Plant Rarity: Species Distributional Patterns, Population Genetics, Pollination Biology, and Seed Dispersal in Persoonia (Proteaceae)

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Plant rarity: species distributional patterns, population genetics, pollination biology, and seed dispersal in Persoonia (Proteaceae)

Paul D. Rymer University of Wollongong

Rymer, Paul D, Plant rarity: species distributional patterns, population genetics, pollination biology, and seed dispersal in Persoonia (Proteaceae), PhD thesis, School of Biological Sciences, University of Wollongong, 2006. http://ro.uow.edu.au/theses/634

This paper is posted at Research Online. http://ro.uow.edu.au/theses/634

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Plant rarity: species distributional patterns, population genetics, pollination biology, and seed dispersal in Persoonia (Proteaceae).

PhD Thesis

by

Paul D. Rymer B.Sc. (Hons) – Uni. of Western Sydney

School of Biological Sciences

UNIVERSITY OF WOLLONGONG

2006 2

DECLARATION

This thesis is submitted, in accordance with the regulations of the University of

Wollongong, in fulfilment of the requirements of the degree of Doctor of Philosophy.

The work described in this thesis was carried out by me, except where otherwise acknowledged, and has not been submitted to any other university or institution. 3

“Yes, Duckie, you’re lucky you’re not Herbie Hart

who has taken his Throm-dim-bu-lator apart”

(Dr. Seuss 1973)

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Abstract An understanding of rarity can provide important insights into evolutionary processes, as well as valuable information for the conservation management of rare and threatened species. In this research, my main objective was to gain an understanding of the biology of rarity by investigating colonization and extinction processes from an ecological and evolutionary perspective. I have focused on the genus Persoonia (family Proteaceae), because these plants are prominent components of the Australian flora and the distributional patterns of species vary dramatically, including several that are listed as threatened. The approach I have taken was first to define the level of commonness/rarity for all species and subspecies in the genus across Australia, in order to identify potential patterns in the traits of common and rare taxa (all termed ‘species’ herein). From this set of species, the subsequent research was based on two pairs (one common and one rare species in each pair) of closely related, obligate seeding Persoonia species: P. mollis subspecies nectens (common pair 1) and P. mollis subspecies maxima (rare pair 1) and

P. lanceolata (common pair 2) and P. glaucescens (rare pair 2). In this research, I investigated population genetics, pollination and seed dispersal to identify consistent differences between the common and rare species in the ecological processes influencing colonization and extinction.

Few robust definitions of rarity enable unambiguous comparative investigations of these processes. I defined rarity using three different methods, and classified Persoonia species into three levels of rarity (common, intermediate, rare). There was no association between rarity and either taxonomic status or geographical distribution, but several environmental (rainfall, temperature and elevation) and life-history (resprouting ability and plant size) traits differed significantly between common and rare species.

These results suggest that the common species have a greater ability to persist in often 5

harsh landscapes, being able to resprout after disturbance and tolerate severe environmental conditions. Of the taxa examined in detail, local abundance was related to distribution patterns, as the rare species tended to have fewer plants within a patch than more common species. The current distribution of Persoonia species in the Sydney region appears to reflect historical patterns rather than recent effects of fragmentation.

Theory predicts that genetic variation is important for long-term persistence of populations, and that the abundance and distribution of variation is strongly dependent on genetic drift and gene flow. Small, isolated populations are therefore expected to be less diverse and more differentiated than large, inter-connected populations. Thus, rare species may be more at risk from inbreeding depression, leading to extinction. I used

389 putative AFLP loci to compare genetic variation and structuring in the two common-rare pairs of closely related species. I genotyped 15-22 adult plants, from each of the four populations, covering the geographic range of each species. Although genetic variation was low for all four species (compared to the average for long-lived outcrossing perennials), I found significantly more variation within populations of the rare species than the common species (% polymorphism = 61.3, 61.0 cf. 54.5, 53.2; expected heterozygosity = 0.170, 0.148 cf. 0.124, 0.128; Shannon’s I = 0.239, 0.216 cf.

0.182, 0.186). My AMOVA revealed significant levels of structure both among species

(21%) and populations (15%), although the proportion of inter-population variation within species did not vary consistently with rarity (Pair 1 - rare 21.1% cf. common

16.5%; Pair 2 - rare 15.8% cf. common 20.6%). I detected more differentiation between populations of the rare species than the common species (controlled for the level of geographic separation), suggesting greater gene flow between populations of the common species. Even relatively small populations of rare species were more diverse than large populations of common Persoonia species. 6

Understanding the interactions between breeding systems and pollination ecology may enable some prediction of the consequences of rarity. Using a comparative approach, I tested whether rarity is associated with aspects of reproductive biology in the two species pairs. This study focused on natural ecosystems in Australia, which have been recently affected by changes in fire regimes, especially over the past 200 years of

European settlement, and by the introduction of European honeybees (Apis mellifera).

In populations of the common species, more than 35% of flowers matured fruits compared to <20% of flowers in the rare species. All species were obligate outcrossers in each of the study populations, but only the two rare species were pollen-limited (lack of compatible pollen), with significantly lower fruit-set on open-pollinated flowers than on those cross-pollinated by hand (mean ± SE; 0.18 ± 0.02 vs. 0.42 ± 0.05; P < 0.001).

Native bees (mostly Leioproctus species) and introduced honeybees (Apis mellifera) visited flowers of all species. The native bees visited fewer flowers within a plant and moved greater distances between plants than honeybees, so the native bees are expected to be more effective in promoting outcrossing. While honeybees were the most frequent visitors to flowers of all species, native bees made more visits to the common than the rare species (number of visits/10min; 0.65 ± 0.20 vs. 0.20 ± 0.09). These results suggest that the poorer reproductive success in the rare Persoonia species was associated with lower pollinator effectiveness.

If seed dispersal and seed predation influence distribution and abundance, rare species may be expected to have lower rates of seed removal and/or higher levels of seed predation than common congeners. I compared post-dispersal seed removal and seed predation in the two species pairs in two populations of each species. Population size differs between common and rare species, so I also compared seed removal and predation in both small and large populations of the common P. lanceolata. Seed 7

removal over a four-week period by macropods was significantly greater in populations of the two common species (>50% seeds/plant) than in their rare congeners (<25%).

There was no overall effect of rarity on seed predation by rodents, but significantly more seeds of the rare P. mollis subspecies maxima were eaten than those of the other three species. There was a significant effect of rarity on seed removal. High levels of seed removal were sustained in both small and large populations of the common P. lanceolata, suggesting that population size may not be contributing to the differences between these common and rare species. Therefore, limited seed dispersal could be a potential cause of rarity in Persoonia.

In this research, I identified some important similarities and differences between common and rare Persoonia species, which provide insights into the processes currently shaping their distribution and abundance. I found that the ability of plants to resprout after fire is associated with commonness/rarity, with rare species generally reliant on seeds to re-establish. Some common species are also unable to resprout, but they appear to have a greater ability to disperse pollen and seed. Rare species harbour greater levels of genetic variation within populations than common congeners. Despite these consistent differences detected between closely related common and rare species, it is difficult to distinguish whether they are causes and/or consequences of rarity. In fact, the current processes influencing the ability of plants to persist and disperse are likely to differ from those operating in historic times due to anthropogenic disturbances, including habitat fragmentation and the introduction of honeybees. While herbarium records and genetic markers give some indication that rare species are likely to have historically restricted distributions and common species appear to have rapidly colonized the landscape since the last glacial maximum, a detailed phylogeographic investigation is required to fully unravel the historic patterns. 8

These findings have important implications for the management of rare and threatened species. Firstly, the species identified here as rare should all be assessed for risk of extinction and considered for listing under national and state legislation, as they may be susceptible to the negative effects of stochastic demographic and genetic processes.

Secondly, most of the species currently listed as threatened are unable to resprout after fire, and therefore may be less persistent in the landscape and susceptible to localized extinction from frequent fire events. The ability to resprout after fire should be determined for all Persoonia I classified as rare. Thirdly, rare obligate seeders may have a reduced ability to colonize surrounding available habitat than common species, but existing populations appear to have maintained genetic variation. Therefore, all populations of rare obligate seeding Persoonia species should be of high conservation priority and efforts should focus on preserving these populations in the wild. 9

Acknowledgements I would firstly like to thank my supervisors David Ayre, Rob Whelan, Tony Auld and

Peter Weston for their consistent support and advice throughout this project. Their individual expertise and enthusiasm has inspired various aspects of this project and given me the energy to complete my thesis. It was a privilege to work with them all.

This project was supported by an Australian Research Council linkage grant to David

Ayre and Rob Whelan (C00001913), with logistical and financial assistance provided by the Department for Environment and Conservation (National Parks & Wildlife

Service and Botanic Gardens Trust divisions). Both my industry partners have far exceeded their requirements spelled out in the linkage agreement, and in many cases their staff have provided me with invaluable advice and resources. I would particularly like to thank (from the National Parks) Meagan Ewings for her work on the endangered

P. mollis subspecies maxima, David Keith for his expert assistance determining species distributional patterns, Ross Bradstock for discussion about fire, Andrew Denham and

Mark Ooi for their general advice and assistance. There are numerous people at the

Botanic Gardens I would like to thank including, Carolyn Porter for help in the DNA lab, Chris Allen for his GIS knowledge, Lesley Elkan for her beautiful drawings, Karen

Rinkel for assistance with editing dendrograms in Adobe Illustrator and Linn Linn Lee and Gary Chapple for their assistance extracting and screening the herbarium records. I must also say that without all the cake it may not have been possible to make it through the long days during the writing of this thesis.

I thank Siegy Krauss for technical advise on AFLPs, and providing the DNA and inspiration to explore seedling establishment at Sublime Point. It has been a pleasure to discuss Persoonia with him. 10

Special thanks to Tanya Llorens, Annette Usher, Craig Sherman and David Roberts for assistance in the Molecular Ecology Lab at UOW. The lab group all helped with technical issues, however their greatest contribution was to keep my spirits high by making jokes (often at my expense). Many of the friendships I have made at

Wollongong will stay with me throughout my life.

David McKenna and I have worked side by side though much of our PhD projects, sharing the same study species and sites. It was a pleasure to work with Dave and this project would have been worse off without him. I will enjoy working with him to analyse and write up our combined work for publications in the future.

Field assistance was provide by David Ayre, Rob Whelan, Tony Auld, Peter Weston,

Andrew Denham, Mark Ooi, David Field, Paul Thomas, Cairo Forrest, David Roberts, and numerous UOW students. Without their help I would still be out in the field today.

To all my friends and family that have put up with me during this long and often laborious process, thank you. Your support and encouragement is very important to me.

I’d also like to thank my devoted dog Zak for greeting me with enthusiasm and love after working in the lab and making me get out of the house for walks when I was writing at home. Finally, and most importantly, I would like to thank my wife, Rachel for her love and support. It will be a long time before I can repay her for waiting patiently for me to finish this thesis.

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TABLE OF CONTENT

PLANT RARITY: SPECIES DISTRIBUTIONAL PATTERNS, POPULATION GENETICS, POLLINATION BIOLOGY, AND SEED DISPERSAL IN PERSOONIA (PROTEACEAE). 1 ABSTRACT 4 ACKNOWLEDGEMENTS 9

Chapter 1 : General introduction 15

1.1. PLANT RARITY 16 1.2. GENETIC VARIATION AND STRUCTURING 17 1.3. BREEDING SYSTEM AND POLLINATION BIOLOGY 18 1.4. SEED DISPERSAL AND PREDATION 19 1.5. THE GENUS PERSOONIA 21 1.6 SELECTED COMMON AND RARE SPECIES 25 1.6.1 CLOSELY RELATED SPECIES PAIRS 25 1.6.2 FIRE AND RARITY 29 1.6.3 POLLINATION AND DISPERSAL 29 1.6.3 CAUSES AND CONSEQUENCES OF RARITY 30 1.7. AIMS AND OBJECTIVES 30

Chapter 2 : Plant rarity in the genus Persoonia (Proteaceae): exploring the importance of phylogenetic, geographic, environmental and life-history traits. 32

2.1 INTRODUCTION 32 2.2 METHODS 35 2.2.1. THE PHYLOGENY OF PERSOONIA 35 2.2.2. DISTRIBUTION, ABUNDANCE AND HABITAT SPECIFICITY 39 2.2.3. GEOGRAPHIC, PHYLOGENETIC, ECOLOGICAL AND ENVIRONMENTAL TRAITS 44 2.2.4. LOCAL ABUNDANCE IN THE SYDNEY REGION 45 2.3. RESULTS 46 2.3.1 GENERAL DESCRIPTION OF HERBARIUM DATA 46 2.3.2. DISTRIBUTION, ABUNDANCE AND ENVIRONMENTAL RANGE 47 2.3.3. CLASSIFYING THE FORMS OF RARITY 51 2.3.4. PHYLOGENETIC, GEOGRAPHIC, ENVIRONMENTAL AND LIFE-HISTORY TRAITS 69 2.3.4. THE BIOLOGY OF COMMON AND RARE TAXA 77 2.4. DISCUSSION 83 2.4.1. FORMS OF RARITY AND COMMONNESS 84 2.4.2. THREAT OF EXTINCTION 85 2.4.3. ENVIRONMENTAL AND ECOLOGICAL PATTERNS 86 2.4.4. LOCAL ABUNDANCE AND PATCHINESS 88 2.4.5. CONCLUSION 90

Chapter 3 : Does genetic variation and gene flow vary with rarity in obligate seeding Persoonia species (Proteaceae)? 91

3.1 INTRODUCTION 91 3.2. METHODS 93 3.2.1. SITE DESCRIPTION 93 3.2.2. AFLP PROCEDURE 95 3.2.3. GENETIC ANALYSIS 96 3.3. RESULTS 99 3.3.1 GENETIC VARIATION 99 3.3.2. GENETIC STRUCTURE 104 3.3. DISCUSSION 109 12

3.3.1. DOES GENETIC VARIATION RELATE TO PLANT RARITY? 109 3.3.2. DOES LIMITED GENE FLOW CAUSE RARITY? 112 3.3.3. CONCLUSION 114

Chapter 4 : Reproductive success and pollinator effectiveness differ in common and rare Persoonia species (Proteaceae). 115

4.1. INTRODUCTION 115 4.2. METHODS 118 4.2.1. STUDY SPECIES AND SITES 118 4.2.2. REPRODUCTIVE SUCCESS 120 4.2.3. EXPERIMENTAL POLLINATION 120 4.2.4. POLLINATOR OBSERVATIONS 123 4.3. RESULTS 125 4.3.1. REPRODUCTIVE SUCCESS 125 4.3.2. BREEDING SYSTEM 125 4.3.3. POLLEN LIMITATION 130 4.3.4. POLLINATION BEHAVIOUR AND MOVEMENT 130 4.3.5. POLLINATOR ABUNDANCE 131 4.4. DISCUSSION 134 4.4.1. RARITY AND REPRODUCTIVE SUCCESS 134 4.4.2. RARITY AND BREEDING SYSTEM 135 4.4.3. RARITY AND POLLINATION 135 4.4.4. FUTURE EFFECTS OF FRAGMENTATION 136 4.4.5 POLLINATOR DISRUPTION 137 4.4.6 CONCLUSION 138

Chapter 5 : Is rarity in fire-sensitive shrubs associated with seed dispersal and predation? 139

5.1. INTRODUCTION 139 5.2. METHODS 142 5.2.1. STUDY SPECIES 142 5.2.2. COMPARISON OF COMMON AND RARE SPECIES 143 5.2.3. PLANT SIZE, FRUIT QUANTITY, PLANT DENSITY AND VEGETATION COVER 146 5.2.4. EFFECT OF POPULATION SIZE 147 5.3. RESULTS 148 5.3.1. COMPARISON OF COMMON AND RARE SPECIES 148 5.3.2. PLANT SIZE, FRUIT QUANTITY, PLANT DENSITY AND VEGETATION COVER 151 5.3.3. EFFECT OF POPULATION SIZE 155 5.4. DISCUSSION 158 5.4.1. THE SPATIAL SCALE OF FORAGING ANIMALS 158 5.4.2. COMMON-RARE DIFFERENCES 159 5.4.3. EFFECT OF DISPERSAL ON RARITY 160 5.4.4. EFFECT OF PREDATION ON RARITY 161 5.4.5. CONCLUSION 162

Chapter 6 : General Discussion 163

6.1. BIOLOGY OF RARITY 167 6.2. GENETIC VARIATION AND STRUCTURING 170 6.3. BREEDING SYSTEM AND POLLINATION 171 6.4. SEED DISPERSAL AND PREDATION 174 6.5. CONCLUSIONS 176 REFERENCES 179 APPENDICES 199 13

TABLE OF TABLES

Table 2.1: Correlation matrix of the traits used to determine the form of rarity...... 50 Table 2.2: Classifying rarity in Persoonia using the ‘quartile’ method (Gaston, 1994, 1997a) based on the EOO k-NNCH and AOO 1 km grid...... 52 Table 2.3: Classifying Persoonia taxa into 8 forms of rarity based on EOO, AOO, and ENV range following (Rabinowitz, 1981)...... 55 Table 2.4: A comparison of several different classification systems for rarity in Persoonia; ...... 67 Table 2.5: The proportion of common and rare Persoonia taxa in geographic and phylogenetic groups.. 70 Table 2.6: The resprouting ability of Persoonia in relation to rarity...... 76 Table 2.7: The number of sites and plants for selected common, intermediate and rare Persoonia taxa in the Sydney region...... 78 Table 2.8: The number of current sites listed in the herbarium, recently discovered, and not relocated sites ...... 80 Table 3.1: The location, estimated population area, number of adult plants and voucher number for the study sites ...... 94 Table 3.2: The level of genetic variation within species, calculated for all four species (based on all 389 loci), for the two pairs of closely related common and rare Persoonia species...... 100 Table 3.3: The level of genetic variation within populations for two pairs of common and rare Persoonia species for each species separately...... 102 Table 3.4: The level of genetic variation within populations for two pairs of common and rare Persoonia species using only the 90 fragments that were common to all species...... 103 Table 3.5: The genetic and geographic distance between populations of common and rare Persoonia species...... 107 Table 4.1: The estimated population size, plant density, plant height and number of open flowers per plant for common and rare Persoonia species at the study sites...... 119 Table 4.2: Mixed model ANOVA for a comparison of the pollination treatments (Treatment being open, closed, self, cross) in closely related (Pair) common and rare species (Rarity) across populations (Site)...... 127 Table 4.3: The mean (SE) proportion of treated flowers that matured into fruits from the pollination experiment (open, closed, self and cross) for common and rare Persoonia species at the study sites...... 129 Table 4.4: Mixed model ANOVA for a comparison of honeybee (A) and native bee (B) visitation rates in closely related (Pair) common and rare species (Rarity)...... 132 Table 5.1: The location, estimated population area and size of the study sites selected for common and rare Persoonia species...... 145 Table 5.2: Mixed model ANOVA for a comparison of the proportion of seeds removed and eaten from experimental caches under adult plants after 4 weeks in closely related (Pair) common and rare species (Rarity) across populations (Site)...... 149 Table 5.3: The mean (SE) seed removal, and plant height of the two pairs of closely related common and rare Persoonia species...... 153 Table 5.4: Mixed model ANOVA for a comparison between large and small populations (Size) of the proportion of seeds removed and eaten ...... 156

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TABLE OF FIGURES

Figure 1.1: Map of the distribution of Persoonia across Australia...... 23 Figure 1.2: Line drawings of Persoonia lanceolata showing the key morphological traits (provided by the NSW National Herbarium)...... 24 Figure 1.3: Map of the greater Sydney district (Australia) ...... 27 Figure 1.4: Line drawings of the leaf and floral habit...... 28 Figure 2.1: A cladogram depicting the phylogeny of Persoonia...... 37 Figure 2.2: The relationship between distribution (EOO k-NNCH) and abundance (AOO 1 km grid) in the genus Persoonia (115 taxa)...... 53 Figure 2.3: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on EOO, AOO, rainfall, temperature, elevation, vegetation and geological range (continuous data)...... 57 Figure 2.4 (Part A): UPGMA dendrogram for Persoonia taxa showing the groupings for plant rarity based on the association between several continuous parameters ...... 58 Figure 2.5: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on EOO, AOO, ENV range (rank data)...... 60 Figure 2.6: UPGMA dendrogram showing the groupings for plant rarity based on the association between EOO, AOO, and ENV range (rank data). Part A showing clade with rare taxa...... 61 Figure 2.7: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping based on EOO, AOO, ENV range (rank data)...... 66 Figure 2.8: Environmental traits for Persoonia across Australia comparing common, intermediate and rare groups...... 72 Figure 2.9: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on the continuous data for several environmental traits (rainfall, temperature, elevation, vegetation and geology)...... 73 Figure 2.10: Plant attributes for Persoonia across Australia comparing common, intermediate and rare groups...... 75 Figure 2.11: Number of grid cells occupied by each taxon as a function of spatial-scale...... 82 Figure 3.1: AMOVA results for the two pairs of common and rare Persoonia species showing the partitioning of genetic variation within and among populations...... 105 Figure 3.2: The relationship between genetic differentiation and geographic distance among populations of the common P. lanceolata (black triangles) and the closely related rare P. glaucescens (grey squares)...... 108 Figure 4.1: The mean reproductive success (proportion of flowers that matured fruit) in plants (n=5) open to natural pollination for common and rare Persoonia species in the eight study sites ...... 126 Figure 4.2: The mean (± SE bars) proportion of flowers that matured into fruits for each of four pollination treatments in the common (open bars) and rare (closed bars) Persoonia species...... 128 Figure 4.3: The mean (± SE) number of native bee, honeybee and total insect visits per plant (per 10 minute observation) in common and rare Persoonia species...... 133 Figure 5.1: The proportion of seeds removed (a) and eaten (b) in caches under adult plants after 4 weeks, across replicate sites from two pairs of common and rare Persoonia species...... 150 Figure 5.2: The relationship between seed removal and plant height in common (filled diamonds) and rare (open squares) Persoonia species...... 152 Figure 5.3: The proportion of seeds removed (a) and eaten (b) in caches under adult plants after 4 weeks, across replicate sites from large and small populations of P. lanceolata...... 157

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Chapter 1 : General introduction

An understanding of rarity can provide important insights into the evolutionary processes of colonization and extinction, which are key determinants of population dynamics (Eriksson, 1996), population genetic structure (Davies et al., 2004), and species distributional patterns (Wilson et al., 2004). In terrestrial flowering plants, which are mostly sessile organisms, pollen and seed dispersal facilitate the exchange of genes between local populations (Ouborg et al., 1999), while seed dispersal is usually the mechanism behind the establishment of new populations. The persistence of plant populations is partially dependent on life-cycle characteristics capable of buffering unfavourable environmental conditions (Eriksson, 1996). Such characteristics include the ability to resprout after disturbance, persistent soil stored seed-banks, and the availability of genetic variation for selection to act upon given environmental change

(Frankham et al., 2002). The abundance and distribution of populations in the landscape, however, reflects the complex interplay between the capacity of plants to disperse and persist, and the impacts of natural and anthropogenic disturbances.

All landscapes throughout the world are affected by disturbances to varying degrees.

Some are affected by low-intensity disturbances that occur relatively infrequently (e.g. a tree falling in a temperate forest), while others experience frequent disturbances of high- intensity (e.g. wildfires in fire-prone habitats). At the same time, landscapes are being altered through clearing and degradation as a result of agricultural and urban developments, leading to loss of habitat and fragmentation of populations (Young and

Clarke, 2000). As a result, most landscapes represent a mosaic of ‘patches’ at various stages of successional growth, from recently disturbed to old growth vegetation found in a range of sizes and levels of isolation. This has important consequences for the ability 16

of plants to disperse between ‘patches’ and the long-term persistence of ‘patches’ in fragmented landscapes.

Species extinctions are occurring at an alarming rate, primarily as a result of land clearing and habitat degradation (IUCN, 1994). In an attempt to curb the rate of extinction the World Conservation Union (IUCN) ‘Red List’ was developed to highlight those species likely to become extinct given current management practices (IUCN,

1994, 2003). Central to the categories and criteria used by the IUCN to determine the threat of extinction is the notion that rarity is an inevitable precursor to extinction. This principle has been adopted by several countries around the world, including Australia, to determine the threat of extinction. Given the scale of the perceived problem of species decline, with 1302 plant species listed as threatened in Australia alone (EPBC,

1999), an understanding of the biology of rarity is essential.

1.1. Plant rarity Numerous definitions of rarity exist in the biological literature (Mayr, 1963; Drury,

1974; Rabinowitz, 1981; Gaston, 1997b; Fiedler & Ahouse 1992). The majority of definitions include at least one parameter based on abundance or distribution (Gaston,

1997a), while others use habitat specificity, in addition to abundance and distribution, to differentiate several ‘forms of rarity’ (Rabinowitz 1981). It is generally accepted that rare species have restricted geographic distributions and tend to be locally sparse

(Gaston, 1997a). ‘Common’ and ‘rare’ species need to be clearly defined at the beginning of any study of rarity, in order to provide a strong foundation for the interpretation of patterns and an understanding of processes that cause rarity. In this thesis, I define commonness/rarity based on distribution, abundance and environmental range (see Chapter 2 for a full discussion of my rationale in using this definition). 17

There are a growing number of studies in the scientific literature that explore the biology of rare plants. It is seldom possible to directly compare the results of these studies, however, because rarity has been defined in a variety of ways and studied at a range of spatial scales (Gaston and Kunin, 1997b). As a consequence, few general trends have emerged (Murray et al., 2002a). It is becoming clear that comparisons of the attributes of closely related ‘common’ and ‘rare’ species are required to help address our lack of understanding of rarity (Kunin, 1997a). There are, however, relatively few such studies, and those that do exist are usually non-experimental (e.g. Eriksson and

Jakobsson, 1998; Hegde and Ellstrand, 1999) and/or limited to a small number of species (e.g. Banks, 1980; Sydes and Calder, 1993; Witkowski and Lamont, 1997).

1.2. Genetic variation and structuring Genetic variation may be a key predictor of the long-term persistence of populations, as it should determine a population’s capacity for adaptive change (Saccheri et al., 1998).

Population genetic processes, particularly genetic drift and gene flow, determine the amount of genetic variation within populations and genetic divergence among populations. Genetic drift is the random change in the frequency of alleles due to small effective population sizes, producing genetic differentiation among populations and loss of genetic variation within populations (Wright, 1931). The movement of alleles between populations, termed gene flow, can alter the allelic frequencies of a population, and tends to reduce genetic divergence among populations (Russell, 1998). Natural selection also alters the genetic variation found within populations by selecting for individuals with greater reproductive success and fitness (Frankham et al., 2002).

To a large extent, the amount of genetic drift and gene flow a population experiences depends on its size and degree of isolation. The effect of drift is much greater in small populations than in large ones, in which allele frequencies are relatively stable over time 18

(Frankham et al., 2002). Gene flow typically follows the simple ‘isolation by distance’ model (Rousset, 1997), such that geographically close populations are expected to be genetically more similar than more distant populations. While historical barriers to dispersal complicate this pattern, the intensity of gene flow is governed by the ability of plants to disperse pollen and seed. Small isolated populations will theoretically lose genetic variation and diverge genetically as a result of random drift and limited gene flow (Wright, 1931, 1951). Therefore, rare species with small isolated populations are expected to have low levels of variation and limited ability to adapt to changing environmental conditions (Loveless and Hamrick, 1984; Cole, 2003).

1.3. Breeding system and pollination biology Reproductive success is crucial for the persistence of populations (Rabinowitz et al.,

1989), especially for plants reliant on seed to re-establish populations after a major disturbance (e.g. obligate seeders in fire prone habitats). The reproductive success of flowering plants is largely determined by their breeding system and pollination biology.

Plant breeding systems have been shown to be predominantly selfing or outcrossing with fewer species having intermediate levels of outcrossing (Lande and Schemske,

1985; Barrett and Harder, 1996). These represent two stable evolutionary states of the breeding system, determined by the conflicting forces of inbreeding depression and reproductive assurance (Lande and Schemske, 1985). In historically large, outcrossing populations, selection will be for the maintenance of outcrossing to avoid substantial inbreeding depression. On the other hand, selection will favour selfing in populations that experience pollinator failure or population bottlenecks, providing reproductive assurance and reducing the level of inbreeding depression (Schemske and Lande, 1985).

The breeding system of plants is also likely to influence their capacity to establish 19

populations after long-distance dispersal events, with selfing species capable of sexual reproduction in the absence of compatible mates and effective pollinators (Baker, 1955).

For most flowering plants, sexual reproduction cannot occur without the movement of pollen among flowers, the pollen vectors being either abiotic (water, wind etc.) or biotic

(animals). For plants, animal pollinators play an important role in the movement of pollen between flowers both within and among flowering plants, thereby determining the availability of potential mates and influencing the plant’s reproductive success

(Talavera et al., 2001). Although many plants receive visits from several animals foraging for floral resources (commonly pollen and/or nectar), not all floral visitors are effective pollinators. Some animals are specialist-pollinators, being well adapted to forage for the floral resources of a particular plant species (or group of related species), which in turn receives compatible pollen for sexual reproduction. In contrast, generalist- pollinators utilize resources from a wide range of flowering plants, and often have characteristics that enable them to forage extensively on different species without being well suited to pollinate any particular species (Thostesen and Olesen, 1996; Waser et al.,

1996). For the multitude of flowering plants that reproduce sexually and require pollination by animals, their reproductive success, and hence their abundance, must be at least partially dependent on their breeding systems and pollinator composition.

Variation in plant breeding systems and the attractiveness of plants to pollinators may therefore be important determinants of rarity.

1.4. Seed dispersal and predation The importance of seed dispersal and predation in affecting population dynamics and in shaping the distribution and abundance of plants is well established (Loveless and

Hamrick, 1984; Cain et al., 1998; Rey and Alcántara, 2000; Kameyama et al., 2001).

Seed dispersal is the one stage in the life-cycle of most plants that potentially allows 20

them to travel long distances (Bullock and Clarke, 2000), and for populations to expand or move. Long-distance dispersal events are critically important for the colonization of islands, migration and metapopulation biology, but are inherently hard to detect or measure (Cain et al., 2000). In addition, seed dispersal is a central process in re- colonization after disturbance events (Bradstock et al., 1996). The persistence of populations may be influenced by seed predation, which limits the availability of seeds for recruitment (Auld and Denham, 2001), and may represent a significant loss of resources. Finally, the intensity of seed dispersal and predation at both a local and regional scale can determine the importance of colonization and extinction within a metapopulation framework (He et al., 2004). Seed dispersal and predation, therefore, may be important determinants of plant rarity.

The species composition and behaviour of frugivorous animals play an important role in the dispersal and predation of seeds from fleshy-fruited plants (Debussche and

Isenmann, 1989). Animal foraging behaviour at local and regional spatial scales is influenced by the quantity and quality of fruits (Curran and Leighton, 2000). Foraging theory predicts that animals optimise the expenditure of energy used to collect and process fruits (Howe, 1986). Foraging efforts should typically be minimized in large populations with high densities of fecund plants because fruiting plants would be easily detected and animals could consume more fruits. This may result in a high proportion of fruits being dispersed or eaten if fruits are regionally scarce; however, the abundance of fruits may exceed the consumption capacity of available frugivores, leading to low levels of dispersal or predation. Conversely, plants in small populations may not be detected by animals foraging at regional scales and would be reliant on animals present in the local area for seed dispersal. The importance of plant and population attributes in determining seed dispersal and predation (which in turn have direct implications for 21

plant rarity) is, therefore, dependent on the scale and intensity of animal foraging patterns and their interaction with fruit production patterns (Hewitt and Kellman, 2002).

1.5. The genus Persoonia I selected the plant genus Persoonia in which to investigate the biology of rarity, with an emphasis on the processes of colonization and extinction, because species in the genus have superficially similar floral and fruit traits but differ dramatically in their distribution and abundance.

The genus Persoonia is in the tribe Persoonieae, subfamily Persoonioideae, family

Proteaceae (c.80 genera). The Proteaceae are largely a Southern Hemisphere family with Australia (46 genera and almost 1100 species) and southern Africa (14 genera and c.387 species) as its centres of greatest diversity. Persoonia is a genus of 100 species, all endemic to Australia (Weston, 1995). Although it can be found in all the states and territories, only 16 species occur in areas that receive <25 mm annual rainfall and only 2 of these have wholly arid distributions (Weston, 1995). This creates a biogeographical division between species in western and eastern Australia; only P. falcata extends east- west across Australia (in northern regions where rainfall is higher than central southern regions). South-eastern and south-western areas of Australia have the greatest diversity for the genus (where 49 and 40 species occur respectively) (Figure 1.1).

The genus consists of shrubs and small trees, with flowers typically comprising four, symmetrical, yellow, recurved tepals and stamens of similar length, and a central carpel with a stigma terminating the style, above an ovary containing 1 or 2 ovules (although sometimes flowers are zygomorphic, tepals red to white, and anthers white to yellow with white tips). Plants produce fleshy drupes containing a single smooth pyrene with a thick woody endocarp surrounding 1 or 2 seeds with a variable number of cotyledons

(2-9) (Weston, 2003). The leaves are highly variable in size (range from 0.75-35 cm in 22

length) and shape (from linear to orbicular, flat to terete in cross-section, with flat, recurved or revolute margins) (Weston, 1995) (Figure 1.2).

23

Figure 1.1: Map of the distribution of Persoonia across Australia. Data compiled from national herbarium records. 24

Figure 1.2: Line drawings of Persoonia lanceolata showing the key morphological traits (provided by the NSW National Herbarium). a. branchlet (scale bar = 30 mm), b. flower (6 mm), c. flower, with one tepal removed (6 mm), d. gynoecium (6 mm), e. ovary with half of ovary wall removed (3 mm), to show ovules, f. stigma (3 mm), g. ovary, hypogynous glands and receptacle (3 mm), h. tepal and anther, adaxial view (3.75 mm), i. tepal and anther, lateral view (3.75 mm), j. fruit with half exocarp and mesocarp removed, to show pyrene(15 mm), k. fruit (15 mm). 25

1.6 Selected common and rare species Comparisons of closely related congeners with widespread and restricted geographic distributions can be used to understand the potential causes of rarity (Kruckeburg and

Rabinowitz, 1985), minimizing the confounding effects of disparate phylogenetic histories (Silvertown and Dodd, 1996). I adopted this powerful approach to explore the patterns of plant rarity in Persoonia species, and establish comparative experiments to investigate the processes shaping their distribution and abundance.

1.6.1 Closely related species pairs

I selected two pairs of closely related taxa (hereafter referred to as species), based on morphological and genetic characters (Weston, 1995, 2003), with sharply contrasting local abundances and geographic distributions. One species pair was Persoonia mollis subspecies (ssp.) nectens S.L. Krauss & L.A.S. Johnson (common) and P. mollis ssp. maxima S.L. Krauss & L.A.S. Johnson (rare). The other pair was P. lanceolata

Andrews (common) and P. glaucescens Sieber ex Spreng (rare). In selecting these species, I defined rarity based on the current knowledge of their local abundance and geographic distribution. Therefore, the rare species have relatively small standing populations and restricted distributions, while the common species have variable population sizes that include some large populations (>1000 plants) and widespread distributions (>500 km2).

Persoonia mollis is a species complex that has been divided into nine subspecies based on morphological, genetic and geographic variation (Krauss and Johnson, 1991; Krauss,

1996, 1998). Persoonia mollis ssp. maxima has been classified as endangered in New

South Wales, under the Threatened Species Conservation Act 1995, and nationally, under the Environment Protection and Biodiversity Conservation Act 1999. It has a restricted geographic distribution (~40 km2 extent of occurrence) (Figure 1.3). 26

Persoonia mollis ssp. maxima is allopatric to, and the sister lineage of, the rest of the P. mollis complex and so could justifiably be recognised at species rank (Krauss 1998). It is separated by more than 75 km from subspecies nectens, which is common and relatively widespread (~1100 km2 extent of occurrence) (Figure 1.3). Both subspecies grow in dry to wet sclerophyll forests on sedimentary substrates (usually sandstone).

Persoonia glaucescens has been classified as endangered in New South Wales

(Threatened Species Conservation Act 1995) and nationally (Environment Protection and Biodiversity Conservation Act 1999). It has a relatively restricted geographic distribution (~500 km2 extent of occurrence) (Figure 1.3), which overlaps that of its closely related congener, P. lanceolata, which is common and widespread (~13,300 km2 extent of occurrence) (Figure 1.3). Both species grow in dry sclerophyll forests on sandstone, where they sometimes co-occur, but P. lanceolata is also found in coastal heath (Weston, 1995).

These species can be identified in the field based on floral and leaf characters.

Persoonia mollis ssp. nectens and Persoonia mollis ssp. maxima are both erect shrubs, which do not co-occur, and the main feature that differentiates them morphologically is the length and density of hairs on flower buds and leaves. The morphology of P. lanceolata and P. glaucescens is similar and they co-occur in the southern highlands of

NSW; the main diagnostic feature is that the new leaves of P. glaucescens are glaucous

(Figure 1.4). 27

Figure 1.3: Map of the greater Sydney district (Australia) showing the geographic distribution of P. mollis ssp nectens, P. mollis ssp maxima, P. lanceolata and P. glaucescens. The records were compiled from the NSW National Herbarium. Filled symbols represent populations sampled for genetic analysis (Chapter 3). 28

Figure 1.4: Line drawings of the leaf and floral habit of P. mollis (a), P. mollis ssp. nectens (b), P. mollis ssp. maxima (c), P. glaucescens (d), and P. lanceolata (e). Drawings care of the NSW National herbarium. 29

1.6.2 Fire and rarity

Much of Australia’s native vegetation is prone to re-occurring fires (Keith, 1996). Many

Persoonia species occur in fire-prone habitats (found on ridges in sandy soils; Benson and McDougall, 2000), with some species resprout after fire, while others are obligate- seeders (i.e. adult plants are killed by fire and depend on a soil stored seed-bank for their regeneration). Frequent fires may result in reduced population sizes and reduced plant densities, increased population fragmentation and even localized extinctions, especially for obligate seeders (Bradstock et al., 1996; Keith, 1996). Of the 16

Persoonia species that are listed as threatened under the various state government legislations (ten of which are listed nationally; EPBCA, 1999), all except two species are obligate seeders, (as compared to 33/115 obligate seeders in the group as a whole; see Appendix 1) which suggests that their response to fire may have caused declines in population sizes. These fire sensitive species rely on seed stored in the soil to re- establish after fire, which kills standing plants. Fire appears to trigger the dormant seeds to germinate, but plants are slow to mature and replenish the seed-bank (6-7 years to flower; Myerscough et al., 2000) leaving populations at risk of extinction from repeated fire events in close succession. However, some obligate-seeding Persoonia species are common and widespread, so this characteristic alone cannot explain rarity.

1.6.3 Pollination and dispersal

My study compares species with similar life-history traits (habitats, plant structure and gross fruit and flower morphology) and phylogenies (Weston, 1995; Krauss, 1998).

These species have similar floral attributes (colour, size and shape) sharing the same suite of native bee pollinators (Bernhardt and Weston, 1996; Wallace et al., 2002). All

Persoonia species produce fleshy fruits capable of being dispersed by large mammals and birds (Benson and McDougall, 2000) although most seeds are expected to 30 germinate within close proximity to parent plants. Rodents are the main seed predators

(cf. Auld and Denham, 1999, Tony D. Auld pers. comm.).

1.6.3 Causes and consequences of rarity

The causes and consequences of rarity are almost certainly complex, and studies on rare taxa should be conducted at multiple spatial scales (Hartley and Kunin, 2003). This is particularly important when exploring the extinction risk associated with plant rarity

(IUCN, 2001), given that the importance of factors influencing colonization ability and population persistence may vary from local to regional scales (Froborg and Eriksson,

1997). There are many plausible explanations for differences in rarity among the obligate seeding species; however, given their reliance on seed production, it may be that they differ in their ability to disperse and/or persist in the landscape.

1.7. Aims and objectives My main objective in this study was to gain an understanding of the biology of rarity in

Persoonia by investigating ecological processes that are relevant to colonization and extinction. The approach I have taken is to focus on a plant genus that displays a wide range of geographic distributions among species, several of which are of conservation interest and require biological information to contribute to future management. I started the study with a broad-scale comparison of all 115 Persoonia taxa, for which I defined the level of rarity and explore the association between rarity and phylogenetic, geographic, environmental and life-history traits (Chapter 2). In the following three chapters (Chapters 3, 4 & 5), I focused on comparing the differences and similarities within two pairs of closely-related common and rare species. Chapter 3 investigated the levels of genetic variation and structuring, while the breeding system and pollination are explored in Chapter 4, and seed dispersal and predation are examined in Chapter 5. 31

The specific aims of my four data chapters are as follows:

Plant rarity (Chapter 2) • My main aim was to define rarity for taxa in the genus Persoonia (Proteaceae) to explore the relationship of phylogenetic, geographic, environmental and life- history traits. For selected common and rare species I aimed to investigate the contribution of historical processes and fragmentation effects in determining current distribution patterns.

Genetic variation and structuring (Chapter 3) • I aimed to determine the level of genetic variation within and among populations of common and rare species to infer the ability of plants to persist and disperse in the landscape.

Breeding system and pollination (Chapter 4) • I aimed to determine the breeding system, pollination and reproductive success in common and rare species. By exploring pollinator behaviour I aimed to gain an indication of pollen limitation and dispersal.

Seed dispersal and predation (Chapter 5) • I aimed to determine the proportion of seeds removed and eaten for common and rare species, and explore the association with plant, site and population attributes.

Finally, in Chapter 6, I combine the results obtained in Chapters 2-5, for the comparisons of common and rare species, in an attempt to gain an understanding of the biology of rarity in Persoonia. The management implications of these findings for rare and threatened species are also discussed.

32

Chapter 2 : Plant rarity in the genus Persoonia (Proteaceae): exploring the importance of phylogenetic, geographic, environmental and life- history traits.

2.1 Introduction Understanding the biology of rarity is critically important for the conservation of biodiversity in the long-term. The role of evolutionary processes and more recent anthropogenic effects in shaping the current distribution and abundance of species has significant implications for genetic composition, pollinator associations and dispersal ability (Jacquemyn et al., 2004; Llorens et al., 2004). However, before patterns of distribution and abundance can be interpreted in relation to the processes that may cause rarity and potentially threaten species with extinction, a clear working definition of what constitutes rarity is required.

Many different definitions of plant rarity have been used in the literature, despite attempts over recent decades to produce a universal definition (Drury, 1974;

Rabinowitz, 1981; Gaston and Kunin, 1997a). Numerous forms of rarity have been recognized based on level of endemism, geographic distribution, rank abundance, local abundance, population size, habitat specificity and environmental range (Gaston and

Kunin, 1997a). This diversity of definitions has created a problem in comparing studies and thereby establishing general patterns. To overcome this, researchers need to clearly specify the form of rarity and how it was derived. 33

Natural-history collections in museums and herbaria contain vital information for biodiversity research. These collections, accumulated over long periods, can produce huge amounts of data that can provide a historical perspective (Ponder et al., 2001;

Skelly et al., 2003; e.g. O'Connell et al., 2004). Unlike many other databases, they are curated by botanical experts and the material they contain allows the maintenance of data integrity in the future. Collectively, the specimen-based data may be used to describe the distribution and abundance of taxonomic units of interest (Joye et al., 2002;

Reutter et al., 2003; Hunter, 2005). This provides a possible way to determine the level of commonness/rarity (Chapter 1, Gaston, 1994, 1997a) and thus set priorities for actions designed to achieve conservation objectives (IUCN, 1994, 2003). However population decline is an essential component of the threat of extinction.

Inherent shortcomings in the data include the ad hoc nature of the collections, presence- only data, biased sampling, and large collection gaps in time and space (Ponder et al.,

2001). Specimen data infrequently reveals anything about local abundance or sampling effort, both of which are important considerations in rarity assessment. The quality and quantity of collections are dependent on the area and taxonomic group under investigation, such that taxa in remote areas and those that are difficult to detect or sample may be under represented. In addition, records are often not electronically data- based, thus restricting access. Older records are typically imprecise and patchy, making it difficult to gain an accurate estimate of historical distributions and making deductions about trends problematic. Inferences about species distributional changes require accurate present-day information on distribution combined with an understanding of recent patterns of change in land use.

Determining the distribution and abundance of species is much more feasible for plants, which “stand still and wait to be counted” (Harper, 1977). Long-lived plants provide the 34 opportunity to compare historic records to current stands, by resurveying sites and assessing the presence/absence of species (Skelly et al., 2003). With this in mind, I selected the genus Persoonia (Proteaceae) to undertake an investigation on the biology of plant rarity. Representatives of this genus are obvious components of the Australian flora (particularly in sclerophyllous vegetation; Weston, 1995). The genus has been a priority group for the ‘Australian Virtual Herbarium’ project (www.chah.gov.au/avh/), and all herbarium records have therefore been data-based. Despite being absent in the arid centre of Australia, Persoonia species occur across much of the continent under a variety of environmental conditions (Chapter 1). Species within this genus also display several variable life-history traits, which may be associated with their ability to persist in harsh environments (e.g. resprouting ability).

Here I use two prominent methods (Rabinowitz, 1981; Gaston, 1997a), and subsequently develop and test a new method using an ordination approach, with the aim of classifying commonness/rarity for all Persoonia taxa using existing herbarium data. I aimed to; (1) determine general patterns of rarity and their associations with phylogenetic and geographic groupings, (2) characterize the environmental and life- history traits of common and rare taxa, and 3) evaluate the effectiveness of three rarity schemes in assessing plant rarity from herbarium data.

Based on the results of these investigations, I selected two pairs of closely-related common and rare taxa in the Sydney region, and determined their present-day distributions and abundances. The primary objectives here were to detect associations of biotic and abiotic factors with commonness/rarity, and determine the historical patterns of distribution and anthropogenic fragmentation processes. 35

2.2 Methods 2.2.1. The Phylogeny of Persoonia

Persoonia species are currently described on the basis of their morphology (Weston,

1995, 2003), and several have been further divided into subspecies. I recognize six species as warranting subdivision into subspecies (giving 115 taxa). I have treated P. hirsuta as a single taxon, despite it being previously recognized as consisting of two subspecies (ssp. hirsuta, ssp. evoluta and intermediates between them) (Weston, 1995), as a recently conducted, unpublished morphometric study concluded that there was no support for these divisions (Peter H. Weston unpublished data). The core distribution of

Persoonia asperula is found in New South Wales (NSW), but there is a disjunct population in Victoria about 250 km west-south-west of the core distribution consisting of plants that are morphologically distinct (Peter H. Weston pers. comm.). Therefore, I have divided P. asperula into two separate subspecies; the Victorian population named ssp. nov. 'watchtower' and the NSW population named ssp. nov. ‘asperula’. All other taxa are as described by (Weston, 1995, 2003), although it should be noted that the geographic boundaries between some closely-related taxa are unclear (particularly for

P. confertiflora and P. silvatica, as well as P. hexagona and P. bowgada). The P. mollis species complex, as described by (Krauss and Johnson, 1991), may require the inclusion of a new subspecies from the south coast of NSW (as specimens from the Bega-Eden area do not fit with the morphological description for the current subspecies and are well outside the published geographic range). A thorough morphometric and phylogeographic investigation is needed for these relationships to be determined.

While the phylogeny of Persoonia is not well resolved at the species-level, 13 well- supported clades can be recognized within the genus, based on cladistic analysis of morphological and genetic data (Weston, Porter and Rymer, unpublished analysis) 36

(Figure 2.1 shows cladogram based on ITS sequence data). The ‘lanceolata’ clade, consisting of 71 taxa, is by far the largest and can be further divided into a south- western clade, nested within a predominantly eastern grade (10 and 61 taxa respectively) (extrapolated ITS cladogram using morphology to include all Persoonia taxa; Appendix 1; Weston, 2003). Apart from the ‘south western clade’ and P. elliptica

(also from south western Australia), all taxa in the ‘lanceolata’ clade occur in eastern

Australia, half of which are found in the Sydney region. Indeed, P. laurina is the only

Sydney species not in the ‘lanceolata’ clade. As a result of the relatively high levels of research activity in the Sydney region, there is much more ecological and taxonomic information available on the Sydney Persoonia taxa, compared with the remaining taxa in the ‘lanceolata’ clade (Weston and Johnson, 1991; Benson and McDougall, 2000).

Species relationships can be determined on the basis of this information, providing a means to select taxonomic units that are very closely-related (possibly sister taxa) that differ in selected ecological characteristics. 37

P. muelleri. muelleri muelleri (5) Garnieria spat Acidonia microcarpa P. bowgada P. acicularis P. filiformis P. angustiflora rudis (10) P. scabra P. striata P. sulcata P. quinquenervis P. rudis P. tropica P. elliptica P. pinifolia P. hindii P. linearis P. isophylla P. katarae P. lanceolata P. microphylla P. nutans P. chamaepitys P. pauciflora P. hirsuta P. amaliae P. stradbrokensis P. bargoensis P. glaucescens lanecoata (6) P. levis P. oblongata P. media P. subtilis P. baeckeoides P. pungens P. coriacea P. cymbifolia western (6.5) P. dillwynioides P. flexifolia P. helix P. mollis. mollis P. mollis. maxima P. laurina laurina (2) P. silvatica P. longifolia P. graminea longifolia (3) P. chapmaniana P. pentasticha P. biglandulosa P. stricta P. saundersiana P. hakeiformis stricta (11) P. falcata P. teretifolia P. comata saccata (10.5) P. saccata Toronia toru P. brevirhachis rufiflora (1) P. rufiflora Plac. cori Bellendena con

Figure 2.1: A cladogram depicting the phylogeny of Persoonia based on ITS sequencing, constructed using the parsimony criterion and a heuristic search in PAUP*. Clades are based on molecular and morphological data and represented by lines grouping taxa into clades (names follow Weston 2003). 38

2.2.1. Herbarium records Between February and March 2005, I obtained records for the genus Persoonia from all major Herbaria in Australia (Adelaide 385 records, Brisbane 1067, Canberra 1763,

Hobart 571, Melbourne 1893, New South Wales 4171, and Perth 1764), yielding a total of 11,614 records. Each record included the following fields: accession number, species, subspecies, specific locality, latitude, longitude, collection date, collector’s name and number, determiners name and date, habitat and notes, but not all fields were filled for each record.

I deleted records that had no information in the species field, and records with imprecise or vague locality descriptions and records where the geoaccuracy (a measure of imprecision) was greater than 1 km. Duplicate records (i.e. when a collector made multiple acquisitions from the same plant, with identical collector’s name and number) were deleted using a PEARL script in UNIX (written by Gary Chapple, NSW National

Herbarium, Botanic Gardens Trust, Sydney). Preference was given to keeping records with latitude/longitude (lat/long) data (maximizing the data available to determine species distributions) and that were taxonomically determined by Peter H. Weston

(PHW, who is an expert on the taxonomy of the genus, Weston, 1995, 2003). Records were added to the data set in the following order of priority: (1) lat/long data, specimen determined by PHW, (2) lat/long data, determined by other, (3) lat/long data, with no determination, (4) no lat/long data, determined by PHW, (5) no lat/long data, determined by other, (6) no lat/long data, with no determination. Once a record was added, all other duplicates were deleted from the data set. Records that did not have the complete collector’s details were checked further for duplicates and I used a database function to discard records with identical species, specific locality, and collection date fields. I then manually searched through the data set to identify and delete additional 39 duplicate records that were clearly from the same collection despite having slightly different wording or formatting.

For records that did not have lat/long data, I used the information in the specific locality field to determine the corresponding latitude and longitude (in datum AGD 1966 decimal degrees format) using OziExplorer version 3.95.4h with assistance from the gazetteer (GAZ2004). Given the time constraints, lat/long data were not added to all records (>1000 records lacked lat/long data) but instead I set a minimum standard of requiring at least 90% of records to have lat/long data for those taxa with >20 records and 100% of records to have lat/long data for those taxa with <20 records. This was done by working through the data set (sorted by species and subspecies) on a taxon-by- taxon basis until I reached the relevant threshold.

Once the records were compiled, I scrutinized the data set for geographic accuracy by cross-checking that the description of the location corresponded to the lat/long, and checking the validity of any outlying (or disjunct locations) against the known species ranges (Weston, 1995). I deleted from the data set any records that appeared to have incorrect determinations (Peter Weston pers. comm.), or had locality descriptions that were obviously inaccurate (based on geographic and environmental information) or were imprecise (>1000m geoaccuracy). The final data set comprised 8,045 records, including 415 records with missing lat/long data (55 taxa with 100%, 24 taxa with 100-

95%, and 36 taxa with 95-90% of the records with lat/long data). The 7,630 records with lat/long data were used to estimate the distribution, abundance and habitat specificity for taxa in the genus Persoonia.

2.2.2. Distribution, abundance and habitat specificity

For each Persoonia taxon, I estimated several measures related to rarity. I used extent of occurrence (EOO sensu IUCN, 2001)) to estimate the geographic distribution, area of 40 occupancy (1 km grid AOO sensu IUCN 2001) as a surrogate/index of the abundance of plant patches, and environmental range (ENV range) as an estimate of habitat specificity of the taxon. I used a Geographic Information System (GIS) spatial analysis

(ArcView v3.3) to estimate the EOO, AOO and ENV range. Data were re-projected from Lat/Long to Lamberts conformal datum (using the National Parks & Wildlife

Service ‘Projection’ extension for ArcView version 3), to enable direct estimation of the distance/area between points in metres.

I used two methods to estimate the EOO, the ‘traditional’ convex-hull method and the recently developed nearest neighbour convex hull method (k-NNHC; Getz and

Wilmers, 2004). Convex-hulls are commonly used for determining risk of extinction

(through Criterion B Geographic Distribution of the IUCN Red List Categories; IUCN

2003) by creating the smallest polygon in which no internal angle exceeds 180 degrees and which contains all the sites of occurrence (IUCN, 2003). This method has been criticized because it includes areas known not to be part of the taxon distribution, particularly when the points are in a crescent shape or have disjunct distributions

(Burgman and Fox, 2003; but see IUCN, 2003 for other ways of dealing with disjunct populations). The k-NNCH method overcomes this problem by using multiple nearest neighbour convex hulls that are merged to create a single polygon (Getz and Wilmers,

2004). The polygon can allow for disjunct distributions and numerous different shapes in species distribution, however it tends to include areas between isolated points at the expense of areas adjacent to densely clustered points. The difficulty with this method is knowing how many nearest neighbour points (k) to use to accurately estimate the distribution of the taxon. I applied it here using a range of values for k (from 3 to 45 nearest neighbours) and then selecting the most appropriate polygon (Getz and 41

Wilmers, 2004), which I subjectively determined to be the best representation of the taxon distribution.

The AOO is highly dependent on the spatial scale of the grid used. I used three different grid sizes; (1) fine scale 1 km, (2) medium scale 10 km, and (3) coarse scale 100 km grid cells. The fine scale is limited by the geoaccuracy of the herbarium data, and here it is assumed to represent the general size of a ‘patch’ or ‘population’ (based on habitat and dispersability; Tony Auld pers. comm.). The medium scale represents a grid size that is assumed to contain all but the most extreme long-distance dispersal events in a

‘metapopulation’, while landscape processes (e.g. wildfires) may operate to the coarse scale. David Keith (NSW Department of Environment and Conservation) developed an extension for ArcView version 3 (named ‘SpRange’), which I used to calculate the number of occupied grid cells. This extension uses the ArcView function ‘spatial analyst’ to convert the point data to occupied grid cells across the range of the taxon. A limitation of this extension is that the grid is fixed at the southeast corner of the box representing the taxon’s range, potentially over or under-estimating the area of occupancy depending on the distribution of points. However, this problem is largely overcome by using several spatial scales.

I used several environmental traits to estimate the ENV ranges of taxa, including temperature, elevation, rainfall, vegetation and geology. I obtained these national GIS data from the Australian Government Bureau of Meteorology (provided on CD as 2.5 km grid data based on 1960-1991; national mean annual rainfall, maximum and minimum annual average daily temperature) and Geosciences Australia (ArcView shape files downloaded from www.ga.gov.au; Vegetation - Post-European Settlement 1988,

National Geology, and Digital Elevation Model 250m grid). I appended these environmental traits to the data table for each point location (using the extension 42

‘MxbSample’ provided by the NSW National Parks & Wildlife Service). For each taxon, I determined the temperature, elevation and rainfall range (by calculating the difference between the minimum and maximum values from the records), and estimated the vegetation and geology range by counting the number of different types in which it was found to occur.

I defined the form of rarity for each Persoonia taxon in three ways; firstly by using the quartile method described by (Gaston, 1997a), secondly by classifying the taxa into the

8 forms of rarity developed by Rabinowitz (1981), and thirdly by the use of ordination and hierarchical classification methods.

Gaston (1994, 1997a) gave an overview of a variety of definitions of rarity, and strongly advocated the ‘quartile’ definition of rarity. This method classifies the 25% of species in an assemblage or taxonomic group with the lowest range sizes or abundances as rare. I used k-NNCH to estimate the EOO for each taxon, because it provided a more realistic estimate of geographic distribution (without dramatically altering the rank order compared to the ‘traditional’ convex-hull method). I used the 1km grid to estimate the

AOO for each taxon, because it was the smallest scale available and provides a reasonable approximation of the number of plant patches (or potential populations). I acknowledge that AOO may not represent ‘local abundance’ as Gaston (and Rabinowitz in her method) defined it, but the preferred estimates of population size are limited to a few species. Population size is, however, correlated with AOO (Kunin, 1998; He and

Gaston, 2000), and the latter may provide a useful indicator of local abundance. Using my estimates for range size and index of abundance (EOO and AOO) to determine the level of commonness/rarity, it is possible to differentiate between 16 classes (4 classes of distribution by 4 classes of abundance). 43

I applied Rabinowitz’s method (Rabinowitz, 1981), which was one of the first to recognize several different forms of rarity based on geographic distribution, local abundance, and habitat specificity. I used EOO (k-NNCH), AOO (1 km grid), and ENV range as estimates of Rabinowitz’s parameters. To estimate the ENV range, I summed the rank number (1 to 115 to each taxa/trait) for range of temperature, elevation, rainfall, vegetation, and geology (range was the difference between the maximum and minimum values for temperature, elevation, rainfall, and for the latter two parameters range was the number of different classes) providing a single metric to describe the environment/habitat within which each taxon occurred. Rabinowitz divides each of these parameters into two classes, however she does not specify how one should make the cut-off between wide/large and narrow/small. As a first pass, the taxa were assigned into two classes above and below the median value for each of these parameters; widespread or restricted EOO, abundant or sparse AOO, and wide or narrow ENV range. The parameters were then combined to allow me to classify the taxa into 8 different forms of rarity (Rabinowitz, 1981).

I also applied an ordination/classification method to avoid the problems inherent in arbitrarily dividing taxa into classes along continuous attributes and having to force the taxa into different forms of rarity. I approached this in two ways: (i) starting with the most complex where seven continuous parameters (EOO k-NNCH, AOO 1km grid, rainfall, temperature, elevation, vegetation, and geology range) were included in the analysis, then (ii) simplifying it using the ranks for only the EOO, AOO, and ENV range. The first method may give more weight to ENV because five ENV parameters are used but only one of EOO and AOO. The latter ordination, with only the three parameters, should be comparable to how I have applied Rabinowitz’s method with the advantage that the natural divisions in the data set are used rather than arbitrary 44 divisions. I used PATN v3.02 to generate a similarity matrix using the Gower Metric.

This was then used to generate a UPGMA dendrogram (classification strategy: agglomerative hierarchical fusion, beta -0.1000) and a three-dimensional ordination

(method: SSH, cut-off = 0.900, random starts: 100, iterations: 500, random seed value:

1235). An ANOSIM was performed to test the significance of the groupings (seed:

1245, number of iterations: 100), which were defined based on the branch distances in the dendrogram.

I compared the groupings of commonness/rarity defined using Gaston’s and

Rabinowitz’s methods to my ordination method (described above) using an ANOSIM in

PATN. The Gower metric was used to estimate the level of similarity/dissimilarity within and among groups, which enabled me to determine if the groupings derived from the different methods were significantly different from each other. Taxa that were in the rarest class in all three methods were classified as rare, similarly for the most common species. I used the results of the ordination method to classify taxa as rare and common where there were discrepancies in the level of rarity between methods. Taxa were put in the intermediate class where they did not fit into the extreme classes of rarity/commonness.

2.2.3. Geographic, phylogenetic, ecological and environmental traits

The Persoonia taxa were classified into simple groups based on geography and phylogenetic patterns (Appendix 1) to examine their association with rarity. In addition,

I explored the relationship between plant rarity and several ecological and environmental attributes. I used literature sources (primarily, Weston, 1995; Benson and

McDougall, 2000) to identify life-history traits that are potentially important to the persistence and dispersal of plants (including resprouting ability, floral attributes, and plant, leaf and floral size) (Appendix 1). Environmental traits (including annual rainfall, 45 mean minimum and maximum temperature, elevation, and vegetation and geology) were extracted from Geographic Information System databases (provided by

Geoscience Australia and Australian Government Bureau of Meteorology) (Appendix

2).

I analysed the data using both multivariate and ordination methods to search for associations between the traits (i.e. traits dimensions) and determine the relationship between the traits and plant rarity (as classified above in 2.2.2.). The importance of individual traits was tested using 1-way ANOVA and linear correlation, using the level of rarity as a fixed factor (common, intermediate, rare).

2.2.4. Local abundance in the Sydney region

The large eastern clade of Persoonia (subclade 6, within the ‘lanceolata’ clade, includes

60 taxa of which all but P. elliptica occur in eastern Australia; Appendix 1). This clade has a variety of forms of rarity, including common and rare species (several of which are listed as threatened under the national and state legislation; (TSCA, 1995; EPBCA,

1999; Appendix 1). Thirty-five of these occur in the Sydney region, for which there are more collections and more biological information available than other regions. Using published data on the ecology of Persoonia (Benson and McDougall, 2000), along with supplementary personal field observations, GIS data and unpublished data (provided by

Tony Auld), I collated estimates of the local abundance, patchiness of plants in the landscape, habitat, vegetation and soil type within the Sydney Basin (Appendix 3).

For several common and rare species, I investigated the current level of rarity; including

P. mollis ssp. nectens (common), P. mollis ssp. maxima (rare), P. lanceolata (common), and P. glaucescens (rare) (see Chapter 1 for species description)1. For these species, I

1 In addition P. bargoensis and P. hirsuta were added to the list because of their relative convenience to study (as they occurred in the same area the other taxa) and their listing as endangered species. 46 attempted to locate all extant plants by checking existing records from the NSW

Herbarium and NPWS Wildlife ATLAS, and exploring areas that were determined to be potential habitat based on topographical, soil and vegetation maps (and advice from local experts). I used this to estimate the ‘current’ distribution, local abundance, and population size for these species in the Sydney region. By determining the area of occupancy over multiple spatial scales, from the local patch or subpopulation (100m2 the finest scale measured here) doubling the grid size until it encompasses the entire distribution of the taxon, an estimation of the level of population fragmentation

(aggregation) can be made (Hartley and Kunin, 2003).

2.3. Results 2.3.1 General description of herbarium data

I collected a total of 11,614 records, of which 8,045 provided reliable determinations of the taxon and acceptably precise locality information (<1000m geoaccuracy). The number of records ranged from only 2 for P. flexifolia, P. kararae, P. laxa and P. prostrata (the latter two species are currently presumed extinct) to 395 for P. falcata,

506 for P. linearis and 611 for P. juniperina. The number of records per taxon is skewed, with 32 taxa having ≤ 20 records (12 of which have ≤ 10 records) and 23 taxa with ≥ 100 records (8 of which have ≥ 200 records). The mean and median number of records per taxon for the whole of Australia was 69.9 ± 8.7 (1SE) and 37, respectively.

There are 74 taxa that occur only in eastern Australia (5858 records), 40 taxa only in western Australia (1791 records), and only one taxon that occurs in both eastern and western Australia (P. falcata with 395 records). The mean number of records per taxon in eastern Australia, 79.1 ± 11.6 (1SE), was much greater than in western Australia,

44.8 ± 8.9 (median 51 and 25, respectively). New South Wales appears to be the centre of diversity for Persoonia taxa, containing 49 species (5 of which have been divided 47 into subspecies giving 61 taxa), followed by the southwest of Western Australia, in which 40 species occur.

2.3.2. Distribution, abundance and environmental range

Species differed dramatically in distribution, abundance and environmental range. For example, P. falcata extends from the east to the west coast, while P. kararae is known from a single location (Karara Station) (Weston, 1995). There are 11 taxa with EOO

<100 km2 (6 of which with EOO <1km2), 55 taxa with EOO <5,000 km2, and 84 taxa with EOO <20,000 km2, all of which satisfy the IUCN extent-of-occupancy criterion threshold, however for listing as threatened they would also have to meet 2/3 sub-rules.

At the other end of the scale, there are 17 taxa with EOO >50,000 km2, 8 of which are extremely widespread with EOO >100,000 km2 (Appendix 2).

The index of abundance of taxa, as measured by the AOO, varied from 2 species (P. asperula ssp. nov. 'Watchtower', and P. kararae) that only occupy a single 1km grid cell

(representing a ‘patch’ of plants) through to the 483 one kilometre grids from which P. juniperina has been collected. All the taxa have AOO <500 km2 (using a 1km grid) and satisfy the IUCN criterion threshold for listing as endangered (increasing the scale to a

2km grid size results in 11 taxa moving to the vulnerable class, but all remain threatened <2000 km2) However, for listing as threatened they would also have to meet two out of three sub-rules (being population fluctuations, decline, fragmentation; IUCN,

2001). The AOO using 10 km grids suggests that there are 32 taxa with fewer than 10 metapopulations and 10 taxa with greater than 100 metapopulations. At the landscape scale (100 km), 45 taxa occupied only a single grid cell, while 20 taxa occupied greater than 10 grids (8 of which occupied greater than 20 grids) (Appendix 2).

Collectively, the taxa showed huge variation across all the environmental traits; annual mean rainfall ranged from 167 to 4242 mm, mean daily temperature 0-36 ºC, elevation 48

0-2095 m, vegetation 1-113 types, geology 1-51 types. Persoonia falcata has the widest range for each of the environmental traits, except elevation, where it ranks 12th greatest and P. chamaepeuce has the greatest range of elevation among sites. Extinct species have a restricted range of environmental traits, eg P. prostrata (presumed extinct;

EPBCA, 1999) has the narrowest vegetation, elevation, and temperature range (along with the 2nd narrowest geology and 3rd narrowest rainfall range). The 5 taxa with the greatest combined ENV range are (declining from greatest) P. chamaepeuce, P. linearis, P. falcata, P. juniperina and P. sericea, and at the other end of the spectrum there is (increasing from lowest) P. prostrata, P. pauciflora, P. laxa, P. cordifolia and

P. kararae, with a continuum in between these extremes (Appendix 2).

Many of the variables are correlated to some degree; from the substantial correlation between AOO 1km and ENV range (r = 0.662), AOO 1km and EOO k-NNCH (r =

0.525), down to the weak correlation between EOO k-NNCH and ENV range (r =

0.327) (Table 2.1). Other traits, such as the number of records, show much higher levels of correlation with AOO (1km r = 0.994 and 10 km r = 0.969) and vegetation (r =

0.883) and geological (r = 0.824) range (but note the lower level of correlation with

EOO CH r = 0.498 and k-NNCH r = 0.507). The range of vegetation and geology are highly correlated (r = 0.936), and both have a relatively high level of correlation with all other traits used to estimate rarity (Table 2.1).

The evaluation of whether a taxon satisfies the ‘geographic range’ IUCN criterion for listing requires not only an understanding of its distribution/abundance but also the level of fragmentation, population decline and fluctuations in population size. While many of the species meet the threshold for extent of occurrence and area of occupancy, it is not possible to assess their conservation status under this criterion without other information. IUCN criterion D (very small or restricted populations), however, allow 49 the evaluation of taxa based on either the number of mature individuals or restricted area of occupancy. Two elements need to be met to satisfy this criterion. Firstly, taxa with AOO <20 km2 or ≤5 locations (provided as guidelines only) would potentially qualify for listing in the ‘vulnerable’ category, and 39 Persoonia taxa satisfy this, using a 1km grid (including 10 taxa ≤5 ‘1km2 patches’; Appendix 2). Secondly, such species would need to be ‘prone’ to the effects of human activities or stochastic events within a very short time period in an uncertain future, and is thus capable of becoming Critically

Endangered or even Extinct in a very short time period to qualify for a vulnerable listing. Consequently it seems imperative for conservation to examine these 39

Persoonia taxa to see if they may meet the second part of IUCN criterion D.

50

Table 2.1: Correlation matrix of the traits used to determine the form of rarity.

# Records EOO-CH Perimeter-CH EOO-NNCH AOO-1km AOO-10km AOO-100km ENV range Rainfall Temperature Elevation Vegetation Geology # Records 1.000 EOO-CH 0.507 1.000 Perim-CH 0.725 0.854 1.000 EOO-NNCH 0.498 0.998 0.856 1.000 AOO-1km 0.994 0.532 0.750 0.525 1.000 AOO-10km 0.969 0.613 0.813 0.611 0.984 1.000 AOO-100km 0.704 0.941 0.951 0.944 0.729 0.803 1.000 ENV range 0.658 0.318 0.632 0.327 0.662 0.661 0.507 1.000 Rainfall 0.632 0.573 0.633 0.563 0.627 0.624 0.623 0.637 1.000 Temperature 0.607 0.427 0.658 0.436 0.610 0.630 0.586 0.853 0.502 1.000 Elevation 0.501 0.198 0.354 0.193 0.476 0.439 0.305 0.742 0.692 0.645 1.000 Vegetation 0.883 0.768 0.910 0.759 0.892 0.925 0.904 0.666 0.710 0.673 0.475 1.000 Geology 0.824 0.753 0.908 0.747 0.844 0.891 0.879 0.705 0.691 0.637 0.418 0.936 1.000

51

2.3.3. Classifying the forms of rarity

Here I define rarity for Persoonia species using three different methods based on a number of attributes including distribution (EOO), an index of abundance (AOO) and environmental range (rainfall, temperature, elevation, vegetation, and geology range).

My first approach was based on Gaston’s ‘quartile’ method (Gaston, 1994, 1997a) using

EOO k-NNCH and AOO 1 km grid divides taxa into 16 groups of variable size covering the full spectrum of commonness/rarity (Table 2.2). There are more taxa in the groups at the extremes with 18 and 21 taxa being in the bottom and top quartile, respectively, for both EOO and AOO. There are fewer taxa in groups with opposing EOO and AOO than groups with intermediate but similar levels of EOO and AOO. The distribution and index of abundance of taxa are correlated (R = 0.526, t114 = -2.43, P = 0.0168), and the strength of the correlation is increased dramatically when the widespread P. falcata is excluded (R = 0.727, t113 = -5.38, P < 0.001). Given this pattern, groups can be combined in five general forms of rarity (narrow/sparse 31 taxa, narrow/abundant 6 taxa, intermediate 38 taxa, wide/sparse 5 taxa, and wide/abundant 35 taxa; Figure 2.2;

Table 2.2). 52

Table 2.2: Classifying rarity in Persoonia using the ‘quartile’ method (Gaston, 1994, 1997a) based on the EOO k-NNCH and AOO 1 km grid. Taxa were ranked and divided into quarters (1 was assigned to taxa with the lowest 25% of values) for EOO and AOO, and then these two parameters were combined to give EOO/AOO. These parameters are correlated (R = 0.526) and taxa fall into 5 general forms of rarity representing the complete spectrum from common to rare.

Forms of rarity EOO/AOO # taxa narrow/sparse 1/1 18 Rare narrow/sparse 1/2 6 narrow/sparse 2/1 7 narrow/abundant 1/3 5 narrow/abundant 1/4 0 narrow/abundant 2/4 1 intermediate 2/2 10 intermediate 2/3 11 intermediate 3/2 11 intermediate 3/3 6 wide/sparse 3/1 4 wide/sparse 4/1 0 wide/sparse 4/2 1 wide/abundant 3/4 7 wide/abundant 4/3 7 Common wide/abundant 4/4 21

53

600 wide/abundant wide/sparse 2 500 intermediate narrow/abundant 400 narrow/sparse

300

200

100 Area of occupancy (1km grid) km

0 0 500 1000 1500 2000 (A) Extent of occurrence (k-NNCH) 1000's of km2

150 2 125

100

75

50

25 Area of occupancy (1km grid) km

0 0 102030405060708090100 (B) Extent of occurrence (k-NNCH) 1000's of km2

Figure 2.2: The relationship between distribution (EOO k-NNCH) and abundance (AOO 1 km grid) in the genus Persoonia (115 taxa). Species are labelled with symbols representing different five general forms of rarity based on the ‘quartile’ method (Gaston, 1994, 1997a). (A) covers the complete AOO and EOO, while (B) zooms into a subset of the range providing more resolution of the forms of rarity (see Table 2.2 for label groupings). 54

My second approach divides the taxa into two equal groups for EOO, AOO, and ENV range that are then combined to produce 8 different forms of rarity. This approach, devised by Rabinowitz (1981) results in a high proportion of taxa being assigned to the extremes, with 40 taxa falling into the widespread EOO, abundant AOO, and wide ENV range, and 36 taxa at the opposite end of the scale (restricted EOO, sparse AOO, and narrow ENV range) (Table 2.3). Fewer species are classified into intermediate forms of commonness/rarity (particularly where AOO and ENV range are opposing). Taxa appear to fall into three general forms of rarity (36 rare, 39 intermediate, and 40 common taxa) providing a working classification. 55

Table 2.3: Classifying Persoonia taxa into 8 forms of rarity based on EOO, AOO, and ENV range following (Rabinowitz, 1981).

56

Association methods provide a way to examine several continuous parameters for the level of similarity/dissimilarity among taxa. The ordination and dendrogram produced when distribution, abundance and environmental range (EOO, AOO, rainfall, temperature, elevation, vegetation and geological range) are included as continuous parameters clearly separates P. falcata from the other taxa as being extremely common

(at the end of the EOO and rainfall range vectors; Figure 2.3). There is a group of five taxa that are widespread (EOO) and abundant (AOO), 19 intermediate taxa, and 90 rare taxa with more restricted EOO and sparse AOO (Figure 2.4). Using only three rank parameters (EOO, AOO, ENV range) to determine the association between taxa produced three clearly separated groups on the end of long branches (Figure 2.6). These groups contained similar numbers of taxa; 33 common, 31 intermediate, and 51 rare

(where the common and rare groups are at opposite ends of the EOO vector) (Figure

2.5). These three groupings (common, intermediate and rare) are significantly different

(ANOSIM P<0.001).

57

Figure 2.3: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on EOO, AOO, rainfall, temperature, elevation, vegetation and geological range (continuous data). Rarity classification based on the ordination method; Squares with the top right filled = common (P. falcata), Squares with the bottom left filled = intermediate-common, Filled squares = intermediate-rare, clear squares = rare. The lines represent the vectors for the main explanatory traits (see Kruskal-Wallis values). 58

Rare

Figure 2.4 (Part A): UPGMA dendrogram for Persoonia taxa showing the groupings for plant rarity based on the association between several continuous parameters (EOO, AOO, rainfall, temperature, elevation, vegetation and geological range). This dendrogram has been split into two parts A and B. 59

Rare

Intermediate

Common

Extremely common Figure 2.4: Part B of dendrogram (details in part A) 60

Figure 2.5: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on EOO, AOO, ENV range (rank data). Rarity classification based on the ordination method; Filled squares = common, squares with bottom right filled = intermediate, clear squares = rare. The lines represent the vectors for the main explanatory traits (see Kruskal-Wallis values).

61

Figure 2.6: UPGMA dendrogram showing the groupings for plant rarity based on the association between EOO, AOO, and ENV range (rank data). Part A showing clade with rare taxa. This dendrogram has been split into three parts A (rare), B (intermediate) and C (common). 62

Figure 2.6: Part B of dendrogram including intermediate taxa (details in part A) 63

Figure 2.6: Part C of dendrogram including common taxa (details in part A) 64

The three groups (common, intermediate, and rare) from the ordination method correspond relatively well with Rabinowitz’s 8 forms of rarity (ANOSIM P = 0.012) and the 3 general forms (common, intermediate, rare; ANOSIM P = 0.014) (Figure 2.7).

The common group contains only taxa that have widespread EOO, abundant AOO, wide ENV range, and the rare group contains only taxa that have restricted EOO, sparse

AOO, narrow ENV range (Figure 2.4.). The intermediate group contains a mix of all forms of rarity (including 7 common and 5 rare taxa), which is partially due to the arbitrary cut-offs I imposed. The ‘quartile’ method (Gaston, 1997a) performs similarly

(the ANOSIM indicates that the 16 forms of rarity are significant groups P = 0.021 and the five general forms P = 0.012) but there are more intermediate forms found in the common and rare groups (Table 2.4). Using the rank ordination groupings as a basis for classifying rarity appears to be biologically valid, representing a common (widespread, abundant with wide environmental range), an intermediate, and a rare (restricted, sparse with narrow environmental range) form. Within each of these forms there is some variation and it may be useful to separate them into further groups. Of the 51 rare taxa there are some that are extremely rare (P. asperula ssp. nov ‘watchtower’, P. baeckeoides, P. bargoensis, P. brachystylis, P. cordifolia, P. flexifolia, P. hindii, P. kararae, P. laxa, P. micranthera, P. mollis ssp. maxima, P. papillosa, P. pauciflora, P. prostrata) and form a clade in the dendrogram. Seven of the common taxa fall into a clade that is extremely common (P. chamaepeuce, P. falcata, P. juniperina, P. linearis,

P. levis, P. rigida, P. sericea). While the intermediate group contains taxa that vary widely in terms of their level of rarity, it is difficult to separate them into biologically meaningful forms of rarity although several species may warrant inclusion into common-intermediate (P. acicularis, P. chapmaniana, P. cymbifolia, P. gaminea, P. hakeiformis, P. inconspicua, P. pentasticha, P. pungens, P. rufiflora, P. scabra, P. 65 stricta) and rare-intermediate (P. brevirhachis, P. glaucescens, P. isophylla, P. myrtilloides ssp. myrtilloides, P. nutans, P. sulcata) groups. 66

Figure 2.7: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping based on EOO, AOO, ENV range (rank data). Labelled with ‘apriori’ groups (Rabinowitz 8 forms of rarity); open squares = 1/1/1, open circles = 1/1/2, open triangles pointing up = 1/2/1, open open triangles pointing down= 1/2/2, filled triangles pointing up = 2/1/1, filled triangles pointing down= 2/1/2, filled circles = 2/2/1, filled squares = 2/2/2 (where 1is high and 2 is low EOO/AOO/ENV range). Line shows the similarity between the most common (P. falcata) and the most rare (P. prostrata) taxa. 67

Table 2.4: A comparison of several different classification systems for rarity in Persoonia; including (Gaston, 1994, 1997a) ‘quartile’ method, (Rabinowitz, 1981) ‘8 forms of rarity’ and my ordination approach. The final classification of taxa represents the rank ordination classification of common (3), intermediate (2) and rare (1) taxa combined with the other approaches to identify taxa that are extremely common (3*) and extremely rare (1*). Species subspecies EOO,AOO,E Final EOO,AOO 5 forms 3 forms Continuous Rank a b NV d e f classification c g P. acerosa 2,3 3 1,2,1 2 1 2 2 P. acicularis 4,3 5 2,2,1 2 1 2 2 P. acuminata 3,2 3 2,1,2 2 2 2 2 P. adenantha 2,2 3 1,1,2 2 1 2 2 P. amaliae 4,3 5 2,2,2 3 1 3 3 P. angustiflora 4,4 5 2,2,2 3 1 3 3 P. arborea 2,2 3 1,1,1 1 1 2 2 P. asperula ssp. nov. 2,3 3 1,2,2 2 2 2 2 'Asperula' P. asperula ssp. nov. 1,1 1 1,1,1 1 1 1 1* 'Watchtower' P. baeckeoides 1,1 1 1,1,1 1 1 1 1* P. bargoensis 1,2 1 1,1,1 1 1 1 1* P. biglandulosa 2,1 1 1,1,1 1 1 1 1 P. bowgada 3,1 4 2,1,1 2 1 2 2 P. brachystylis 1,1 1 1,1,1 1 1 1 1* P. brevifolia 1,2 1 1,1,1 1 1 1 1 P. brevirhachis 2,2 3 1,1,1 1 1 2 2 P. chamaepeuce 4,4 5 2,2,2 3 3 3 3* P. chamaepitys 3,3 3 2,2,2 3 1 2 2 P. chapmaniana 3,2 3 2,1,1 2 1 2 2 P. comata 3,3 3 2,2,2 3 1 2 2 P. confertiflora 4,4 5 2,2,2 3 2 3 3 P. conjuncta 2,2 3 1,1,2 2 1 2 2 P. cordifolia 1,1 1 1,1,1 1 1 1 1* P. coriacea 4,4 5 2,2,2 3 1 3 3 P. cornifolia 4,4 5 2,2,2 3 2 3 3 P. curvifolia 4,3 5 2,2,2 3 1 3 3 P. cuspidifera 2,3 3 1,2,2 2 1 2 2 P. cymbifolia 3,2 3 2,1,1 2 1 2 2 P. daphnoides 1,1 1 1,1,1 1 1 1 1 P. dillwynioides 2,1 1 1,1,1 1 1 1 1 P. elliptica 3,4 5 2,2,2 3 1 3 3 P. falcata 4,4 5 2,2,2 3 4 3 3* P. fastigiata 3,1 4 2,1,2 2 1 2 2 P. filiformis 2,1 1 1,1,1 1 1 1 1 P. flexifolia 1,1 1 1,1,1 1 1 1 1* P. glaucescens 1,2 1 1,1,1 1 1 2 2 P. graminea 3,2 3 2,1,1 2 1 2 2 P. gunnii 3,4 5 2,2,2 3 2 3 3 P. hakeiformis 3,1 4 2,1,1 2 1 2 2 P. helix 4,4 5 2,2,2 3 1 3 3 P. hexagona 3,2 3 2,1,1 2 1 2 2 P. hindii 1,1 1 1,1,1 1 1 1 1* P. hirsuta 3,4 5 2,2,2 3 1 3 3 P. inconspicua 4,2 4 2,1,1 2 1 2 2 P. iogyna 1,2 1 1,1,1 1 1 1 1 P. isophylla 1,3 2 1,2,1 2 1 2 2 P. juniperina 4,4 5 2,2,2 3 3 3 3* P. kararae 1,1 1 1,1,1 1 1 1 1* P. katarae 2,2 3 1,1,1 1 1 1 1 P. lanceolata 3,4 5 2,2,2 3 2 3 3 P. laurina ssp. intermedia 2,2 3 1,1,2 2 1 2 2 P. laurina ssp. laurina 3,3 3 2,2,2 3 1 3 3 P. laurina ssp. leiogyna 3,3 3 2,2,2 3 1 2 2 P. laxa 1,1 1 1,1,1 1 1 1 1* P. leucopogon 1,1 1 1,1,1 1 1 1 1 P. levis 4,4 5 2,2,2 3 2 3 3 P. linearis 4,4 5 2,2,2 3 3 3 3* P. longifolia 4,4 5 2,2,2 3 2 3 3 P. marginata 1,1 1 1,1,1 1 1 1 1 P. media 4,4 5 2,2,2 3 2 3 3 P. micranthera 1,1 1 1,1,1 1 1 1 1* P. microphylla 2,2 3 1,1,2 2 1 2 2 P. mollis ssp. budawangensis 1,3 2 1,2,1 2 1 2 2 P. mollis ssp. caleyi 1,3 2 1,2,2 2 1 2 2 68

Table 2.4: continued… Species subspecies EOO,AOO,E Final EOO,AOO 5 forms 3 forms Continuous Rank a b NV d e f classification c g P. mollis ssp. ledifolia 2,3 3 1,2,2 2 1 2 2 P. mollis ssp. leptophylla 2,3 3 1,2,2 2 1 2 2 P. mollis ssp. livens 2,3 3 1,2,2 2 1 2 2 P. mollis ssp. maxima 1,2 1 1,1,1 1 1 1 1* P. mollis ssp. mollis 2,3 3 1,2,1 2 1 2 2 P. mollis ssp. nectens 2,2 3 1,1,1 1 1 2 2 P. mollis ssp. revoluta 1,2 1 1,1,1 1 1 1 1 P. moscalii 2,1 1 1,1,1 1 1 1 1 P. muelleri ssp. angustifolia 3,2 3 2,1,2 2 2 2 2 P. muelleri ssp. densifolia 2,3 3 1,2,2 2 2 2 2 P. muelleri ssp. muelleri 3,3 3 2,2,2 3 2 3 3 P. myrtilloides ssp. 2,3 3 1,1,2 2 1 2 2 cunninghamii P. myrtilloides ssp. 2,3 3 1,2,1 2 1 2 2 myrtilloides P. nutans 1,3 2 1,2,1 2 1 2 2 P. oblongata 3,3 3 2,2,2 3 1 2 2 P. oleoides 3,3 3 2,2,2 3 2 2 2 P. oxycoccoides 3,2 3 2,1,2 2 1 2 2 P. papillosa 1,1 1 1,1,1 1 1 1 1* P. pauciflora 1,1 1 1,1,1 1 1 1 1* P. pentasticha 3,2 3 2,1,1 2 1 2 2 P. pertinax 2,1 1 1,1,1 1 1 1 1 P. pinifolia 2,4 2 1,2,1 2 1 2 2 P. procumbens 2,2 3 1,1,2 2 1 2 2 P. prostrata 1,1 1 1,1,1 1 1 1 1* P. pungens 3,1 4 2,1,1 2 1 2 2 P. quinquenervis 4,4 5 2,2,2 3 1 3 3 P. recedens 1,1 1 1,1,1 1 1 1 1 P. rigida 4,4 5 2,2,2 3 3 3 3* P. rudis 3,2 3 2,1,1 2 1 2 2 P. rufa 1,1 1 1,1,1 1 1 1 1 P. rufiflora 4,3 5 2,2,1 2 1 2 2 P. saccata 3,4 5 2,2,2 3 1 2 2 P. saundersiana 4,4 5 2,2,2 3 1 3 3 P. scabra 3,2 3 2,1,1 2 1 2 2 P. sericea 4,4 5 2,2,2 3 3 3 3* P. silvatica 3,4 5 2,2,2 3 2 3 3 P. spathulata 2,1 1 1,1,1 1 1 1 1 P. stradbrokensis 4,4 5 2,2,2 3 2 3 3 P. striata 4,4 5 2,2,2 3 1 3 3 P. stricta 4,3 5 2,2,2 3 1 2 2 P. subtilis 4,3 5 2,2,2 3 1 3 3 P. subvelutina 3,4 5 2,2,2 3 2 3 3 P. sulcata 2,2 3 1,1,1 1 1 2 2 P. tenuifolia 4,4 5 2,2,2 3 2 3 3 P. teretifolia 4,4 5 2,2,2 3 2 3 3 P. terminalis ssp. recurva 3,2 3 2,1,1 2 1 2 2 P. terminalis ssp. terminalis 1,1 1 1,1,1 1 1 1 1 P. trinervis 4,3 5 2,2,2 3 1 3 3 P. tropica 2,1 1 1,1,1 1 1 1 1 P. virgata 4,4 5 2,2,2 3 2 3 3 P. volcanica 1,3 2 1,2,2 2 1 2 2 a EOO,AOO is the results from the Gaston’s ‘quartile’ method , where 1 and 4 are within the lowest and highest 25%, respectively. b 5 forms are based on the ‘quartile’ method. where similar forms have been combined (narrow/sparse, narrow/abundant, intermediate , wide/sparse, wide/abundant; Table 2.2) c EOO,AOO,ENV is the results from Rabinowitz’s ‘8 forms of rarity’ method, where 1 and 2 are values below and above the median, respectively. d 3 forms are based on the ‘8 forms of rarity’ method. where similar forms have been combined (narrow/sparse, intermediate, wide/abundant). e Continuous is the result of the ordination including several continuous variables (EOO, AOO, rainfall, temperature, elevation, vegetation and geology range). f Rank is the result of the ordination including EOO, AOO and ENV range as rank data. g Final classification is the result after combining the above methods (1 = narrow/sparse/wide environmental range; 2 = intermediate; 3 = widespread/abundant/wide) (* extreme forms are rare or common in all classifications). 69

2.3.4. Phylogenetic, geographic, environmental and life-history traits

Phylogenetic association appears to show a random pattern in relation to rarity (χ2 =

26.98, df = 24, P > 0.25), with common and rare taxa appearing in most clades (except where clades have small sample sizes) (Table 2.5). There are similar levels of commonness and rarity in Persoonia from eastern and western Australia (χ2 = 0.88, P2

> 0.975). If anything, the proportion of rare taxa is slightly less in eastern than western

Australia. This suggests that phylogeny and geography are not directly associated with rarity. 70

Table 2.5: The proportion of common and rare Persoonia taxa in geographic and phylogenetic groups. Rarity is based on the Gower associations (final classification in Table 2.4) and the phylogeny is described in Figure 2.1. n = number of taxa in the group.

Rarity / Geographic Phylogenetic clades

Commonness East West 1 2 3 4 5 6 6.5 7 8 9 10 10.5 11

Rare 0.24 0.33 0.00 0.00 0.00 0.00 0.20 0.28 0.60 0.00 0.50 0.00 0.23 0.00 0.38

Intermediate 0.51 0.45 1.00 0.60 0.00 1.00 0.80 0.46 0.20 1.00 0.50 1.00 0.46 1.00 0.25

Common 0.24 0.23 0.00 0.40 1.00 0.00 0.00 0.26 0.20 0.00 0.00 0.00 0.31 0.00 0.38

n 74 40 3 5 1 2 5 61 10 1 2 2 13 2 8

71

I found that common and rare groups differed in terms of their environmental attributes.

Common taxa typically occur in areas in which they experience higher maxima and lower minima (in terms of rainfall, temperature and elevation) encompassing a wider range of environmental conditions (including vegetation and geology) than rare taxa, which are found in much milder environments with a narrower range of conditions

(Figure 2.8). Furthermore, an ordination with all environmental traits as continuous data

(rainfall, temperature, elevation, vegetation and geology) separates groups of common and rare taxa, with the intermediate group in between (ANOSIM P = 0.011) (Figure

2.9). Trait vectors are spread in all directions but fall into two groups, the first dimension being maximum elevation, minimum and maximum rainfall and the second being vegetation, geology, minimum elevation, minimum and maximum temperature.

The most common and rare taxa (P. falcata and P. asperula ssp. nov ‘Watchtower’) are at opposite ends of the second dimension (with different vegetation, geology and maximum temperature).

72

2000 30 1800 25 1600 1400 C) 20 Rain (max ) ˚ Temp (max) 1200 Rain (min) Temp (min) 1000 15 800 10 600 temperature ( 400 daily mean Annual 5

Annual meanrainfall (mm) 200 0 0 rare intermediate common rare intermediate common

(A) Rar ity (B) Rar ity

1600 35

1400 30

1200 25 1000 Elevation (max) Vegetation 20 Elevation (min) Geology 800 15 600 10 400 mean habitat range habitat mean mean elevation (m) 200 5

0 0 rare intermediate common rare intermediate common Rar ity (C) Rar ity (D)

Figure 2.8: Environmental traits for Persoonia across Australia comparing common, intermediate and rare groups. Mean habitat range is the number of different vegetation/geology types a taxa occurs divided by the number of taxa in rarity group. 73

Figure 2.9: A three-dimensional ordination showing the clustering of Persoonia taxa into grouping defined based on the continuous data for several environmental traits (rainfall, temperature, elevation, vegetation and geology). Labelled with ‘apriori’ groups (Rabinowitz 8 forms of rarity); open squares = 1/1/1, open circles = 1/1/2, open triangles pointing up = 1/2/1, open open triangles pointing down= 1/2/2, filled triangles pointing up = 2/1/1, filled triangles pointing down= 2/1/2, filled circles = 2/2/1, filled squares = 2/2/2 (where 1is high and 2 is low EOO/AOO/ENV range). 74

Life-history-traits, including plant size, floral display and ability to resprout after fire, do not resolve the three commonness/rarity groups. However, common taxa are generally taller plants with longer leaves and more flowers/inflorescence than intermediate taxa, which are in turn larger than rare taxa (ANOVA; Height F2,114 = 5.98

P = 0.003; leaf length F2,114 = 5.46 P = 0.005; flowers/inflorescence F2,94 = 3.41 P =

0.037P < 0.05) (Figure 2.10). However, no significant difference was detected between the forms of rarity for leaf width and tepal length (ANOVA; F2,114 = 2.62 P = 0.078;

F2,113 = 1.11 P = 0.334, respectively), although they follow the same trend for common taxa to be larger than rare taxa. Common taxa also have a significantly greater capacity to resprout after disturbance such as fire than intermediate, which resprout more often than rare plants (88% cf. 45% cf. 28%; ANOVA F2,73 = 10.72 P < 0.001). There are currently no rare taxa known to resprout from the base and stem, and the majority (69%) are unable to resprout (i.e. rely on seed to re-establish after fire) (Table 2.6).

Resprouting ability remains unknown for about a third of the Persoonia taxa (including

18 of the 31 rare taxa). 75

40 tepal length 35 leaf length 30 leaf width 25 flower/infl 20 plant height 15 mean +/- SEmean +/- 10 5 0 rare intermediate common Rarity

Figure 2.10: Plant attributes for Persoonia across Australia comparing common, intermediate and rare groups. Tepal length (mm), leaf length (cm), leaf width (mm), plant height (m), and the number of flowers/inflorescence. 76

Table 2.6: The resprouting ability of Persoonia in relation to rarity. Rarity is based on the Gower associations (final classification in Table 2.4). Resprouting ability 1 = obligate seeder, 2 = resprout only from the base, 3 = resprout from the base and stem. n = number of taxa in the group.

Rarity / Resprouting ability Commonness 1 2 3 unknown Total Rare 9 4 0 18 31 Intermediate 21 15 2 18 56 Common 3 15 7 3 28 n 33 34 9 39 115

77

2.3.4. The biology of common and rare taxa

Area of occupancy (1km grid) may be a reasonable approximation of patchiness

(common taxa with >100km2 AOO are not patchy, while rare taxa with <28km2 AOO are all patchy); however, it gives little indication of local abundance within patches or populations (Appendix 3). Obtaining direct counts of plants in the field provides the best measure of local abundance. The common P. lanceolata has many more sites in the

Sydney region than the intermediate and rare taxa due to its larger extent of occurrence

(Table 2.7). Surprisingly, P. mollis ssp. nectens, with an intermediate level of rarity, has fewer sites than two of the three rare taxa, including the closely related P. mollis ssp. maxima that has almost twice the number of sites (this is probably an artefact of P. mollis ssp. nectens having large areas within its range that were relatively inaccessible

(i.e. in the water catchments), and targeted surveys carried out for P. mollis ssp. maxima due to its listing as threatened. While the total number of plants within the Sydney region follows the rank order for rarity (common > intermediate > rare), there is less of a difference between intermediate and rare taxa than among the three rare taxa. Local abundance (as measured by the mean number of plants per site) also appears to vary in order of rarity, but this time there is much more separation between the groups. The common P. lanceolata is about twice as abundant (locally) than the closely-related rare

P. glaucescens, and a similar pattern can be seen for the intermediate P. mollis ssp. nectens and closely-related rare P. mollis ssp. maxima (Table 2.7). Persoonia hirsuta is an exceptional case, because it is frequently found as isolated plants but has been recorded from several sites across the greater Sydney area.

78

Table 2.7: The number of sites and plants for selected common, intermediate and rare Persoonia taxa in the Sydney region.

Rarity or # plants / site Status Taxon commonness # sites # plants b average SE a P. mollis ssp. nectens intermediate Not threatened 70 1612 23.03 4.16 P. mollis ssp. maxima rare Endangered 132 1316 9.97 1.74 P. lanceolata common Not threatened 205 7504 35.40 3.03 (Sydney Region) P. glaucescens intermediate Endangered 84 1495 17.80 2.80 P. bargoensis rare Endangered 54 955 17.69 3.10 P. hirsuta common Endangered 15 32 2.1 0.8 (Southern Highlands)

a Based on the Gower associations (final classification in Table 2.4). b Listing under New South Wales Threatened Species Legislation (TSCA, 1995)

79

The targeted surveys conducted here to find extant plants for several common and rare

Persoonia taxa revealed many more sites, which in all cases substantially increased the estimated area of occupation. The number of new sites was about double that of the herbarium records (except for P. lanceolata; Table 2.8) reflecting the increased effort at a finer spatial scale. The majority of these new sites were within the general distribution of the taxa (Weston, 1995), expect for P. glaucescens and P. bargoensis where the known range was increased by the discovery of large populations (both protected within water catchment areas). Generally, the greater the distribution of species the more sites that could not be relocated, with the widespread P. lanceolata having 20 sites that could not be found during the targeted survey and only 6 for the restricted P. mollis ssp. maxima. Persoonia bargoensis is the exception as for this rare taxa 11 sites could not be relocated, which is greater than the more common P. mollis ssp. nectens (intermediate level of rarity) (Table 2.8). It is possible that some plants were not detected while resurveying sites listed in the herbarium, however sites that have been cleared/degraded and where no plants could be found after several survey attempts are presumed to be extinct. Persoonia species that tend to occur on ridges and gentle slopes have been effected more by land clearing for agriculture and urbanisation, resulting in P. lanceolata, P. glaucescens and P. bargoensis being presumed to be extinct from more sites (Table 2.8). The core distribution of P. lanceolata has been highly urbanized (10 sites presumed extinct), while P. glaucescens and P. bargoensis have been more effected by agriculture (3 and 4 sites presumed extinct, respectively). 80

Table 2.8: The number of current sites listed in the herbarium, recently discovered, and not relocated sites for selected common and rare Persoonia taxa in the Sydney region.

Taxon Rarity # current # herbarium # new # lost (extinct)

P. mollis ssp. nectens intermediate 70 29 53 8(2) P. mollis ssp. maxima rare 132 31 107 6(1) P. lanceolata common 205 122 103 20(10) P. glaucescens intermediate 84 35 58 7(3) P. bargoensis rare 54 25 47 11(4) 81

Exploring the relationship between the number of occupied grids and scale gives an indication of the patchiness or level of natural fragmentation (Hartley and Kunin, 2003).

The slope of the curve is steeper in P. glaucescens than the closely-related P. lanceolata, indicating that the rare taxon is patchier. A similar but less obvious pattern can be seen for the rare P. mollis ssp. maxima and related intermediate P. mollis ssp. nectens (Figure 2.11). The curve does not flatten off as it approaches zero on the x-axis in the rarest taxa (P. mollis ssp. maxima, all points within a 163 km grid), but the curve starts to flatten off at increasing spatial scales with increasing commonness (rare P. glaucescens 0.04 km grid, intermediate P. mollis ssp. nectens 0.04km grid, and common

P. lanceolata 0.16km grid). The steeper slope may indicate the rare taxa occupy less of the available habitat within the distributional range (i.e. less saturated) than common taxa, or it may be a function of sampling effort. 82

P. mollis ssp. maxima 140 P. mollis ssp. nectens 80

120 70 60 100 50 80 40 60 30 40 20 20

number grids of occupied 10 number grids of occupied

0 0 0 1 100 10,000 1,000,000 0 1 100 10,000 1,000,000 scale area (km2) scale area (km2)

P. glaucescens 90 P. lanceolata 250 80

70 200 60 150 50

40 100 30

20 50 number grids of occupied 10 gridsnumber of occupied 0 0 0 1 100 10,000 1,000,000 0 1 100 10,000 1,000,000 scale area (km2) scale area (km2)

Figure 2.11: Number of grid cells occupied by each taxon as a function of spatial-scale. 83

2.4. Discussion Traditionally, taxonomic units have either been classified as common or rare (Drury,

1974). However, rarity and commonness almost certainly form a continuum, with taxa differing in several traits. In this Chapter, I have compared and contrasted three methods for defining rarity, including a novel ordination approach, to come up with a working definition of rarity (common, intermediate and rare) for 115 taxa in the plant genus

Persoonia. While the intermediate group represents a mix of species that may be more or less common (and more detailed information is required to delimit the taxa in this group), the distribution patterns of these species are well resolved based on the herbarium data and this classification provides biologically meaningful groups at the extremes (common and rare).

I found no relationship with these forms of rarity to phylogeny and geography, despite the disparate characters (morphological and genetic; Weston, 2003) and the striking longitudinal divide (see Chapter 1, Figure 1.1). Several environmental (rainfall, temperature and elevation; Appendix 2) and life-history (resprouting ability and plant size attributes; Appendix 1) traits differed significantly between common and rare forms. This fits with the expectation that common taxa have a greater ability to persist in often-harsh landscapes, being able to resprout after disturbance and tolerate relatively extreme environmental conditions. Local abundance is related to distributional patterns, with rare taxa having fewer plants within a patch then more common species (Table

2.7). Despite the limitations of the herbarium records the current distribution of

Persoonia species appears to reflect historical patterns rather than recent fragmentation effects (investigated in two pairs of closely-related taxa that differ dramatically in their levels of commonness/rarity) (Table 2.8), based on land-use patterns. These findings 84 have implications for the ability of plants to persist and disperse, which are linked to the likelihood of extinction (Eriksson, 1996).

2.4.1. Forms of rarity and commonness

Classifying rarity is difficult given the wide spectrum of distributions and abundances that appear in natural species. Each of the methods I used here to define rarity has its advantages and disadvantages. The strength of the ‘quartile’ method advocated by

(Gaston, 1994, 1997a) is that it incorporates much of the variation in the distribution and abundance by dividing taxa into four groups along these continuous parameters.

This method fails to account for environmental variation, which Gaston (1997) argued would be a prejudgement of rarity and should be omitted from its definition. However, the inclusion of habitat specificity (or environmental range) should minimize the variation within the different forms of rarity, thus allowing for greater precision in the selection of common and rare taxa for comparative studies. Rabinowitz (1981) integrated habitat specificity, along with geographic distribution and local abundance, into her definition to divide species into ‘8 theoretical forms of rarity’. She identifies only seven of these forms of rarity existing in nature, omitting the form with small geographic range and population size with wide habitat specificity. Here, however, I detected six Persoonia taxa that fit into this category, which is more than the two found in the widespread and abundant with a narrow environmental range. This could be an artefact of using AOO as a surrogate of local abundance or be due to the high level of endemism in the genus. The main limitation of my application of Rabinowitz’s method is that much of the information is lost by arbitrarily dividing the continuous parameters into two groups at the median. My ordination method overcomes this problem by determining groups based on their similarity using an association metric. The use of continuous parameters clearly separates extremely widespread and abundant taxa but 85 makes it difficult to explore groupings among rarer taxa (Figure 2.3). While rank data

(EOO, AOO, ENV range) produce three clear groups, it is difficult to interpret the exact differences between them. Evaluating all three methods provides a means for exploring the relationship within and among the ordination groups, which clearly represent a common (widespread, abundant with wide environmental range), an intermediate, and a rare (restricted, sparse with narrow environmental range) form. By comparing the traits associated with these three forms of commonness/rarity it may be possible to pull out trends and patterns.

2.4.2. Threat of extinction

Currently there are ten taxa listed under the national Environment Protection and

Biodiversity Conservation Act 1999, including two presumed extinct (P. laxa and P. prostrata), one critically endangered (P. pauciflora), four endangered (P. hirsuta, P. micranthera, P. mollis ssp. maxima and P. nutans) and three vulnerable (P. bargoensis,

P. glaucescens, P. marginata). Additional taxa are listed under the various state legislations; including P. hindii (endangered) and P. acerosa (vulnerable) in New South

Wales, P. asperula (endangered) and P. arborea (vulnerable) in Victoria, and P. moscalii (rare) and P. muelleri ssp. angustifolia (rare) in Tasmania (Appendix 1). Of these listed taxa P. hirsuta is the only one classified in my analysis as common (k-

NNCH EOO>12,200 km2, 1km grid AOO 89 km2). This highlights one of the limitations of this method, lacking a direct estimate of local abundance, as P. hirsuta has very small population sizes (Table 2.7) it is considered at risk of extinction.

There are five intermediate taxa [P. muelleri ssp. angustifolia (>8,900km2, AOO 29 km2), P. arborea (>1,600km2, AOO 18 km2), P. acerosa (>1,200 km2, AOO 42 km2), P. glaucescens (>700km2, AOO 28 km2), and P. nutans (>600km2, AOO 38 km2)

(Appendix 2)], and the majority of listed taxa (10/16) are classified as rare in this study. 86

Only 10 of the 31 rare taxa have been listed as threatened (2/2 presumed extinct, 1/1 critically endangered, 2/4 endangered, 2/3 vulnerable taxa national listed, and 3/6 on state lists). Given that rarity is associated with risk of extinction (IUCN, 1994, 2003), the rare taxa not protected under legislation should be assessed to determine the most appropriate classification using the IUCN guidelines. Particularly P. baeckeoides, P. brachystylis, P. cordifolia, P. flexifolia, P. kararae, P. papillosa which are extremely rare (Table 2.4), and would satisfy criteria D of the IUCN guidelines having <20 km2 area of occupancy (1 km grid) (Appendix 2). While AOO appears to give a reasonable estimation of relative abundance, it provides little information on the local abundance of plants and detailed collections of local site abundance data should become standard practise for museums and herbaria. Clearly more work is required to prioritise the conservation objectives in this plant genus and others which may also contain taxa that have been omitted from threatened species lists simply because they have not been nominated.

2.4.3. Environmental and ecological patterns

The causes and consequences of rarity are often complex and not obvious. Numerous attempts have been made to uncover general differences between common and rare taxa, but very few have emerged (Gaston and Kunin, 1997a; Murray et al., 2002a). This is partially due to the lack of a clear definition of rarity, which increases the variance within common and rare groups at the expense of differences between them. Using my defined rarity/commonness groupings, I explored the relationship with phylogenetic, geographic, environmental and life-history traits.

Phylogeny and geography appear to be unrelated to current levels of rarity in Persoonia, suggesting that recent speciation is not driving the observed patterns of rarity (Byrne et al., 2001). In Persoonia there is a random pattern of common and rare taxa across 87 different phylogenetic clades, which may be explained by a basic model of evolution

(Coyne and Orr, 2004) where speciation and extinction events are co-occurring within any of the clades. The absence of Persoonia from the arid interior of Australia creates an obvious divide between taxa in the east and west (with the exception of P. falcata, no taxa are found in either geographic areas) (Appendix 1). The proportion of common, intermediate, and rare taxa is similar in eastern and western Australia, despite obvious differences in the geographic (e.g. the Great Dividing Range; max elevation 2095 cf.

925 metres, respectively) and environmental (mean ± SD; min temperature; 6.6 ± 3.5 ˚C cf. 10.4 ± 1.5 ˚C; min rainfall 867 ± 313 mm cf. 359 ± 135 mm) features. Utilizing phylogenetic and geographic groups with more resolution may provide different results, but it appears that other factors are more important in shaping plant distributional patterns.

Environmental traits might be expected to play a role in rarity if they determine the ability of plants to persist in the landscape. Common and rare taxa were significantly different in terms of their environmental traits. Rare taxa tended to occur in areas that had more median environmental conditions, while common taxa occur in areas that experience much more extreme rainfall, temperature and elevation cover a wider range of environmental conditions (Appendix 2). During the last glacial maxima in the late

Quaternary rainfall was lower than present-day forcing plants into refugial areas (Lloyd and Kershaw, 1997). This suggests that common taxa have a greater capacity to persist in a wider range of environments, which may represent greater plasticity of water use efficiency in leaflets from common species (Pohlman et al., 2005). If this is a causal relationship, plants with a greater ability to persist in low rainfall areas would occupy more of the landscape. This hypothesis remains to be tested and may be potentially important in explaining the distribution of many other taxonomic groups in Australia. 88

Persistence in the landscape is likely to depend on life-history traits that enable plants to survive after disturbance. Fire is a major disturbance that effects many habitats and the ability of plants to resprout from roots or basal stems (rhizomes) and aerial stems is likely to increase their chance of persistence, especially if fire is frequent. Common and rare Persoonia taxa are significantly different in terms of their reprouting ability.

Common taxa are more likely to resprout (88%) than not (12%), and of the taxa that can resprout from both the base and stems the majority are common (78%). There are currently no rare taxa known to resprout from both the base and stem, and the majority

(69%) rely solely on seed to re-establish after fire. Taxa in the common group are also taller with longer leaves and more flowers/inflorescence than the rare group, but this may be related to the resprouting ability (i.e. larger plants > resprouting ability; r2 =

0.286, F1, 75 = 6.60, P = 0.012). These findings contrast with published findings reporting that resprouters have lower fecundity than obligate seeders (Carpenter and

Recher, 1979), but plants capable of resprouting may allocate more resources to their survivorship and growth, indicating that the persistence of plants in the landscape may be related to the ability to resprout after disturbance. Given that some of the most common taxa are unable to resprout and some extremely rare taxa can resprout it appears that resprouting ability alone is not driving rarity.

2.4.4. Local abundance and patchiness

Inferences concerning local abundance for large taxonomic groups are infrequent in the literature and are not available (or not reliable) from herbarium records. A major limitation of defining commonness/rarity for Persoonia, based solely on records obtained from herbaria, is that abundance has to be inferred from area of occupancy.

While abundance tends to be highly correlated with occupancy (Gaston et al., 2000), even relatively fine scale (1km grid) measures of AOO may not provide good 89 information on within ‘patch’ local abundance. Some herbarium records do provide approximate assessments of local abundance (Benson and McDougall, 2000), which may be useful for classifying taxa as ‘sometimes locally rare’ or ‘sometimes locally frequent’. All the rare taxa studies here are ‘sometimes locally rare’ (P. mollis ssp. maxima and P. bargoensis), and the intermediate taxa ‘generally locally occasional’ (P. mollis ssp. nectens and P. glaucescens), but surprisingly the most common and most rare taxa are both ‘sometimes locally frequent’ (P. mollis ssp. maxima and P. lanceolata). These data, however, do not provide a means to quantify differences between taxa and may not be consistent between collectors. It may be possible to extrapolate the scale-area curve to the plant scale (~5 metres) to give a relative measure of population size (Kunin, 1998; He and Gaston, 2000), however true estimates of local abundance can only be obtained through field observations. The local abundance of common, intermediate and common Persoonia taxa, based on field estimates, appears to be in the same general rank order as their level of commonness/rarity (Appendix 3. &

Table 2.7). While this is a small sample and I have identified at least one exception to the trend (P. hirsuta), this finding adds weight to the classification system used here to determine the forms of rarity in Persoonia.

The timing that rarity emerged (or was imposed) has implications for the biological response of the taxon (Buist et al., 2002). However, in many cases the available historical data are limited. In this study, locations identified in herbarium records (some more than 150 years old) were re-surveyed to assess changes in abundance and distributional patterns. I was unable to re-locate several sites for each of the taxa studied, and current land-use (agriculture and urban developments) strongly suggests that they have become locally extinct. On the other hand, many more new sites were discovered than were lost, simply due to an increased search effort. It appears that the 90 geographic distribution currently known for several common and rare Persoonia taxa is historical or an effect of sampling rather than a result of more recent habitat fragmentation. This suggests that environmental and life-history traits may be responsible for current distribution and abundance in Persoonia.

2.4.5. Conclusion

I used herbarium data to assign Persoonia taxa to three robust commonness/rarity groups (common, intermediate, rare), which enabled me to explore the relationship between the phylogeny, geography, environment and life-history of taxa in a comparative manner. Given appropriate data-sets, it is possible to investigate and characterize plant rarity in a biologically meaningful way. In the Persoonia species I studied, rare taxa tend to be restricted to moderate environmental conditions, to be small in size and to lack the ability to resprout after disturbance. This strongly suggests that rare taxa may be less persistent in the landscape. However, an experimental approach is required to test the causal nature of these attributes. While herbarium records provide a means for comparing the distribution and abundance between taxonomic groups they do not accurately represent historical distributions, and generally are of limited application when attempting to infer distributional changes. The strategic survey conducted here to determine the locality of plants from common, intermediate and rare taxa in the Sydney region will provide a useful baseline to determine future changes in abundance and distribution. In addition this study illustrates the usefulness of targeting potentially rare taxa to determine actual distributions and levels of threat.

91

Chapter 3 : Does genetic variation and gene flow vary with rarity in obligate seeding Persoonia species (Proteaceae)?*

3.1 Introduction Genetic variation may be a key predictor of the persistence of populations, as this together with the breeding system, dispersal ability, generation length and effective population size should determine a population’s capacity for adaptive change (Saccheri et al., 1998; Frankham et al., 2002). Theory predicts that small isolated populations will lose genetic variation and diverge genetically as a result of random drift and limited gene flow (Wright, 1931, 1951). Therefore, populations of rare species are expected to have low levels of variation and limited ability to adapt to changing environmental conditions. However, despite recent efforts to verify these features of populations few generalities seem to be emerging about the relationship between plant rarity and genetic variation (Nybom, 2004; but see Cole, 2003). This may reflect the nature of the comparisons that have been made, as results are likely to differ depending on the criteria used to determine rarity (based on local abundance, geographic range, and habitat specificity; Rabinowitz, 1981) and the life history attributes of the species. Ideally closely related species groups or pairs with similar history, breeding systems, pollinators and dispersal strategies as these can also determine the capacity to respond to environmental change, but which differ in their level of rarity should be compared.

Here I compare the level of genetic variation and structuring between two pairs of closely related common and rare perennial shrubs in the genus Persoonia (Proteaceae)

(Chapter 1) The four Persoonia species are all erect shrubs occurring in south-eastern

* This chapter has been accepted for publication in Conservation Genetics. 92

Australia (Weston, 1995) and their current distribution probably reflect historical patterns rather than any recent effects of habitat fragmentation (Chapter 2). Importantly these species share a suite of life-history traits that might determine their ability to persist and disperse, being unable to resprout after disturbance and having superficially similar floral and fruit morphology (Weston, 1983).

Here I predict that the effect of sustained rarity on population genetic attributes will be that the rare species will have: (1) less total intra-specific genetic variation than common species with greater geographic ranges that are exposed to a wider range of environmental conditions; (2) less genetic variation within populations than common species, reflecting the increased susceptibility of small populations to lose variation through genetic drift; and (3) greater genetic differentiation among populations as a consequence of lower levels of gene flow. 93

3.2. Methods 3.2.1. Site description

For each of the four Persoonia species, I sampled four populations spread across the geographic range of each species (Chapter 1, Figure 1.4). This meant that the geographic separation of populations was greater for common than rare species. I characterised all the sampled populations in terms of the area they covered, and number of adult plants (Table 3.1). Once the population boundaries were determined using vegetation maps and field observations, I randomly selected plants (15-22 adults) along a haphazard walk covering the whole population. I collected leaf and floral buds, from each plant, which were frozen immediately in liquid N2 and then stored at -80°C prior to

DNA extraction. 94

Table 3.1: The location, estimated population area, number of adult plants and voucher number for the study sites selected for genotyping to compare the two pairs of common and rare Persoonia species.

Species (species pair, plant rarity) Site (abbreviation) Location a Population Number of adult Herbarium area b plants c voucher d P. mollis ssp. nectens (pair 1, common) Colo Vale (CO) 34°23'45" E, 2.2 300 714581 150°27'57 " S Mount Kembla (KE) 34°26'29" E, 1.0 300 714582 150°48'11" S Loddon Falls (LO) 34°17'12" E, 3.1 500 714583 150°53'42" S Nattai (NA) 34°08'10" E, 4.7 >1000 714584 150°29'10" S P. mollis ssp. maxima (pair 1, rare) Binya Close (BI) 33°38'41" E, 1.2 60 714587 151°06'55" S Flinders Place (FL) 33°39'28" E, 1.8 100 714586 151°06'44" S Galston Creek (GC) 33°39'21" E, 1.5 100 714585 151°04'12" S Ku-ring-gai (KU) 33°40'34" E, 2.2 200 714588 151°8'02" S P. lanceolata (pair 2, common) Bundeena (BU) 34°06'11" E, 5.3 >1000 714589 151°05'60" S Crowdy Head (CR) 31°48'49" E, 3.3 >1000 710502 152°43'39" S Meryla Road (ME) 34°38'21" E, 2.0 300 710519 150°24'11" S Ryland Track (RY) 33° 42' 10" E, 2.5 800 714590 151° 12' 18" S P. glaucescens (pair 2, rare) Berrima (BE) 34°28'03" E, 0.8 40 710520 150°20'52" S Joadja (JO) 34°23'47" E, 3.3 300 710513 150°19'04" S Robertson (RO) 34°31'28" E, 3.8 300 714591 150°34'09" S Welby (WE) 34°25'60" E, 2.1 200 714592 150°24'55" S a Based on GPS position using datum WGS1984 b Estimated area in hectares based on field survey c Estimated number of flowering individuals per population d Vouchers lodged at the New South Wales National Herbarium 95

3.2.2. AFLP procedure

AFLP analysis followed the method of (Vos et al., 1995). Total cellular DNA was extracted from frozen leaf material using a CTAB procedure described by (Doyle and

Doyle, 1987), modified by the addition of Proteinase K during the initial incubation

(65°C/60 min) and RNAse during DNA suspension (37°C/30 min). To test for reproducibility, random duplicate DNA samples were extracted. Restriction digestion of genomic DNA was carried out in a total volume of 25 µL containing 1.25 U Eco RI/

Mse I, 125 ng of DNA, 12 µL adapter solution, 0.5 U T4 DNA Ligase, buffer and DNA- free water using AFLP™ Core Reagent Kit (Life Technologies), then diluted 1:10 in TE buffer. Pre-selective PCR was performed in a 25 µL total volume containing 2.5 µL 10 x PCR buffer, 1.5 mM MgCl2, 20 µL Preamp Primer Mix (Life Technologies), 1 U Taq

DNA Polymerase (Perkin Elmer), 2.5 ng restricted DNA template and DNA-free water.

PCR was performed with a Perkin-Elmer Applied Biosystems 9700 thermal cycler with heated lid, programmed for 20 cycles each at 94°C for 30 s, 56°C for 2 min, 72°C for 2 min. A final extension step at 60°C for 30 min was performed after 20 cycles. PCR products were diluted 1:20 with TE buffer for subsequent selective amplification. For selective amplification three primer pairs were selected. Selective PCR was carried out in a 20 µL total volume containing three Eco RI fluorescent primers including; 7 ng of

E-aca (fam), 7 ng of E-agg (hex), and 7 ng E-acc (ned), 15 ng of M-cacg primer, 0.2 mM of each of four dNTP, 0.25 U Taq DNA Polymerase (Perkin-Elmer), 2.5 µL of diluted preselective PCR product, 1.5 mM MgCl2, 2.0 µL 10 x PCR buffer and DNA- free water. PCR was performed on a Perkin-Elmer Applied Biosystems thermal cycler.

A touch-down PCR was initiated with 1 cycle at 94°C for 2 min (denaturation), 70°C for 1 min (primer annealing), 72°C for 2 min (extension) followed by eight cycles 96 starting at 94°C for 30 s, 69°C for 1 min, 72°C for 2 min reducing annealing temperature by a 1.0°C after each cycle, followed by 23 cycles at 94°C for 30 s, 61°C for 1 min, 72°C for 2 min A final extension step at 60°C for 30 min was performed after

23 cycles. To test reproducibility, duplicate reactions were run. Following selective

PCR the fluorescently labelled fragments were visualized on 5% polyacrylamide gels with an ABI Prism 377XL sequencer (Applied Biosystems). Four multiplexed dyes constituted a fingerprint for each individual. Three dyes represented primers used in the

PCR and fourth dye included internal size standard. The fingerprints were visualized using ABI Genescan software. AFLP profiles were scored for presence or absence of fragments, based on minimum fragment intensity. Initial trials indicated that fragments between 100-400 bp in size were highly repeatable, and therefore these were used for further analysis (also similar to the range used by; Krauss, 1999).

3.2.3. Genetic analysis

I conducted this analysis in three ways, designed to compare levels of genetic variation within all four species using all fragments produced, within populations for each species using the fragments produced by the species, and within populations for each species using only the fragments common to all species.

I estimated the allele frequencies (assuming that any value of the marker or null allele frequency in the range 0 to 1 is equally probable), at each locus using a Bayesian method, assuming non-uniform prior distribution of allele frequencies (Zhivotovsky,

1999) in the computer program AFLP-surv 1.0 (Vekemans et al., 2002). Estimates of allele frequencies were used to calculate the unbiased expected heterozygosity (Hj)

(Lynch and Milligan, 1994) (AFLP-surv 1.0), % of polymorphic loci (% polymorphism)

(calculated in Popgen 1.32), and the Shannon information index (I) (Popgen 1.32) 97

(Shannon and Weaver, 1949) was used to estimate genetic variation within species and populations.

I tested for significant differences between common and rare species in the levels of genetic variation found within each species with a 1-way Analysis of Variance

(ANOVA, using SAS v8). The raw data were the % polymorphism, expected heterozygosity, and Shannon’s I based on the complete data set and the fragments found in each species pair. Rarity (common or rare) was a fixed factor, with the two species pairs used as replicates. To test for significant differences between the levels of genetic variation within populations of common and rare species I used an ANOVA (using SAS v8). Species pair (Pair) and plant rarity (Rarity) were fixed factors in the analysis. Each

Pair by Rarity combination had four replicate populations.

I used an analysis of molecular variance (AMOVA) to assess the amount of genetic variation partitioned among species and populations, and determine the level of genetic structure within species (Weir and Cockerham, 1984; Excoffier et al., 1992; Weir,

1996). I used the program ARLEQUIN (Schneider et al, 1997) to compute the variance components among species, among populations, within populations. The significance of the components was tested using a hierarchical, nonparametric permutation approach

(Excoffier et al., 1992). To calculate the level of genetic structuring within each of the four species I used an AMOVA within the computer program GenAlEx v6 (Peakall and

Smouse, 2004). This program computed the partitioning of genetic variation within and among populations, as well as Wright’s FST within the species to assess genetic differentiation among populations (assuming that each locus is a two allele system, the markers are selectively neutral, and in gametic-phase equilibrium; Lynch and Milligan,

1994). The significance of FST was tested by comparing the observed FST with a null distribution created by 1000 random permutations of individuals among populations. 98

To test whether the genetic differentiation among populations within the species was caused by geographic isolation (isolation by distance model) I used a MANTEL test

(Mantel, 1967). This test performed in ARLEQUIN (Schneider et al., 1997) compared the association between pair-wise FST / (1 - FST) (using ARLEQUIN) and linear geographical distances (based on GPS positions, precision ± 3 m) among populations

(Rousset, 1997). 99

3.3. Results The three AFLP primer pairs produced a total of 389 fragments (putative loci) scored between 100 and 400 bp from the four Persoonia species (339 samples), none of which were present in all samples. All three primers produced a large number of fragments

(M-cacg E-aca produced 136, E-agg 129, and E-acc 124 fragments). The number of fragments amplifying in at least one individual varied among the species pairs (P. mollis ssp. nectens and ssp. maxima produced 282 fragments; P. lanceolata and P. glaucescens produced 335 fragments) and species (P. mollis ssp. nectens 241 fragments; P. mollis ssp. maxima 167 fragments; P. lanceolata 243 fragments; P. glaucescens 266 fragments). The great majority of fragments were polymorphic within species.

I analysed the data for each primer pair separately, and also with all the fragments from the three primer pairs combined. The results of these analyses were similar for each primer pair, so the following results show the analyses conducted on all fragments.

3.3.1 Genetic variation

Species-level genetic variation did not differ significantly between common and rare species (ANOVA, df = 1, P > 0.30) based on the complete data set. Estimates of genetic variation calculated across all of the 389 fragments were higher for the rare P. glaucescens (% polymorphism = 68.1, Hj = 0.105, I = 0.177) than for the other three species (Table 3.2). Both the average expected heterozygosity and Shannon’s I values were similar for P. lanceolata (common, Hj = 0.084, I = 0.145), P. mollis ssp. maxima

(rare, Hj = 0.078, I = 0.128), and P. mollis ssp. nectens (common, Hj = 0.078, I =

0.133). However, the % polymorphism was less for the rare P. mollis ssp. maxima

(42.9%) compared to both P. mollis ssp. nectens (59.9%) and P. lanceolata (62.0%), which reflects the number of fragments detected for each species (Table 3.2). 100

Table 3.2: The level of genetic variation within species, calculated for all four species (based on all 389 loci), for the two pairs of closely related common and rare Persoonia species. I calculated these measures of genetic variation for each species separately in AFLP-surv 1.0 and Popgen 1.31. n = number of individuals genotyped. # loci = number of fragments scored for the species. % polymorphism = % of polymorphic fragments of any frequency. Expected heterozygosity = mean expected heterozygosity averaged over all loci. Shannon’s I = Shannon's Information index.

Species Expected n #loci % polymorphism Shannon’s I (Rarity) heterozygosity

Mean SE Mean SE

P. mollis ssp. nectens 81 389 59.9 0.078 0.006 0.133 0.010 (common) P. mollis ssp. maxima 69 389 42.9 0.078 0.007 0.128 0.011 (rare) P. lanceolata 78 389 62.0 0.084 0.007 0.145 0.010 (common) P. glaucescens 79 389 68.1 0.105 0.007 0.177 0.011 (rare)

101

To estimate the levels of genetic variation within populations, I used only the fragments that amplified in at least one individual of the species within the four populations surveyed. An ANOVA designed to compare the levels of genetic variation within populations (n = 4) of the two pairs of common and rare Persoonia species found plant rarity to be a significant factor. The common species had significantly (% polymorphism, F1,12 = 12.06, P = 0.0046; Hj, F1,12 = 16.30, P = 0.0016; Shannon’s I,

F1,12 = 10.02, P = 0.0081) less genetic variation within populations than the rare species

(Table 3.3). Both the rare species had 10% more polymorphic loci than their closely related common species (61.3% P. mollis ssp. maxima cf. 54.5% P. mollis ssp. nectens;

61.0% P. glaucescens cf. 53.2% P. lanceolata). The level of expected heterozygosity and Shannon’s I I found in the rare P. glaucescens (Hj = 0.148, I = 0.216) were more than 15% greater than the closely related common P. lanceolata (Hj = 0.128, I = 0.186), and more than 30% greater in P. mollis ssp. maxima (rare; Hj = 0.170, I = 0.240) than P. mollis ssp. nectens (common; Hj = 0.124, I = 0.182) (Table 3.3). The trend was similar when only the fragments common to all species were included in the analysis (Table

3.4), although the difference was not significant. 102

Table 3.3: The level of genetic variation within populations for two pairs of common and rare Persoonia species for each species separately. I calculated these measures of genetic variation (including only the fragments it produced) in AFLP-surv 1.0 and Popgen 1.31. n = number of individuals genotyped. # loci = number of fragments scored for the species. % polymorphism = % of polymorphic fragments of any frequency. Expected heterozygosity = mean expected heterozygosity averaged over all loci. Shannon’s I = Shannon's Information index.

Expected Population n #loci % polymorphism Shannon’s I heterozygosity Mean SE Mean SE P. mollis ssp. nectens (common) CO 19 241 60.2 0.123 0.009 0.187 0.048 KE 20 241 49.4 0.123 0.010 0.175 0.051 LO 20 241 51.0 0.120 0.010 0.174 0.051 NA 20 241 58.5 0.131 0.010 0.193 0.050 mean 20 241 54.5 0.124 0.010 0.182 0.050 P. mollis ssp. maxima (rare) BI 16 167 60.5 0.170 0.014 0.245 0.063 FL 17 167 55.1 0.173 0.014 0.243 0.064 GA 18 167 76.7 0.185 0.014 0.269 0.057 KU 16 167 52.7 0.152 0.013 0.201 0.058 mean 17 167 61.3 0.170 0.014 0.239 0.061 P. lanceolata (common) BU 19 243 62.5 0.137 0.010 0.202 0.051 CR 18 243 33.7 0.088 0.010 0.120 0.050 ME 21 243 53.1 0.134 0.010 0.197 0.051 RY 19 243 63.4 0.154 0.011 0.226 0.055 mean 19 243 53.2 0.128 0.010 0.186 0.052 P. glaucescens (rare) BE 21 266 62.8 0.156 0.010 0.224 0.052 JO 20 266 62.0 0.142 0.010 0.209 0.051 RO 18 266 60.5 0.144 0.009 0.219 0.054 WE 19 266 58.7 0.149 0.010 0.213 0.053 mean 20 266 61.0 0.148 0.010 0.216 0.052

103

Table 3.4: The level of genetic variation within populations for two pairs of common and rare Persoonia species using only the 90 fragments that were common to all species. I calculated these measures of genetic variation in AFLP-surv 1.0 and Popgen 1.31. n = number of individuals genotyped. # loci = number of fragments scored for the species. % polymorphism = % of polymorphic fragments of any frequency. Expected heterozygosity = mean expected heterozygosity averaged over all loci. Shannon’s I = Shannon's Information index.

Expected Population n #loci % polymorphism Shannon’s I heterozygosity Mean SE Mean SE P. mollis ssp. nectens (common) CO 19 90 78.9 0.215 0.017 0.361 0.056 KE 21 90 62.2 0.219 0.019 0.317 0.062 LO 20 90 65.6 0.212 0.020 0.311 0.059 NA 20 90 75.6 0.236 0.018 0.376 0.059 mean 20 90 70.6 0.221 0.019 0.341 0.059 P. mollis ssp. maxima (rare) BI 16 90 72.2 0.233 0.020 0.359 0.067 FL 17 90 65.6 0.234 0.021 0.338 0.065 GA 18 90 81.1 0.249 0.020 0.393 0.055 KU 16 90 57.8 0.187 0.019 0.274 0.065 mean 17 90 69.2 0.226 0.020 0.341 0.063 P. lanceolata (common) BU 20 90 84.4 0.248 0.018 0.412 0.054 CR 18 90 48.9 0.146 0.019 0.210 0.057 ME 21 90 66.7 0.200 0.019 0.320 0.058 RY 18 90 84.4 0.261 0.019 0.395 0.054 mean 19 90 71.1 0.214 0.019 0.334 0.056 P. glaucescens (rare) BE 21 90 78.9 0.247 0.017 0.374 0.054 JO 20 90 78.9 0.218 0.018 0.361 0.054 RO 17 90 73.3 0.209 0.017 0.372 0.065 WE 19 90 70.0 0.211 0.017 0.347 0.061 mean 19 90 75.3 0.221 0.017 0.363 0.059

104

3.3.2. Genetic structure

Analysis of Molecular Variance (AMOVA) revealed that there were significant levels of variation among species (P < 0.0001) and populations (P < 0.0001). In my analysis of the total data set 20.5% of variation was attributed to differences among species, and

14.9% population differentiation. When analysing the species pairs separately, I found similar levels of genetic variation partitioned among populations for both species pairs

(P. mollis ssp. nectens and ssp. maxima 16.1%; P. lanceolata and P. glaucescens

15.7%). The proportion of inter-population variation did not vary consistently with rarity when I analysed the data separately for each species. I found relatively more variation among populations for the rare P. mollis ssp. maxima (21.1% P = 0.001) than the closely related common P. mollis ssp. nectens (16.5% P = 0.001). However, I also found that populations of P. glaucescens (rare 15.8% P = 0.001) were less differentiated than P. lanceolata populations (common 20.6% P = 0.001) (Figure 3.1). 105

Common Rare

P. mollis ssp. nectens P. mollis ssp. maxima

16.5% 21.1% Pair 1

Among Among Populations Populations Within Within Populations Populations

P. lanceolata P. glaucescens

20.6% 15.8% Pair 2

Among Among Populations Populations Within Within Populations Populations

Figure 3.1: AMOVA results for the two pairs of common and rare Persoonia species showing the partitioning of genetic variation within and among populations. P < 0.001 based on 1000 permutations in GenAlEx. 106

The relationship between genetic and geographic distance was more pronounced among populations for the common species (P. mollis ssp. nectens r2 = 0.674; P. lanceolata r2

= 0.896) than the rare species (P. mollis ssp. maxima r2 = 0.228; P. glaucescens r2 =

0.112). Of these Persoonia species, I only detected a significant correlation between genetic and geographic distance in the common P. lanceolata (MANTEL; P = 0.035), which has the greatest geographic range (>380 km; Table 3.5). However, further sampling of populations would increase the power to detect significant relationships in

P. mollis ssp. nectens, P. mollis ssp. maxima and P. glaucescens and the lack of a significant correlation between genetic and geographic distance should be treated with some caution. The closely related rare P. glaucescens has a much smaller geographical range (<30 km), however the genetic distance between populations is similar to its common relative (P. lanceolata FST = 0.071 to 0.320, P. glaucescens FST = 0.090 to

0.229) (Figure 3.2). 107

Table 3.5: The genetic and geographic distance between populations of common and rare Persoonia species.

Pair-wise FST values (GenAlEx, P < 0.05) are below the diagonal and linear geographic distances (km) are above the diagonal.

Species pair 1 Species P. mollis ssp. nectens (common) Populations KE LO NA CO KE 0 19.07 44.68 31.41 LO 0.03 0 41.12 41.25 NA 0.20 0.22 0 28.94 CO 0.22 0.22 0.05 0 Species P. mollis ssp. maxima (rare) Populations BI FL GA KU BI 0 1.48 4.41 4.09 FL 0.03 0 3.91 3.06 GA 0.17 0.15 0 6.47 KU 0.32 0.31 0.24 0 Species pair 2 Species P. lanceolata (common) Populations CR RY BU ME CR 0 253.38 295.93 380.87 RY 0.24 0 45.47 127.49 BU 0.28 0.11 0 87.41 ME 0.32 0.19 0.07 0 Species P. glaucescens (rare) Populations BE JO RO WE BE 0 8.35 21.25 7.29 JO 0.09 0 27.07 9.88 RO 0.17 0.12 0 17.31 WE 0.21 0.23 0.09 0

108

]) 0.50 ST

F 0.45

/[1- 0.40 ST

F 0.35 0.30 0.25 0.20 0.15 0.10 0.05

Genetic differentiation( 0.00 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400

Geographic distance (km)

Figure 3.2: The relationship between genetic differentiation and geographic distance among populations of the common P. lanceolata (black triangles) and the closely related rare P. glaucescens (grey squares). The black line represents the ‘line of best fit’ (y = 0.0007x + 0.0646) for P. lanceolata (MANTEL r2 = 0.8959 P = 0.035). 109

3.3. Discussion I found no evidence that lower levels of genetic variation are determining rarity in fire sensitive Persoonia species. Contrary to theoretical predictions (Wright, 1931) my comparisons of closely related common and rare Persoonia species detected significantly higher levels of genetic variation in the rare species, despite their relatively small population sizes and narrow geographic ranges. The loss of alleles through genetic drift within populations of these historically rare species may therefore not be as great as predicted. A plausible explanation for the persistence of variation in these populations could be that the long lived soil seed-banks found in Persoonia species

(Auld et al., 2000) buffers populations against the effects of genetic drift (Llorens et al.,

2004), and that current population sizes may reflect the recent effects of fragmentation and frequent fire since European settlement and as such loss of genetic variation may not be detected (Young et al., 1999). Nevertheless, my findings provide support for the prediction that rare species have limited gene flow as evidenced by greater differentiation of populations in rare compared to common species (Frankham et al.,

2002). I found that populations of the rare Persoonia species were more differentiated than those of the common species when comparisons are made over similar spatial scales. In fact, the lower levels of genetic variation detected in the common species could be explained by rapid range expansion through long-distance dispersal events from a narrow gene pool (Hewitt, 2000; Tang et al., 2003; Ye et al., 2004).

3.3.1. Does genetic variation relate to plant rarity?

Empirical studies exploring the relationship between genetic variation and plant rarity have produced mixed results, depending on the type of comparison employed. Different types of rarity, measured in terms of local abundance, geographic range and habitat specificity (Rabinowitz, 1981), as well as the duration of rarity, may have very different 110 genetic implications. In my study, I make clear comparisons between species pairs that differ dramatically in terms of their local abundance and geographic range (Table 3.1)

(with similar habitat requirements), both of which are likely to be consequences of climate change since the late Pleistocene (Pickett et al., 2004).

I found no consistent relationship between total intra-species genetic variation and rarity. The only robust finding that came out of my analysis of variance testing for the effect of plant rarity was that the rare P. glaucescens had more genetic variation than the closely related common P. lanceolata. Despite the fact that P. glaucescens covers a geographic range less than one fourteenth the area encompassing P. lanceolata, and that it is restricted to open woodlands in montane locations (unlike P. lanceolata that is found in coastal heath and montane woods), it appears that the greater geographic range and wider habitat preference of the common P. lanceolata is not associated with greater genetic variation. This goes counter to the idea that common species have more genetic variation than rare species (Frankham et al., 2002), but mixed results have been reported in other studies comparing common-rare congeners (Coates et al., 2003). A potential explanation could be that local selection and drift in several small isolated populations of P. glaucescens has increased genetic variation across the species (Altukhov, 1981).

Alternatively, the rare species may have more genetic variation because they are hybrids or polyploids, however this appears unlikely because the number of chromosome appears to be stable in Persoonia (n = 7 in 21 species investigated; Stace et al., 1998).

The amount of genetic variation within populations (intra-population variation) is an important determinant of the ability of populations to persist (Saccheri et al., 1998), particularly in unpredictable environments (e.g. fire prone habitats). It is well- established in theory that small populations will lose genetic variation over time as a result of genetic drift (Wright, 1931). Rare species generally have lower levels of 111 genetic variation within populations than related common species (Loveless and

Hamrick, 1984; Cole, 2003; Nybom, 2004). However, numerous exceptions to this general trend have been found. For example, in a meta-analysis, Cole (2003) found 10 out of 48 comparisons in which rare species have higher levels of polymorphism than common species and 14 out of 54 comparisons in which rare species have higher levels of heterozygosity. The rare species I studied, which had relatively small standing populations, had similar (or even greater) levels of genetic variation than closely related common species with much larger populations. I therefore reject my prediction that “the rare species will have less genetic variation within populations than common species, reflecting the increased susceptibility of small populations to lose variation through genetic drift”. One possible explanation is that my estimate of population size is likely to underestimate the effective population size of these Persoonia species, all of which can develop substantial seed-banks in the soil (Auld et al., 2000). A persistent seed- bank provides the opportunity for gene flow over time (between the offspring of multiple cohorts) and can potentially buffer populations against the effects of genetic drift (Llorens et al., 2004). Furthermore, there may not have been sufficient time to detect the recent effects of habitat fragmentation (<150 year ago) in these long-lived perennials (Rossetto et al., 1995). The differences I detected in the genetic variation between common and rare species (Table 3.3) appear to be counter-intuitive (and in the opposite direction to that predicted based on population size differences). This relationship is intriguing and warrants further investigation to address its biological importance; does it reflect rapid colonization in the common species?

Overall, the average levels of genetic variation within populations of all four Persoonia species were low (Hj < 0.17; Table 3.3) for long-lived perennial species (Hj = 0.25) with an outcrossing breeding system (Hj = 0.27) and seed dispersal through animal 112 ingestion (Hj = 0.24) based on dominant markers (Nybom, 2004). This may be due to historical bottlenecks, potentially attributed to continental drying during glaciation events (Pickett et al., 2004). The predicted relationship between genetic variation and drift assumes that the system is at equilibrium (Wright, 1969). In reality while the general distribution of these species may have been relatively constant for thousands of years, metapopulation processes may reduce genetic variation (Pannell and

Charlesworth, 2000) in these fire prone landscapes through continual colonization and extinction events in these obligate-seeding Persoonia species. Whatever the mechanism, the question of whether and how this variation relates to population persistence still remains. This requires an understanding of the demographic effect of frequent fire events on population persistence, and potential long-distance seed dispersal events on population colonization ability, in conjunction with estimates of genetic variation (all of which are currently being investigated in the family Proteaceae; Ayre and Whelan).

3.3.2. Does limited gene flow cause rarity?

A plausible explanation for the differences in geographic range between common and rare Persoonia species is a more rapid expansion by common species from glacial refugia (Krauss, 1998). Assuming that common species are better colonists (and they have been found to have more seed dispersed; Rymer, unpublished) they might be expected to have increased levels of gene flow between populations maintaining their genetic similarity. However, my results suggest that the level of genetic divergence in

Persoonia species is not consistently related to rarity across their geographic range

(Figure 3.1). A lack of relationship between population differentiation (FST) and geographic range has also been found in recent reviews (Cole, 2003; Nybom, 2004).

Plant breeding systems and seed dispersal mechanisms have been found to be more important in determining population differentiation than geographic range (Cole, 2003; 113

Nybom, 2004). As closely related species typically share similar breeding systems and dispersal mechanisms, genetic distances between populations may not be expected to differ in these comparisons despite the sharply contrasting geographic ranges.

To compare population genetic differentiation the geographic separation of sampled populations should be standardised. Spatial analysis (such as MANTEL’s test) allows for comparison of the genetic differentiation between populations of species that differ in geographic range by relating genetic and geographic distance (Heywood, 1991). I found genetic differentiation to be significantly correlated with geographic distance for populations of the common P. lanceolata (explaining 89.6% of the variation, P = 0.035;

Figure 3.2). No relationship was found for the other species, which had considerably smaller geographic ranges, suggesting that isolation by distance model does not apply at these smaller spatial scales. Nevertheless, this enables us to compare the level of genetic differentiation found in the rare P. glaucescens to its common congener. An equivalent amount of genetic divergence (FST = 0.229) in the two species equates to up to ten times the geographic distance (approximately 30 km cf. 300 km) in the common P. lanceolata

(Figure 3.2). The other species pair shows a similar pattern, with the common P. mollis ssp. nectens having less genetic differentiation (FST = 0.223 cf. 0.318) despite having a larger geographic range (approximately 44.6 km cf. 6.5 km) than its rare congener (P. mollis ssp. maxima). Assuming genetic differentiation is inversely related to gene flow

(Wright, 1951), this indicates that common Persoonia species have greater levels of gene flow between populations than rare species, supporting the findings of the meta- analysis performed by Cole (2003) (based on FST in 65% of the 37 comparisons).

Further research investigating the levels of gene flow in common and rare species at similar spatial scales using both indirect and direct methods needs to be done to confirm this relationship. 114

3.3.3. Conclusion

This study provides an important first step in understanding the association between genetic variation and plant rarity in fire sensitive Persoonia species. My finding that the rare species contained greater genetic variation than the common species goes against theoretical expectations. However given the potential for soil seed-banks to buffer populations against the effects of genetic drift and the relatively recent occurrence of habitat fragmentation, these species may require more time for effects of population size to be detected. I propose that the most likely explanation for the lower genetic variation found in common Persoonia species is rapid range expansion through long-distance dispersal events from a narrow gene pool. My findings suggest that common species have higher levels of gene flow support this hypothesis, but further investigations are required to determine historical colonization rates for common and rare species. This study will provide a valuable base line for future investigations into the long-term effects of anthropogenic disturbances.

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Chapter 4 : Reproductive success and pollinator effectiveness differ in common and rare Persoonia species (Proteaceae).*

4.1. Introduction The reproductive success of plants and hence their abundance must be at least partially dependent on their breeding systems (e.g. level of self-compatibility) and the activity of pollinators. Variation in plant breeding systems and the attractiveness of plants to pollinators may therefore be a determinant of rarity. However, empirical investigations of the causes of rarity have to date typically looked at these attributes in isolation and have so far yielded equivocal results (Murray et al., 2002a). The small number of relevant studies also seldom includes comparisons of closely related taxa with similar suites of pollinators and floral characters (but see Banks, 1980). This kind of comparative approach has been strongly advocated as a tool with which to investigate the causes of rarity (Bevill and Louda, 1999).

Pollinators play an important role in the movement of pollen from flowers within and among flowering plants, thereby determining the availability of potential mates and influencing the reproductive success of plants (Talavera et al., 2001). Some animals are specialist-pollinators, being well adapted to forage for the floral resources of a particular species (or group of related species), which in turn receives compatible pollen for sexual reproduction. In contrast, generalist-pollinators utilize resources from a wide range of flowering plants, and often have characteristics that enable them to forage extensively on different species without being well suited to pollinate any particular species

* An edited version of this chapter has been published in Biological Conservation in 2005, volume 123, pages 521-532. 116

(Thostesen and Olesen, 1996; Waser et al., 1996). The European honeybee (Apis mellifera) is a generalist pollinator that harvests floral resources from numerous flowering plants in many cases without pollinating them (Paton, 1997). Honeybees have been introduced to many countries, including Australia in the 1820’s, and have the potential to disrupt native plant/pollinator relationships (Butz Huryn, 1997).

The impact of pollinators on the mating system of plants (i.e. level of outcrossing) and their reproductive success is dependent, in part, on the level of self-compatibility exhibited by the plant. Indeed levels of self-compatibility can vary dramatically within

(Young and Brown, 1998; McIntosh, 2002) and among plant populations (e.g.

Vaughton, 1989; Medrano et al., 1999; Eckert, 2002). So, in order to predict the impacts of habitat fragmentation and plant rarity an understanding of the interactions between the levels of self-compatibility and patterns of pollinator activity is required. The interaction between the quantity and quality of pollen a plant receives and the level of self-compatibility determines the degree to which reproductive success is affected by fragmentation (Aizen et al., 2002). For example, obligate-outcrossers are dependent on reliable pollinators transferring pollen between compatible mates to ensure fruit production (Richardson et al., 2000; Goodwillie, 2001). In such a case, I predict the impacts of rarity will be greatest for species with only a single specialist-pollinator, because as a population becomes smaller and more isolated the visitation rates will decrease as a result of stochastic processes (Steffan-Dewenter and Tscharntke, 1999).

At the other extreme, autogamous species do not require pollinators to produce fruit and therefore reproductive success is likely to be less affected by fragmentation. Plants that are unable to set fruit via autogamy but are self-compatible still require pollinators to transfer pollen to the stigma. In this case, I predict that the impact of fragmentation will be least severe for plant species with a suite of generalist-pollinators. However, there 117 are a wide range of cases between these extremes that offer no simple predictions, including plants with partial self-compatibility and a mix of specialist and generalist- pollinators. The impacts of fragmentation and rarity are best explored in closely related species that have similar floral biology and share pollinators, whilst differing in local abundance and geographic distribution.

In this study, I used a comparative approach to test for differences in reproductive success, breeding system, and pollination ecology between the two pairs of common and rare fire sensitive Persoonia species. Differences in the reproductive biology is a plausible explanation for differences in rarity among these obligate seeder species, given that the availability of seed is essential for the establishment of population after fire disturbance, and in the Sydney region many Persoonia are found in fire prone habitats (Chapter 1).

I hypothesised that the common species would have greater fecundity than rare species, due to differences in the breeding system and/or pollination. I predicted that fruit production in the rare species would be limited by effective pollination, being self- incompatible and receiving fewer visits from effective pollinators. The objectives of this study were first to determine the reproductive success in common and rare Persoonia species, and then to test for differences in the breeding system and pollination.

Specifically, I aimed to (1) assess the level of self-compatibility, (2) determine if pollination is limiting reproductive success, and (3) investigate the behaviour and the visitation rates of pollinators. 118

4.2. Methods 4.2.1. Study species and sites

Persoonia species display a range of breeding systems, from self-compatible to obligate-outcrossing (Krauss, 1994; Goldingay and Carthew, 1998; Trueman and

Wallace, 1999; Cadzow and Carthew, 2000). Flowers are small (6-14 mm long) and hermaphroditic. The peak flowering period is summer to autumn (November to April), and fruits mature into fleshy drupes in late spring (Weston, 2003).

All Persoonia species, for which pollinators are known are pollinated by native bees, the most important of which appear to be species of Leioproctus subgenus Cladocerapis

(Bernhardt and Weston, 1996). These are solitary bees that appear to be specialist foragers on and pollinators of Persoonia (Wallace et al., 2002). The European honeybee

(Apis mellifera) also visits the flowers of Persoonia. Since its introduction in Australia

(c.1820s) Apis mellifera has become the dominant floral visitor in many species (Paton,

1997).

For each of these four species (Chapter 1), I selected two sites to compare reproductive success, breeding systems and pollinator behaviour. Sites (approximately 100 x 100 m) were chosen that contained relatively large populations (>100 plants). As no locations were found where the study species co-occurred in large enough numbers to conduct this work, separate study sites were used for each species (Table 4.1).

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Table 4.1: The estimated population size, plant density, plant height and number of open flowers per plant for common and rare Persoonia species at the study sites.

Species (Rarity) Mean (SE) Study site Latitude, Population Plants density Plant size Floral display Longitude a size b c d e P. mollis ssp. nectens (common) 1. Hilltop 34°19'48"E 300 0.5 (0.10) 1.8 (0.30) 260 (2.4) 150°28'41"S 2. Little River 34°16'05" E 600 1.0 (0.15) 3.2 (0.40) 392 (2.5) 150°30'54" S P. mollis ssp. maxima (rare) 1. Ku-ring-gai 33°40'34" E 200 0.3 (0.05) 3.5 (0.35) 253 (2.6) 151°8'02" S 2. Galston Creek 33°39'21" E 100 0.2 (0.05) 2.5 (0.30) 170 (2.3) 151°04'12" S P. lanceolata (common) 1. Wise’s Track 34°06'47" E 500 1.5 (0.20) 1.3 (0.10) 79 (1.9) 151°03'34" S 2. Bundeena 34°06'11" E >1000 2.8 (0.20) 1.2 (0.10) 90 (2.0) 151°05'60" S P. glaucescens (rare) 1. Braemar 34°25'05" E 400 1.3 (0.20) 2.5 (0.30) 54 (1.8) 150°28'26"S 2. Buxton 34°15'07" E 100 0.4 (0.10) 2.0 (0.25) 71 (2.0) 150°30'54" S a Based on GPS position using datum WGS1984 b Estimated number of flowering individuals per population c Number of flowering plants per 10 m2 d Plant height (m) e Number of open flowers per plant during peak flowering season

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4.2.2. Reproductive success

At each site, I randomly selected (using random number) five large reproductive plants

(along haphazard transects across the population) to represent the population. On each plant floral buds were tagged immediately prior to opening (January to April 2001).

These flowers were left open to pollinator visits, and monitored monthly until the fruit matured (October-November 2001). On each occasion, flowers were scored as ‘aborted’ if the gynoecium dropped off, and ‘fertilized’ if the ovary was swollen, indicating fruit initiation. The proportion of flowers that developed into mature fruits was used as an estimate of reproductive success in common and rare species after natural pollination.

I used an ANOVA (performed in SAS version 8.2) to test for differences in the reproductive success between the common and rare species. The ANOVA was constructed with Pair (two pairs of closely related species) and Rarity (common vs. rare) as factors in a 2 × 2 factorial design, with Site and Plant (within Site) as random block factors. The raw data in the analyses were the proportion of flowers maturing into fruits.

To satisfy the assumptions of normality and homogeneity of variances I used angular transformation.

4.2.3. Experimental pollination

I carried out experimental pollinations to characterise breeding systems and to determine whether pollination was limiting reproductive success. At each site (Table

4.1), I selected another five large reproductive plants to undertake the hand-pollinations.

From the available branches (20 - 40 cm in length) that were producing floral buds, I randomly selected four and assigned each to one of the following treatments: (1) Open:

Floral buds tagged immediately prior to opening and left to allow pollinators to visit freely. (2) Closed: Floral buds tagged immediately prior to opening and the branch was bagged to exclude all flower visitors. (3) Self: Anthers removed from 1-2 day-old 121 flowers (which appeared receptive and anthers had not yet dehisced) that opened within the bagged branch, self-pollen was applied to the stigma, the treated flowers were tagged and the branch re-bagged. (4) Cross: Anthers removed from 1-2 day-old flowers that opened within the bag, cross-pollen was applied to the stigma, the treated flowers were tagged and the branch re-bagged.

I compared the level of fruit-set after open-pollination on plants with and without additional treatments (including flowers that received high quality pollen from the cross-pollination treatment), which yielded no evidence for competition among

2 branches for resources (χ 7 = 6.95, P > 0.25). The allocation of plant resources for fruit development in Persoonia species is more likely to be confined within branches

(Trueman and Wallace, 1999), so the pollination treatments carried out on the same plant should be independent of each other.

In every treatment, I removed all insect-damaged floral buds open flowers and senesced flowers from the selected branches. I tagged the treated flowers with 2 mm clear plastic bands placed on the branch immediately below the flower. I used plastic coated wire to attach 30 by 60 cm black netting bags (0.5 mm pore-size) to individual branches. I achieved pollination by application of either self-pollen (collected from other flowers on the same plant as the flowers to be treated) or Cross-pollination (collected from three plants that were more than 10 m away from the treated plant). Pollen was collected by removing the anthers from bagged (1-2 day-old) flowers, placing them in a 1.5mL centrifuge tube and flicking the tube until the pollen adhered to the sides. I applied pollen to the receptive stigmas with a toothpick within 2 hours of collection.

I performed the pollination treatments on flowers between January and March 2001.

Branches were checked two days after initial bagging, and I pollinated “receptive” flowers (i.e. with sticky stigmatic surfaces). I pollinated additional flowers on the 122 following days until 10-40 flowers had been treated per branch. Bags were removed after all the treated flowers had senesced, about two to three weeks after being pollinated.

I monitored the treated flowers monthly until the fruit matured in October-December

2001. On each occasion, flowers were scored as ‘aborted’ if the gynoecium dropped off, and ‘fertilized’ if the ovary was swollen, indicating fruit initiation. Prior to fruit drop, branches were re-bagged (at the end of September). Fruit set was recorded when the fruits matured (at the beginning of fruit drop).

Seed viability could not be tested at all the study sites due to extensive wildfires in

December 2001. Four of the study sites were burned prior to fruit collection: P. mollis ssp. nectens at Hill Top and Little River, P. glaucescens at Buxton and P. lanceolata at

Wise’s Track. As a result, a statistically valid comparison of seed-viability in common and rare species was not possible.

I used an ANOVA, to test the hypothesis that common and rare species differ in their responses to the pollination treatments. The ANOVA was constructed with Treatment

(four pollination treatments, open, closed, self and cross), Rarity (common vs. rare), and

Pair (two pairs of closely related species) as fixed factors. These three factors

(Treatment, Rarity and Pair) were combined in a full factorial design. Site and Plant

(within Site) were random block factors. The two sites per species were used as replicates for each Pair by Rarity combination (2 sites/species x 4 species = 8 sites). The raw data were the proportion of flowers that matured fruits for each plant (n=5). I transformed the raw data using an angular transformation to overcome heterogeneity of variances. After transformation a plot of the residuals versus the fitted values showed a relatively random scatter of points, which implies homogeneous variation (Zar, 1999).

A histogram of the residuals suggested a normal distribution (Kolmogorov-Smirnov test 123 for normality P > 0.15). Where significant differences occurred, multiple comparisons were performed using Tukeys Studentised Range Test. Analyses of the raw data and the transformed data yielded the same significant results, so I used the raw data to construct the Tables and Figures for ease of interpretation.

4.2.4. Pollinator observations

To determine the effectiveness of the insect visitors as pollinators, I made observations of the behaviour and movement of individual insects as they foraged on Persoonia plants within the study sites. I observed the foraging behaviour of pollinators for a period of 60 minutes for two days at each site. Observations were made during the middle of the day 1100-1500 hr during the period of maximum insect activity

(Richardson et al., 2000). I recorded the time that each insect spent on each flower, the number of flowers visited per plant, the total time foraging on the plant, whether the stigma and/or anthers were contacted and whether the insects were collecting pollen and/or nectar. In addition, the distance insects moved to the next plant was recorded, where possible. Insects were followed from plant to plant, to get an indication of the movement of pollen within the study sites. I also noted whether the floral visitor had pollen visible when they arrived at the plant. The ratio of the number of within versus between-plant movements was used as an indication of the quality (i.e. potential effectiveness) of pollen received by flowers visited by insect visitors.

I also observed pollinators in order to estimate visitation rates (pollen quantity). For each of the study sites (Table 4.1), I observed five large reproductive plants for 10 minutes during the middle of the day 1100-1500 hr and the number of introduced honeybees (Apis mellifera); native bees (Leioproctus subgenus Cladocerapis spp.) and other floral visitors (including Exoneura species) were recorded to quantify the number of insects visits received by common and rare species. 124

I attempted an ANOVA (design as for reproductive success) to examine the hypothesis that common species receive more insect visitors compared to rare species. However some of the data sets (the native bees, proportion of native bees, and the rate of native bee visits) showed skewed distributions that could not be improved through transformation. I therefore used a randomisation analysis (Edgington, 1995) that was constructed with Pair (random) and Rarity (fixed) factors in a full factorial design using the mean values for number of visits for each Pair by Rarity combination (4 species) as the raw data. To test for a Pair by Rarity interaction all possible randomisations (2520 in total) of pairs of raw data values to the four treatment combinations were carried out, and the F-value for the interaction calculated for each within a 2-way factorial ANOVA.

The original F-value calculated from the raw data was then compared with the distribution of F-values after randomisation to obtain the probability of achieving a value as extreme as this by chance (P-value). To test for differences between the two species pairs (Pair 1 and 2) the four mean values within each Rarity class (common and rare) were randomly allocated to the two Pairs without altering their Rarity, resulting in

36 allocations. Similarly, differences between the common and rare species (Rarity) were tested by randomly allocating the four mean values within each species pair (1 or

2) to the two Rarity classes without altering their species pair (36 allocations). F-values were calculated from each allocation. The F-value from the raw data was compared with this distribution of 36 values to obtain the probability value. The minimum possible P-value (2/36 or 0.056) for the test of each of the main effects (Pair and Rarity) was interpreted as a significant result. 125

4.3. Results 4.3.1. Reproductive success

Common and rare species showed a similar pattern of fruit initiation and development.

Fruits initiated after 70-100 days following flowering in all species except P. glaucescens, which retained flowers much longer and initiated fruits after about 210 days. There was very little fruit abortion (<15% after initiation) and fruit matured into a fleshy drupe (8-14 mm diameter) in all species about 250 days after flowering. All species had high levels of seed viability, P. mollis ssp. nectens (91%), P. mollis ssp. maxima (89%), P. lanceolata (97%) and P. glaucescens (86%) in fruit matured after natural pollination.

The common species (P. mollis ssp. nectens and P. lanceolata) had significantly higher levels of fruit-set than the rare species (P. mollis ssp. maxima and P. glaucescens)

(ANOVA; Rarity, F1,4 = 15.08, P = 0.018). On average, more than one third of flowers matured fruits in the common species after natural pollination compared to less than one fifth in the rare species (Figure 4.1).

4.3.2. Breeding system

All species showed a similar response to the pollination treatments (Table 4.2). There were highly significant effects of pollination treatments on fruit-set (Treatment, P <

0.0001) (Table 4.2). Very few (<1% of treated flowers) fruits matured from the closed or self-pollination treatments (Figure 4.2), indicating that both the common and rare species are self-incompatible. On the other hand, a relatively high proportion (range 17-

54%) of fruits matured in both the open and cross-treatments consistently among sites and species (Table 4.3). This indicates that species are outcrossers and cannot produce seeds by selfing.

126

0.70 A

0.60 AB A A 0.50

0.40

fruits 0.30 B B B 0.20 B

0.10

0.00 Proportion of open flowers that matured Proportion of open flowers that matured P. mollis subsp. P. mollis subsp. P. lanceolata P. glaucescens nectens maxima

Figure 4.1: The mean reproductive success (proportion of flowers that matured fruit) in plants (n=5) open to natural pollination for common and rare Persoonia species in the eight study sites (as in Table 1). For each species site 1 and 2 are the clear and filled bars, respectively. Letters show the results of the Tukeys test, where two mean values share the same letter are not statistically different (α=0.05). 127

Table 4.2: Mixed model ANOVA for a comparison of the pollination treatments (Treatment being open, closed, self, cross) in closely related (Pair) common and rare species (Rarity) across populations (Site). Data = ARCSIN(√{mature fruits/ number of treated flowers }). To calculate the F values the Mean Square (MS) for Pair, Rarity and Pair*Rarity was divided by MS(Site), while Treatment, Rarity*Treatment, Pair*Treatment, Pair* Rarity*Treatment and Site*Plant were divided by MS(Error), and Site was divided by MS(Site*Plant).

Source of variance df MS F value P Pair 1 21.53 0.15 0.72 Rarity 1 78.19 0.54 0.50 Treatment 3 14252.00 185.45 0.0001 Pair*Rarity 1 29.02 0.20 0.68 Pair*Treatment 3 15.26 0.20 0.90 Rarity*Treatment 3 741.17 9.64 0.0001 Pair*Rarity*Treatment 3 16.28 0.21 0.89 Site 4 145.36 1.71 0.17 Site*Plant 32 84.85 1.10 0.34 Error 108 76.85 128

0.50 A A 0.45

0.40 AB 0.35 0.30

0.25 B 0.20 0.15

that matured fruits matured that 0.10 0.05 C C C C Proportion of treated flowers flowers treated of Proportion 0.00 Open Closed Self Cross Pollination treatments

Figure 4.2: The mean (± SE bars) proportion of flowers that matured into fruits for each of four pollination treatments in the common (open bars) and rare (closed bars) Persoonia species. Letters show the results of the Tukeys test, where a Treatment*Rarity combination shares the same letter as another they are not statistically different (α=0.05). 129

Table 4.3: The mean (SE) proportion of treated flowers that matured into fruits from the pollination experiment (open, closed, self and cross) for common and rare Persoonia species at the study sites.

Pollination treatments

Species (Rarity) Site Open Closed Self Cross P. mollis ssp. nectens Hilltop 0.34 (0.13) 0.01 (0.01) 0.00 (0.00) 0.35 (0.09) (common) Little River 0.35 (0.07) 0.00 (0.00) 0.00 (0.00) 0.22 (0.03) mean 0.35 (0.10) 0.00 (0.00) 0.00 (0.00) 0.28 (0.08) P. mollis ssp. maxima Ku-ring-gai 0.18 (0.06) 0.00 (0.00) 0.01 (0.01) 0.54 (0.09) (rare) Galston Creek 0.18 (0.05) 0.00 (0.00) 0.00 (0.00) 0.33 (0.12) mean 0.18 (0.05) 0.00 (0.00) 0.01 (0.01) 0.43 (0.11) P. lanceolata Wise’s Track 0.52 (0.11) 0.00 (0.00) 0.01 (0.01) 0.41 (0.13) (common) Bundeena 0.31 (0.06) 0.01 (0.01) 0.00 (0.00) 0.23 (0.07) mean 0.41 (0.10) 0.00 (0.00) 0.00 (0.01) 0.32 (0.11) P. glaucescens Braemar 0.18 (0.04) 0.01 (0.01) 0.00 (0.00) 0.47 (0.08) (rare) Buxton 0.17 (0.02) 0.01 (0.01) 0.00 (0.00) 0.32 (0.08) mean 0.18 (0.03) 0.01 (0.01) 0.00 (0.00) 0.40 (0.08)

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4.3.3. Pollen limitation

There was a significant interaction between the pollination treatments and plant rarity

(Treatment*Rarity, P < 0.001) (Table 4.2). The two common species, P. mollis ssp. nectens and P. lanceolata, had similar levels of fruit-set in the open (mean ± SE; 0.35 ±

0.10, 0.41 ± 0.10, respectively) and cross-treatments (0.25 ± 0.18, 0.31 ± 0.16). In contrast, in the two rare species, P. mollis ssp. maxima and P. glaucescens, the levels of fruit-set in the open-treatment (0.18 ± 0.05, 0.18 ± 0.03) were significantly lower than the cross-treatment (0.43 ± 0.11, 0.40 ± 0.08) suggesting that pollination (quantity or quality) was limiting fruit-set in these taxa (Table 4.3).

4.3.4. Pollination behaviour and movement

The behaviour and movements of floral visitors were similar on all four Persoonia species. During the 16 hours of direct observations, 241 honeybees (Apis mellifera) and

40 native bees (including 34 Leioprotus species and 6 Exoneura species) were recorded foraging on Persoonia flowers. Although honeybees and native bees displayed very different foraging behaviours, these were consistent across all the study species.

Honeybees contacted the stigmatic surface with their abdomens while foraging for pollen (and nectar), usually remaining on the flower for less than five seconds before moving to another flower. Honeybees visited an average of 8.0 ± 1.8 (± SE) flowers on a plant before moving to another Persoonia plant (of the same species), which was predominantly the plant’s nearest neighbour (distance moved between plants ranged from 0.5-2 m). The majority of pollen collected by honeybees was transferred from their front collecting legs to the corbiculae on their hind legs. Additional pollen was frequently groomed from their abdomen and thorax to be stored in their hind legs where it is inaccessible for pollination. Honeybees collecting pollen consistently arrived at plants with large pollen loads, in the form of a smooth pellet found in the corbiculae. 131

Native bees (predominantly Leioprotus species) contacted the stigma frequently with their thorax and abdomen while collecting nectar and pollen. Fewer flowers were visited within plants (2.1 ± 0.8) by native bees than honeybees. In addition, native bees moved greater distances between Persoonia plants (range 1-5 m, usually out of sight) than honeybees. Native bees collecting pollen arrived with a large pollen load on the hairs of the dorsal surface of the thorax, abdomen and legs.

4.3.5. Pollinator abundance

There was a significant difference in native bee visitation between common and rare species (Table 4.4; Rarity, Randomised P = 0.056). The common species (P. mollis ssp. nectens and P. lanceolata) had three times more native bee (primarily Leioprotus species) visits than the rare species (P. mollis ssp. maxima and P. glaucescens) (0.65 ±

0.20 vs. 0.20 ± 0.09) (Figure 4.3).

Overall, the introduced European honeybee (Apis mellifera) was the most common floral visitor to Persoonia flowers, being observed three to ten times more frequently than native bees. The total number of insect visits (mean ± SE; 5.25 ± 0.71, 4.25 ± 0.69) and the number of honeybee visits (4.60 ± 0.70, 4.05 ± 0.65) were similar for both pairs of common and rare species (Figure 4.3).

There was a significant difference in the number of honeybee visits between the two pairs of closely related species (Randomised P = 0.056) (Table 4.4). Species pair 1 (P. mollis ssp. nectens and P. mollis ssp. maxima) had more honeybees than pair 2 (P. lanceolata and P. glaucescens), which may be due to plant size (Table 4.1). 132

Table 4.4: Mixed model ANOVA for a comparison of honeybee (A) and native bee (B) visitation rates in closely related (Pair) common and rare species (Rarity). (A) Honey bee data = number of visits/plant/10 min. (B) Native bee data = number of visits/plant/10 min. To calculate the F values the Mean Square (MS) for Pair, Rarity and Pair*Rarity was divided by MS(Site). The P value was calculated based on standard F-tables, while the Randomised P value was based on output of the randomisation analysis (see methods).

Source of variance df MS F value P Randomised P (A) Honeybee Pair 1 235.225 177.53 < 0.001 0.056 Rarity 1 3.025 2.28 0.21 0.222 Pair*Rarity 1 1.225 0.92 0.39 0.495 Site 4 1.325 0.39 Error 32 3.375 (B) Native bee Pair 1 0.225 1.80 0.25 0.667 Rarity 1 2.025 16.20 0.01 0.056 Pair*Rarity 1 0.225 1.80 0.25 0.257 Site 4 0.500 0.24 Error 32 16.800

133

7.0 Common Rare 6.0

5.0

4.0

3.0

2.0

1.0

0.0 Number of visits/plant/10Number min Native bee Honeybee Total visits Insect visitors

Figure 4.3: The mean (± SE) number of native bee, honeybee and total insect visits per plant (per 10 minute observation) in common and rare Persoonia species. 134

4.4. Discussion This comparative study links reproductive success, breeding system and pollination ecology to plant rarity in two pairs of closely related common and rare species with replicate populations. It found that both common and rare Persoonia species are obligate-outcrossers and are dependent on insect-pollinators for sexual reproduction.

Pollination was limited in the rare species, which was associated with fewer native bee visits, resulting in reduced reproductive success. Here I compare the associations between rarity and reproductive success, breeding system, and pollination found in this study with other findings in the published literature. Then I discuss the implications for the management of these historically rare species and consider the effects of recent habitat fragmentation and altered suites of pollinators.

4.4.1. Rarity and reproductive success

Greater seed production may enable plants to regenerate in greater abundance after disturbances (e.g. fire) and establish new populations more readily through dispersal.

There is growing evidence that common species are more fecund than rare species, with the majority of studies reviewed by Murray et al. (2002) supporting this trend (9 from

13 cited). In fact the studies that found no difference in fruit production involved only one common-rare comparison, and despite non-significant results, (except for

Witkowski and Lamont, 1997 where no difference was found) the rare species tended to produce fewer fruits (Fiedler, 1987; Pavlik et al., 1993; Young and Brown, 1998). In both pairs I found rare species to have a lower reproductive success than their common congeners across replicate populations (see Figure 4.1). If this is a general trend, the variation in reproductive success may partially explain the marked differences in geographic distribution and local abundance observed between common and rare species. 135

4.4.2. Rarity and breeding system

Selfing has been suggested as an evolutionary consequence of rarity, providing reproductive assurance when compatible mates and/or pollinators become limited

(Baker, 1955; Carpenter and Recher, 1979; but see Herlihy and Eckert, 2002). However, highly developed self-incompatibility mechanisms have been found across numerous plant families and habitats in both common and rare species (Kunin and Shmida, 1997;

Murray et al., 2002a). My results (see Figure 4.2) are consistent with the majority of published studies, in which the breeding systems of common and rare congeners are similar (Fitz-Sheridan, 1988; Sydes and Calder, 1993; Premoli, 1996; Bosch et al.,

1998; Affre and Thompson, 1999). In those studies that have found inter-specific differences in breeding system, there is no consistent association between the level of self-compatibility and rarity, with both the common and rare species displaying selfing or outcrossing (Karron, 1989; Purdy et al., 1994; Hermanutz et al., 1998; Mateu and

Figueres, 1998; Ng and Corlett, 2000). I conclude, therefore that plant breeding systems are not directly related to rarity, and other factors, including population characteristics, may be more important in determining the level of self-compatibility.

4.4.3. Rarity and pollination

Pollination is required for seed production in species not capable of autogamy, even when self-pollination is possible. The effectiveness of different floral visitors as pollinators is dependent on their behaviour and movement (Wallace et al., 2002).

Despite this, few studies have compared the association between pollination and plant rarity. Where this has been done for insect pollinated plants, rare species tend to receive fewer visits than their common relatives (Banks, 1980; Karron, 1987; Fitz-Sheridan,

1988; Sydes and Calder, 1993; this study). The Persoonia species in my study are all obligate outcrossers and native bees (Leioproctus species) were observed moving 136 between plants, carrying pollen and contacting anthers and stigmas, therefore promoting outcrossing. Leioproctus species forage primarily on Persoonia flowers (Bernhardt and

Weston, 1996), suggesting that it may be a specialist-pollinator (Wallace et al., 2002).

The frequency of visits to the rare species was significantly lower than to the common species (see Figure 4.3). If this is a general pattern limited pollination may be a cause or consequence of rarity, however the exact mechanisms require further investigation.

4.4.4. Future effects of fragmentation

Recent habitat destruction has fragmented the landscape and led to populations becoming progressively more isolated and reduced in size, greatly increasing the probability of extinction (Barrett and Kohn, 1991; Ellstrand and Elam, 1993; Young and

Brown, 1996). Small isolated populations are expected to have altered pollinator behaviour and movement, as well as decreased pollinator visitation rates (Aizen and

Feinsinger, 1994; Mustajarvi et al., 2001). As all the study species were obligate outcrossers with a single effective pollinator, the impacts of habitat fragmentation are likely to be severe, despite the fact that these species were probably historically restricted in range (Chapter 2).

Populations of the four study species are affected by fragmentation to varying degrees, through natural and anthropogenic disturbances. Even though these obligate seeders possess adaptations, including a persistent soil-stored seed-bank and animal dispersed fleshy fruits (Auld et al., 2000, personal observation) that enable them to persist in these unpredictable (fire-prone) environments, continual frequent fires have the potential to reduce population sizes and ultimately force them to extinction (Bradstock et al., 1996).

The encroachment of urban areas on natural bushland has led to subdivision of the available habitat and increased fire frequencies (through hazard reduction burning and arson). Populations of both common and rare P. mollis subspecies have patchy 137 distributions within relatively continuous habitats, and are generally restricted to drainage lines and creeks (fire shadows; personal field observation). Persoonia lanceolata and P. glaucescens populations are found in fragmented landscapes, subdividing populations by areas of urban and/or agricultural development. Population sizes differ between the species, with the common species locally abundant (c. >500 plants) and the rare species generally consisting of fewer than 100 plants at a site. In addition to limiting the number of potential mates available this is likely to alter pollinator visitation, depending on the nature of the matrix within the landscape.

4.4.5 Pollinator disruption

The introduction of the European honeybee may have disrupted the existing plant- pollinator interaction (Goulson, 2003). In Australia, honeybees have been recorded visiting a wide range of native flowering plants (Paton, 1993, 1997). In many of these species, their role as effective pollinators is questionable. In my study, honeybees were observed collecting and contacting stigmas of Persoonia flowers, and they are therefore potential pollinators. However, honeybees frequently groom pollen from their body, storing it in the corbiculae making it inaccessible for transfer onto the stigmatic surface

(Bernhardt and Weston, 1996; Paton, 1997; Wallace et al., 2002). Combined with the high proportion of movements within plants (Gross, 2001; Dupont et al., 2004) and restricted movements between plants (Michaelson-Yeates et al., 1997), encouraging selfing and bi-parental inbreeding, respectively, the honeybee may be inefficient as a pollinator to these obligately outcrossing species. The results of other studies are mixed as to whether honeybees are effective as pollinators (Butz Huryn, 1997). It is clear, however, that the honeybee is now the dominant floral visitor to many native plants, which co-evolved with a range of vertebrates and solitary insect species (Paton, 2000;

Spira, 2001). This shift in the composition of floral visitors has been shown to have the 138 potential for a direct effect on reproductive success (Spira, 2001), to alter the genetic structure of populations (England et al., 2001) and to encourage (bi-parental) inbreeding depression (Spira, 2001). While honeybees appear to visit Persoonia species equally, their impact may be much greater in rare species (as they contribute to a greater proportion of the total floral visits) and may merit a greater focus in future studies.

4.4.6 Conclusion

Both the common and rare Persoonia species are obligate outcrossers and the most effective pollination is likely to be provided by a native, specialist pollinator. The rare species of Persoonia that I investigated are less fecund than their common relatives, and are visited less frequently by native bees. Despite these consistent differences between common and rare species, it is premature to conclude that differences in pollinator activities are the cause of rarity. Modified fire regimes and habitat fragmentation are important processes that have altered the distribution and abundance of plants, and pollinator activity may be responding to these changes. Further, the introduced honeybee is likely to be disrupting the existing plant-pollinator interactions in the genus

Persoonia, and this relationship warrants further investigation. Whatever the ultimate cause of rarity, the reduced fecundity of the rare obligate-seeders may increase the likelihood of localized extinction in fire-prone environments. 139

Chapter 5 : Is rarity in fire-sensitive shrubs associated with seed dispersal and predation?*

5.1. Introduction Processes operating on seeds (e.g. dispersal and predation) play important roles in population dynamics, particularly in landscapes dominated by disturbances (such as fire). In addition, seed dispersal is a central process in re-colonization after disturbance events. Frequent fires may result in reduced population sizes and plant densities, increased population fragmentation, and even localized extinctions in fire-sensitive plants (Bradstock et al., 1996; Keith and Tozer, 1997). The persistence of populations in fire prone habitats may be influenced by seed predation, which limits the availability of seeds for post-fire recruitment (Auld and Denham, 2001). The importance of seed dispersal and predation in affecting population dynamics and shaping the distribution and abundance of plants is well established (Loveless and Hamrick, 1984; Cain et al.,

1998; Rey and Alcántara, 2000; Kameyama et al., 2001). However, few empirical studies have explored their potential role in plant rarity (Pirie et al., 2000; Scott and

Gross, 2004).

The causes and consequences of rarity (based on geographic range size, local abundance and degree of habitat specificity, Rabinowitz, 1981) are almost certainly complex, and studies on rare taxa should be conducted at multiple spatial scales (Hartley and Kunin,

2003). This is particularly important when exploring the extinction risk associated with plant rarity (IUCN, 2001), given that the importance of factors influencing colonization ability and population persistence may vary from local to regional scales (Froborg and

Eriksson, 1997). In interpreting impacts, it is essential to take account of both individual

* This chapter has been accepted for publication in the International Journal of Plant Sciences. 140 plant and site attributes to account for differences in animal foraging behaviour

(Alcántara et al., 2000). Many plant and microhabitat attributes may also affect animal foraging activity, including plant size (Alcántara et al., 2000), fruit quantity (Mittelbach and Gross, 1984; Cummings and Alexander, 2002), plant density (Notman et al., 1996), and vegetation cover (Manson and Stiles, 1998). At a larger scale, population size is likely to affect animal foraging behaviour, leading to variation in the levels of seed dispersal and predation found within and among populations (Garcia et al., 2001). The relative importance of such attributes for plant rarity must be addressed through comparative studies.

Comparisons of closely related congeners with widespread and restricted geographic distributions have been used to understand the potential causes of rarity (Kruckeburg and Rabinowitz, 1985), minimizing the confounding effects of disparate phylogenetic histories (Silvertown and Dodd, 1996). This study employs such a comparative approach to test whether seed removal and seed predation differ between common and rare perennial shrubs in the genus Persoonia (Proteaceae). I used seed removal as a relative measure of dispersal, assuming that the majority of seeds that were removed were not destroyed and were deposited in favourable sites. To estimate seed predation, I used the number of seeds eaten (i.e. destroyed) in situ, which may underestimate seed predation levels. I selected two common-rare pairs of closely related Persoonia species taxa (Chapter 1), which share similar habitats, plant structure and gross fruit morphology (Weston, 1995; Krauss, 1998). Plants in the genus produce fleshy fruits capable of being dispersed over relatively long-distances (a few kilometres) by large mammals and birds (Rose, 1973; Buchanan, 1980; Lane, 1999; McGrath and Bass,

1999). Given this, I proposed that a plausible explanation for differences in rarity 141 among the obligate seeder species, which rely on seed to re-establish after fire, is that they differ in the level of seed dispersal and predation.

The primary objective of this study was to explore the relationship between rarity and seed dispersal and predation, and thereby test my prediction that rare species have lower seed dispersed and/or greater seed predation than common species. Seeds removed and eaten were used as indicators of the processes of seed dispersal and seed predation, respectively. I aimed: (1) to determine the proportion of seeds removed and eaten in two common and two rare Persoonia species, and (2) to explore the association of seed dispersal and predation with plant size, fruit quantity, plant density and vegetation cover. Population size is typically a confounding factor when comparing common and rare species; the latter often have smaller population sizes, therefore I also used one common species (Persoonia lanceolata, found in small and large populations) to investigate the potential effect of population size on seed dispersal and predation. 142

5.2. Methods 5.2.1. Study species

All the Persoonia species investigated in this study drop their fleshy fruits to the ground after they have matured. Both species in pair 1 (P. mollis ssp. nectens and P. mollis ssp. maxima) drop fruits that are firm, round and bright green in colour. In Pair 2, the fruits of P. lanceolata are firm, elliptical, and bright green and partially red in colour when they drop, while P. glaucescens fruits are more narrow and pointed, and deep red in colour. The fruits of all species ripen while on the ground, becoming initially softer and darker red in colour. After two to three weeks, the flesh starts to dry and the skin turns black, and all fruits are dry and black after four weeks.

I conducted a preliminary study in November 2000 to determine the timing of seed removal and predation and the potential agents responsible in sites of several Persoonia species (including all the study species except P. mollis ssp maxima). Seed removal and predation are not mutually exclusive processes and both occur predominantly between dusk and dawn. I found seed removal to be confined to the four weeks following fruit drop prior to the flesh becoming dry and black. The majority of seed predation also occurred within these four weeks, but I observed seeds to be eaten over a longer period of time (up to 11 months or until the seeds are covered by litter/soil). Macropod marsupials (Wallabia bicolor and Macropus rufogriseus) were the main agents of seed removal, while rodents (Rattus fuscipes and Rattus rattus) were the main seed predators

(identified through fruit/seed remains, scats and tracks). Both are common in the

Sydney region (NSW National Parks and Wildlife Service ATLAS database). Seed removal by large birds (currawongs) and seed predation by mammals (possums and wombats) cannot be excluded, but these agents left little evidence behind. Macropod scats collected within the study sites contained intact and viable Persoonia seeds 143

(ranging from 0 to 8 seeds/scat during peak fruiting), confirming that they are potential seed dispersal agents rather than seed predators. The scats of rodents contain fragments of woody endocarp of Persoonia species, indicating that they are seed predators (sensu

Auld and Denham, 1999, 2001).

5.2.2. Comparison of common and rare species

For each of the two common and two rare species, I selected two study sites in which seed removal and predation were estimated. Sites were chosen that contained relatively large populations (>100 plants) within the core of the distribution of each species. As no locations were found where the study species co-occurred in large enough numbers to conduct this work, separate study sites were used for each species (Table 5.1). Within each site, 20 fruiting plants were selected. Criteria for selection were that the canopy did not intersect with adjacent plants and that all mature fruits could be removed from the canopy, in order to control fruit numbers beneath the plant. Under each plant five fruit caches of 10 mature fruits (confined within a 0.1 m diameter PVC ring partially pushed into the ground with 1 cm protruding from the ground) were established in November

2001, representing similar fruit densities and patchy distributions to those naturally found under relatively large reproductive plants (ranging from 10 ± 6 seeds/0.31 m2 for the common species to 6 ± 5 seeds/0.31 m2 during peak fruiting).

I revisited individual caches of fruits every week for four weeks. I searched the area within the ring and its immediate surrounds (~20 cm radius) for intact seeds, evidence of fruit/seed remains, and animal scats, tracks and diggings. Seed remaining intact were recorded as “remaining”, seeds that were cracked or chewed open with the embryo missing were recorded as being “eaten”. Seeds that could not be relocated after 4 weeks were recorded as being “removed”. Seed removal was estimated as the number of seeds missing, expressed as a proportion of the number of seeds initially placed in each cache. 144

Seed predation was estimated as the number of seeds eaten, expressed as a proportion of the number of seeds remaining after removal. There by making seed removal and predation independent and uncorrelated (R = 0.09).

I used a multi-factor mixed-model ANOVA (performed in SAS version 8.2), to test the hypothesis that seed removal and predation differed between common and rare species.

The ANOVA was constructed with Rarity (common and rare) and Pair (species pairs 1 and 2) as fixed factors. The two sites were used as replicates for each Pair by Rarity combination (2 sites/combination × 4 combinations = 8 sites). Site and Plant were nested factors, Site being nested within Pair by Rarity combination, and Plant being nested within Site (within (Pair, Rarity)). As the raw data were expressed as proportions

I transformed them using an angular transformation to conform to the distributional assumptions of the analysis (Zar, 1999). Tukeys post hoc HSD test was used to determine which combinations were significantly different in seed removal and predation. The alpha level was corrected for multiple comparisons using a Bonferroni correction (Underwood, 1997). 145

Table 5.1: The location, estimated population area and size of the study sites selected for common and rare Persoonia species. Including the mean plant and microhabitat attributes (n = 40 plants) at each site. ‘-‘ indicates missing values. * sites statistically different from each other do not share the same letter (Tukeys test ∝ = 0.05).

Species (rarity) Mean (SE) * Study site Longitude, Population Population Plant Fruit Distance Vegetation Latitude a area b size c size d quantity e to plant f cover g P. mollis ssp. nectens (common) 1. Hilltop 150°28'41"S, 40 300 2.3 (0.1) 59.9 (18.1) 7.0 (1.1) 34.2 (4.0) 34°19'48"E b ab bc abc 2. Little River 150°30'54" S, 100 600 2.5 (0.1) 107.9 (28.7) 3.9 (0.4) 30.9 (4.1) 34°16'05" E b ab ac abc P. mollis ssp. maxima (rare) 1. Ku-ring-gai 151°8'02" S, 100 200 3.3 (0.2) 156.1 (38.6) 7.2 (1.5) 14.5 (1.7) 33°40'34" E c b b ad 2. Galston 151°04'12" S, 30 100 2.5 (0.3) - 5.1 (0.3) - Creek 33°39'21" E c ac P. lanceolata (common) 1. Moore Track 151°03'34" S, 500 >1000 1.2 (0.0) 50.0 (5.7) 1.5 (0.2) 25.9 (4.7) 34°06'47" E a a a ac 2. Bundeena 151°05'60" S, 350 >1000 1.3 (0.0) 57.2 (5.9) 1.1 (0.2) 42.4 (4.4) 34°06'11" E a ab a bc 3. Bola Heights 151°01'41" S, 40 100 1.5 (0.0) 11.0 (2.8) 6.1 (1.4) 51.6 (5.9) 34°10'00" E a a ac bc 4. Ulloola Track 151°01'30" S, 35 50 1.5 (0.1) 28.3 (2.9) 5.3 (0.9) 39.1 (4.0) 34°07'28" E a a ac bc P. glaucescens (rare) 1. Braemar 150°28'26"S, 80 400 2.4 (0.1) 157.5 (34.0) 2.6 (0.3) 20.3 (2.7) 34°25'05" E b b a ac 2. Buxton 150°30'54" S, 35 100 2.0 (0.3) - 3.1 (0.4) - 34°15'07" E b a

a Based on GPS position using datum WGS1984 b Estimated area (hectares) based on vegetation maps and field observations c Estimated number of flowering individuals per population d Plant height (meter) e Number of fruits under the plant canopy f Distance to nearest flowering plants (m) g Percentage ground cover under the plant canopy 146

5.2.3. Plant size, fruit quantity, plant density and vegetation cover

For the plants monitored for seed removal and predation in 2001, I recorded several plant and microhabitat attributes, except for plants at two sites (Galston Creek and

Buxton; see Table 5.1) where only plant size was measured due to time constraints. I made the following measurements: plant size (height, width at widest point, perpendicular width, and basal diameter at ground level), fruit quantity (the number of fruits under the plant canopy), local plant density (distance to nearest Persoonia plant, and number of Persoonia plants <5m away), and vegetation cover (% ground cover under plant canopy recorded as 12, 25, 37, 50, 62, 75, 87 and 100%).

I used a step-wise multiple regression to test whether seed removal and predation were related to any of these variables (plant size, fruit quantity, plant density and vegetation cover). For variables that were highly correlated with each other, one was selected based on biological interpretation (i.e. for plant size, volume was included and basal

2 diameter was omitted to simplify the analysis; radj = 0.643). Variables that produced a relationship significant at α = 0.05 were used in a regression model, and the linear relationship is reported. These variables were then used as covariates in further analyses. I performed separate regressions for common and rare species using the variables that were significant in the model that used all four rarity by pair combinations.

I used an analysis of covariance (ANCOVA) to test whether the covariates accounted for any potential differences in the main factors (Rarity and Pair). An ANCOVA was performed with the covariate preceding the main factors in the model statement

(Covariate, Pair, Rarity, Pair*Rarity, Site). The number of seeds removed under a plant was significantly correlated with the number of seeds eaten (n = 154, r = 0.35, P =

0.001). Consequently, the proportion of seeds eaten was included as a covariate in the 147

ANCOVA on seed removal (and vice versa). The fact that there are unequal numbers of plants at the various sites complicates the analyses. In the F-ratios, the denominator is a linear combination of several mean squares and its degrees of freedom is not an integer.

5.2.4. Effect of population size

To explore the potential effect of population size, which typically differs between the common and rare species (Table 5.1), I tested whether levels of seed removal and predation varied between large and small populations in the common P. lanceolata (the latter being of equivalent size to populations of the rare P. glaucescens). Using the experimental set up described above, with 5 caches of 10 fruits established under 20 plants, I established two additional sites comprising small populations of plants (Bola

Heights and Ulloola Track; equivalent in size to populations of the rare species) to compare with the large populations at Moore Track and Bundeena. I determined the size of populations based on the size of the vegetation unit (Sandstone Heath) with which P. lanceolata is associated (David Keith, unpublished) and field observations. All four P. lanceolata sites are located within Royal National Park and separated by areas of relatively undisturbed natural bushland.

I used an ANOVA to test for differences in seed removal and predation between small and large populations of P. lanceolata. Population size was fixed, and Site was a nested random blocking factor. Plant (nested within Site) was a random factor. As the raw data were expressed as proportions I transformed them using an angular transformation to conform to the distributional assumptions of the analysis (Zar, 1999). 148

5.3. Results 5.3.1. Comparison of Common and Rare species

More than 45% of the seeds were removed from all sites for the common species, while sites for the rare species had less than 25% seed removal. The two common species had significantly more seeds removed from under plants after four weeks than their rare congeners (Rarity F1,4 = 21.19, P = 0.010; Table 5.2). This pattern was consistent for both species pairs. Seed removal also varied significantly between sites of both common and rare species (Figure 5.1a). 149

Table 5.2: Mixed model ANOVA for a comparison of the proportion of seeds removed and eaten from experimental caches under adult plants after 4 weeks in closely related (Pair) common and rare species (Rarity) across populations (Site). Seed removal data = ARCSIN(√{seeds removed/total seeds}). Seed predation data = ARCSIN(√{seeds eaten/(total seeds - seeds removed}). Site was a nested random factor. To calculate the F values the Mean Square (MS) for Pair, Rarity and Pair*Rarity was divided by MS(Site), while Site was divided by MS(Error).

Seed removal Seed predation Source df MS F P a MS F P a Pair 1 1792 1.85 0.245 7152.5 13.50 0.021 Rarity 1 20457 21.19 0.010 2667 5.04 0.088 Pair*Rarity 1 2132 2.21 0.211 12154 22.96 0.009 Site (Pair, Rarity) 4 961 6.00 0.001 527.7 4.93 0.001 Error 146 160 107.0

a Statistically significant P-values are in bold 150

1.0

0.8

0.6

0.4

0.2 Mean proportion of total seeds totalremoved seeds 0.0 Site 1 Site 2 Site 3 Site 4 Site 5 Site 6 Site 7 Site 8

Species pair 1 Species pair 2 (a)

1.0

0.8

0.6

0.4

0.2 total seeds eatentotal seeds Mean proportion of 0.0 Site 1 Site 2 Site 3 Site 4 Site 5 Site 6 Site 7 Site 8

Species pair 1 Species pair 2 (b)

Figure 5.1: The proportion of seeds removed (a) and eaten (b) in caches under adult plants after 4 weeks, across replicate sites from two pairs of common and rare Persoonia species. P. mollis ssp. nectens = Sites 1 and 2, P. mollis ssp. maxima = Sites 3 and 4, P. lanceolata = Sites 5 and 6, and P. glaucescens = Sites 7 and 8. Filled bars represent the common species and clear bars represent the rare species. Error bars are one standard error. 151

The levels of seed predation were dependent on both the level of rarity and the species pair (Pair*Rarity F1,4 = 22.96, P = 0.009; Table 5.2). Overall, the percentage of seeds eaten after four weeks was similar for common and rare species (mean ± SE; 38 ± 8 % and 38 ± 16 %, respectively), but this varied greatly within each pair and within each rarity category (Figure 5.1b). A post hoc comparison (at an overall level of significance of 0.001) of seed predation found that P. mollis ssp. maxima (50 to 51%) had more seeds eaten than P. mollis ssp. nectens (10 to 17%) and P. glaucescens (5 to 10%). P. glaucescens had similar levels of seed predation to P. mollis ssp. nectens (10 to 17%), but less than P. lanceolata (12 to 24%).

5.3.2. Plant size, fruit quantity, plant density and vegetation cover

The multiple regression analysis revealed that only plant size was correlated with seed removal, and none of the other attributes measured were significantly associated with either seed removal or predation. The proportion of seeds removed decreased with plant height (Figure 5.2), but the linear relationship only explained a small proportion of the

2 total variation across all species (radj = 0.189, F1,152 = 36.67, P < 0.001). Slightly more

2 variation is explained in the common species (radj = 0.229, F1,75 = 23.57, P < 0.001),

2 but there was no relationship in the rare species (radj = 0.004, F1,75 = 1.29, P = 0.259)

(Figure 5.2). The common species were on average shorter and had greater seed removal than their rare relatives (Table 5.3). 152

90 80 70 60 50 40 30 20

Angular seed removal Angular 10 0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Log10 height (metres)

Figure 5.2: The relationship between seed removal and plant height in common (filled diamonds) and rare (open squares) Persoonia species. Angular seed removal = Arcsin (√proportion of seeds removed). Height has been log10 transformed. The solid line represents the line of best fit for the 2 common species (y = -39.181 x + 58.181; radj = 0.229). There was no relationaship in the rare species. n = 20 plants x 4 sites. 153

Table 5.3: The mean (SE) seed removal, and plant height of the two pairs of closely related common and rare Persoonia species.

Taxa Pair a Rarity n b Seed removal c Plant height d P. lanceolata 1 Common 37 0.45 (0.03) 2.42 (0.04) P. glaucescens 1 Rare 39 0.24 (0.03) 3.17 (0.01) P. mollis ssp. nectens 2 Common 40 0.67 (0.03) 1.25 (0.03) P. mollis ssp. maxima 2 Rare 38 0.22 (0.03) 2.23 (0.03)

a Closely related species pairs b 17-20 plants from two sites c Proportion of seeds removed d Plant height in meters 154

Plant height has some value in predicting seed removal within a site and species (plant height was squared to account for non-linearity) (ANCOVA F1,4.8 = 6.45, P = 0.053).

However, even when plant height was accounted for in the ANCOVA, plant rarity remained a significant factor (ANCOVA F1,4.5 = 24.29, P = 0.006). The proportion of seeds eaten was a significant covariate (ANCOVA F1,5.3 = 17.73, P = 0.007) and plant rarity remained significant (ANCOVA F1,4.0 = 32.65, P = 0.005), but its inclusion in the analysis of seed removal made the Pair*Rarity interaction term significant (ANCOVA

F1,5.1 = 18.70, P = 0.007). When both plant height and seeds eaten were included as covariates in the analysis of seed removal, plant rarity was still a highly significant factor (ANCOVA F1,4.7 = 36.48, P = 0.002), but the result was dependent on the species pair (Pair*Rarity interaction ANCOVA F1,5.0 = 15.90, P = 0.011). A post hoc comparison (at an overall level of significance of 0.001) of seed removal among species confirmed that the common species had significantly more seeds removed than the rare species (P. mollis ssp. nectens > P. mollis ssp. maxima, and P. lanceolata > P. glaucescens). The rare species had similar levels of seed removal (15 to 28%), however the two common species were significantly different with more seeds removed in P. lanceolata (54 to 80%) than P. mollis ssp. nectens (44 to 47%).

Seed predation was not associated with any of the variables measured (plant size, fruit quantity, plant density and vegetation cover) in the multiple regression analysis, but after pair and rarity were factored into the analysis plant height covaried significantly

(ANCOVA F1,5.0 = 13.03, P = 0.016). While the proportion of seeds removed was a significant covariate in the ANCOVA on seed predation (ANCOVA F1,6.4 = 27.77, P =

0.002), it did not alter the results of the original analysis. Plant rarity remained insignificant when plant height and seed removal were included as covariates in the analysis of seed predation (ANCOVA F1,6.7 = 1.21, P = 0.309). 155

5.3.3. Effect of population size

The proportions of seeds removed under P. lanceolata plants were similar in large (54 ±

8%, 80 ± 7%) and small populations (66 ± 9, 76 ± 8%) (F1,4 = 21.29, P = 0.804; Table

5.4), although there was a significant nested site effect. Similar levels of seed predation were found in large (24 ± 8%, 12 ± 8%) and small (26 ± 9%, 16 ± 8%) populations (F1,4

= 8.23, P = 0.103; Table 5.4). Seed removal showed some variation between sites of both large and small populations (Figure 5.3). 156

Table 5.4: Mixed model ANOVA for a comparison between large and small populations (Size) of the proportion of seeds removed and eaten from experimental caches under adult plants after 4 weeks, with replicate sites for P. lanceolata. Seed removal data = ARCSIN(√{seeds removed/total seeds}). Seed predation data = ARCSIN(√{seeds eaten/(total seeds - seeds removed}). The site factor was set as a random effect. To calculate the F values the Mean Square (MS) for Size was divided by MS(Site), while Site was divided by MS(Error).

Seed removal Seed predation Source df SS MS F P a MS F P a Size 1 0.0316 0.0316 0.08 0.8041 0.6734 8.23 0.1031 Site (Size) 2 0.7916 0.3958 21.29 0.0001 0.0819 1.18 0.3132 Error 76 1.4129 0.0186 0.6945

a Statistically significant P-values are in bold

157

1.0

0.8

0.6

0.4

seeds removed 0.2 Mean proportion of 0.0 Site 1Site 2Site 3Site 4 (a) Large population Small population

1.0

0.8

0.6

0.4 seeds eaten 0.2 Mean proportion of 0.0 Site 1Site 2Site 3Site 4 (b) Large population Small population

Figure 5.3: The proportion of seeds removed (a) and eaten (b) in caches under adult plants after 4 weeks, across replicate sites from large and small populations of P. lanceolata. Filled bars show the large populations and clear bars show the small populations. 158

5.4. Discussion This comparative study explored the association between seed dispersal and predation in plant rarity using two pairs of closely related common and rare species. This allowed me to test my prediction that rare species have lower levels of seed dispersal and/or greater seed predation than common species, potentially being one key aspect contributing to different levels of rarity (Gaston and Kunin, 1997a). I found that common species had more than twice as many seeds removed (and therefore potentially dispersed) than their rare relatives, in both species pairs (Figure 5.1), supporting my prediction. Plant height and population size differ between common and rare species potentially confounding this comparison, nevertheless rarity still had a significant effect on seed removal even when these attributes were accounted for in the analysis.

Furthermore, the common Persoonia species studied here have been found to have greater reproductive success than their rare congeners (Chapter 4), indicating that the absolute number of fruits being dispersed will be much greater for the common species.

Seed predation, on other hand, was not related to rarity or to any of the plant and microhabitat attributes measured, and appeared to be unaffected by population size.

There was however significantly more seed predation in the rare P. mollis ssp. maxima than its common relative (P. mollis ssp. nectens) (Figure 5.1), but the other species pair did not fit with my prediction. These findings have implications for the processes of colonization and extinction and may provide valuable insights into the population dynamics of obligate seeders.

5.4.1. The spatial scale of foraging animals

Animal foraging behaviour may vary at different spatial scales (Kollmann, 2000), depending on a range of plant and site characteristics. I found that seed removal by large mammals (macropods) and seed predation by small mammals (rodents) varied 159 significantly between sites. The plant-scale attributes measured here may not explain the variation between sites. Although plant size was associated with seed removal, it explained a relatively small proportion of the total variation. Plant size is often thought of as a surrogate for fecundity, which has been found to have a strong relationship with seed removal and predation (Casper, 1988; Herrera et al., 1994; Delgado Garcia, 2002) with an obvious link to animal foraging behaviour. In this study, individual plant fecundity and local plant density were not related to seed dispersal and predation, but mammals may be responding to these factors at a larger spatial scale (i.e. site or populations). The weak relationship of increasing plant size associated with decreasing seed removal in common species (Figure 5.2) may reflect satiation of seed removal agents in larger plants, if such larger plants have larger fruit crops. I found no effect of population size on seed removal or predation in the common P. lanceolata within a relatively continuous natural landscape. While the small populations selected were of equivalent size to the rare relative (P. glaucescens) of this common species, differences in habitat connectivity and the quality of the surrounding matrix may have consequences for seed dispersal and predation (Guariguata et al., 2000; Hewitt and

Kellman, 2002). Future research needs to link mammal foraging behaviour to landscape and local scale attributes to gain a better understanding of the underlying mechanisms influencing variation in seed dispersal and predation.

5.4.2. Common-rare differences

Seed dispersal and predation are important factors influencing colonization and extinction events, thus potentially determining the distribution and abundance of species. Relatively few studies have explored the role of seed dispersal and predation in plant rarity. A small number of well replicated comparative studies using groups of unrelated species have failed to find any relationship between dispersal mode and 160 geographic range (Kelly and Woodward, 1996; Hegde and Ellstrand, 1999; Murray et al., 2002b), suggesting that dispersal mode alone can not explain rarity. Studies looking at closely related species with similar dispersal modes have had mixed results. Pirie et al. (2000), for example, found that seed removal and predation by rodents did not differ between a congeneric widespread and endemic species pair (after accounting for differences in seed availability), whereas Scott and Gross (2004) found lower seed predation by ants (when mammals were excluded) in a common species than in its rare congener. While these studies may minimize potentially confounding differences by using related species (Silvertown and Dodd, 1996), they lack spatial replication and only investigate a single species pair. A review of the literature was unsuccessful in finding other comparative studies exploring this relationship, and my study may be the first to use replicated common-rare comparisons (two pairs of closely related species), with some spatial replication (two populations) for each species. Clearly more research with adequate replication is required to test the generality of the potential relationship found here between plant rarity and seed dispersal for fleshy-fruited plants.

5.4.3. Effect of dispersal on rarity

Where populations are prone to extinction through disturbance (e.g. frequent fire) species with a high capacity to re-colonize areas would be expected to cover a greater proportion of the landscape (e.g. Froborg and Eriksson, 1997). Fire is a major disturbance in many habitats throughout the world (Whelan, 1995), and is particularly regular in the fire prone sclerophyllous vegetation on the east coast of Australia. In this landscape, populations of fire sensitive plants are vulnerable to extinction (Bradstock et al., 1996; Keith and Tozer, 1997), and may contract into fire refuges (i.e. areas with more optimal fire frequencies) during periods of persistently frequent fires. These fire refuges may provide a source of seed to re-colonise areas during more optimal 161 conditions, but refuge areas may move around the landscape over time (Keith and

Tozer, 1997). So, the persistence of populations in fire prone landscapes may be dependent on the species colonisation ability. Assuming that fruit removal is positively correlated with dispersal and subsequent colonization ability (Valverde and Silvertown,

1997), I hypothesis that the higher levels of fruit removal I found in common Persoonia species, compared to rare Persoonia species (Figure 5.1), could explain the different geographic distributions and local abundances observed in these fire sensitive species within this fire prone landscape. To test this hypothesis it would be necessary to determine if increasing fruit removal increases the probability of reaching and colonizing a suitable site.

5.4.4. Effect of predation on rarity

Seed predation limits the availability of seeds for post-fire recruitment (Auld and

Denham, 2001), and therefore influences the persistence of populations in fire prone landscapes (Regan et al., 2003). I found seed predation to vary between species, with no consistent pattern between common and rare species. The high level of seed predation I found in the rare P. mollis ssp. maxima may limit the number of seeds contributing to the soil-stored seed-bank (<50% seeds). The other three species had a similar predicted contribution to the seed-bank (75 to 95% combining seeds removed, and those remaining under plants), but different proportions of seeds found under (local) plant canopies and dispersed (away) from parents. In fact, the number of seeds available to contribute to the local seed-bank was greater for the rare P. glaucescens than the other three species (where P. mollis ssp. nectens > (P. mollis ssp. maxima ≈ P. lanceolata)).

Soil seed-bank dynamics are poorly understood (Edwards and Whelan, 1995; Regan et al., 2003), however it is likely that species will have different levels of seed dormancy, decay and germination (Auld et al., 2000). This polymorphism adds another layer of 162 complexity on top of the enormous spatial and temporal variation within and among fires (Bradstock and Auld, 1995; Morrison, 2002). Future research priorities should be directed towards exploring seed bank dynamics and their interaction with wildfires, without which it is difficult to assess the persistence of obligate seeders in fire prone landscapes.

5.4.5. Conclusion

These results indicate that seed dispersal is more limited in rare fire-sensitive Persoonia species but, without an understanding of the fate of seeds, it is difficult to quantify differences in the colonization ability between common and rare species. Documenting long-distance dispersal events is not easy through traditional ecological methods

(tracking the movements of dispersal agents and collecting dispersed seeds in the landscape), but it may be possible through the use of molecular markers (as recently applied by, He et al., 2004). For obligate seeders, there is a direct link between seed predation and the availability of seeds for post-fire recruitment, but the complexity of persistent soil stored seed-banks (where residual seeds remain viable through consecutive fires) creates uncertainty in predictions for the persistence of populations.

This is further complicated by the high degree of spatial and temporal variability in wildfires. Incorporating seed dispersal and predation into a metapopulation framework

(through ecological modelling) may provide further insights into the relative importance of colonization and extinction events for plant rarity. 163

Chapter 6 : General Discussion

Life-history characteristics that determine the ability of plants to persist and disperse, play an important role in population dynamics, and therefore species distributional patterns (Eriksson, 1996; Lopez and Pfister, 2001). Anthropogenic habitat fragmentation throughout the world has led to the division of populations into spatially separated units (Young and Clarke, 2000), increasing the likelihood of extinction through demographic and genetic processes (Barrett and Kohn, 1991; Ellstrand and

Elam, 1993; Lande, 1999). Models of island biogeography have been used to characterize fragmented populations, but the matrix between patches in terrestrial landscapes may not be as hostile for plants as previously thought (Watson, 2002). A metapopulation framework may be more appropriate for short-lived organisms with good dispersal, where landscapes consist of local populations and non-occupied but potentially suitable sites in a continuous flux of local colonization and extinction

(Eriksson, 1996). Plants that can survive unfavourable environmental conditions, through resprouting bodies and/or extensive seed banks, tend to build up remnant populations systems (Eriksson, 1996). The extent to which either of these models explain the dynamics of natural populations also depends on the level of disturbance.

Disturbance is a critical factor responsible for shaping the distribution and abundance of populations in the landscape (Riba et al., 2002). In landscapes dominated by frequent and intense disturbance regimes (e.g. fire-prone habitats) plants must be resilient if they are to persist, and/or they must be highly mobile to recolonise unoccupied habitat.

Fire and drought are major natural disturbances that directly affect the ability of plants to persist in the landscape, and are especially prominent in the Australian continent 164

(New, 2000). The frequency and intensity of these disturbances has been highly altered by human activity. While some areas are more prone than others to these disturbances, their temporal and spatial pattern across the landscape is often highly unpredictable

(Whelan, 1995). Increasing spatial aggregation of disturbance generally leads to increased extinction risk (Kallimanis et al., 2005), as does a high frequency of disturbance. Obligate seeding plants are susceptible to frequent fire events, which have been found to reduce population sizes and even lead to localized extinction (Bradstock et al., 1996; Keith, 1996). In fire-prone landscapes, plants unable to resprout might be expected to be sparse or patchily distributed in refuges where fire has less of an impact.

Resprouting ability is one obvious contributor to resilience to disturbance and, where it occurs, it allows species to persist through disturbance in isolated fragments and to maintain more sources for recolonisation by dispersal, thereby making plants more common in the landscape.

As shown in my study on Persoonia, commonness is indeed associated with the ability to resprout after disturbance (Table 2.9), as a lower proportion of rare species studied were resprouters. However, like many other generalizations that have emerged in ecology, the pattern is not absolute and counter-examples exist. In fact, some of the most common Persoonia species are obligate seeders, rather than resprouters, and therefore are unable to resprout after the death of the aboveground parts of the plant

(Table 2.1). This poses the question of exactly what characteristics enable these obligate-seeding common species to be more abundant than the many rare species that also lack the ability to resprout? Are there other traits that differ between these obligate- seeding common and rare species, which influence their persistence and dispersal? This has been the main question I have sought to answer during the course of my PhD 165 research project, in which I employed a comparative approach, comparing two pairs of closely-related common and rare species, and utilized both ecological and genetic techniques to explore this complex and challenging problem.

The persistence of obligate seeders in fire prone habitats is reliant on the availability of seeds to re-establish after disturbance, which is largely determined by seed production, seed predation, seed-bank dynamics, and seedling recruitment (Enright and Lamont,

1989; Rabinowitz et al., 1989; De Lange and Boucher, 1993; Wenny, 2000; Denham and Auld, 2002). Here I have focused on comparing the ability of common and rare obligate seeding Persoonia species to produce seed and the immediate fate of these seeds, and have contributed to a parallel PhD project exploring seed longevity in the soil and seedling establishment after fire (conducted by David J. McKenna, University of

Wollongong). While seed predation in this study was not consistently related to rarity

(Figure 5.3), I found the common Persoonia species had significantly greater reproductive success (Figure 4.2), leading to a higher proportion of seeds potentially contributing to the seed bank than for rare species (66% cf. 19%). Long-term persistence is also dependent on sufficient genetic variation for adaptive evolution in changing environments (Lande, 1999). Genetic variation also contributes to the short- term persistence of populations by determining the availability of compatible mates in self-incompatible species (DeMauro, 1993; Young and Clarke, 2000).

Population genetic theory predicts that species with smaller populations will generally have lower levels of genetic variation (Frankham et al., 2002). In this study, however, I found that rare Persoonia species had greater variation within populations than the common species (Table 3.3.). Given these conflicting results from the ecological and 166 genetic components of this study, it is unclear how population or species persistence relates to rarity. It is likely that the recent fragmentation of landscapes in Australia will have had immediate ecological effects (e.g. reduced reproductive success; Brys et al.,

2004), which are likely to alter the genetic composition in rare species in the long-term

(Schmidt and Jensen, 2000; Llorens et al., 2004), although it may not be detectable in the short term.

Pollen and seed dispersal facilitate the exchange of genes between local populations

(Ouborg et al., 1999), thereby influencing the distribution of genetic variation and enabling plants to move through the landscape. An understanding of animal behaviour can provide insights into the movement of pollen within and between animal-pollinated plants (Richardson et al., 2000), as well as the dispersal of seed from plants (Jordano,

1995). Persoonia flowers are effectively pollinated by native bees (Bernhardt and

Weston, 1996; Wallace et al., 2002), and their fleshy fruits are typically dispersed by large mammals and birds (Benson and McDougall, 2000). I found that the number of flowers visited by native bees of the genus Leioproctus subgenus Cladocerapis and the proportion of fruits removed by macropod marsupials (Wallabia bicolor and Macropus rufogriseus) was greater in common than in rare Persoonia species (Chapter 4 & 5).

Accordingly, I detected less genetic divergence among populations of common than rare species (at similar spatial scales; Figure 3.2. & 3.3.), signifying that common species have higher levels of gene flow among populations. These findings provide a strong indication that common and rare Persoonia species differ in their dispersal ability, with historical levels of gene flow among populations and current levels of pollen and seed dispersal likely to be greater in common species.

167

Comparisons of closely related species with contrasting distributions and abundances may provide insights into the causes of rarity (Kruckeburg and Rabinowitz, 1985;

Silvertown and Dodd, 1996). This is a strength of my study, which used two replicates of carefully constructed species pairs. Despite the obligate seeding Persoonia species, that were the subject of my study, having similar gross floral and fruit morphology, and attracting the same suite of pollinators and seed dispersal/predation agents, I detected several key genetic and ecological differences. The implications of these findings for the processes of colonization and extinction are discussed below in relation to plant rarity, population genetics, pollination and seed dispersal.

6.1. Biology of rarity Conservation biology is motivated by the need to reduce current rates of extinction and conserve biodiversity, and the scale of the problem is enormous. The world’s biological diversity is being rapidly depleted as a direct and indirect consequence of human actions

(WCMC, 1992). The threat of extinction, as defined by the World Conservation Union

(IUCN, 1994, 2003), depends on the rate of decline in population size, restricted habitat area and/or limited population size. Museum and herbarium records often contain the only information available on historical patterns of distribution and abundance, but in many cases this information is not detailed enough to allow the estimation of changes in population size (Chapter 2). However, such records do provide a means of estimating the extent of occurrence and area of occupancy for the majority of species, which are attributes frequently used as the basis of defining the level of commonness/rarity

(Gaston, 1997a). This does not mean that all rare species are also threatened, as evident in the genus Persoonia, in which several species – in all three categories of rarity (Table

2.7)– are listed as nationally threatened (EPBCA, 1999). Conversely, there are a number of rare species not currently listed as threatened. While herbarium records provide 168 relatively good estimates of species distributional patterns, they lack information on local abundance (i.e. population size), which is a vital component of assessments for threat of extinction (IUCN, 2001).

Historically, rare species that are well adapted to a specific ecological niche may be able to persist in relatively small populations for many generations (Elliott et al., 2002;

Lloyd et al., 2003). Extinction is not necessarily a consequence of rarity as allopatric speciation by peripheral isolation is likely to produce restricted taxa, which may expand during times of favourable conditions to become common (Endler, 1977; Coyne and

Orr, 2004). However, rarity is often a precursor to extinction, and the genetic and demographic factors operating on small populations are expected often to lead to extinction (Frankham et al., 2002). Several extremely rare Persoonia species are currently not protected under state or national legislation, but may warrant listing as vulnerable under criterion D, ‘very small or restricted population’ (IUCN, 2003), having an area of occupancy <20 km2 or being found in <5 locations (Table 2.2). The classification of the threat of extinction for these species will depend on the rate of population decline, level of fragmentation and severity of population fluctuations.

The genetic and ecological consequences of rarity are likely to be very different for historically rare species than for those that have recently become rare. The effects of genetic drift may not be detected in recently rare species, but inbreeding depression and reproductive failure may be more prevalent (Barrett and Kohn, 1991; Llorens et al.,

2004). Good historical records are essential to reconstruct the distribution and abundance of species prior to anthropogenic disturbance. Unfortunately, records are typically patchy (prior to 1900AD) even after European settlement in Australia

(1788AD) and do not provide an accurate estimate of historical distributions. 169

For many species, the combined herbarium records provide the best available information for determining the distribution and abundance of species. While this allows the classification of rarity (as done here in Chapter 2), it does not separate the potential contribution of historical patterns from anthropogenic effects required to determine the rate of population decline or growth. Inferences about the decline of populations can be gained by comparing the area of occupancy for species from herbarium records and targeted surveys for extant plants, and overlaying land use patterns. In intensively used areas, the available habitat for species may be reduced and fragmented, thereby directly causing declines in plant numbers (e.g. Persoonia rudis found in the WA wheat belt was classed as endangered by; Briggs and Leigh, 1988), while in more remote areas, the known abundance of species may actually increase with greater survey work (e.g. P. leucopogon was presumed extinct by Briggs and Leigh

(1988) but has since been located after targeted surveys).

Targeted surveys, conducted as part of my project on several common and rare species in the Sydney region, revealed that while some occurrences have been lost through land clearing/degradation, species distributions have not declined dramatically since

European settlement ( in some cases the distribution has increased due to the discovery of new sites of occurrence; Chapter 2). Populations of these common and rare

Persoonia species are patchily distributed in the landscape. The species have been impacted by anthropogenic disturbances to varying degrees depending on their preferred habitat. Drainage lines and gullies where P. mollis ssp. nectens and P. mollis ssp. maxima occur are not heavily affected by anthropogenic fragmentation, while recent urban and agricultural development have subdivided populations of P. lanceolata and P. 170 glaucescens, both of which occur on ridges and gentle slopes (Chapter 2). Plant populations naturally fluctuate in size as a response to demographic and environmental stochasticity, depending on life-history traits (Harper, 1977). Plants are likely to differ in this respect, and rare species of may be more variable in growth and survivorship from year to year (David J. McKenna PhD research). Plants with traits that enable them to persist after disturbance events, such as the ability to resprout, are likely to maintain relatively stable population sizes (Bradstock, 1990). Population declines, level of fragmentation and magnitude of fluctuations are all likely to have genetic and ecological implications for the Persoonia species investigated in this study.

6.2. Genetic variation and structuring Theoretically, the loss of genetic variation, which is usually associated with small populations or historical bottlenecks, will reduce the ability of populations to evolve in response to environmental change (Hoffmann and Parsons, 1997). Contrary to these predictions, my study found that the common Persoonia species, which appear to be well adapted to a relatively wide range of environmental conditions, had less genetic variation within populations than the rare species. Given that the overall levels of variation were low (compared to other long-lived, outcrossing, animal dispersed perennials, Nybom, 2004), this suggests that populations of common species may be less persistent in the long-term given the forecast of rapid rates of environmental change

(CSIRO, 2001; Allen_Consulting_Group, 2005). On the other hand, such species may have additional genetic diversity within persistent soil stored seed-banks (Llorens,

2004) and/or within refugial populations (Dumolin-Lapegue et al., 1997). I did not sample genetic diversity in the soil-stored seed banks of my study species, and neither did I sample all of the extant populations of the common species. Furthermore, the variation I did measure, using neutral genetic markers (AFLPs), may not give a true 171 indication of the adaptive potential of populations. Components of quantitative genetic variation determine the ability of a population to undergo adaptive evolution (Frankham et al., 2002), and quantitative differences among populations can be maintained by natural selection even under high levels of dispersal (Endler, 1977). Further research is needed to determine the relative adaptive potential of common and rare species, requiring more thorough sampling of above ground plants and the soil seed-bank from populations across the species’ range, using quantitative and neutral genetic markers.

The amount of genetic divergence between populations provides an indication of historic levels of gene flow (Russell, 1998). In my study, populations of common species had lower divergence (at similar spatial scales; Figure 3.2. & 3.3.) than populations of rare species, suggesting that the common species had higher historic levels of gene flow. As predicted, this could potentially explain the observed differences in geographic distribution. Given the apparently high levels of gene flow, through both pollen and seed dispersal, founder effects are unlikely to explain why common species had less genetic variation than rare species. In fact, the lower levels of genetic variation detected in the common species could be attributed to rapid range expansion through long-distance dispersal events from a narrow gene pool (Hewitt, 2000; Tang et al.,

2003; Ye et al., 2004). Alternatively, the low levels of genetic diversity found in all taxa may be explained by historical bottlenecks (England et al., 2002), or metapopulation dynamics (Pannell and Charlesworth, 2000). Further research is required to test these potential explanations.

6.3. Breeding system and pollination Selfing has been suggested as an evolutionary response to increasing rarity, as it provides reproductive assurance when compatible mates and/or pollinators become 172 limited (Baker, 1955; Carpenter and Recher, 1979; but see Herlihy and Eckert, 2002).

On the other hand, plants with large outcrossing populations tend to have highly developed self-incompatibility mechanisms that prevent the negative effects of inbreeding depression (Barrett and Harder, 1996). Predominantly selfing and outcrossing represent two alternative stable states in plant breeding systems (Lande and

Schemske, 1985). Despite the expectation that the level of commonness or rarity would be associated with breeding systems, the majority of published studies comparing the breeding systems of common and rare congeners found them to be similar (as in this study, see Chapter 4; Fitz-Sheridan, 1988; Sydes and Calder, 1993; Premoli, 1996;

Bosch et al., 1998; Affre and Thompson, 1999), indicating that the traits may vary at a higher phylogenetic level. This does not appear to be the case in Persoonia, because a range of breeding systems, from self-compatible to obligate-outcrossing (Krauss, 1994;

Goldingay and Carthew, 1998; Trueman and Wallace, 1999; Cadzow and Carthew,

2000) have been documented for species within the ‘lanceolata’ clade. Historical patterns of species abundance may therefore be determinants plant breeding systems

(Baker, 1955), alternatively the ability of plants to produce seed from self pollination could be selected for in small isolated poopulations.

The effectiveness of different floral visitors as pollinators is dependent on their behaviour and movement (Richardson et al., 2000; Wallace et al., 2002). Self- incompatible species, including the Persoonia species studied here, require pollen to be effectively transferred between compatible plants. The behaviour of the native bees that are the most effective pollinators of Persoonia, species of Leioproctus subgenus

Cladocerapis, was found here to promote outcrossing in Persoonia (cf. Bernhardt and

Weston, 1996; Wallace et al., 2002). This contrasts with the role of the introduced 173 honeybee, Apis mellifera, which appears to be an inefficient effective pollinator of

Persoonia (Bernhardt and Weston, 1996), as its behaviour encourages selfing. The frequency of visits by Leioproctus and Apis was found to differ in common and rare species (Figure 4.4). Effective pollination was limited in the rare species, which were associated with fewer native bee visits, resulting in reduced reproductive success

(Chapter 4). While similar results have been published elsewhere (Banks, 1980; Karron,

1987; Fitz-Sheridan, 1988; Sydes and Calder, 1993), the cause of this difference remains unclear. Plant and flower attributes of the study species were superficially similar, however pollinators may be more attracted to flowers of a particular colour

(differing in P. lanceolata having yellow and P. glaucescens having orange flowers), odor or nectar composition (species differences were noted by Bernhardt & Weston

1996).

Pollinators are also likely to respond to differences in site attributes (Eckert, 2002), local abundance (Kunin, 1997b), and fragmentation (Aizen and Feinsinger, 1994). As different sites had to be used for common and rare species in this study, site attributes that are likely to alter the composition of the pollinator community cannot be eliminated. Local abundance has been found to affect pollinator visitation rates (Kunin,

1997b), however it is difficult to separate the affect of population size and plant density.

Population sizes differ between the species, with the common species locally abundant

(c. >500 plants) and the rare species generally consisting of fewer than 100 plants at a site. The combined effects of recent fragmentation and introduced floral visitors are likely to reduce the number of compatible mates and native pollinators. Future research should focus on investigating the role of honeybees, through selective exposure 174 experiments (pollen loads, fruit set, paternity analysis, and offspring fitness) and the sites and plant attributes that attract native bees.

6.4. Seed dispersal and predation Seed dispersal and predation are important factors influencing colonization and extinction events, thus potentially determining the distribution and abundance of species

(Eriksson, 1996). In my study, rare species had fewer fruits removed than common species (Figure 5.2). The fate of seeds removed from plants by dispersal agents is usually unknown; they may be deposited immediately outside the parent canopy, in a similarly favourable site away from the parent plant, in an unfavourable site away from the parent plant, or be destroyed during the process (Howe, 1986). Inevitably, only a small fraction of the seeds removed will be able to successfully colonize a new site away from the parent plant and an even smaller fraction of these will represent effective long-distance dispersal events (representing the tail of the dispersal curve; Harper, 1977;

Cain et al., 2000). Despite this, plants have various adaptations for dispersal (including the fleshy fruits found in Persoonia and many other plant groups around the world;

Howe, 1986). It follows that there must be some ecological and evolutionary advantages to having seed dispersed. Seeds that remain under the parent canopy may have lower fitness than those that are dispersed because they are more likely to be eaten, attacked by pathogens, and/or have to compete with higher densities of siblings and other conspecific individuals (Rey and Alcántara, 2000).

These conflicting processes make it difficult to interpret the spatial patterns of seedlings using classical ecological techniques alone, but in combination with hyper-variable chloroplast and nuclear genetic markers (e.g. microsatellites), it may be possible to decouple the effects of density and dispersal (see Donohue, 1997 for ecological 175 framework). For long-lived perennials, there are few opportunities to explore these issues. During the course of our PhD projects, however, David McKenna and I were able to map seedlings that emerged in a small population of P. mollis ssp. nectens at

Sublime Point (Wollongong, New South Wales) for which all standing adult plants had been genotyped prior to being killed by fire (Krauss, 1999, 2000). This site presents an exciting research opportunity, which will be explored in more detail in a later study using a combination of genetic and ecological techniques.

The effects of seed predation may be greatest immediately after fruit drop, when seed densities are greatest and leaf litter or soil debris have not concealed the location of seeds (Curran and Leighton, 2000). In my study, I found no indication that seed predation was related to rarity, but the rare Persoonia mollis ssp. maxima had greater levels of seed predation than the other three species (Figure 5.3.). Seeds that are not removed or eaten may contribute to the seed-bank, where they may decay as a result of fungal attack or persist until dormancy is broken. Persoonia species have persistent soil stored seed-banks (Auld et al., 2000), although their magnitude may vary between species (David J. McKenna PhD Thesis), because dormant seeds slowly decay until germination is triggered by disturbance (even though the mechanism for breaking dormancy is unknown; Wasley, 1997). Given that fire kills standing plants, processes acting on seeds (e.g. dispersal and predation) will play an important part in the dynamics of populations, particularly in landscapes dominated by frequent fires.

The levels of seed dispersal and predation are dependent on the community composition and abundance of agents responsible for removing and destroying seeds, as well as their foraging behaviours (Guariguata et al., 2000). In these Persoonia species, macropods 176

(predominantly wallabies) were found to remove fruits from under plants, and rodents

(predominantly native rats) were responsible for eating and destroying seeds (Chapter

5). These animals are likely to forage at very different spatial scales (daily foraging range of wallabies and rats is 5-7 km and 0.1 km, respectively) and their behaviour will be influenced by a variety of different plant, microhabitat and population attributes

(Alcántara et al., 2000). However, only plant size was associated with seed removal in

Persoonia (Figure 5.4.), and it only explained a small proportion of the variation in seed removal, which was mostly between sites. While none of the plant/site attributes that I measured accounted for the differences observed between common and rare species, other site differences might effect seed dispersal and predation, potentially confounding this comparison. Similarly, population size had no effect on seed removal in the common P. lanceolata, but differences in the regional abundance of plants and the composition of the landscape matrix remain to be explored. Further investigations are needed to gain an understanding of the processes responsible for the observed patterns, and animal tracking would provide valuable insights.

6.5. Conclusions The causes and consequences of rarity are complex and often difficult to distinguish based on current patterns, without some knowledge of historical relationships. It is, however, possible to explore differences and similarities between well-defined common and rare species, which provide some insights into the processes currently shaping their distribution and abundance. In the genus Persoonia, the ability of plants to resprout after fire is associated with commonness/rarity, with rare species generally reliant on seed to re-establish. Some common species are also unable to resprout, but they appear to have a greater ability to disperse pollen and seed, enabling them to colonize more of the landscape than rare species. While important differences have been detected in 177 attributes that affect the persistence and dispersal of common and rare species, a greater understanding of the mechanisms involved is essential to determining their potential causal relationships.

To this end, I proposed the following questions as being of high priority for future research: • Why do the common Persoonia species have lower levels of genetic variation within populations than the rare species? Is it because of rapid range expansion through long-distance dispersal events from a narrow gene pool or historical bottlenecks or metapopulation biology?

• To test this a phylogeographic approach is required, thoroughly sampling populations across species ranges to potentially detect refugial populations, which may harbour greater levels of genetic diversity.

• Why do the common species have more native bee visits and fruit removed than the rare species? Is it because they are more attractive or is it because pollinating/dispersal agents are more abundant where they occur?

• To test this plants of both common and rare species need to be studied at the same site (at similar densities), through reciprocal transplants, and greenhouse experiments with controlled exposure of plants to bees.

The findings of this study have important value for conservation, enabling the following recommendations to be made: • Assess the species with extremely restricted distributions for listing under national and state threatened species legislation, by including a more detailed examination of local population size, and threats including risk of decline.

• Determine the ability to resprout after fire for all Persoonia species (~30% unknown, including 8 of the 14 species classified as extremely rare). For those species that are unable to resprout, explore their potential to produce viable seed and disperse.

• Conservation of all wild populations of P. mollis ssp. maxima and P. glaucescens should be a priority, since they harbour relatively high levels of genetic diversity and have limited ability to disperse to new locations. 178

• The impact of the introduced honeybee should be monitored, and if future research confirms that they are directly or indirectly reducing reproductive success and outcrossing, action should be taken, through the removal of hives, to ameliorate these negative affects.

• Recent habitat fragmentation is likely to lead to loss of genetic variation in the long- term, and this study should be used as a base line to monitor for any changes in the levels of genetic variation in the study populations over time.

The findings of my research will be combined with the parallel PhD project undertaken by David McKenna (University of Wollongong). McKenna focused his research on the same suite of Persoonia species that I used, for which he collected demographic data on the survival and fecundity of plants, enabling him to model the long-term persistence of common and rare obligate seeding Persoonia species. McKenna’s findings indicate that rare Persoonia species are more variable from year to year in their growth and survivorship than common species, especially during drought years. This fits nicely with my finding that rare species may be less persistent, tending to lack the ability to resprout and being found in moderate environmental conditions. While both of our studies have provided valuable information for the conservation of rare and threatened

Persoonia species, the real benefits will be in combining our findings to explore the role of persistence and dispersal in plant rarity. Spatially explicit models will be constructed to better advise conservation managers and build on the current scientific understanding of plant rarity. 179

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Appendices Appendix 1: The geography, phylogeny and life-history traits for Persoonia.

Species East/West Phylogeny Threatened Records Resprouting Floral No. Flowers/ Tepal length Height Leaf area Subspecies 1 2 3 4 ability 5 type 6 ovules 7 Inflorescence 8 (mm) 9 (m) 10 (mm2) 11 P. acerose east 6 5 86/89 1 1/1/1/2 1 80 10.0 2.0 12 P. acicularis west 10 0 35/35 2 1/1/1/3 1 80 15.5 1.2 25 P. acuminata east 6 0 36/36 1/1/1/2 1 12 10.0 1.5 70 P. adenantha east 6 0 33/33 3 1/1/1/2 1 40 13.0 9.0 4200 P. amaliae east 6 0 36/36 3 1/1/1/2 2 13.0 8.0 1440 P. angustiflora west 10 0 68/71 2 1/1/1/3 1 4 16.0 1.8 182 P. arborea east 4 5 22/22 1 1/3/1/1 1 19.0 14.0 2100 P. asperula east 6 0 55/55 1 1/1/1/2 1 9 11.0 2.0 132 ssp. nov. 'Asperula' P. asperula east 6 5 5/5 1/1/1/2 2.0 16 ssp. nov. 'Watchtower' P. baeckeoides west 6.5 0 9/9 1/1/1/2 1 3 9.0 0.9 44 P. bargoensis east 6 4 25/25 1 1/1/1/2 1 20 10.0 2.5 55 P. biglandulosa west 11 0 13/13 2 1/3/2/5 2 13.0 1.5 325 P. bowgada west 10 0 14/14 1/1/1/3 1 15.5 3.5 143 P. brachystylis west 11 0 6/6 1/3/2/5 2 20 13.0 1.5 1200 P. brevifolia east 6 0 21/22 1/1/1/2 3 10 12.0 1.5 300 P. brevirhachis west 1 0 37/37 1/3/1/2 2 2 9.0 2.0 275 P. chamaepeuce east 6 0 217/239 2 1/1/1/2 1 20 13.0 0.2 50 P. chamaepitys east 6 0 68/71 1 1/1/1/1 1 18.0 0.2 19 P. chapmaniana west 9 0 26/26 1/1/1/2 2 30 11.5 2.0 104 P. comata west 10.5 0 51/54 2 1/2/2/5 2 90 15.0 1.5 2700 P. confertiflora east 2 0 121/134 2 1/3/1/2 1 1 14.0 2.0 2700 P. conjuncta east 6 0 23/24 3 1/1/1/2 1 13.0 7.0 3640 P. cordifolia west 6.5 0 7/7 1 1/1/1/2 2 8 11.0 2.0 156 P. coriacea west 6.5 0 107/110 2 1/1/1/2 2 10 11.5 2.0 910 P. cornifolia east 6 0 120/125 2 1/1/1/2 1 4 13.0 6.0 3600 P. curvifolia east 6 0 53/56 3/1/1/2 3 18 12.0 1.5 65 P. cuspidifera east 6 0 40/44 3/1/1/2 1 25 12.0 2.0 100 P. cymbifolia west 6.5 0 31/31 2 1/1/1/2 2 3 11.5 0.6 135 P. daphnoides east 6 0 13/13 1/1/1/2 1 8 10.0 0.1 1000 P. dillwynioides west 6.5 0 15/15 1/1/1/2 2 4 12.0 1.8 26 P. elliptica west 6 0 106/116 3 1/1/1/2 2 12.5 8.0 5500 P. falcata east + west 11 0 368/395 3 1/3/2/4 2 80 16.0 9.0 10500 P. fastigiata east 6 0 17/17 2 1/1/1/2 2 5 10.0 1.5 40 P. filiformis west 10 0 13/13 2 1/1/1/3 1 20 16.0 0.4 20 P. flexifolia west 6.5 0 2/2 1/1/1/2 2 3 12.0 2.0 75 P. glaucescens east 6 4 35/35 1 1/1/1/2 1 12.0 2.0 1440 P. graminea west 8 0 24/25 1 1/1/1/3 2 25 4.5 0.6 2800 P. gunnii east 5 0 113/116 2/3/1/1 2 13.5 3.0 500 P. hakeiformis west 11 0 10/10 1/1/2/6 2 60 12.0 1.8 70 P. helix west 6.5 0 64/70 2 1/1/1/2 2 5 11.0 2.8 240 P. hexagona west 10 0 26/26 1/1/1/3 1 10 20.0 3.5 169 P. hindii east 6 5 17/17 2 1/1/1/2 1 15.0 1.5 54 P. hirsuta east 6 3 116/120 1 1/1/1/2 1 10 10.0 1.5 70 P. inconspicua west 1 0 26/26 1/3/1/2 2 3 10.5 2.0 85 P. iogyna east 6 0 17/17 1/1/1/2 1 11 13.0 4.0 2090 P. isophylla east 6 0 50/55 1 1/1/1/2 1 70 8.0 1.5 15 P. juniperina east 6 0 571/611 2 1/1/1/2 2 40 11.0 2.0 53 P. kararae west 11 0 2/2 //2/ 2 10 13.5 5.0 490 P. katarae east 6 0 24/24 /// 22 12.0 9.0 3740 P. lanceolata east 6 0 164/165 1 1/1/1/2 3 30 12.0 1.6 1440 P. laurina east 2 0 28/31 2 1/3/1/2 1 1 15.0 2.0 6600 ssp. intermedia P. laurina east 2 0 72/77 2 1/3/1/2 1 1 15.0 2.0 6600 ssp. laurina P. laurina east 2 0 49/49 2 1/3/1/2 1 1 15.0 2.0 6600 ssp. leiogyna P. laxa east 6 1 2/2 //1/ 2 3 9.0 0.1 27 P. leucopogon west 6.5 0 6/6 1/1/1/ 2 2 10.5 0.6 33 P. levis east 6 0 202/217 3 1/1/1/2 2 34 14.0 5.0 11200 P. linearis east 6 0 460/506 3 1/1/1/2 2 50 14.0 5.0 630 P. longifolia west 3 0 268/284 3 1/1/1/2 2 12.0 5.0 3200 P. marginata east 6 4 13/13 2 1/1/1/2 2 4 12.0 0.6 920 P. media east 6 0 152/154 2 1/1/1/2 1 16 14.0 25.0 4900 P. micranthera west 8 3 4/4 1 1//1/ 2 15 14.0 0.4 2400 P. microphylla east 6 0 29/32 1/1/1/2 1 14 10.0 2.0 45 P. mollis east 6 0 63/66 1 1/1/1/2 2 30 11.5 2.5 240 ssp. budawangensis P. mollis east 6 0 71/76 1 1/1/1/2 2 30 11.5 4.0 360 ssp. caleyi P. mollis east 6 0 45/45 1 1/1/1/2 2 30 11.5 2.5 240 ssp. ledifolia P. mollis east 6 0 66/68 1 1/1/1/2 2 30 11.5 1.5 80 ssp. leptophylla 200

Appendix 1: Continued…

Species East/West Phylogeny Threatened Records Resprouting Floral No. Flowers/ Tepal length Height Leaf area subspecies 1 2 3 4 ability 5 type 6 ovules 7 Inflorescence 8 (mm) 9 (m) 10 (mm2) 11 P. mollis east 6 0 52/56 1 1/1/1/2 2 30 11.5 1.5 60 ssp. livens P. mollis east 6 3 31/31 1 1/1/1/2 2 30 11.5 5.0 2040 ssp. maxima P. mollis east 6 0 72/74 1 1/1/1/2 2 30 11.5 5.0 1500 ssp. mollis P. mollis east 6 0 29/29 1 1/1/1/2 2 30 11.5 3.0 1500 ssp. nectens P. mollis east 6 0 30/33 1 1/1/1/2 2 30 11.5 0.5 600 ssp. revoluta P. moscalii east 5 5 15/15 1/1/1/ 2 11.0 0.1 60 P. muelleri east 5 5 29/30 1/1/1/1 2 19.0 4.0 420 ssp. angustifolia P. muelleri east 5 0 49/52 1/1/1/1 2 19.0 3.5 500 ssp. densifolia P. muelleri east 5 0 77/80 1/1/1/1 2 22.0 4.0 400 ssp. muelleri P. myrtilloides east 6 0 44/44 1 1/1/1/2 2 40 12.0 2.5 1140 ssp. cunninghamii P. myrtilloides east 6 0 80/88 1 1/1/1/2 2 40 11.0 2.5 600 ssp. myrtilloides P. nutans east 6 3 71/76 1 1/1/1/2 2 40 11.0 1.5 113 P. oblongata east 6 0 53/58 1 1/1/1/2 2 16 12.0 3.0 1500 P. oleoides east 6 0 57/60 2 1/1/1/2 1 25 15.0 1.0 900 P. oxycoccoides east 6 0 49/51 2 1/1/1/2 3 13 11.0 0.9 66 P. papillosa west 10 0 3/3 //1/ 1 20 14.0 0.3 39 P. pauciflora east 6 5 11/11 1 1/1/1/2 1 8.0 1.5 28 P. pentasticha west 9 0 21/21 2 1/1/1/2 2 15 12.0 1.8 144 P. pertinax west 6.5 0 13/13 1/1/1/ 2 10 11.0 2.5 138 P. pinifolia east 6 0 90/96 1 1/1/1/2 1 200 9.0 4.0 35 P. procumbens east 6 0 25/27 1/1/1/2 1 6 9.0 0.1 612 P. prostrata east 6 1 2/2 /1/1/2 5 10.0 0.1 1200 P. pungens west 6.5 0 20/20 2 1/1/1/2 1 5 12.5 0.8 75 P. quinquenervis west 10 0 182/182 2 1/1/1/3 1 10 15.0 2.5 750 P. recedens east 6 0 19/19 1/1/1/2 1 12 10.0 1.5 70 P. rigida east 6 0 184/194 1 1/1/1/2 3 20 12.0 2.0 950 P. rudis west 10 0 18/18 1 1/1/1/3 1 30 14.0 1.0 63 P. rufa east 6 0 14/14 1 1/1/1/2 1 12 14.0 2.5 1500 P. rufiflora west 1 0 49/52 2 1/3/1/2 2 2 10.0 2.5 360 P. saccata west 10.5 0 88/90 2 1/2/2/5 2 90 14.0 1.5 238 P. saundersiana west 11 0 118/120 1/3/2/5 2 25 14.0 5.0 672 P. scabra west 10 0 15/15 2 1/1/1/3 1 3 10.0 0.9 210 P. sericea east 6 0 235/255 2 1/1/1/2 2 23 11.0 4.0 1260 P. silvatica east 2 0 132/146 2 1/3/1/2 1 1 14.0 9.0 3000 P. spathulata west 10 0 5/5 1 1/1/1/3 1 13.0 0.6 400 P. stradbrokensis east 6 0 111/114 3 1/1/1/2 1 20 13.0 6.0 4400 P. striata east 10 0 65/69 2 1/1/1/3 1 5 12.5 0.7 122 P. stricta west 11 0 44/45 1/3/2/5 2 25 16.0 5.0 1200 P. subtilis east 6 0 48/51 2 1/1/1/2 2 18 10.0 1.0 40 P. subvelutina east 4 0 73/80 1/3/1/2 1 15.0 5.0 1050 P. sulcata west 10 0 33/35 2 1/1/1/3 2 11.0 1.0 60 P. tenuifolia east 6 0 111/122 2 1/1/1/2 2 8 10.0 0.5 13 P. teretifolia west 11 0 105/114 1/2/2/4 2 20 13.0 3.0 105 P. terminalis east 6 0 28/28 1 1/1/1/2 2 5 10.0 1.0 15 ssp. recurva P. terminalis east 6 0 18/18 1 1/1/1/2 2 5 13.0 1.5 20 ssp. terminalis P. trinervis west 10 0 45/46 2 1/1/1/3 1 4 16.0 1.8 1800 P. tropica east 7 0 16/16 1/3/1/2 2 10 11.0 3.5 2310 P. virgata east 6 0 216/231 1 1/1/1/2 2 75 9.0 4.0 100 P. volcanica east 6 0 46/46 1/1/1/2 1 20 13.0 6.0 900

1 Geographic groups; Eastern and Western Australia. 2 Phylogenetic groups; see Figure 2.1 for details. 3 Taxa listed as threatened; 1= ‘presumed extinct’ under EPBC national list, 2= ‘critically endangered’ under EPBC national list, 3= ‘endangered’ under EPBC national list, 4= ‘vulnerable’ under EPBC national list, 4= listed under state legislation not listed under EPBC national list, 0= not listed as threatened under state or national legislation (EPBCA, 1999). 4 Final number of herbarium records included into the spatial analysis / number of herbarium records assumed to be accurate on the basis of collection information. 5 The plants ability to resprout after disturbance; 1= unable to resprout and relies on seed to re-establish, 2= able to resprout from the base only, 3= able to resprout from the base and stem (data obtained from the NSW National Parkes and Wildlife Service ‘Fire Response Database’, Peter Weston, Tony Auld, Peter Clarke and other botanical/ecological experts). 6 A description of the type of flowers produced; tepal colour (1=yellow, 2=white, 3=yellow/red) / anther colour (1:yellow, 2=yellow with white tips, 3=white) / floral symmetry (1= actinomorphic perianth. 2= zygomorphic perianth) / floral openness (1= open, 2= closed - lanceolata type, 3= closed - quinquenervis type, 4= closed - teretifolia type, 5= closed - saundersiana type, 6= closed - hakeiformis type)(data complied by PHW). 7 The number of ovules produced/flower (data complied by PHW). 8 The maximum number of flowers/inflorescence (data complied by PHW).. 9 The maximum tepal length (data obtained from the Floral of Australia Vol 16 and Flora of NSW Vol 2). 10 The maximum plant height (data obtained from the Floral of Australia Vol 16 and Flora of NSW Vol 2). 11 An estimate of leaf area, maximum leaf length and width (data obtained from the Floral of Australia Vol 16 and Flora of NSW Vol 2). 201

Appendix 2: The distribution, abundance and environmental range for Persoonia.

Species EOO EOO AOO AOO AOO Rainfall Temperature Elevation Vegetation Geology ENV subspecies (α-hull) (k-NNCH) 1km 10km 100km max/min (mm) max/min (˚C) max/min (m) range range range 1 2 3 3 3 4 4 5 6 7 8 P. acerosa 1816.23 1225.55 42 1600 20000 1408/919 20.9/6.7 1152/338 3 2 244 P. acicularis 20710.55 25347.94 32 2600 50000 533/248 28.9/12.6 262/0 5 6 275 P. acuminata 18748.89 12096.34 27 1700 50000 2140/951 22.7/4.6 1548/96 11 9 479 P. adenantha 5762.01 5176.05 25 2000 20000 2508/1001 25.3/11.9 453/0 12 6 345 P. amaliae 62604.05 45364.38 33 2100 50000 1717/619 28.2/12.2 777/15 10 10 410 P. angustiflora 94074.61 83667.72 62 4900 130000 1148/313 26.4/9.0 453/6 13 9 399 P. arborea 1697.95 1697.95 18 1000 10000 1861/1125 19.1/4.3 1320/357 2 3 297 P. asperula 3410.56 2818.24 44 2100 20000 1226/703 20.4/2.2 1614/148 6 5 376 ssp. nov. 'Asperula' P. asperula 0.16 0.16 1 100 10000 1738/1738 12.6/3.7 1326/1213 1 2 68 ssp. nov. 'Watchtower' P. baeckeoides 254.81 254.81 7 500 10000 336/312 23.6/9.7 436/261 4 3 167 P. bargoensis 234.30 234.30 18 500 10000 1114/817 21.6/8.7 385/87 2 1 98 P. biglandulosa 3386.78 3386.78 13 1000 10000 442/320 27.4/12.6 250/16 2 3 141 P. bowgada 11307.21 8071.03 14 1200 40000 390/219 29.5/13.0 279/5 7 5 277 P. brachystylis 324.59 308.48 6 400 10000 420/374 27.2/13.3 222/4 1 2 88 P. brevifolia 515.58 515.58 16 500 10000 1473/911 18.7/4.1 918/275 3 3 256 P. brevirhachis 12063.00 5152.44 31 1300 40000 461/338 23.3/9.5 372/187 2 3 112 P. chamaepeuce 352685.27 201864.01 193 13600 290000 2078/544 21.7/-0.3 2094/100 53 19 555 P. chamaepitys 9531.32 7918.70 46 1900 20000 1389/741 21.7/5.7 1143/290 3 2 297 P. chapmaniana 12626.05 12626.06 20 1400 40000 437/306 26.4/11.5 327/212 2 4 139 P. comata 10828.33 9432.89 49 3500 30000 774/372 26.4/11.4 335/19 7 9 289 P. confertiflora 52850.69 42081.20 109 9000 100000 2102/625 21.2/2.0 1582/0 18 13 526 P. conjuncta 4901.76 4297.12 19 1500 20000 1834/1207 24.6/8.1 627/0 6 5 344 P. cordifolia 11.44 11.44 4 100 10000 381/362 23.1/9.9 247/219 1 1 41 P. coriacea 265912.76 214358.63 101 8500 220000 498/167 27.7/9.3 528/172 16 7 373 P. cornifolia 50373.67 49343.35 91 6500 80000 1444/641 25.9/5.5 1399/36 23 9 500 P. curvifolia 70293.24 54017.96 43 3200 100000 806/423 25.2/6.7 803/128 12 11 406 P. cuspidifera 4456.09 3950.17 33 2000 20000 1112/624 25.1/6.1 827/296 6 3 364 P. cymbifolia 17067.88 11856.06 30 2000 40000 488/317 23.6/9.7 401/134 5 8 215 P. daphnoides 718.37 716.08 10 500 10000 1218/864 21.3/7.4 1235/782 5 2 241 P. dillwynioides 3305.20 2808.91 13 900 10000 515/405 23.0/9.7 307/15 3 6 150 P. elliptica 61037.04 20341.28 98 6100 80000 1203/545 24.4/8.8 550/0 14 9 393 P. falcata 3514487.20 1938755.72 334 29600 1170000 4242/314 35.6/11.0 1087/0 113 51 563 P. fastigiata 8497.28 7363.38 14 1100 30000 984/679 24.1/4.6 1258/468 7 4 354 P. filiformis 1283.34 1242.69 9 700 10000 618/494 26.8/12.2 279/90 2 3 138 P. flexifolia 0.00 0.00 2 200 10000 736/531 22.6/11.1 17-Aug 2 2 72 P. glaucescens 776.20 713.57 28 1000 10000 1639/845 20.3/7.1 749/305 3 1 194 P. graminea 18618.79 15684.25 24 1800 40000 1248/781 21.8/8.6 209/0 7 6 235 P. gunnii 14570.04 11873.61 94 5200 40000 3391/1217 16.3/0.6 1306/23 12 12 472 P. hakeiformis 20752.98 20752.99 9 700 40000 515/355 23.1/9.1 416/301 3 3 130 P. helix 47925.94 41119.97 57 4500 70000 600/278 25.0/9.1 495/11 14 8 360 P. hexagona 19553.86 14829.92 25 1800 40000 508/291 27.5/12.5 325/21 5 11 265 P. hindii 111.05 69.25 14 300 10000 1168/913 18.7/6.6 1165/828 2 1 121 P. hirsuta 13741.26 12285.32 89 4100 40000 1376/732 23.5/7.0 814/0 11 5 371 P. inconspicua 44043.40 44043.40 25 2100 70000 361/282 25.9/9.7 480/325 8 4 232 P. iogyna 467.54 467.54 15 800 10000 1569/1101 25.0/12.7 576/292 4 5 206 P. isophylla 1413.67 815.90 43 1600 10000 1407/947 22.7/10.6 332/0 5 2 159 P. juniperina 522172.31 246086.41 483 32700 430000 2665/348 22.7/1.6 1200/0 81 32 554 P. kararae 0.00 0.00 1 100 10000 307/307 27.0/13.0 318/318 1 1 58 P. katarae 616.79 971.88 15 800 10000 1549/1284 23.6/12.6 40/0 5 5 150 P. lanceolata 34495.62 17091.69 141 6700 70000 1729/838 24.0/6.8 746/0 20 7 429 P. laurina 4423.52 2189.53 21 1500 20000 1775/810 22.5/5.6 978/4 7 4 370 ssp. intermedia P. laurina 17956.30 8011.46 54 2800 50000 1418/760 23.5/6.4 1127/0 10 5 412 ssp. laurina P. laurina 8894.25 7565.13 40 2800 20000 1890/763 21.2/4.4 1089/17 9 8 439 ssp. leiogyna P. laxa 0.00 0.00 2 200 10000 1293/1248 22.2/14.0 80/74 2 1 30 P. leucopogon 3666.46 685.91 6 400 40000 371/205 26.6/10.5 498/359 4 3 235 P. levis 102275.65 74918.29 162 11000 130000 2136/790 23.4/5.7 1081/0 27 16 511 P. linearis 192594.86 112404.18 396 30200 220000 2093/584 24.7/3.7 1444/0 62 27 555 P. longifolia 61453.28 31232.69 237 15700 90000 1336/579 23.9/8.2 505/0 16 14 423 P. marginata 246.58 222.11 9 400 10000 964/693 20.7/5.6 1112/636 2 2 213 P. media 41794.68 40414.50 103 6400 110000 3163/875 25.0/4.6 1444/36 23 8 524 P. micranthera 12.47 12.47 4 200 10000 912/596 18.7/6.9 925/270 1 1 149 P. microphylla 3939.63 2542.53 23 1400 20000 1241/718 19.7/4.4 1186/243 6 4 317 P. mollis 1314.13 770.31 36 800 10000 1334/929 19.0/4.8 1130/198 4 4 267 ssp. budawangensis P. mollis 7105.46 822.62 49 2200 20000 1589/696 22.0/6.3 715/0 9 6 370 ssp. caleyi P. mollis 1078.10 970.63 34 1300 10000 2136/848 21.6/6.9 840/103 6 3 309 ssp. ledifolia P. mollis 1708.00 1213.91 44 1600 10000 1374/808 21.8/6.3 785/0 6 5 312 ssp. leptophylla 202

Appendix 2: Continued…

Species EOO EOO AOO AOO AOO Rainfall Temperature Elevation Vegetation Geology ENV subspecies (α-hull) (k-NNCH) 1km 10km 100km max/min (mm) max/min (˚C) max/min (m) range range range 1 2 3 3 3 4 4 5 6 6 7 P. mollis 3145.54 2840.78 46 2600 10000 1241/674 21.0/5.2 729/103 7 8 337 ssp. livens P. mollis 40.41 39.95 17 100 10000 1342/1213 21.7/11.6 215/6 2 2 70 ssp. maxima P. mollis 1610.51 1538.98 37 2100 10000 1415/950 22.0/6.6 1144/143 2 3 264 ssp. mollis P. mollis 1211.53 1136.54 23 1200 10000 1854/848 21.2/7.4 608/104 4 2 244 ssp. nectens P. mollis 391.08 376.39 21 500 10000 1260/772 19.7/6.8 763/264 3 3 183 ssp. revoluta P. moscalii 825.15 825.15 7 400 10000 2958/2240 13.8/3.8 1040/150 1 1 143 P. muelleri 12547.26 8953.39 29 2300 40000 3418/1851 16.1/2.3 1136/7 7 11 404 ssp. angustifolia P. muelleri 3771.16 3076.08 43 2200 10000 2658/1221 16.3/3.5 976/0 4 7 333 ssp. densifolia P. muelleri 18555.21 13450.01 51 2900 40000 2936/791 14.3/0.5 1534/340 11 10 427 ssp. muelleri P. myrtilloides 2448.62 2126.15 32 1400 10000 1182/634 23.2/5.7 1257/391 5 6 372 ssp. cunninghamii P. myrtilloides 1063.82 971.82 44 1300 10000 1416/760 19.5/6.2 1156/638 3 1 219 ssp. myrtilloides P. nutans 724.40 619.51 38 1100 10000 1054/859 23.5/10.0 112/1 3 0 86 P. oblongata 6545.54 6545.54 40 2500 20000 1376/732 23.4/6.8 1019/3 5 1 325 P. oleoides 13678.46 8040.89 43 2800 40000 1626/957 24.9/5.6 1399/115 9 7 448 P. oxycoccoides 72624.67 7257.46 28 1200 10000 1969/795 20.5/5.2 1100/450 6 6 375 P. papillosa 1351.62 0.00 3 300 10000 369/280 27.6/12.7 269/155 2 2 129 P. pauciflora 1.12 1.12 3 100 10000 769/752 23.4/11.6 69/48 1 1 25 P. pentasticha 16853.68 9855.75 19 1400 30000 353/270 27.5/12.4 401/218 5 5 209 P. pertinax 4493.47 3278.55 11 1000 20000 212/185 26.6/11.1 360/237 3 5 167 P. pinifolia 4544.37 3767.90 63 2300 10000 1480/879 22.8/8.4 534/0 5 2 254 P. procumbens 1437.31 1137.88 21 700 10000 1447/880 20.1/5.6 1414/406 4 4 311 P. prostrata 0.00 0.00 2 100 10000 1315/1312 25.6/18.8 80/13 1 1 8 P. pungens 14463.21 13837.14 13 1200 40000 416/314 26.5/10.6 378/205 2 4 161 P. quinquenervis 171422.28 141098.91 162 13900 210000 934/252 26.4/8.8 455/67 16 8 397 P. recedens 198.86 147.90 13 400 10000 1342/947 17.6/6.7 1152/638 2 1 128 P. rigida 325093.53 176807.36 147 11900 260000 1775/478 25.9/2.5 1371/8 44 19 535 P. rudis 11692.36 9750.62 17 1400 40000 746/459 26.9/11.8 301/0 4 8 244 P. rufa 193.09 193.09 11 300 10000 1395/1194 20.1/7.9 1081/310 1 2 152 P. rufiflora 42732.86 41981.64 45 3300 70000 614/327 26.8/11.4 378/160 4 9 260 P. saccata 15352.23 10358.84 75 4800 30000 1139/684 24.4/9.9 312/0 10 11 304 P. saundersiana 75069.12 68693.22 105 7500 110000 379/220 26.5/9.3 495/239 13 6 332 P. scabra 15510.38 15510.38 15 1400 30000 635/312 23.4/9.8 312/23 5 6 208 P. sericea 548689.86 282616.06 187 14800 340000 1662/490 29.5/5.1 1397/0 54 24 548 P. silvatica 26981.36 19839.56 118 6100 50000 1621/499 20.8/2.2 1373/60 14 6 454 P. spathulata 4161.16 4092.66 5 400 20000 527/357 23.2/10.0 216/10 4 2 122 P. stradbrokensis 53077.20 32372.41 93 6900 100000 2146/1062 25.9/10.5 649/0 27 11 419 P. striata 58965.94 58965.94 63 5600 120000 751/302 23.8/9.0 431/17 15 11 361 P. stricta 49806.83 38144.50 43 3400 70000 568/301 27.4/11.6 375/6 3 10 265 P. subtilis 70617.94 59426.96 42 3000 80000 860/606 29.1/10.4 933/92 10 5 351 P. subvelutina 15580.80 13709.84 60 3300 50000 2301/764 20.8/0.1 1900/346 12 3 459 P. sulcata 3608.69 3608.69 30 2100 10000 913/469 24.8/10.7 338/111 5 2 195 P. tenuifolia 108431.77 75367.84 94 6900 110000 1806/662 26.9/7.3 1131/0 28 11 512 P. teretifolia 100329.48 78065.88 101 8300 160000 884/317 23.4/9.5 418/0 17 14 367 P. terminalis 9513.19 6967.80 23 1500 30000 784/637 26.0/8.9 727/244 6 3 262 ssp. recurva P. terminalis 336.49 327.28 11 600 10000 921/764 22.7/7.4 1132/718 3 3 231 ssp. terminalis P. trinervis 64957.82 62160.14 41 3800 100000 711/302 25.6/8.8 407/41 8 8 334 P. tropica 1281.53 1040.45 11 700 10000 2891/857 26.2/13.7 1257/619 4 2 268 P. virgata 168447.70 48779.30 162 10900 130000 2278/1029 27.6/12.4 688/0 40 20 471 P. volcanica 15382.60 652.66 39 1400 20000 1554/901 25.3/9.8 954/200 7 4 313

1 Extent of occurrence estimated by drawing a polygon around the point records using the ‘traditional’ α-hull method (measured in km2). 2 Extent of occurrence estimated by drawing a polygon around the point records using the k-Nearest Neighbour Convex Hull method (measured in km2). 3 Area of occupancy estimated by presence of records in 1km, 10km and 100km grid cells 4 Annual mean rainfall and minimum and maximum annual average daily temperature data (2.5km grids; Australian Bureau of Meteorology) were appended to the point records and the maximum/minimum values reported for each taxon 5 DEM 250 m grids ( Geoscience Australia) were appended to the point records and the maximum/minimum values reported for each taxon 6 Vegetation - Post-European Settlement 1988 (1643 types) and national geological regions (257 types) polygon data obtained from GA were appended to the point records and the number of different types reported for each taxon 7 Environmental range was calculated by summing the ranks (1-115) for rainfall, temperature, elevation range (max – min), and the number of different vegetation and geological classes.

203

Appendix 3: The life-history traits for Persoonia in the Sydney region.

Species AOO Local Vegetative Habitat Altitude Vegetation Substrate Nutrient subspecies 1km abundance spread P. acerosa 43 rare-occasional no ridges, rock outcrops 400-1000m Eucalypt open-forest, clay-sand low heath P. acuminata 27 occasional-frequent hillsides 1000-1200m Eucalypt woodland, well drained low-high open-forest P. bargoensis 18 rare-occasional no woodland to open- 100-300m Eucalypt woodland, clayey soils low-medium forest open-forest P. chamaepeuce 193 occasional yes hillsides 800-1200m Eucalypt woodland, sandy soils low open-forest P. chamaepitys 46 occasional-frequent no plateaus, slopes and 300-1200m Eucalypt woodland, sandy soils low near swamps open-forest P. glaucescens 28 occasional no ridgetops and slopes 400-700m Eucalypt woodland, clay-sand low open-forest P. hindii 14 rare yes plateaus-slopes 1130-1170m Eucalypt woodland, sandy soils low open-forest P. hirsuta 89 rare-frequent no ridges 0-600m Eucalypt open-forest, sandy soils low heath P. isophylla 43 occasional-frequent no heath 0-250m woodland, heath sandy soils low P. lanceolata 141 occasional-frequent no ridgetops and slopes 0-700m Eucalypt open-forest, sandy soils low woodland, heath P. laurina 21 frequent no ridges 0-620m Eucalypt open-forest sandy soils low ssp. intermedia P. laurina 54 occasional-frequent no ridges 0-1100m Eucalypt woodland, sand-shale low-medium ssp. laurina heath P. laurina 40 occasional-frequent rocky hillsides 550-1000m Eucalypt open-forest sandy soils low ssp. leiogyna P. levis 162 occasional-frequent no ridges and slopes 0-1100m Eucalypt woodland, sandy soils low open-forest P. linearis 396 occasional-frequent no ridges and slopes 0-1100m Eucalypt woodland, Sandy-clay low open-forest P. marginata 9 rare-occasional ridges and slopes 700-800m Eucalypt open-forest sand-clay low P. microphylla 23 frequent 900-1200m Eucalypt open-forest sand-clay low P. mollis 49 frequent no ridges and slopes 100-200m Eucalypt open-forest clayey soils ssp. caleyi P. mollis 34 occasional-frequent no plateaus and hillsides 600-700m Eucalypt woodland, sandy soils low ssp. ledifolia open-forest P. mollis 44 frequent no woodland 0-200m Eucalypt woodland, sand-clay low ssp. leptophylla heath P. mollis 46 occasional no ridgetops, upper 500-700m Eucalypt woodland, sandy soils low ssp. livens hillside open-forest P. mollis 17 rare-frequent no hillsides and gullies 50-150m Eucalypt open-forest sandy soils low ssp. maxima P. mollis 37 frequent no ridges and hillsides 400-1100m Eucalypt open-forest sandy soils low ssp. mollis P. mollis 23 occasional no ridgetops, slopes and 0-600m Eucalypt open-forest sandy soils low ssp. nectens gullies P. mollis 21 occasional no gentle slopes 600-800m Eucalypt open-forest sandy soils low ssp. revoluta P. myrtilloides 32 occasional-frequent ridges and rocky 600-1000m Eucalypt woodland sandy soils low ssp. cunninghamii outcrops P. myrtilloides 44 occasional ridges and slopes 800-1100m Eucalypt open-forest sandy soils low ssp. myrtilloides P. nutans 38 occasional-frequent no dry woodland 0-60m Eucalypt woodland sandy soils low P. oblongata 40 occasional-frequent no ridges, rocky hillsides 200-800m Eucalypt woodland, sandy soils low open-forest P. oxycoccoides 28 occasional ridgetops 600-1000m Eucalypt open-forest, sandy soils low heath P. pinifolia 63 occasional-frequent no hillsides 0-500m Eucalypt woodland, sandy soils low open-forest P. recedens 13 occasional-frequent plateaus and hillsides 630-1170m Eucalypt open-forest sandy soils low P. rigida 147 rare-occasional gentle slopes 0-800m Eucalypt open-forest sand-clay low