Bl. 0.35 (0.11%) 0.30 (1.79%) 0 (0) 0 (0) 0 (0) 0.05 (0.03%) Neolitsea vidalii Merr. 6.08 (1.90%) 0 (0) 0 (0) 2.61 (4.67%) 0.73 (1.22%) 2.73 (1.72%) Neonauclea bartlingii (DC.) Merr. 0.38 (0.12%) 0 (0) 0 (0.01%) 0.05 (0.09%) 0.17 (0.28%) 0.17 (0.11%) Neonauclea formicaria (Elmer) Merr. 1.34 (0.42%) 0 (0) 0.17 (0.46%) 0.81 (1.45%) 0.20 (0.34%) 0.16 (0.10%) Neotrewia cumingii (Müll.Arg.) Pax & K.Hoffm. 0.49 (0.15%) 0 (0) 0.02 (0.06%) 0.01 (0.02%) 0.18 (0.30%) 0.27 (0.17%) Nephelium lappaceum 0.01 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0) 0 (0) Octomeles sumatrana Miq. 0.25 (0.08%) 0 (0) 0 (0) 0 (0) 0.25 (0.42%) 0 (0) Ormosia calavensis Blanco 1.53 (0.48%) 0 (0) 0.81 (2.19%) 0.03 (0.05%) 0.66 (1.10%) 0.04 (0.02%) Palaquium luzoniense (Fern.-Vill.) Vidal 9.60 (3.01%) 0 (0) 0.63 (1.69%) 1.27 (2.27%) 3.32 (5.52%) 4.39 (2.77%) Pandanus radicans Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) Parartocarpus venenosus (Zoll. & Morr.) Becc. ssp. 0.17 (0.05%) 0.02 (0.15%) 0.02 (0.05%) 0.03 (0.05%) 0.02 (0.04%) 0.08 (0.05%) papuanus (Becc.) Jarr. Parashorea malaanonan (Blanco) Merr. 106.08 (33.23%) 3.63 (21.73%) 2.54 (6.84%) 13.57 (24.28%) 12.95 (21.59%) 73.38 (46.30%) Petersianthus quadrialatus (Merr.) Merr. 8.72 (2.73%) 0 (0) 0 (0) 0 (0) 0.39 (0.65%) 8.33 (5.26%) Piper anduncum L. 0.02 (0.01%) 0.00 (0.03%) 0 (0) 0.00 (0.01%) 0.00 (0.01%) 0.01 (0.01%) Pipturus arborescens (Link) C. B. Rob. 0.27 (0.08%) 0 (0) 0 (0) 0.08 (0.14%) 0.19 (0.32%) 0 (0) Planchonella nitida (Blume) Dubard. 1.09 (0.34%) 0 (0) 0 (0) 0.03 (0.06%) 1.06 (1.77%) 0 (0)

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Polyalthia flava 2.59 (0.81%) 0 (0) 0.07 (0.19%) 0.01 (0.03%) 0.01 (0.02%) 2.49 (1.57%) Polyalthia oblongifolia Burck 0.37 (0.12%) 0 (0) 0.17 (0.47%) 0.01 (0.01%) 0.18 (0.31%) 0 (0) Polyscias nodosa (Blume) Seem. 3.23 (1.01%) 0.04 (0.22%) 0.65(1.75%) 0.82 (1.47%) 1.22 (2.04%) 0.51 (0.32%) Premna cumingiana Schauer 0.07 (0.02%) 0.00 (0.03%) 0 (0) 0 (0) 0 (0) 0.06 (0.04%) Premna odorata Blanco 0.14 (0.04%) 0.13 (0.75%) 0 (0) 0.01 (0.03%) 0 (0) 0 (0) Premna stellate Merr. 0.04 (0.01%) 0 (0) 0 (0) 0.04 (0.07%) 0 (0) 0 (0) Pterocarpus indicus Willd. 1.51 (0.47%) 1.51 (9.01%) 0 (0) 0 (0) 0 (0) 0 (0) Pterospermum diversifolium Bl. 0.02 (0.01%) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) 0 (0) Pterospermum obliquum Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Radermachera pinnate (Blanco) Seem. 2.83 (0.89%) 0.01 (0.03%) 1.21 (3.25%) 0.87 (1.56%) 0.58 (0.97%) 0.17 (0.11%) Securinega fIexuosa (Muell. -Arg.) 0.45 (0.14%) 0 (0) 0.16 (0.42%) 0.15 (0.27%) 0.14 (0.23%) 0 (0) Senna siamea (Lam.) Irwin et Barneby 0.02 (0) 0 (0) 0 (0) 0.01 (0.02%) 0.01 (0.01%) 0 (0) Shorea almon Foxw. 0.40 (0.13%) 0 (0) 0.01 (0.02%) 0 (0) 0.40 (0.66%) 0 (0) Shorea contorta Vidal 12.41 (3.89%) 0.26 (1.57%) 2.35 (6.32%) 6.59 (11.80%) 2.67 (4.45%) 0.53 (0.34%) Shorea guiso (Blanco) Blume 8.24 (2.58%) 0 (0) 2.57 (6.92%) 0.71 (1.27%) 0.20 (0.34%) 4.76 (3.01%) Shorea palosapis (Blanco) Merr. 2.47 (0.77%) 0 (0) 0.55 (1.49%) 0.35 (0.63%) 0.03 (0.05%) 1.54 (0.97%) Shorea polysperma (Blanco) Merr. 10.36 (3.25%) 7.39 (44.23%) 0.61 (1.65%) 2.19 (3.91%) 8.17 (13.62%) 1.02 (0.64%) Strombosia philippinensis (Baill.) Rolfe 1.61 (0.50%) 0 (0) 0.25 (0.67%) 0.54 (0.97%) 0.20 (0.34%) 0.62 (0.39%) Syzygium crassilimbum (Merr.) Merr. 0.09 (0.03%) 0 (0) 0.03 (0.07%) 0.02 (0.04%) 0.04 (0.06%) 0 (0) Syzygium gigantifolium (Merr.) Merr. 0.62 (0.19%) 0 (0) 0.22 (0.59%) 0 (0) 0.29 (0.48%) 0.11 (0.07%) Syzygium hutchinsonii (C.B.Robinson) Merr. 1.13 (0.36%) 0.06 (0.34%) 0.16 (0.44%) 0.23 (0.42%) 0.47 (0.79%) 0.21 (0.13%) Syzygium surigaense (Merr.) Merr. 2.51 (0.79%) 0 (0) 0 (0) 0 (0) 0.05 (0.09%) 2.45 (1.55%) Tectona grandis L. f. 0.14 (0.04%) 0 (0) 0 (0) 0 (0) 0.14 (0.24%) 0 (0) Terminalia microcarpa Decne. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0) 0 (0) Toona philippinensis Elmer. 0.84 (0.26%) 0 (0) 0.01 (0.01%) 0.13 (0.23%) 0.13 (0.21%) 0.58 (0.36%) Trema orientalis (L.) Bl. 0.08 (0.03%) 0.00 (0.01%) 0 (0) 0 (0) 0 (0) 0.08 (0.05%) Trichospermum involucratum (Merr.) Elmer 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Vitex quinata (Lour.) F. N. Williams 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Vitex turczaninowii (Turcz.) Merr. 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Wrightia pubescens R.Br. 0.80 (0.25%) 0 (0) 0.56 (1.50%) 0.12 (0.21%) 0.13 (0.22%) 0 (0) Xanthostemon verdugonianus Naves 1.19 (0.37%) 1.19 (7.10%) 0 (0) 0 (0) 0 (0) 0 (0) Anungo 0.98 (0.31%) 0 (0) 0.17 (0.46%) 0.04 (0.07%) 0.03 (0.04%) 0.75 (0.47%) Nandamai 0.001 (0.001%) 0 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0) Pandukaki 0.003 (0.001%) 0 (0) 0 (0) 0 (0) 0.003 (0.01%) 0 (0)

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Pegonngon 0 (0) 0 (0) 0 (0) 0 (0) 0.003 (0.01%) 0 (0) Poelig 0.80 (0.25%) 0 (0) 0.56 (1.5%) 0.12 (0.21%) 0.13 (0.22%) 0 (0) Siyao 1.19 (0.37%) 1.19 (7.10%) 0 (0) 0 (0) 0 (0) 0 (0) * Values in the parenthesis indicatse the percentage share of respective species in sites total living woody biomass carbon.

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Supplementary Figure 4.1. Relative contribution of living stems of different diameter class in living woody biomass carbon (LWBC). Values in the bars indicate absolute contribution (Mg C ha - 1) to LWBC of respective diameter class.

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Supplementary Figure 4.2. Relative contribution of living stems of different height class in living woody biomass carbon (LWBC). Values in the bars indicate absolute contribution (Mg C ha -1) to LWBC of individual height class.

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Supplementary Table 5.1. Pearson’s correlation (2 tailed) between site environmental attributes. Where, FA = fallow age, EL = elevation, SL = slope, PS = patch size, DIS = distance, N = tree species richness, A = tree species abundance, BA = tree basal area, LAI = leaf area index. FA EL SL PS DIS N A BA LAI FA 1 -0.09 0.25 0.07 -0.35 0.73** 0.65** 0.61** 0.57** EL -0.09 1 0.52* -0.01 -0.12 -0.31 -0.16 -0.56* -0.41 SL 0.25 0.52* 1 -0.16 0.07 0.08 0.2 -0.18 0.02 PS 0.07 -0.01 -0.16 1 -0.09 -0.06 0.06 -0.03 -0.04 DIS -0.3 -0.12 0.07 -0.09 1 -0.14 0.13 -0.25 0.22 N 0.73** -0.31 0.08 -0.06 -0.14 1 0.87** 0.68** 0.84** A 0.65** -0.16 0.2 0.06 0.13 0.87** 1 0.58** 0.9** BA 0.61** -0.55* -0.18 -0.03 -0.25 0.68** 0.58** 1 0.69** LAI 0.57** -0.41 0.02 -0.04 0.22 0.84** 0.9** 0.69** 1 **correlation is significant at the p < 0.01 level; *correlation is significant at the p < 0.05 level.

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Supplementary Figure 5.1. Percentage concentrations of soil organic carbon and soil nutrients on Leyte Island, the Philippines. Note the different scales are used on the Y axes.

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