EVALUATION OF RESTORATION:

A GRASSY WOODLAND

BY

PETER WILLIAM BROUGHTON NICHOLS

A Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy at the University of Western Sydney

© Peter Nichols 2005

Acknowledgements

A work of this scale would not have been possible without the assistance of several people. The author would like to express gratitude to the following people for assistance throughout the completion of this Thesis.

Firstly, I would like to thank my supervisors Dr E. Charles Morris (University of Western Sydney) and Dr David Keith (National Parks and Wildlife Service) for their support and guidance throughout all phases of the project. Both have provided timely advice throughout the project and critical comments on the many versions of the draft Thesis. Their assistance has been much appreciated.

Particular thanks go to Peter Wood for his assistance with fieldwork, species identification and comments on draft versions of the Thesis. Thanks are also due to several people who assisted with fieldwork and provided general advice and comment including: Jeanette Lawrence, Paul Nichols, Monique de Barse and Jennifer Fitzgerald. In addition, thanks go to several people working for Greening Australia for help with access to sites and fieldwork equipment and historical documents including Dave Warren, Dan Williams and Judy Christie.

I would especially like to thank my parents-in-law, Alma and Howard Dudgeon for their child minding efforts and my parents, Denise and Alan and Nichols for their timely encouragement and support, especially through the writing phase of the Thesis.

Finally, I would like to thank my wife Coralie Nichols for her patience, good humour and support throughout. Without your love and support, this project would not have been possible. Thank you.

ii Declaration

I certify that this Thesis has not already been submitted for any degree and is not currently being submitted for any other degree or qualification.

I certify that this work is original and a result of my own research. To the best of my knowledge and belief, this Thesis does not contain any material published or written by other persons, except where due reference is made in the text.

Signed,

PETER W. B. NICHOLS

Date:

iii

Table of Contents

Acknowledgements...... ii Declaration ...... iii Table of Contents ...... iv List of Tables ...... viii List of Figures...... xii Appendices ...... xv Summary ...... xvi Chapter 1 ...... 1 Introduction, rationale for study and case study details ...... 1 1.1 Introduction...... 1 Land degradation in Australia...... 2 Revegetation as a form of restoration ...... 4 Current policy in Australia on revegetation...... 4 1.2 Restoration planning...... 6 1.3 Evaluation of Restoration ...... 9 1.4 State and transition models of vegetation dynamics...... 14 1.5 Rationale for this study...... 15 1.6 Previous work ...... 16 1.7 Case study: Cumberland Plain Woodland (CPW)...... 17

Chapter 2 Study location...... 23 2.1 Introduction...... 23 2.2 Study sites...... 31 2.2.1 Hoxton Park (HP) ...... 33 2.2.2 Plough and Harrow (P&H) ...... 34 2.2.3 Western Sydney Regional Park (WSRP)...... 35 2.2.4 Prospect Reservoir (Prospect, PR)...... 37

Chapter 3 Measuring the Success of Revegetation ...... 39 3.1 Introduction...... 39 3.2 Methods ...... 43 Restoration treatment ...... 43 Sampling approach...... 44 Sampling design...... 45 Site selection ...... 46 Data collection ...... 50 Species composition...... 50 Vegetation structure...... 52

iv Environmental data ...... 52 Data analyses ...... 53 Species composition...... 53 Species richness ...... 53 Comparisons amongst treatments ...... 53 Community composition...... 54 Native species returning or not returning to restored pasture as a result of revegetation ...... 55 Temporal development of species composition...... 55 Species contribution: Percentage similarity and dissimilarity...... 55 Plant groups ...... 56 Vegetation structure...... 56 Tree height, foliage cover, percentage cover of rock, bare ground, lichen and litter ...... 56 Environmental variation...... 56 3.3 Results ...... 58 Species richness- total species ...... 58 Species richness- native species (excluding planted species)...... 58 Species richness- native species (including planted species) ...... 60 Species richness- proportion of exotic species ...... 62 Species richness- exotic species...... 64 Vegetation community composition...... 66 All species (excluding planted species) ...... 66 All species (including planted species)...... 67 Native species (excluding planted species)...... 68 Exotic species...... 69 Native species returning after restoration ...... 70 Plant groups ...... 74 Temporal development of species composition...... 75 Species contribution: Comparisons within vegetation communities ...76 Pasture...... 76 Young revegetation...... 77 Old Revegetation ...... 78 Remnant vegetation ...... 79 Species contribution: Comparisons between vegetation communities 80 Species abundance changes after restoration...... 82 Native species ...... 82 Exotic species...... 82 Vegetation structure...... 85 Tree canopy cover...... 85 Tree canopy height...... 87 Shrub crown cover and height ...... 88 Ground layer percentage cover ...... 90 Percentage cover of rock...... 92 Percentage cover of bare ground...... 92 Percentage cover of lichen ...... 94 Percentage cover of litter ...... 94 Principal components analysis (PCA) ...... 95 Linking community analyses to environmental variables ...... 97

v 3.4 Discussion...... 98 Implications for restoration programs...... 106 Effectiveness and potential use of the evaluation methodology...... 107

Chapter 4 The effect of a planted tree canopy on species composition...... 109 4.1 Introduction...... 109 4.2 Methods ...... 111 Site selection ...... 111 Data collection ...... 115 Data analysis ...... 116 Species richness ...... 116 Native species returning to underneath the planted tree canopy...... 116 Multivariate analysis...... 116 Species Composition...... 116 Percentage similarity...... 117 Linking community analyses to environmental variables ...... 117 Environmental variation...... 117 4.3 Results ...... 119 Species number- total species ...... 119 Species richness- native species...... 119 Species richness- exotic species...... 120 Total species composition...... 121 Native species composition...... 122 Exotic species composition...... 123 Species composition: Comparisons within vegetation communities.124 Comparisons between vegetation underneath and outside planted tree canopies...... 125 Species contribution: Underneath planted tree canopies of different planting ages ...... 126 Comparisons between vegetation underneath tree canopies of different ages ...... 127 Linking community analyses to environmental variables...... 128 Principal components analysis (PCA) ...... 128 BIOENV ...... 129 4.4 Discussion...... 130 Implications for restoration programs...... 133

Chapter 5 Seedling Emergence and Establishment after Fire and Neighbour Removal: A comparative analysis between pasture, restored vegetation and remnants ...... 135 5.1 Introduction...... 135 5.2 Methods ...... 140 Experimental design...... 140 Site and vegetation community selection ...... 140 Treatments...... 143 Data collection ...... 147 Species composition...... 147

vi Data analyses ...... 148 Species composition...... 148 Cumulative total number of germinants over time ...... 148 Species richness and total number of germinants ...... 148 Community composition...... 149 Pre-treatment vegetation composition ...... 149 5.3 Results ...... 151 Cumulative total number of germinants over time ...... 151 Number of native species germinants ...... 155 Number of exotic species germinants ...... 158 Vegetation community composition...... 163 Species composition after treatments...... 163 Native species ...... 165 Exotic species...... 168 Comparisons within treatment groups and vegetation communities .170 Pre-treatment species composition ...... 172 5.4 Discussion...... 177

Chapter 6 Summary – Has revegetation been successful in the restoration of abandoned agricultural land? ...... 184 State and transition model for restored grassy woodlands...... 190 (Case study: CPW)...... 190 Implications for restoration programs...... 194 Effectiveness and potential use of the evaluation methodology...... 197

References ...... 198

vii List of Tables

Table 2.1 Climate details of the study location within the Cumberland...... 28 Table 2.2 Number of sampling quadrats at Hoxton Park, all studies ...... 34 Table 2.3 Number of sampling quadrats at Plough and Harrow, all studies ...... 34 Table 2.4 Number of sampling quadrats at WSRP, all studies...... 36 Table 2.5 Number of sampling quadrats at Prospect, all studies ...... 38 Table 3.1 Species planted in restoration process, Sample 1 and 2 ...... 44 Table 3.2 Sites within the Horsley Park Corridor (location) and number of quadrats sampled at each site during each sample...... 46 Table 3.3 Frequency score method illustrated for two species...... 50 Table 3.4 Braun-Blanquet cover-abundance scores...... 51 Table 3.5 Mean number (+-se) of species recorded per quadrat (1024m²) pooled over samples 1 & 2...... 58 Table 3.6 ANOVA of mean number of native species per quadrat ...... 59 Table 3.7 Planned Comparisons of numbers of native species between Vegetation within Time...... 60 Table 3.8 ANOVA of mean number of native species per quadrat (including planted) ...... 61 Table 3.9 Planned Comparisons of numbers of native species between Vegetation within Time (planted individuals included)...... 62 Table 3.10 ANOVA of the proportion of exotic species ...... 63 Table 3.11 Planned Comparisons of the proportion of exotic species between Vegetation within Site (interaction means)...... 64 Table 3.12 ANOVA of mean number of exotic species per quadrat ...... 65 Table 3.13 Comparisons of total species composition (species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM...... 66 Table 3.14 Comparisons of total species composition (species cover-abundance recorded per quadrat, planted individuals included) between vegetation treatments by ANOSIM...... 67 Table 3.15 Differences in between-group pairwise R Values between total species composition (of species cover-abundance recorded per quadrat , planted individuals excluded and included) between vegetation treatments by ANOSIM...... 67

viii Table 3.16 Comparisons of native species composition (of species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM...... 68 Table 3.17 Comparisons of exotic species composition (species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM...... 69 Table 3.18a Native species (planted and unaided) returning after restoration…….70 Table 3.18b Recruitment method breakdown of returned species. Species returning presumed by seed from elsewhere………………………………………………72 Table 3.18c Recruitment method breakdown of returned species. Species returning by self sewn seed presumed from planted parent ………………………………73 Table 3.19 Native species from remnants missing from restored vegetation ...... 73 Table 3.20 Plant groups (returning species) ...... 74 Table 3.21 Pasture vegetation community descriptors (species cover-abundance recorded per quadrat) ...... 76 Table 3.22 Young Revegetation community descriptors (species cover-abundance recorded per quadrat) ...... 77 Table 3.23 Old Revegetation community descriptors (species cover-abundance recorded per quadrat) ...... 78 Table 3.24 Remnant vegetation community descriptors (species cover-abundance recorded per quadrat) ...... 79 Table 3.25 Number of species contributing up to 50% average similarity (species cover-abundance recorded per quadrat)...... 80 Table 3.26 Average % dissimilarity between vegetation groups (species cover- abundance recorded per quadrat) ...... 81 Table 3.27 Average change (+,- compared to previous column) in species abundance after restoration (species cover-abundance recorded per quadrat, Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute) ...... 83 Table 3.28 ANOVA of means of tree cover ...... 86 Table 3.29 ANOVA of means of tree height ...... 87 Table 3.30 ANOVA of shrub percentage crown cover (arcsine transformed, species cover-abundance recorded per quadrat)) ...... 89 Table 3.31 ANOVA of shrub height...... 90 Table 3.32 ANOVA Mean percentage cover ground layer (species cover-abundance recorded per quadrat) ...... 91

ix Table 3.33 ANOVA of percentage cover of bare ground (Arcsine transformed, species cover-abundance recorded per quadrat)) ...... 93 Table 3.34 ANOVA of percentage cover of litter (species cover-abundance recorded per quadrat) ...... 94 Table 3.35 Principal components analysis of environmental variables and the % variation explained...... 96 Table 3.36 BIO-ENV: Environmental variables matched to species composition...... 97 Table 4.1 Location of replicate quadrats sampled ...... 111 Table 4.2 ANOVA of mean number of native species per quadrat ...... 119 Table 4.3 Planned Comparisons of numbers of native species between ...... 119 Table 4.4 ANOVA of mean number of exotic species per quadrat ...... 120 Table 4.5 Global R comparisons of total species composition averaged across groups...... 121 Table 4.6 Number of species contributing up to 50% average similarity (species cover-abundance recorded per quadrat)...... 124 Table 4.7 Underneath planted tree canopy vegetation community descriptors ...... 124 Table 4.8 Outside planted tree canopy vegetation community descriptors ...... 124 Table 4.9 Average % dissimilarity: Underneath planted tree canopy & Outside planted tree canopy...... 125 Table 4.10 Number of species contributing up to 50% average similarity (species cover-abundance recorded per quadrat)...... 126 Table 4.11 Underneath 3-5 year old restored tree canopy vegetation ...... 126 Table 4.12 Underneath 8-10 year old restored tree canopy vegetation ...... 127 Table 4.13 Average % dissimilarity: vegetation underneath tree canopies of different ages ...... 127 Table 4.14 Principal components analysis of environmental variables and the % variation explained...... 129 Table 4.15 BIOENV: Environmental variables matched to species composition .....129 Table 5.1 Experimental design ...... 140 Table 5.2 Sampling events and corresponding dates ...... 147 Table 5.3 Mean number of native germinants (m-2) (se) (untransformed) ...... 155 - Table 5.4 Mean number of native germinants (m ²) (logx+1 transformed) ...... 156 - Table 5.5 ANOVA mean number of native germinants (m ²) (logx+1 transformed, pooled) ...... 156

x Table 5.6 Planned Comparisons of numbers of native species between Neighbour

treatments across vegetation types (logx+1 transformed)...... 156 Table 5..7 Planned Comparisons of numbers of native species between Fire treatments

at different sites (nested within Veg) (logx+1 transformed)...... 156 Table 5.8 Mean number of exotic germinants (m-2) (se) (untransformed) ...... 159 -2 Table 5.9 Mean number of exotic germinants (m ) (log x+1transformed)...... 159 - Table 5.10 ANOVA of mean number of exotic germinants (m ²) (log x+1 transformed, pooled) ...... 160 Table 5.11 Planned Comparisons of numbers of exotic species between neighbour

removal treatments at Vegetation types (logx+1 transformed)...... 160 Table 5.12 Comparisons of mean numbers of exotic species between fire treatments after different neighbour treatments (untransformed)...... 161 Table 5.13 Planned Comparisons of numbers of exotic species between neighbour

removal treatments within fire treatments (logx+1 transformed) ...... 161 Table 5.14 Planned Comparisons of numbers of exotic species between neighbour

removal treatments within fire treatments (logx+1 transformed) ...... 161 Table 5.15 Native species germinants ...... 166 Table 5.16 Exotic species germinants...... 168 Table 5.17 Average similarity within each treatment and vegetation group ...... 170 Table 5.18 Vegetation and treatment group community descriptors...... 171 Table 5.19 Average similarity within each treatment and vegetation group (natives only) ...... 171 Table 5.20 Species recorded in pre-treatment survey and germination success...... 174 Table 5.21 Species not recorded in pre-treatment survey and successfully germinated ...... 175

xi

List of Figures

Figure 1.1 Model illustrating the response of an ecosystem to disturbance ...... 7 Figure 1.2 Model of restoration outcomes. (adapted from Chapman and Underwood 2000) ...... 10 Figure 2.1 Map of the Cumberland Plain, west of Sydney, NSW...... 25 Figure 2.2 Temperature extremes of the Sydney region...... 28 Figure 2.3 Rainfall recorded at Bankstown weather station over duration of sampling...... 29 Figure 2.4 Long-term average monthly maximum and minimum temperature (°C) and total rainfall for the Bankstown area...... 29 Figure 2.5 Rainfall during sampling period and long-term average...... 30 Figure 2.6 Study location in relation to Sydney and NSW...... 31 Figure 2.7 Study sites...... 32 Figure 2.8 Pasture with scattered trees at Hoxton Park ...... 33 Figure 2.9 Remnant vegetation at Plough and Harrow overlooking residential development...... 35 Figure 2.10 Pasture with scattered trees at Plough and Harrow ...... 35 Figure 2.11 Pasture vegetation at WSRP...... 36 Figure 2.12 Remnant CPW at Prospect Reservoir...... 37 Figure 3.1 Location of restoration works by Greening Australia and sampling quadrats, Sample 1 ...... 48 Figure 3.2 Location of restoration works by Greening Australia and sampling quadrats, Sample 2 ...... 49 Figure 3.3 Nested quadrat used for sampling ...... 50 Figure 3.4 Mean native species richness, by vegetation treatment and sampling time59 Figure 3.5 Mean native species richness by vegetation treatment and sampling time (planted individuals included)...... 61 Figure 3.6 Mean proportion of exotic species, by site...... 63 Figure 3.7 Mean exotic species richness...... 65 Figure 3.8 Ordination analysis (nMDS): total species composition...... 66

xii Figure 3.9 Ordination analysis (nMDS): native species composition of species cover- abundance recorded per quadrat ...... 68 Figure 3.10 Ordination analysis (nMDS): exotic species composition (species cover- abundance recorded per quadrat) ...... 69 Figure 3.11 Temporal development of species composition (species cover-abundance recorded per quadrat) ...... 75 Figure 3.12 Mean percentage tree cover per quadrat for each vegetation community at each time of sampling for each site (bars represent se, dashed line represents lower boundary of target of tree cover range, species cover-abundance recorded per quadrat))...... 86 Figure 3.13 Mean tree height per quadrat for each vegetation community at each time of sampling for each site. (bars represent se, area between dashed lines represents lower boundary of target of tree height target) ...... 87 Figure3.14 Mean percentage shrub crown cover per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for percentage shrub cover)...... 89 Figure 3.15 Mean shrub height per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for shrub height)...... 90 Figure 3.16 Mean percentage cover of the ground layer per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for percentage ground layer cover, species cover-abundance recorded per quadrat ...... 92 Figure 3.17 Mean percentage cover bare ground per quadrat for each vegetation community at each time of sampling for each site. (species cover-abundance recorded per quadrat, ...... 93 Figure 3.18 Mean percentage cover litter per quadrat for each vegetation community at each time of sampling for each site. (species cover-abundance recorded per quadrat ...... 95 Figure 3.19 PCA Environmental variables ...... 96 Figure 4.1 Sampling design schematic ...... 112

xiii Figure 4.2 Location of revegetation works by Greening Australia and quadrats sampled ...... 114 Figure 4.3 Sampling quadrat...... 115 Figure 4.4 Mean species richness per quadrat by canopy treatment across sites (m-2) ...... 120 Figure 4.5 Ordination analysis: total species composition ...... 121 Figure 4.6 Ordination analysis: native species composition...... 122 Figure 4.7 Ordination analysis: exotic species composition...... 123 Figure 4.8 PCA of environmental variables ...... 128 Figure 5.1 Location of revegetation works by Greening Australia and sampling quadrats ...... 142 Figure 5.2 Application of slashed strip in pasture vegetation...... 143 Figure 5.3 Fire application in remnant vegetation ...... 144 Figure 5.4 Neighbour removal treatment in remnant vegetation...... 145 Figure 5.5 Neighbour removal, then fire application in pasture vegetation ...... 146 Figure 5.6 Quadrat used for sampling...... 147 Figure 5.7 Mean cumulative number of germinants recorded in pasture vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale ...... 151 Figure 5.8 Mean cumulative number of germinants recorded in restored vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale ...... 152 Figure 5.9 Mean cumulative number of germinants recorded in remnant vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale ...... 152 Figure 5.10 Mean cumulative number of germinants recorded in pasture vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale...... 153 Figure 5.11 Mean cumulative number of germinants recorded in restored vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale...... 153 Figure 5.12 Mean cumulative number of germinants recorded in remnant vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale...... 154

xiv Figure 5.13 Rainfall during sampling period and long-term average...... 154

Figure 5.14 Mean number (logx+1) native species germinants across vegetation communities between neighbour treatments (m-²)...... 157

Figure 5.15 Mean number (logx+1) native species germinants across Fire treatments between sites (m-²) ...... 157

Figure 5.16 Mean number (logx+1) exotic species germinants between neighbour removal treatments in different vegetation groups (m-²) ...... 160

Figure 5.17 Mean number (logx+1) exotic species germinants between fire treatments after different neighbour removal treatments (m-²)...... 161

Figure 5.18 Mean number (logx+1) exotic species germinants between fire treatments at different sites (m-²)...... 162 Figure 5.19 Ordination analysis: total species composition of germinants (site means), week 52...... 164 Figure 5.20 Ordination analysis: native species composition of germinants, week 52...... 167 Figure 5.21 Ordination analysis: exotic species composition of germinants, week 52...... 169 Figure 5.22 Ordination analysis: total pre-treatment species composition...... 176 Figure 6.1 State and transition model for CPW restoration. States include: abandoned pasture, revegetated land and remnant vegetation. See text below for full descriptions of states and transitions...... 191

Appendices

Appendix 3.A Abundance of vascular plant species and their percentage contribution to dissimilarities between four vegetation communities ...... 216 Appendix 3.B Comparisons between vegetation communities...... 233 Appendix 4.C Abundance of vascular plant species ...... 245

xv Summary

The aims of this project were to: 1. further develop the evaluation systems of

Westman (1986), Chapman and Underwood (2000) and Wilkins et al (2004) proposed for the assessment of restored ecosystems; and 2. use these developments to evaluate whether the revegetation of agricultural land on the Cumberland Plain, west of

Sydney, NSW, has led to the re-establishment of a grassy woodland.

The evaluation system developed in this Thesis was designed to compare three key ecosystem attributes. First, to assess how restoration was progressing, the species richness, composition and vegetation structure of abandoned pasture (starting point), was compared to that of restored vegetation of differing ages (putative mid points), and remnants (goal or end point). Refinements of the previous assessment models included formulation of predictions about native and exotic species richness and composition under the assumption that restoration was succeeding, and explicit testing of these predictions by planned comparisons and trajectory analysis of species composition. Second, the small-scale effects of planted tree canopies on species composition were assessed to test the hypothesis that native tree canopies facilitate the return of natives. Third, the effects of fire and neighbour removal on seedling emergence and establishment in pasture, restored vegetation and remnants were examined to explore what factors controlled germination and establishment.

The results of this study indicate that to date, there has been a partial success of the restoration program at the study sites: while native species have returned unaided to restored sites, the trajectory of native species composition was not in the direction of remnants. Native species richness was found to be significantly increased due to

xvi revegetation at one (of two) sampling times only, while other positive changes in species composition and vegetation structure have been uneven and variable. Native species richness increased from approximately 19 to over 32 species per 1024 m² quadrat after revegetation. This is to be compared with a native species richness of 37 species per quadrat found in remnants. Although 23 native species were found to be returning unaided after revegetation, they comprised a different suite of species to those in remnants. Only three species (Aristida ramosa, Glycine tabacina and

Microlaena stipoides var. stipoides) have returned at abundances comparable to that found in remnants. Five species planted in restored sites self-propagated vegetatively.

Native species composition underneath tree canopies remained unchanged following the planting of trees, falsifying the hypothesis that native species return preferentially under tree canopies. There was however, increased species richness of exotic species detected underneath planted tree canopies.

Patterns of seedling emergence observed in this study suggest that recruitment plays a role in the maintenance of the species composition found in restored vegetation, with seedling emergence dominated by exotics. Emergence of exotics responded to any form of neighbour removal; native emergence and establishment was low, and uneven by comparison.

The recruitment of a diverse understorey following tree planting requires additional input to overcome restoration barriers. Further efforts may be needed for an improved trajectory towards success, for example importing additional genetic material via either seed or established seedlings, and creating recruitment opportunities.

xvii

If restoration is held to be a possible answer to degradation of grassy woodland systems, the long time-frames and risks of restoration failure should be acknowledged and accommodated in planning.

The evaluation methodology developed within this Thesis is a transparent and accurate way to measure ecological changes in vegetation that have occurred as a result of restoration.

The restoration evaluation methodology further developed here will be useful to an industry that involves tree planting, landcare, revegetation and bush regeneration. It will complement guidelines provided by government and other sources that advise on practical aspects of revegetation and will be one of the few which have examined the success of revegetation in ecological terms that are founded on sound scientific basis.

xviii Chapter 1

Introduction, rationale for study and case study details

1.1 Introduction

There is a widely recognised imperative for the restoration of ecosystems, both for nature conservation and for sustainable production (Hobbs 1993, Box 1996). Jackson et al (1995) defines restoration as the process of repairing damage caused by humans to the diversity and dynamics of indigenous ecosystems.

Approaches to nature conservation in recent times have moved on from protection and conservation to encompass regeneration and even fabrication techniques used under the general title of ecological restoration (Box 1996, Ehlrich 1993, Cairns 1993).

Recently restoration ecology has emerged as a new and important approach to protecting and conserving the existing natural capital of ecosystems, restoring biodiversity and saving rare species (Clewell, 2000). Restoration ecology also provides an opportunity for re-invigoration of our depleted agricultural and horticultural lands and the potential to enhance production at the same time (Bullock, 2001). There is no doubt that in the future, restoration ecology will play a large role in biodiversity conservation (Hobbs and Norton 1996, Bullock et al 2001).

Restoration of the world’s ecosystems is a necessity if the problems caused by land degradation are to be overcome. Land degradation is a world-wide phenomenon, affecting nearly twenty percent of the earth’s vegetated land (Burgman and Lindenmayer 1998). The increasing pace and scale of land degradation processes and their consequences necessitate that the discipline of restoration ecology play an ever increasing role to resolve these problems by repairing environmental damage (Hobbs and Harris 2001, Ehlrich 1993, Daily 1993).

Restoration ecology is still an emerging discipline and there are many aspects of ecosystem function that are unknown. A large proportion of the literature deals with the theory of restoration ecology, considerations of scale, setting goals, measuring

1 change, and the use of scientific protocols. There is little in the existing literature that deals with the practical aspects of measuring the success of restoration projects of degraded agricultural ecosystems in an Australian context.

Land degradation in Australia

One major cause of land degradation is the clearing of vegetation (Burgman and Lindenmayer 1998). The effects of clearing include among other things, soil and water quality degradation (salinity, soil erosion), losses in biological diversity (above and below ground, plant and animal), and declines in agricultural productivity. These impacts have been identified by conservationists as requiring urgent remedial action (Cairns 1993).

The effects of European settlement in Australia on the natural ecosystems vary depending on the location, soil type, level of disturbance and type of existing vegetation (Benson and Howell 1990). The fertile soils found in undulating plains that once sustained woodlands throughout Australia were the first to be cleared following settlement for agriculture and grazing (Hobbs and Hopkins 1988, Benson 1991, Lunt and Bennett 2000). These areas were cleared first by settlers mainly because the landforms upon which this vegetation type exists are well suited to pastoral activities and cropping (Bauer and Goldeny 2000, Burgman and Lindenmayer 1998).The removal of woodland vegetation resulted in widespread local and regional extinctions (Goldeny and Bowie 1990, Bennett 1990, Saunders et al 1995). Large areas currently require treatment for degradation. In the Murray-Darling basin for example, it is believed that agricultural productivity is reduced by $200 m annually because of land degradation (Richardson 1990).

The main causes of vegetation change since the beginning of European settlement in Australia have been due to the use of imported techniques of agricultural, pastoral and horticultural activities. These techniques were, and still are, inappropriate to the Australian environment because most of the soils in Australia are old, shallow and infertile compared to those found in Europe. The Australian climate in most areas is harsh, and rainfall unpredictable from year to year and season to season. Agricultural

2 introductions of hoofed livestock, rabbits and weeds into Australian edaphic and climatic conditions has led not only to the failure of many agricultural ventures, but also to swift and possibly irreparable environmental damage (Burgman and Lindenmayer 1998, Clarke 1990).

The woodland that originally existed in Australia has been permanently cleared and replaced by exotic vegetation as a result of European settlement (Burgman and Lindenmayer 1998). In some areas of Australia, only five percent of temperate Eucalyptus woodlands remain. In NSW, seventy to ninety-five percent of the box- ironbark woodlands have been cleared (Yates and Hobbs 2000). In Victoria where woodlands originally occupied just over thirty percent of the land, by 1987 ninety-two percent had been cleared for agriculture (Lunt and Bennett 2000). In the wheat belts of south-western Australia, as little as three percent of some types of woodland remain (Yates and Hobbs 1997a).

Woodlands have been devastated by the impact of European agriculture to the extent that there are few woodland types adequately conserved and many now only exist in the landscape as remnant patches (Burgman and Lindenmayer 1998). As an example, only twenty-five percent of the original woodland vegetation in central NSW remains scattered across the region in 3500 remnants (Goldeny and Bowie 1990).

The management and maintenance of the integrity of these fragments of remnant vegetation will require some human intervention. Most likely, this will take the form initially of conservation and later restoration strategies (Hobbs and Hopkins 1990, Lunt and Bennett 2000).

The main effect of grazing and clearing in Australia’s temperate woodlands, along with fragmentation, has been the loss of habitat and invasion of exotic species and in particular the introduction of exotic grasses and herbs in the understorey. The impact of grazing and clearing is widespread and poses an enormous challenge for the conservation of these ecosystems (Humphries et al 1994, Yates and Hobbs 1997a, Burgman and Lindenmayer 1998).

3 Revegetation as a form of restoration

McDonald and Conroy (1996) suggests that the fundamental goal of restoration is restoring the self-perpetuating capacity of an ecological community. Revegetation can be seen as environmental reconstruction, i.e. the last ditch effort to restore a degraded environment, to reconstruct habitat, and to address other land degradation problems such as soil erosion, lowering of water tables, organic matter loss, and reduction in biodiversity and increasing salinity (Malcom 1990). Revegetation is maximum intervention for the restorationist. Despite this, revegetation is still seen as a valid form of ecological restoration. The measurement of success of revegetation is identical to the measurement of other forms of restoration (McDonald and Conroy, 1996) .

Revegetation is thought to be one way of achieving the pre-existing natural balance by reintroducing the structural elements once present in the landscape and is widely understood to be a response to wildlife conservation issues resulting from the clearing of native vegetation in rural landscapes (Wilson and Lindenmayer 1996, Bruyn et al 1999, Windsor, 2000).

Past research on temperate eucalypt woodlands has focused on identifying the processes of degradation and these are now relatively well documented. There is a need to change the focus of research to developing solutions to these problems (Yates and Hobbs 1997a).

Current policy in Australia on revegetation

Revegetation through tree planting is the most strongly supported method of land restoration in Australia. Since the mid 1980’s, Government sponsored programs such as the Natural Heritage Trust, Landcare, One Billion Trees, and Save the Bush and have promoted a large number of planting and fencing projects aimed at restoring native vegetation on farms and other privately owned lands.

4 Public authorities and forestry and mining companies have also committed significant resources to revegetation activities. The annual national commitment to revegetation adds up to millions of dollars.

While initially much revegetation work was carried out only in a local context, there has been an increasing emphasis on regional co-ordination through Catchment Management Committees and Regional Vegetation Plans. In NSW, for example, the Native Vegetation Act (1997) aimed to regulate clearing and plan revegetation in a manner mindful of regional goals for conservation and sustainable production. These plans identify areas where the condition of native vegetation should be improved and recommend areas that should be revegetated. The Native Vegetation Act (2003), which superseded the earlier Act, has as one of its main objects to encourage the revegetation of land, and the rehabilitation of land, with appropriate native vegetation.

In addition, provision has been made within the Act to direct landholders to carry out one or more of the following types of remedial work: (a) Work to repair any damage caused by the clearing; (b) Work to rehabilitate any land affected by the clearing (including the taking of steps to allow the land to regenerate); and, (c) Work to ensure that specified land, or any specified river or lake, will not be damaged or detrimentally affected, or further damaged or detrimentally affected, by the clearing.

Similarly in Victoria adoption of a policy originally termed ‘No Net Loss' of native vegetation was founded on the premise that any continuing losses of native vegetation can and must be balanced by gains through revegetation (Department of Natural Resources and Environment, 2004). The Victorian State Government revamped this policy and has recently released a new framework for managing native vegetation in Victoria. The new framework establishes the strategic direction for the protection, enhancement and revegetation of native vegetation across the State. It addresses native vegetation from a whole catchment perspective, but with a focus on private land where the critical issues exist from past clearing and fragmentation of native vegetation. The new policy term coined by the Victorian Government is called ‘Net Gain’. The objectives are to both better manage and increase a reversal, across the

5 entire landscape, of the long-term decline in the extent and quality of native vegetation, leading to a Net Gain (Department of Natural Resources and Environment, 2004).

The Queensland State Government also adopted measures in 2003 to reduce the amount of native vegetation clearing by introducing a halt in processing applications to clear native vegetation. Penalties for clearing without approval include not only exclusion from further approvals to clear native vegetation, but also revegetating cleared land. Approval of a property vegetation management plan is an essential requirement for permits to clear native vegetation. This plan must include information on proposed vegetation rehabilitation or restoration (Department of Natural Resources and Mines, 2003).

Despite the substantial reliance by governments and their departments throughout Australia on revegetation as a remedy to excessive vegetation clearing and land degradation, little has been done to critically examine whether these initiatives have been actually successful in terms of rehabilitating habitats for native vegetation. In other words, it is still unknown whether the activity of revegetation actually encourages the survival of sustainable native vegetation in agricultural lands.

1.2 Restoration planning

The initial step in planning a restoration project is to identify and control the cause of degradation (Hobbs and Norton 1996, Chapman and Underwood 2000). If the ecosystem has residual resilience, removing the cause of the degradation may be sufficient to shift the ecosystem into a trajectory of recovery rather than one of degradation (Hobbs and Norton 1996, Yates and Hobbs 1997a).

Westman (1986b) defined resilience of a disturbed ecosystem as the degree, manner and pace of its recovery to the pre-disturbance level. There are four components to resilience including elasticity, amplitude, hysteresis, and malleability. Figure 1.1 (adapted from Westman 1986b) illustrates the response of an ecosystem to a disturbance (Majer 1990). Elasticity, the rate of recovery of an ecosystem, is a

6 commonly chosen attribute to measure when trying to determine the success of a restoration project.

Figure 1.1 Model illustrating the response of an ecosystem to disturbance Figure shows the five components of resilience following cessation of the stress. From (Majer 1990)

Land that has experienced a lower degree of impact from human activity is likely to have higher resilience than are zones of higher impact, irrespective of the type of impact (McDonald and Conroy, 1996) .

The identification of an ecosystem’s resilience level is one of the first steps in the restoration process. It can often dictate the level of intervention required to place the ecosystem in a trajectory of recovery. For example, advantage can be gained from prioritising the treatment of less damaged remnants to optimise their capacity for reintegration into larger areas.

The measurement of the success of restoration is burdened with problems, most particularly the wide temporal and spatial variation inherent in natural systems. “Restoration can only be identified as an interaction between patterns in space and patterns in time, in the opposite direction to that typically used for the detection of environmental impacts” (Chapman and Underwood 2000). The specification of goals is also one of the most important parts of defining success of a restoration project (Ehrenfeld, 2000) as these identify the parameters of the project and set the measures

7 of success (Box 1996, Jackson et al 1995, Chapman and Underwood 2000, Cairns 1993).

The features that successfully restored vegetation should contain are a vital part of goal specification. Restoration target conditions are usually specified that represent degraded natural vegetation communities (Hobbs 1993, Hobbs and Norton 1996). Measurements of ecosystem attributes such as restoration trajectories, species composition, vegetation structure and ecosystem function can be used to measure restoration success (Hobbs and Norton 1993 , Hobbs and Norton 1996, Wilkins et al 2004). Identification and detailed specification of the chosen ecosystem attributes during the restoration planning process are critical to the evaluation of restoration progress. Without identification of the goal, restoration success may never be claimed. Key to restoration success is the directed succession of the degraded vegetation towards conditions found in reference conditions (Hobbs 1993, Hobbs and Norton 1996).

According to Hobbs and Norton (1996), successful incorporation of restoration into land management requires a number of essential processes, including: a) Identification of the degrading processes; b) Developing methods to reverse the degrading processes; c) Recognising the ecological limitations, the determination of realistic goals for re- establishing species and ecosystems; d) Development of simple measures of success; e) Development of practical techniques for the accomplishment of the restoration objective; f) Documentation and communication of these restoration techniques for widespread use; g) Monitoring key system variables and assessment of restoration against agreed goals.

8 Reinstatement of ecosystem function, variability and unpredictability into assemblages may be as important as restoring average abundances and diversity and one may not be able to exist without the others (Chapman and Underwood 2000, Holmes and Richardson 1999, Armstrong 1993).

In addition to the biological considerations of restoration, Higgs (1997) asserts that good restoration requires an expanded view that includes historical, social, cultural, political, aesthetic, and moral aspects. Ecological fidelity is also an essential ingredient, and is based on three principles: (1) structural/compositional replication; (2) functional success; and, (3) durability. The results of an inclusive restoration project will achieve both ecological fidelity and fulfilling human relationships with ecosystems (Higgs 1997).

1.3 Evaluation of Restoration

Figure 1.2 below, describes diagrammatically the model for measuring attributes that would best describe potential outcomes regarding the evaluation of restoration projects. There are four possible trajectories of the selected response variable after restoration. These are, that after restoration: 1. the variable measured approximates those found in reference remnants (restoration success); 2. the variable has moved away from the degraded condition towards the remnant but has not attained a similar value; the trajectory is however towards the reference sites (restoration partial success, on trajectory);and , 3. the variable has moved away from the degraded condition, part of the way towards the reference condition, but is on a trajectory that is not towards the reference condition eg parallel to the reference condition (restoration partial success, not on trajectory); and, 4. the variable has not responded to restoration at all and remains similar to those values found in controls (restoration failure).

9

Figure 1.2 Model of restoration outcomes. (adapted from Chapman and Underwood 2000) Comparison of potential responses of environmental variables to restoration between restored sites, reference sites and control sites. Restored sites shown as dashed lines. Range of restoration outcomes shown includes 1. success; 2. partial success- on trajectory towards remnants; 3. partial success- not on trajectory towards remnants; 4. failure. For details, see text.

The lack of a clear definition of restoration ecology has been identified as one of the barriers to an adequate definition of the success of an individual project. Hobbs and Norton (1996) argue that restoration consists of a continuum of activities and achievements and therefore cannot be unambiguously defined. The specific objectives of restoration may change in response to changes of the ecosystem and interactions with the natural environment.

According to Chapman and Underwood (2000), the argument that unambiguous definitions are not possible presents two problems for the process of project evaluation. First, without a definition of what the restoration is to achieve beforehand, it will be impossible to use any scientifically rigorous protocol to determine whether it has been successful; and second, because of the lack of forethought regarding what the restoration may achieve, all of the definitions used by ecologists and planners are irrational and unattainable. This does not mean evaluation of restoration is pointless.

10 What it does highlight, is the need for prior planning and continuous objective setting for individual projects. This would allow future evaluation and ongoing monitoring of progress against the set objectives.

Due to the nature of restoration programs being completed in complex ecosystems, the restored area will change over time, hopefully, gradually converging with the reference areas (Hobbs and Norton 1996, Cairns 1993). Restoration must also correct the causes of the degradation not just the symptoms. These causes too may be measured (Cairns 1993).

In addition, the restored habitat must be contrasted with a number of different reference sites. The use of a single reference area does not allow for differences seen to be directly attributed to the effects of the restoration project. The definitive aim of restoration is often to establish a self-maintaining, ecologically functioning piece of habitat (Chapman and Underwood 2000).

Success of restoration is based on performance criteria or standards. These may also be named design criteria or success criteria. These standards are largely derived from an understanding of the reference ecosystem. They provide an empirical basis from which to determine whether the project objectives have been attained and account for ongoing disturbances experienced by the reference ecosystem (Chapman and Underwood 2000).

A high-quality example of an evaluation framework was developed by Westman (1986a) who identified three potential strategies for conducting an evaluation: direct comparison, attribute analysis and trajectory analysis:

• Direct comparison: selected ecosystem parameters are determined in the reference system and restoration sites and directly compared. This type of evaluation would provide a limited basis for interpretation of results. • Attribute analysis: ecosystem attributes are assessed in relation to one or more of the following, o Characteristic assemblage of species;

11 o Indigenous species are present to the maximum practical extent; o All functional groups necessary for the continued development/functioning of the ecosystem are represented or have the potential to colonise by natural means; o The physical system is capable of sustaining reproducing populations of the species necessary for continued stability or development along the desired trajectory; o The ecosystem functions apparently normally for its ecological stage of development; o The ecosystem is suitably integrated into a larger ecological matrix with which it interacts and exchanges; o Potential threats to the health and integrity of the ecosystem have been eliminated or reduced as much as possible; o The ecosystem is sufficiently resilient to endure normal periodic stress events in the local environment; o The ecosystem is self-sustaining to the same degree as the reference system and has the potential to persist indefinitely.

• Trajectory analysis: involves collecting data periodically to establish trends. Trends that lead towards the reference condition confirm that restoration is following its intended trajectory. Factors to consider when assessing the trajectory of ecosystem recovery include: o Elasticity (speed of the recovery process); o Degree of similarity of recovery; hysteresis (decline trajectory); o Damping (amount of fluctuation of attributes around their desired endpoint); o Barriers to recovery can be identified; o The state and transition model of vegetation dynamics can be applied and current state identified (Westman 1986).

All of the above possibilities are unlikely to be assessed in any one project evaluation. However, one or a few may be selected depending on the nature of the restoration efforts and the ecosystem in question. Direct comparison and attribute analysis are ‘one-off’ measures of ecosystem states at a point in time. Trajectory analysis involves

12 time and is preferable system because it makes it possible to discern between the degrees of restoration success. Trajectory analysis allows us to determine whether a restored ecosystem is on trajectory towards a reference remnant or not.

The ability of plants to directly reflect changes in their physical environment makes them an efficient indicator of environmental change (Landsberg and Crowley 2004, Schmidt et al 1999). However, prior to using plants as bio-indicators, a sound understanding of the ecological characteristics of the plant species used is required (Pywell et al 2003).

Reay and Norton (1999) effectively assessed the success of restoration plantings in New Zealand by sampling vascular plant composition and structure in three different aged restoration plantings (12, 30, and 35 years old) and compared the results with a remnant of the original old-growth forest of the area. Measurements of functional processes, such as dispersal, were also undertaken in this study. The ability of restored areas to recruit and sustain new, introduced species was used as a base line measure of contribution to biodiversity conservation (Tucker and Murphy 1997) and an effective measure of success. Results obtained by Reay and Norton (1999) showed that despite the restoration plantings being dominated by a native tree not indigenous to the area, the plant species had become compositionally more similar to the forest sites with increasing age of restoration. The success of the restoration plantings were largely attributed to the functional processes that initiate regeneration, such as seed dispersal. Without restoration plantings, colonisation of grassland by forest species was found to be slow. The restoration plantings studied were considered to have been successful because they accelerated the return of forest understorey plants, even though the tree canopy composition of the remnant reserved its distinctiveness.

13 1.4 State and transition models of vegetation dynamics

Classical succession theory is based on the assumption that a vegetation community will always tend towards its climax state after disturbance or release from a pressure such as grazing (Clements 1928, 1936).

Alternative models of vegetation dynamics have since been developed, including state-and-transition models that suggest different meta-stable states may exist under the same environmental conditions (Westoby et al 1989, Hobbs 1994, Yates 1997b). Transitions between different stable states may be rapid or irreversible due to climatic events, different management regimes, and disturbances. These factors may act together or individually (Yates 1997b). State and transition models may be useful tools for planning and carrying out restoration projects (Hobbs and Norton 1996, Prober 2002b).

Ecological thresholds that delineate separate states and transition phases may prevent key ecosystem processes, such as recruitment of canopy species. These thresholds may account for the persistence of multiple apparently stable states of degraded, restored and undisturbed woodland ecosystems under the same conditions. For example, recruitment of native plant species (particularly eucalypts) may be mediated by ecological thresholds defined by fire frequency and intensity, and the density of exotic ground cover. Returning one or both of these thresholds to pre-disturbance levels may prove critical in overcoming a barrier to the recruitment of native species, particularly canopy species. The degree of intervention required to return an ecosystem once a threshold has been crossed is likely to increase substantially (Hobbs and Norton 1996).

The development and use of detailed state and transition models within restoration planning and evaluation may be a valuable tool (Yates 1997b). In a study completed by Wilkins (2003) in Cumberland Plain Woodland at study sites near this project, a steady state model of vegetation dynamics was suggested to apply. Detailed state and transition models have been developed for grassy woodland vegetation (Prober, 2002b) but models do not yet consider improved pastures. One such model has been proposed in this Thesis.

14

1.5 Rationale for this study

There are many guidelines provided by government and other sources that advise on practical aspects of revegetation (e.g. Department of Arts 1985, Cremer 1990) however, there are few scientific studies that critically examine the success of revegetation in ecological terms.

Relevant mining industry studies (Fox and Fox 1984, Majer et al 1984, Collins et al 1996, Majer 1989, Greenslade and Majer 1993, Buckney and Morrison 1992) concern themselves with localised sites where vegetation cover has been replaced following mineral extraction from subsurface soil horizons.

There is a considerable difference in the nature of the rehabilitation of mining sites, which are often proximal to large natural areas, and fragmented agricultural landscapes which have been subject to variety of past land management practices. The remaining remnant vegetation in agricultural areas is often small, fragmented, and highly degraded.

Portions of studies already completed in this area are based on comparative surveys that quantify differences between remnant and restored vegetation, but which do not consider the dynamics or sustainability of restored vegetation. A study on the survival and reproduction of reintroduced plantings of a threatened grassland herb (Morgan 1999) in Victoria is one of the few investigations aimed at this level. There are few scientific studies that examine the success of revegetation of Australian agricultural landscapes (Yates and Hobbs 1997b). Recent reviews of restoration success reveal similar gaps in knowledge overseas, but suggest high failure rates (Pimm 1999, Bean et al 1999).

Despite the amount of government and private funds spent and the degree of reliance of law and policy on revegetation to redress clearing and degradation there is a lack of critical evaluation of the success of revegetation works completed in agricultural land.

15 This project intends to fill this gap in knowledge and provide some of the first empirical data upon which to base broader policy decisions regarding the restoration of native vegetation and biological diversity in an agricultural setting.

1.6 Previous work

Research on the ecology of fragmented landscapes has focussed on documenting the impact of vegetation loss and understanding how fragmentation of vegetation influences the decline of biological diversity, particularly birds (Arnold and Weeldenberg 1990, Barrett et al 1994, Luck 2003, Fletcher and Koford 2003, Marzluff and Ewing 2001), mammals (Bennett 1990, Arnold et al 1993, Bladon et al 2002) and to a lesser degree invertebrates (Abensperg-Traun et al 1996, Margules 1992, Sumner et al 2004, Colgan 2002).

Numerous studies have surveyed patterns of species occupancy within and beyond fragments, shelterbelts and hedgerows both in Australia (e.g. Brookerand Brooker, 2003, Loyn 1987, McIntyre and Lavorel 1994, Downes et al. 1997) and internationally (Lewis 1969, Osborn 1984, Limpens and Kapteyn 1989, Schroeder et al. 1992).

The success of restoration programs in Australia has seldom been assessed (Grayson et al 1998). Very few studies have tried to link the survival by a plant species in a location with population-level mechanisms that allow the persistence of native species in fragmented landscapes. Exceptions include work on recruitment in fragmented populations of Salmon Gum in south-western Australia (Yates et al 1995), work on reproductive biology of understorey shrubs in fragmented woodlands of the central- western NSW (Cunningham, 2000) and work on habitat alteration and within- population processes of invertebrates (Stow and Sunnucks, 2004). Several studies have also been completed by Catteral et al (2004) on biodiversity values of reforestated rainforest.

16 1.7 Case study: Cumberland Plain Woodland (CPW)

Cumberland Plain Woodland (CPW) is listed as an endangered ecological community under the NSW Threatened Species Conservation Act 1995 and the Commonwealth Environmental Protection and Biodiversity Conservation Act 1999. There are two main forms of CPW that have been identified (Tozer, 2003), shale hills woodland and shale plains woodland. Shale plains woodland is the most widely distributed form of Cumberland Plain Woodland. Shale hills woodland occurs mainly on the elevated and sloping southern half of the Cumberland Plain.

The diverse understorey layer is similar for both forms of CPW. It is common to find grasses such as kangaroo grass (Themeda australis), weeping meadow grass (Microlaena stipoides var. stipoides) and herbs such as kidney weed (Dichondra repens), blue trumpet (Brunoniella australis) and Desmodium varians.

CPW forms a distinct ecological community confined to the relatively nutrient-rich shale based soils, which can be recognised by a diverse understorey, including a substantial cover of a few dominant grasses. This contrasts with the landscape surrounding the Cumberland Plain, which has an underlying geology of sandstone soils, and an understorey characterised by a complex understorey of sclerophyllous shrubs and relatively few grasses (Benson and Howell 1988).

Before European settlement, Cumberland Plain Woodland was extensive across western Sydney, covering over 125,000 hectares. Two hundred years later, in 1988 just 8% (6420 hectares) remained (Benson 1991). On the Cumberland Plain only 7.7 percent of Shale Plains Woodland and 11.3 percent of Shale Hills Woodland are estimated to remain (Tozer, 2003), with a further 13-14 % enduring as scattered trees across the landscape. Notwithstanding the reductions in area of CPW, it remains an important part of the western Sydney landscape.

Replacement of the native vegetation by agriculture has possibly had the largest effect on native vegetation. A large portion of the Cumberland Plain has been used for cattle and sheep grazing for many years. The use of the land for grazing or agriculture involves clearing of trees and shrubs and the utilisation of the above ground portions

17 of native grasses and herbs. In addition, pasture improvement with over sowing crops or fodder species, fertilisation and artificial irrigation, has been carried out over much of the land once covered by CPW (Benson and Howell 1988).

The portion of the Cumberland Plain selected for study is known as the Horsley Park Corridor, located approximately 15 km west of Parramatta which is approximately 22 km from Sydney.

The Horsley Park Corridor was chosen as study site because the project completed at this location contained the following attributes:

• The goals of the restoration/revegetation program were to reconstruct native vegetation/biological diversity and to connect remnants while using a majority of locally indigenous plants and to improve biological diversity; • There are multiple areas of remnant bushland in close proximity to the revegetated area to serve as reference areas; • All revegetated sites are within a ten kilometre radius and occur within similar habitats to reduce variation between soils, topography and other environmental variables; • A suitable size of revegetated area was available to allow for replicate sampling; • Abandoned pasture was the starting point of the restoration activities. Areas of this vegetation type remained proximal and were abundant. This allowed replicate sampling of this vegetation type; • Adequate documentation was completed prior to and during the revegetation program; • The past land management practices included similar agricultural activities (cropping, improved/unimproved pasture); • The ages of revegetation available in the area include a range from recent to over ten years old and there is a suitable number of sub-sites for adequate replication; • The management histories of sites known and comparable (pre-treatment of pasture, seedling production, planting techniques).

18

To guide the restoration in 1992 Ian Perkins, a consultant to the landowner (Department of Planning), proposed a model of vegetation dynamics that became the basis of a series of Land and Vegetation Management Plans. These plans involved a restoration continuum within which a range of land restoration techniques was used. The main revegetation technique used at these sites was tree planting. In partnership with the Department of Planning, these Land and Vegetation Management Plans were implemented by the non-government natural resource management organisation, Greening Australia.

The essence of the model of vegetation dynamics was competitive exclusion; the planting of native canopy trees in abandoned agricultural land was assumed to affect the composition and structure of surrounding vegetation and encourage convergence of species composition with remnant open woodland. The understorey plants of CPW often rely on underground tubers or profuse annual seed production to survive adverse conditions (Department of Environment and Conservation, 2004). These attributes contribute to the resilience of this ecosystem. During restoration planning Perkins relied on this resilience and assumed that re-creation of a sustainable native grassy woodland was possible through the assisted self-recruitment of native species over time. Reliance on the ability of the ecosystem to return to reference conditions was a central component of the restoration plan (Davies and Christie 2001).

Restoration began with herbicide treatment to patches of pasture. The mechanical planting of trees followed in the treated areas. Mostly tree canopy species were planted. These species were propagated from local seed sources, grown in a nursery and planted out as tube-stock sized plants. Maintenance sprays of herbicide were applied were irregularly applied to reduce competition from exotic weeds.

19 Overall aim The aims of this project were to: 1. further develop evaluation systems, methodologies and frameworks of Westman (1986), Chapman and Underwood (2000) and Wilkins et al (2004) used for the assessment of restored ecosystems; and 2. Use these developments to evaluate whether the revegetation of agricultural land on the Cumberland Plain, west of Sydney, NSW, has led to the re-establishment of a grassy woodland.

The initial questions to be answered by this study include whether the composition and structure of revegetated pasture had changed as a result of revegetation and converged with remnant vegetation which was used as a reference system. The technique of revegetation being measured is the mechanical planting of trees for the specific purpose of creating shade and increasing the ‘halo’ effect around native trees that, according to the model of vegetation dynamics described earlier, encourages the growth and recruitment of native plants (Perkins 1992, Davies and Christie 2001).

A detailed methodology for the evaluation of a restored grassy woodland ecosystem was developed in this Thesis that involved a combination of large scale vegetation sampling of non-permanent plots in conjunction with a range of univariate and multivariate data analysis. This system allowed comparisons to be made between treatments, and two controls; the degraded starting point, and the reference end point. Sampling over a chronosequence allowed identification of restoration trajectories.

A series of three field-based studies were designed to test the effectiveness of this methodology and a series of hypotheses was developed to analyse and compare three key ecosystem attributes:

1. Species composition and vegetation structure of pasture and restored vegetation, and remnants (Chapter 3);

2. The small scale effects of planted tree canopies on species composition (Chapter 4); and,

20 3. The effects of fire and neighbour removal on seedling emergence and establishment in pasture, restored vegetation and remnants (Chapter 5).

One standard feature of all these studies was the use of several local remnants as a reference goal for restoration and making comparisons between remnants, restored vegetation and pasture (used as controls).

The hypotheses explored within Chapters 3 and 4 include that revegetation would: ° Increase native species richness in restored vegetation compared to pasture, that native species richness would increase with time since revegetation, and be similar in restored vegetation to that found in remnants;

° Reduce exotic species richness in restored vegetation compared to pasture, that exotic species richness would decrease with time since revegetation, and be similar in restored vegetation to that found in remnants;

° Encourage species composition in restored vegetation to converge with remnants and diverge from pasture. The extent of convergence was to be greater with time since revegetation. Any trajectory of restoration was to be from pasture towards remnants after revegetation;

° Encourage the structure (eg. height, canopy cover etc) of restored vegetation to converge with remnants and diverge from pasture; and,

° Increase native species richness with time underneath the canopy of planted trees compared to outside the canopy of planted trees and have the opposite effect on exotics.

The study within Chapter 5 investigated the mechanisms of plant germination and establishment across abandoned agricultural pasture, revegetated land and remnant vegetation. There are limited data relating to the temporal dynamics of the original understorey vegetation present in Cumberland Plan Woodland (CPW). An understanding of CPW understorey species’ responses to disturbance is crucial to its successful restoration. The rate of recruitment of native species is crucial in

21 determining the long-term sustainability of the restored vegetation. Key to this is understanding seedling emergence and establishment. These are important factors to consider during the evaluation of restoration success. This study aimed to determine whether there are differences in germination, recruitment and establishment of native plant species between untreated pasture, restored pasture and remnant vegetation that can be attributed to fire or the presence of neighbours.

The hypotheses tested within Chapter 5 were that the two forms of neighbour removal used (fire and slashing) would:

• increase seedling establishment compared to controls;

• may combine in their effects, either additively or interactively;

In addition;

• native and exotic species may react differently to the fire and neighbour removal treatments; and,

• Seedling emergence and establishment response may differ between pasture, restored vegetation and remnants.

22 Chapter 2

Study location

2.1 Introduction

The aim of this project was to develop an evaluation system to determine whether the revegetation of agricultural land on the Cumberland Plain, has led to the re- establishment of a grassy woodland. In order to develop and examine an evaluation system, a large area of restored grassy woodlkand was required for sampling and detailed anaylsis. The portion of the Cumberland Plain selected for study is known as the Horsley Park Corridor, and contains relatively undisturbed bushland remnants, abandoned agricultural land and revegetated agricultural land. Three sites within the Horsley Park Corridor were selected for sampling and were located within approximately twenty km of each other.

The Horsley Park Corridor was chosen as study site because the project completed at this location was one of the largest restoration projects in Australia and contained multiple areas of remnant bushland in close proximity to the revegetated area to serve as reference areas, revegetation sites within a twenty kilometre radius, and were of a suitable size to allow for replicate sampling;

The study was undertaken within the Cumberland Plain (34°S, 151°E) in western Sydney. West of Parramatta, the Cumberland Plain encompasses the area from Sackville in the north to Thirlmere in the south (Figure 2.1).

Geophysical properties of the Cumberland Plain The Cumberland Plain is made up of undulating plains and low hills rising to a maximum altitude of about 350 m altitude. The eastern ridge of the Plain is the catchment boundary and divides drainage to the west to the Hawkesbury River from that to the east draining into the Georges River.

The geology and soil landscapes of the area have been described by Chapman (1989) and consist mainly of clays and shales of the Wianamatta group. The soils comprise

23 claystone, siltstone, laminate and fine to medium-grained lithic sandstone ranging in texture from loam to heavy clay. The Wianamatta group overlies the discontinuous Mittagong Formation and Hawkesbury Sandstone. The Mittagong Formation contains inter-bedded and laminated fine to medium-grained quartz sandstone and siltstone.

The Wianamatta group is overlain with deposited and reworked sediments providing some of the most naturally fertile soils of the region. These predominantly clay soils of relative high nutrient status supported a sub-coastal grassy woodland, also making the land attractive to farmers and graziers from times of early European settlement to the present day for production (Bannerman and Hazelton 1990).

Agricultural development was already underway in 1792 at which time just over 600 hectares were under cultivation in the Parramatta region (Tozer, 2003). By the mid nineteenth century, the majority of the Cumberland Plain was either under cultivation or being grazed. Recent urban development has accelerated the loss and degradation of the Cumberland Plain vegetation (Benson and Howell 1990).

24

Figure 2.1 Map of the Cumberland Plain, west of Sydney, NSW.

25 The soils of the Cumberland Plain have been degraded and eroded, with changes to nutrient levels, by European farming activities such as pasture improvement and fertilisation in combination with intensive grazing. The European history of the study sites has been traced back by Wilson-Fuller (1991) to the early 1800’s when land grants were given (Perkins 1997). Initially grazing and timber getting were the main activities in the area through to the 1900’s. Market gardening and dairy farms then followed from the 1950’s which is the period when pasture improvement and fertilisation took place (Perkins 1997).

Vegetation of the Cumberland Plain CPW is a form of the familiar grassy woodlands that are familiar in the Australian rural landscape. In eastern Australia, sub-coastal grassy woodlands originally extended in a wide band from southern Queensland through to central Victoria, occurring where rainfall variation is between 500-900 mm per year (Keith 2004). CPW occurs throughout the driest part of the Sydney Basin . The understorey plants often rely on underground tubers or profuse annual seed production to survive adverse conditions (Department of Environment and Conservation, 2004).

Substantial losses of the species diversity that has occurred in the vegetation of the Cumberland Plain have been paralleled elsewhere in Australia in sub-coastal grassy woodlands due to the degrading effects brought about by clearing, weed invasion, overgrazing by livestock, and salinisation (Yates and Hobbs 2000).

In recognition of the need to protect, manage and restore remnants, CPW has been listed as an endangered ecological community under the NSW Threatened Species Conservation Act (1995) and the federal Environmental Protection and Biodiversity Conservation Act (1999).

There are two main forms of CPW that have been identified, Shale Hills Woodland and Shale Plains Woodland (Tozer, 2003). Shale Hills Woodland occurs mainly on the elevated and sloping southern half of the Cumberland Plain. The dominant canopy trees include grey box (Eucalyptus moluccana), forest red gum (E. tereticornis) and narrow-leaved ironbark (E. crebra). It has a shrub layer dominated by blackthorn

26 (Bursaria spinosa), with other shrubs, such as Acacia implexa, Indigophora australis and Dodonaea viscosa subsp. cuneata.

Shale Plains Woodland typically occurs on the flat areas with lower rainfall on the Cumberland Plain and is the most widely distributed form of Cumberland Plain Woodland. Bursaria spinosa is the dominant shrub species and canopy trees include Grey Box (E. moluccana), Forest Red Gum (E. tereticornis), Spotted Gum (Corymbia maculata) and Thin Leaved Stringybark (E. eugenioides).

The diverse understorey layer is similar in both forms of CPW. It is common to find grasses, such as kangaroo grass (Themeda australis), weeping meadow grass (Microlaena stipoides var. stipoides) and herbs, such as kidney weed (Dichondra repens), blue trumpet (Brunoniella australis) and Desmodium varians.

The main weather patterns on the Cumberland Plain, including both rainfall and minimum and maximum temperatures, are determined by the distance from the coast and topography (Figure 2.2) (Howell, 2000). Sydney is part of the sub-tropical east coast of Australia, receiving a warm and wet summer to autumn and cool, drier winter and spring seasonal variations. Average annual rainfall is highest closer to the coast and then decreases with distance from the coast. Some locations within the Cumberland Plain receive less than 800 mm per year, whilst rainfall also increases with elevation to approximately 900 mm.

The study site is in the eastern portion of the Cumberland Plain and receives about 900 mm per year on average (Table 2.1) (Anon. 1979). Rainfall over the study period was slightly below average with 58.8 mm per month, compared to the long-term average of 76.8 mm recorded for the duration of sampling at the Bankstown weather station near the study location. The study period included three periods that averaged zero rainfall around the late winter to spring period (Figure 2.3, Figure 2.4, Figure 2.5). Despite this, there were several months of higher than average rainfall scattered throughout the duration of the study period in February 2002, May 2003, and October 2004 and two periods of several months of temperatures that averaged around 30 degrees Celsius (Anon. 1979).

27

Figure 2.2 Temperature extremes of the Sydney region Isotherms in degrees Centigrade: a) average January maxima b) average July minima From Howell (2000)

Table 2.1 Climate details of the study location within the Cumberland Plain (Anon. 1979) Recording Bankstown Mean daily maximum temperature - deg C 23.1 Mean no. of days where Max Temp >= 40.0 deg C 1.1 Mean no. of days where Max Temp >= 35.0 deg C 8.4 Mean no. of days where Max Temp >= 30.0 deg C 36.2 Highest daily Max Temp - deg C 44.8 Mean daily minimum temperature - deg C 12 Mean no. of days where Min Temp <= 2.0 deg C 9.5 Mean no. of days where Min Temp <= 0.0 deg C 1.2 Lowest daily Min Temp - deg C -4 Mean 3pm relative humidity - % 52 Mean monthly rainfall - mm 917 Mean no. of rain days 113.6 Highest recorded wind gust - km/h 133.6 Average no. severe frost days 46

28 300 35

30 250

25 200

20 Rainfall 150 Min. temp.

15 Max. temp. Temp ( °C) Rainfall (mm) 100 10

50 5

0 0 Jul Jul Jul Apr Apr Oct Apr Oct Oct Jun Jan Mar Jun Jan Mar Jun Jan Mar Jan May Feb May Feb May Feb Aug Nov Aug Nov Aug Nov Sep Dec Sep Dec Sep Dec 2002 2003 2004 2005 Time (Year/Month)

Figure 2.3 Rainfall recorded at Bankstown weather station over duration of sampling Precipitation was recorded at Bankstown weather station by the Bureau of Meteorology for the duration of sampling. Rainfall was recorded as 23.6% below average for the entire period, with particularly dry periods during the winter and spring of 2002-2003. Adapted from (Anon. 1979).

140 30

120 25

100 20

80 Rainfall 15 Max. temp. Min. temp. 60 Temp (°C) Rainfall Rainfall (mm)

10 40

5 20

0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Time (Month)

Figure 2.4 Long-term average monthly maximum and minimum temperature (°C) and total rainfall for the Bankstown area. Adapted from (Anon. 1979).

29 300

250

200

150 Rainfall (mm)

100

Actual rainfall during sampling 50 Long term average rainfall

0 Jul Jul Jul Oct Jan Jun Oct Jan Jun Oct Jan Jun Jan Feb Mar Apr Feb Mar Apr Feb Mar Apr Sep Nov Dec Sep Nov Dec Sep Nov Dec Aug Aug May Aug May May 2002 2003 2004 2005 Time (Year/Month)

Figure 2.5 Rainfall during sampling period and long-term average Adapted from (Anon. 1979).

30 2.2 Study sites

The study location (Figure 2.6) sits within the Horsley Park Corridor which forms part of a green-space area located approximately 50 km from the Sydney CBD. It is approximately 15 km west of Parramatta and runs to the south. The Corridor is over 20 km in length, and has a width that ranges from 2 km to 15 km. The northern most portion of the area begins in the upper reaches of Eastern Creek catchment, directly east of, and contiguous with Prospect Reservoir, 4 km south of Blacktown. The southern most point of the Corridor is in the Bringelly, Kemps Creek area.

Four study sites within this location were chosen. Each site, except for the one additional reference site (Prospect), contained areas of abandoned agricultural land, restored vegetation and remnant vegetation. The study sites are hereafter referred to as: Hoxton Park (HP), Plough and Harrow (PH), Western Sydney Regional Park (WSRP), and Prospect Reservoir (Pr) (Figure 2.7).

Study Location

New South Wales

Study Location Parramatta Sydney

N

W E

S

0 500 1000 Kilometres

Figure 2.6 Study location in relation to Sydney and NSW.

31

Figure 2.7 Study sites Locations (circled), dates indicate year of revegetation

32 2.2.1 Hoxton Park (HP) This site is located at 33°52’S, 150°45’E, south of Elizabeth Drive, Cecil Hills (Figure 2.7). The land is owned by the NSW Department of Infrastructure, Planning and Natural Resources and forms part of a wider open space corridor known as the Horsley Park Corridor.

The main past land uses included leasehold grazing and recreation, service corridors for gas, electricity and water. More recently, the construction of the Sydney Orbital (M7) began in 2004 across the eastern portion of the site.

Hoxton Park is generally cleared of woodland vegetation and consists mainly of improved pasture with scattered trees (Figure 2.8). A programme of revegetation was undertaken to restore plant communities representative of the original vegetation communities (Perkins 1997). A number of samples were undertaken in Hoxton Park within each study (Table 2.2).

Remnant vegetation located on the site includes CPW (Shale Hills Woodland and Shale Plains Woodland with a canopy cover of less than 10% (Tozer, 2003).

Figure 2.8 Pasture with scattered trees at Hoxton Park

33

Table 2.2 Number of sampling quadrats at Hoxton Park, all studies Site 2002 2004 Halo study Germination Treatment study Pasture 2 4 8 12 Younger restored 2 4 - - Older restored 2 4 8 12 Remnant 2 4 8 12

2.2.2 Plough and Harrow (P&H) This site is located at 33°52’S, 150°47’E, to the north east of the Hoxton Park site on the northern side of Elizabeth Drive, Cecil Hills (Figure 2.7).

The previous land uses included horse riding and agistment, commercial and retail stock feed business and a semi-rural residential dwelling. A program of revegetation was undertaken to improve the environmental qualities of the site (Perkins 1995). A number of samples were undertaken at Plough and Harrow within each study (Table 2.3).

Remnant vegetation located on the site (Figure 2.9) includes CPW (Shale Hills Woodland with a canopy cover of greater than 10%) (Tozer, 2003). Improved pasture vegetation dominated the site until recent work by the NSW Roads and Traffic Authority involved the installation of a network of roads, carparks, dams and bicycle tracks (Figure 2.10).

Table 2.3 Number of sampling quadrats at Plough and Harrow, all studies Site 2002 2004 Halo study Germination Treatment study Pasture 2 4 8 12 Younger restored 2 4 - - Older restored 2 4 8 12 Remnant 2 4 8 12

34

Figure 2.9 Remnant vegetation at Plough and Harrow overlooking residential development

Figure 2.10 Pasture with scattered trees at Plough and Harrow

2.2.3 Western Sydney Regional Park (WSRP) This site is located at 33°52’S, 150°47’E and is bounded by Wallgrove Road on the west, Cowpasture Road on the east, and The Horsley Drive on the north and Fairfield City Farm on the south (Figure 2.7). A program of revegetation was undertaken in areas with depleted natural recovery capacity to initiate restoration of the CPW (Wilkins, 2001). A number of samples were undertaken at WSRP within each study (Table 2.4).

35 Previous land uses included horse riding and agistment, wholesale flower growing, market gardening, and several semi-rural residential dwellings. A program of revegetation was undertaken to improve the ‘environmental qualities’ of the site (Perkins 1995). A number of samples were undertaken at Plough and Harrow within each study (Table 2.3).

Remnant vegetation located on the site includes CPW (Shale Hills Woodland and Shale Plains Woodland) with a canopy cover of less than 10% (Tozer, 2003). More recently, the Olympic horse-riding course and the Sydney Orbital (M7) have been constructed in the northeastern portion of the site. Pasture vegetation was dominant at WSRP (Figure 2.11) until the extensive revegetation works by Greening Australia began in 1992. These works are widespread throughout the site.

Table 2.4 Number of sampling quadrats at WSRP, all studies Site Study 1 Study 2 Halo study Germination Treatment study Pasture 2 4 - - Younger restored 2 4 - - Older restored 2 4 - - Remnant 2 4 - -

Figure 2.11 Pasture vegetation at WSRP

36 2.2.4 Prospect Reservoir (Prospect, PR) This site is located at 33°47’S, 150°48’E and is bounded by Ferrers, Reservoir, Greystanes and Davis Roads, Prospect (Figure 2.7). This site contains remnant CPW along most of the northern and eastern shores of the reservoir (Figure 2.12).

Since the late 1800’s the main previous and current land use at the site was water storage and conserved land for water catchment. Limited livestock grazing and tree clearing has occurred on this site for over 30 years (MacCormick, 2005) however, most of the intact remnant vegetation appears to be in excellent condition. Previous bushfires were evident at the site whilst the author witnessed one fire during September 2003.

The Prospect Dam was developed for water supply purposes in the 1880s, and includes remains of development and land use from this early period including several heritage items: a road bridge and spillway, Pincott's Roller, the Upper and Lower Canals and associated structures, and the Upper and Lower Valve Houses. Although many activities and developments took place in the late nineteenth and early twentieth century,. An example is the extensive trout hatchery developed at the base of the dam wall from 1895 (Anon., 2005).

Figure 2.12 Remnant CPW at Prospect Reservoir

37 Prospect Reservoir is being used within the first and second comparative analysis studies as a part of this Thesis as an additional reference site, and data used to capture the potential variation within and between other reference areas (Table 2.5).

Prospect was the best available site to be used as a reference remnant with no site on the Cumberland Plain without some European influence. Remnant vegetation located on the site includes CPW (Shale Hills Woodland and Shale Plains Woodland) with a canopy cover of greater than 10% (Tozer, 2003).

Table 2.5 Number of sampling quadrats at Prospect, all studies Site Study 1 Study 2 Halo study Germination Treatment study Pasture - - - - Younger restored - - - - Older restored - - - - Remnant 6 6 - -

38 Chapter 3

Measuring the Success of Revegetation

3.1 Introduction

This study was designed to evaluate the success of revegetation of abandoned agricultural land using a comparative design with two periods of sampling. Current assessments of restoration programs used by funding bodies include indicators such as km fenced, volunteer hours dedicated, and number of tubestock planted but ecological evaluation is not widely applied (Wilkins et al. 2003). It is therefore not possible to know from these largely administrative assessments how effectively the time and money spent on restoration projects have contributed to the restoration of degraded ecosystems (see Chapter 1).

Many restoration projects carried out in grassy woodland ecosystems that have been modified and degraded by a range of land use practices for over two hundred years. The clearing of trees and vegetation, addition of fertiliser and exotic species and grazing by livestock are recognised as the main drivers of ecological change in agricultural landscapes (Prober 2005) and have been the main contributors to degradation at the study site on the Cumberland Plain.

After tree clearing, the transformation of grassy woodland to exotic pasture was accelerated by the application of fertilisers, and sowing of kikuyu, canary grass and clover by landholders seeking to improve native pastures for livestock grazing. These species construct tussocks and runners that modify the movement of surface runoff after rain, change litter accumulation rates, litter quality, and reduce light levels reaching the soil surface (Prober et al 2002a). Such changes negatively affect the conditions required for the germination and establishment of native species and maintain the vegetation structure and habitat in a form that is less favourable for native species and more conducive to the perpetuation of the dominant exotic species (Prober et al 2002a).

39 The goal of the revegetation program completed at the study location was the re- establishment of the original grassy woodland to the ‘highest practicable extent’ (Perkins 1999). It was acknowledged that changes to the physical (biological) environment resulting from revegetation would be gradual and subtle and that they would require long-term commitment before results would become apparent (Davies and Christie 2001). The focus of the restoration of the grassy woodland areas in the study location in particular was reconstruction by revegetation. To guide the restoration of grassy woodlands degraded by these processes on the Cumberland Plain, Perkins (1992) proposed a model of vegetation dynamics that became the basis of management plans implemented by Greening Australia. The essence of the model involves competitive exclusion, whereby local resources (water, nutrients, light) are captured by planted trees, starving the dominant exotic species of the ground layer. The model proposes that the thinning of this inhibitory exotic layer, would affect the species composition of the surrounding environment, allowing native species to enter the understorey community (Davies and Christie 2001).

The majority of species planted at the study location as a part of the revegetation program were trees from the Myrtaceae and Fabaceae families. Large numbers of species from these families were planted in order to reinstate the canopy species that existed prior to disturbance. Species planted included a mixture of relatively short- lived trees that grow quickly (Acacia spp.) and those that grow comparatively slowly but achieve long-term dominance of the community (Eucalypts).

The re-establishment of the grassy woodland has been identified as the target for success of the revegetation program. In order to define the criteria of success for the project, this broad goal has been interpreted to include species richness, species composition and vegetation structure. These attributes have been measured in restored pasture and compared to abandoned pasture (before revegetation treatment) and remnant vegetation (reference). Species composition (and its development over time since restoration) was considered the most important attribute for analysis. Vegetation structure was analysed mainly for its potential contribution to understanding changes in habitat value of the vegetation and the functioning of the ecosystem after revegetation. Changes in vegetation structure may be successfully modified to reflect a reference condition may be achieved with the use of exotic species; therefore, this

40 analysis has been given less weight in the final comparative analysis between restored vegetation and the reference remnants.

Overall Aim: • To determine whether the revegetation of the abandoned pasture at sites on the Cumberland Plain, has led to the re-establishment of a grassy woodland.

To achieve this aim, this study examined a series of hypotheses about the compositional and structural relationships between abandoned pastures, revegetated stands of various ages and remnant woodland vegetation. These are based on expectations derived from Perkins’ (1992) model.

In a grassy woodland, restoration might conceivably take decades. Three questions critical to the assessment of restoration success are:

1. Is species composition of restored vegetation changing?

2. Are these changes on a course (trajectory) to be more similar to remnants?

3. Have the changes to restored vegetation reached the reference condition? Criteria used to determine revegetation success: 1. Species richness Natives: if natives are returning then for native species richness

• Revegetation>Pasture

• Old revegetation>Young revegetation

• Revegetation ≈ Remnant

• Time of sampling 2004>2002 Exotics: if exotics are declining then for exotic species richness

• Revegetation

• Old revegetation

• Revegetation ≈ Remnant

• Time of sampling 2004<2002

41 2. Species composition If revegetation is succeeding then the species composition of

• Revegetation will converge with Remnant (increase similarity)

• Revegetation will diverge from Pasture (increase dissimilarity) and the

• Changes in species composition will be greater in Old revegetation compared to Young revegetation

• Trajectory of species composition of restored vegetation will be from Pasture towards Remnant

3. Vegetation structure If revegetation is succeeding then

• Revegetation will converge with Remnant (increase similarity)

• Revegetation will diverge from Pasture (increase dissimilarity)

• Effects will be stronger in Old revegetation compared to Young revegetation

• Trajectory of restoration will be from Pasture towards Remnant

Test of alternate hypothesis That changes in species richness, composition and vegetation structure are mainly due to environmental factors only including slope, aspect, runoff speed, soil erosion, landform element and landform morphology and are independent of vegetation type or restoration treatment.

42 3.2 Methods

Restoration treatment Revegetation works at the study location began in 1992 with the goal to re-establish the native grassy woodland (Perkins 1992). From the underlying geology and topography present in the Horsley Park Corridor, it was originally assumed by Greening Australia that the sites identified for revegetation were located on land that once contained grassy woodland vegetation (Perkins 1992).

Revegetation started with a glyphosate herbicide treatment of abandoned pasture in long parallel strips at least one-metre wide and approximately three metres apart. After the herbicide began to take effect, the planting of a variety of juvenile (tubestock sized) plant species was undertaken in rows along the treated strips. Most of the species planted were canopy trees, propagated from local seed sources, grown in a nursery and planted out as tube-stock sized plants protected by a staked plastic sleeve. Maintenance sprays of herbicide were applied periodically to reduce competition from exotic weeds. Fencing was erected to exclude livestock from restoration areas and remnants. The mix of species that were planted varied across the landscape, the aim being to match topography and soil with appropriate species (Table 3.1).

43 Table 3.1 Species planted in restoration process, Sample 1 and 2 Species Trees Acacia falcata Shrubs Bursaria spinosa ∑=20 Acacia implexa ∑=7 Dillwynia sieberi Acacia longifolia ssp. longifolia Dodonaea cuneata ssp. cuneata Acacia parramattensis Dodonaea viscosa ssp. cuneata Angophora floribunda Indigofera australis Angophora subvelutina Leptospermum flavescens Casuarina cunninghamiana Ozothamnus diosmifolius Casuarina glauca Other Hardenbergia violacea Corymbia maculata ∑=2 Lomandra longifolia Eucalyptus crebra Eucalyptus eugenioides Eucalyptus fibrosa Eucalyptus moluccana Eucalyptus punctata Eucalyptus tereticornis Melaleuca decora Melaleuca lineariifolia Melaleuca nodosa Melaleuca quinquenervia Melaleuca styphelioides

Sampling approach The size of the restoration programme completed in the Horsley Park Corridor by Greening Australia allowed for a space-For-time (SFT) substitution or chronosequence approach i.e., a comparison of different aged restoration sites within similar localities. SFT substitution allows analyses of trends in vegetation composition to be evaluated over a chronosequence of sites, which are sampled contemporaneously.

The main limitation of SFT is the use of spatial variation as a proxy for past environment status. One critical issue as to the effectiveness of SFT is the role of other historical factors that may influence the system under examination by confounding the inferred temporal trends. In some cases, vegetation succession has been inferred where confounding factors explained much of the variation over time.

44 However, the nature of changes in vegetation structure and species composition has been adequately exposed by SFT in many cases (Pickett 1989).

The alternatives to using the SFT approach included evaluation of the progress of a single revegetation project through time, beginning at year one to encompass the state of the environment before the revegetation treatment, or some form of Beyond BACI (Before-After-Control-Impact) measurement technique. The SFT approach was deemed appropriate given the number and size of revegetated stands available for comparison with acceptable numbers of pasture and remnants in the local vicinity. There are also many potential benefits of evaluating a project over a ten-year period using SFT substitution, the most important feature being able to infer a restoration trajectory. A limitation of SFT is that if spatial variation is of a similar magnitude to temporal variation then temporal trends may not be detected. This may be an issue due to the three-year time limitation on this project.

An important feature of the study design was the use of a remnant reference community that occurred on the same or similar geology, soils, topography and fire history. Based on nearby remnants and habitat models (Tozer, 2000) the disturbed agricultural land was assumed to have once supported Cumberland Plain Woodland (CPW) and most of the areas under restoration and the subject of this study were Shale Hills and Shale Plains woodland forms of CPW.

Sampling design Four sites with similar topography within the Horsley Park Corridor were selected for comparative analysis. The design had the following factors: 1. Vegetation type with 4 levels (pasture, young revegetation, old revegetation, remnant) 2. Time of sampling with 2 levels (November 2002-June 2003, June-August 2004) 3. Site with 3 levels (Hoxton Park-HP, Plough & Harrow-P&H, Western Sydney Regional Park-WSRP). Prospect Reservoir-PR was used as an additional reference site for multivariate analysis.

45 4. At site level, sampling differed between sampling times. During 2002-2003, two quadrats were sampled per site. In the 2004 sample, there were two sub- sites per site with two quadrats sampled per sub-site (Table 3.2).

Table 3.2 Sites within the Horsley Park Corridor (location) and number of quadrats sampled at each site during each sample. Hoxton Park Plough & WSRP Prospect Site (HP) Harrow (WSRP) (PR) (P&H) Year sample taken 2002 2004 2002 2004 2002 2004 2002 2004

Pasture 2 4 2 4 2 4 - - Young (3-6yrs) 3 4 3 4 3 4 - - reveg Old (8-11yrs) 3 4 3 4 3 4 - - reveg Remnant 2 4 2 4 2 4 12 12 Vegetation community

Site selection The four sites were selected to sample similar underlying parent material, topography and vegetation type. Sites were also distributed throughout the study area to provide an adequate representation of the spatial variability in vegetation.

In order to control for environmental variation, the following factors have been either kept within a small range of variation, as far as possible, or randomly selected from topographic maps at sub-site level: slope (0-20%); remnant vegetation type (shale plains and shale hills woodland remnants of Tozer 2003); aspect (0-360 degrees); soil type (clay loams derived from Wianamatta shales); previous agricultural practices (pasture improvement with cattle grazing), and; revegetation technique (mechanical planting). Each vegetation treatment (untreated pasture, revegetated pasture of different ages and remnant vegetation) was mapped on 1:25 000 topographic maps. I verified these maps by site inspection. Due to the disturbed matrix of extant vegetation, the sizes and shapes of the treatment areas were variable. For experimental purposes, sampling was confined to vegetation patches of a minimum size of one hectare and a minimum width of 100 metres.

46 To achieve a balanced sampling design, it was necessary to pool samples of restored vegetation of different ages into two groups. In the repeat survey, the time since restoration progressed by one year from the initial vegetation survey in 2002-03. Prior to each sampling event, patches of vegetation for each treatment were overlain by a grid of 500 metres x 500 metres. These grids were then numbered and a random numbers table used to select the locations of quadrats. A minimum of 2 quadrats in the first and 4 in the second sample were randomly selected within each site and re- selected using the same process during the second sampling event (Figure 3.1, Figure 3.1). An additional layer (sub-site) was used in the second sample because additional sites of revegetation were discovered after the first sample and the additional data collected improved the precision of the comparisons. The sub-sites were selecetd from wihtin the sites in the second time of sampling by marking each site area into numbered grids and randomly selecting subsite locations. The sub-site dimensions were variable and were generally delineated in the field by landform. For example, one site contained several ridges and valleys. This site was then halved into two sub- sites, each of which would have comprised a ridge and a valley of approximately the same size.

47

Figure 3.1 Location of restoration works by Greening Australia and sampling quadrats, Sample 1 Dates adjacent to each planting show age of revegetation (only a small selection of areas and ages shown)

48

Figure 3.2 Location of restoration works by Greening Australia and sampling quadrats, Sample 2 Dates adjacent to each planting shows age of revegetation (only a small selection of areas and ages shown)

49 Data collection

Species composition Vegetation sampling was based on a frequency score method described by Morrison et al (1995). This technique uses nested sub-quadrats in a geometric progression from 1x 1 metre to 32 x 32 metres to calculate frequency scores for each species (Figure 3.3).

Figure 3.3 Nested quadrat used for sampling Model quadrat concept adapted from Morrison et al. (1995) incorporating the nested format to obtain frequency scores with a total area of 1024m². Numbers show dimensions of sub-quadrats in metres.

The presence or absence of each species was recorded within each sub-quadrat and a frequency score was then calculated for each species by summing the number of sub- quadrats (of out seven) in which the species was present (Table 3.3). These scores give a measure of abundance that is equivalent to density (Morrison et al 1995). The two primary axes of the quadrats followed N-S and E-W directions and were established with tape measures and a compass. Fluorescent flags marked the boundaries.

Table 3.3 Frequency score method illustrated for two species (after Morrison et al 1995) Nested 1m² 4m² 16m² 64m² 256m² 1024m² ∑ quadrat (Frequency score) Species A + - - + + + 4 Species B + - + - - + 3

50 Naturally occurring individuals and planted individuals were recorded separately. When planted individuals were excluded, differences in frequency scores between untreated pasture and restored pasture were expected to indicate recruitment of species.

In the first survey, at least two quadrats were established within each vegetation treatment at each sampling site (two in untreated pasture and remnant vegetation and three at both young and old revegetated pasture, giving a total of 10 at each site, except Prospect where 12 quadrats were sampled). In the second survey, two quadrats were established in each vegetation treatment at each sampling sub-site (giving a total of 16 at each site except Prospect where 12 quadrats were sampled) (Table 3.2).

A cover abundance estimate was also assigned to each species according to the Braun-Blanquet scale (Poore 1955) for a 20 metre by 20-metre quadrat (Table 3.4). These cover-abundance estimates were made in the same format as previous surveys completed over a larger area of the Cumberland Plain. The Braun- Blanquet scale is not linear, but approximates a logarithmic scale. Mean abundances in the Braun-Blanquet scale are not absolute abundances.

Table 3.4 Braun-Blanquet cover-abundance scores Species rooted within each nested quadrat were assigned a cover- abundance score from 1-7. 1 Rare, few individuals present <5% cover 2 Uncommon & <5% cover 3 Common & <5% cover 4a Very abundant & <5% cover 4b 5% ≤cover≥20% cover 5 20% ≤cover≥50% 6 50% ≤cover≥75% 7 75% ≤cover≥100%

Species were either identified on site using Harden (1990-1993) as the reference or at the National Herbarium of NSW, Sydney. Reference specimens are held in the herbarium at the Ecology Research Group, University of Western Sydney. Nomenclature is according to Harden (1990-1993). Individual plants that could not be identified due to an inadequate specimen size were not included in the data analyses.

51

Vegetation structure Height and cover of each vegetation stratum (tree, shrub, and ground) were estimated in each quadrat in accordance with vegetation sampling protocols described by Sivertsen and Smith (2001). Within each quadrat and each plant growth form percentage cover was also assessed by eye for rock, bare ground, lichen and litter. Vegetation structure was measured irrespective of whether the plants comprising each stratum were native or exotic.

Environmental data Additional site-specific environmental data was collected at each quadrat. A compass and clinometer were used to measure slope and aspect at the apex of the quadrat, as well as the horizon elevations at azimuths 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°. A Global Positioning System (GPS) was used to determine quadrat locations. Soil type was determined by field technique using Northcote (CSIRO 1960).

Evidence of rock outcrops, erosion, weed infestation, logging, and fire were noted. Interviews were also conducted where possible with local landholders to determine fire histories and disturbance regimes of the last 30 years.

52 Data analyses

Species composition

Species richness Numbers of species, with and without plantings included (native and exotic species, and proportion of exotic species) were compared using a three-level mixed model ANOVA with the following terms: vegetation community (fixed factor), time of sampling (fixed factor), and site (random factor). From the first sample, numbers of species from two replicate quadrats per site of each treatment were used as data for analysis, whilst from the second, the sub-site means of species numbers were used. These analyses excluded planted individuals except where stated.

Analyses were completed both including, and excluding numbers of planted individuals. Numbers of planted individuals were included to acknowledge the amount of revegetation work completed. Analysis was done excluded planted individuals in order to isolate the effects of the revegetation work.

Homogeneity of variances was tested using Cochran’s test and log transformations were used where required to satisfy the assumptiuons of the test (Quinn, 2002).

Comparisons amongst treatments Planned comparisons were made amongst treatment means to test the outcomes expected if revegetation is successful. Interactions were examined for significance (Chapman 1997). Where interaction means were found to be significant, the interaction means were tested. I examined the simple effects of treatments within the interaction (Keppel et al 1992). Three planned comparisons were made to test the hypotheses set out on page 41 including: 1. Pasture vs. pooled revegetation; 2. Young vs. Old revegetation; and, 3. Pooled Revegetation vs. Remnant.

The last possible comparison between Remnant and Pasture was not made because it was considered illogical for the purposes of testing the hypotheses. Where interactions

53 were found to be not significant, the main effect means were tested and the same three planned comparisons made. If revegetation is working then the null hypotheses should be rejected for planned comparisons 1 and 2 and accepted for planned comparison 3.

These three planned comparisons were orthogonal and no adjustments for type I error were made (Quinn and Keogh 2002, Sokal and Rohlf 1995).

Community composition Multivariate analyses were carried out on frequency score data using PRIMER (Clarke and Gorley 2001). Analyses excluded planted individuals except where stated. Similarity matrices were calculated for abundance at quadrat level of total species, native species and exotic species, using the Bray-Curtis metric and a square root transformation. Square root transformation was used to have the effect of down weighting the importance of highly abundant species, so that constructed similarities also depend on less common species (pers.comm. Clarke, 2003).

An ordination analysis was then performed using non-metric multi-dimensional scaling (nMDS). This analysis provided a two or three-dimensional graphical representation of the similarities in species composition between samples

Analyses of similarity (ANOSIM) were used to test for significant differences in species composition between treatments. Where significant differences were found in the Global R, then the pairwise R Values have been used to determine where the between-group differences have arisen: large values (close to 1) are suggestive of complete separation of groups, whilst small values (close to 0) indicate little separation between groups (Clarke and Gorley 2001). In the case of native species composition, the second sample from WSRP contained only one native species, was identified as an outlier in the plot by increasing the similarities between other quadrats and was omitted from presentation in analysis to assist in comparison and presentation of the results. Two-way crossed ANOSIM was used to test simultaneously for differences between treatments and sites. Analyses of the pairwise comparisons showed where the differences occurred within and between treatments.

54 The differences between vegetation communities resulting from the inclusion of planted individuals were measured by the differences in R-values (between-group pairwise analysis) obtained during the ANOSIM analysis before and after planted individuals were included.

Native species returning or not returning to restored pasture as a result of revegetation Native species that were present only in restored vegetation and absent from pasture vegetation were inferred to have returned to the community because of the restoration treatment. These species have been called ‘returning species’.

Similarly, native species that were not recorded in pasture or restored vegetation communities, yet found in remnant vegetation communities, were identified as not having returned to the vegetation after the restoration treatment.

Temporal development of species composition Centroids of vegetation treatments untreated pasture, young and old revegetation groups were calculated from nMDS scores for respective samples at each time of sampling. Two-dimensional x and y co-ordinates were plotted for each sample, along with centroids. These centroids were linked with lines to construct a restoration trajectory of compositional change over the chronosequence. No centroids were calculated for the Remnant group to identify the restoration goal as compositional range, rather than a single point.

Species contribution: Percentage similarity and dissimilarity SIMPER analysis (Clarke and Gorley 2001) was used to determine the contribution of each species to the average similarity within and dissimilarity between vegetation treatments using no standardisation and untransformed data. Species contributing to more than 50% of the dissimilarity between pasture, 3-5 year old restored vegetation, 8-10 year old restored vegetation and remnant vegetation communities were identified. This was repeated for the second sample, giving results for 4-6 year old restored vegetation, and 9-11 year old restored vegetation.

55

The changes in abundances of native and exotic species since restoration were identified from those species contributing to more than 50% of the dissimilarity between pasture, 3-5 yr old restored pasture, 8-10 yr old restored pasture, remnant, 4- 6 year old restored pasture, and 9-11 year old restored pasture vegetation communities. The Braun-Blanquet scale sued within this analysis is non-linear. Compirison of mean abundances can be done, so long as that they are considered relative rather than absolute numbers.

Plant groups Native species that had returned to pasture after revegetation were grouped by the following criteria: native, exotic, perennial, and annual; and categorised into life forms of tree, shrub, forb, or grass. Native species unique to remnants were grouped by the same criteria.

Vegetation structure Tree height, foliage cover, percentage cover of rock, bare ground, lichen and litter Total foliage cover and canopy height of trees, shrubs and ground layer vegetation and percentage cover of rock, bare ground, lichen and litter were compared amongst treatment using the mixed-model analysis of variance (ANOVA) and planned comparisons as detailed in the univariate analyses for species richness above, except that due to the lack of shrubs and trees in pasture vegetation, this treatment was omitted from analysis of tree and shrub data. Homogeneity of variances was tested using Cochran’s test and transformations were necessary (Arcsine transformations were made to percentage cover of shrubs data due to heterogeneous variances (Quinn, 2002).

Environmental variation The testing of the alternate hypothesis: that all changes in species richness and composition were due to environmental factors and not the revegetation treatment, was made by Principal Components Analysis (PCA) and the BIO-ENV procedure from PRIMER (Clarke and Gorley 2001).

56

PCA was used to describe the relationships between environmental variables including slope, aspect, runoff, landform element, and landform morphology. The PCA plot obtained was then visually compared with MDS plots of species composition to understand the degree to which species composition varies with environment. It is possible for a suite of environmental variables to be responsible for structuring species composition in a community (Clarke and Gorley 2001). If these variables are responsible for structuring the species composition in the restored CPW then a PCA in conjunction with a BIO-ENV (below) tests will determine which species group, if any, are dependent on which environmental variables and by how much.

The effects of environmental variables on species composition were further analysed using the BIO-ENV procedure in PRIMER (Clarke and Gorley 2001) to effectively match environmental attributes relationships with each other shown by slope (percentage), aspect (degree), runoff (1-3), landform element (1-3), and landform morphology to the variations evident in the species composition in the different vegetation communities.

57 3.3 Results

Species richness- total species A total of 319 plant species were recorded during sampling (212 native and 107 exotic) (Appendix 3.A).

Old revegetation and remnant had the highest total species richness followed by Young revegetation, then pasture (Table 3.5). There were 29 different species that had been planted in restored vegetation (Table 3.1).

Table 3.5 Mean number (+-se) of species recorded per quadrat (1024m²) pooled over times of sampling 1 & 2 Vegetation community Total species Native species Exotic species Proportion of exotic species (%) Pasture 31.5 (1.0) 18.9 (0.86) 12.6 (0.32) 44.9 (1.3) Young revegetation - 4.5 (0.07) - - (planted) Young revegetation 43.6 (0.9) 26.7 (0.86) 16.9 (0.3) 38.7 (0.74) (non-planted only) Young revegetation 48.1 (0.9) 31.2 (0.47) 16.9 (0.3) 35.1 (0.6) Total Old revegetation - 3.1 (1.05) - - (planted) Old revegetation 49.6 (0.8) 32.5 (0.75) 17.1 (0.4) 34.4 (0.7) (non-planted only) Old revegetation 52.7 (1.33) 35.6 (0.9) 17.1 (0.4) 32.4 (0.86) Total Remnant 47.8 (1.2) 37.3 (0.96) 10.5 (0.28) 21.9 (0.46)

Species richness- native species (excluding planted species) Native species richness differed between the four vegetation type, but in interaction with sampling time (Figure 3.4, Table 3.6); differences between sites were also significant (Site significant, Table 3.6).

The three hypotheses proposed in the Introduction to this Chapter were that for native species richness, revegetation>pasture, older revegetation>younger revegetation and

58 revegetation ≈ remnant. The results showed that the increase in the numbers of natives recorded in restored vegetation compared to pasture was significant for the first sample but not the second, and there were no differences between the other treatments (Time 1, Planned Comparison 1, Table 3.7). While there was a slight trend for more natives in older revegetation compared to young revegetation, this was not significant at both times of sampling. For the comparison of revegetation with remnant, it was not significant at time 1, but significant at time 2, with revegetation less than pasture (Time 2, Planned Comparison 3, Table 3.7).

60

50

40

Time 1 30 Time 2

20

10 Mean no. native species (1024m²) native quadrat per no. Mean

0 Pasture Young reveg Old reveg Remnant Vegetation community

Figure 3.4 Mean native species richness, by vegetation treatment and sampling time

Table 3.6 ANOVA of mean number of native species per quadrat (Planted individuals excluded) Source of variation SS df MS F P F-ratio vs. Veg 2249.35 3 749.78 14.52 0.004* VegxSite Time 31.68 1 31.68 0.30 0.64 TimexSite Site 1329.26 2 664.63 16.31 <0.001* Residual Veg x time 1452.18 3 484.06 6.91 0.02* VegxTimexSite Veg x site 309.74 6 51.62 1.27 0.31 Residual Time x site 208.22 2 104.11 2.56 0.09 Residual VxTxS 420.28 6 70.05 1.72 0.16 Residual Error 977.75 24 40.74 Total 6978.48 47

Cochran C24,1=0.25, NS

59 Table 3.7 Planned Comparisons of numbers of native species between Vegetation within Time (Planted individuals excluded)

2002 (Time 1) SS df MS F1,6 P 1. Pasture vs. pooled reveg 852.64 1 852.64 12.18 <0.025* 2. Young rev vs. old reveg 232.32 1 232.32 3.32 0.1

2004 (Time 2) 1. pasture vs. pooled reveg 189.06 1 189.06 2.70 0.10.50 3. Pooled reveg vs. 1734.72 1 1734.72 24.78 <0.005* remnant Sum for Time 2 1948.15 3 Total 3158.5 6

Species richness- native species (including planted species) When the numbers of planted individuals were included in the analysis, native species richness again increased with revegetation treatment and approached that found in remnants (Figure 3.5). The pattern of this trend differed with the two times of sampling (Veg x Time interaction significant, Table 3.8). Native species richness was greater in revegetation when compared to pasture at both times of sampling; Old revegetation was greater than Young revegetation at the 2002 sample only; and, species richness was significantly different in remnant revegetation compared to revegetation but with opposite trends at the two times of sampling. In 2002 species richness was higher in revegetation compared to remnant and in 2004 species richness in remnants were higher than revegetation (Time 1 and Time 2 PC3, Table 3.9).

60 60

50

40

2002 30 2004

20

Mean no. Mean native (1024m²) species quadrat per 10

0 Pasture Young reveg Old reveg Remnant Vegetation community

Figure 3.5 Mean native species richness by vegetation treatment and sampling time (planted individuals included)

Table 3.8 ANOVA of mean number of native species per quadrat (including planted) Source of variation SS df MS F P Veg 2580 3 860 17.6 0.002* Time 20 1 20 0.15 0.73 Site 1403 2 701 14.9 <0.001* Veg x time 1572 3 524 5.9 0.03* Veg x site 292 6 48.7 1.04 0.42 Time x site 258 2 129 2.7 0.08 VxTxS 527 6 87.8 1.8 0.12 Error 1124 24 Total 7776 47

Cochran C24,1=0.24, NS

61 Table 3.9 Planned Comparisons of numbers of native species between Vegetation within Time (planted individuals included) 2002 (Time 1) SS df MS F1,6 P 1. Pasture vs. pooled reveg 1482 1 1482 31.6 <0.001* 2. Young rev vs. old reveg 252 1 252 5.38 0.02* 3. Pooled reveg vs. remnant 420 1 420 8.9 0.006* Sum for Time 1 2154 3

2004 (Time 2) 1. pasture vs. pooled reveg 469 1 469 10 0.004* 2. Young rev vs. old reveg 2 1 2 0.04 0.83 3. Pooled reveg vs. remnant 1133 1 1133 24.19 <0.001* Sum for Time 2 1604 3 Total 3758

Species richness- proportion of exotic species There was a trend for a decrease in the proportion of exotic species from pasture through revegetation treatment to remnant vegetation (Figure 3.6). The proportion of exotics differed significantly between sites (Veg x Site interaction significant, Table 3.10). Hypotheses proposed were; that the proportion of exotic species in revegetation would be less than in pasture, old revegetation would be less than younger revegetation and revegetation would approximate remnants. Only two of these were confirmed by analyses. Comparison amongst treatment means within sites showed revegetation to have a lower proportion of exotics when compared to pasture at Plough and Harrow and WSRP but not at Hoxton Park (Table 3.11), and Old revegetation to have similar proportion of exotics when compared to Young revegetation at all sites. The proportion of exotics was greater in revegetation when compared to pasture at all sites (Table 3.11). Interestingly, neither the main effects, nor interactions for time were significant, implying that the differences in species richness between vegetation communities did not change over time. Despite this, the evaluation of ‘success’ of revegetation in reducing the proportion of exotics showed a generally decreasing trend after revegetation, whilst only two sites out of three achieved formal success as shown by the planned comparisons.

62

70

60

50

40 HP P&H 30 WSRP

20

10

0 Mean Mean (1024m²) proportion per quadrat exotics Pasture Young revegetation Old revegetation Remnant Vegetation community

Figure 3.6 Mean proportion of exotic species, by site

Table 3.10 ANOVA of the proportion of exotic species Source of variation SS df MS F P Veg 3444 3 1148 7.1 0.02* Time 66 1 66 1.4 0.34 Site 1656 2 828 14.4 <0.001* Veg x time 123 3 41 1.05 0.43 Veg x site 970 6 161 2.8 0.03* Time x site 88 2 44.4 0.77 0.47 VxTxS 232 6 38.8 0.67 0.67 error 1379 24 Total 7958 47

63

Table 3.11 Planned Comparisons of the proportion of exotic species between Vegetation within Site (interaction means) Hoxton Park SS df MS F1,6 P 1. Pasture vs. pooled reveg 60.62 1 60.62 1.56 0.1

Plough and Harrow 1. pasture vs. pooled reveg 1179.03 1 1179.03 30.38 <0.025* 2. Young rev vs. old reveg 109.27 1 109.27 2.81 0.1

WSRP 1. pasture vs. pooled reveg 252.10 1 252.10 6.49 <0.025* 2. Young rev vs. old reveg 0.95 1 0.95 0.02 0.1

Species richness- exotic species The numbers of exotic species differed significantly between treatments; time and site interactions were not significant, thereby allowing analysis of main effects. Exotic species richness was significantly higher in Pooled Revegetation groups when compared to both Pasture and Remnant vegetation (Planned Comparisons 1 and 3, Table 3.12, Figure 3.7). There was no significant difference between the different ages of revegetation (Planned Comparison 2, Table 3.12, Figure 3.7). Neither the main effects, nor interactions for time were significant, implying that the differences in exotic species richness between vegetation communities did not change over time.

64

Table 3.12 ANOVA of mean number of exotic species per quadrat Source of variation SS df MS F P Veg 389 3 129 8.4 0.014* PC1. Pasture vs. Pooled Reveg 159 1 159 10.7 0.003* PC2. Young Reveg vs Old Reveg 0.17 1 0.17 0.01 0.9 PC3. Pooled Reveg vs. Remnant 342 1 342 23.01 <0.001* Time 44 1 44 3.3 0.21 Site 38 2 19 1.3 0.29 Veg x time 81.5 3 27 3.2 0.1 Veg x site 91.9 6 15.3 1.03 0.42 Time x site 26.6 2 13.3 0.9 0.42 VxTxS 50.8 6 8.4 0.57 0.74 Error 355 24 Total 1577 47

Cochran C24,1=0.38*

20

18

16

14

12

10

8

6

4 Mean no. exotics per quadrat (1024m²) exotics no. quadrat per Mean 2

0 Pasture Young revegetation Old revegetation Remnant Vegetation community

Figure 3.7 Mean exotic species richness

65 Vegetation community composition

All species (excluding planted species) While there was an overall significant difference in species composition between vegetation treatments, this was not due to differences between pasture and restored vegetation, which were interchangeable (Figure 3.8, Table 3.13). The major differences found in species composition lay in the comparison of remnant vegetation with both ages of revegetation and pasture vegetation (Table 3.13).

Figure 3.8 Ordination analysis (nMDS): total species composition Ordination of species cover-abundance recorded per quadrat completed using non-metric multi- dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of total species composition. Straight line differentiates remnants.

Table 3.13 Comparisons of total species composition (species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM. R Values (significance level) Global R: 0.354; P=0.1%. Groups Pasture Young reveg Old reveg Remnant Pasture - 0.188 (0.001) 0.203 (0.001) 0.636 (0.001) Young reveg - - 0.012 (0.28) 0.512 (0.001) Old reveg - - - 0.47 (0.001) Remnant - - - -

66 All species (including planted species) While there was an overall significant difference in species composition between vegetation treatments this was not due to differences between pasture and restored vegetation, which were indistinguishable from each other (Figure 3.8, Table 3.14). The major differences found in species composition remained in the comparison of remnant vegetation with both ages of revegetation and pasture vegetation (Table 3.14). The differences between vegetation communities resulting from the inclusion of planted individuals, as measured by differences R values (between-group pairwise analysis), was minimal (Table 3.15).

Table 3.14 Comparisons of total species composition (species cover-abundance recorded per quadrat, planted individuals included) between vegetation treatments by ANOSIM. R Values (significance level) Global R: 0.401; P=0.1%. Groups Pasture Young reveg Old reveg Remnant Pasture - 0.295 (0.001) 0.242 (0.001) 0.625 (0.001) Young - - 0.063 (0.28) 0.606 (0.001) reveg Old reveg - - - 0.51 (0.001) Remnant - - - -

Table 3.15 Differences in between-group pairwise R Values between total species composition (of species cover-abundance recorded per quadrat , planted individuals included) between vegetation treatments by ANOSIM. Groups Pasture Young reveg Old reveg Remnant

Pasture - 0.107 0.039 -0.011 Young reveg - 0.051 0.094 0.094 Old reveg - - - 0.04 Remnant - - - -

67 Native species (excluding planted species) When native species were isolated for analysis, ordination results showed a small difference between restored vegetation and pasture vegetation (Figure 3.9, Table 3.16). The analysis distinguished the remnant vegetation community from all other vegetation communities.

Figure 3.9 Ordination analysis (nMDS): native species composition of species cover- abundance recorded per quadrat Ordination completed using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of native species composition. Straight line separates remnant group from others.

Table 3.16 Comparisons of native species composition (of species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM. R Values (significance level) Global R: 0.337; P=0.1%. Groups Pasture Young reveg Old reveg Remnant Pasture - 0.11 (0.005) 0.14 (0.001) 0.59 (0.001) Young reveg - - 0.02 (0.22) 0.48 (0.001) Old reveg - - - 0.49 (0.001) Remnant - - - -

68 Exotic species When exotic species were isolated for analysis, there were no discernable differences in species composition found between any of the vegetation groups (as indicated by the R-values). Importantly, restored vegetation was not different from pasture vegetation (Figure 3.10, Table 3.17).

Figure 3.10 Ordination analysis (nMDS): exotic species composition (species cover- abundance recorded per quadrat) Ordination completed using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of exotic species composition.

Table 3.17 Comparisons of exotic species composition (species cover-abundance recorded per quadrat) between vegetation treatments by ANOSIM. R Values (significance level) Global R: 0.235; P=0.1%; Groups Pasture Young reveg Old reveg Remnant Pasture - 0.224 (0.001) 0.222 (0.001) 0.357 (0.001) Young reveg - - 0.013 (0.29) 0.308 (0.001) Old reveg - - - 0.271 (0.001) Remnant - - - -

69

Native species returning after restoration From the results in the community structure analysis (Table 3.18a), a total of 37 native species were found to have returned to pasture after restoration. There were 24 species restored within the younger revegetation period since restoration and an additional 13 species after a longer period since restoration (including one, Hardenbergia violacea recorded as a returning plant both via suckering from a planted individual in young revegetation and also as a self-sown plant, not originating from a planted individual, in old revegetation). Importantly, there were 24 native species that returned to the revegetated areas unaided. Most species found to have returned were herbs and graminoids (61%). There were 16 shrub and tree species found to have self-recruited, 11 of which originating from planted individuals. There were 8 species observed to self-recruit in both the younger and the older revegetation group (Table 3.18b, Table 3.18c).

There were 36 native species recorded within remnant vegetation not found in either revegetated or pasture vegetation (Table 3.19). This group of species comprised all growth forms and species with a wide range of life history characteristics.

70 Table 3.18a Native species (planted and unaided) returning after restoration Native species (planted and unaided) returning after restoration Species returning within young Species returning within old revegetation revegetation Trees 1. Acacia falcata#* Trees 1. Allocasuarina littoralis#* 1. Acacia implexa#* 2. Angophora subvelutinass 1. Acacia parramattensis#* 1. Eucalyptus crebra#* 4. Angophora costata ss 2. Eucalyptus moluccanass 1. Eucalyptus crebra#* 2.Melaleuca nodosass Shrubs 1 Astroloma humifusum#* Shrubs 2.Dillwynia sieberiss 1. Dillwynia sieberi#* 4. Bossiaea prostrata 1. Indigofera australis#* 4.Bulbine bulbosa 1 Leucopogon juniperinus#* Grasses/herbs 4.Cheilanthes sieberi ssp. sieberi 1. Ozothamnus diosmifolium#* 4.Austrodanthonia racemosa 4.Eriostemon myoporoides subsp myoporoides 4.Chloris ventricosa Grasses /herbs 4. Centella asiatica 4.Dichondra repens 4.Cymbonatus lawsonianus 4.Fimbristylis dichotoma 4.Dichelachne micrantha 2. Hardenbergia violaceass 4.Dichelachne parviflora 4.Hypoxis hygrometrica 4.Entolasia marginata 4. Plantago debilis 4.Eragrostis brownii 4.Lagenifera stipitata 4.Eragrostis leptostachya 2. Hardenbergia violacea#ss 4. Hypoxis hygrometrica 4. Lomandra multiflora 4. Oplismenus aemulus 4. Pandorea pandorana 4. Schoenis brevifolius Total 24 17 (-4 occurring in Young) 13 Planted, 9 2 veg = 1 Planted, 1 5 seed = 2 Planted, 0 0 veg+ seed = 3 Unplanted, 14 10 seed = 4 Mode of recruitment: # planted species, * root suckering, ss self-sown seed

71 Table 3.18b Recruitment method breakdown of returned species. Species returning presumed by seed from elsewhere Species returning presumed by dispersal from elsewhere Trees Angophora costata

Shrubs Eriostemon myoporoides subsp myoporoides

Grasses /herbs Austrodanthonia racemosa Bossiaea prostrata Bulbine bulbosa Centella asiatica Cheilanthes sieberi ssp. sieberi Chloris ventricosa Cymbonatus lawsonianus Dichelachne micrantha Dichelachne parviflora Dichondra repens Entolasia marginata Eragrostis brownii Eragrostis leptostachya Fimbristylis dichotoma Hypoxis hygrometrica Lagenifera stipitata Lomandra multiflora Oplismenus aemulus Pandorea pandorana Plantago debilis Schoenis brevifolius Total no. 23

72 Table 3.18c Recruitment method breakdown of returned species. Species returning by self sewn seed presumed from planted parent

Species returning by self sewn seed presumed from planted parent Trees Angophora subvelutina Eucalyptus moluccana Melaleuca nodosa

Shrubs Dillwynia sieberi Hardenbergia violacea Total no. 5

Table 3.19 Native species from remnants missing from restored vegetation Species Grasses & herbs Trees Eucalyptus amplifolia ssp. amplifolia Laxmannia spp. Eucalyptus punctata Lepidosperma cocavuum Shrubs Dillwynia retorta Lomandra gracilis Dodonaea viscosa ssp. cuneata Lomandra micrantha Daviesia ulicifolia Medanya spp. Exocarpus cuppressiformis Oxylobium scandens Grasses & herbs Arthropodium minus Panicum simile Austrodanthonia fulva Patersonia sericea Calotis lappulacea Phyllanthes similis Capallidium parviflorum Pimelea spicata Carex longebrachiata Platylobium formosum ssp. formosum Clematis aristata Plectranthus parvifolia Clematis glycinoides Pomax umbellata Cyperus eragrostis Scaevola albida Echinopogon caespitosa Senecio hispidulus Eremophila debilis Solenogyne bellioides Hibbertia linearis Vittadinia pustulata Kennedia rubicunda Vittadinia cuneata var. cuneata

73 Plant groups

Of the 37 returning species, approximately 30% were perennial native C4 grasses and graminoids, perennial herbs and forbs comprised another 31%. Of tree canopy species recorded during sampling, 83% were found to have self-recruited; all except one of these was via root suckering. There was also one annual native herb (Senecio hispidulus) recorded as missing from pasture and restored vegetation (Table 3.20).

Table 3.20 Plant groups (returning species) Growth form Groups No. No. Total No. not % of total returning restored returning returning returning (Young) (Old) Tree Perennial Native 5 4 10 2 90 Shrub Perennial Native 5 0 6 3 67 Forb/Herb Annual Native 0 0 0 1 0 Forb/Herb Perennial Native 8 4 14 11 56 Grass/Graminoids Perennial Native 6 5 11 19 37 Total 24 13 37 36 97%

74 Temporal development of species composition Sampling species composition over the chronosequence provided three points (pasture, young and old revegetation pooled over times 1 and 2) from which to analyse a directional change. If revegetation is succeeding, the expectation is that revegetation is on a trajectory towards remnant. The data show however that the trajectory is tangential to, rather than directly towards remnant vegetation (Figure 3.11 ). The species composition of restored pasture vegetation does not resemble, nor is it increasing its resemblance, to that found in remnant vegetation.

Figure 3.11 Temporal development of species composition (species cover-abundance recorded per quadrat) Centroids of Pasture, Young revegetation and Old revegetation groups were calculated. Red circles with dark line show the restoration trajectory or direction of change of species composition over time since revegetation from Year 0 through to Year 11. The group of red triangles represent the remnant reference condition (restoration target).

75 Species contribution: Comparisons within vegetation communities

Pasture There were 8 species, 3 of which were native that contributed up to 50% of the average similarity (Bray-Curtis) within pasture. The species making the largest contributions were Pennisetum clandestinum, Paspalum dilatatum, and Sida rhombifolia; Verbena rigida was the other common exotic. Natives were restricted to Carex inversa, and Glycine tabacina (Table 3.21). Cynodon dactylon was found to be widespread in remnants, and has been identified as a naturalised native in these analyses.

Table 3.21 Pasture vegetation community descriptors (species cover-abundance recorded per quadrat) These species contributed up to 50% of the average similarity between sites within Pasture vegetation. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 35.82%. (Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Species Average abundance Cumulative % *Pennisetum clandestinum 3.50 10.42 *Paspalum dilatatum 4.05 20.29 *Sida rhombifolia 3.05 29.75 Carex inversa 3.00 36.78 Cynodon dactylon 3.05 43.42 Glycine tabacina 2.75 48.63 *Verbena rigida 2.48 49.72 *Setaria gracilis 2.55 53.71

76 Young revegetation There were 11 species, 4 of which were native that contributed up to 50% of the average similarity (Bray-Curtis) of the Young Revegetation community (Table 3.22). Paspalum dilatatum, Sida rhombifolia, and Setaria gracilis were still major contributors, but in addition to the natives seen in pasture (Carex inversa, Cynodon dactylon), Desmodium varians and Microlaena stipoides var. stipoides now made a reasonable contribution to similarity.

Table 3.22 Young Revegetation community descriptors (species cover-abundance recorded per quadrat) These species contributed up to 50% of the average similarity between sites within the Young Revegetation community. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 39.72%. (Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Species Average abundance Cumulative % Cynodon dactylon 4.08 6.67 *Paspalum dilatatum 3.82 12.91 Carex inversa 3.11 18.49 *Sida rhombifolia 3.37 24.03 *Setaria gracilis 3.34 29.14 Microlaena stipoides var. stipoides 3.63 33.83 *Cerisium vulgare 2.37 37.82 *Plantago lanceolata 2.63 45.27 *Verbena bonariensis 2.16 48.76 *Verbena rigida 2.45 49.56 Desmodium varians 2.11 51.95

77 Old Revegetation There were 12 species, 6 of which were native that contributed up to 50% of the average similarity (Bray-Curtis) of the Old Revegetation community (Table 3.23). The pasture exotics (Paspalum dilatatum, Sida rhombifolia, Setaria gracilis) still form a major part of the species composition, but the natives appearing in pasture and young revegetation pasture (Glycine tabacina, Carex inversa, Cynodon dactylon, Desmodium varians and Microlaena stipoides var. stipoides) are now added to by Aristida ramosa and Danthonia linkii var. linkii.

Table 3.23 Old Revegetation community descriptors (species cover-abundance recorded per quadrat) These species contributed up to 50% of the average similarity between sites within the Old Revegetation community. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 31.94%.(Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Species Average abundance Cumulative % Cynodon dactylon 3.98 8.8 Carex inversa 2.62 14.18 Microlaena stipoides var. stipoides 3.19 19.49 *Sida rhombifolia 2.86 24.47 *Paspalum dilatatum 2.62 28.59 *Setaria gracilis 2.67 32.64 Glycine tabacina 2.29 36.1 Aristida ramosa 2.24 39.22 *Senecio madagascariensis 1.95 42.06 Danthonia linkii var. linkii 1.67 44.8 *Cerisium vulgare 1.67 48.96 *Conyza bonariensis 1.81 50.08

78 Remnant vegetation Of the native species that contribute up to 50% of the average similarity (Bray-Curtis) of the pasture and revegetated vegetation communities, only Microlaena stipoides var. stipoides, Glycine tabacina and Aristida ramosa appear in Table 3.24, which describes species contributing to remnant vegetation. The remaining natives making a major contribution to the average similarity (Bray-Curtis) in remnant vegetation do not make a major contribution to those species contributing to similarity in revegetated communities.

Table 3.24 Remnant vegetation community descriptors (species cover-abundance recorded per quadrat) These species contributed up to 50% of the average similarity between sites within the Remnant vegetation community. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 37.43%.(Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Species Average abundance Cumulative % Brunoniella australis 3.64 6.63 Bursaria spinosa 3.73 13.03 Lomandra filiformis ssp. filiformis 3.95 19.06 Microlaena stipoides var. stipoides 3.66 25.07 Themeda australis 3.86 30.99 Aristida ramosa 3.39 36.31 Glycine tabacina 2.46 40.03 *Senecio madagascariensis 2.29 43.58 Cheilanthes sieberi ssp. sieberi 2.29 46.82 Opercularia diphylla 1.89 49.4 Eragrostis leptostachya 1.93 51.76

79 Table 3.25 Number of species contributing up to 50% average similarity (species cover- abundance recorded per quadrat)

Vegetation Native Exotic Total Within group community similarity (%) Pasture 3 5 8 35.82 Young Reveg 4 7 11 39.72 Old Reveg 6 6 12 31.94 Remnant 10 1 11 37.43

Two native grass species in particular, Microlaena and Aristida, and one herb (Glycine tabacina) were found to be abundant in the older revegetation and remnant vegetation groups.

In all vegetation communities except for the Remnant vegetation, groups were characterised by ground layer species. Unique to the Remnant vegetation group was the dominance of the common shrub species Bursaria spinosa.

Species contribution: Comparisons between vegetation communities The SIMPER analysis revealed what percentage each species contributed to the average dissimilarity between vegetation communities.

While the dissimilarity value between Pasture, Young and Old Revegetation groups were comparable (65-72%, Table 3.26), Young Revegetation and Old Revegetation had the lowest dissimilarity value. Dissimilarity values between revegetation and pasture increased by approximately 6% from young to old revegetation (Table 3.26). If the dissimilarity values between pasture and remnant (79.4, reveg vs. remnant comparison, Table 3.26) are taken as a goal dissimilarity value, then young revegetation is short of this goal by approximately 13% and old revegetation is short by approximately 7.5% (Table 3.26).

There was a very slight increase in the dissimilarity value between pasture and revegetation evident with time since restoration compared to the goal dissimilarity value observed between Remnant vegetation and pasture (Bray-Curtis) (Table 3.26).

80

Table 3.26 Average % dissimilarity between vegetation groups (species cover-abundance recorded per quadrat) Pasture Young Old Reveg Remnant Reveg Pasture - 66.2 71.7 79.4 Young - - 65.2 74.7 Reveg Old Reveg - - - 75.7 Remnant - - - -

Pasture and Young Revegetation had the lowest percentage dissimilarity values, determined by 31 species, 16 of which were native (Bray-Curtis) (Appendix 3.B). There were 14 native species that increased their abundance after restoration, including one (Viola hederacea) making a substantial increase. There were 11 exotic species that increased their abundance after restoration, including 5 species making substantial increases. There were 2 native and 4 exotic species that decreased their abundance after revegetation.

The dissimilarity values between Pasture and Old Revegetation was determined by 29 species, 16 of which were native (Bray-Curtis). There were 12 native species that increased their abundance after restoration, including one making a substantial increase. There were 6 exotic species that increased their abundance after restoration, including one species making a substantial increase. There were 7 exotics that decreased their abundance including one substantial decrease by Verbena rigida after restoration. Four natives also decreased their abundance after restoration.

The dissimilarity values between Young Revegetation and Old Revegetation was determined by 45 species, 26 of which were native (Bray-Curtis). There were 11 native species that increased their abundance with time after restoration and 4 exotic species that increased their abundance with time after restoration, including one species making a substantial increase. Fifty-Four exotic species decreased their abundance, including one (Verbena bonariensis) making a substantial decrease and 15 natives that decreased their abundance from Young revegetation to Old revegetation.

81 The dissimilarity values between Old Revegetation and Remnant vegetation was determined by 41 species, 27 of which were native (Bray-Curtis). Most importantly, the species with increased abundance include tree and shrub canopy species. These are the species not recorded in restored vegetation. There were 11 native species found to have reduced abundance in Remnant vegetation, most of these are grasses and herbs, however one shrub species (Acacia parramattensis) included in this group and used often in revegetation works. This species was found to respond to disturbance and senescence by re-sprouting from the roots.

The dissimilarity values between Young Revegetation and Remnant vegetation was determined by 42 species, 27 of which were native which contributed up to 50% of the average dissimilarity (Bray-Curtis). Most importantly, the species with increased abundance in Remnant vegetation included tree and shrub canopy species. These structural canopy species were not making comparable contributions to similarities as found in restored vegetation.

Species abundance changes after restoration

Native species There were 29 native species found to have increased their abundance from Pasture to Young Revegetation, whilst one was found to have decreased its abundance. Progression through time after Young to Old Revegetation resulted in 9 native species increasing and 21 species decreasing their abundance (Table 3.27).

Exotic species There were 17 exotic species found to have increased and 3 that decreased their abundance from Pasture to Young Revegetation. There were 3 exotic species found to have increased and 17 that decreased their abundance after progression from young revegetation to old revegetation (Table 3.27). Three exotic species (Paspalum dilatatum, Sida rhombifolia, and Pennisetum clandestinum) and four native species (Cynodon dactylon, Carex inversa, Microlaena stipoides var. stipoides, and Glycine tabacina) shared high abundance across pasture and both young and old restored vegetation communities.

82

Table 3.27 Average change (+,- compared to previous column) in species abundance after restoration (species cover-abundance recorded per quadrat, Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Species Average Average abundance Average abundance abundance (young) (Old) (Pasture) Native Microlaena stipoides var. stipoides 2.6 3.63 (+) 3.19 (-) Aristida ramosa 1.6 1.95(+) 2.24 (+) Cynodon dactylon 3.05 4.08 (+) 3.98 (-)

Cymbopogon refractus 0 0.76 (+) 1.62 (+)

Glycine tabacina 2.75 2.42(-) 2.29 (-)

Asperula conferta 0.93 1.53 (+) 1.81 (+)

Viola hederacea 1.4 2.26 (+) 1.71 (-) Desmodium varians 1.45 2.11 (+) 1.62 (-) Acacia parramattensis 0 0.89 (+) 1.52 (+) Danthonia linkii var. linkii 0 0.95 (+) 1.67 (+) Lomandra filiformis ssp. filiformis 0.85 1.68 (+) 0.52 (-)

Carex inversa 3 3.11 (+) 2.62 (-) Hypericum gramineum 1.05 1.42 (+) 1.19 (-) Poa labillardierii 0 1.00 (+) 1.05 (-) Lotus australis 0.95 1.05 (+) 0.81 (-) Oxalis exilis 0 1.47 (+) 0.19 (-) Phyllanthes virgatus 0.8 1.21 (+) 0.71 (-) Eragrostis leptostachya 0 1.16 (+) 1.19 (+) Dichelachne rara 0 0.84 (+) 1.00 (+) Dianella caerulea ssp. revoluta 0 0.16 (+) 1.19 (+) Geranium homaneum 0 1.00 (+) 0.90 (-) Bothriochloa decipiens 0 1.05 (+) 0.52 (-) Themeda australis 0 0.68 (+) 0.93 (-) Sporobolus creber 0 1.21 (+) 0.43 (-) Juncus usitatus 0 0.63 (+) 0.76 (+) Einadia hastata 0 0.89 (+) 0.67 (-) Geranium homaneum 1.45 1.00 (+) 0.00 (-) Oxalis exilis 0.7 1.47 (+) 0.00 (-) Poa labillardierii 0.8 1.00 (+) 0.00 (-)

83 Exotic *Anagallis arvensis 0.15 1.37 (+) 1.10 (-) *Sonchus oleraceus 0 1.05 (+) 0.81 (-) *Briza minor 0.3 2.00 (+) 0.00 (-) *Sida rhombifolia 3.05 3.37 (+) 2.86 (-) *Phalaris minor 1.28 1.45 (+) 1.43 (-) *Plantago lanceolata 1.65 2.63 (+) 1.52 (-) *Paspalum dilatatum 4.05 3.82(-) 2.62 (-) *Pennisetum clandestinum 3.5 2.13 (-) 1.48 (-) *Setaria gracilis 2.55 3.34(+) 2.67 (-)

*Verbena rigida 2.48 2.45(-) 1.38 (-) *Verbena bonariensis 2.05 2.16 (+) 1.19 (-) *Senecio madagascariensis 1.85 2.37 (+) 1.95 (-) *Briza minor 0.3 2.00 (+) 1.33 (-) *Conyza bonariensis 0 0.79 (+) 1.81 (+)

*Apium leptophyllum 0 1.68 (+) 0.95 (-) *Chloris gayana 0 1.13 (+) 1.14 (+)

*Cerisium vulgare 0.7 2.37 (+) 1.67 (-) *Hypochoeris radicata 0 1.42 (+) 0.95 (-)

*Olea europaea ssp. africana 0 0.53 (+) 1.38 (+) *Malva parviflora 1.5 1.26 (+) 0.90 (-)

84 Vegetation structure Several features of vegetation structure were measured and used as response variables. If revegetation is succeeding then the expectations were that:

• The structure of Revegetation will converge with that of Remnant;

• The structure of Revegetation will diverge from that of Pasture;

• Effects will be stronger in Old revegetation compared to Young revegetation;

• Trajectory of restoration will be from Pasture towards Remnant.

Higher order interactions amongst factors in the sampling design were generally significant in analyses, making statistical assessment of restoration success difficult, and so to simplify assessment of success, the upper and lower ranges of mean percentage cover cover and heights found in remnants were taken as the restoration goal.

Tree canopy cover Due to the absence of trees in pasture vegetation, those data were excluded from analysis. The difference in the percentage tree cover between vegetation treatments varied between sites and sampling times (Second order interaction significant, Table 3.28, Figure 3.12). If 28% cover found in remnants is taken as the goal, then of 12 restoration means in Figure 3.12, five (5) have reached or exceeded the target cover, 6 have failed. Therefore, tree cover at just under half the restored sites was within the range of cover values found at remnant sites.

85

Table 3.28 ANOVA of means of tree cover ANOVA Source of Variation SS df MS F P Veg 1073 2 536 1.2 0.36 Time 574 1 574 2.8 0.23 Site 61 2 30.8 0.2 0.81 Veg x Time 1404 2 702 0.48 0.64 Veg x Site 1659 4 414 2.8 0.056 Time x Site 398 2 199 1.3 0.28 Veg x Time x Site 5837 4 1459 9.8 0.0002* Error 2660 18 Total 13666 35

Cochran C11,1=0.6718, P=0.62, NS

90

80

70

60

50 2002 40 2004

30

20

10 % Tree cover per quadrat %(1024m²) cover quadrat Tree per 0 HP P&H WSRP HP P&H WSRP HP P&H WSRP Young reveg Old reveg Remnant Treatment / Site

Figure 3.12 Mean percentage tree cover per quadrat for each vegetation community at each time of sampling for each site (bars represent se, dashed line represents target range of tree cover, species cover-abundance recorded per quadrat)) Excluding pasture treatments and including planted trees (Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

86 Tree canopy height The differences in tree height found between vegetation treatments varied between sites (Veg x site interaction significant, Table 3.29, Figure 3.13). If a mean tree height range of 18-27 metres found in remnants is taken as the goal, then none of the 12 means has reached the target. The tallest mean tree height achieved in revegetation was approximately 7 metres. Tree heights in restored vegetation have a long way to go before they reflect tree height in remnants.

Table 3.29 ANOVA of means of tree height ANOVA Source of Variation SS df MS F P Veg 2971 2 1485 89 <0.0005* Site 0.26 2 0.13 0.031 0.97 Time 1.7 1 1.7 0.23 0.68 Veg x Time 17 2 8.6 1.1 0.4 Veg x Site 66 2 16.54 4 0.016* Time x Site 15 2 7.8 1.8 0.18 Veg x Time x Site 29 4 7.5 1.8 0.17 Error 74 18 Total 6145 35

Cochran C18,1=0.42, P=0.63, NS

Figure 3.13 Mean tree height per quadrat for each vegetation community at each time of sampling for each site. (bars represent se, area between dashed lines represents boundary of target of tree height target)

87 70

60

50

40 2002 30 2004

20

10

% Shrub cover per quadrat (1024m²) % cover quadrat Shrub per 0 HP P&H W HP P&H WSRP HP P&H WSRP HP P&H WSRP Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.14 Mean percentage shrub crown cover per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for percentage shrub cover). (species cover-abundance recorded per quadrat, Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Shrub crown cover and height The differences in the percentage cover of shrubs was found to be significant at different sites at different sampling times, with a generally higher percentage cover of shrubs found in Remnant compared to restored vegetation, however results were uneven and varied depending on site (Table 3.30, Figure 3.15). Variances remained heterogeneous after arcsine transformation. If a shrub percentage cover range of 8- 50% found in remnants is taken as the restoration goal then 8 out of 12 means have reached the goal however, all but three of these were in the lower half of this range.

If a shrub height range of 0.5-4.5 metres found in remnants is taken as the goal, then 11 of the 12 means have reached the target. The differences in the shrub height were found to be significant at different sites at different sampling times (Time x Site significant, Table 3.31, Figure 3.16). Both percentage shrub cover and shrub height were particularly variable in remnants, and this variability was reflected in the other vegetation treatments.

Thus, measures of shrub cover and height in restored sites showed greater convergence with the remnant target than for tree cover and height.

88 Table 3.30 ANOVA of shrub percentage crown cover (arcsine transformed, species cover- abundance recorded per quadrat)) ANOVA Source of Variation SS df MS F P Vegetation 0.12 3 0.063 1.9 0.25 Site 0.003 2 0.001 0.09 0.91 Time 0.02 1 0.02 0.23 0.67 Veg x Site 0.13 4 0.03 1.8 0.17 Veg x Time 0.09 2 0.04 1.00 0.44 Time x Site 0.18 2 0.09 5.11 0.017* Veg x Time x Site 0.18 4 0.04 2.5 0.07 Error 0.32 18 Total 1.2 35

Cochran C11,1=0.74, P=0.27 *

70

60

50

40 2002 30 2004

20

10

% Shrub cover per quadrat (1024m²) % cover quadrat Shrub per 0 HP P&H W HP P&H WSRP HP P&H WSRP HP P&H WSRP Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.15 Mean percentage shrub crown cover per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for percentage shrub cover). (species cover-abundance recorded per quadrat, Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

89 Table 3.31 ANOVA of shrub height ANOVA Source of Variation SS df MS F P Vegetation 11.2 3 5.6 4.9 0.08 Site 3.6 2 1.8 2.7 0.09 Time 10.4 1 10.4 4.3 0.17 Veg x Time 2.5 4 1.2 2.3 0.21 Veg x Site 4.5 2 1.1 1.7 0.19 Time x Site 408 2 2.4 3.6 0.04* Veg x Time x Site 2.1 4 0.51 0.78 0.55 Error 11.9 18 0.51 Total 454 35

Cochran C13,1=0.31, P=0.55, NS

5

4

3 2002 2004 2

1

0 Meanshrub height per (m) quadrat (1024m²) HP P&H W HP P&H WSRP HP P&H WSRP HP P&H WSRP Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.16 Mean shrub height per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for shrub height).

Ground layer percentage cover The general trend in the percentage cover of ground layer was decreasing from pasture to restored vegetation and then to remnant, although results are inconsistent across sites. Arcsine transformations were made due to heterogeneous variances.

The expected outcome for ground layer percentage cover after revegetation is the opposite of previous variables. That is, successful restoration would involve a decrease in ground layer percentage cover. If a ground layer percentage cover range

90 of 35-97% found in remnants is taken as the goal then 11 out of 12 means have reached the goal however, most of these were in the upper half of this range.

Differences in the percentage cover of the ground layer between vegetation treatments varied between sites, with a significantly higher percentage cover of ground layer species found in Pooled Revegetation groups compared to Remnant at Hoxton Park and Plough and Harrow, but not at Western Sydney Regional Park (VegxSite significant, Table 3.32, Figure 3.17).

Table 3.32 ANOVA Mean percentage cover ground layer (species cover-abundance recorded per quadrat) ANOVA Source of Variation SS df MS F P Vegetation 1.9 3 0.64 2.7 0.13 Site 0.04 2 0.02 0.36 0.69 Time 0.35 1 0.35 3.8 0.18 Veg x Time 0.26 3 0.08 0.74 0.56 Veg x Site 1.3 6 0.23 3.7 0.008* Time x Site 0.18 2 0.09 1.4 0.24 Veg x Time x Site 0.71 6 0.11 1.9 0.11 Error 1.5 24 Total 6.2 47

Cochran C16,1=0.22, P=0.99, NS

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100 90 80 70 60 2002 50 2004 40 30 20 10 0 %Ground layercover (1024m²) quadrat per HP P&H W HP P&H W HP P&H W HP P&H W

Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.17 Mean percentage cover of the ground layer per quadrat for each vegetation community at each time of sampling for each site (bars represent se, area between dashed lines represents upper and lower boundaries of target range for percentage ground layer cover, species cover-abundance recorded per quadrat, Braun-Blanquet scale data used, therefore comparisons are relative rather than absolute)

Percentage cover of rock The percentage cover of rock recorded in all vegetation groups was found to be less than 5%. Due to the low percentages of cover found, further analysis was not attempted.

Percentage cover of bare ground There were generally low values recorded of percentage cover of bare ground in all vegetation communities: Remnant, 2-7% with one outlying site with a mean of 20%; Revegetation, generally less than 5% with one outlying site at 10%; and, Pasture, 0- 6%. Differences in percentage bare ground cover varied between sites, vegetation treatments and sampling times (Table 3.33, Figure 3.18). Variances remained heterogeneous after arcsine transformations were made.

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Table 3.33 ANOVA of percentage cover of bare ground (Arcsine transformed, species cover-abundance recorded per quadrat)) ANOVA Source of Variation SS df MS F P Vegetation community 0.02 3 0.006 2.10 0.2 Site 0.008 2 0.004 8.50 0.001* Time 0.001 1 0.001 0.26 0.66 Veg x Time 0.009 3 0.003 1.00 0.45 Veg x Site 0.01 6 0.003 6.5 0.0003* Time x Site 0.008 2 0.004 8.3 0.001* Veg x Time x Site 0.018 6 0.003 6.15 0.0005* Error 0.011 24 Total 0.085 47

Cochran C9,1=0.38, P<0.001*

20

15

2002 10 2004

5 % Bare ground per quadrat (1024m²) quadrat per % ground Bare

0 HP P&H WSRP HP P&H WSRP HP P&H WSRP HP P&H WSRP Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.18 Mean percentage cover bare ground per quadrat for each vegetation community at each time of sampling for each site. (species cover-abundance recorded per quadrat, Braun- Blanquet scale data used, therefore comparisons are relative rather than absolute)

93 Percentage cover of lichen There was less than 2% cover of lichen recorded in any vegetation group. Due to the low percentages of cover found, further analysis was not attempted.

Percentage cover of litter The percentage cover of litter differed between sampling times, and differences between vegetation treatments varied between sites, with remnants having more litter than revegetated areas at some sites (Table 3.34, Figure 3.19). There was a high degree of variability found in the percentage cover of litter: Remnant, 5-15%; Young revegetation, 2-17%; Old revegetation, 2-10%; and pasture, 1-12%.

Table 3.34 ANOVA of percentage cover of litter (species cover-abundance recorded per quadrat) ANOVA Source of Variation SS df MS F P Vegetation community 227 3 75 0.92 0.48 PC2. Young Reveg & Old Reveg vs Remnant 160 1 160 8.1 0.009* PC3. Young Reveg vs Old Reveg 10 1 10 0.5 0.48 Site 6.7 2 3.3 0.17 0.84 Time 245 1 245 18.8 0.049* Veg comm x Time 16.2 3 5.4 0.15 0.92 Veg comm x Site 489 6 81 4.1 0.005* Time x Site 26 2 13 0.66 0.52 Veg comm x Time x Site 206 6 34 1.7 0.15 Error 473 24 Total 1858.9 47

Cochran C10,1=0.34, P<0.001

94 25

20

15 2002 2004 10

5 % (1024m²) Litter cover quadrat per 0 HP P&H W HP P&H W HP P&H W HP P&H W Pasture Young reveg Old reveg Remnant Treatment / Site

Figure 3.19 Mean percentage cover litter per quadrat for each vegetation community at each time of sampling for each site. (species cover-abundance recorded per quadrat, Braun- Blanquet scale data used, therefore comparisons are relative rather than absolute)

Principal components analysis (PCA) The test of alternate hypothesis that changes in species richness, composition and vegetation structure are mainly due to environmental factors was done using PCA.

Figure 3.20 is a PCA plot of environmental variables in relation to each other. This plot displays the first two axes (PC1 and PC2) of a PCA ordination on the transformed environmental data from the sampling. Two outliers on an initial plot were identified during analysis (both WSRP Remnants) and were removed to avoid undue influence on the analysis. The first component accounts for a low percentage (39%) of the variation in the full data matrix (Table 3.42).

The first two components account for over half of the variation (65.7%, Table 3.42). Given that 75% would be an acceptable proportion of variation explained (Clarke and Gorley 2001), the percentage of variation explained by environmental factors in this study, 65.7% reflects that the PCA of environmental variables does not provide an accurate summary of the relationships between vegetation groups indicated by the previous MDS plot of total species composition.

95 The was no trend found in the environmental attributes of the individual vegetation groups. There was no clear distinction between remnant vegetation, pasture and restored vegetation. This is an indication that the results in the differences between pasture, restored and remnant vegetation shown by the nMDS plots of species composition are largely attributable to the activities of revegetation and not attributable to environmental variation. There are other environmental variables not measured here which may ‘explain’ more variation.

Table 3.35 Principal components analysis of environmental variables and the % variation explained PC Eigenvalues %Variation Cum.%Variation explained 1 2.35 39.2 39.2 2 1.59 26.5 65.7 3 0.96 16.1 81.8 4 0.48 8.0 89.7 5 0.38 6.3 96.1

Figure 3.20 PCA Environmental variables Two-dimensional PCA ordination of the environmental variables transformed and normalised for the vegetation groups (percentage variation explained=65.7%). Variables recorded include Slope (%), Aspect, Runoff 1-3, Landform element 1-3, and landform morphology 1-3. Both WSRP Remnant plots ommitted as outliers.

96

Linking community analyses to environmental variables When up to five environmental variables were used to forecast species composition, only 7.3% of the variation would be predicted (Table 3.36). This was supported by a direct visual comparison of the PCA (Figure 3.20) with the MDS plot of total species composition (Figure 3.8). The PCA plot does not reflect the variation visually evident in this MDS plot of species composition to an acceptable extent (70- 75%).

Table 3.36 BIO-ENV: Environmental variables matched to species composition No. variables 1 % variation explained Landform element 1-3 6.7 No. variables 2 Slope % 7.2 Aspect No. variables 3 Slope % 7.3 Aspect Landform element 1-3 No. variables 4 Slope (%) Aspect 7.3 Runoff 1-3 Landform element 1-3 No. variables 5 Slope (%) Aspect 7.3 Runoff 1-3 Landform element 1-3 landform morphology 1-3

97

3.4 Discussion

The goal of the revegetation program completed at the study location was the re- establishment of the original grassy woodland to the ‘highest practicable extent’ (Perkins 1999). It was acknowledged by Greening Australia during the planning stages that changes to the physical (biological) environment resulting from revegetation by tree planting would be gradual and subtle and that they would require long-term commitment before results would become apparent (Davies and Christie 2001).

Questions critical to the assessment of restoration success being addressed by this study are whether species composition of restored vegetation is changing on a course (trajectory) to be more similar to remnants?; and whether the changes to restored vegetation have reached the reference condition?

The results of this study indicate that to date, there has been a partial success of the restoration program at the study sites with some response variables showing a trajectory towards remnants and others not.

Results for a range of compositional variables varied between the year of sampling (2002 and 2004). The degree of variation attributable to year of sampling in determining attributes, such as species composition, remains unknown. The year of sampling would incorporate both temporal and spatial variability as the samples were spatially independent at each time of sampling, but the contrribution of each are difficult to separate. Due to the time limitations of the project, these effects could not be estimated.

There were four possible trajectories of the selected response variable after restoration identified in Chapter 1 (Page 9). The first two options (1. restoration success, and 2. restoration partial success, on trajectory) represent the targets for restoration. There has been some restoration progress in terms of native species returning to restored vegetation. Other positive changes in species composition and vegetation structure

98 varied depending on site. The overall assessment of the restoration program is therefore partial success, not on trajectory towards remnants. These changes have been discussed below individually.

The most important variable in measuring restoration success at the study sites is considered to be species composition and its development over time as a result of revegetation. The observed trajectory in species composition from pasture through young revegetation to old revegetation was not in the direction of remnant vegetation. The species composition of revegetated pasture, whilst changing, does not resemble, nor is it increasing its resemblance, to that found in remnant vegetation. Referring to the four options of restoration evaluation, species composition, as a measured ecological attribute, rates as a 3, the variable has moved away from the degraded condition, part of the way towards the reference condition, but is on a trajectory that is not towards the reference condition eg parallel to the reference condition (restoration partial success, not on trajectory).

Results have shown some changes in the extant vegetation of the study location following revegetation activities. Native species recruitment in restored vegetation was inferred from increased abundance and dominance of non-planted native species. Many of the native species inferred to have returned to revegetation sites were identified as C4 grasses. This may be a result of slow and long term changes in soil chemistry caused by tree planting. However, there was no trend found in species composition from younger to older restored vegetation. The lack of trends towards reference goals could be a result of the relatively short time period within the chronosequence under analysis. After 11 years of revegetation large differences remained in native species composition between restored and remnant vegetation.

Referring to the four options of restoration evaluation, species richness rates as a 2. the variable has moved away from the degraded condition towards the remnant but has not attained a similar value; the trajectory is however towards the reference sites (restoration partial success, on trajectory).

Whilst the proportion of introduced species remained high overall, it was significantly reduced after restoration, however, the results were uneven and this positive response

99 occurred at some sites only. Assigning a restoration outcome to this variable has not been done due to the inconsistent results obtained for this response variable. The inconsistent response of this attribute to the revegetation treatment may be a result of the degree of disturbance and the long term nature of the infestation of exotics at any parttyicular site.

The numbers of exotic species was significantly higher after revegetation when compared to both Pasture and Remnant vegetation. Time since revegetation made little difference to numbers of exotic species. Assigning a restoration outcome to the variables proportion of introduced species and exotic species richness has not been done due to the inconsistent results obtained for these response variables.

Analysis of the species composition results revealed that the native species returning after revegetation comprised a different set of species than those found in remnants. These differences contributed to the enduring distinction in species composition between remnants and restored vegetation and the apparently tangential direction of restoration trajectory. In particular, revegetation did not make any difference to the composition of exotic species.

The positive results include a total of 37 native species inferred to have returned after revegetation, 24 of these appearing unaided (not planted, seeded or arising from vegetative growth). The presence of 24 ‘returned’ native species in young revegetation chronosequence, 13 ‘returned’ species in old revegetation, and 4 species common to both young and old revegetation, suggests that some of these apparent ‘returns’ may be attributable to spatial variation. This is a limitation of chronosequence sampling method. Native species found in revegetation and not found in pasture may represent returning species or spatial variation. These species probably represent a mix of both returning species and those sampled because of spatial variation but have tentatively been identified as returning. It also points to the majority of returns occurring at the start of the restoration process, soon after revegetation.

Almost 50% of returning species being identified as herbs and graminoids, there were 13 shrub and tree species found to have self-recruited, mostly by way of vegetative

100 growth (resprouting of roots). With these canopy species becoming more dominant over time, this may mark the beginning of a transitional phase of the restored vegetation, from pasture to re-created woodland. There were 23 species (1 tree, 1 shrub, 21 grasses and herbs) returning unaided to revegetated areas. Using the return of native species as the criteria for measurement of revegetation success alone, it could be said the overall assessment of revegetation program rates as having moved away from the degraded condition towards the remnant but has not attained a similar value; the trajectory is however towards the reference sites (restoration partial success, on trajectory).

With approximately 30% of species planted as a part of the restoration process having self-recruited from suckering from the roots after disturbance, these species exhibited one of the life history characteristics required to succeed in the Greening Australia objective of modifying the species composition of the revegetated community, mainly by vegetative propagation.

Most of the species recruited after revegetation have been in addition to the planted species; they have not been physically implanted via the revegetation process, rather they have returned to restored vegetation via some other means. These species appear to be early evidence of the success of the revegetation program in allowing the return of native species, however only three species achieved abundances similar to that found in remnants.

The changes in species composition revealed in this study were expected as a result of an increase in shade created by the growth of planted trees, suppressing exotic C3 grasses found in abundance in abandoned pasture and reducing competition experienced by native species. If this holds, a ‘halo’ effect would be expected around the canopy of a planted tree. This hypothesis will be tested in Chapter 4.

Despite the recruitment of some native species, many found in remnant vegetation did not recruit after revegetation. This latter group of species comprised all growth forms and species with a wide range of life history characteristics. If restoration is completely successful, the full complement of floristic diversity should re-established. To date, this has not occurred at the study location.

101

A large proportion of native species found in remnant vegetation were not recorded in revegetated areas and require additional assistance over and above the restoration techniques applied in this study. This point is further discussed in Chapter 6.

Increased similarity was evident in several structural attributes of the restored vegetation at the study sites compared to those found in remnants. This is different from other studies including (Buckney and Morrison 1992) that revealed little evidence of change in the habitat attributes of restored compared to remnant vegetation communities.

Although more variable, tree cover found in restored vegetation sometimes achieved higher cover percentages than those found in remnants. Tree heights however, were currently well below those found in remnants; this will change as plants grow. Percentage cover of shrubs and shrub height were variable in remnants and almost all restoration targets for these variables were achieved, however restored vegetation contained low shrub heights and percentage cover when compared to remnants. The expected trends in percentage cover of ground layer after revegetation revealed some positive results and exhibited a general downwards trend in cover of ground layer compared to remnant.

Shrub percentage cover and height were variable in remnants. Almost all restoration targets for cover of shrubs and height were reached, and again, assuming continued shrub growth they appear to be on a trajectory to remnants (restoration partial success; on trajectory).

The reverse expected trends in percentage cover of ground layer after revegetation also revealed positive results and although uneven across sites, the general trend in the percentage cover of ground layer was decreasing after revegetation then to remnant, which may also be considered as restoration partial success; on trajectory.

Overall, although exhibiting some positive signs of the recovery, through the increased abundance of some native species, major deficiencies in species composition and structure remain. The number and abundance of native species have

102 increased with time since restoration and two returing native grass species and one herb were found to be abundant in both older revegetation and remnant vegetation. However, all vegetation communities except for the Remnant vegetation, groups were characterised by ground layer species. Importantly, Remnant vegetation was the only group to be dominated by the common shrub species Bursaria spinosa, which were absent from revegetation.

The overall assessments of restoration between ‘success’, ‘partial success (on trajectory and not on trajectory)’ and ‘failure’ are determined by the relative importance assigned to the different response variables chosen during project evaluation. Within this Thesis species composition has been ranked as most important because of the diverse understorey of the CPW community. Structural response variables (e.g. tree and shrub height) have been given a lower importance, as they could be achieved with exotics.

The overall conclusion then, is ‘partial success not on trajectory’ because although some response variables have responded positively to restoration and assessed as on trajectory, many of these variables were structural. The critical assessment of the development of species composition of restored vegetation at a tangent to remnants establishes the overall evaluation outcome as restoration success, not on trajectory.

The results of this study contrast with studies of restoration of other terrestrial plant communities which have measured change in species composition. In their study of sand dunes restored after mining, Buckney and Morrison (1992) found the dominant trend of temporal development of species composition to be a reduction in similarity to that of the sand dune prior to mining. McDougall and Morgan (2005) also found no changes to native species richness over 15 years of restoration of a grassland. My study showed an increase in native species richness after revegetation at one sampling time only, and an insignificant increase (or no change) in similarity between remnant and restored vegetation.

Although finding some changes in tree species composition, Reay and Norton (1999) in their study of rainforest in New Zealand also found no trend in plant composition over time since restoration. Similar to these results, my study found tangential

103 development in the trajectory of species composition from restored vegetation to remnant. Also comparable to this study Reay and Norton found that similarities between restored and remnant vegetation remained unchanged with time since restoration.

A lack of convergence of floristic composition from restored to remnant vegetation is a common feature of studies of restored vegetation. The results of my study were also similar to those found in a study measuring the success of urban riparian revegetation projects by Hynes et al (2004) who found that vegetation communities at revegetation and reference sites were different. Hynes et al (2004) using structure as one of the key attributes, found the structure of the vegetation community remained distinct, in that case because the pattern of tree planting used during restoration did not reflect patterns found in remnants. Trees and shrubs were planted close to the creek bank in the restoration areas, where in the natural reference system they were absent.

An assessment was made of the restoration of three sand dunes in France by Rozé and Lemauviel (2004) who found satisfactory stabilisation of the dunes had taken place after ten years of restoration. Like others, their study found no convergence of species composition or species richness in restored vegetation compared with remnants over the ten-year restoration period. Similarly, studies of wetland restoration, including Campbell et al (2002) and Zedler and Callaway (1999), concluded that restored vegetation communities differ significantly from remnant vegetation.

The changes in the abundance of native species in restored vegetation found in this study correspond with an analogous study completed by Wilkins et al (2004) which assessed the success of restoration at the same location. They found the floristic analyses supported a ‘steady-state model of vegetation dynamics rather than direct successional’. One point of difference was that they found no change in native species richness after restoration, whereas I found significant increases in native species richness for one time of sampling in conjunction with several key canopy species having been recruited.

Although the results have been different, this study leads to the same conclusion made by Wilkins et al (2004) and McDougall and Morgan (2005) that the lack of

104 convergence of floristic composition may be attributed to either ecosystem resources having been maintained at below (or above) threshold levels for changes or the short time since restoration. One acknowledged constraint to the establishment of natives is the lack of seed in restored vegetation i.e. propagule limitation (Tillman 1993, 1997). In addition, due to the infrequent nature of successful recruitment exhibited by many native species, recruitment blockages may be common in restored vegetation communities i.e. recruitment limitation (McDougall and Morgan 2005). Further studies within this Thesis have focused on native species germination and establishment to advance understanding of the processes necessary for more successful restoration.

Recent studies by (Prober 2005, McDonald 2000) have identified that the re- establishment of a thick sward of native perennial grasses is important for restoring the natural functioning of a grassy woodland. Prober (2005) suggests that a thick sward of natives out-compete exotics, and maintains low levels of available nitrogen and phosphorus in the soil, which retards the growth of exotics and allows natives to dominate.

Relying on the competitive exclusion of exotics, the revegetation program aimed to reinvigorate the lost tree canopy and re-establish a grassy woodland. Results from this study have shown that several tree and shrub canopy species have been self-recruited after revegetation, however many of the ground layer species remain missing from restored vegetation. In fact, the natives found to be returning to restored vegetation are a different suite of species than found in remnants.

The dominance of the tree canopy is one of the main characteristics of CPW, especially Shale Hills and Shale Plains Woodland and should be recorded in 100% of samples (Tozer, 2003). Without including planted tree species, this high abundance of tree species was not achieved in revegetated areas. The lack of dominance of self- recruited trees in this study is critical in appreciating how, after eleven years, restored pasture remains different from remnant vegetation.

105 Implications for restoration programs It is becoming apparent from recent restoration evaluations that if significant changes in species composition in restored communities are possible due to restoration works, then these changes have either been too slow to measure or they have not yet occurred. It should be acknowledged that restoration of grassy woodland systems might take several decades or longer to succeed in terms of a re-establishment of species composition to pre-disturbance levels. Where approvals for development or destruction of native vegetation are provided on the condition that restorative plantings are undertaken based on the disingenuous understanding that this will compensate for loss of habitat for native flora, acknowledgement of the long period for restoration success should be made. The protection of the existing remnant vegetation may be a more cost effective method of off-setting the negative impacts of development.

This study was based on one of the largest restoration programs in NSW. This program was, and still is, one of the best funded and well resourced program implemented by a comparatively large, mainly volunteer, workforce. Lesser resourced programs are likely to be less effective in terms of achieving their stated goals.

While initially, much revegetation work has been carried out only in a local context, there has been an increasing emphasis on regional planning through Catchment Management Committees and Regional Vegetation Plans. In NSW, for example, the Native Vegetation Management Act (1997) aims to regulate clearing and plan revegetation in a manner mindful of regional goals for conservation and sustainable production. These plans identify areas where the condition of native vegetation should be improved and recommend areas that should be revegetated. This Act has now been superseded by the Native Vegetation Act (2003) which has as one of its main objects to encourage the revegetation of land, and the rehabilitation of land, with appropriate native vegetation.

Similar policies have been adopted by the Victorian and Queensland state governments on the premise that any continuing losses of native vegetation can and must be balanced by gains through revegetation (Department of Natural Resources

106 and Environment, 2004). Plans for clearing in Queensland must include information on, among other things, proposed vegetation rehabilitation or restoration (Department of Natural Resources and Mines, 2003).

Despite the apparently slow rates of success shown by this study, the restoration of ecosystems has been made compulsory by regulation. The results of this study support previous suggestions by others including Zedler and Callaway (1999) and (Prober, 2005) regarding regulations governing the removal or destruction of native vegetation. Prevention of the impact on native vegetation should be the focus, rather than a reliance on restoration.

Regulations needs to recognise that long term ecological monitoring is required for all large scale restoration projects and that due to the difficult nature of restoration, a high value needs to be paced on the retention of existing native vegetation prior to approvals being issued for clearing.

Effectiveness and potential use of the evaluation methodology The approach of this study in evaluating the success of a large restoration program has been to identify measurable ecological response variables and set criteria for the evaluation of a large scale restoration program. It involved sampling a starting point, intermediate points and end points, then using a range of analyses to determine; whether natives are returning to restored vegetation, restoration trajectories, and overall restoration success. This method was based on the theory and models of Westman (1986), Chapman and Underwood (2000) and Wilkins et al (2004).

An innovation adopted in my study was to make a series of predictions of ecosystem variable response (eg species richness) assuming that revegetation was succeeding and testing these with explicit planned comparisons.

This evaluation technique addresses the critical lack of adequate ecological audit methodologies available for the evaluation of restoration projects. This method could be made available to restoration practitioners and funding bodies alike and used by both as a tool for advanced restoration planning and improve the long-term ecological

107 outcomes of projects. Without effective ecological audits, it is not possible to determine whether best value is derived from the monetary and human contributions made.

One of the outcomes of this study has been the development of an evaluation methodology to detect small changes in the environment that have occurred in response to restoration activities. This methodology involves using SFT substitution to obtain ‘before impact’ data, and compares data over a chronosequence to allow evaluation of trends over time.

Currently administrative audits of kilometres fenced, volunteer hours spent, and tubestock planted are measurements undertaken by funding bodies and restorationists to determine restoration success and provision of financial assistance. As opposed to these ecologically meaningless measures, this evaluation methodology represents a unique opportunity to measure ecological changes in the environment that have occurred because of restoration. Such measures are more authentic in evaluating the true environmental impacts of restoration activities.

108

Chapter 4

The effect of a planted tree canopy on species composition

4.1 Introduction

The ecosystem degradation observed at the study location is being addressed in part by Greening Australia utilising Perkins’ (1992) theory that revegetation of abandoned pasture with canopy trees assists natural succession and restoration of an ecosystem to a state which existed prior to disturbance. The planting of canopy trees was instituted as the main method of returning highly degraded abandoned pasture to native grassy woodland to the ‘maximum practicable extent’ (Perkins 1999). Whether the model postulated by Perkins is working or not has never been tested, this Chapter reports such a test.

Under Perkins’ (1992) model, interspecific competition is one of the principles upon which the success of revegetation relies. That is, individuals of one species suffer reduced abundance as a result of resource exploitation or interference by individuals from another species (Begon et al 1986). In the case of the planted tree affecting species composition in the surrounding environment, it is proposed that the growth of the tree will dominate the resources (water, nutrients, light) in the local vicinity and starve the competing exotic species of resources. The planting of trees at the study location was therefore expected to facilitate local-scale changes to species composition by favouring natives and reducing exotics. These small-scale changes were the focus of this study.

The majority of species planted at the study location as a part of the revegetation program were trees from the Myrtaceae and Fabaceae families. The range of species planted included pioneer species but mainly canopy dominants. Planted trees with attributes such as wide seed dispersal, the ability to germinate and become established in unoccupied places, and rapid maturation were expected to successfully modify the small-scale environment to one that was more favourable to the recruitment of ground layer native species. The study detailed in Chapter 3 revealed significant increases in

109 native species richness in restored vegetation compared to untreated pasture at one time of sampling.

Revegetation works at the study location began in 1992 with the goal to re-establish the native grassy woodland (Perkins 1992). The methods of revegetation used at the site since 1992 have been given in Chapter 3 of this Thesis. The location, existing vegetation types and previous land use have been described in Chapter 2.

This study aims to evaluate the small-scale effects of planted tree canopies on species composition underneath those canopies compared to non-canopy areas of the immediately surrounding abandoned agricultural pastures.

Aims:

1. To determine whether planted trees in restored vegetation affect the species richness and composition beneath their canopies; and

2. To identify trends in the development of species composition beneath tree canopies from younger aged (3-5 years) revegetation through time to older aged (8-10 years) revegetation.

Hypotheses: That: 1. Native species richness under planted tree canopies will be greater than that found away from canopies;

2. There will be an increasing trend with time since revegetation in the species richness and cover of native species present underneath compared to outside the canopy of planted trees in restored vegetation;

3. That exotic species richness under planted tree canopies will be less than that found away from canopies;

110 4. There will be a decreasing trend with time since revegetation in the exotic species richness and cover present underneath compared to outside the canopy of planted trees in restored vegetation;

4.2 Methods

Site selection Three sites were selecetd to sample simliar underlying parent material, topography and vegetation type. The sites (Hoxton Park-HP , Plough and Harrow-P&H, and Western Sydney Regional Park- WSRP) were distributed throughout the study area to provide representation of spatial variability in the vegetation throughout the area. There were two canopy types sampled (canopy present or absent); Three site levels sampled (HP, P&H, WSRP), Two revegetation age levels (3-5 years old, 8-10 years old); Two levels of Plot (2 per site of both revegetation age combinations); Four levels of Transect (4 per plot, 2 to select +canopy samples and 2 to select –canopy samples in order to ensure independence of canopy treatments); and, 4 Quadrats per transect (+canopy, -canopy).

The details of the sampling design are shown in Table 4.1 and a sampling design schematic in Figure 4.2.

Table 4.1 Location of replicate quadrats sampled Restoration 3-5 3-5 5 Age Site HP P&H WSRP Plot P1 P2 P1 P2 P1 P2 Canopy + - + - + - + - + - + - Transect 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 n= 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

Restoration 8-10 8-10 10 Age (yrs) Site HP P&H WSRP Plot P1 P2 P1 P2 P1 P2 Canopy + - + - + - + - + - + - Transect 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 n= 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

111

Figure 4.1 Sampling design schematic

In order to control for environmental variation, the following factors have been either kept within a small range of variation, as far as possible, or randomly selected from topographic maps using grid overlays and random numbers tables at plot level: slope (0-360 degrees); aspect (0-360 degrees); soil type (clay loams derived from Wianamatta shales); previous agricultural practices (pasture improvement with cattle grazing), and; revegetation technique (mechanical planting).

Each vegetation type (3-5 year old restored pasture, and 8-10 year old restored pasture vegetation) was mapped on 1:25000 topographic maps. Vegetation types were verified by site inspection. Due to the disturbed matrix of extant vegetation, the restored vegetation was in patches of variable sizes and shapes. Sampling was confined to vegetation patches of a minimum size of one hectare and a minimum width of 100 metres. All quadrats surveyed were located underneath the canopy or outside the canopy of planted Grey Box (Eucalyptus moluccana) trees because this was by far the most commonly planted species.

112 To facilitate a balanced sampling design, it was necessary to pool samples of restored vegetation by age groups (3-5 years and 8-10 years). Patches of vegetation for each treatment were overlain by a grid of 500 metres x 500 metres. These grids were then numbered and random numbers used to select the locations of transects and quadrats (Figure 4.2).

113

Figure 4.2 Location of revegetation works by Greening Australia and quadrats sampled

114 Data collection Three sites were surveyed from December 2003 through to June 2004. Sites were stratified by underlying parent material, topography and assumed pre-disturbance vegetation type. Sites were also randomly distributed to provide an adequate representation of the variability of species composition and vegetation structure throughout the area.

The sampling method involved a quadrat of slightly over one square metre in area with primary axes following N-S and E-W directions with tape measures. The quadrat was circular to encompass the average size of a tree canopy being sampled and purpose-built of flexible polypipe with a central portion excluded for the tree trunk (Figure 4.3).

Figure 4.3 Sampling quadrat

Vascular plant species composition (presence – absence) and vegetation structure was sampled within each quadrat. Habitat structure was assessed by estimating percentage cover of rock, litter and bare ground. Additional information was collected at each sampling event including: slope, aspect, position via GPS, and soil type. A cover abundance measure was also assigned to each species according to the Braun- Blanquet scale in Poore (1955). Species were either identified on site using Harden (1990-1993) as the reference, or at the National Herbarium of NSW, Sydney. Examples of each species are held in the herbarium at the Ecology Research Group, University of Western Sydney. Nomenclature is according to Harden (1990-1993).

115 Data analysis

Species richness The number of species (native and exotic) per quadrat were compared using a mixed model ANOVA with the following terms: canopy treatment (fixed), site (random), restoration age (fixed), plot nested within site x age (random) and transect nested within plot (random). Four replicate quadrats per transect were sampled. These analyses excluded planted individuals.

The homogeneity of variances was tested using Cochrane’s test and transformations were not required.

Native species returning to underneath the planted tree canopy Data from Chapter 3 regarding the absence of species from pasture were used in conjunction with results from this study. Native species recorded under tree canopies and not recorded outside tree canopies or in pasture were inferred to be present as a consequence of the tree canopy. These were compared between plantings of different ages.

Multivariate analysis Species Composition Multivariate analyses were used to identify floristic patterns for total, native and exotic species using the PRIMER software package (Clarke and Gorley 2001). Similarity matrices were calculated using the Bray-Curtis index and clustered using group averages with non-transformed data. This analysis was completed at the quadrat level.

An ordination analysis was then performed using non-metric multi-dimensional scaling (nMDS). This analysis provided a two or three-dimensional graphical representation of the groupings. Differences in the floristic composition between the treatments (underneath and outside planted tree canopies), if any, were inferred from these two ordinations.

116 For the nMDS ordinations, Bray-Curtis dissimilarity matrices have been computed from the cover-abundance scores. ANOSIM has been used to test for significant differences in species composition between treatments. Two-way crossed ANOSIM has been used to compare all orthogonal data to test simultaneously for differences between treatments and sites. Analyses of the pairwise comparisons show where the differences occurred between treatments.

Species composition has been analysed using Bray-Curtis dissimilarity matrices from cover-abundance score data for all naturally occurring vascular plants (planted individuals excluded).

Percentage similarity SIMPER analysis was used to determine the contribution of each species to the average dissimilarity between different treatments. No standardisation and no transformation were applied to the data, and species were listed if they contributed to more than 50% of the dissimilarity between underneath planted tree canopies and outside planted tree canopies. The analysis was repeated to determine the contribution of each species to the average dissimilarity between treatments of different restoration age (3-5 years cf. 8-10 years).

The most abundant species recorded underneath and outside planted tree canopies were identified by manipulation of cover-abundance scores of species within the PRIMER software package SIMPER function (Clarke and Gorley 2001).

Linking community analyses to environmental variables

Environmental variation The testing of the alternate hypothesis: that all changes in species richness and composition were due to environmental factors and not the planted tree canopy treatment was made by using Principal Components Analysis (PCA) and the BIO- ENV procedures from PRIMER (Clarke and Gorley 2001).

117 PCA was plotted to describe the relationships between environmental variables including slope, aspect, runoff and landform element. The PCA plot obtained was then visually compared with MDS plots of species composition to understand the degree to which species composition varies with environment.

The effects of environmental variables on species composition were further analysed using the BIO-ENV procedure in PRIMER (Clarke and Gorley 2001) to effectively match environmental attributes relationships with each other shown by slope (degrees), aspect (degree), runoff (1-3), and landform element (1-3) to any variations evident in the species composition in the different canopy treatments.

The extent to which the variation is captured by each combination of species is assessed in the degree to which the two similarity matrices match: it is the Spearman rank correlation () applied to the elements of the rank similarities.

118 4.3 Results

Species number- total species There were 93 plant species recorded throughout the sampling (57 native and 36 exotic) (Appendix 4.C). On average, over both revegetation ages there were 5.17 (±se 0.03) native and 4.3 (±se 0.02) exotic species m-2 found underneath planted tree canopies; and, 4.8 (±se 0.03) native and 3.6 (±se 0.02) exotic species m-2 recorded outside planted tree canopies.

Species richness- native species The numbers of native species beneath canopies compared to outside canopies varied between sites (Table 4.2, canopy x site interaction significant; Figure 4.4), with significantly higher native species richness under tree canopies at Hoxton Park only. Both Plough and Harrow and WSRP showed slight reductions in numbers under canopies compared to outside canopies. Plot (nested within site x reveg age) and Transect (nested within can x site x reveg x plot) were also significantly different, reflecting spatial variation at these scales. (Table 4.2).

Table 4.2 ANOVA of mean number of native species per quadrat ANOVA Source of Variation SS df MS F P F-versus Canopy 8.33 1 8.33 0.63 0.51 can x site Site 28.82 2 14.41 0.59 0.58 plot Reveg age 1.02 1 1.02 0.29 0.64 pooled error Plot(site x reveg) 144.31 6 24.05 3.33 0.016* transect Transect(can x site x reveg x plot) 173.25 24 7.21 2.06 <0.01* pooled error can x site 26.32 2 13.16 3.76 <0.025* pooled error pooled error 541.60 155 3.49 1.83 0.16 Total 923.66 191

Cochran’s C(11, 1)=0.085, P=0.47, NS

Table 4.3 Planned Comparisons of numbers of native species between + and - canopy at different sites SS df MS F1,6 P 1. HP +- canopy 31.64 1 31.64 9.44 0.002* 2. P&H +- canopy 2.25 1 2.25 0.67 0.41 3. WSRP +- canopy 0.76 1 0.76 0.23 0.63 Total 34.65 3

119

) 7 -2

6

5

4 Native 3 Exotic 2

1

Meanno.species perquadrat (m 0 + canopy - canopy + canopy - canopy + canopy - canopy

HP P&H WSRP Site / Canopy

Figure 4.4 Mean species richness per quadrat by canopy treatment across sites (m-2)

Species richness- exotic species The exotic species richness beneath tree canopies was higher underneath tree canopies (+canopy) compared to outside canopies (-canopy) (Figure 4.4, Canopy main effect significant, Table 4.4). Exotic species richness also varied between transects (Figure 4.4, Transect significant, Table 4.4).

Table 4.4 ANOVA of mean number of exotic species per quadrat ANOVA Source of Variation SS df MS F P Canopy 18.75 1 18.75 6.13 <0.005* Site 10.53 2 5.27 0.63 0.56 Reveg age 1.02 1 1.02 0.33 >0.50 Plot(site x reveg) 49.81 6 8.30 1.22 0.32 Transect (can x site x reveg age x plot) 162.75 24 6.78 2.20 <0.001* can x site x rev age 16.95 2 8.47 2.77 0.05< P <0.10 Error 474.00 155 3.06 Total 733.81 191

Cochran’s C(11, 1)=0.07, P=0.67, NS

120

Total species composition The ordination results showed floristic composition underneath planted tree canopies to be similar to that outside planted tree canopies (Figure 4.5, Table 3.13).

Figure 4.5 Ordination analysis: total species composition Ordination completed using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of total species composition. Global R: 0.025; P=0.1%. (species cover-abundance recorded per quadrat)

Table 4.5 Global R comparisons of total species composition averaged across groups (significance level), (species cover- abundance recorded per quadrat) Groups Avg Age Avg Canopy Age - 0.098 (0.001) Canopy 0.036 (0.001) -

121 Native species composition There was no difference found between native species composition under planted tree canopies compared to outside planted tree canopies (Figure 4.6).

Figure 4.6 Ordination analysis: native species composition Ordination completed using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of native species composition. Global R: 0.007; P=3.5%. Three quadrats (WSRP 10 year old revegetation 2 quadrats under canopy and 1 quadrat outside canopy) were excluded from analysis to avoid skewing of results (species cover-abundance recorded per quadrat)

122 Exotic species composition Exotic species composition underneath planted tree canopies did not differ from that outside planted tree canopies (Figure 4.7).

Figure 4.7 Ordination analysis: exotic species composition Ordination completed using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of exotic species composition. Global R: 0.044; P=0.1%. Four quadrats (WSRP 10 year old revegetation outside canopy, 2 WSRP 5 year old revegetation quadrats under canopy, and 1 quadrat in HP 10 year old revegetation under canopy) were excluded from analysis to avoid skewing of results (species cover-abundance recorded per quadrat)

123 Species composition: Comparisons within vegetation communities

Average similarity within the respective groups (among sites) was relatively low and was characterised by relatively few ground layer species (Table 4.6).

Table 4.6 Number of species contributing up to 50% average similarity (species cover-abundance recorded per quadrat)

Treatment Native Exotic Total Within group similarity (%) Underneath canopy 2 3 5 19.41 Outside canopy 3 1 4 21.22

Five species, two of which were native, contributed up to 50% of the average similarity between sites within underneath planted tree canopies (Table 6).

Table 4.7 Underneath planted tree canopy vegetation community descriptors These species contributed up to 50% of the average similarity between sites within the Underneath planted tree canopy vegetation community. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 19.41%. (species cover- abundance recorded per quadrat)

Species Average abundance Cumulative % Cyperus gracilis 1.68 14.49 Paspalidium distans 1.48 26.89 *Myrsiphyllum asparagoides 1.48 38.87 *Sida rhombifolia 1.26 47.60 *Rubus fruiticosus 1.08 53.86

Outside planted tree canopy, four species, three of which were native, contributed up to 50% of the average similarity (Table 7).

Table 4.8 Outside planted tree canopy vegetation community descriptors These species contributed up to 50% of the average similarity between sites within the Outside planted tree canopy vegetation community. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 21.22%. (species cover-abundance recorded per quadrat) Species Average abundance Cumulative % *Myrsiphyllum asparagoides 2.33 20.64 Cyperus gracilis 1.52 33.28 Viola hederacea 1.74 45.29 Paspalidium distans 1.50 54.33

124 Comparisons between vegetation underneath and outside planted tree canopies

Underneath and outside planted tree canopy treatments had a high percentage similarity (81.0%), comprising of 11 species, 7 of which were native (Bray-Curtis) (Table 4.9). There were 4 native species that increased their abundance under tree canopies and 3 that decreased their abundance. There were 2 exotic species that increased their abundance under tree canopies and 2 that decreased their abundance. There was no clear pattern of increase in native and decline in exotics.

Table 4.9 Average % dissimilarity: Underneath planted tree canopy & Outside planted tree canopy These species contributed up to 50% of the average dissimilarity between Underneath canopy & Outside canopy vegetation. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. (species cover-abundance recorded per quadrat) Species Average Average Cumulative abundance abundance % (+ canopy) (- canopy) *Myrsiphyllum asparagoides 1.48 2.33 6.92 Cyperus gracilis 1.68 1.52 12.79 Viola hederacea 1.00 1.74 18.41 Phyllanthus virgatus 0.86 1.38 24.01 Paspalidium distans 1.48 1.50 29.60 *Sida rhombifolia 1.26 1.20 34.26 Aristida vagans 0.96 1.07 38.50 Microlaena stipoides 0.84 0.67 42.12 Poa labillardierii 0.93 0.80 45.72 *Rubus fruiticosus 1.08 0.55 49.29 *Centaurium asiaticum 0.68 1.11 52.86

125 Species contribution: Underneath planted tree canopies of different planting ages

Vegetation underneath planted tree canopies of both ages of tree planting were characterised by few ground layer species and low similarity between (Table 4.10).

Table 4.10 Number of species contributing up to 50% average similarity (species cover-abundance recorded per quadrat)

Treatment Native Exotic Total Within group similarity (%) 3-5 year old restored 2 2 4 25.09 vegetation 8-10 year old 3 2 5 18.22 restored vegetation

Underneath 3-5 year old tree canopies, four species, three of which were native, contributed up to 50% of the average similarity (Table 4.11).

Table 4.11 Underneath 3-5 year old restored tree canopy vegetation These species contributed up to 50% of the average similarity between sites within the Underneath 3-5 year old restored tree canopy vegetation community. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 25.09%. (species cover-abundance recorded per quadrat) Species Average abundance Cumulative % Cyperus gracilis 2.10 18.27 *Myrsiphyllum asparagoides 2.36 36.07 Paspalidium distans 1.86 49.08 Viola hederacea 1.63 59.05

Underneath 8-10 year old tree canopies, five species, two of which were native, contributed up to 50% of the average similarity (Bray-Curtis) (Table 4.12).

126 Table 4.12 Underneath 8-10 year old restored tree canopy vegetation These species contributed up to 50% of the average similarity between sites within the Underneath canopy vegetation community. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity was 18.22%. (species cover- abundance recorded per quadrat) Species Average abundance Cumulative % Phyllanthus virgatus 2.11 18.40 *Myrsiphyllum asparagoides 1.45 30.52 Aristida vagans 1.54 41.39 *Sida rhombifolia 1.30 49.16 *Centaurium asiaticum 1.05 56.79

Comparisons between vegetation underneath tree canopies of different ages

Vegetation underneath tree canopies of different ages had a high percentage similarity (82.56%), for which 10 species, including 7 native contributed most of the difference (Table 4.13). Of these, three native species that increased their abundance after tree planting, and four that decreased their abundance. Two exotic species that increased their abundance after tree planting and one that decreased its abundance (Table 4.13).

Table 4.13 Average % dissimilarity: vegetation underneath tree canopies of different ages These species contributed up to 50% of the average dissimilarity between vegetation underneath tree canopies of different ages. Average abundance is the average importance score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. (species cover-abundance recorded per quadrat) Species Average Average Cumulative Change abundance abundance % (++,+,0,-,--) (3-5yrs old) (8-10yrs old) *Myrsiphyllum asparagoides 2.36 1.45 6.81 - Phyllanthus virgatus 0.13 2.11 13.14 + Cyperus gracilis 2.10 1.10 19.15 - Paspalidium distans 1.86 1.12 24.75 - Viola hederacea 1.63 1.11 30.24 - *Sida rhombifolia 1.16 1.30 34.80 + Aristida vagans 0.48 1.54 39.24 + Poa labillardierii 1.30 0.43 43.03 - Microlaena stipoides 0.69 0.82 46.58 + *Centaurium asiaticum 0.74 1.05 50.04 +

127 Linking community analyses to environmental variables

Principal components analysis (PCA) Figure 4.8 displays the first two axes (PC1 and PC2) of a PCA ordination on the transformed of environmental variables. The first component accounts for 41% of the variation. Both canopy treatments span the full range of environmental variation. A visual comparison with the PCA and the MDS of species composition (Figure 4.5, page 121) revealed no clear relationship.

Figure 4.8 PCA of environmental variables (Canopy factor shown; =+ underneath canopy, =- outside canopy). Variables measured include: Landform element 1-3, Slope (%), and Aspect (degrees).

128 Table 4.14 Principal components analysis of environmental variables and the % variation explained PC Eigenvalues %Variation explained Cum.%Variation 1 1.23 41.1 41.1 2 1.05 35 76.1 3 0.72 23.9 100

There was no trend found in the environmental attributes of the individual treatment groups. This is an indication that any result found in the differences between canopy treatments would be entirely attributable to the effect of the planted tree canopy and not attributable to environmental variation.

BIOENV When up to three environmental variables were used to represent species composition, only 11% of the variation would be predicted (Table 4.15). The relationships between environmental variables recorded at the sampling locations clearly did not reflect the variation visually evident in this MDS plot of species composition to an acceptable extent (70-75%).

Table 4.15 BIOENV: Environmental variables matched to species composition No. variables 1 % variation explained Landscape position 11.1 No. variables 2 Landscape position 18.7 Slope No. variables 3 Landscape position 11.4 Slope Aspect

129 4.4 Discussion

Small scale effects of planted tree canopies The results of this study indicate that planted trees in abandoned agricultural land do not affect the native species composition at a local level, directly beneath the planted tree canopy. No trend of increasing natives or decreasing exotics was detected under canopies through time since tree planting. Native species richness was significantly higher under canopies at one site only (Hoxton Park), whereas under tree canopies at the other sites the native species richness if anything, was reduced. If sampling to test the Perkins hypothesis had been conducted at Hoxton Park only, the data would have supported its predictions. However, by sampling across several sites to test the generality of the hypothesis, little support for it emerged. There was also increased exotic species richness found underneath tree canopies at all sites, a strong and spatially consistent trend.

These results indicate a continued dominance of vegetation underneath planted tree canopies by exotic species. There was a small range of native species that characterised vegetation underneath the planted tree canopy including Cyperus gracilis, Viola hederacea, Phyllanthus virgatus, Paspalidium distans, Aristida vagans, Microlaena stipoides, and Poa labillardierii. However, these species were also recorded outside tree canopies within restored vegetation. These native species appear to characterise a component of native flora that exists in the pastures irrespective of treatment (McIntyre and Lavorel 1994).

By planting a tree, there was an expectation from the principle of competitive exclusion that the growth of the tree and its canopy would dominate the local resources (water, nutrients, light), starving the dominant exotic species, and facilitating their replacement by native species that are more tolerant of low resource levels (Perkins 1999). At the scale of individual tree canopies, no evidence was found to support this expectation. Trees may shade, but they may also accumulate nutrients under their canopies (Prober et al 2002b). If increased nutrient accumulation is occurring in revegetation, it may in part explain the result observed. The return of natives to revegetated areas found in studies completed in Chapter 3 is a generalised return and not localised to under tree canopies.

130 Evidence from studies in Chapter 3 of this Thesis indicate that the revegetation may be too recent to have had any substantive effect on the dominance of exotics and that it may be that more time is required before native species begin to dominate both in terms of species richness and cover.

The balance of numbers and abundance of native and exotic species observed in this study are subject to the specific responses of each species to the positive and negative effects of tree planting. Based on a balance of species responses to existing environmental conditions, without an extreme disturbance mechanism (for example, repeated spring burns or permanent changes to soil nutrient levels), combined with a massive input of seed, a synthetic mixture of exotics and natives is likely to remain for a long time. This leads into the idea that restoration barriers exist that cannot be overcome by tree planting alone (Hobbs 1993).

Potential barriers may exist at the dispersal or recruitment stage of individual species. Species that would be particularly susceptible to dispersal barriers include those with short-range seed dispersal mechanisms, which once removed from the immediate environment, would find it difficult to return.

Native species with underground tubers would be susceptible to damage by tilling in an agricultural environment and be permanently removed from the ecosystem.

Native species with that primarily used vegetative means of reproduction would also be affected by the negative effects of competition from aggressive and dominant exotics.

Native species that are sensitive to nitrogen and phosphorus levels in soil would be negatively impacted by potential long-term changes in the soil chemistry (pH, nutrient availability, soil water availability etc) that may exist in an agricultural setting. Studies have shown vegetation to modify soil chemistry, creating a potential feedback loop between vegetation and soil chemistry that usually favours the status quo (Prober et al 2002b) and an important source of species composition heterogeneity (Hartwell, 2001). Perennials have more extensive root systems, and take up nutrients year round, while annuals deplete the nitrogen from the soil throughout the growing season

131 returning it when the plant dies and is re-incorporated back into the soil (Prober et al 2002b). The seasonal changes in nutrient levels at the study site were not tested in this study, however the continued dominance of exotics at the study sites may be a direct result of such effects.

One of the main goals of the revegetation program was to improve the diversity of the vegetation via encouraging native understorey species, including grasses and herbs, because together they contribute a large proportion of the species richness of CPW. The majority of herbs and shrubs that occur in temperate woodlands do not have seed stored in soil seed banks. In addition, due to the time since the parent plants existed in abandoned pasture, the seeds that were in the soil seed bank are likely to be lost due to predation and seed death (Clarke 1999). This lack of seed or recruitment blockage forms one of the main limitations to the success of restoration in this grassy woodland. The recruitment of understorey species following tree planting may not be possible without additional input in the form of seed to succeed, at least in the short term, although even this may be insufficient to overcome restoration barriers.

Trends in the development of species composition over time There was no clear trend over time in species composition found underneath tree canopies. The results of this study substantiate those found in Chapter 3, that tree planting may take several decades or longer to facilitate re-establishment of native species. The results found here do not discount the ability of natives to increase abundance following tree planting in the future, however the long time frame it should be acknowledged, along with the realisation that additional re-instatement of understorey (grass and herb) species may be required.

The lack of increase in abundance of natives underneath tree canopies found in this study illustrates the difficult nature of restoring native plant communities in reconstructed ecosystems. Despite attempting to provide increased shading (prompting expectations of increased inter-stitial spaces and decreased competition from exotics), and there being adequate rainfall and temperature, increased abundance of natives was unlikely to be found due to the lack of viable seed and time since the parent plants (and their seed stock) were removed. These results are comparable to a

132 study completed by Windsor (2000) who found that trees and tree canopies were not capable of restoring degraded land without additional intervention.

This study has demonstrated that the tree canopy itself has not in over 10-12 years encouraged an increase in the abundance of native species. The seed source of the desired species must be reintroduced in some form otherwise, it is likely that a mixture of exotic and native species will persist through time. If improvement in the diversity of native species is to occur at these restoration sites, further efforts may needed in terms of importing additional genetic material either via seed or established seedling. Alternatively, although further study is required to determine their effects, other management actions such as burning or grazing may have a positive effect on the abundance of natives under planted tree canopies. Further work in this area has been completed and is reported in Chapter 5 of this Thesis.

This study represents a small-scale analysis of changes in the abundance of native species in restored pasture. The results found in this study correspond with previous comparable study completed by Wilkins et al (2004) which assessed the success of restoration at a large scale at the same location. Although not addressing local level effects of tree canopies, Wilkins et al (2004) found the floristic analyses supported a steady-state model of vegetation dynamics rather than direct successional and that there had been no change in native species richness in restored vegetation.

Implications for restoration programs Alternative methods for reducing the competitive advantage of dominant exotic species include spring burning, herbicide, scalping slashing or crash grazing (Clements 1983, Prober 2005b). All of these methods firstly involve the physical removal of the exotic species and potentially reduce the weed seed pool, both favourable outcomes for re-establishment of native species. However, the effect of these treatments may also be exploited by exotic species that are also adept at utilising recently created bare patches and excluding native species (McDonald, 2000).

To achieve sustainable changes in species composition in restored communities, environmentally sensitive management practices may be required in addition to tree

133 planting to optimise conditions for natural regeneration. After the initial removal of the degrading influence, environments need to be managed appropriately for the longer term, to maintain the dominance of native species (Windsor, 2000).

134

Chapter 5

Seedling Emergence and Establishment after Fire and Neighbour Removal: A comparative analysis between pasture, restored vegetation and remnants

5.1 Introduction

There are limited data relating to the temporal dynamics of the original understorey vegetation present in Cumberland Plan Woodland (CPW). An understanding of CPW understorey species’ responses to disturbance is crucial to its successful restoration. A range of disturbances including fire, climatic extremes, grazing animals and soil invertebrates that create small-scale soil movement, may promote grass and herb recruitment. For example, grazing animals have the effect of neighbour removal that creates greater inter-tussock spaces that may be required for annual forbs and herbs to germinate. Many sparsely occurring native perennial species in CPW previously occurred in the interstitial spaces between tussocks of the dominant C4 grasses (Howell, 2000).

The rate of recruitment of native species is crucial in determining the long-term sustainability of the restored vegetation. Key to this is understanding seedling emergence and establishment. These are important factors to consider during the evaluation of restoration success.

The dormancy and germination cues of Australian temperate grassland plant species are comparatively poorly understood (Yates and Hobbs 1997b). Seed germination or the lack of it, is a crucial transition between life history stages of plant populations (Clarke et al 2000). This transition phase of plants forms a central link to understanding plant population dynamics and how these populations are maintained over the longer term.

Several critical mechanisms were identified as necessary to complete the life-cycle processes of species in restored vegetation. These include: seed release and seed

135 germination; seedling establishment; maturation and successful reproduction (Keith 1996). These issues are addressed below in turn.

In many species, seed release and seed germination need appropriate fire regimes to break seed dormancy or release the seed from the canopy. For example, eucalypt trees regenerate when seeds are released from the tree canopy after burning (Purdie 1977 ). Fire can stimulate germination through direct heat effects on the seeds and by removing inhibiting factors present in seeds and seed coats (Clarke 1999).

Fire is an important germination cue for eucalypts, the main canopy species of CPW, and performs a variety of functions, including preparing the seed bed; more work is required to understand this process (Clarke 1999). The modified fire regimes in restored vegetation, including fire frequency and fire intensity, may contribute to the lack of recruitment of the tree canopy species, in particular species from the Myrtaceae family. Fires that destroy the leaf litter on the ground are known to be important for the regeneration of natural woodland eucalypts because of the subsequent release from competitive effects (Cluff and Semple 1994). Results of previous experiments in this Thesis (Chapter 3) showed little or no recruitment in restored vegetation at other sites, however recruitment without fire has occurred elsewhere (Clarke 1999). Lack of recruitment in restored vegetation may also be attributable to episodic germination of seeds, infrequent seed supply or seed predation, factors observed in remnants (Clarke 1999).

In the absence of fire, accumulation of litter and increased shading may inhibit recruitment of some species, while others disappear in a heavily shaded environment and may find future recruitment difficult due to the lack of viable seeds in the soil (Lunt 1990, Morgan 1995a, 1995b). Litter accumulation benefits shade tolerant species and decreases light, reducing germination and establishment (Foster 1998).

The herbaceous layer including grasses, graminoids and herbs of grassy woodlands require light stimulation to recruit (Morgan 1998, Lodge and Whalley 1981). Light stimulation is a common requirement for germination of grassy woodland species and is consistent with previous studies of temperate grassland forbs (Clarke et al 2000). Several authors have described the effects of heat and smoke and fire related effects

136 on the germination and growth of shrubs (Auld 1996, Keith 1996), however little is known about the germination and establishment requirements of shrubs in temperate woodlands (Clarke et al 2000).

It is possible that two management regimes, fire and slashing (neighbour removal) may improve the rate of restoration in a grassy woodland by promoting the germination of canopy species and retarding the growth of dominant exotic C3 grasses. Neighbour removal may also improve the germination success of native annual forbs and graminoids, thereby increasing the diversity of restored vegetation. These two management techniques may both be applied cost effectively at a large or small scale and may have significant impact on the long-term sustainability of restored vegetation. Despite this, their effects on restored vegetation in CPW have not been studied. Gilfedder et al (1994) have completed studies on the effects of neighbour removal on a population of an endangered species in Tasmanian remnants. They found seedling establishment to be low and short-lived on grass-covered compared with herb-dominated ground and germinants more abundant in grazed compared to ungrazed plots.

The presence of dominant exotic species in restored vegetation may have several negative effects that influence the long-term sustainability of native plants including: failure of seed production of desired species; making the seedbed less suitable for germination and establishment of native species; and, modifying the fire regime (frequency and intensity) causing disruption to growth of young plants. Removing exotic species and controlling the timing, frequency and intensity of fire, may create a suitable seedbed, and encouraging seed release.

Experiments detailed in previous Chapters revealed significant increases in native species richness in restored vegetation compared to untreated pasture. Despite these increases, exotics still remain dominant in the community and affect the long-term sustainability of restored vegetation.

Revegetation works at the study location began in 1992 with the goal to re-establish the native grassy woodland (Perkins 1992). The methods of revegetation used at the site since 1992 have been described in Chapter 3 of this Thesis. The location, existing

137 vegetation types and previous land uses have also been described in previous Chapters.

This study aims to explore the mechanisms controlling plant germination and establishment by manipulating fire and the presence of neighbours across abandoned agricultural pasture, revegetated land and remnant vegetation.

Aims: Given the gaps in knowledge identified above, and the possible usefulness of fire and neighbour removal in revegetation the following aims were identified:

1. To compare seedling emergence (numbers and species composition) over 12 months in: untreated pasture, restored vegetation, and remnants subject to the factorial combination of fire and neighbour removal treatments; and,

2. Follow seedling survival of native and exotic species over 12 months to determine whether either fire or presence of neighbours are reasons for differences in establishment of natives in restored pasture compared to remnants.

The responses of species to the proposed treatments in restored vegetation are largely unknown. However, some generalised predictions of responses of species to the proposed management treatments may be useful. The predictions are based on the evolutionary history of different plant groups.

The predicted responses of native and exotic species to the treatments may be explained in terms of their pre-adaptations to different environments (Denslow 1985). Due to the evolutionary history experienced by Australian natives species of low fertility soils and low disturbance history (except for wildfires), they would have limited adaptation to productive, moist sites and disturbances. Opposed to this, exotic species are more likely to have been derived from a history of agricultural cultivation and other major disturbances such as glaciation, and therefore be more adapted to

138 moister, more productive sites, and capable of exploiting changes in their environment.

In response to the management treatments, exotics are likely to display increased germination in the plots where neighbours have been removed because they are more adept at exploiting changes in environmental conditions and a part of their success as weeds is their ability to respond quickly (germinate) to bare soil. However, it is predicted that due to the absence of fire in their evolutionary history, an application of fire will destroy more of the exotic seeds than native seeds in the seedbank. Conversely, it is expected that the natives will have an augmented germination response to the fire and the combined fire and neighbour removal treatments.

Both treatments (neighbour removal and fire) remove aboveground biomass of neighbours, result in openings in the sward, and higher light levels at soil surface. Fire has a number of other effects additional to neighbour removal; it also provides germination cues (heat, combustion products), elevated nutrients (ash-bed), and potentially destroys surface or litter seed.

The hypotheses tested within this Chapter were that the two forms of neighbour removal used (fire and slashing) would: • increase seedling establishment compared to controls; • may combine in their effects, either additively or interactively; In addition;

• native and exotic species may react differently to the fire and neighbour removal treatments; and,

• seedling emergence and establishment response may differ between pasture, restored vegetation and remnants.

The proposed fire and neighbour removal treatments attempt to replicate natural environmental conditions, create suitable seed beds and stimulate seed rain. If successful in terms of promoting restoration, the treatments would also be cost effective and practical land management techniques for land managers over and above simply planting trees and shrubs.

139 5.2 Methods

Experimental design The experiment had the following factors in the design: • Fire: unburnt and burnt • Neighbours: neighbours present or absent. • Vegetation community: pasture, 8 – 10 year old restored, and remnant vegetation • Site: Hoxton Park, and Plough and Harrow. Fire and neighbour treatments were combined factorially (Table 5.1). Three replicate quadrats of 5 x 5 m were established for each treatment x vegetation community x site combination making a total of seventy-two 25m² quadrats. Treatments were randomized amongst quadrats in each vegetation community at each site.

Table 5.1 Experimental design FIRE - +

NEIGHBOUR + No fire Fire No Neighbour removal No Neighbour removal

- No fire Fire Neighbour removal Neighbour removal

Site and vegetation community selection The two sites were selected with similar underlying parent material, topography and vegetation types. The geology, topography and climate relevant to the location are described in Chapter 2 of this Thesis.

In order to control for environmental variation, the following factors have been either kept within a small range of variation, as far as possible, or randomly selected from topographic maps using grid overlays and random numbers tables at plot level: slope (0-30 degrees); aspect (0-360 degrees); soil type (clay loams derived from Wianamatta shales); previous agricultural practices (pasture improvement with cattle grazing): and, revegetation technique (mechanical planting).

140 Each vegetation type (pasture, 8-10 year old restored vegetation and remnant) was mapped on 1:25000 topographic maps. Vegetation types were verified by site inspection. Due to the disturbed matrix of extant vegetation, the restored vegetation was in patches of variable sizes and shapes. Sampling was confined to vegetation patches of a minimum size of one hectare and a minimum width of 100 metres. All quadrats surveyed were located underneath the canopy or outside the canopy of planted Grey Box (Eucalyptus moluccana) trees because this was by far the most commonly planted species.

To enable a balanced sampling design, it was necessary to pool samples of restored vegetation by age groups (8-10 years). Patches of vegetation for each treatment were overlain by a grid of 500 metres x 500 metres. These grids were then numbered and a random numbers used to select the locations of quadrats (Figure 5.1). Within each 25m² of plot area, a 1m² was randomly selected for sampling.

141

Figure 5.1 Location of revegetation works by Greening Australia and sampling quadrats Dates show year of revegetation (only some displayed)

142 Treatments Treatments included an application of fire and/or temporary neighbour removal (neighbour removal and herbicide). Control treatments involved slashing a 1-metre wide boundary strip and a water application to dampen the slashed strip (Figure 5.2).

Figure 5.2 Application of slashed strip in pasture vegetation

Fire treatments involved slashing a 1 metre wide boundary strip one day prior to the fire treatment; water application to dampen the slashed strip; fire application of to all four corners of the plot area via LPG gas tank and flame applicator until entire combustion of vegetative material was achieved (Figure 5.3).

143

Figure 5.3 Fire application in remnant vegetation

Neighbour removal treatments involved slashing of a 1 metre wide boundary strip of vegetation one day prior to the herbicide application; all vegetation within the 25m² plot area was slashed to <10 mm above ground level with petrol driven slasher; vegetation was removed from quadrat area; non-selective herbicide Roundup® was sprayed as per label directions (10 ml/L) over the quadrat area; where rainfall occurred within 6 hours of herbicide application, a follow up application was made the next dry day (Figure 5.4).

144

Figure 5.4 Neighbour removal treatment in remnant vegetation

Application of both treatments (fire and neighbour removal) involved slashing of a 1 metre wide boundary strip of vegetation one day prior to the fire then slash and herbicide treatment; non-selective herbicide Roundup® was sprayed as per label directions (10 ml/L) at least three days day prior to the fire application; all vegetation within the 25m² plot area was slashed to <10 mm above ground level with petrol driven slasher; vegetation was removed from quadrat area and where rainfall occurred within 6 hours of herbicide application, a follow up application was made the next dry day to ensure the full effect of the herbicide; on the day of the fire treatment, water was applied to the slashed strip and to dampen any dry vegetation; fire was applied to all four corners of the plot area via LPG gas tank and flame applicator until entire combustion of vegetative material was achieved (Figure 5.5). Fire intensity (as indicated by flame height) was maintained by a consistent application of flame via the gas tank over the entire plot area, however a potential confounding factor within the treatment was the removal of the slashed vegetation prior to fire which would reduce the fuel load and fire intensity (flame height) compared to the fire alone plots. All treatments were applied during June-July 2003.

145

Figure 5.5 Neighbour removal, then fire application in pasture vegetation

146 Data collection

Species composition All quadrats were surveyed from July 2003 through to July 2004 (Table 5.2). The cover-abundance assessment method was used for pre-treatment sampling of the vegetation using the Braun-Blanquet scale as detailed previously in Chapter 3 of this Thesis.

Table 5.2 Sampling events and corresponding dates Week no. Date / Year 2 30 July 2003 3 6 August 2003 4 20 August 2003 9 24 September 2003 29 15 January 2004 52 25 June 2004

The quadrats comprised two primary axes following N-S and E-W directions and were established with tape measures and a compass. Steel stakes marked the boundaries. Quadrats were re-sampled at each sampling time.

Figure 5.6 Quadrat used for sampling Twenty five metres squared of treatment area outside which an additional 1-metre wide strip formed a boundary buffer from existing vegetation surrounding the quadrat. Within the 25m² treatment area, 1m² was randomly selected for sampling of germinants and was re- sampled on each sampling occasion (repeated measures sampling). A 0.5-metre minimum distance from the outside edge of the larger plot boundary acted as a buffer.

147

Germination and establishment response of plants to the treatments were observed in all quadrats. Each germinating seedling was tagged, recorded and survivorship monitored for twelve months. All germinating species were either identified on site using Harden (1990-1993) as the reference or at the National Herbarium of NSW, Sydney. Reference specimens are held in the herbarium at the Ecology Research Group, University of Western Sydney. Nomenclature is according to Harden (1990- 1993). Numbers of plants that could not be identified due to an inadequate specimen size were low and were not included in the data analyses. However, germinants were identified as monocotyledon or dicotyledon wherever possible. Over the duration of sampling, most species became large enough to identify in the field.

Within each 1m² quadrat each germinant was recorded by number, species (where possible) and location within quadrat (numbered stake) during each sampling event. The fate of all germinants was followed over a twelve-month period. Sampling was undertaken during weeks numbered 2, 3, 4, 9, 29, and 52. Week Ø was taken as the end of the first week in August 2003.

Data analyses

Species composition

Cumulative total number of germinants over time The cumulative numbers of seedlings emerging were recorded after each treatment over the duration of sampling. Mean numbers were plotted for each vegetation type at each site and visually compared.

Species richness and total number of germinants Mean numbers of germinants (native and exotic species numbers) were compared within and between treatments using a four-level mixed model ANOVA with the following terms: fire (fixed), neighbour (fixed), vegetation community (fixed), site (nested within vegetation community) with (n=3) replicate quadrats.

Non-significant interactions (P>0.25) with error terms were pooled with error terms in both analyses (native and exotic species numbers). Homogeneity of variances was

148 tested using Cochran’s test and log transformations were necessary for numbers of both native and exotic species germinants data due to heterogeneous variances (Quinn, 2002).

Community composition Multivariate analyses were used to identify floristic groups using PRIMER (Clarke and Gorley 2001). Similarity matrices were calculated for total species, native species and exotic species, using the Bray-Curtis index on un-transformed data and clustered using group averages. These analyses were done at quadrat level. Analyses were also performed at the site level. Quadrats recording a nil germination result in all sampling events were excluded from analysis.

An ordination was then performed using non-metric multi-dimensional scaling (nMDS) to produce a two or three-dimensional graphical representation of the treatments and vegetation groups.

For the nMDS ordinations, Bray-Curtis dissimilarity matrices were computed from cover-abundance scores for all germinants in each sampling event. ANOSIM was used to test for significant differences in species composition between treatments; no standardisation, and square root transformation and the Bray Curtis similarity measure applying. All treatment and vegetation groups giving zero germination were excluded from analysis.

Two-way crossed ANOSIM was used to test simultaneously for differences between treatments and sites. Analyses of the pairwise comparisons after sampling Week 52 was completed showed where the differences, if any, occurred within and between vegetation communities and treatments. Many comparisons comprised numbers too low for analysis.

Pre-treatment vegetation composition The effect of the pre-treatment vegetation community on the species composition and abundance of germinants was tested using multivariate analysis. Multivariate analyses were used to identify floristic groups of pre-treatment vegetation composition using

149 PRIMER (Clarke and Gorley 2001). Similarity matrices were calculated for species cover using the Bray Curtis similarity measure and clustered using group averages with un-transformed data. These analyses were completed at quadrat level using data from all quadrats. Data were grouped according to their similarity in species composition and abundance.

An ordination analysis was then performed using non-metric multi-dimensional scaling (nMDS). This analysis provided a two or three-dimensional graphical representation of the pre-treatment vegetation composition. Differences in the floristic composition between the pre-treatment vegetation communities are based on these analyses.

For the nMDS ordinations, Bray-Curtis dissimilarity matrices were computed from cover abundance scores for all plant species. ANOSIM was used to test for significant differences in species composition and analysed between treatments: Euclidean Distance similarity measure, no standardisation, and without transformation.

The ordinations were then visually compared with those obtained from the analysis of germination data. Similarities between vegetation and treatments groups were noted. Further matching of multivariate patterns using the RELATE and 2STAGE routines from Primer were not possible due to the different numbers of quadrats with no individuals present during sampling.

150 5.3 Results

Cumulative total number of germinants over time The pattern of total seedling emergence was variable over the duration of sampling (July 2003 until June 2004). One recognisable pattern at both sites was that numbers of emerging seedlings increased from week 1 until week 9, when the numbers began to plateau (Figure 5.7, Figure 5.8, Figure 5.9, Figure 5.10, Figure 5.11, Figure 5.12).

The stabilising of numbers of emerging seedlings after week 9 may correspond to local rainfall patterns experienced over the duration of sampling (Figure 5.13). After a high period of rain just prior to the treatment period, a period of below average rainfall followed for the remainder of the sampling period. At one site (Plough and Harrow), the numbers of emerging seedlings in pasture after neighbour removal were approximately six times higher than all others. Similar differences were found in restored vegetation, where again at one site (Hoxton Park) the numbers of emerging seedlings after neighbour removal were substantially higher than all others. Several combinations of treatments including +Fire and -Neighbour and -Fire +Neighbour, resulted in no emergent seedlings until week 29.

Pasture

500 ) -2

400

300 No fire Neighbour

No fire Neighbour removed

200 Fire Neighbour

Fire Neighbour removed

100

0 Meancumulative no.germinants perquadrat (m 2 3 4 9 29 52 Week (n.t.s.)

Figure 5.7 Mean cumulative number of germinants recorded in pasture vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale

151 Restored

700 -

600

500 No fire Neighbour No fire Neighbour removed 400 Fire Neighbour

) Fire Neighbour removed 2

300

200

100 Meancumulative no. germinants per quadrat (m 0 2 3 4 9 29 52 Week (n.t.s.)

Figure 5.8 Mean cumulative number of germinants recorded in restored vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale

Remnant

300 -

200 No fire Neighbour No fire Neighbour removed

Fire Neighbour ) 2 Fire Neighbour removed

100 Meancumulative no. germinants per quadrat (m 0 2 3 4 9 29 52 Week (n.t.s.)

Figure 5.9 Mean cumulative number of germinants recorded in remnant vegetation at Hoxton Park over the duration of sampling across treatments (m-²). Time axis not to scale

152 Pasture

- 800

700

600

500 No fire Neighbour No fire Neighbour removed ) 2 400 Fire Neighbour Fire Neighbour removed 300

200

100

Meancumulative no. germinants per quadrat (m 0 2 3 4 9 29 52 Week (n.t.s.)

Figure 5.10 Mean cumulative number of germinants recorded in pasture vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale

Restored )

-2 180 160 140 120 No fire Neighbour 100 No fire Neighbour removed Fire Neighbour 80 Fire Neighbour removed 60 40 20 0 Meancumulative no. germinants per quadrat (m 2 3 4 9 29 52 Week (n.t.s.)

Figure 5.11 Mean cumulative number of germinants recorded in restored vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale

153 Remnant

120 ) -2 100

80 No fire Neighbour No fire Neighbour removed Fire Neighbour 60 Fire Neighbour removed

40

20 Mean cumulative no. germinants per quadrat (m quadrat per germinants no. cumulative Mean

0 1 2 3 4 5 6 Week (n.t.s.)

Figure 5.12 Mean cumulative number of germinants recorded in remnant vegetation at Plough and Harrow over the duration of sampling across treatments (m-²). Time axis not to scale

300 Week 29Week 52Week 250 Week2 Week4 Week9

200

150 Actual rainfall during sampling

Rainfall (mm) Rainfall Long term 100 average rainfall

50

0 Jul Jul Jul Jan Jun Oct Jan Jun Oct Jan Jun Oct Jan Feb Mar Apr Feb Mar Apr Feb Mar Apr Sep Nov Dec Sep Nov Dec Sep Nov Dec May May Aug May Aug Aug 2002 2003 2004 2005 Time (Year/Month)

Figure 5.13 Rainfall during sampling period and long-term average Sampling weeks shown by dashed arrows. Adapted from (Anon. 1979).

154 Number of native species germinants The total number of native germinants was low for all treatments; 12.6% of quadrats sampled recorded no germinants at all in the six sampling events over the 12-month period. Control plot (baseline) germination results gave a range of 0-4m-2 over the 12- month period. In remaining treatments and sites (20 means), there were only 4 cases where germination was substantially greater than this baseline germination rate (Table 5.3). These were; Remnant +Fire -Neighbour at Hoxton Park (30 m-2); Pasture +Fire +Neighbour at Plough and Harrow (19m-2); Restored -Fire -Neighbour Hoxton Park (12m-2); and Remnant +Fire +Neighbour at Hoxton Park (9m-2). It is noteworthy that 3 of the above-mentioned treatments were +Fire treatments at Hoxton Park, 2 of which were in Remnant vegetation

Table 5.3 Mean number of native germinants (m-2) (se) (untransformed) Veg / Site Pasture Restored Remnant Treatments HP P&H HP P&H HP P&H -Fire +Neighb 0(0) 2(1.15) 0(0) 0(0) 0.67 (0.38) 4 (2.3) -Fire -Neighb 5.33(2.52) 0(0) 11.67(6.44) 6.67(1.83) 0.33(0.19) 0.67(0.38) +Fire +Neighb 0(0) 18.67(10.77) 0.67(0.38) 0(0) 9.33(0.69) 1.67(0.51) +Fire -Neighb 7.33(4.23) 4(1.33) 4(1.33) 0(0) 30(16.74) 0(0)

Against this background of low and uneven germination of natives, only two terms were significant in the ANOVA (Transformed means, Table 5.4; ANOVA, Table 5.5). Firstly, neighbour removal was significant in interaction with vegetation type. Comparison between the neighbours treatments within each vegetation type showed that differences between neighbours present or absent was significant for restored pasture only (Table 5.5, Table 5.6 Planned comparison 2, Figure 5.14). This result was as much a product of lack of recruitment of natives in the neighbours present treatment, as it was of an increase in native germination due to removal of neighbours in restored vegetation (Figure 5.14). Neighbour removal had no significant effect on recruitment of natives in pasture or remnant vegetation types.

Secondly, fire was significant in interaction with site (Table 5.5); comparison of means showed an increased although not significant fire effect at Hoxton Park (Table 5..7, Figure 5.15).

155 - Table 5.4 Mean number of native germinants (m ²) (logx+1 transformed) Veg / Site Pasture Restored Remnant Treatments HP P&H HP P&H HP P&H No fire Neighb 0.00 0.28 0.00 0.00 0.16 0.37 No fire No neighb. 0.55 0.00 0.62 0.82 0.10 0.16 Fire Neighb 0.00 0.59 0.16 0.00 1.01 0.36 Fire No neighb. 0.45 0.55 0.55 0.00 0.81 0.00

- Table 5.5 ANOVA mean number of native germinants (m ²) (logx+1 transformed, pooled) ANOVA Source of Variation SS df MS F P F-ratio vs. Fire 0.25 1 0.25 0.43 0.56 FirexSite(Veg) Neighb 0.35 1 0.35 1.50 0.31 Error Veg 0.13 2 0.07 0.29 0.77 Error Fire x Neighb 0.17 1 0.17 0.82 >0.25 Error Fire x Veg 0.87 2 0.44 0.74 0.55 FirexSite(Veg) Neigh x Veg 1.32 2 0.66 11.30 0.04* Error Fire x Site (Veg) 1.77 3 0.59 10.04 0.04* Error Error 12.42 59 0.21 Total 17.31 71

Cochran’s Test C15,2=0.16, P<0.001, NS

Table 5.6 Planned Comparisons of numbers of native species between Neighbour treatments across vegetation types (logx+1 transformed) Planned comparison SS df MS F1,71 P 1 Remnant: +Neighb. vs. –Neighb. 0.25 1 0.25 1.17 0.28 2 Restored: +Neighb. vs. –Neighb. 1.25 1 1.25 5.65 0.02* 3 Pasture: +Neighb. vs. –Neighb. 0.18 1 0.18 0.81 0.37 Sum 1.68 3

Table 5..7 Planned Comparisons of numbers of native species between Fire treatments at different sites (nested within Veg) (logx+1 transformed) Planned comparison SS df MS F1,71 P HP: +Fire vs. –Fire 0.60 1 0.60 2.74 0.10 P&H: +Fire vs. –Fire 0.004 1 0.004 0.02 0.89 Sum 0.604 2

156 0.6 ) -2

0.5

0.4

0.3

0.2 number native germinants per quadrat (m native quadrat number per germinants

x+1 0.1 Log Log

0 Neighb. No neighb. Neighb. No neighb. Neighb. No neighb.

Pasture Restored Remnant Neighbour / Vegetation treatments

Figure 5.14 Mean number (logx+1) native species germinants across vegetation communities between neighbour treatments (m-²)

0.6 ) -2

0.5

0.4

0.3

0.2

(m no. native quadrat germinants per 0.1 (x+1) Log 0 - Fire + Fire - Fire + Fire HP P&H Site / Fire treatment

Figure 5.15 Mean number (logx+1) native species germinants across Fire treatments between sites (m-²)

157 Number of exotic species germinants Numbers of exotic species germinants were higher than natives and were lowest in controls and highest after -Neighbour treatments in restored vegetation (Table 5.8, Table 5.9). Control (baseline) germination was in the range of 0-33m-2 over the 12- month period. In remaining treatments and sites (20 means), there were 11 cases where germination of exotics exceeded this baseline level. There were 3 cases where germination was greater than 200 m-2: 2 in -Fire, -Neighbour at Plough and Harrow restored and pasture, and one in +Fire -Neighbour at Hoxton Park in restored vegetation. There were 4 cases in the range of 100-199m-2: 3 in +Fire, +Neighbour at Hoxton Park pasture, restored and remnant and 1 in +Fire -Neighbour at Hoxton Park in restored vegetation. There were 4 cases in the range of 50-99m-2: 3 in +Fire, one in -Fire (Table 5.8, Table 5.9).

Two terms were significant in the ANOVA (transformed means, Table 5.9, ANOVA, Table 5.10). Firstly, differences in the numbers of exotic species germinants varied between sites, with significantly higher numbers at Hoxton Park compared to Plough and Harrow (Site significant, Table 5.10). Secondly, the neighbour removal treatment was significant in interaction with vegetation community; numbers of exotic species germinants were significantly higher in pasture after neighbour removal compared to neighbour present (Table 5.11, Figure 5.16). This trend was repeated for restored vegetation, though not sufficiently so to be significant (Table 5.11, Figure 5.16), whilst in remnant this trend was reversed.

Two further interactions approached significance after analysis, and patterns of treatment effects were examined. The means for the fire x neighbour interaction (P = 0.055) are shown in Figure 5.17, with interaction means for the raw data shown in Table 5.12. The fire x neighbour interaction means summarised important trends in the response of exotics, so effects of fire were compared within neighbour treatments, and effects of neighbours were compared within fire treatments. Within neighbour treatments, the number of exotic species germinants was low in controls (+Neighbour -Fire), and showed a significant increase after fire only in the +Neighbour treatment; this effect of fire disappeared in –Neighbour treatment, as numbers of exotic

158 germinants were high after slashing, regardless of fire treatment (Table 5.13, Figure 5.17). Comparing neighbour treatments within fire treatments showed that exotics responded significantly to neighbour removal only in unburnt plots (Figure 5.17, Table 5.14), and not in burnt plots, where numbers were universally high. Thus, exotics increased significantly after any form of neighbour removal (fire or slashing); the two forms of neighbour removal were equivalent and not additive in effect. (Whilst the Planned Comparisons shown in Table 5.13 and Table 5.14 exceed the degrees of freedom available for comparison of the four interaction means in Figure 5.17, requiring adjustment to the α level strictly speaking, the F-ratios detected as significant were large, and would still be so under any adjusted α level.)

The fire x site interaction approached significance also (Table 5.10), and the means are shown in Figure 5.18. The effects of fire in stimulating germination of exotics were stronger and more consistent at Hoxton Park, then at Plough and Harrow.

Table 5.8 Mean number of exotic germinants (m-2) (se) (untransformed) Exotic Pasture Restored Remnant Site HP P&H HP P&H HP P&H -Fire +Neighbour 8(1.86) 0(0) 4(1.76) 32.67(10.86) 0.67(0.19) 13.33(6.57) -Fire -Neighbour 4.33(1.71) 0.67(0.39) 125.33(23.53) 471(248.15) 68.67(11.54) 261.67(139.54) +Fire +Neighbour 108.67(47.88) 10.67(2.67) 184.33(41.86) 69(27.72) 127.33(33.5) 36.67(17.81) +Fire -Neighbour 51(20.79) 0.67(0.38) 224.33(88.34) 16.33(4.76) 55.67(19.42) 52.33(22.14)

-2 Table 5.9 Mean number of exotic germinants (m ) (log x+1transformed) Exotic Pasture Restored Remnant Site HP P&H HP P&H HP P&H No fire Neighbour 0.20 0.76 0.51 1.39 0.87 0.00 No fire No neighbour 1.79 1.83 2.04 2.04 0.55 0.16 Fire Neighbour 1.97 1.04 2.19 1.63 1.55 0.98 Fire No neighbour 1.26 1.49 2.09 1.12 1.43 0.16

159 - Table 5.10 ANOVA of mean number of exotic germinants (m ²) (log x+1 transformed, pooled) ANOVA Source of Variation SS df MS F P Fire 2.84 1 2.84 2.91 0.18 Neighb 1.03 1 1.03 3.86 0.14 Veg 10.28 2 5.14 4.09 0.13 Site (V) 3.77 1 1.25 3.41 0.02* Fire x Neighb 5.27 1 5.27 9.40 0.055 Neigh x Veg 2.51 2 1.25 3.41 <0.05* Fire x Site (V) 2.94 3 0.97 2.66 0.059 Fire x Neighb x Site(V) 1.68 3 0.56 1.52 0.22 Error 20.10 55 0.37 Total 50.43 71

Cochran’s C22,2=0.18, P<0.01, NS Veg comm tested against error

Table 5.11 Planned Comparisons of numbers of exotic species between neighbour removal treatments at Vegetation types (logx+1 transformed) Planned comparison SS df MS F1,71 P Remnant: +Neighbour vs. –Neighbour 0.46 1 0.46 1.24 0.27 Restored: +Neighbour vs. –Neighbour 0.92 1 0.92 2.50 0.12 Pasture: +Neighbour vs. –Neighbour 2.16 1 2.16 5.87 0.02* Sum 3.54 3

2 ) -2 1.8

1.6

1.4

1.2

1

0.8

0.6

0.4 number exotic (m number quadrat germinants per x+1 0.2 Log Log

0 Neighbour Neighbour removed Neighbour Neighbour removed Neighbour Neighbour removed

Pasture Restored Remnant Treatment

Figure 5.16 Mean number (logx+1) exotic species germinants between neighbour removal treatments in different vegetation groups (m-²)

160 1.8 ) -2 1.6

1.4

1.2

1

0.8

0.6

0.4 number exotic(m number quadrat germinants per x+1 0.2 Log Log

0 Neighbour Neighbour removed Neighbour Neighbour removed No fire Fire Treatment

Figure 5.17 Mean number (logx+1) exotic species germinants between fire treatments after different neighbour removal treatments (m-²)

Table 5.12 Comparisons of mean numbers of exotic species between fire treatments after different neighbour treatments (untransformed) Treatment Mean no. exotic species -Fire +Neighbour 9.8 -Fire –Neighbour 155.3 +Fire +Neighbour 89.4 +Fire –Neighbour 66.7

Table 5.13 Planned Comparisons of numbers of exotic species between neighbour removal treatments within fire treatments (logx+1 transformed) Planned comparison SS df MS F1,71 P 1. +N: +F vs. –F 7.94 1 7.94 21.53 <0.001* 2. -N: +F vs. -F 0.18 1 0.18 0.50 0.48 Sum 8.12 2

Table 5.14 Planned Comparisons of numbers of exotic species between neighbour removal treatments within fire treatments (logx+1 transformed) Planned comparison SS df MS F1,71 P 1. +F: +N vs. -N 0.82 1 0.82 2.23 0.14 2. -F: +N vs. -N 5.48 1 5.48 14.86 <0.001* Sum 6.30 2

161 ) 2.5 -2

2

1.5

1

0.5 no. exotic germinants per quadrat (m no. exoticquadrat per germinants x+1

Log 0 No fire Fire No fire Fire No fire Fire No fire Fire No fire Fire No fire Fire

Pasture Restored Remnant Pasture Restored Remnant

Hoxton Park (HP) Plough & Harrow (P&H) Fire treatments & Vegetation type between Sites

Figure 5.18 Mean number (logx+1) exotic species germinants between fire treatments at different sites (m-²)

162 Vegetation community composition

Species composition after treatments There was no difference in species composition of germinants between vegetation communities and treatments after week 52 (Figure 5.19). The relative changes in species composition at the end of the sampling period from controls to treatments (fire and neighbour removed) have been highlighted in Figure 5.19. Different coloured lines have been used to clearly identify changes in species composition of germinants with experimental treatment of fire and neighbour removal with the end points marked as dots. Although there are no clear relationships between treatments or vegetation types, a vertical axis of movement after fire emerged for pasture and restored vegetation, whilst the neighbour removal treatment had a variable effect on the species composition of germinants. In remnant vegetation, movement of species composition after treatments was more in the horizontal plane (Figure 5.19).

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Figure 5.19 Ordination analysis: total species composition of germinants (site means), week 52. Global R=-0.0 (P=0.47). No difference between treatments or vegetation communities. Ordination completed using non-metric multi- dimensional scaling. The symbols represent centroids of quadrats in their treatment classifications based on ordination analysis of total species composition. Lines indicate change in species composition from controls (circled) after each treatment.

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Native species

Two species (Einadia hastata and Glycine tabacina) germinated in all vegetation types. Twelve native species germinated in pasture vegetation. After restoration a further 8 native species germinated, with 5 present in pasture not further recorded in restored vegetation. Remnant vegetation recorded a total of 19 species, these comprised 5 in common with restored vegetation and an extra 14 germinated (Table 5.15).

There was no difference in native species composition of germinants between vegetation communities and treatments after week 52 (Figure 5.20). There were 33 native germinant species recorded during sampling over the twelve-month period (Table 5.15), however of these species 55% were not found in restored vegetation and 42% were not found in Remnant vegetation.

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Table 5.15 Native species germinants Native species found to have germinated over the twelve-month sampling period. Species Pasture Restored Remnant Asperula conferta √ Bothriochloa macra √ Brunoniella australis √ √ Bulbine bulbosa √ Bursaria spinosa √ Carex inversa √ √ Centella asiatica √ Daucus spp. √ Desmodium varians √ Dianella revoluta √ Dichondra repens √ Dillwynia sieberi √ Einadia trigonos √ Einadia hastata √ √ √ Eragrostis leptostachya √ Geranium homaneum √ Glycine tabacina √ √ √ Hardenbergia violacea √ Hypericum gramineum √ √ Hypoxis hygrometrica √ Lagenifera stipitata √ Lomandra filiformis ssp. filiformis √ √ Lotus suaveolens √ √ Oplismenus imbecillis √ Oxalis perennans √ √ Paspalidium distans √ Phyllanthes virgatus √ Ranunculus lappaceus √ Rumex brownii √ Solanum pinifolium √ √ √ Themeda australis √ Viola hederacea √ √ Wahlenbergia gracilis √ ∑ 12 15 19

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Figure 5.20 Ordination analysis: native species composition of germinants, week 52. Global R=-0.073 (P=0.865). No difference between treatment and vegetation groups. Ordination using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of total species composition.

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Exotic species

Thirteen exotic species germinated after week 52 (Table 5.16). All exotic species germinated in all vegetation groups in all treatments though in variable numbers. There was no difference in exotic species composition of germinants between vegetation communities and treatments after week 52 (Figure 5.21).

Table 5.16 Exotic species germinants Total exotic species found to have germinated in all quadrats in all sites in the twelve-month sampling period (Week 52) *Anagallis arvensis *Senecio madagascariensis *Apium leptophyllum *Setaria gracilis *Araujia hortorum *Sida rhombifolia *Cirsium vulgare *Sonchus oleraceus *Conyza bonariensis *Trifolium repens *Hypochoeris radicata *Verbena rigida *Plantago lanceolata

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Figure 5.21 Ordination analysis: exotic species composition of germinants, week 52. Global R=-0.024 (P=0.3%). No difference between treatment and vegetation groups. Ordination using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of total species composition. Analysis excluded outliers to avoid skew of results (HP Fire Neighbour Restored, Fire No Neighbour Pasture at HP and WSRP)

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Comparisons within treatment groups and vegetation communities A SIMPER analysis determined the percentage contribution of each species to the average similarity within and average dissimilarity between treatment groups and vegetation communities. Within group similarity for all vegetation and treatment groups was low, the highest recorded as 15.6 in the Fire and Neighbour Restored Group (Table 5.17). In 9 out of 15 groups there was zero (Ø) similarity which means there were no shared species within these groups reflecting the high level of heterogeneity within groups. This high degree of background variability within quadrats in each vegetation group renders any differences between treatments groups insignificant. Community group descriptors were dominated by two exotic species (Sida rhombifolia and Senecio madagascariensis) and one native species (Lagenifera stipitata) (Table 5.18). The treatment groups and vegetation communities missing from this table had too low a degree of similarity for analysis.

Table 5.17 Average similarity within each treatment and vegetation group Treatment and vegetation group Average Similarities No fire Neighbour Pasture 0 No fire Neighbour Restored 0 No fire Neighbour Remnant 0 No fire Neighbour removed Pasture 11.1 No fire Neighbour removed Restored 5.7 No fire Neighbour removed Remnant 0 Fire Neighbour Pasture 0 No fire Neighbour removed Restored 5.7 No fire Neighbour removed Remnant 0 Fire Neighbour Pasture 0 Fire Neighbour Restored 15.6 Fire Neighbour Remnant 8.5 Fire Neighbour removed Pasture 0 Fire Neighbour removed Restored 8.3 Fire Neighbour removed Remnant 0

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Table 5.18 Vegetation and treatment group community descriptors These species contributed up to 50% of the average similarity between sites within each vegetation and treatment group community. Average abundance is per quadrat. Quadrats where nil germination was recorded have been excluded. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. The average similarity of each group is also shown.

Group Average Species community Average Cumulative similarity descriptors abundance % No fire Neighbour removed Pasture 11.11 *Senecio madagascariensis 0.75 100 No fire Neighbour removed Restored 5.79 *Sida rhombifolia 10.60 52.38 No fire Neighbour removed Remnant 0.00 *Sida rhombifolia 10.60 52.38 Fire Neighbour Restored 15.61 *Senecio madagascariensis 3.00 76.27 Fire Neighbour Remnant 8.59 Lagenifera stipitata 2.80 56.22 Fire Neighbour removed Restored 8.39 * Sida rhombifolia 1.67 100

A SIMPER analysis was completed for native species only and determined the percentage contribution of each species to the average similarity within and average dissimilarity between treatment groups and vegetation communities. The average within group similarity for all vegetation and treatment groups was very low at 0.56. The highest recorded within group similarity was 0.40 in the No Fire No Neighbour Restored Group (Table 5.19).

Table 5.19 Average similarity within each treatment and vegetation group (natives only) Treatment and vegetation group Average Similarities No fire No neighbour Remnant 0.06 No fire No neighbour Restored 0.40 Fire Neighbour Remnant 0.21 Missing groups = 0

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Pre-treatment species composition There were 21 native and 11 exotic species recorded during the pre-treatment vegetation sampling (Table 5.20). There were no differences in species composition between treatment groups and vegetation communities evident at the pre-treatment stage (Figure 5.22). This is a different result from earlier studies that found significantly more native species in restored vegetation when compared to pasture. These differences are likely the result of the smaller area sampled; in this case 25m² whilst in previous studies quadrats of 1024m² area were sampled. There was no easily distinguishable pattern or similarity between this plot (Figure 5.22) and the MDS plot of the species composition of germinants at week 52 (Figure 5.19).

No germination was recorded in a large number of quadrats, restricting the comparison between MDS plots to a visual comparison. There was no apparent visual similarity between the MDS plot of pre-treatment vegetation and post-treatment germinants. This lack of similarity indicates that the germinants formed a mainly distinct suite of species compared to the pre-existing vegetation composition.

As a measure of the divergence between pre-treatment vegetation and composition of germinants; for pasture 9 species germinated (5 exotic, 55%) from 22 recorded in pre- treatment sampling; for restored vegetation 12 species germinated (6 exotic, 50%) from 29 recorded in pre-treatment sampling; and, for remnants 6 species germinated (1 exotic, 17%, *Cirsium vulgare) from 10 found in pre-treatment sampling. As a group, 27 species germinated (12 exotic) from 40 (67.5%) species recorded in pre-treatment sampling (Table 5.20).

The majority of the exotic species found in pre-treatment sampling were successful germinators in all vegetation types. The exceptions were those with vegetative growth habits such as Pennisetum clandestinum, Phalaris minor, and Paspalum dilatatum (Table 5.20) which had no germinants at all. These species form a major component of the dominant grass sward. Three native species germinated in pasture vegetation only

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(Dichondra repens, Eragrostis leptostachya, and Geranium homaneum), only one of which was found in pasture pre-treatment (Geranium homaneum).

There were 2 natives that successfully germinated in restored vegetation without occurring in pre-treatment sampling: Einadia hastata and Viola hederacea (Table 5.20). Restored vegetation also contained three species (Bothriochloa macra, Ranunculus lappaceus, and Viola hederacea) that had germinated in addition to those in found in pasture.

There were 27 species (19 native) found in pre-treatment sampling that recruited successfully and 13 species (10 native) that did not (Table 5.20, Table 5.21).

There were 14 ‘new’ native species found to have recruited successfully as a result of the treatments (Table 5.21). Half (7) of these ‘new’ species were found in remnant vegetation, and a further 6 (43%) were found in restored vegetation. Only 3 of these ‘new’ species (21%) were found in pasture vegetation.

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Table 5.20 Species recorded in pre-treatment survey and germination success Pre-treatment survey completed during June 2004 (Winter) Successful germination Species Vegetation type P Rs Rem recorded # *Anagallis arvensis P √ √ √ *Apium leptophyllum P √ √ √ Aristida ramosa P Rs Rem Aristida vagans Rs Rem Bothriochloa macra Rs √ Brunoniella australis Rs Rem √ √ Carex inversa Rs √ √ Centella asiatica Rem √ Chloris ventricosa Rs *Cirsium vulgare Rs Rem √ √ √ *Conyza bonariensis Rs √ √ √ Cymbopogon refractus Rem Cynodon dactylon P Rs Danthonia linkii var. linkii P Rs Rem Desmodium varians P Rs √ Dianella revoluta P Rs √ Dichelachne rara Rem Dichondra repens Rem √ Einadia hastata P √ √ √ Eragrostis leptostachya Rs √ Geranium homaneum P √ Glycine tabacina Rs √ √ √ Hypericum gramineum Rs √ √ Lomandra filiformis subsp. filiformis P Rs Rem √ √ Microlaena stipitata var. stipitata P Oplismenus imbecillis P Rs √ *Paspalum dilatatum P Rs *Pennesetum clandestinum P Rs *Phalaris minor P Rs Phyllanthes virgatus P Rs √ Poa labillardierii P Rs Pratia purpurascens P Rs Ranunculus lappaceus Rs √ *Setaria gracilis P Rs √ √ √ *Sida rhombifolia P Rs √ √ √ Solanum pinifolium P Rs √ √ √ *Trifolium repens Rs √ √ √ Themeda australis Rem √ *Verbena rigida P Rs √ √ √ Viola hederacea Rem √ √ ∑ 22 29 10 18 16 20 Key: P=Pasture, Rs=Restored, Rem=Remnant

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Table 5.21 Species not recorded in pre-treatment survey and successfully germinated Species Vegetation type# Asperula conferta Rs Bulbine bulbosa Rs Bursaria spinosa Rem Daucus spp. Rs Dillwynia sieberi Rem Einadia trigonos Rem Hardenbergia violacea Rs Hypoxis hygrometrica Rem Lagenifera stipitata Rem Lotus suaveolens P, Rs Oxalis perennans P, Rs Paspalidium distans Rem Rumex brownii P Wahlenbergia gracilis Rem # P=Pasture, Rs=Restored, Rem=Remnant

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Figure 5.22 Ordination analysis: total pre-treatment species composition Ordination using non-metric multi-dimensional scaling. The symbols represent quadrats in their treatment classifications based on ordination analysis of total species composition. Global R: 0.141; P=0.1%.

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5.4 Discussion

Seedling emergence The most outstanding pattern of seedling emergence and establishment observed over the twelve months of this study was the dominance of seedlings from relatively few exotic species. In all treatments except for the controls, there were approximately four times more exotic species than native species germinants. All native species germinants were herbs or grasses and were recorded in low abundances. No trees and only two shrub species (Bursaria spinosa- found in remnant, and Dillwynia sieberi- found in restored) germinated over the twelve months duration of sampling.

The revegetation program instituted by Greening Australia was designed to enhance the natural recruitment of natives after tree planting, in particular tree canopy species in recognition that this would make a major contribution to the sustainability of the restored grassy woodland. This study has found a distinct lack of germination of tree canopy species in restored vegetation over the period of observation. Either this suggests a failure of the revegetation program to promote a sustainable native woodland; or that time since revegetation has not been sufficient to promote the germination of these species; or, that the treatment and time of study was not favourable for germination and seedling emergence and that the species concerned are the ‘event-dependent’ type.

Species composition of emerging seedlings There were 40 species recorded in the pre-treatment vegetation survey, comprising 29 natives and 11 exotics. Although a comparable species richness was found in the species germinating, the standing vegetation was found to comprise quite a distinct suite of species. This suggests that there appears to be a group of species that act as effective colonisers after disturbance, with a major contribution from exotics. Excluding pasture, the composition of germinants corresponds with over 50% of species recorded in the standing vegetation.

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The abundance of all native germinants except for two (Lagenifera stipitata and Lotus suaveolens) was very low. A lack of rain during the first six months of sampling ensured very low numbers of individuals remained after 12 months.

The low number of native species encouraged to germinate in restored vegetation in addition to those found in pasture suggests that revegetation does not adequately encourage the recruitment of a wide range of species, over the period of this study.

The limited species richness of native germinants and absence of tree species germinants in all vegetation groups supports the hypothesis that seedling emergence and establishment of native species in restored grassy woodlands is episodic, and may rely on a greater amount or better quality of seed to be available for the potential barriers to germination to be overcome (McDougall and Morgan 2005).

The low species richness of germinants may be the result of a combination of factors, including; low rainfall (see Chapter 2) after the treatment and during the sampling period; low numbers of germinable seeds in the soil seed bank, and domination of the remaining soil seed bank by only a few durable species. The episodic nature of recruitment by some species (particulalry Eucalypts) may also have played a role in the low species richness of germinants found in this study. These results confirm conclusions made by other similar studies, such as McDougall and Morgan (2005), Morgan (2001) and Hynes et al (2004), into germination and recruitment of natives after restoration.

The expectations from the investigation included that germination in both treatments would exceed that of controls and that native and exotic species may react differently to the fire and neighbour removal treatments. Native species germinants did show significantly higher numbers at one site only, after fire and after neighbour removal in pasture and restored vegetation. This was also the case for exotic species, which had significantly higher numbers after the fire treatment compared to controls, and after neighbour removal in pasture and restored vegetation when compared to remnants, where they decreased after neighbour removal. Seedling emergence of exotics was were found to respond favourably to all forms of neighbour removal, that is either fire or slashing and contrary to expectation did not vary between treatments.

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Ten native species were recorded as germinants in pasture and, after revegetation, a further 3 species were found to germinate. This small increase in species richness of native germinants does not appear promising for successful restoration especially as some of these species (for example Hypericum gramineum) are known to germinate in disturbed environments (Auld 1992). Consequently, the increase in species richness after restoration found in previous experiments (Chapter 3) does not necessarily reflect convergence of species composition with that of remnants via germination of native species from in situ seed. Over longer timeframes, seed may be transported in by means of a range of mechanisms including avifauna.

Although only 19 species germinated in remnant vegetation, this group comprised quite a different range of species compared to pasture or restored vegetation, and included 13 different species compared to those species that germinated in restored vegetation.

Despite these differences, because the native species richness of germinants was low and dominated by only a few species with high abundance, the species composition of germinants in pasture was indistinguishable from that found in remnant vegetation, irrespective of treatment. Notwithstanding the overall low numbers of native germinants, there is some evidence that some native species in restored vegetation require a fire cue to generate seedling emergence. This is in accordance with other studies that have shown fire cues to be an important part of the recruitment of natives (Morgan, 2001, Lunt 1990).

The differences in the numbers of exotic species germinants after fire were uneven and higher at one site only after fire. These results were counter-intuitive given the predicted outcome of an intolerance of exotic seeds to the fire treatment.

The differences in the numbers of exotic species after neighbour removal treatments were also variable and higher after neighbour removal treatments in pasture and restored vegetation which were both greater than numbers in remnants which decreased after treatment. These results are consistent with the predicted outcome,

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which suggested increased germination of exotics after neighbour removal depending on the mix of species present.

There was no difference found in the numbers of exotic species germinants between pasture and restored vegetation. Revegetation activities had no effect on the numbers of exotics. In fact, after the fire treatment there were increased numbers of exotic germinants. This supports previous evidence that revegetation has not yet had a large impact on reducing the dominance of exotics at these sites. In fact, if exotics continue to recruit as seedlings, the results support a similar conclusion to that made in Chapter 3 of this Thesis, that a mixture of natives and exotics (synthetic vegetation community) will persist through time and that any disturbance involving the removal of vegetation increases the seedling emergence of exotics.

Overall, all vegetation and treatment groups had a similar species composition. This indicates a soil seed bank dominated by exotic species, their germination triggered by fire and/or the removal of neighbours. Other studies, including Morgan (1999), have highlighted the failure of re-introduced species to produce seedlings and attributed the failure to poor seed production, poor conditions for germination of seed, competition from exotics and stress caused by environmental factors.

Exotic species remained dominant in the soil seed bank of pasture, restored and remnant vegetation. These seeds were able to quickly and effectively respond to disturbances including both fire and neighbour removal. These dominant exotics are known as ‘non-specialist’ germinators (Morgan 1998) that take advantage of predictable rainfall seasons and less predictable but common disturbances that characterise urban remnant vegetation. Because there are few natives that occupy the gaps made available during the treatments, exotics were able to fill them without a great deal of competition.

The majority (65%) of the native species present in standing vegetation were observed in low abundance as germinants. Even when native germinants were recorded, often this was only an individual plant. This was in contrast to the abundance of exotic germinants. Despite sampling being limited to a twelve-month period, many native species in the surrounding vegetation were never seen as seedlings. This may reflect

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the infrequent nature of recruitment events experienced by native species (Morgan, 2001) and highlights the need for further development of recruitment management strategies that focus on restored vegetation (Morgan 1999).

Seedling germination and establishment was very low in the control plots in pasture, restored and remnant vegetation. This is typical for undisturbed vegetation (Goldberg and Werner 1983, Lunt 1990) and comparable with results found by Clarke and Davison (1994) where little natural germination of native species was observed in the field in treatments that did not involve addition of seed. In pasture and restored vegetation, the thick layer of extant, mostly exotic, vegetation would not have provided a suitable environment for the germination of plants, particularly native species. Germination of only the most prolific exotic species such as Senecio madagascariensis and Verbena rigida were found in these controls.

Trends in seedling germinants In pasture and restored vegetation, there was no decreasing trend in the number of exotic species germinants after neighbour removal and fire treatments were combined. Although there is some evidence that shows fire and neighbour removal may effectively promote natives in restored vegetation, the results of my study were inconsistent between sites. Because of time constraints, repeated treatments were not applied. The effectiveness of repeated neighbour removal and fire treatments to promote native recruitment and retard exotic seedling emergence was not tested. Results do not discount the potential for repeated fire treatments by land managers and restoration practitioners to direct restored vegetation along a certain successional pathway. Although no treatment in restored vegetation was found to increase the number of native species germinants, these data show that it may be possible to direct succession by applying a combination of neighbour removal and fire treatments at certain times of year to reduce the dominance of exotics and create a more suitable seedbed for natives. Although not tested within this study, modification of exotic species composition over time with repeated spring burns to control exotics may potentially provide for an improved environment within which native species may germinate (Prober et al 2002b).

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The reduced local rainfall may have affected germination results found in this study after the treatments. Rainfall patterns experienced during this period are given in Chapter 2 and show below average rainfall (approximately 20% below average) overall. Prior to the treatment period of June-July 2003 there was a period of extremely low rainfall, however there were several months of above average rainfall surrounding the sampling period including May 2003, and October 2004. These variable rainfall patterns may have led to desiccation of some of the available seeds either held by some species or found in the soil seed bank.

Although no evidence was collected of direct grazing of seedlings, there was some proof (scats) of some browsing by rabbits within the study sites. This may also have affected seedling numbers observed during the sampling period. Studies by others have also shown an active ant population at the study sites. Seed herbivory by ants is common and often reduces the available soil seed bank.

The patterns of seedling emergence observed are evidence that seedling recruitment does play a role in the maintenance of the species composition found in pasture, restored pasture and remnant vegetation. The role of seedling recruitment was found to be dominated by exotics that appear to be exploiting a recruitment niche not dominated by native species and exploiting disturbance of the extant canopy. This study cannot discount episodic fluctuations that may be found in native species recruitment patterns from one year to the next.

Despite recruitment by seedlings playing a small role in the short-term dynamics of restored vegetation, sampling suggests a dominance of the vegetative growth by exotic species. There is however, a longer-term persistence of native populations at the study sites that suggests that native species persist through periods of dominance by exotic species. Perennial native species with long-lived populations, able to reproduce vegetatively, with a low level of annual turnover are more likely to persist in restored vegetation found at the study sites.

One consequence of the low levels of native seedling recruitment found in this study is that any populations that are rare or threatened may become locally extinct due to these infrequent periods of successful recruitment. Some species may disappear, or

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may have already disappeared, due to the ongoing dominance of exotics and the reduced potential for native species recruitment at the study site.

Management considerations of restored vegetation communities must plan for the long-term impact of low levels of native species recruitment. If a restoration target of full re-instatement of a grassy woodland is to be achieved over the longer term, priority needs to be given to the maintenance of the existing natives (promotion or maintenance of tubers, flowering and seed rain) to ensure ongoing persistence of the extant individuals, and the recruitment of these and absent native species. The low level of recruitment of natives shown in this study calls for an on-going program of re-introduction in the restored vegetation in order to enhance local native species diversity.

Once species are missing from the composition of a vegetation community, it becomes an extremely difficult situation to reverse because few native species form large persistent soil seed banks (Lunt 1997b), seedling recruitment is low and difficult to predict (Morgan, 2001), and seedling survival rates can be low (Gilfedder and Kirkpatrick 1993). These factors may explain why attempts to restore grasslands and grassy woodland vegetation have met with great difficulty (McDougall and Morgan 2005 1989, Wilkins et al 2004).

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Chapter 6

Summary – Has revegetation been successful in the restoration of abandoned agricultural land?

Restoration evaluation

The measurement of the success of restoration is burdened with problems such as the wide temporal and spatial variation inherent in natural systems. The: 1. specification of goals; and, 2. measurement of ecosystem attributes such as restoration trajectories, species composition, vegetation structure and ecosystem function are two of the most important parts of defining success of a restoration project (Ehrenfeld, 2000). These identify the parameters of the project and set the measures of success that normally call for resemblance to natural vegetation communities as the end goal (Box 1996, Jackson et al 1995, Chapman and Underwood 2000, Cairns 1993, Hobbs 1993, 1996).

Previous work by Westman (1986a) and Chapman et al (2000) provided potential strategies for conducting an evaluation (outlined in Chapter 1) and drew attention to the need for scientific protocols to be more widely used. Wilkins et al (2004) first proposed a system for the evaluation of restored grassy woodlands. This Thesis has been based on previous work by these authors and builds on this body of work.

There are four possible trajectories of restoration: restoration success where ecosystem variables return to refernce condition, restoration partial success, on trajectory where ecosystem variables have moved away from the degraded condition but not attained a similar value, and partial restoration success, not on trajectory where the ecosystem variable has moved away from the degraded condition, but is on a different trajectory and, restoration failure. The first two options (1. restoration success, and 2. restoration partial success, on trajectory) represent the desirable outcomes for the Greening Australia restoration program.

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Although constrained by sampling design, Wilkins et al (2004) completed a study to determine restoration success of a grassy woodland at similar sites to the ones used in this Thesis with Chapman’s arguments in mind. This Thesis builds on components of the Chapman model and the methodology developed by Wilkins (2001).

Aim The aims of this project were to: 1. further develop the evaluation systems of Westman (1986), Chapman and Underwood (2000) and Wilkins et al (2004) proposed for the assessment of restored ecosystems; and 2. use these developments to evaluate whether the revegetation of agricultural land on the Cumberland Plain, west of Sydney, NSW, has led to the re-establishment of a grassy woodland.

To achieve this aim, sampling of restored, unrestored control and reference vegetation was used to identify trends in the restored community. This system could be able to be used as a general model for evaluation of projects involving ecological restoration.

A series of three field-based studies were designed to test the effectiveness of this methodology and a series of hypotheses was developed to analyse and compare three key ecosystem attributes:

1. species richness, composition and vegetation structure of pasture, restored vegetation, and remnants; 2. the small scale effects of planted tree canopies on species composition; and, 3. the effects of fire and neighbour removal on seedling emergence and establishment in pasture, restored vegetation and remnants.

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Overview of findings In general, tree planting was found to have a positive effect on the native species composition of restored vegetation. However, the results were uneven depending on sampling time. The specific theory that natives are encouraged to return underneath planted tree canopies was not supported and the mechanisms by which revegetation encourage natives to return remain unknown, although are believed to be a generalised effect rather than occurring underneath tree canopies. Exotic species germinants rather than natives were found to respond favourably to ‘one-off’ fire and neighbour removal treatments. Seedling emergence and establishment in restored vegetation was found to be dominated by exotics.

What was the restoration trajectory in species richness, composition and vegetation structure of restored vegetation?

Native species Native species richness in restored vegetation was found to resemble that in remnants, but at the first time of sampling only.

The trajectory of species composition of restored vegetation through time since revegetation from untreated pasture to twelve-year-old revegetation was at a tangent to and not in the direction of remnant vegetation. The species composition of restored vegetation does not resemble, nor does it increase in its resemblance, to remnant vegetation. Only three native species were found to have returned to restored vegetation at levels similar to their abundance in remnants.

Exotic species The proportion of introduced species in restored vegetation remained high, with results from the first comparative study showing a significant reduction after restoration. These results were also inconsistent. They occurred at some sites only and were contradicted by an increase in exotic species richness found in both the first and second studies.

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Vegetation structure Some structural attributes including tree and shrub cover were found to resemble remnants at some sites, however the majority of structural characteristics were found to be well below targets.

Do planted tree canopies reduce exotic ground cover and increase native species abundance? After the first comparative study found an increased native species richness in restored vegetation, an examination was undertaken of whether this was a consequence of the small-scale effects of the planted tree canopy. According to Perkins (1992, 1999) changes in species composition of surrounding vegetation were expected as a result of an increase in shade created by the growth of planted trees which suppress the growth of exotic C3 grasses. The Perkins model asserted that a planted tree canopy would encourage a native species ‘halo’ effect around its canopy. This ‘halo’ effect was tested in the second study (Chapter 4).

The results of this second study indicated that individual planted trees do not affect species composition of vegetation directly beneath the canopy. No trend of increasing natives or decreasing exotics was detected with age of planted tree canopy.

Species composition directly underneath tree canopies remained unchanged following the planting of trees. There was a continued dominance of restored vegetation by exotic species underneath tree canopies. The increased native species richness found in restored vegetation found in the first study must be as a result of processes occurring both under and outside the localised area directly underneath the planted tree canopy. At the scale of individual tree canopies, no evidence was found to support the principle of competitive exclusion as the main driver of changes in species composition.

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Did restoration increase the recruitment of natives and decrease recruitment of exotics? The third study examined the long-term sustainability of the restored vegetation and was an investigation into seedling emergence and establishment patterns in pasture, restored vegetation and remnants.

Observed patterns of seedling emergence suggested that recruitment maintained the dominance of exotic species in restored vegetation. Seedling emergence was dominated by exotics utilising a recruitment niche not used by native species. Clarke (1999) suggests that episodic fluctuations in native species recruitment may play a role in the dynamics of grassy vegetation communities. This temporal variability in native species recruitment may have influenced the results obtained at the study site that showed little native species seedling emergence and a continuing dominance of the seedbank by exotics.

Morgan (1998) has made similar conclusions about episodic periods of native recruitment. He argued that exotic species remain dominant in the soil seed bank of restored vegetation and are able to react quickly and effectively to disturbances. They are known as ‘non-specialist’ germinators. These exotic species are able to take advantage of predictable rainfall seasons and advantage of less predictable but common disturbances that characterise urban remnant vegetation. The findings of my studies confirm the dominance of exotics in restored vegetation and that recruitment of natives is episodic and consistently less successful than recruitment of exotics.

The main canopy trees of CPW are Eucalypt species. The recruitment of Eucalypts was therefore one of the key processes to be reinstated for restoration success to be achieved. No seedling emergence of Eucalypts was found in any vegetation type during the study.

The episodic and infrequent nature of recruitment events experienced by native species (including Eucalyptus species) also highlights the need for active management of recruitment processes of natives in restored vegetation (Morgan 1999, 2001).

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Factors limiting restoration success An overall evaluation of the restoration of the grassy woodland at the study sites would be that it has been a partial success; while many response variables show change from the degraded starting point, reference end-points have not been achieved to date. However, for the very important characteristic of species composition, the development of restored vegetation was not in the trajectory of remnants. If species composition were taken as the most important variable, then the overall evaluation would be ‘partial success, not on trajectory’.

Factors limiting restoration success may include among other things; lack of native species propagules, lack of recruitment opportunities (fire, disturbance), altered abiotic factors such as increased nitrogen (Prober et al 2002b), and altered animal- plant interactions.

Local extinction of populations that are rare or threatened is one consequence of low levels of recruitment. Some species may have already disappeared from Cumberland Plain Woodland due to the ongoing dominance of exotics and the reduced potential for native species recruitment. Prompt conservation-oriented action is required to avoid any species extinctions. Management considerations must include priority for the maintenance of the existing native populations along with the recruitment of missing native species.

Many of the herb and shrub species that occur in temperate woodlands, including CPW, do not have seed stored in soil seed banks (Benson and Howell 1990). Due to the long time period since parent plants existed in the abandoned pastures of the study sites and the resultant scarcity of seeds stored in the soil, any seeds that are in the soil seed bank are likely to be lost due to predation and seed death (Clarke 1999).

Recruitment of a diverse understorey following tree planting needs additional input. If improvement in the diversity of native species is to occur at these restoration sites, further efforts are needed for success, particularly in terms of importing additional genetic material either via seed or established seedling, creating a variety of recruitment opportunities and restoring animal-plant interactions.

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The general results found in studies in this Thesis contrast with other studies including Wilkins et al (2004) which concluded steady-state model of vegetation dynamics rather than direct successional existed at similar sites. My studies, even though results were somewhat inconsistent, demonstrate some positive changes to restored vegetation.

In summary, the vegetation at the study site was found to dominated by vegetative growth and germination of exotics. Several key markers for restoration success including the recruitment of Eucalypts and improvement in the diversity of the understorey species vegetation to resemble those in remnants were not achieved by tree planting.

This evaluation of revegetation activities was conducted on one of the best resourced restoration programs in Australia. Lesser resourced programs are likely to be less effective in terms of achieving their stated goals.

State and transition model for restored grassy woodlands

(Case study: CPW) In order to assist with the development of a comprehensive restoration plan for CPW, a state and transition model has been developed for vegetation that has been subject to revegetation by Greening Australia at the study sites in western Sydney.

The model (Figure 6.1) is based on knowledge obtained from the experiments contained within this Thesis, knowledge of the CPW ecosystem from general observations and discussions with other researchers at the University of Western Sydney and their unpublished data. (pers.comm. de Barse 2006, Watson 2006, Morris 2006).

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State & transition model for the restoration of Cumberland Plain Woodland

S4 Remnant S3 Pasture + plantings T3 B4 + returnees B3 B2 T2 B1

S2 Pasture + plantings

T1 T4 clearing

S1 Pasture

Figure 6.1 State and transition model for CPW restoration. States include: abandoned pasture, revegetated land and remnant vegetation. See text below for full descriptions of states and transitions.

Vegetation states State 1 Pasture: A vegetation community comprising a mixture of native and exotic species. • Dominated by exotics in terms of richness, abundance and cover; • Structure of ground layer is dominated by a dense canopy of exotic grasses with no shrubs or trees; • Soil seed bank dominated by annuals.

State 2 Pasture plus plantings Pasture plus plantings of over storey trees and shrubs. A vegetation community comprising a mixture of native and exotic species: • Dominated by exotics in terms of richness and abundance; • With a soil seed bank dominated by exotic annuals and depleted of natives; • With a simple structure dominated by planted tree canopies; • With a reduced probability of fire.

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State 3 Pasture plus plantings plus returned native species Pasture plus plantings of over storey trees and shrubs plus approximately 24 species which ‘returned’ to the revegetated area.

A vegetation community comprising a mixture of native and exotic species comprising:

• 3 species returned in abundances similar to that found in remnants; • Species richness and abundance dominated by exotics; • A soil seed bank dominated by annual exotics; • A simple structure dominated by planted tree canopies with a dense understorey of exotics.

State 4 Remnant vegetation Grassy woodland vegetation with a complex, heterogenous cover of shrubs, ground covers and grasses. This state may have several possible sub-states based on time since fire & other factors (Watson 2004). Successful natural recruitment of tree species is variable from year to year and is at least partially dependent on fire timing, intensity, and rainfall.

Transition between states Transition 1 Revegetation of canopy species involves the mechanical planting of canopy trees and select shrub species.

• Removal of grazing pressure is not sufficient to encourage natural regeneration of woodland; Barriers

• Restoration requires amelioration of soil characteristics including both chemical and physical properties, removing compaction, removing excess nutrients, re-introduction of any natural symbiotic relationships between plants, animals and fungi;

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• Control of exotics is also required in the short to medium term in order to maintain the health and condition of the planted trees and shrubs.

Transition 2 This transition involves the re-introduction of native species by unknown means. The Tree Canopy Halo study (Chapter 4) shows that it is achieved independtly of the planted tree canopy. Possible (untested) factors which have encouraged the return of some native species include:

• Restoration of soil characteristics;

• Restoration of favourable habitat;

• Restoration of propagule availability to allow for the natural re-introduction of native species previously removed from agricultural vegetation.

Transition 3 The re-introduction of the full complement of native species found in remnants. Comprehensive restoration of all ecosystem characteristics to those previously existing prior to disturbance to allow for the natural progression of the ecosystem along its natural successional pathway. This transition is yet to be observed in CPW.

Possible barriers to this transition include B1. lack of propagules of natives in S2; B2. lack of recruitment opportunities, even if propagules were present; B3. possible elevated nitrate levels post-establishment leading to exotic dominance; and, B4. other unknown factors include disturbance to mycorrhizal fungi, animal/plant interactions, pollination or seed dispersal mechanisms.

Transition 4 Clearing of native vegetation The removal of a part of the full complement of native species and ecosystem characteristics found in remnant vegetation. Comprehensive removal or destruction of key ecosystem characteristics for agriculture, farming, timber production, forestry or other development.

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The key attributes of this transition include:

• Removal or replacement of most of the above-ground vegetation; • Disturbed soil profiles; • Removal or degradation of other unknown ecosystem attributes/structures/species assemblages including mycorrhizal fungi, animal/plant interactions, pollination or seed dispersal mechanisms.

This state and transition model for CPW restoration via revegetation suggests a range of possible remnant (goal) states may occur on a site within the possible geographic variables of landform, topography, soils and microclimate previously found on the Cumberland Plain and supporting CPW.

State and transition models are considered to be useful for developing restoration strategies (Yates and Hobbs 1997). The model proposed for CPW (described above) may be considered as the first step in progressing broad strategies for restoration of CPW and may even be used by land managers as a decision making tool when considering maintenance or management options such as burning. The different states within the model (Stage 3 Figure 6.1) described above may even be used as staged goals to judge to success of future restoration efforts.

Implications for restoration programs The restoration evaluation methodology developed here will be useful to an industry that involves tree planting, landcare, revegetation and bush regeneration. Revegetation through tree planting is the most strongly supported method of land restoration in Australia, the largest projects including the Natural Heritage Trust, Landcare, One Billion Trees, and Save the Bush. These projects have promoted a large number of planting and fencing projects aimed at restoring native vegetation on farms and other privately owned lands. Public authorities and forestry and mining companies have also committed significant resources to revegetation activities. The annual national commitment to revegetation adds up to millions of dollars with little formal scientific evaluation. This study has provided some of the first complete empirical data upon

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which to base broader policy decisions regarding the clearing and/or restoration of native vegetation in grassy woodlands.

The methodology developed within this Thesis will complement guidelines provided by government and other sources that advise on practical aspects of revegetation and will be one of the few which examine the success of revegetation in ecological terms and are founded on scientific study.

This methodology will redress the current lack of systems able to scientifically evaluate the success of restoration projects. Restoration practitioners will be able to use it to assess the ecological success of projects, funding bodies will be able to use it to determine the future funding of projects.

This study has further developed and expanded the application of a methodology available for restoration evaluation. The methodology has been tested on an important, formerly widespread vegetation type heavily impacted on since European settlement.

The findings of these studies will also be able to assist governments and lawmakers wishing to control environmental harm caused by the clearing of vegetation in the development of policy and new legislation. In NSW, for example, the Native Vegetation Act (2003) aimed to regulate clearing and plan revegetation in a manner mindful of regional goals for conservation and sustainable production. The results of these studies will guide appropriately worded policy and law mindful of the success rates and timeframes involved in restoration and potential for restoration failure.

Studies that evaluate restoration, including this one, suggest that changes to species composition are slow to occur or may not fully develop. If restoration is held to be a possible answer to degradation of grassy woodland systems, the long time frames and risks of restoration failure should be acknowledged and accommodated in planning.

It is also important to recognise that even small positive changes to the environment as a result of restoration should be viewed as progress, particularly given the disturbance history of the study sites of over 200 years and the 12 years of restoration

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completed by Greening Australia. As acknowledged in the initial planning stages of the restoration program, an ongoing commitment to the program is essential if further restoration progress is to be made, particularly in terms of understorey species diversity.

Despite the apparently slow rates of success shown by this study, the restoration of ecosystems has been made compulsory by regulation in NSW including the Native Vegetation Act 2003. Similar legislation exists in Queensland and Victoria. The results of this study support previous suggestions by others including Zedler and Callaway (1999) and Prober (2005), regarding regulations governing the removal or destruction of native vegetation. That is, prevention of the clearing of native vegetation should be the focus, rather than a reliance on restoration.

Where development approvals for destruction of native vegetation are given on the basis that restorative plantings are undertaken, it should be acknowledged that even after 12 years, restored vegetation does not resemble remnants. The protection of existing remnants may be a more cost-effective method of off-setting the negative impacts of vegetation removal than the alternative cost in time and expense of restoration planting.

Regulations need to recognise that long-term ecological monitoring is required for all large-scale restoration projects and that due to the difficult and complex nature of restoration, a high value needs to be placed on the retention of existing native vegetation prior to approvals being issued for clearing.

Restorationists need to focus on finding practical solutions to barriers of restoration success. Recruitment barriers such as the lack of native species propagules and provision of recruitment opportunities for native species are examples of barriers that may have practical solutions. Further investigation into the effectiveness of fire as a tool for the provision of recruitment opportunities is required. Broad-scale applications of fire and additional seed inputs may be a practical example of how to overcome some of these barriers. Nutrient reduction may be required.

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Effectiveness and potential use of the evaluation methodology I believe the evaluation methodology used here is a simple and straight forward system, which may be used by restoration practitioners Australia-wide. The methodology may be applied by any person, provided the sampling is being undertaken by a person with a good level of knowledge of the flora of the ecosystem under examination, and the data analysis performed by someone with experience in statistical software packages. It may be possible for the analysis and interpretation to be contracted out for completion by an external party. Interpretation of the results requires the specialist knowledge which many restoration practitioners already possess. The methodology involved sampling 100 quadrats, most of which consumed an entire working day for two people. Analysis of data and interpretation of results took a similar period to complete. Considering this is one of the largest restoration projects you might find in Australia, application and use of the methodology in other locations for other projects would involve relatively lesser amounts of time to complete.

Without effective ecological audits, it is not possible to determine whether best value is derived from the monetary and human contributions made during restoration programs. Until now there has been a lack of ecological audit methodologies available for the evaluation of restoration projects. This Thesis has successfully further developed a system for evaluating large restoration programs. This methodology could be made available to restoration practitioners and funding bodies and used as a tool for better restoration planning, improve the long-term ecological outcome of projects and help identify restoration barriers.

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Appendix 3.A Abundance of vascular plant species and their percentage contribution to dissimilarities between four vegetation communities Time of sampling 1 mean frequency score, se % Contribution to Dissimilarity (Top 50% Cumulative Contribution) Past. Past. Past. Rev Rev Rev Yng Yng Old cf. cf. cf. cf. cf. cf. Rev Rev Old Remt Rev Remt Remt Young Old SPECIES Pasture Rev Young Rev Old Remnant

Sinopteridaceae Cheilanthes seiberi 0.00 0.00 0.00 0.00 0.00 0.00 1.58 0.31

Acanthaceae Brunoniella 1.33 0.26 0.33 0.00 0.17 0.00 1.92 0.42 2.60 2.64 2.73 australis Apiaceae a Apium leptophyllum 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 Centella asiatica 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 a Foeniculum vulgare 0.00 0.00 0.33 0.00 0.00 0.00 0.00 0.00 a Hydrocotyl 0.50 0.13 0.33 0.00 0.17 0.00 0.00 0.00 bonariensis Asclepiadaceae a Araujia hortorum 0.00 0.00 0.00 0.00 0.00 0.00 0.42 0.16 a Gomphocarpus 0.17 0.00 0.00 0.00 0.17 0.00 0.08 0.06 fruiticosus Asteraceae a Bidens pilosa 0.00 0.00 0.17 0.00 0.67 0.15 0.42 0.16 a Carthamus lanatus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.17 a Cirsium vulgare 1.00 0.16 2.00 0.37 1.83 0.30 0.00 0.00 1.43 1.38 1.42 a Chondrilla juncea 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 a Conyza albida 0.33 0.00 0.67 0.00 0.83 0.30 0.25 0.11 a Conyza bonariensis 0.33 0.00 0.00 0.00 0.50 0.13 0.00 0.00 Cymbonatus 0.00 0.00 0.00 0.00 0.83 0.00 0.00 0.00 lawsonianus a Euchiton 0.00 0.00 0.00 0.00 0.17 0.00 0.08 0.06 americanum Euchiton 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.06 gymnocephela a Facelis retusa 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 a Gnaphalium 0.00 0.00 0.00 0.00 0.67 0.00 0.00 0.00 pensylvanicum a Hypochoeris 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 microcephela var. albiflora a Hypochoeris 0.00 0.00 0.33 0.00 1.33 0.75 0.00 0.00 1.24 radicata a Hypochoeris spp 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Ozothamnus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.11 diosmifolium a Phytolacca 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 octandra Scaevola albida 0.00 0.00 0.00 0.00 0.00 0.00 0.33 0.17 a Senecio albida 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Senecio hispidulus 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.06 a Senecio 2.00 0.61 0.67 0.00 2.17 0.60 1.58 0.23 1.59 1.58 1.34 1.54 1.30 1.38 madagascariensis Senecio 0.00 0.00 0.17 0.00 0.00 0.00 0.75 0.27 quadridentatus

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mean frequency score, se % Contribution to Dissimilarity

(Top 50% Cumulative Contribution) Pasture Pasture Pasture Rev Rev Rev Young Young Old cf. cf. cf. cf. cf. cf. SPECIES Pasture Rev Young Rev Old Remnant Rev Rev Old Remnt Rev Remnt Remnt Young Old a Sonchus oleraceus 0.33 0.00 0.33 0.00 0.83 0.15 0.00 0.00 a Taraxicum 0.17 0.00 0.00 0.00 0.33 0.00 0.00 0.00 officinale a Tragapogon 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 porrifolius Vittadinia pustulata 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.06 Bignoniaceae a Heliotropium 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 europaeum Pandorea 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 pandorana Casuarinaceae c Casuarina 0.00 0.00 0.83 0.00 0.00 0.00 0.00 0.00 cunninghamiana Casuarina distyla 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Chenopodiaceae Einadia hastata 0.83 0.16 0.33 0.00 0.17 0.00 0.00 0.00 Einadia 0.17 0.00 0.00 0.00 0.33 0.00 0.00 0.00 polygonoides Einadia trigonos 0.67 0.15 0.50 0.00 0.50 0.13 0.00 0.00 Convolvulaceae Dichondra repens 0.00 0.00 0.00 0.00 0.83 0.39 0.00 0.00 Cuppressaceae Callitris 0.00 0.00 0.00 0.00 0.00 0.00 0.42 0.10 rhomboidea Dilleniaceae Hibbertia linearis 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.06 Phyllanthes 1.00 0.00 1.00 0.00 0.67 0.26 0.00 0.00 virgatus Poranthera 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 microphylla Fabaceae b Acacia falcata 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 b Acacia implexa 0.00 0.00 2.17 0.40 0.67 0.15 0.50 0.17 1.00 1.42 1.55 b Acacia longifolia 0.17 0.00 0.67 0.00 0.33 0.00 0.00 0.00 1.88 ssp. longifolia b Acacia 0.00 0.00 1.50 0.30 3.00 0.61 0.25 0.11 1.38 2.13 1.48 1.15 1.83 parramattensis Bossiaea prostrata 0.00 0.00 0.00 0.00 0.17 0.00 1.00 0.36 Daviesia ulicifolia 0.00 0.00 0.00 0.00 0.00 0.00 0.92 0.18 Desmodium 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 rhytidophyllum Desmodium varians 1.83 0.39 1.50 0.26 1.17 0.39 0.17 0.11 1.54 1.68 1.21 1.48 1.21 c Dillwynia sieberi 0.00 0.00 0.50 0.00 0.50 0.00 0.83 0.20 1.26 1.21 1.28 Glycine clandestina 0.17 0.00 0.83 0.30 0.50 0.13 0.83 0.20 0.95 1.07 Glycine 1.00 0.32 0.83 0.30 0.83 0.16 0.00 0.00 microphylla Glycine spp. A 0.50 0.13 0.00 0.00 0.17 0.00 0.00 0.00 Glycine tabacina 3.17 0.70 3.00 0.75 3.17 0.31 0.50 0.22 2.22 1.79 1.58 2.00 1.75 1.19 c Hardenbergia 0.00 0.00 0.67 0.00 0.50 0.00 1.50 0.45 violaceae

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mean frequency score, se % Contribution to Dissimilarity (Top 50% Cumulative Contribution) Pasture Pasture Pasture Rev Rev Rev Young Young Old SPECIES cf. cf. cf. cf. cf. cf. Pastur Rev Young Rev Old Remnant Rev Rev Old Remnt Rev Remnt Remnt e Young Old Oxylobium 0.00 0.00 0.00 0.00 0.0 0.00 0.08 0.06 scandens 0 Pultenaea 0.17 0.00 0.00 0.00 0.0 0.00 0.75 0.19 microphylla 0 Pultenaea 0.00 0.00 0.00 0.00 0.0 0.00 0.75 0.21 parviflora 0 Pultenaea spp. 0.00 0.00 0.00 0.00 0.1 0.00 0.00 0.00 7 a Trifolium repens 0.50 0.00 0.17 0.00 0.5 0.00 0.00 0.00 0 Unknown pea 0.00 0.00 0.00 0.00 0.0 0.00 0.08 0.06 0 a Vicia sativa ssp. 0.00 0.00 0.17 0.00 0.1 0.00 0.00 0.00 angustifolia 7 Gentianaceae a Centaurium 0.17 0.00 0.00 0.00 0.0 0.00 0.00 0.00 asiaticum 0 a Centaurium 0.00 0.00 0.00 0.00 0.8 0.00 0.00 0.00 tenuiflorum 3 Geraniaceae Geranium 1.83 0.15 0.00 0.00 1.0 0.26 0.08 0.06 1.39 1.44 homeanum 0 Geranium solanderi 0.33 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0 Goodeniaceae Goodenia 0.00 0.00 0.00 0.00 0.0 0.00 0.08 0.06 hederacea 0 Hypericaceae Hypericum 1.00 0.26 1.33 0.45 1.3 0.26 0.50 0.17 1.34 1.47 1.22 1.14 gramineum 3 Lamiaceae Mentha dimenica 0.17 0.00 0.00 0.00 0.0 0.00 0.08 0.06 0 Lauraceae a Cinnamomum 0.00 0.00 0.00 0.00 0.1 0.00 0.00 0.00 camphora 7 Lobeliaceae Pratia 0.33 0.00 0.50 0.00 0.0 0.00 0.17 0.11 purpurescens 0 Malaceae a Pyrocantha 0.00 0.00 0.00 0.00 0.3 0.00 0.00 0.00 fortuneana 3 Malvaceae a Malva parviflora 1.67 0.41 0.67 0.15 0.6 0.00 0.00 0.00 1.36 1.39 1.33 7 a Sida corrugata 0.17 0.00 0.00 0.00 0.0 0.00 0.00 0.00 0 a Sida rhombifolia 3.67 0.42 3.50 0.76 3.6 0.20 0.00 0.00 1.33 1.21 1.38 1.45 1.47 1.56 7

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mean frequency score, se % Contribution to Dissimilarity (Top 50% Cumulative Contribution) Pasture Pasture Pasture Rev Rev Rev Young Young Old cf. cf. cf. cf. cf. cf. SPECIES Pastur Rev Rev Remnant Rev Rev Old Remna Rev Remna Remn e Youn Old Young nt Old nt ant g Myoporaceae Eremophila debilis 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.17 Myrtaceae c Angophora costata 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 c Angophora 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 floribunda b Corymbia maculata 0.17 0.00 1.33 0.54 0.00 0.00 0.00 0.00 1.21 1.45 1.22 1.21 1.48 c Eucalyptus 0.00 0.00 1.00 0.00 0.17 0.00 0.08 0.06 eugenioides b Eucalyptus fibrosa 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 b Eucalyptus 0.00 0.00 0.83 0.13 0.67 0.26 1.75 0.25 1.67 1.26 1.29 moluccana c Eucalyptus 0.00 0.00 0.83 0.13 0.00 0.00 1.08 0.29 tereticornis c Leptospermum 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 polygalifolium b Melaleuca 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 lineariifolia Oleaceae a Olea europaea ssp. 0.67 0.15 0.50 0.13 2.83 0.47 0.58 0.17 1.50 1.69 1.34 1.61 1.75 africana Oxalidaceae a Oxalis corniculata 1.50 0.13 0.00 0.00 0.00 0.00 0.00 0.00 1.31 1.31 Oxalis perennans 0.17 0.00 0.67 0.26 1.50 0.52 0.00 0.00 1.27 1.04 1.42 a Oxalis pes-caprae 1.17 0.39 0.50 0.00 0.33 0.00 0.00 0.00 Phytolaccaceae a Picris echiodes 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 Pittosporaceae b Bursaria spinosa 0.00 0.00 0.83 0.30 1.17 0.30 2.08 0.25 2.01 1.45 1.56 Plantaginaceae Plantago debilis 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 a Plantago lanceolata 1.67 0.41 1.67 0.32 1.33 0.49 0.33 0.12 1.72 1.35 1.61 1.56 a Plantago major 0.83 0.13 0.00 0.00 0.00 0.00 0.00 0.00 a Plantago spp. 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 Polygonaceae a Persicaria 0.00 0.00 0.17 0.00 0.33 0.00 0.00 0.00 decipiens Rumex brownii 1.17 0.16 1.33 0.15 0.33 0.00 0.00 0.00 0.93 a Rumex spp. 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 Primulaceae a Anagallis arvensis 0.50 0.13 0.17 0.00 1.33 0.39 0.00 0.00 Proteaceae a Grevillea robusta 0.00 0.00 0.17 0.00 0.17 0.00 0.08 0.06 Ranunculaceae Clematis 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.06 glycinoides Ranunculus 0.67 0.26 0.00 0.00 0.33 0.00 0.00 0.00 lappaceus Rosaceae a Rubus fruiticosus 0.17 0.00 0.00 0.00 1.00 0.00 0.08 0.06

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mean frequency score, se % Contribution to Dissimilarity (Top 50% Cumulative Contribution) Pasture Pasture Pasture Rev Rev Rev Young Young Old cf. cf. cf. cf. cf. cf. Rev Rev Old Remnt Rev Remnt Remnt Young Old SPECIES Pasture Rev Young Rev Old Remnant a Rubus fruiticosus 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 (small) Rubiaceae Asperula conferta 1.17 0.13 0.33 0.00 0.67 0.15 0.42 0.17 1.57 1.37 1.25 Opercularia 0.17 0.00 0.00 0.00 0.00 0.00 1.58 0.19 diphylla a Richardia 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 brasiliensis a Richardia stellaris 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 Sapindaceae b Dodonaea viscosa 0.00 0.00 0.50 0.00 0.33 0.00 0.58 0.22 ssp. cuneata Solanaceae a Cestrum parqui 0.00 0.00 0.50 0.13 1.00 0.00 0.00 0.00 Solanum brownii 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 a Solanum nigrum 0.17 0.00 0.33 0.00 0.17 0.00 0.00 0.00 a Solanum pungetium 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.00 Stackhousiaceae Stackhousia 0.67 0.00 0.50 0.00 0.33 0.00 0.00 0.00 viminea Thymelaeaceae Pimelea spp. 0.00 0.00 0.33 0.00 0.00 0.00 0.00 0.00 Verbenaceae a Lantana camara 0.00 0.00 0.17 0.00 0.33 0.00 0.00 0.00 a Verbena 3.50 0.34 3.17 0.79 2.00 0.52 0.58 0.15 1.55 1.92 2.49 1.75 1.78 1.32 bonariensis a Verbena officinalis 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Verbena rigida 2.17 0.75 2.00 0.26 1.50 0.45 0.00 0.00 2.27 2.19 1.79 1.57 1.36 1.17 Violaceae Viola hederacea 0.83 0.15 2.17 0.84 1.50 0.52 0.33 0.17 1.76 1.07 2.22 1.71 1.91 2.22

Antheriaceae Arthropodium 0.00 0.00 0.00 0.00 0.00 0.00 0.42 0.16 1.10 1.14 milleflorum Arthropodium 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.11 minus Tricoryne elatior 0.50 0.00 0.67 0.00 0.00 0.00 1.08 0.32 0.96 Asparagaceae a Myrsiphyllum 0.00 0.00 0.33 0.00 0.00 0.00 0.00 0.00 1.39 1.19 1.36 asparagoides a Protasparagus 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 aethiopicus Campanulaceae

220

mean frequency score, % Contribution to se Dissimilarity (Top 50% Cumulative Contribution) Pastur Pastur Past Rev Rev Rev e e ure You You Old ng ng cf. cf. cf. cf. cf. cf. Rev Rev Rem Rev Rem Re Youn Old nt Old nt mnt g SPECIES Pasture Rev Rev Old Remnant Young

Wahlenbergia 0.17 0.00 0.00 0.0 0.00 0.00 0.25 0.1 communis 0 1 Wahlenbergia 0.00 0.00 0.33 0.0 0.00 0.00 0.17 0.1 gracilis 0 1 Cyperaceae Bolboschoenus 0.33 0.00 0.00 0.0 0.00 0.00 0.00 0.0 caldwellii 0 0 Capillipedium 0.00 0.00 0.00 0.0 0.00 0.00 0.42 0.2 parviflorum 0 4 Carex inversa 3.50 0.92 3.17 0.6 3.50 0.60 0.17 0.0 1.98 1.94 1.79 1.29 1.78 1.71 0 6 Carex 0.00 0.00 0.00 0.0 0.00 0.00 0.42 0.1 longebrachiata 0 6 a Cyperus 0.00 0.00 0.33 0.0 0.00 0.00 0.00 0.0 exaltatus 0 0 Cyperus gracilis 0.00 0.00 1.00 0.3 0.83 0.39 0.00 0.0 2 0 a Cyperus 0.33 0.00 0.00 0.0 0.00 0.00 0.00 0.0 rotundus 0 0 Cyperus spp. 0.00 0.00 0.17 0.0 0.00 0.00 0.00 0.0 (big) 0 0 Fimbristylis 0.00 0.00 0.00 0.0 0.17 0.00 0.00 0.0 dichotoma 0 0 Lepidosperma 0.00 0.00 0.00 0.0 0.00 0.00 0.17 0.1 concavum 0 1 Hypoxidaceae Hypoxis 0.00 0.00 0.17 0.0 0.00 0.00 0.00 0.0 hygrometrica 0 0 Juncaceae a Juncus acutus 0.00 0.00 0.00 0.0 0.33 0.00 0.00 0.0 0 0 Juncus usitatus 1.00 0.45 1.00 0.5 0.50 0.13 0.00 0.0 1.21 2 0 Lomandraceae Lomandra brevis 0.00 0.00 0.00 0.0 0.33 0.00 0.00 0.0 0 0 Lomandra 0.50 0.13 1.17 0.6 0.33 0.00 1.42 0.3 1.27 2.80 1.26 2.25 2.52 filiformis ssp. 5 3 filiformis Lomandra 0.00 0.00 0.00 0.0 0.00 0.00 0.17 0.0 1.10 gracilis 0 6 Lomandra 0.67 0.00 0.67 0.2 0.50 0.13 0.00 0.0 longifolia 6 0 Lomandra 0.00 0.00 0.00 0.0 0.00 0.00 0.08 0.0 micrantha 0 6 Lomandra 0.00 0.00 0.50 0.0 0.00 0.00 2.00 0.2 multiflora 0 4 Phormiaceae Dianella 0.83 0.13 0.50 0.0 0.50 0.13 1.00 0.2

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caerulea ssp. 0 3 caerulea Dianella 0.33 0.00 0.33 0.0 0.33 0.00 1.75 0.3 caerulea ssp. 0 0 revoluta Dianella 0.50 0.13 0.33 0.0 0.17 0.00 0.42 0.1 longifolia var. 0 2 longifolia Poaceae Aristida ramosa 2.00 0.68 1.17 0.6 2.50 0.54 0.92 0.1 1.81 2.31 2.88 2.15 2.74 2.00 5 8 Aristida vagans 0.00 0.00 0.33 0.0 0.00 0.00 0.00 0.0 0 0 Austrodanthonia 0.00 0.00 0.00 0.0 0.00 0.00 0.08 0.0 fulva 0 6

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Time of sampling 2 mean frequency score, % Contribution to se Dissimilarity (Top 50% Cumulative Contribution) Pasture Pasture Rev Pasture Rev Rev Old Young Young cf. cf. cf. cf. cf. cf. Rev Rev Rev Remnant Remnant Remnant Young Old Old Species Pasture RevegYoung Reveg Remnant Old Ferns Sinopteridaceae Cheilanthes 0.00 0.00 0.00 0.00 0.00 0.00 3.00 0.15 sieberi Dicotyledons Acanthaceae Brunoniella 0.00 0.00 0.50 0.08 1.30 0.10 5.69 0.07 australis Amaranthaceae a Alternanthera 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 nodiflora a Amaranthus 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 viridis Amygdalaceae a Prunus spp. 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 Apiaceae a Apium 0.00 0.00 1.58 0.13 2.41 0.17 0.00 0.00 1.8 1.25 1.31 0.94 leptophyllum Centella asiatica 0.00 0.00 0.00 0.00 0.00 0.00 1.06 0.09 a Ciclospermum 0.17 0.03 0.08 0.03 0.01 0.00 0.19 0.05 leptophyllum Daucus 0.25 0.08 0.08 0.03 0.09 0.02 0.00 0.00 glochidiatus a Foeniculum 0.00 0.00 0.83 0.17 0.95 0.14 0.06 0.02 1.02 vulgare Hydrocotyl spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.03 a Hydrocotyl 0.00 0.00 0.17 0.05 0.19 0.04 0.00 0.00 bonariensis Apocynaceae a Vinca major 0.00 0.00 0.08 0.03 0.09 0.02 4.88 0.09 Asclepiadaceae a Araujia hortorum 0.00 0.00 0.33 0.04 1.03 0.08 0.13 0.02 0.85 a Gomphocarpus 0.00 0.00 0.75 0.12 1.00 0.10 0.00 0.00 fruit Asparagaceae a Myrsiphyllum 0.58 0.13 0.75 0.10 0.83 0.08 0.81 0.06 0.85 0.89 asparagoides Asteraceae a Artemisia verlosa 0.00 0.00 0.25 0.08 0.28 0.06 0.00 0.00 a Aster nova-belgi 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 a Bidens pilosa 0.08 0.03 1.17 0.13 1.71 0.11 0.25 0.04 0.93 Calotis lappaceus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.04 a Carthamus lautus 0.00 0.00 0.00 0.00 0.33 0.08 0.00 0.00

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a Cirsium vulgare 0.58 0.12 3.83 0.14 4.93 0.17 2.25 0.10 1.86 1.33 1.39 1.06 1.15 a Chondrilla 0.00 0.00 0.08 0.03 0.09 0.02 0.06 0.02 juncea a Conyza albida 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 a Conyza 0.33 0.07 1.75 0.11 3.67 0.16 1.31 0.06 1.61 1.14 1.14 1.07 1.14 1.11 bonariensis Cymbonatus 0.00 0.00 0.33 0.07 0.37 0.05 0.38 0.07 lawsonianus a Euchiton 0.25 0.08 0.17 0.03 0.18 0.03 0.31 0.05 americanum a Euchiton 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 gymnocephela Euchiton 0.08 0.03 0.25 0.05 0.36 0.05 1.25 0.10 sphericum a Facelis retusa 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.06 a Gnaphalium 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 americanum a Gnaphalium 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 pensylvanicum a Hypochoeris 0.17 0.05 0.58 0.07 0.48 0.04 1.44 0.08 radicata a Hypochoeris 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 albida a Hypochoeris 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 microcephela var. albiflora a Hypochoeris spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Lagenifera 0.00 0.00 0.67 0.09 0.74 0.08 1.31 0.14 0.83 stipitata c Ozothamnus 0.00 0.00 0.08 0.03 0.01 0.00 0.00 0.00 diosmifolium Ozothamnus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.03 diosmifolium a Phytolacca 0.00 0.00 0.17 0.05 0.19 0.04 0.00 0.00 octandra Podolepis 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 jaceoides Scaevola 0.00 0.00 0.00 0.00 0.00 0.00 0.63 0.11 albiflora Senecio 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.02 linearifolius a Senecio 2.92 0.18 2.00 0.19 3.55 0.15 3.50 0.15 1.19 1.08 1.15 madagascariensis Senecio 0.67 0.14 1.50 0.15 1.91 0.10 1.38 0.14 1.3 1.23 1.09 1.47 1.08 1.01 pteropheros Senecio 0.08 0.03 0.50 0.08 0.30 0.03 0.25 0.06 1.1 1 0.99 quadridentatus Senecio spp. 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 Senecio 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 hispidulus Sigesbeckia 0.17 0.05 1.00 0.20 0.14 0.02 0.81 0.09 1.31 1.65 1.25 2.43 1.33 0.96 orientalis Solenogyne 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.05 bellioides a Sonchus 0.33 0.06 1.08 0.11 1.36 0.08 0.19 0.04 oleraceus a Tagetes erecta 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Vernonia spp. 0.00 0.00 0.96 0.14 0.11 0.02 0.25 0.06 1.39 1.33 1.17 1.67 1.24 1.16 Vittadinia 0.00 0.00 0.92 0.19 0.13 0.02 0.06 0.02 1.31 1.28 1.18 1.51 1.22 cuneata

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Bignoniaceae a Heliotropium 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 europaeum Pandorea 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 pandorana Brassicaceae a Brassica juncea 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 Cactaceae a Opuntia stricta 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 var. stricta Caryophyllaceae a Portulaca 0.00 0.00 0.08 0.03 0.09 0.02 2.44 0.16 oleraceae Spergula arvensis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1 0.93 Casuarinaceae Allocasuarina 0.00 0.00 0.00 0.00 0.08 0.02 0.06 0.02 torulosa c Allocasuarina 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 torulosa c Casuarina glauca 0.00 0.00 0.17 0.05 0.19 0.04 0.00 0.00 Casuarina 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 cunninghamiana Casuarina distyla 0.00 0.00 0.00 0.00 0.42 0.07 0.00 0.00 Chenopodiaceae Einadia hastata 0.00 0.00 1.17 0.08 2.36 0.19 0.63 0.06 1.44 0.96 1.05 1.04 1 Einadia nutans 0.75 0.16 0.33 0.06 0.70 0.09 0.00 0.00 Einadia trigonos 0.50 0.10 0.50 0.07 0.64 0.07 0.19 0.03 Cuppressaceae Callitris 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.06 rhomboidea Dilleniaceae Hibbertia dentata 0.17 0.05 0.00 0.00 0.00 0.00 0.00 0.00 Hibbertia linearis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Phyllanthes 0.00 0.00 0.00 0.00 0.00 0.00 0.56 0.09 1.25 1.21 1.01 1.16 similis Phyllanthes 1.00 0.13 0.67 0.11 1.16 0.10 1.94 0.10 virgatus Poranthera 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 microphylla Droseraceae Drosera peltata 0.00 0.00 0.50 0.13 0.07 0.01 0.06 0.02 Epacridaceae Astraloma 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.03 humifusum Leucopogon 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 juniperinus Euphorbiaceae Chamaesyce 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 dallachyana Fabaceae Acacia falcata 0.00 0.00 0.33 0.06 0.29 0.04 0.50 0.07 c Acacia falcata 0.00 0.00 0.17 0.05 0.35 0.05 0.00 0.00 c Acacia implexa 0.00 0.00 0.92 0.12 1.85 0.11 0.00 0.00 Acacia implexa 0.00 0.00 0.17 0.05 0.69 0.09 0.38 0.04

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Acacia longifolia 0.00 0.00 0.08 0.03 0.09 0.02 0.25 0.05 subsp. longifolia c Acacia 0.00 0.00 1.08 0.10 2.11 0.10 0.00 0.00 parramattensis Acacia 0.00 0.00 1.58 0.13 3.16 0.13 0.00 0.00 1.44 1.13 1.04 1.21 1.06 parramattensis Bossiaea 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.03 prostrata Daviesia 0.00 0.00 0.00 0.00 0.00 0.00 0.69 0.09 ulicifolia Desmodium 2.67 0.38 3.00 0.17 4.38 0.19 3.50 0.16 1.45 1.41 0.9 1.28 1.15 1.2 varians Desmodium 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 rhytidophyllum Dillwynia sieberi 0.00 0.00 0.00 0.00 0.33 0.06 0.81 0.10 c Dillwynia sieberi 0.00 0.00 0.17 0.05 0.02 0.00 0.00 0.00 Glycine 1.67 0.24 0.00 0.00 0.25 0.06 1.25 0.13 1.07 clandestina Glycine 0.50 0.15 0.08 0.03 0.84 0.10 0.63 0.05 microphylla Glycine spp. A 1.08 0.16 0.50 0.06 0.80 0.07 0.19 0.05 1.06 0.9 0.96 "hairy" Glycine tabacina 4.00 0.35 2.67 0.19 3.86 0.19 4.00 0.12 1.22 1.07 0.89 1.27 1.06 0.98 c Hardenbergia 0.00 0.00 1.25 0.08 0.87 0.07 1.31 0.15 violacea Hardenbergia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 violacea c Indigophera 0.00 0.00 0.17 0.03 0.10 0.02 1.31 0.15 australis Indigophera 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 australis Kennedia 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.05 rubicunda Lotus australis 1.92 0.18 1.50 0.15 1.16 0.09 0.06 0.02 1.21 1.16 0.99 1.28 1.1 1.13 Lotus spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Lotus suaveolens 0.42 0.13 0.00 0.00 0.00 0.00 0.13 0.03 Oxylobium 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 scandens Platylobium 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 1.21 1.35 1.37 1.59 1.66 formosum subsp. formosum Pultenaea 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 microphylla Pultenaea 0.00 0.00 0.08 0.03 0.09 0.02 1.19 0.15 parviflora a Trifolium repens 0.42 0.08 0.75 0.13 0.68 0.06 0.00 0.00 a Vicia spp. 0.00 0.00 0.42 0.08 0.55 0.06 0.00 0.00

Gentianaceae Centaurium 0.58 0.08 0.33 0.08 0.46 0.06 0.00 0.00 erythraea Geraniaceae Geranium 2.83 0.32 2.00 0.19 2.47 0.15 1.06 0.10 1.3 1.27 1.11 1.26 1.14 1.2 homaneum Geranium spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 Goodeniaceae Goodenia 0.00 0.00 0.00 0.00 0.00 0.00 0.63 0.10 hederaceae Hypericaceae Hypericum 1.75 0.20 1.50 0.16 2.83 0.27 0.44 0.03 1.19 1.3 1.13 1.13 1.06 1.22

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gramineum Lamiaceae Mentha dimenica 0.08 0.03 0.25 0.04 0.19 0.03 1.13 0.10 Plectranthus 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.05 parviflorus Scuttelaria 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.05 humilis Lobeliaceae Pratia 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 pendunculata Pratia 0.08 0.03 0.00 0.00 0.08 0.02 0.00 0.00 purpurascens Malvaceae a Malva parviflora 2.17 0.23 2.08 0.13 1.95 0.15 0.38 0.04 1.23 1.2 1.1 1.32 0.96 1.23 a Sida rhombifolia 4.75 0.28 3.50 0.23 5.03 0.21 2.63 0.12 1.06 1.04 2.13 1.41 1.32 Myoporaceae Eremophila 0.00 0.00 0.00 0.00 0.00 0.00 1.44 0.12 debilis Myrtaceae Angophora 0.00 0.00 0.08 0.03 0.09 0.02 0.13 0.03 subvelutina c Angophora 0.00 0.00 0.25 0.05 0.28 0.04 0.00 0.00 subvelutina Angophora 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 costata Angophora 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 floribunda Corymbia 0.00 0.00 0.00 0.00 0.33 0.05 0.94 0.09 maculata c Corymbia 0.00 0.00 0.42 0.08 1.21 0.11 0.00 0.00 maculata c Eucalyptus 0.00 0.00 0.50 0.10 0.48 0.08 0.00 0.00 maculata Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 (corky) Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 amplifolia subsp. amplifolia Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 1.13 0.09 crebra c Eucalyptus 0.00 0.00 0.08 0.03 0.84 0.13 0.00 0.00 crebra Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.04 eugenioides Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.05 fibrosa Eucalyptus 0.00 0.00 0.00 0.00 0.08 0.02 2.06 0.09 moluccana c Eucalyptus 0.00 0.00 2.83 0.10 3.42 0.12 0.00 0.00 moluccana Eucalyptus 0.00 0.00 0.00 0.00 0.00 0.00 2.00 0.08 tereticornis c Eucalyptus 0.00 0.00 0.25 0.05 0.61 0.07 0.00 0.00 tereticornis c Leptospermum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 flavescens Leptospermum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 polygalifoilum c Melaleuca 0.00 0.00 0.25 0.04 0.44 0.05 0.13 0.03 nodosa c Melaleuca 0.00 0.00 0.00 0.00 0.08 0.02 0.06 0.02 quinquenervia

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Melaleuca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 squarrosum Oleaceae a Ligustrum 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 lucidum a Olea europea 0.33 0.06 0.75 0.08 1.16 0.08 1.63 0.12 0.86 subsp. africana Oxalidaceae Oxalis perennans 1.92 0.21 2.08 0.17 1.97 0.13 2.75 0.14 1.32 1.21 1.1 1.33 1.14 1.17 Oxalis exilis 1.75 0.17 2.08 0.16 2.13 0.13 0.19 0.04 1.23 1.11 1.02 1.24 1.15 1.12 Pittosporaceae Bursaria spinosa 0.17 0.03 0.08 0.03 1.09 0.13 3.88 0.12 c Bursaria spinosa 0.00 0.00 1.25 0.13 2.05 0.13 0.00 0.00 a Pittosporum 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 undulatum Plantaginaceae Plantago 0.33 0.08 0.67 0.15 0.84 0.12 1.50 0.14 gaudichaudi Plantago varians 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 Plantago debilis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Plantago 2.58 0.20 3.75 0.18 3.94 0.20 1.69 0.13 1.7 1.54 1.41 lanceolata Polygonaceae a Rumex acetosella 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 Rumex brownii 1.00 0.07 0.58 0.07 1.23 0.09 0.38 0.06 Rumex sagittatus 0.00 0.00 0.67 0.11 0.08 0.01 0.00 0.00 1.06 1.03 0.92 1.14 0.94 Rumex umbellata 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 Primulaceae a Anagalis arvensis 0.00 0.00 2.58 0.14 2.50 0.15 0.69 0.06 1.62 1.11 1.11 1.18 1.12 Ranunculaceae Clematis aristata 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.04 Ranunculus 0.08 0.03 0.17 0.03 0.60 0.07 0.00 0.00 lappaceus Rosaceae a Pyracantha 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 fortuneana a Rubus fruiticosus 0.00 0.00 0.08 0.03 0.51 0.07 0.13 0.03 Rubiaceae Asperula conferta 1.33 0.20 1.50 0.18 2.59 0.19 1.38 0.11 1.28 1.19 1.16 1.13 1.11 Galium spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.05 Opercularia 0.17 0.05 0.08 0.03 0.09 0.02 2.44 0.15 diphylla Pomax umbellata 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 a Richardia 0.33 0.06 0.00 0.00 0.25 0.04 1.25 0.13 stellaris Rutaceae Philotheca 0.00 0.00 0.00 0.00 0.25 0.04 0.19 0.05 myoporoides subsp. myoporoides Santalaceae Exocarpos 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 cupressiformis Sapindaceae

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a Cardiospermum 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.05 halicacabum L. var. halicacabum Dodonaea 0.00 0.00 0.25 0.08 0.28 0.06 0.81 0.11 cuneata subsp. cuneata c Dodonaea 0.00 0.00 0.58 0.09 1.73 0.11 0.00 0.00 cuneata subsp. cuneata Scrophulariaceae a Veronica 0.08 0.03 0.00 0.00 0.08 0.02 0.50 0.05 arvensis Veronica plebeia 0.00 0.00 0.08 0.03 0.01 0.00 0.06 0.02 Solanaceae a Cestrum parqui 0.00 0.00 0.50 0.08 0.64 0.07 0.00 0.00 a Lycium 0.08 0.03 0.00 0.00 0.08 0.02 0.00 0.00 ferocissimum a Solanum 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 mauritianum a Solanum nigrum 0.42 0.06 0.50 0.07 1.64 0.08 1.25 0.10 Solanum 0.00 0.00 0.17 0.05 0.02 0.00 0.00 0.00 opachum Solanum 0.42 0.08 0.08 0.03 0.68 0.07 2.75 0.14 prinophyllum Solanum 0.08 0.03 0.42 0.07 0.05 0.01 0.00 0.00 pungetium a Solanum spp. 0.00 0.00 0.58 0.15 0.67 0.12 0.00 0.00 Stackhousiaceae Stackhousia 0.25 0.08 0.08 0.03 0.34 0.05 0.81 0.09 1.06 0.92 viminea Thymelaeaceae Pimelea spicata 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 Verbenaceae a Lantana camara 0.00 0.00 0.08 0.03 0.09 0.02 0.25 0.03 a Verbena 1.58 0.18 1.83 0.14 1.60 0.11 0.00 0.00 1.28 1.14 1.15 bonariensis a Verbena 0.42 0.07 0.25 0.05 0.11 0.02 0.00 0.00 1.24 1.16 1.06 1.23 1.08 officinalis a Verbena rigida 5.42 0.80 2.75 0.23 3.93 0.18 0.75 0.09 0.99 0.87 1.33 1.21 1.24 Violaceae Viola hederacea 2.50 0.29 2.25 0.20 3.99 0.19 0.00 0.00 1.42 1.13 1.14 Monocotyledons Asphodelaceae Bulbine bulbosa 0.00 0.00 0.00 0.00 0.00 0.00 0.38 0.07 Antheriaceae Arthropodium 0.08 0.03 0.00 0.00 0.00 0.00 3.19 0.12 milleflorum Dichopogon 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 fimbriatus Laxmannia spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 Tricoryne elatior 0.92 0.14 0.17 0.03 0.68 0.09 2.19 0.14 Campanulaceae Wahlenbergia 0.00 0.00 0.33 0.08 0.71 0.07 0.38 0.06 communis Wahlenbergia 0.50 0.09 0.50 0.10 0.64 0.09 1.63 0.10 gracilis Cyperaceae

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Bolboschoenus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 caldwellii Capillipedium 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.02 parviflorum Carex spp. 0.00 0.00 0.00 0.00 0.00 0.00 1.06 0.13 Carex inversa 4.67 0.42 4.83 0.15 5.44 0.18 2.63 0.11 1.05 0.99 1.26 0.9 Carex 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 longebrachiata Cyperus gracilis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Cyperus rotundus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Cyperus spp. 1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Cypress spp. 2 0.00 0.00 0.00 0.00 0.00 0.00 0.56 0.08 Cyprus spp. 3 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Fimbristylis 0.00 0.00 0.00 0.00 0.17 0.03 0.19 0.03 dichotoma Isolepis spp. 0.00 0.00 0.08 0.03 0.09 0.02 0.00 0.00 Lepidosperma 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 concavum Schoenus spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.02 Hypoxidaceae Hypoxis 0.00 0.00 0.00 0.00 0.00 0.00 0.88 0.08 hygrometrica Iridaceae Medanya spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.06 Patersonia 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.06 1.15 1.55 1.35 2.15 1.88 1.2 sericea a Romulea rosea 0.00 0.00 0.17 0.05 0.52 0.07 0.44 0.10 var. australis Juncaceae Juncus 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 subsecundus Juncus usitatus 0.58 0.07 0.42 0.06 0.96 0.08 1.00 0.09 0.99 0.89 0.94 Lomandraceae Lomandra 0.67 0.10 0.58 0.15 0.83 0.12 4.63 0.10 filiformis subsp. filiformis Lomandra 0.00 0.00 0.17 0.05 0.19 0.04 1.69 0.12 multiflora Lomandra 0.00 0.00 0.00 0.00 0.00 0.00 0.69 0.10 gracilis Lomandra 0.08 0.03 0.17 0.03 0.35 0.04 2.00 0.10 longifolia c Lomandra 0.00 0.00 0.17 0.05 0.19 0.04 0.00 0.00 longifolia Lomandra brevis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Lomandra 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 micrantha Phormiaceae Dianella 0.33 0.10 0.25 0.08 0.95 0.11 1.06 0.10 caerulea subsp. caerulea Dianella 0.17 0.05 0.00 0.00 1.17 0.17 0.81 0.09 caerulea subsp. revoluta Dianella 0.58 0.12 0.00 0.00 0.92 0.10 0.19 0.03 0.96 0.84 longifolia var. longifolia Dianella 0.00 0.00 0.00 0.00 0.33 0.05 0.00 0.00 multiflora

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Dianella prunina 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Dianella spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Poaceae Aristida ramosa 1.58 0.19 1.75 0.19 3.28 0.20 3.69 0.14 1.22 1.15 1.09 1.04 1.09 1.08 Aristida vagans 0.42 0.10 0.42 0.07 0.30 0.04 2.06 0.14 Austrodanthonia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 fulva (?) Axinopus affinus 0.33 0.06 0.33 0.06 0.12 0.02 0.31 0.08 Bothriochloa 0.92 0.13 2.25 0.20 1.66 0.14 0.75 0.08 1.23 1.09 1.14 rara Bothriochloa 0.58 0.09 0.75 0.08 0.91 0.07 0.69 0.06 1 0.96 0.9 0.92 parva Bothriochloa 0.00 0.00 0.00 0.00 0.58 0.08 0.13 0.03 decipiens Bothriochloa 0.25 0.04 0.08 0.03 0.18 0.03 0.88 0.11 macra a Briza maxima 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Briza minor 0.17 0.05 1.33 0.11 1.46 0.09 0.13 0.02 1.32 1 1.05 0.97 a Bromus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 molliformis a Bromus 0.17 0.05 0.58 0.07 0.73 0.07 0.00 0.00 catharticus a Bromus diandrus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Bromus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 molliformis a Chloris gayana 1.00 0.20 1.42 0.17 2.33 0.14 0.06 0.02 1.24 1.01 1.11 0.91 Chloris truncata 0.00 0.00 0.08 0.03 0.59 0.07 0.44 0.10 Chloris 0.75 0.14 0.33 0.04 0.62 0.06 1.81 0.14 ventricosa Cymbopogon 0.50 0.15 0.50 0.15 1.91 0.19 1.50 0.12 0.88 refractus Cynodon 3.08 0.35 4.75 0.16 7.18 0.19 0.81 0.10 1.38 1.3 1.33 0.92 0.96 dactylon Danthonia spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.03 Danthonia linkii 0.58 0.11 1.67 0.18 2.77 0.16 1.25 0.11 1.36 1.17 1.09 1.16 1.1 subsp. linkii Danthonia 0.08 0.03 0.00 0.00 0.17 0.04 0.00 0.00 micrantha Danthonia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 racemosa Dichelachne 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.03 micrantha Dichelachne rara 0.00 0.00 0.17 0.03 0.60 0.06 0.69 0.07 Echinopogon 0.00 0.00 0.00 0.00 0.00 0.00 0.50 0.06 caespitosus Echinopogon 0.00 0.00 0.00 0.00 0.00 0.00 1.31 0.07 ovatus Entolasia 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 marginata Eragrostis 0.00 0.00 0.17 0.05 0.77 0.09 1.19 0.10 brownii a Eragrostis 1.25 0.15 0.00 0.00 1.00 0.14 0.00 0.00 1.1 0.97 1.03 curvala Eragrostis 0.08 0.03 1.00 0.10 2.02 0.20 2.94 0.14 1 1.01 0.95 1.02 leptostachya a Festuca elatior 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Imperata 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 cylindrica a Lolium loliaceum 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00

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a Lolium perenne 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Microlaena 5.83 0.74 4.92 0.17 6.20 0.22 5.63 0.06 1.16 1.04 1.22 0.92 stipoides var. stipoides Osplismenus 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.04 aemulus Osplismenus 0.00 0.00 0.00 0.00 0.00 0.00 0.88 0.11 imbecillis Panicum effusum 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 Panicum simile 0.00 0.00 0.00 0.00 0.08 0.02 2.06 0.10 Panicum 0.08 0.03 0.50 0.10 0.56 0.08 0.56 0.08 maximum Paspalum spp. 1.25 0.17 0.75 0.11 0.25 0.03 0.50 0.06 0.87 Paspalidium 0.42 0.07 0.25 0.08 0.37 0.05 2.13 0.14 distans a Paspalum 6.83 0.72 4.42 0.19 6.96 0.40 1.44 0.12 1.17 1.03 1.7 1.63 1.36 dilatatum a Pennisetum 5.58 1.21 1.83 0.21 2.05 0.18 0.00 0.00 1.14 1.02 1.1 clandestinum a Pennisetum spp. 2.25 0.24 0.00 0.00 0.00 0.00 0.00 0.00 1.39 1.26 1.09 1.82 1.21 1.2 a Phalaris 0.00 0.00 0.00 0.00 0.08 0.02 0.00 0.00 1.47 1.41 1.85 arundinaceae var. arundinaceae a Phalaris 0.17 0.05 0.00 0.00 0.00 0.00 0.00 0.00 canariensis a Phalaris minor 1.75 0.20 1.50 0.19 2.10 0.16 0.06 0.02 0.91 1.06 a Poa annua 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.00 Poa cheellii 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Poa labillardieri 0.58 0.09 1.17 0.14 1.79 0.13 0.69 0.08 Poa sieberana 0.33 0.07 0.00 0.00 0.00 0.00 1.00 0.08 0.94 0.92 Poa spp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 a Setaria gracilis 3.00 0.20 3.08 0.22 5.07 0.18 3.06 0.15 1.4 1.28 1.25 a Setaria 0.08 0.03 0.83 0.12 0.51 0.08 0.00 0.00 1.29 1.23 1.17 1.52 1.25 1.15 sphacelata a Sporobolus 1.00 0.14 0.58 0.09 0.57 0.06 0.88 0.09 africana Sporobolus 1.08 0.12 1.25 0.15 0.89 0.08 2.63 0.13 0.94 creber Stipa pubescens 0.83 0.20 0.17 0.03 0.52 0.10 0.00 0.00 Themeda 0.67 0.11 0.08 0.03 1.09 0.11 2.81 0.16 australis a Exotic species b Planted and non-planted species c Species recorded in restored treatments by planted species only

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Appendix 3.B Comparisons between vegetation communities Average % dissimilarity between vegetation groups Pasture Young Old Reveg Remnant Reveg Pasture - 66.21 71.71 79.4 Young - - 65.23 74.7 Reveg Old Reveg - - - 75.72 Remnant - - - -

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Pasture and Remnant

Pasture and Remnant vegetation had a low percentage dissimilarity, comprising of 35 species, 30 of which were native (Bray-Curtis).

Average % dissimilarity: Pasture & Remnant These species contributed up to 50% of the average dissimilarity between Pasture & Remnant. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (pasture-remnant) shown on scale --,-,0,+,++.

Species Average Average Cumulative abundance abundance % (Pasture) (Remnant) *Pennisetum clandestinum 3.50 0.00 2.72 Bursaria spinosa 0.15 3.73 5.18 Brunoniella australis 0.40 3.64 7.62 Lomandra filiformis ssp. filiformis 0.80 3.95 9.96 *Paspalum dilatatum 4.05 0.82 12.29 Themeda australis 1.00 3.86 14.59 Aristida ramosa 1.60 3.39 16.57 Cynodon dactylon 3.05 0.43 18.47 Microlaena stipoides var stipoides 2.60 3.66 20.13 *Verbena rigida 2.48 0.57 21.72 Cheilanthes sieberi ssp. sieberi 0.00 2.29 23.25 Carex inversa 3.00 1.71 24.64 Glycine tabacina 2.75 2.46 26.03 *Setaria gracilis 2.55 1.75 27.38 *Verbena bonariensis 2.05 0.25 28.71 Eragrostis leptostachya 0.00 1.93 30.02 Lomandra multiflora 0.00 1.89 31.30 Opercularia diphylla 0.15 1.89 32.90 *Sida rhombifolia 3.05 1.43 33.86 Arthropodium milleflorum 0.15 1.93 3.11 Viola hederacea 1.40 1.00 6.31 Desmodium varians 1.45 1.57 37.45 *Vinca minor 0.00 1.68 38.54 *Senecio madagascariensis 1.85 2.29 39.61 *Solanum pinifolium 0.25 1.50 40.66 *Olea europaea ssp. africana 0.40 1.36 41.69 *Plantago lanceolata 1.65 0.93 42.71 *Malva parviflora 1.50 0.21 43.72 Tricoryne elatior 0.55 1.43 44.72 Sporobolus creber 0.60 1.50 45.72 Geranium homaneum 1.45 0.61 46.69 Eucalyptus moluccana 0.15 1.25 47.66 Cymbopogon refractus 0.45 1.20 48.59 Asperula conferta 0.93 0.89 49.47 Poa labillardierii 0.80 0.86 50.35

234

Pasture and Young Revegetation

Pasture and Young Revegetation had a low percentage dissimilarity, comprising of 31 species, 16 of which were native (Bray-Curtis). There were 14 native species that increased their abundance after restoration, including one (Viola) making a substantial increase. There were 11 exotic species that increased their abundance after restoration, including 5 species making substantial increases. There were 2 native and 4 exotic species that decreased their abundance after revegetation.

Average % dissimilarity: Pasture & Young Revegetation These species contributed up to 50% of the average dissimilarity between Pasture & Young Revegetation. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (pasture- young reveg) shown on scale --,-,0,+,++. Species Average Average Cumulative Change abundance abundance % (--, -, 0, (Pasture) (Young) +, ++) *Pennisetum clandestinum 3.50 2.13 2.88 - Microlaena stipoides var. stipoides 2.60 3.63 5.15 + Cynodon dactylon 3.05 4.08 9.51 + *Paspalum dilatatum 4.05 3.82 11.45 - *Setaria gracilis 2.55 3.34 13.28 + Glycine tabacina 2.75 2.42 15.09 - *Verbena rigida 2.48 2.45 16.86 - Aristida ramosa 1.60 1.95 18.59 + *Cerisium vulgare 0.70 2.37 20.29 ++ Viola hederacea 1.40 2.26 21.87 ++ *Phalaris minor 1.28 1.45 23.39 + *Verbena bonariensis 2.05 2.16 24.91 + *Briza minor 0.30 2.00 26.39 ++ *Plantago lanceolata 1.65 2.63 27.87 + Desmodium var 1.45 2.11 29.35 + *Senecio madagascariensis 1.85 2.37 30.8 + Carex inversa 3.00 3.11 32.19 + Lomandra filiformis ssp. filiformis 0.80 1.68 33.55 + Asperula conferta 0.93 1.53 34.87 + Geranium homaneum 1.45 1.00 36.13 - *Apium leptophyllum 0.00 1.68 37.36 ++

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*Malva parviflora 1.50 1.26 38.57 - Hypericum gramineum 1.05 1.42 39.78 + *Sida rhombifolia 3.05 3.37 40.98 + Oxalis exilis 0.70 1.47 42.17 + Poa labillardierii 0.80 1.00 43.30 + Lotus australis 0.95 1.05 47.70 + *Hypochoeris radicata 0.00 1.42 48.74 ++ Danthonia linkii var. linkii 0.85 0.95 50.80 +

236

Pasture and Old Revegetation Group Pasture and Old Revegetation Group had a low percentage dissimilarity, comprising of 29 species, 16 of which were native (Bray-Curtis). There were 12 native species that increased their abundance after restoration, including 1 making a substantial increase. There were 6 exotic species that increased their abundance after restoration, including 1 species making a substantial increase. There were 7 exotics that decreased their abundance including 1 substantial decrease by Verbena rigida after restoration. 4 native also decreased their abundance after restoration.

Average % dissimilarity: Pasture & Old Revegetation Group These species contributed up to 50% of the average dissimilarity between Pasture & Old Revegetation Group. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (pasture- old revegetation shown on scale --,-,0,+,++. Species Average Average Cumulative Change abundance abundance % (--, -, 0, +, (Pasture) (Old) ++) *Pennisetum clandestinum 3.50 1.48 3.05 - *Paspalum dilatatum 4.05 2.62 5.26 - Microlaena stipoides var. stipoides 2.60 3.19 7.37 + Cynodon dactylon 3.05 3.98 9.41 + *Setaria gracilis 2.55 2.67 13.28 + Aristida ramosa 1.60 2.24 15.11 + *Verbena rigida 2.48 1.38 16.91 -- Glycine tabacina 2.75 2.29 18.71 - Asperula conferta 0.93 1.81 20.37 + *Verbena bonariensis 2.05 1.19 23.66 - Cymbopogon refractus 0.45 1.62 25.26 + Carex inversa 3.00 2.62 26.84 - *Sida rhombifolia 3.05 2.86 28.36 - *Phalaris minor 1.28 1.43 29.87 + *Conyza bonariensis 0.10 1.81 31.36 ++ Desmodium varians 1.45 1.62 32.83 + Danthonia linkii var. linkii 0.85 1.67 34.26 + Viola hederacea 1.40 1.71 35.68 + *Senecio madagascariensis 1.85 1.95 37.02 + *Plantago lanceolata 1.65 1.52 38.32 -

237

*Cerisium vulgare 0.70 1.67 39.62 + Acacia parramattensis 0.00 1.52 42.14 ++ *Malva parviflora 1.50 0.90 43.38 - Geranium homaneum 1.45 0.90 44.60 - Lotus australis 0.95 0.81 45.77 - Hypericum gramineum 1.05 1.19 46.91 + *Olea europaea ssp. africana 0.40 1.38 48.03 + Dianella caerulea ssp. revoluta 0.20 1.19 49.12 + Poa labillardierii 0.80 1.05 50.19 +

238

Young Revegetation and Old Revegetation 3-5 year old restored and 8-10 year old restored vegetation had the lowest percentage dissimilarity, comprising of 45 species, 26 of which were native (Bray-Curtis). There were 11 native species that increased their abundance after restoration and 4 exotic species that increased their abundance after restoration, including 1 species making a substantial increase. 54 exotic decreased their abundance, including 1 (Verbena bonariensis) making a substantial decrease and 15 natives that decreased their abundance from Young revegetation to Old revegetation. Average % dissimilarity: Young Revegetation and Old Revegetation These species contributed up to 50% of the average dissimilarity between Young Revegetation and Old Revegetation. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (Young-Old) shown on scale --,-,0,+,++. Species Average Average Cumulative Change abundance abundance % (--, -, 0, +, (Young) (Old) ++) *Pennisetum clandestinum 2.13 1.48 2.06 - Microlaena stipoides var. stipoides 3.63 3.19 4.07 - *Paspalum dilatatum 3.82 2.62 7.60 - Aristida ramosa 1.95 2.24 11.00 + *Setaria gracilis 3.34 2.67 12.60 - Cynodon dactylon 4.08 3.98 14.16 - *Verbena rigida 2.45 1.38 15.69 - Cymbopogon refractus 0.76 1.62 17.18 + Glycine tabacina 2.42 2.29 18.68 - *Verbena bonariensis 2.16 1.19 20.15 -- Asperula conferta 1.53 1.81 21.60 + *Sida rhombifolia 3.37 2.86 23.03 - *Phalaris minor 1.45 1.43 24.43 - *Plantago lanceolata 2.63 1.52 25.81 - Viola hederacea 2.26 1.71 27.16 - *Senecio madagascariensis 2.37 1.95 28.46 - *Briza minor 2.00 1.33 29.72 - *Conyza bonariensis 0.79 1.81 30.97 + Desmodium var 2.11 1.62 32.22 - Acacia parramattensis 0.89 1.52 34.67 + Danthonia linkii var linkii 0.95 1.67 35.85 + Lomandra filiformis ssp. filiformis 1.68 0.52 37.00 -

239

Carex inversa 3.11 2.62 38.14 - *Apium leptophyllum 1.68 0.95 39.27 - *Chloris gayana 1.13 1.14 40.40 + *Cerisium vulgare 2.37 1.67 41.49 -- Hypericum gramineum 1.42 1.19 42.55 - Poa labillardierii 1.00 1.05 43.62 + *Hypochoeris radicata 1.42 0.95 45.70 - Lotus australis 1.05 0.81 46.74 - *Olea europaea ssp. africana 0.53 1.38 47.76 + Oxalis exilis 1.47 0.19 48.76 - *Malva parviflora 1.26 0.90 49.76 - Phyllanthes virgatus 1.21 0.71 50.75 - Eragrostis leptostachya 1.16 1.19 51.73 + *Anagallis arvensis 1.37 1.10 52.69 - Dichelachne rara 0.84 1.00 53.65 + Dianella caerulea ssp. revoluta 0.16 1.19 54.60 + Geranium homaneum 1.00 0.90 55.50 - Bothriochloa decipiens 1.05 0.52 56.38 - Themeda australis 0.68 0.93 57.25 + Sporobolus creber 1.21 0.43 58.10 - *Sonchus oleraceus 1.05 0.81 58.90 - Juncus usitatus 0.63 0.76 59.70 + Einadia hastata 0.89 0.67 60.47 -

240

Old Revegetation and Remnant vegetation Old Revegetation and Remnant vegetation had the second highest percentage dissimilarity, comprising of 41 species, 27 of which were native (Bray-Curtis). Most importantly, the species with increased abundance include tree and shrub canopy species. These are the species not recorded in restored vegetation. There were 11 native species found to have reduced abundance in Remnant vegetation, most of these are grasses and herbs, however included was one shrub species (Acacia parramattensis) which was a commonly used in revegetation works and was found to respond to disturbance and senescence by re-sprouting from the roots. Average % dissimilarity: Old Revegetation and Remnant vegetation These species contributed up to 50% of the average dissimilarity between Old Revegetation and Remnant vegetation. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (Old Revegetation-Remnant) shown on scale --,-,0,+,++. Species Average Average Cumulative % Change abundance (Old) abundance (--, -, 0, +, (Remnant) ++) Cynodon dactylon 3.98 0.43 2.27 - Lomandra filiformis ssp. 0.52 3.95 4.48 + filiformis Themeda australis 0.93 3.86 6.56 + Bursaria spinosa 2.33 3.73 8.51 + Brunoniella australis 0.62 3.64 10.45 + Aristida ramosa 2.24 3.39 12.01 + Microlaena stipoides var. 3.19 3.66 13.57 + stipoides *Paspalum dilatatum 2.62 0.82 14.96 - Cheilanthes sieberi ssp. 0.19 2.29 16.34 + sieberi *Sida rhombifolia 2.86 1.43 17.68 - *Setaria gracilis 2.67 1.75 19.01 - Eucalyptus moluccana 0.00 1.25 20.35 + Cymbopogon refractus 1.62 1.20 21.68 - Glycine tabacina 2.29 2.46 22.88 + Viola hederacea 1.71 1.00 24.07 - Asperula conferta 1.81 0.89 25.25 - Lomandra multiflora 0.14 1.89 26.41 +

241

Opercularia diphylla 0.05 1.89 27.57 + Arthropodium milleflorum 0.05 1.93 28.7 - Carex inversa 2.62 1.71 29.81 - *Olea europaea ssp. 1.38 1.36 30.92 - africana Dianella caerulea ssp. 1.19 1.14 32.01 - revoluta *Conyza bonariensis 1.81 0.57 33.08 - Danthonia linkii var. linkii 1.67 0.82 34.14 - Eragrostis leptostachya 1.19 1.93 35.18 + Desmodium varians 1.62 1.57 36.21 - *Senecio madagascariensis 1.95 2.29 37.24 + *Vinca minor 0.10 1.68 38.23 ++ Dodonaea cuneata 0.35 0.36 39.22 + Solanum prinophyllum 0.52 1.54 40.19 + Acacia parramattensis 1.52 0.00 41.14 -- Tricoryne elatior 0.43 1.43 42.08 + *Verbena rigida 1.38 0.57 42.99 - *Cerisium vulgare 1.67 0.96 43.91 - *Plantago lanceolata 1.52 0.93 44.81 - Sporobolus creber 0.43 1.50 45.70 + *Phalaris minor 1.43 0.00 46.57 -- Poa labillardierii 1.05 0.86 47.42 - *Pennisetum clandestinum 1.48 0.00 48.27 - Aristida vagans 0.48 1.23 49.07 + *Briza minor 1.33 0.07 49.86 -- *Verbena bonariensis 1.19 0.25 50.64 -

242

Young Revegetation and Remnant vegetation Young Revegetation and Remnant vegetation had a high dissimilarity, comprising 42 species, 27 of which were native which contributed up to 50% of the average dissimilarity (Bray-Curtis). Most importantly, the species with increased abundance include tree and shrub canopy species. These structural canopy species are missing from restored vegetation.

Average % dissimilarity: Young Revegetation and Remnant vegetation These species contributed up to 50% of the average dissimilarity between: Young Revegetation and Remnant vegetation. Average abundance is the average frequency score value. The cumulative percentage contribution of each species to the total average Bray-Curtis value is also given. Change (Young-remnant) shown on scale --,-,0,+,++. Species Average Average Cumulative % Change abundance abundance (--, -, 0, +, (Young) (Remnant) ++) Cynodon dactylon 4.08 0.43 2.21 - Themeda australis 0.68 3.86 4.40 + Lomandra filiformis ssp. 1.68 3.95 6.46 + filiformis Brunoniella australis 0.63 3.64 8.39 + *Paspalum dilatatum 3.82 0.82 10.30 - Aristida ramosa 1.95 3.39 11.99 + Bursaria spinosa 1.37 3.73 13.67 + Microlaena stipoides var. 3.63 3.66 15.22 + stipoides *Pennisetum clandestinum 2.13 0.00 16.70 - Eucalyptus moluccana 0.00 1.25 18.10 + Cheilanthes sieberi ssp. sieberi 0.00 2.29 19.45 + *Verbena rigida 2.45 0.57 20.79 - *Setaria gracilis 3.34 1.75 22.12 - *Sida rhombifolia 3.37 1.43 23.42 - Viola hederacea 2.26 1.00 24.72 - *Verbena bonariensis 2.16 0.25 25.99 - *Plantago lanceolata 2.63 0.93 27.19 - Glycine tabacina 2.42 2.46 28.32 + Lomandra multiflora 0.26 1.89 29.45 + Opercularia diphylla 0.11 1.89 30.56 + Arthropodium milleflorum 0.05 1.93 31.66 +

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*Briza minor 2.00 0.07 32.76 - Carex inversa 3.11 1.71 33.83 - Eragrostis leptostachya 1.16 1.93 34.88 + *Senecio madagascariensis 2.37 2.29 35.89 - *Cerisium vulgare 2.37 0.96 36.89 - Solanum prinophyllum 0.53 1.54 37.85 + *Vinca minor 0.16 1.68 38.81 + Tricoryne elatior 0.79 1.43 39.73 + *Apium leptophyllum 1.68 0.00 40.63 - *Olea europaea ssp. africana 0.53 1.36 41.52 + Desmodium varians 2.11 1.57 42.40 - Phyllanthes virgatus 1.21 1.00 43.27 - Cymbopogon refractus 0.76 1.20 44.14 + *Phalaris minor 1.45 0.00 44.99 - Corymbia maculata 0.00 0.50 45.84 + Asperula conferta 1.53 0.89 46.69 - Poa labillardierii 1.00 0.86 47.53 - Oxalis exilis 1.47 0.14 48.36 - Sporobolus creber 1.21 1.50 49.18 + *Hypochoeris radicata 1.42 0.71 49.99 - Hypericum gramineum 1.42 0.64 50.77 -

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Appendix 4.C Abundance of vascular plant species mean frequency score, se

Age of revegetation 5 5 10 10 Canopy (+) / No canopy (-) + - + - Species Acanthaceae

Brunoniella australis 0.16 0.02 0.20 0.04 0.02 0.00 0.02 0.00

Antheriaceae

Tricoryne elatior 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00

Apiaceae

a Apium leptophyllum 1.09 0.06 0.39 0.07 0.33 0.01 0.24 0.01

a Hydrocotyl bonariensis 0.00 0.00 0.07 0.02 0.07 0.01 0.19 0.01

a Foeniculum vulgare 0.00 0.00 0.00 0.00 0.08 0.01 0.16 0.01

Asclepiadaceae

a Araujia hortorum 0.00 0.00 0.00 0.00 0.10 0.00 0.01 0.00

Asparagaceae

a Myrsiphyllum asparagoides 1.50 0.11 3.22 0.23 1.45 0.02 1.44 0.02

Asteraceae

a Bidens pilosa 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00

a Cirsium vulgare 0.00 0.00 0.00 0.00 0.00 0.01 0.13 0.01

a Conyza albida 0.06 0.01 0.20 0.02 0.06 0.01 0.18 0.01

a Conyza bonariensis 0.30 0.04 0.19 0.03 0.13 0.00 0.14 0.01

a Hypochoeris radicata 0.00 0.00 0.03 0.01 0.02 0.01 0.53 0.01

a Senecio madagascariensis 0.01 0.00 0.03 0.01 0.00 0.00 0.02 0.00

a Sonchus oleraceus 0.03 0.01 0.01 0.00 0.21 0.01 0.01 0.00

Campanulaceae

Wahlenbergia communis 0.55 0.07 0.28 0.04 0.43 0.01 0.00 0.00

Caryophyllaceae

a Petrorhagia nanteuilii 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Chenopodiaceae

Einadia hastata 0.07 0.02 0.00 0.00 0.07 0.00 0.00 0.00

Einadia trigonos 0.33 0.05 0.15 0.04 0.00 0.00 0.01 0.00

Commelenaceae

a Tradescantia albiflora 0.22 0.05 0.08 0.02 0.35 0.01 0.21 0.01

245

Convolvulaceae

Dichondra repens 0.00 0.00 0.03 0.01 0.00 0.00 0.03 0.00

Cyperaceae

Carex inversa 0.34 0.06 0.21 0.06 0.58 0.01 0.50 0.01

Cyperus gracilis 2.51 0.18 1.70 0.12 0.86 0.02 1.34 0.02

Dilleniaceae

Phyllanthus virgatus 0.14 0.04 0.13 0.03 1.59 0.03 2.64 0.03

Fabaceae

Acacia implexa 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Acacia floribunda 0.01 0.00 0.00 0.00 0.32 0.01 0.18 0.01

Acacia parramattensis 0.00 0.00 0.00 0.00 0.04 0.00 0.00 0.00

Desmodium varians 0.00 0.00 0.14 0.03 0.09 0.00 0.04 0.00

Glycine clandestina 0.02 0.01 0.09 0.02 0.16 0.01 0.17 0.01

Glycine tabacina 0.27 0.07 0.29 0.04 0.49 0.01 0.66 0.01

Glycine spp. A 0.64 0.10 0.35 0.04 0.71 0.01 0.74 0.01

Indigofera australis 0.24 0.04 0.00 0.00 0.05 0.00 0.03 0.00

Lotus australis 0.02 0.01 0.01 0.00 0.02 0.00 0.02 0.00

Lotus suaveolens 0.04 0.01 0.08 0.03 0.02 0.00 0.07 0.01

a Trifolium repens 0.05 0.02 0.02 0.01 0.04 0.00 0.00 0.00

Gentianaceae

a Centaurium asiaticum 0.41 0.07 1.07 0.07 0.95 0.01 1.15 0.02

Geranium homeanum 0.00 0.00 0.03 0.01 0.01 0.00 0.08 0.01

Hypericaceae

Hypericum gramineum 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00

Juncaceae

Juncus subsecundus 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Lomandraceae

Lomandra brevis 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00

Lomandra filiformis subsp. filiformis 0.14 0.04 0.01 0.00 0.06 0.00 0.03 0.00

Lomandra multiflora 0.03 0.01 0.00 0.00 0.40 0.01 0.20 0.01

Malvaceae

a Sida rhombifolia 1.40 0.10 0.92 0.06 1.11 0.02 1.48 0.02

a Verbena bonariensis 0.06 0.02 0.00 0.00 0.00 0.00 0.00 0.00

Oleaceae

a Olea europea subsp. africana 0.00 0.00 0.00 0.00 0.26 0.01 0.04 0.00

246

Oxalidaceae

a Oxalis corniculata 0.01 0.00 0.00 0.00 0.21 0.01 0.26 0.01

Oxalis exilis 0.17 0.03 0.14 0.03 0.00 0.00 0.10 0.01

Oxalis perennans 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00

Phormiaceae

Dianella caerulea var. caerulea 0.16 0.03 0.18 0.04 0.16 0.01 0.06 0.00

Dianella caerulea var. revoluta 0.00 0.00 0.00 0.00 0.08 0.00 0.02 0.00

Plantaginaceae

Plantago gaudichaudii 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

a Plantago lanceolata 0.52 0.08 0.35 0.07 0.11 0.01 0.28 0.01

Poaceae

Aristida ramosa 0.31 0.04 0.43 0.07 0.06 0.00 0.07 0.00

Aristida vagans 0.33 0.04 0.63 0.09 1.58 0.02 1.51 0.02

Bothriochloa decipiens 0.00 0.00 0.21 0.06 0.00 0.00 0.00 0.00

Bothriochloa macra 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00

a Briza minor 0.11 0.03 0.09 0.02 0.08 0.00 0.00 0.00

a Bromus catharticus 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Chloris ventricosa 0.06 0.02 0.00 0.00 0.03 0.00 0.00 0.00

a Chloris gayana 0.38 0.09 0.02 0.01 0.41 0.01 0.26 0.01

Cymbopogon refractus 0.04 0.01 0.03 0.01 0.09 0.01 0.05 0.00

Cynodon dactylon 0.67 0.11 0.84 0.12 0.28 0.01 0.42 0.01

Danthonia linkii 0.00 0.00 0.06 0.01 0.00 0.00 0.00 0.00 Danthonia tenuior 0.13 0.04 0.00 0.00 0.39 0.01 0.03 0.00

Danthonia racemosa 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00

Danthonia spp 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00

Dichelachne micrantha 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00

Dichelachne siebera 0.03 0.01 0.04 0.01 0.00 0.00 0.00 0.00

Digitaria spp. 0.00 0.00 0.00 0.00 0.11 0.00 0.01 0.00

Entolasia whiteana 0.22 0.05 0.08 0.02 0.04 0.00 0.03 0.00

Eragrostis leptostachya 0.04 0.01 0.15 0.04 0.02 0.00 0.07 0.01

a Lolium annua 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00

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Poaceae (Continued)

Microlaena stipoides var. stipoides 0.80 0.13 0.58 0.10 0.88 0.02 0.77 0.02

a Paspalum dilatatum 0.48 0.07 1.19 0.16 0.43 0.01 0.14 0.01

Paspalidium distans 1.86 0.14 1.85 0.14 1.09 0.02 1.15 0.02

a Pennisetum clandestinum 0.05 0.02 0.00 0.00 0.03 0.00 0.00 0.00

a Phalaris minor 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00

Poa labillardierii 1.19 0.08 1.41 0.09 0.67 0.01 0.19 0.01

a Setaria gracilis 1.00 0.05 0.40 0.05 0.55 0.01 0.08 0.00

Sporobolus creber 0.07 0.01 0.02 0.01 0.00 0.00 0.00 0.00

Themeda australis 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.00

Polygonaceae

Rumex brownii 0.00 0.00 0.03 0.01 0.22 0.01 0.04 0.00

Primulaceae

a Anagallis arvensis 0.17 0.03 0.00 0.00 0.11 0.01 0.04 0.00

Rosaceae

a Rubus fruiticosus 1.07 0.11 0.42 0.05 1.09 0.02 0.69 0.01

Rubiaceae

a Asperula conferta 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00

Sapindaceae

a Cardiospermum halicacabum L. var. halicacabum 0.03 0.01 0.01 0.00 0.00 0.00 0.00 0.00

Sinopteridaceae

Cheilanthes sieberi 0.06 0.01 0.05 0.02 0.27 0.01 0.24 0.01

Solanaceae

a Cestrum parqui 0.01 0.00 0.00 0.00 0.26 0.01 0.02 0.00

a Solanum nigrum 0.97 0.09 0.75 0.07 0.71 0.02 0.79 0.02

Stackhousiaceae

Stackhousia viminea 0.00 0.00 0.03 0.01 0.00 0.00 0.01 0.00

Verbenaceae

a Verbena rigida 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00

Violaceae

Viola hederacea 1.28 0.10 1.98 0.14 0.72 0.02 1.50 0.02

a Exotic species

248