Invertebrate monitoring as measure of ecosystem change

Mélissa Jane Houghton

B. Arts and Sciences M. Environmental Management

A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2020

School of Biological Sciences Centre for and Conservation Science

Abstract

Islands and their biodiversity have high conservation value globally. Non-native are largely responsible for island extinctions and island ecosystem disruption and are one of the major drivers of global biodiversity loss. Developing tools to effectively measure and understand island ecosystem change is therefore vital to future island conservation management, specifically island communities and the threatened species within them. One increasing utilised island conservation management tool is invasive mammal eradication. Such programs are increasing in number and success, with high biodiversity gains. Typically, it is assumed that the removal of target non-native species equates to management success and in some instances, recovery of a key threatened or charismatic species affected by the pest species are monitored. Yet to date, there are few published studies quantifying post- eradication ecosystem responses. Such monitoring helps to calculate return-on-investment, understand the conservation benefits of management and inform conservation decision- making associated with current and future restoration programs. Not only are there few studies providing empirical evidence of whole-of-ecosystem recovery following mammal eradications, but research that measures the responses of lower trophic organisms and communities is also scarce. In consequence, questions remain regarding how best to manage ecosystems following large-scale eradications. When should we intervene to actively restore habitats or species interactions? What biodiversity indicators do we use to measure and monitor ecosystem change? How do we compensate when data are scarce? And perhaps most importantly, how can we learn from previous management efforts to inform future conservation decisions? To investigate optimal monitoring strategies for changing ecosystems, it is vital to understand which sampling methods to use, which habitats to focus on, and which taxa to monitor that will reflect broader ecosystem change. Moreover, non- native and invertebrate species that are not targets of invasive mammal eradication, can persist in an ecosystem following an eradication. These organisms interact with native species, impact biodiversity and can even create novel ecosystems. To understand the implications of these changes and make informed decisions to act effectively, conservation managers require tools to efficiently measure ecosystem change.

My research focuses on World Heritage islands of the sub- and I concentrate on a commonly overlooked group – terrestrial invertebrates. My thesis aims to address some of the questions raised above; first by reviewing the state of knowledge around non-native species

ii impacts on invertebrates on in the sub-Antarctic region (Chapter 2), developing methods for effective and meaningful monitoring of invertebrates in changing ecosystems (Chapter 3), quantifying the invertebrate response to sub-Antarctic island mammal eradications (Chapter 4), understanding drivers of invertebrate richness and abundance in order to interpret these responses and develop indicators for effective long-term monitoring (Chapter 5), and using a traits-based analysis to identify non-native invertebrate taxa of biosecurity concern and future threat to the region (Chapter 6).

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Declaration by author

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

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

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

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co- authors for any jointly authored works included in the thesis.

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Publications included in this thesis

Houghton, MJ., Terauds, A., Merritt, D. Driessen, M., and Shaw, JD. (2019) Journal Conservation 23: 435. https://doi.org/10.1007/s10841-019-00147-9

Houghton, MJ., Terauds, A., and Shaw, JD. (2019) Methods for monitoring invertebrate response to vertebrate eradication. Island Invasives: scaling up to meet the challenge 62. IUCN, Gland, Switzerland, 381-388.

Submitted manuscripts included in this thesis

No manuscripts submitted for publication.

Other publications during candidature

Peer-reviewed publications:

Phillips, L., Janion-Scheepers, C., Houghton, M., Terauds, A., Potapov, M. Chown, S. L., (2017) Polar Biology 40: 2137. https://doi.org/10.1007/s00300-017-2129-9

Bergstrom, D.M., Sharman, A., Shaw, J.D. Houghton, M., Janion-Scheepers, C., Achurch, H., Terauds, A., (2018) Biological Invasions 20: 293. https://doi.org/10.1007/s10530-017- 1551-9

Russell JC, Peace JE, Houghton MJ, Bury SJ, Bodey TW (2020) Systematic prey consumption by introduced mice exhausts the ecosystem on Antipodes Island. Biological Invasions.

Conference abstracts:

Houghton M, Terauds A, Merritt D, Dreissen M, Possingham H, and Shaw, JD (2019). Invertebrates as indicators of ecosystem change on sub-Antarctic islands. Island Arks Symposium, February 2019, Rottnest Island, Western .

Houghton M, Terauds A, Merritt D, Dreissen M, Possingham H, and Shaw, JD (2018). Invertebrates as indicators of ecosystem change on sub-Antarctic islands. Australasian Wildlife Management Society Conference, December 2018, Hobart, Tasmania.

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Houghton M, Terauds A, Merritt D, Dreissen M, Possingham H, and Shaw, JD (2018). Invertebrates as indicators of ecosystem change on sub-Antarctic islands. Ecological Society of Australia, November 2018, Brisbane, Queensland.

Houghton M, Terauds A, Merritt D, McQuillan P, Chown SL, and Shaw JD (2017). Invasion risk of non-native invertebrates to sub-Antarctic ecosystems: a traits based assessment. Australian Entomological Society 2017, Terrigal, NSW, Australia.

Houghton M, Terauds A, Merritt D, McQuillan P, Chown SL, and Shaw JD (2017). Invasion risk of non-native invertebrates to sub-Antarctic ecosystems: a traits-based assessment. British Ecological Society, July 2017, Durham University, Durham, England, UK.

Houghton M, Terauds A, Merritt D, Dreissen M, Possingham H, and Shaw, JD (2017). Post- eradication invertebrate monitoring on Macquarie Island. Island Invasives Conference (IUCN Specialist Group), July 2017, Dundee, Scotland, UK.

Contributions by others to the thesis

Justine Shaw - was responsible for conceiving, designing and developing the overarching project. Shaw also provided advice and feedback on the interpretation of research data and revision of drafts for all chapters. Aleks Terauds – contributed ideas for analysis and interpretation of research data for all chapters, and contributed revisions of drafts for all chapters. David Merritt – provided advice and feedback for drafts of Chapter 2, 4 and 6. Michael Driessen – was instrumental in the design of the Macquarie Island invertebrate trapping survey underpinning Chapter 3 and 4 and provided feedback and advice for Chapter 2, 3, 4 and 5. James C Russell – provided feedback, advice and reviewed drafts for Chapter 4. Steven L Chown – provided input into the analysis for Chapter 6. Peter McQuillan – assisted in the identification of the ‘detected’ invertebrates used in Chapter 6.

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

No works submitted towards another degree have been included in this thesis.

Research Involving Human or Subjects

During field surveys as part of this work, invertebrate (, slugs, etc.) were trapped and preserved in ethanol. Ethics approval was not required for invertebrate subjects.

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Acknowledgements

In the waning days of this PhD journey, I reflect on how I came to be here, furiously typing and formatting on a tome so long that I am allowed to use the word tome for the first time in practice. This all began with a strong urge to witness Macquarie Island with my own eyes. Remarkably, this fantasy became reality. I was included in the first field team on the ground for the Macquarie Island Pest Eradication Project as a dog handler. Fast forward - I had spent nearly a year chasing the sniff of rabbits around with the wonderful Wags the dog, and I was now offshore to the island on an icebreaker heading home. I was revelling in my involvement in the ambitious program to rid the island of mammal pests, a prospect that seemed frankly ludicrous upon first sight of the steep, rugged island, covered in snow. I was reminiscing on the vision of the last adult rabbit on the island (although we didn’t know it at the time), which had appeared like an apparition in the thick fog from a bird burrow Wags had tracked it to. My life had turned, I wanted more of this invasive species management – the feeling I had been a part of making an environmental difference. I found myself intrigued about how the island would transform without mammals. Given I was sharing the icebreaker with fascinating creatures called scientists, I approached them to ask, and find out what I could do next. It was then that I met Dana Bergstrom and Justine Shaw, not the typical scientists my mind had conjured. They were women, they were gregarious, vivacious, unpretentious, and excited to work with me. Once I began research with these extraordinary women of science, my love affair with the world of the very small and spineless began. Thus began a quite different experience of Macquarie Island from the one I had been enjoying. While everyone else was looking at the sky filled with seabirds, across dramatic landscapes clothed in fields, or at the beaches weighed down with the bulk of blubbery marine mammals, I was on my stomach, face down in the grass, or under Stilbocarpa cabbage leaves, staring at the island’s micro-cosmos. The globular bright yellow with speckles on their back, or lean and long, iridescent purple with shimmery scales. The plump little green and yellow spiders, and the cute pink booklice with large unblinking eyes. Others might not share my appreciation for their beauty, but I feel so fortunate to have had the time to discover all the other creatures of Macquarie Island.

This work would not have been possible without funding support from the Australian Government through the Research Training Scholarship, the Australian Antarctic Science Program (Project 4305 - Post eradication ecosystem response on Macquarie Island), the Threatened Species Recovery Hub and the National Environmental Science Programme (Project 4.2 - Saving species on Australian Islands). The Tasmanian Government (DPIPWE) also provided project support through Tasmanian Parks and Wildlife Service on Macquarie Island. I am immensely grateful for the additional funding I received through the Australian Academy of Science through the Max Day Environmental Science Fellowship, which changed the course of my PhD journey. I still recall receiving the award letter, and reading it several times before I could believe my eyes. The Max Day award gave me a platform to speak to the science community and the public about the power and fascination of invertebrates. I was able to travel far and wide to meet with invertebrate taxonomists and

viii island ecology specialists for training and advice. In a time when support for taxonomic training is low, this experience was invaluable. Thank you also to the Australian Entomological Society, for awarding me the Phil Carne Prize that gave me a mid-PhD boost.

To Justine and Aleks, I could not have for one moment achieved this epic document without your initial belief in me, followed by unwavering dedication, support and advice. Thanks for eye-watering editing work in the initial stages, and Training me Out of Captilising every Second word. Justine thanks for having the big ideas, always seeing opportunities for your students, and for making me push myself. If it weren’t for you, this project wouldn’t exist. Aleks – I am incredibly grateful for the time you spent working with me, patiently educating me on coding. No matter how busy you invariably were, you always made time available, shut the door and made it valuable time. Your patience, promptness, communication, constructive criticism and positivity are qualities I will aspire to should I ever find myself in a supervisory or management position.

Thank you to Michael Driessen, my unofficial fifth supervisor, who contributed to the design of the Macquarie Island invertebrate surveys and provided pivotal constructive feedback on two of the thesis chapters, all while being just an all-round lovely chap. To James Russell of the University of Auckland for willingness to embroil New Zealand in this project, for belief in my abilities from the get-go, great conversations, and for late night airport pick-ups. To Sarah Tassell from Landcare Research in New Zealand, for her knowledge and dedication to invertebrates, imparting some of her super organisation and cataloguing skills, and for being so generous with her time. To Dana Bergstrom and John van den Hoff aka ‘Snake’ – for friendship, humour and assistance throughout my time at the Antarctic Division. To Steven Chown who provided invaluable advice for Chapter 6, and wisdom on the foundation of scientific inquiry. His note: ‘The point of being a PhD student is to be a fuss – repeat!’ – still sits above my desk. To Hugh Possingham for taking the time to sign petty paperwork in the midst of saving the world, and providing funding for travel, conferences and Berlese funnels. To my readers John Dwyer and Kerrie Wilson – for their instrumental feedback which became the backbone of this thesis and for pushing me so hard to tackle the ‘Stats Monster’. Kerrie also for providing additional conference funding. David Merritt – thank you for coming on board to supervise an unknown quantity so readily, to dot my ‘I’s and cross my ‘T’s, and for being a calm and fair voice of constructive criticism outside my Tasmanian bubble. Thank you also to Charlene Janion-Scheepers for igniting and guiding my passion for springtails, superior taxonomic training, and for being so generous with her precious time.

To the station community and rangers on Macquarie Island, my field buddies Aimee, Alex, Andrea, Cath, Chris, Emily, Emry, George, Ian, Jacqui, Jez, Jules, Kerri, Kim, Kristen, Marcus, Margi, Matt, Mel, Penny, Rich, Robbie, Rowena, Toby - who enthusiastically assisted me with invertebrate surveys, sometimes carrying bulky material around the island, and for making me laugh when I needed it.

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I want to thank the passionate entomologists I have met along the way, often larger than life characters, with gory stories of bug death and insect sex. I may not have got much work done while I listened to Peter McQuillan but afterwards I always felt a certain joie de vie and had eyes wide for the life around me. Thank you all those entomological enthusiasts out there, persuading the public to care for the small organisms that run the world.

To my family, Sophie, Marc and Chloe, for providing drama and entertainment through the years as a relief from PhD fixation. Particularly to my mother Danielle - the Black Dragon - who would have loved to witness the making of a ‘doctor’ in the family.

To my great friends in Tasmania and beyond, including many of my field work companions, and specifically Laura, Jaimie, Marion, Erich, Mads, Aude, Helena, Jess, Derick, Shaun, Matt - for distracting me from myself with good company. Thanks to you - I survived. Special thanks to my friend Jasmine, for assistance helping me navigate UQ PhD life - formatting, administration and reading drafts. And to Abigael who gave me a statistical education, sowing the first seeds of my data analysis skills.

Thank you especially to my partner Ben for companionship, for encouraging me to take on this project, for providing a wall upon which to verbally head-butt on, for being my final editor, and for holding down the ranch while I hunted invertebrates in the high latitudes.

To the hounds – Wicket, Frank and Opi, who more than any other provided me love and companionship through thick and thin. Despite my occasional bleats when the wind was howling and the morning still dark, being obliged to take them walking in the steep hills every day prevented me from becoming a PhD dumpling, gave me much needed moments of silliness and laughter, and importantly, vital PhD thinking time.

To Macquarie Island – a place which not only saturated my senses with wild life, but brought me into contact with a world of fascinating people. This experience has changed my life. Thank you for lifting me, then humbling me, sometimes belting me to the ground, making me scream and smile, reminding me I am a servant to the powerful forces of Nature.

Despite the high number of causalities involved in my research, ethics approval was not required. I thought about this more and more often as I traipsed around solo on Macquarie Island in the wind and fog with my macabre quarry of invertebrate samples on my back. As the years went on, I was haunted by spiders in my dreams, screaming and scuttling away from my hunting tweezers as fast as their eight little legs could carry them and finally, unsuccessful in their plight, drowning slowly in an ethanol bath. Which brings me to my last, but perhaps most important thankyou – to the 100s of 1000s of invertebrates who sacrificed their lives in the spirit of invertebrate conservation research. I hope to be powered by the stilling of their small beating hearts to become an invertebrate conservation warrior. I dedicate this thesis to them.

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Financial support

This research was supported by an Australian Government Research Training Program Scholarship, the Threatened Species Recovery Hub as part of the National Environmental Science Program, and by the Australian Antarctic Division through the Australian Antarctic Science grant Project 4035. The Australian Academy of Science also supported this research through the Max Day Environmental Science Fellowship. The University of Auckland, through Dr James Russell, supported the New Zealand aspect of this research.

Keywords

Ecosystem recovery, invertebrates, mammal eradications, islands, biosecurity, conservation decision-making, invasive species

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 060808, Invertebrate Biology, 30%

ANZSRC code: 060208, Terrestrial Ecology, 30%

ANZSRC code: 050206, Environmental Monitoring, 40%

Fields of Research (FoR) Classification

FoR code:0502, Environmental science and management, 40% FoR code:0501, Ecological applications, 30% FoR code:0608, Zoology, 30%

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Table of Contents

Abstract...... ii Declaration by author ...... iv Publications included in this thesis ...... v Submitted manuscripts included in this thesis ...... v Other publications during candidature ...... v Contributions by others to the thesis ...... vi Statement of parts of the thesis submitted to qualify for the award of another degree ...... vii Research Involving Human or Animal Subjects ...... vii Acknowledgements ...... viii Financial support ...... xi Keywords ...... xi Australian and New Zealand Standard Research Classifications (ANZSRC)...... xi Fields of Research (FoR) Classification ...... xi Table of Contents ...... xii List of Figures ...... xiv List of Tables ...... xvii Thesis Acronyms ...... xix

CHAPTER 1 | INTRODUCTION ...... 1 Island conservation ...... 2 Island monitoring and restoration ...... 3 Invertebrate conservation on islands ...... 5 Invertebrates as indicators of island restoration ...... 7 Invasive species on Islands ...... 9 Biosecurity ...... 11 Thesis structure ...... 12

CHAPTER 2 | THE IMPACTS OF NON-NATIVE SPECIES ON THE INVERTEBRATES OF SOUTHERN OCEAN ISLANDS...... 15 Abstract ...... 15 Introduction ...... 16 The Study Area ...... 18 Literature Search ...... 22 Non-native species impacts on native invertebrates ...... 23 Non-native ...... 23 Non-native invertebrates...... 24 Non-native vertebrates ...... 27 Discussion...... 34 Ackowledgements ...... 38

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CHAPTER 3 | METHODS FOR MONITORING INVERTEBRATES RESPONSE TO VERTEBRATE ERAICATION ...... 39 Abstract ...... 39 Introduction ...... 40 Methods ...... 42 Results ...... 47 Discussion...... 53 Ackowledgements ...... 58

CHAPTER 4 | ISLAND INVASIVE MAMMAL ERADICATIONS AND INVERTEBRATE CONSERVATION ...... 59 Abstract ...... 59 Introduction ...... 60 Methods ...... 62 Results………………………………….…………………………………………………70 Discussion...... 728

CHAPTER 5 | DRIVERS OF MACRO-INVERTEBRATE COMMUNITIES FOLLOWING A MAMMAL ERADICATION ON MACQUARIE ISLAND ...... 88 Abstract ...... 88 Introduction ...... 88 Methods ...... 94 Results ...... 99 Discussion...... 120

CHAPTER 6 | SPECIES TRAITS CAN PREDICT INVERTEBRATE INVASIONS ON SOUTHERN OCEAN ISLANDS ...... 127 Abstract ...... 127 Introduction ...... 128 Methods ...... 132 Results ...... 138 Discussion...... 151

CHAPTER 7 | GENERAL DISCUSSION ...... 158 Key findings ...... 159 Limitations and opportunities for terrestrial invertebrate indicators ...... 164 Entomological training ...... 166 Support for invertebrate conservation...... 168 Future directions ...... 169 Conclusion ...... 172

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REFERENCES ...... 173 APPENDICES ...... 198 Appendix 1 | Supplementary material for Chapter 2 ...... 198 Appendix 2 | Supplementary material for Chapter 4 ...... 203 Appendix 3 | Supplementary material for Chapter 5 ...... 218 Appendix 4 | Supplementary material for Chapter 6 ...... 227

List of Figures

Figure 2-1 Map of the biogeographic region referred to as the Southern Ocean Islands, between 37˚S and 55˚S ...... 19

Figure 3-1 Map of 20 invertebrate trapping sites surveyed at Macquarie Island in 2015/16. All historic sites sampled in 1986/87 (indicated by grey diamonds) were resampled in 2015/16...... 46

Figure 3-2 Order richness (summed across 20 sites) and Simpson’s diversity of four different trapping methods on Macquarie Island in 2015/16 following mammal eradication...... 49

Figure 3-3 Order richness (summed across 20 sites) of four trapping types in five vegetation communities on Macquarie Island in 2015/16 following mammal eradication ...... 50

Figure 3-4 Simpson’s Index of Diversity (Order) of four trap types in five vegetation communities on Macquarie Island in 2015/16 following mammal eradication...... 51

Figure 3-5 a) Order richness (summed across 20 sites) and, b) Simpson’s Index of Diversity of pitfall trapping (Order level) at seven invertebrate monitoring sites at Macquarie Island that were first sampled in 1986/87 (prior to mammal eradication) and repeat sampled in 2015/16 (post mammal eradication)...... 52

Figure 4-1 The Antipodes Islands. Long-term invertebrate pitfall trapping sites are marked with a star symbol. (Map source: Russell 2012)...... 64

Figure 4-2 Macquarie Island. Long-term invertebrate pitfall trapping sites are marked with a grey circle...... 65

Figure 4-3 Free-living terrestrial invertebrate orders/ classes present, trapped and analysed in this study from Antipodes Island and Macquarie Island, illustrating taxonomic groups and species shared between both islands.…………………………………………………………………...... 68

Figure 4-4 Predicted invertebrate order richness (log scale) - for Antipodes Island pre- eradication (summer 2011, winter 2013, winter 2016), and following eradication (summer 2018) and for Macquarie Island pre-eradication (summers 1986, 1993, 2009) and post- eradication (summers 2015, 2016, 2018). Grey shading around the mean indicates the size of the 95% confidence intervals. The short blue lines at the upper and lower margin of the plots

xiv are indicative of the number of sampling events. The yellow vertical line represents successful eradication...... 75

Figure 4-5 Predicted diversity (Simpson’s Index – log scale) of invertebrates for Antipodes Island pre-eradication (summer 2011, winter 2013, winter 2016) and following eradication in 2018 (summer) and for Macquarie Island prior to eradication (summers 1986, 1993, 2009), and following eradication (summers 2015, 2016, 2018). Grey shading indicates the size of the 95% confidence intervals around the mean. . The short blue lines at the upper and lower margin of the plots are indicative of the number of sampling events. The yellow vertical line represents successful eradication...... 76

Figure 4-6 Predicted abundance (log scale) of 13 invertebrate orders on Antipodes Island, in three sampling seasons prior to rodent eradication (2011, 2013, 2016), and one sampling season post eradication (2018). The eradication program commenced in 2016 and was declared successful in 2018. DD = data deficient. Grey shading indicates the size of the 95% confidence intervals around the mean. The blue lines at the upper and lower margin of the plots are indicative of the number of sampling events...... 78

Figure 4-7 Abundance of 11 invertebrate orders on Macquarie Island, in three sampling seasons prior to rodent and rabbit eradication (1986, 1993, 2009), and three sampling seasons post eradication (2015, 2016, 2018). The eradication program commenced in 2011 and was declared successful in 2014. DD = Data deficient. Grey shading indicates the size of the 95% confidence intervals around the mean The blue lines at the upper and lower margin of the plots are indicative of the number of sampling events...... 79

Figure 5-1 The location of 24 invertebrate monitoring sites established on Macquarie Island in 2015, 2016-17 and resampled in 2018...... 93

Figure 5-2 Partial residual plots of total invertebrate richness across vegetation communities found in four trapping methods on Macquarie Island; a) pitfall, b) count, c) litter, and d) sweep. Grey shading indicates the 95% confidence intervals...... 103

Figure 5-3 Partial residual plots of total invertebrate richness across 3 years of sampling (2015, 2016-17, 2018) on Macquarie Island using four trapping methods; a) pitfall, b) count, c) litter, and d) sweep. Grey shading indicates the 95% confidence intervals...... 104

Figure 5-4 The number of times each environmental parameter was selected in the best model to describe invertebrate family abundance on Macquarie Island for each trapping method...... 105

Figure 5-5 The mean number of times each environmental parameter was selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe non-native and native invertebrate family abundance on Macquarie Island...... 106

Figure 5-6 The mean number of times each environmental parameter selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe invertebrate family abundance on Macquarie Island according to feeding guild (herbivore, predator, detritivore)...... 107

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Figure 5-7 The mean number of times each environmental parameter was selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe Insecta and non-Insecta family abundance on Macquarie Island...... 108

Figure 5-8 Examples of partial residual plots derived from generalised additive models and illustrating some of the key invertebrate abundance relationships to elevation (m) on Macquarie Island: a) Desidae (pitfall), b) Staphylinidae (count), c) Agriolimacidae (count), d) Agriolimacidae (pitfall). Grey shading indicates the 95% confidence intervals...... 109

Figure 5-9 Examples of partial residual plots generated from generalised additive models and illustrating invertebrate abundance relationships to slope (degree) on Macquarie Island: a) Linyphiidae (pitfall), b) Desidae (count), c) Punctidae (litter), d) Staphylinidae (pitfall). Grey shading indicates the 95% confidence intervals ...... 111

Figure 5-10 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to solar radiation ((Wh/m²) on Macquarie Island: a) Annelida (count), b) Punctidae (litter), c) Linyphiidae (count), d) Australimyzidae (pitfall). Grey shading indicates the 95% confidence intervals ...... 112

Figure 5-11 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to wind speed (kts)on Macquarie Island: a) Australimyzidae (litter) and b) Staphylinidae (count). Grey shading indicates the 95% confidence intervals...... 113

Figure 5-12 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to wetness (index) on Macquarie Island: a) Doliochpodidae (count) and b) Thripidae (sweep). Grey shading indicates the 95% confidence intervals...... 114

Figure 5-13 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to ridge (‘ridgeness’ index as defined by Bricher et al. 2013) on Macquarie Island: a) Aphididae (sweep) and b) Aphididae (litter). Grey shading indicates the 95% confidence intervals...... 115

Figure 5-14 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to vegetation community on Macquarie Island: a) Australimyzidae (sweep), b) Australimyzidae (pitfall), c) Australimyzidae (litter), d) Australimyzidae (count). Grey shading indicates the 95% confidence intervals...... 116

Figure 5-15 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to vegetation on Macquarie Island: a) (count) and b) Thripidae (litter). Grey shading indicates the 95% confidence intervals...... 117

Figure 6-1 Total number of taxa identified and analysed in each status group along the invasion pathway...... 138

Figure 6-2 Variation in (log) maximum body size per status group along the invasion pathway; ‘detected’, ‘transient-alien’, ‘established-alien’, ‘indigenous’ and invertebrates associated with Macquarie Island...... 141

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Figure 6-3 Percentage of winged and wingless in each of the four status groups: ‘Detected’, ‘Transient alien’, ‘Established alien’, and ‘Indigenous’ ...... 142

Figure 6-4 Partial residual plots, from the model of maximum body size (mm) vs vagility, status and their interaction, showing predicted (log) body size for both ‘established’ and ‘not established’ groups and both winged or wingless arthopods. The vertical blue dashes present at the upper and lower margins of the plot represent the number of data points...... 143

Figure 6-5 Partial residual plots, from the model of maximum body size (mm) vs vagility, status and their interaction, showing predicted (log) body size for each status group (Detected –D, Transient – T , Established – E, and Indigenous – I) and both winged and wingless taxa. The vertical blue dashes present at the upper and lower margins of the plot represent the number of data points...... 145

Figure 6-6 The percentage of invertebrates found in eleven guild categories that are either ‘established’ on Macquarie Island or ‘not-established’...... 147

Figure 6-7 Percentage of invertebrates found in status groups along the invasion pathway ‘detected’, ‘transient-aliens’, ‘established-aliens’ and ‘indigenous’ from eleven guild categories...... 148

Figure 6-8 Partial residual plots, from the model of maximum body size (mm) vs establishment status, guild and their interaction, showing predicted (log) body size for the 11 guilds either ‘Established’ and ‘Not established’. A star symbol denotes a statistically significant variation (p< 0.05)……………………………………………………………….149

Figure 6-9 Partial residual plots, from the model of maximum body size (mm) vs establishment status, guild and their interaction, showing predicted (log) body size for the 11 guilds in each of the status groups along the pathway (Detected –D, Transient – T , Established – E, and Indigenous – I). A star symbol denotes a significant variation (p<0.05)...... 150

List of Tables

Table 3-1 Trapping methodology employed during invertebrate sampling studies on Macquarie Island – Watson in 1961 (reported in Watson, 1967), Greenslade in 1986-87 (reported in Greenslade, 1987), Anonymous in 1993-94 (reported in Stevens, et al., 2010), Davies and Melbourne in 1996 (reported in Davies and Melbourne, 1999), Stevens, et al., in 2009-10 (reported in Stevens, et al., 2010)...... 43

Table 3-2 The number of individuals from each Order of invertebrates collected via four different trapping methods on Macquarie Island following mammal eradication: Pitfall traps, sweeping, 20 minute counts, and litter collection in the 2015/16 season following mammal eradication...... 48

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Table 3-3 Abundance of Coleoptera, and Araneae in pitfall traps sampled at seven sites at Macquarie Island in 1986/87 (prior to mammal eradication) and 2015/16 (post- mammal eradication)...... 53

Table 4-1 Percentage of 13 invertebrate orders detected each year through pitfall sampling on Antipodes Island for the three years prior to mouse eradication (2011, 2013, 2016) and one year following eradication in 2018...... 73

Table 4-2 Percentage of the catch for 11 invertebrate orders detected each year through pitfall sampling on Macquarie Island for the three years prior to mammal eradication (1986, 1993, 2009) and the three years following eradication (2015, 2016, 2018)...... 74

Table 5-1 Description of the environmental parameters used in this work, derived from the Digital Elevation Model developed for Macquarie Island by Bricher et al. 2013...... 98

Table 5-2 Environmental parameters explaining invertebrate richness on Macquarie Island, calculated by generalised additive models in R. Yellow highlighting indicates that the associated environmental parameter was selected by the best model for the trapping method tested...... 102

Table 5-3 Invertebrate families identified as indicators of different vegetation communities found at Macquarie Island (via Inval indicator analysis)...... 119

Table 6-1 The status of invertebrates on Macquarie Island and en route to Macquarie Island...... 133

Table 6-2 Classifications used for our guild analyses including incorporated terms from the literature...... 137

Table 6-3 Proportional representation of taxonomic Orders per status group on Macquarie Island...... 139

Table 6-4 Percentage of ‘indigenous’, ‘transient aliens’, ‘established aliens’ and ‘detected’ invertebrates represented by each of the eleven guild categories...... 146

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Thesis Acronyms

AAD – Australian Antarctic Division

AAP – Australian Antarctic Program

AAS – Australian Antarctic Science

AAP – Australian Antarctic Program

AUS - Australia

ANOVA - Analysis Of Variance

CEP – Committee Environmental Protection

DPIPWE – Department of Primary Industries, Parks, Water and the Environment

GAM – Generalised Additive Model

GPS – Global Positioning System

NZ – New Zealand

OTU – Operational Taxonomic Unit

SID – Simpson’s Index of Diversity

SOI – Southern Ocean Islands

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Chapter 1 | Introduction

A global biodiversity crisis is taking place in the twenty-first century. Substantial biodiversity losses as a result of human activity and climate change are driving the sixth mass-extinction event in Earth’s history (Barnosky et al. 2011; Ceballos et al. 2015). Given that islands hold a large proportion of the world’s biodiversity (Courchamp et al. 2003; Kier et al 2009; Keitt et al. 2011; Ewel et al. 2013), with rates of endemism a magnitude higher than for continents (Kier et al. 2009), this crisis has elevated the conservation value of island species and habitats (Kier et al. 2009; McCreless et al. 2016). Island ecosystems are important globally and have their own intrinsic attributes. Many biodiversity hotspots are made up in part or entirely of islands, such as the Caribbean, the Philippines, and New Zealand (Bellard et al. 2014). Island ecosystems have high levels of endemism and are often comprised of simple trophic webs and under-utilised resources (Kier et al. 2009). Island indigenous species have unique evolutionary histories, evolving devoid of ordinary pressures such as competition and predation (Kier et al. 2009; Courchamp et al. 2014; Helmstedlt et al. 2016). Attributes that shape island endemism and biodiversity also make island species particularly vulnerable to external threats such as habitat loss and invasive species (Chapuis et al. 1994; Courchamp et al. 2003; Tershy et al. 2015; Wood et al. 2017). Indeed, the majority of bird, reptile and mammal extinctions have been on islands (Keitt et al. 2011), and 40% of all terrestrial species threatened with extinction are island-based (Tershy et al. 2015). It is clear that island conservation is vital to preserving global terrestrial biodiversity (Courchamp et al. 2003; 2014; Tershy et al. 2015).

In this thesis, I inform ecological understanding and management of high-conservation value islands that have recently undergone invasive mammal eradication. I focus on terrestrial invertebrates - a commonly overlooked group that are rarely at the forefront of island conservation goals, but can be key indicators of environmental change. My thesis evaluates the efficacy of island invasive mammal eradications for invertebrate conservation, which naturally occupy lower trophic levels in the ecosystem. Such knowledge contributes to assessing ecosystem-wide conservation return-on-investment of eradication programs and informs future conservation planning.

1

Island conservation

As a consequence of their range restriction, geographical isolation and limited historical exchange with biota from other islands or mainland regions, island indigenous species are naturally less competitive and less adaptable (Courchamp et al. 2003; Keir et al. 2009). Thus, invasive species are one of the greatest drivers of biodiversity loss and ecosystem disruption on islands (Tershy et al. 2015; McCreless et al. 2016). Invasive mammals are the most widespread group of invasive vertebrates (Towns et al. 2006; Medina et al. 2011; McCreless et al. 2016), being found on more than 80% of the world's major island groups (Aguirre- Muñoz et al. 2008). Rats have invaded more than 80% of all islands (Atkinson 1985) and cats are found on 65 major island groups globally (Atkinson 1989). Mice, rabbits, goats, mustelids, cattle, sheep and pigs have also devastated island flora and fauna, destroyed habitats, driven species to extinction and irreversibly altered ecosystems (e.g. Courchamp et al. 1999; 2003; Campbell and Donlan. 2005; Wanless et al. 2007; Jones et al. 2008; Howald et al. 2010; Headland 2012; Nogales et al. 2013; McCreless et al. 2016). Consequently, the management of invasive mammal species to prevent species and habitat loss is a high priority for island conservation.

Conservation actions on islands are attractive, given biodiversity benefits are considerable and the management of threats is more feasible in their closed, isolated systems (Courchamp et al. 2003; Helmstedt et al. 2015). On the other hand, due to their isolation, conservation actions on islands are often expensive and logistically challenging (Martins et al. 2006; Holmes et al. 2015). Although a range of options are available for managing invasive species (Pysěk and Richardson 2010; Shine et al. 2010), eradications provide the best long-term results, but they are also the most expensive in terms of upfront costs (Pluess et al. 2012a; Helmstedt et al. 2015). Despite this dilemma, in recent years, island eradication attempts – i.e. the complete removal of an invasive species - have increased in frequency and success (Glen et al. 2013; DIISE 2018; Martin and Richardson 2017), with enormous conservation benefit (Zavaleta et al. 2001; Zavaleta 2002; Helmstedlt et al. 2015; Jones et al. 2016). More than 1,200 successful eradications of invasive vertebrates have occurred on islands worldwide (DIISE 2018).

Island conservation via invasive species eradication has evolved into a science. Planning and methods have been refined (Howald et al. 2007; Aguirre-Muῆoz et al. 2008; Gregory et al.

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2014; Elliot et al. 2015; Springer 2016; Horn et al. 2019) and best-practise eradication techniques have been developed together with rapidly evolving technology (Carrion et al. 2006; Morrison et al. 2007; Aguirre-Muῆoz et al. 2008; Broome et al. 2014; Campbell et al. 2015; 2019; Parkes 2019). Factors which influence eradication success or failure have been investigated (Mackay et al. 2007; Pluess et al. 2012a; 2012b), and we can now prioritize island eradication programs for maximum return-on-investment (Brooke et al. 2007; Capizzi et al. 2010; Moore et al. 2010; Myers et al. 2000; Naidoo et al. 2006; Dawson et al. 2015; Helmstedt et al. 2015). Projects are increasingly undertaken on larger islands (Towns and Broome 2003; Innes and Saunders 2011; Russell and Broome 2016; Springer 2016; Martin and Richardson 2017). However, in spite of the proliferation of research around planning and enacting eradications, aside from occasional monitoring of key threatened or charismatic fauna, there remains a lack of published post-eradication monitoring data that quantifies how ecosystems respond once an eradication has occurred (St Clair 2011; Prior et al. 2018; Bird et al. 2019). Conversely, other restoration programs outside protected areas, such as mine site rehabilitations, are regularly evaluated (e.g. Longcore et al. 2003; Smith et al. 2016, Bandyopadhyay and Maiti 2019). Aside from confirming the successful removal of the invader, the outcomes of eradications, and responses of remaining species, are relatively rarely evaluated (Myers et al. 2000; Zavaleta et al. 2001; Reid et al. 2009; Schweizer et al. 2016; Jones et al. 2016; Brooke et al. 2018; Towns 2018). In the absence of post-eradication monitoring research, we are unable to inform ongoing adaptive management, assess the return-on-investment of these costly eradication programs, determine how future programs could be improved, or understand the extent to which they achieve conservation benefits.

Island monitoring and restoration

Eradication techniques have certainly become powerful tools for conservation (Donlan et al. 2003; Towns and Broome 2003; Aguirre-Muñoz et al. 2008; Medina et al. 2011; Spatz et al. 2014; Jones et al. 2016). However, their ‘success’ is often focused on the removal of the target species rather than quantifying the ensuing conservation benefits (St Clair 2011; Prior et al. 2018; Bird et al. 2019). It is challenging to assess conservation benefits by monitoring only threatened or charismatic megafauna such as seabirds, which are often the conservation targets of eradication programs, given that many have relatively long-life spans and respond slowly to change. The immediate answers sought by managers and policy makers as to

3 whether an eradication has been successful for the ecosystem as a whole are not ordinarily derived from monitoring these long-lived species in isolation.

Restoration traditionally refers to returning an ecosystem to its pre-disturbed state (Simberloff 1990). However, even though restoration of invaded islands cannot occur without removal of pest species, their removal is not always sufficient to return the ecosystem to this ideal condition (Atkinson 2001; Mulder et al. 2009; Jones 2010a; Prior et al. 2018). The success of restoration actions greatly depend on the invasion degree of the target species, given invaders have differing impacts on ecosystems depending on the species involved and the structure of the ecosystem (Courchamp et al. 2003; Simberloff et al. 2013; Russell and Kaiser-Bunbury 2019 and references therein). The duration of invasion, as well as the number, strength and nature of interactions between the targeted invasive species and existing species in the ecosystem can drive the recovery of the community following the removal of the target invasive species, but for many cryptic species these interactions remain unquantified. The presence of multiple invaders and/or long-term invaders, even once removed, can leave long-lasting and sometimes permanent changes to ecosystems (Zavaleta et al. 2001; Caut et al. 2009; David et al. 2017; Russell and Kaiser-Bunbury 2019). Local species may take considerable time or possibly never recover to their pre-invasion distribution or function (Caut et al. 2009; Mulder et al. 2009; David et al. 2017). Typically, many island restoration programs rely on passive recovery, i.e. no active management following eradication (Beltran et al. 2014; Kappes and Jones 2014; Russell and Broome 2016), but in some instances active management is required for ecosystem restoration (Atkinson 1988; Simberloff 1990; Jones 2010a). For example, islands with depleted seabird populations due to rodent predation, lack the large marine-derived nutrient input previously provided by seabird manuring, which leads to host of cascading trophic implications for plant nutrients and biomass, soil nutrients, and invertebrate communities (Fukami et al 2006; Towns et al. 2009; Mulder et al. 2009; Wardle et al. 2009; Thoresen et al. 2017). In such circumstances, active augmentation of seabirds may be desirable as a post-eradication management action, in order to achieve the full potential ecosystem benefits (Jones 2010b). Moreover, adverse consequences of the invasive species control itself can impact the ecosystem, such as poisoning of non-target species (Courchamp et al. 2003; Caut et al. 2009). Assumptions that an island ecosystem will naturally recuperate once a pest has been removed can also lead to disastrous consequences and trophic cascades when remaining species released from predation or herbivory interact unexpectedly (Kessler 2001; Zavaleta et al.

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2001; Courchamp et al. 1999; 2003; Caut et al. 2007; 2009). Examples include, the explosion of an exotic vine on Sarigan Island (Northern Mariana Island Archipelago) after the removal of invasive herbivorous goats and pigs that had previously kept it at low levels (Kessler 2001), and the decline in indigenous plant cover on islands in the Kerguelen archipelago following the removal of rabbits as more competitive alien plants increased (Chapuis et al. 2004; 2011).

Identifying criteria for restoration or quantifying restoration success can be ambiguous (Simberloff 1990), given that prior ecosystem knowledge and historical data required to measure a return to baseline are typically lacking (Longcore et al. 2003; Simberloff 1990; Hutcheson et al. 1999; Suding and Leger 2012; Watari et al. 2013; Schweizer et al. 2016). Furthermore, little is generally known at the community level of ecosystems (Suding and Leger 2012), and it is increasingly recognised that novel ecosystems have emerged that differ in function and composition from present and past systems (Hobbs et al. 2009). Ultimately, the extent to which an ecosystem is repaired following eradication, either by passive recovery or active restoration, requires accurate and representative measurements of change (Atkinson 1988; Beltran et al. 2014; Prior et al. 2018; Bird et al. 2019). Research in post-eradication monitoring can inform practise in a funding-poor conservation field, providing clues as to when or if we should monitor, what the most effective and meaningful monitoring strategies are, and how we compensate when data are scarce (Bird et al. 2019). This thesis answers some of these questions, with a particular focus on informing meaningful and effective ways to monitor post-eradication ecosystems to inform both management and operational decision- making associated with future programs.

Invertebrate conservation on islands

While invertebrates comprise more than 90% of animal species on Earth and are critical to the functioning of all global ecosystems, including on islands, they receive far less research and conservation attention than vertebrates and plants (Clark and Mary 2002; Angel et al. 2009; St Clair 2011; Collen et al. 2012; McGeoch et al. 2011; Titley et al. 2017). This is despite the fact that invertebrates are a keystone ecological group, important biological indicators (Kremen et al. 1993; Gerlach et al. 2013), and without them the world’s biospheres would collapse (St Clair, 2011; St Clair et al. 2011; Collen et al. 2012). Furthermore, they provide significant value through their ecosystem services, such as in agricultural production,

5 and have enormous economic significance as a result (Losey and Vaughan 2006; Gerlach et al. 2012). Insects alone, being a single category within the invertebrate group - are estimated to number more than 5.5 million species, but only approximately 1 million species are known and described (Stork 2018). Comprehensive knowledge of their ecology, life history and distribution exists for only the most charismatic, economically important or visible species (Stork 2018). This is despite the fact that over 20% of invertebrate species are threatened with extinction – equal to mammals (Collen et al. 2012). Habitat loss, pollution, pathogens, invasive species, and climate change are the primary human activities responsible for threatening invertebrate species across the planet (New 2008; Robinet and Roques 2010; Gerlach et al. 2012; Lister and Garcia 2018; Sanchez-Bayo and Wyckhuys 2019), but there is little representation of invertebrates in conservation science compared to other animal groups. This bias is reflected in a pervasive taxonomic bias against invertebrates in publications compared to mammals and plants, with only 11% of published literature on invertebrates, even though they comprise 79% of described species (Clark and May 2002). Alarmingly, where it has been undertaken, long-term invertebrate monitoring reveals dramatic declines in the world’s insect species (Conrad et al. 2006; Dirzo et al. 2014; Hallmann et al. 2017; 2019; Lister and Garcia 2018; Sanchez-Bayo and Wyckhuys 2019; Siebold et al. 2019; Wagner 2019), prompting cries of ‘insectaggedon’ in popular media (e.g. Monbiot 2017).

Most known insect extinctions to date come from island communities (Priddell et al. 2003; Gerlach et al. 2012). In the Hawaiian archipelago for example, at least 40 species of insect are known to have been lost (Hilton-Taylor 2000). On islands, invertebrates are critical to ecosystem functioning, speciose, and demonstrate a high degree of endemism (Samways 2010; St Clair 2011; McGeoch et al. 2011). However, although conservation actions on islands give high biodiversity returns (Courchamp et al. 2003; Towns and Broome 2003; Spatz et al. 2014; Helmstedt et al. 2015), typically such actions (such as invasive species management), focus on the protection of threatened, charismatic or iconic species, usually vertebrates such as mammals and birds, and monitoring is tailored accordingly (Samways 2007; Angel et al. 2009, Collen et al. 2012). Conversely, monitoring of invertebrates on islands prior to, or following, conservation actions such as invasive species eradications is comparatively rarely undertaken, or at least rarely reported, rarely accessible or rarely published in English science literature (St Clair 2011; Houghton et al. 2019a).

6

Invertebrates as indicators of island restoration

As eradications on islands have increased in frequency, size, and success, so have calls to better document island recovery (e.g. Jones 2010a, b; St Clair 2011; Russell and Broome 2016; Jones et al. 2016; Towns 2018). However, there is currently no clear framework on how best to do this (Shaw et al. 2011; Watari et al. 2013; although see Bird et al 2019), and the focus remains largely on monitoring threatened vertebrates (e.g. Jones 2010a, b; Buxton et al. 2014; Monks et al. 2014; Le Corre et al. 2015; Croll et al. 2016; Spatz et al. 2017; Brooke et al. 2018).

‘Bioindicators’ - taxa or functional groups that are reflective of broader environmental or trophic changes that can be utilised as tools to assess ecosystem condition. For example, they can be used to assess environmental conditions and perturbations, to identify of specific ecosystem stresses, or reflect broader changes in biodiversity trends (Kremen et al. 1993; Hutcheson et al. 1999; McGeoch 1998, 2007; Towns et al. 2009; Gerlach et al. 2013). Bioindicators can be particularly useful for monitoring the effects of habitat management and the progress of restoration (Towns et al. 2009; Gerlach et al. 2013). Invertebrates, being extraordinarily abundant, diverse and functionally critical, are ideal candidates to measure ecosystem trends, species richness, species turnover and community composition (Kremen et al. 1993; Hutcheson et al. 1999; Bowden et al. 2018). Additionally, their small size =and short life-spans makes them particularly sensitive to local environmental variations (Kremen et al. 1993; Samways et al. 2010; McGeoch et al. 2011; Gerlach et al. 2013; Hein et al. 2019; Bowden et al. 2018). They possess a wide range of attributes that reflect specific ecological variables and environmental conditions, such as body size, growth rate, short generation times, life history strategies and ecological preferences (Clarke 1993; Hutcheson et al. 1999; Niemelä et al. 2000; Kremen et al. 1993; Samways et al. 2010b; McGeoch et al. 2011; Gerlach et al. 2013).

There have been many attempts to identify suitable invertebrate bioindicators to answer environmental, ecological or agricultural questions (e.g. Hansen et al. 2016a; b; Bandyopadhyay and Maiti 2019, and see references in Hutcheson et al. 1999, and Gerlach et al. 2013). Invertebrates have been used to track restoration progress in many contexts (e.g. mine sites - Parmenter and MacMahon 1990, Greenslade and Majer 1993, Andersen & Sparling 1997; forest restoration - Williams 1993, Jansen 1997; prairie recovery - Peters

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1997; dune recovery - Mattoni et al. 2000; quarry site recovery - Wheater et al. 2000). However, in natural and protected areas, biodiversity monitoring, conservation planning and management, invertebrates are often overlooked (McGeoch et al. 2011). Ants are the most widely used bioindicators for assessing conservation activities (Underwood and Fisher 2006), but examples of invertebrate indicators in broad ecosystem assessments remain scarce. In the context of eradications, they have been used to assess the effect of rat invasions on island ecosystems by measuring changes in invertebrate abundance, community composition, trophic complexity, and diversity (e.g. Towns et al. 2009; and St Clair et al. 2011; Thoresen et al 2017). Few have measured their response to invasive mammal removal (although see St Clair et al. 2011 and other examples in St Clair 2011). Fenced ‘islands’ can be created on continents to permit conservation actions such as reintroduction of vulnerable native mammals (e.g. Gibb et al. 2018) or for exclusion of non-native mammals (e.g. Watts et al. 2011; Vergara Parra 2018). However through introduction and dispersal potential of invertebrate and vertebrate fauna, fenced islands allow for different invertebrate population responses than those from traditional islands distant from continental source populations. Bottom-up responses to environmental conditions were found to be a more significant driver of abundance than mammal predation pressure in one such fenced ’island’ in desert Australia (Gibb et al. 2018). Mammal eradication from an enclosure on Maungatautai in New Zealand, lead to dramatic increases in weta (Orthoptera) populations. Also in New Zealand, Vergara Parra (2018) assessed the effects of invasive mammal exclusion on invertebrates in another mainland ‘island’ protected area, but found few significant differences in invertebrate abundance and community composition inside and outside the mammal exclusion fence. This was mostly likely because, in combination, the relatively high numbers of native insectivorous birds and mice (that were never excluded from enclosures), maintained predation pressure on invertebrates within the fenced area.

The reluctant application of invertebrate bioindicators in terrestrial ecosystems has several possible explanations. Firstly, clear definitions of study objectives and careful consideration of the scale of the study are required to deliver reliable results using invertebrate indicators (Underwood and Fisher 2006; McGeoch 1998, Hutcheson et al. 1999; Gerlach et al. 2013), and not all taxa are equally effective as indicators (Kremen et al. 1993; Hutcheson et al. 1999). Multiple indicator taxa are generally required to measure change given the lack of congruency across invertebrate groups (Lovell et al. 2007), and our general knowledge of many invertebrates is scant (Collen et al. 2012). Invertebrate surveys are time-consuming and

8 often considered too difficult, yielding enormous abundance and diversity of species for which few specialists are available to identify (McGeoch 1998; Ward and Larivière 2004). However, there is evidence that in some instances, higher taxonomic levels, such as order or family, or even morphospecies, can be useful surrogates for biodiversity and environmental monitoring (Oliver and Beattie 1996a, b; Driessen and Kirkpatrick 2017; Vergara Parra 2018), particularly where there are only a few abundant species per taxonomic classification and major changes are being evaluated (Driessen and Kirkpatrick 2017).

Invasive species on Southern Ocean Islands

Southern Ocean Islands (SOI) are a series of cool, wet and windy islands spanning the mid- to high latitudes (c. 37˚– 60˚S) that are of exceptional conservation value for several reasons. They host a high proportion of endemic vegetation and invertebrates (Gressit 1970), as well as large concentrations of the world’s seabirds (CEP 2011; de Villiers 2006) and globally significant populations of marine mammals (Woehler et al. 2001). Terrestrial faunal richness is dominated by invertebrates, which are critical to ecosystem function, particularly in relation to their nutrient cycling roles (Smith and Steenkamp 1992a, 1992b; Bergstrom et al. 2006; Smith 2007a, 2007b; 2008; Chown and Convey 2016). Due to their isolation and relatively recent human history (Chown et al. 2005), SOI are also some of the least biologically-invaded terrestrial ecosystems on the planet (Wall 2005; Hughes et al. 2010; Duffy et al. 2017), and are thus relatively pristine, often described as some of the last wildernesses on Earth (Shaw 2013). Moreover, their small size, isolation and limited human activity make these islands ideal locations to monitor the processes of alien invasion (Chown et al. 2008).

The greatest threats to biodiversity of SOI are invasive alien species, climate change and the interactions between them (Chown et al. 2008; Shaw 2013; Chown and Convey 2016). Invasive alien species on SOI include mammals, birds, fish, invertebrates and plants that have either been introduced inadvertently or deliberately transported for farming or food (Frenot et al. 2005; Headland 2012; Chown et al. 2012; McGeoch et al. 2015). These alien species have had devastating impacts on native species and ecosystems on SOI, particularly predatory rodents and cats (Courchamp et al. 2003; Frenot et al. 2005; Shaw 2013; McGeoch et al. 2015; Houghton et al. 2019a). Control and eradications of alien vertebrate species have occurred on SOI, and some species have naturally become extirpated due to unfavourable

9 conditions (Headland 2012). However, alien invertebrate and plant species transfer to the region has increased as human activity has accelerated, and in consequence, isolation is no longer such a limiting factor in the dispersal and spread of new taxa (Frenot et al. 2005; Hughes et al. 2006; Convey et al. 2006b; Chown et al. 2012). The ease with which new introductions establish and spread once expedited to these remote locations (usually via humans), highlights the role remoteness has played in limiting diversity on these islands, rather than any functional redundancy within the recipient ecosystems (Chown and Convey 2016). During only c. 200 years of human contact (Frenot et al. 2005), more than 560 species of alien plants and invertebrates have established on SOI and in the Antarctic region (McGeoch et al. 2015). Almost all of these are found on SOI, with only 11 alien species found in the Antarctic (Houghton et al. 2016). For some SOI, the rate of natural colonisations has been surpassed by human facilitated introductions by more than two orders of magnitude (Gaston et al. 2003; Gremmen and Smith 1999; Pugh 2004). The ameliorating climate in the present-day warming period further reduces environmental hurdles for alien species establishment (Chown et al. 1998; Bergstrom and Chown 1999; Davies and Melbourne 1999; Walther et al. 2009; Shaw et al. 2010; Nielsen and Wall 2013; Chown and Convey 2016).

Their small size and cryptic habits also make invertebrates ideal hitchhikers - hundreds of non-native invertebrates have been inadvertently introduced to SOI (Frenot et al. 2005, Shaw et al. 2010; McGeoch et al. 2015). They comprise the greatest proportion of non-native species in the region (Shaw et al. 2010; McGeoch et al. 2015). They have been found to have substantial impacts on native invertebrates with projected flow-on effects in recipient ecosystems, although these broader changes are largely yet to be quantified (Houghton et al. 2019a). Common non-native invertebrate species include saphrophagous Diptera (Chevrier et al. 1997; Convey et al. 2010), terrestrial Mollusca (e.g. slugs at Marion Island – Smith 1992), phytophagus Lepidoptera (e.g. Plutella xylostella, also at Marion Island - Convey 2005) or predaceous Coleoptera (e.g. Trechisibus antarcticus at South Georgia and Merizodus soledadinus at Kerguelen Island - Ernsting et al. 1995; Convey et al. 2010; Lebouvier et al. 2019). Non-native springtails (Collembola) are recorded as the most abundant across the region (Frenot et al. 2005), but he diversity of non-native terrestrial invertebrates extends to , earthworms, , terrestrial , , parasitic wasps, slugs, spiders, cockroaches, thrips, booklouse, , aphids, springtails, and more (Frenot et al. 2005; Houghton et al. 2019a).

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Biosecurity

The presence of non-native species on SOI is correlated with human activity (Chown et al. 2005), and climate change will lead to increased suitability of SOI for some of the world’s worst invasive species (Duffy et al. 2017). There has been great success in eradicating mammals from SOI (e.g. Springer 2016; Horn et al 2019; Martin and Richardson 2017) and biosecurity screening for non-native mammal stowaways is common and widespread. However, plants and invertebrates are less visible and thus more easily transported inadvertently (Whinam et al. 2005; Chown et al. 2012; Houghton et al. 2016). Invasive invertebrates continually arrive despite modern biosecurity measures being in place (e.g. Lee et al. 2009; Hughes et al. 2010; Chwedorzewska et al. 2013; Houghton et al. 2016; Newman et al. 2018). Invertebrates are transported on ships and planes, in food, building materials, bulk cargo, and in personal effects, sometimes in high numbers (Hughes et al. 2010; Chwedorzewska et al. 2013; Houghton et al. 2016; Newman et al. 2018). Many non-native invertebrates arrive alive at the SOI destination (Chwedorzewska et al. 2013; Houghton et al. 2016), their small size and cryptic habits making them difficult to detect and contain. Conversely, many species do not survive the journey, or will arrive alive but do not survive to establish a colony. Yet once established, in spite of their potential impact on SOI ecosystems and native invertebrates, non-native invertebrates are exceptionally difficult to eradicate, particularly on these isolated islands. Indeed, invertebrate eradications are generally uncommon, regardless of context, and there is no documented successful invertebrate eradication on SOI to date, although an attempt is currently underway on Marion Island (Greve et al. 2017). With this background in mind, it is clear that improving biosecurity at ports of departure, is the most logical, effective and economical option to managing invasions of non-native invertebrates on SOI.

Clearly, prevention of new invasive species arrivals is critical to protecting the high conservation values of SOI. Moreover, the distance of SOI and the Antarctic from continental ports provides a unique opportunity to treat and manage movement of biological invaders to prevent their establishment. Departing cargo often undergoes rigorous biosecurity screening, for example at Hobart, Tasmania, on behalf of the Australian Antarctic Program (Bergstrom and Shaw 2016; Bergstrom et al. 2017), but improving national biosecurity centres servicing SOI and the Antarctic region through targeted measures for high-risk taxa are considered essential (CEP 2011; McGeoch et al. 2015; Newman et al. 2018). For a group as ubiquitous

11 and diverse as invertebrates however, how can the establishment risk of species or groups being transported be identified? For some time, researchers have tested the utility of various species traits as proxies for more complex and difficult-to-measure physiological and life history traits, and also as indicators of potential invasive success (e.g. Mondor et al. 2006; Peacock 2008; Chown 2012; Capellini et al. 2015; Mathakutha et al. 2019). There has been much debate on this topic, but few generalities have emerged. Trait-based invasion theory for plants is well-explored (e.g. Pyšek 1998; Whitney et al. 2008; Van Kleunen et al. 2010a, b; Parker et al. 2013; Su et al. 2013; Funk et al. 2017), but for invasive invertebrates, being more mobile than plants, measuring traits is inherently more difficult. A detailed review of the species traits explored for their links to invasion success is found in Chapter 6 of this thesis, including some studies that have linked select traits to fitness and competitive advantages on SOI (Frenot 1992; Frenot et al. 2005; Convey 1996a, 1996b; 1997; Convey et al. 2006a; Hullé et al. 2010; Lebouvier et al. 2011; Hughes et al. 2019). However, despite recommendations to identify high-risk taxa to inform targeted biosecurity in the region, no study has yet tested trait-based invasion theories for the broad suite of invertebrates being transported.

Thesis structure

The broad objectives of the research outlined in this thesis are to i) assess our understanding of native invertebrate interactions with non-native species on islands, ii) improve our understanding of invertebrate responses to mammal eradication on islands, and ii) test a trait- based analysis of invertebrate invaders. By studying the lower trophic levels of a changing ecosystem via invertebrate monitoring, we can better understand what underpins broader ecosystem responses, in turn facilitating an assessment of the conservation benefit of invasive species control. Ultimately, this knowledge can inform decision-making around island conservation, management and restoration. This research is undertaken on sub-Antarctic Islands of Australia and New Zealand that have recently undergone mammal eradications.

Islands in the Southern Ocean Island biogeographic zone (Shaw et al. 2010), are relatively well-studied for invertebrates, which are the main terrestrial fauna. However, despite hundreds of non-native vertebrate, plant and invertebrate species introductions across the region (Headland 2012; McGeoch et al. 2015), the impacts they have on the invertebrates are inconsistently known. In Chapter 2, I review the breadth of existing research around non-

12 native species impacts on the invertebrates of Southern Ocean Islands. I identify knowledge gaps and research biases across taxonomic groups and islands.

In Chapter 3, I assess and identify trapping methodology and the utility of historic data for tracking ecosystem change on Macquarie Island (a Southern Ocean Island), following eradication of rabbits, rats and mice. I conduct a post-eradication field survey for invertebrates, replicating where possible the sites and techniques used by historical invertebrate surveys. Replicating historical survey designs maximised the utility of their data for detecting invertebrate community fluctuations over time corresponding to habitat changes and invasive mammal eradication. I explore both the effectiveness of trapping techniques in different habitats on Macquarie Island and the effectiveness of different taxonomic groups in tracking change over time in a range of habitats in relation to rodent and rabbit pressure. I use the results of this methodological investigation to inform additional post-eradication invertebrate surveys that I included in other aspects of this thesis.

To investigate the impact of vertebrate eradication on invertebrates, in Chapter 4 I undertake post-eradication surveys and processed field samples from two Southern Ocean Islands that have recently undergone mammal eradication - Antipodes Island in the New Zealand subantarctic for mice and Australian subantarctic Macquarie Island for rabbits, rats and mice. These Southern Ocean Islands share ecological and biogeographic similarities, and for both islands we have detailed knowledge of the invertebrate fauna and historical invertebrate sampling prior to mammal eradications. I identify invertebrates trapped prior to and post mammal eradications on both islands. I use order level analysis of richness, diversity and abundance to quantify structural change in invertebrate communities. I then discuss the implications of the observed (different) responses on the two islands for monitoring post- eradication ecosystem change.

In Chapter 5, I delve deeper into the varying responses of invertebrates detected in Chapter 4. To do this I undertake a detailed assessment of the drivers of abundance, richness and diversity for each taxonomic family on Macquarie Island, using both abiotic variables such as elevation and wetness, and biotic variables such as vegetation and non-native species interactions. With this information, I gain insight into the key explanatory variables that drive invertebrate responses to eradication of mammals, and the role of non-native invertebrate species in shaping novel post-eradication ecosystems.

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Biosecurity is vital to the island’s post mammal eradication restoration and ongoing protection and can be improved by identifying invertebrates with high establishment risk. Determining the traits of invasive, established and native invertebrates, and how they differ, is a critical element to this process. In Chapter 6, I compare traits of the suite of invertebrates being introduced to Macquarie Island through the Australian Antarctic Program (but not yet established), with those that are non-native and established on the island, and native species. I use these findings to identify invertebrate traits that are linked to transportation and those which are most strongly linked to establishment. Importantly, I also identify groups of invertebrates that have high establishment risk. I highlight weaknesses in existing biosecurity screening and identify areas for improvement. This research has direct application in improving biosecurity surveillance practises across Antarctic National Programs.

In Chapter 7, the general discussion, I draw on the findings of the five previous chapters to discuss themes that emerge from this thesis as a whole in the context of limitations encountered by this research and with consideration to future research directions.

Note: All data chapters within this thesis have been prepared as independent, self-contained manuscripts for publication. Chapter 2 and 3 have been published in peer-reviewed publications – Chapter 2 a journal and Chapter 3 for special publication for the International Union for the Conservation of Nature – see individual chapters for details. Chapter 4, 5 and 6 are yet to be submitted to peer-reviewed journals.

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Chapter 2 | The impacts of non-native species on the invertebrates of Southern Ocean islands

Houghton, MJ., Terauds, A., Merritt, D. Driessen, M., and Shaw, JD. (2019) Journal of Insect Conservation 23: 435. https://doi.org/10.1007/s10841-019-00147-9

This chapter was researched and written by MJH, with editorial advice from all authors. MJH, JDS and DM conceived the idea. MJH undertook the literature meta-analysis and interpretation.

ABSTRACT

Isolation and climate have protected Southern Ocean Islands from non-native species. Relatively recent introductions have had wide-ranging, sometimes devastating, impacts across a range of species and ecosystems, including invertebrates, which are the main terrestrial fauna. In our comprehensive review, we found that despite the high abundance of non-native plants across the region, their impacts on native invertebrates are not well-studied and remain largely unknown. We highlight that non-native invertebrates are numerous and continue to arrive. Their impacts are multi-directional, including changing nutrient cycling regimes, establishing new functional guilds, out-competing native species, and mutually assisting spread of other non-native species. Non-native herbivorous and omnivorous vertebrates have caused declines in invertebrate habitat, but data that quantifies implications for invertebrates are rare. Predatory mammals not only indirectly effect invertebrates through predation of ecosystem engineers such as seabirds, but also directly shape community assemblages through invertebrate diet preferences and size-selective feeding. We found that research bias is not only skewed towards investigating impacts of mice, but is also focused more intensely on some islands, such as Marion Island, and towards some taxa, such as beetles and moths. The results of our review supports and build on previous assessments of non-native species in the Antarctic region - that the responses of invertebrate fauna on these islands are under-reported and often poorly understood. Given the importance of invertebrates as indicators of environmental change, and their potential utility in quantifying change associated with island restoration projects (such as eradications), these knowledge gaps need to be urgently addressed.

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INTRODUCTION

Invasive species are the greatest driver of global biodiversity loss and ecosystem disruption on islands (Mack et al. 2000; McCreless et al. 2016). Although islands comprise only 5% of the world’s landmass, their level of endemism is a magnitude higher than for continents, and many global biodiversity hotspots are islands and archipelagos (Keir et al 2009; Bellard et al. 2014; Courchamp et al. 2014). Thus, island ecosystems have proportionally high biodiversity, and often host näive indigenous species that lack competitive traits and are highly adapted (Bowen and van Vuren 1997; Convey et al. 2006a; Smith 2007).

Sub-Antarctic and cool-temperate islands of the Southern Ocean are some of the most remote environments in the world, yet their ecosystems are susceptible to invasion by non-native species (Frenot et al. 2005; Convey et al. 2006b; Shaw 2013; McGeoch et al. 2015). Low temperature, remoteness and associated low human visitation to these islands have historically been an important limiting factor in the establishment of non-native species (Smith and Steenkamp 1990; Chown et al. 1998, 2005; Gabriel et al. 2001). However, increasing human visitation has intensified opportunities for new introductions (Whinam et al. 2005; Convey et al. 2006b; Chown et al. 2012), and relatively recent climatic changes are likely to further reduce physical barriers to invasion and enhance colonisation success (Walther et al. 2009; Janion et al. 2010; Chown and Convey 2016; Laparie and Renault 2016). The relatively simple ecosystems found on Southern Ocean islands (SOI) provide a unique opportunity to understand the processes of colonisation, establishment and impacts of non-native species.

Most of the 560 non-native species documented for the Antarctic and Southern Ocean region are established on SOI (McGeoch et al. 2015). The majority are plants and invertebrates inadvertently introduced through human activity (Frenot et al. 2005). Although some non- native invertebrates and plant species have been studied individually (e.g. Convey et al. 2010; Laparie et al. 2010; Williams et al. 2016), their broader ecosystem impacts remain largely unknown. Vertebrates such as house mice (Mus musculus), black rats (Rattus rattus) and brown rats (Rattus norvegicus) were introduced unintentionally, but others such as rabbits (Oryctolagus cuniculus), cats (Felis catus), sheep (Ovis aries), mouflon (Ovis ammon musiman), cattle (Bos Taurus), goats (Capra hircus), pigs (Sus Scrofa), reindeer (Rangifer tarandus), weka (Gallirallus australis), and trout (Salmo trutta) were purposefully released

16 as companions, food or game (Headland 2012; McGeoch et al. 2015). As has occurred globally, non-native mammals have transformed SOI ecosystems through habitat destruction, causing extinctions and altering ecosystem processes (e.g. Courchamp et al. 2003; Campbell and Donlan 2005; Frenot et al. 2005; Wanless et al. 2007; Jones et al. 2008; Nogales et al. 2013; McGeoch et al. 2015; McCreless et al. 2016; Brooke et al. 2018).

The impact of species invasions on islands has typically been determined through monitoring the responses of iconic or charismatic species, like albatrosses (Towns et al. 2006; Towns 2009; Angel et al. 2009; St. Clair 2011; Jones et al. 2016). On SOI, this translates to extensive research on the impacts of non-native vertebrates on seabirds and vegetation (e.g. Copson and Whinam 1998; Cuthbert and Hilton 2004; Scott and Kirkpatrick 2008). Impacts on invertebrates have been less comprehensively studied. This is despite the fact that invertebrates comprise most of the terrestrial fauna on SOI and perform a variety of critical ecosystem functions such as soil nutrient cycling (Convey et al. 2006a; Smith 2008; Chown and Convey 2016). In consequence, their suppression or extinction by invasive species has a range of important implications (Fukami et al. 2006; St Clair 2011; Collen et al. 2012). Furthermore, because of their diversity, invertebrates are important biological indicators of environmental change, and can be useful for conservation planning and monitoring (Kremen et al. 1993; Gerlach et al. 2013). Comprehensive understanding of the interactions between invasive species and invertebrates is therefore critical for future SOI conservation and management (Chown et al. 2008). Non-native vertebrates, invertebrates and plants threaten native SOI invertebrates through predation, competition, and loss of habitat, but our understanding of these interactions is limited compared to other threatened taxa (McGeoch et al. 2015). Here we review the current state of knowledge of non-native species interactions with, and impacts on, native invertebrates on SOI and discuss the consequences and ramifications these ecosystems.

Terminology

Greenslade and Convey (2012) outline terminology around invasive species that we follow here, including for the terms ‘invasive’, ‘introduced’, ‘exotic’, ‘naturalised’, ’native’, and ‘endemic’. Taxa that we refer to as ’non-native’ are synonymous with ‘introduced’ in Greenslade and Convey (2012), and are those which have clearly been transported to a novel locality, directly or indirectly, by human activities. Taxa that we refer to as ‘invasive’ are

17 those that have followed the invasion pathway, i.e. they been introduced to a new location, colonised, reproduced and spread, causing disruption to the pre-existing ecosystem (Williamson and Fitter 1996).

THE STUDY AREA

Southern Ocean Islands

Southern Ocean Islands (SOI) comprise a series of relatively small, isolated, oceanic islands and archipelagos located on either side of the Antarctic Polar Frontal Zone (APFZ) between 37⁰S and 55⁰S (Figure 2-1) (Shaw 2013). They are known for their cool, wet, windy but equable climates (Bergstrom and Chown 1999; Huiskes et al. 2006; Pendlebury and Barnes- Keoghan 2007). Almost all are designated as protected areas (Shaw 2013). Despite similarities in their contemporary climate, SOI have significantly different climatic histories, glaciations, geological origins and ages that have influenced natural (i.e. not mediated by humans) colonisation by terrestrial biota, speciation, and species turnover (Bergstrom and Chown 1999; Shaw et al. 2010; Shaw 2013). Most SOI have no resident human settlements (except for the Falkland Islands and Tristan da Cunha), but some island groups are visited by tourists, and most are either regularly visited by research expeditions or have permanent research stations (de Villiers et al. 2006).

Ecosystems

A significant component of the fauna of Southern Ocean islands are the millions of marine mammals and seabirds, across numerous species, which live and breed on them (Shirahai 2007). There are no native amphibians, reptiles or terrestrial mammals, and very few land- based birds (Bergstrom and Chown 1999; Convey 2007). Compared to continental ecosystems, terrestrial ecosystems on SOI are relatively simple, characterised by non-utilized ecological resources and unrepresented functional groups (Whinam et al. 2005; Convey et al. 2006a). Although levels of endemism are high (Chown and Convey 2016), species diversity is generally low, and many taxonomic and functional groups typically found at lower latitudes are absent (Block 1984; Convey and Lebouvier 2009). A lack of functional redundancy is linked to a higher likelihood of establishment by exotic species, given that new arrivals may experience little competitive resistance (Frenot et al. 2005; Convey et al. 2006b).

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Figure 2-1 Map of the biogeographic region referred to as the Southern Ocean Islands, between 37˚S and 55˚S

Low temperatures and numerous but relatively inefficient invertebrate detritivores mean that organic decay is generally slow (Tréhen et al. 1990; Smith 2008), resulting in ‘bottlenecks’ in available nutrients (Slabber and Chown 2002). Across the region, vegetation communities are dominated by grasslands, herbfields (including ) and are characteristically devoid of trees. High altitude areas support feldmark communities populated by cushion plants and bryophytes (Greenslade 2006; Convey 2007; Bergstrom et al. 2006). The absence of native

19 herbivores means that vegetation is generally vulnerable to grazing by non-native herbivorous mammals due to a lack of defences and high palatability (Bowen and van Vuren 1997; Courchamp et al. 1999; Chapuis et al. 2004; Hullé 2012).

Invertebrate assemblages are characterised by few herbivores or predators and a high number of decomposers (Smith and Steenkamp 1990; Vernon et al. 1998). Typically, assemblages feature adversity or stress selection traits (Crafford et al. 1986; Convey 1996a, 1996b, 1997; Chown 2001) such as low reproductive investment, limited competitive and dispersal abilities, investment in stress tolerance (Chown and Convey 2016) and unusually long life cycles (Haupt et al. 2014). The most abundant native invertebrate groups are mites (Acarina) and springtails (Collembola) (Chown and Convey 2016). Flies (Diptera) and beetles (Coleoptera) are the most common insects in the region (Chown and Convey 2016). Other abundant native groups are Araneae (spiders), Lepidoptera (moths), enchytraeids, earthworms, tardigrades, and nematodes (Convey 2007; Chown and Convey 2016). Flightlessness is unusually common (Roff 1990). Given there are very few large, native predators of invertebrates on SOI, the ecology of native invertebrate communities is unlikely to include adaptations to predation pressure (Convey and Lebouvier 2009).

Biogeography

Consistent low levels of immigration from nearby continents have shaped the terrestrial environments of older SOI with continental origins (Chown et al. 1998; Bergstrom and Chown 1999), as per classic island biogeography theory (Macarthur and Wilson 1967). Informative examples are the Falkland Islands and Auckland Island group. For the majority of SOI, which are typically more isolated, younger, volcanic islands, the origin of most biota remains largely unknown (Bergstrom and Chown 1999). Natural colonisation and dispersal in the region occurs broadly via wind, air, water or with assistance from vectors such as animals, birds or marine debris (Gressit 1970; Barnes et al. 2006; Hughes et al. 2006; Moon et al. 2017). Native insect and species richness are linked, but principally explained by island isolation and temperature (Chown et al. 1998; Leihy et al. 2018). Native vascular plant species richness varies widely across SOI, ranging from 180 species on Auckland Island and one species on Bounty Island, but some inter-regional similarities are apparent (Leihy et al. 2018). Native insect assemblages are more similar between island groups close to each other (Greve et al. 2005; Shaw et al. 2010; Leihy et al. 2018), but

20 richness is highly variable across the region - with as few as six species on MacDonald Island to over 230 on Auckland Island (Chown et al. 1998; Bergstrom and Chown 1999; Chown and Convey 2016). For SOI invertebrates other than insects (e.g. springtails, mites, and spiders), drivers of diversity and distribution are less well known, largely due to imbalanced survey effort and lack of data for many island groups (Chown et al. 1998, 2008). Repeated surveys of some islands reveal incremental increases in diversity over time, likely due to increased search effort in new habitats and documentation of more cryptic species (e.g. Jones et al. 2003c; Green and Mound 1994; Grobler et al. 2011a; 2011b). Non-native species invertebrate richness on SOI is strongly correlated with native species richness, energy availability, island temperature and area, and the frequency of human visitation (Chown et al. 1998, 2005).

Climate and invasive species

Climate change is occurring across the region (Pendlebury and Barnes Keoghan 2007; Le Roux 2008; Bergstrom et al. 2015). At some locations, warming is occurring rapidly, at more than twice the mean global rate (Le Roux 2008). Warming increases the likelihood of non- native species establishment (Gabriel et al. 2001; Janion et al. 2010; Chown and Convey 2016; Laparie and Renault 2016), while also putting pressure on native species (van der Merwe et al. 1997). Duffy et al. (2017) modelled the future climatic suitability for some of the world’s most invasive species to SOI and the Antarctic region. They found all SOI suitable and at invasion risk under future climate scenarios, particularly Macquarie Island and the New Zealand sub-Antarctic islands. Many non-native species are generally more adaptable (Duffy et al. 2017) and have broader climatic tolerance (Chown et al. 2002; Janion et al. 2010), than native species that are cool-climate adapted and vulnerable to increasing thermal conditions (Convey 1996a, 1996b, 1997; van der Merwe et al 1997). Even if invertebrates that are non-native to SOI originate from a cool region, their competitive advantage in a warming climate is amplified (Lebouvier et al. 2011; Laparie and Renault 2016). Thus, native invertebrate species on SOI are likely to be disadvantaged and outcompeted with rapid climate change (Chown et al. 2004; McGeoch et al. 2006; Duffy et al. 2017).

Concurrently, accidental transport of non-native species has increased as human activity in the region has escalated (Frenot et al. 2005; Convey et al. 2006b; Hughes et al. 2006; Chown et al. 2012; McGeoch et al. 2015; Duffy et al. 2017). Already for some SOI, the rate of

21 natural colonisations has been surpassed by human-facilitated introductions. On Gough Island, the rate of non-native invertebrate establishment is 2-3 orders of magnitude in excess of the natural rate (Gaston et al. 2003), and for Iles Crozet and Kerguelen 3-4 orders of magnitude for plant and invertebrate species respectively (Frenot et al. 2001, 2008; Lebouvier and Frenot 2007).

LITERATURE SEARCH

Our primary objective was to determine how invasions on SOI impact native invertebrates. Therefore, we conducted a literature search in Web of Science using the terms “invertebrate*”, “insect*”, “non-native”, “impact” and “invasive” and three groups of invertebrates widespread on SOI “Diptera”, “Coleoptera” and “Lepidoptera”, searching each term individually but paired with each of one of the 32 named Southern Ocean islands (between 37˚S and 55˚S) (e.g. “Campbell Island”, “ Macquarie Island”, “ Prince Edward Island” etc.), adding “Antarctic” to focus the search where necessary (e.g. where multiple islands of the same name exist). The reference lists of all relevant publications were further examined to identify other relevant publications. The titles and abstracts of these papers were viewed and 45 publications were identified that measure, through experiment or observation, impacts of invasive species on invertebrates on SOI. By island group, the break down was: Marion Island (18 - including three also investigating ), South Georgia (8), the Kerguelen archipelago (6), Antipodes Island and Bollons Islands (4), Auckland Island (3), Macquarie Island (3), Gough Island (2), and Falkland Islands (1). Impacts were identified for taxa from 11 higher groups of invertebrates. Of the papers examined the most studied taxa were: Coleoptera (21 times), Lepidoptera (19), and Annelidae (10), followed by Araneae (9), Diptera (7), Amphipoda (4), Collembola (4), Hemiptera (3), Orthoptera (1), Mollusca (1) and Chilopoda (1). Many studies did not specifically identify which invertebrate groups were impacted, rather discussing indirect effects through changes to vegetative or soil habitat. In these cases, the impact group was identified as ‘Unspecified’. Twenty studies identified impacts on invertebrates from predators (14 of these relating to mice alone, one on mice and rats, two on mice and cats, and four focussing on either, or both, brown and black rats), 17 invasive invertebrate papers, three invasive plant papers, two invasive omnivore papers, and one study which explicitly tested the impacts of herbivores on invertebrate communities. A summary of these papers is presented in Appendix 1, Table 1. This table underpins our review of invasive species impacts on native invertebrates on SOI.

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NON-NATIVE SPECIES IMPACTS ON NATIVE INVERTEBRATES

Non-native plants

More than 250 non-native plant species, mostly grasses and small herbs, have established across the SOI (Shaw 2013). Despite the relatively high number and diversity of non-native plants across the region, making up a substantial component of vascular plant species and altering habitat (Frenot et al. 2001; Jones et al. 2003b; Le Roux et al. 2013), their impacts are generally considered to be relatively minor (e.g. Frenot et al. 2005). This assumption may well be a product of limited investigation (Le Roux et al. 2013) as very few studies have investigated SOI invertebrate and non-native plant interactions (Appendix 1, Table 1).

There is compelling evidence that habitat quality and composition strongly influence invertebrate assemblages and species richness on SOI (Crafford and Scholtz 1987; Davies and Melbourne 1999; Barendse et al. 2002; Terauds et al. 2011; Errington et al. 2018). Often, specific plants or communities provide habitat and food for native SOI invertebrates (e.g. Hugo et al. 2004, 2006; Nyakatya and McGeoch 2008; Phiri et al. 2009; Greenslade et al. 2011). Some endemic plants are particularly important– for example Azorella selago cushions act as climatically benign, resource-rich refuges and support diverse invertebrate communities (Barendse and Chown 2001; Hugo et al. 2004). Habitat specificity by invertebrate fauna on SOI is identified by some studies (e.g. earthworms and flies - Tréhen et al. 1985; and spiders – Davies 1973; Davies et al. 2011). Others show that many taxa demonstrate broad habitat tolerances (Burger 1985; Gressit 1971; Convey at el. 1999; Hänel and Chown 1998; Greenslade 2006).

The effect of non-native plants on insect assemblages varies among taxa (Gremmen et al. 1998 and references therein), but they can greatly reduce local invertebrate diversity (Gremmen et al. 1998, 2001). Gremmen et al. (1998) described impacts on both overall insect species composition and individual species population densities of micro-invertebrates and soil macroinvertebrates due to the increasingly dominant non-native grass Agrostis stolonifera on Marion Island. They showed that up to 30% of native invertebrate species were absent from drainage areas dominated by A. stolonifera, and that enchytraeid worm biomass declined in these areas. Only one other study (Chown and Block 1997) tested and demonstrated detrimental effects of non-native plant species on invertebrates on SOI. This

23 study demonstrated that the poorer nutrition absorption potential of the invasive Poa annua compared to native grasses affected the foraging dynamics of the native herbivorous beetle Hydromedion sparsutum on South Georgia, with implications for its body size and fitness. P. annua is the most widespread weed in the region (McGeoch et al. 2015). Despite the paucity of published data on the effect of P. annua on invertebrates from other SOI, detrimental effects on invertebrate taxa or communities are expected, especially where disturbance and grazing pressure by mammalian herbivores has encouraged spread of the grass (e.g. Macquarie Island, Scott and Kirkpatrick 2008, 2013).

The extent of impacts due to non-native plants on SOI may take some time to be realised due to complicated interactions with native and non-native plants and invertebrates, and associated lag times. For example, mutually beneficial relationships can form between non- native plants and non-native invertebrates, including mutually-assisted dispersal (Barnes et al. 2006). Very few native plants on SOI are insect-pollinated – a consequence of the lack of native pollinating insect fauna (Convey et al. 2006a) and reflected in plant floral structures (Shrestha et al. 2016). Thus, the establishment of pollinating insects such as the Eristalis croceimaculata and the blowfly Calliphora vicina on South Georgia, represent a novel ecological guild, aiding the seed set and dispersal of currently-localised non-native plants such as dandelions (Taraxacum officinale) that require pollination (Convey et al. 2010). Moreover, the dandelions themselves are likely to have facilitated the spread of these pollinating flies (Convey et al. 2010). Several other non-native plants on South Georgia have, until recently, also lacked suitable pollinators (Barnes et al. 2006). In time, native plants on SOI may be outcompeted by non-native insect-pollinated plants (Frenot et al. 2005, 2008) as new species of insect pollinators become established (Convey et al. 2010). Invertebrate communities on SOI reliant on this native vegetation could be impacted, but it is yet to be tested.

Non-native invertebrates

Non-native invertebrates on the SOI include flatworms, earthworms, moths, terrestrial crustaceans, predatory carabid beetles, parasitic wasps, slugs, isopods, spiders, booklouse, flies, aphids, springtails, mites and more (Frenot et al. 2005). The non-native insects total more than 180 species across the region (McGeoch et al. 2015). Most species are from families that include well-documented pest species worldwide – e.g. Thripidae, Aphididae,

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Noctuidae and (Annecke and Moran 1982; Roques et al. 2009). However, the composition of non-native species can vary between islands - for example, non-native springtails comprise 38% of the introduced fauna on Marion, compared to 10% on South Georgia (Frenot et al. 2005). On some islands, non-native invertebrates represent the majority of terrestrial species – 60% on the Kerguelen archipelago (Frenot et al. 2005), and 70% on Gough Island (Jones et al. 2003b).

A small number of introduced invertebrates are considered invasive on SOI, with the majority regarded as ‘persistent’ (i.e. not expanding their range) and/or synanthropic (i.e. occurring in and/around research stations alongside humans) (Frenot et al. 2005; Greenslade 2006; Convey et al. 2011). Some have naturalised with little apparent impact (Frenot et al. 2005), although this may change over time due to potential changes in temperature, nutrient availability and water availability (Crooks et al. 1999; Nielsen and Wall 2013). Non-native invertebrates can change status from transient, persistent or synanthropic to invasive if environmental circumstances change in their favour (Chown and Avenant 1992; Chown and Language 1994; Bergstrom and Chown 1999, Frenot et al. 2005; Lebouvier et al. 2011). For example on Marion Island, the establishment of the diamond-back , Plutella xylostella, a globally significant crucifer crop pest (Crafford and Chown 1990), is thought due to recent warming in the region (Chown and Avenant 1992). Similarly, the blowfly Calliphora vicina, repeatedly arrived but did not establish at Kerguelen Island until a temperature threshold was reached in the early 1970s, facilitating the completion of its life cycle, followed by a rapid increase in range (Lebouvier et al. 2011). C. vicina and the hoverfly Eristalis croceimaculata larvae are macrodetrivores. Their activity intensifies nutrient cycling naturally performed by microarthropod soil fauna and native insects, thereby altering soil nutrient availability and decomposition dynamics (Convey et al. 2010). Native flies on South Georgia such as Paractora trichosterna are likely outcompeted (Convey et al. 2010), as has occurred on Kerguelen due to C. vicina invasion (Laparie et al. 2010). There are relatively few naturally occurring invertebrate herbivores on SOI (Vernon et al. 1998). Thus, non-native aphids found at the Kerguelen archipelago that are sap-feeders, a guild nearly vacant on these islands, capitalise on plant resources previously unutilized (Hullé et al. 2010). At least one species, Myzus ascalonicus, occurs in colonies 2-7 larger on native plants than on non-native host plants (Hullé 2012).The parasitic wasp Aphidius matricariae (an aphid parasite), is the only kind species of this guild in the Marion Island ecosystem, and has rapidly expanded its range since its introduction in 2001 (likely by a single gravid female – Lee et al. 2007). Its

25 colonisation and spread is facilitated by an established non-native aphid (Lee and Chown 2016). Non-native, predatory carabid ground beetles on South Georgia Island and Kerguelen Island (Trechisibus antarcticus and Merizodus soledadinus), occupy a novel guild as arthropod predators (Ernsting et al. 1995, 1999; Chevrier et al. 1997; Laparie et al. 2010, Lebouvier et al. 2011). Through predation, T. antarcticus and M. soledadinus have reduced the abundance and increased the adult body size of the endemic herbivorous beetle Hydromedion sparsutum on South Georgia Island (Ernsting et al. 1995). Larger adult body sizes in H. sparsutum increased as predation of juveniles by the invasive carabids increased, a direct response of both selection by the predator in favour of larvae with rapid growth rate and reduced competition for high-quality food for the survivors (Ernsting et al. 1995). Across the Kerguelen archipelago, M. soledadinus has steadily increased its dominance in arthropod communities. It lacks competitors as it is the only predatory insect species (Frenot et al. 2005; Laparie et al. 2010). Since the 1990s, it has expanded its range from the introduction site to remote locations (including other islands in the archipelago) at an accelerating rate of colonisation (Chevrier et al.1997; Lebouvier et al. 2019), and dramatically increased in abundance (Laparie et al. 2010; Lebouvier et al. 2019). M. soledadinus invasion has led to the near disappearance of its preferred prey, the native wingless flies Anatalanta aptera (Diptera: ) and Calycopteryz moseleyi (Diptera: ) in some areas (Laparie et al. 2010; Lebouvier et al. 2011). In contrast, M. soledadinus on South Georgia only colonises a limited area (Ernsting 1993), is found in lower abundance, and has a much reduced rate of expansion (Brandjes et al. 1999), probably due to cooler annual temperatures than the Kerguelen Archipelago (Lebouvier et al. 2011).

Non-native soil invertebrates compete directly with native species and alter nutrient turnover in soils (Hänel and Chown 1998; Smith 2007; Smith and Steenkamp 1990, 1992a, 1992b; Greenslade et al. 2008). Through competition and/or predation, invasive species can eventually lead to a decline in abundance or local extinction of native species that may play major roles in organic material decomposition (Greenslade et al. 2007; Convey et al. 2011). For example, on Gough Island, the only indigenous terrestrial isopod, Styloniscus australis, is abundant only in upland sites where the non-native terrestrial isopod Porcellio scaber is rare, and is rare where P. scaber is abundant in the lowlands (Jones et al. 2003b). Some of the non- native fauna on Gough Island, including worms (Ogliochaeta), P. scaber and a millipede, are the most abundant on the island (Jones et al. 2003b). The long-term effect of such a large biomass of macro-detritivores on Gough Island, in a system naturally lacking such species, is

26 likely to considerably speed up organic nutrient cycling, affecting peat formation, and substantially changing floral and faunal assemblages (Jones et al. 2002, 2003b; Reynolds et al. 2002; Smith 2007, 2008). On Tristan da Cunha, introduced millipedes and earthworms may similarly be impacting soil types, as native litter-decomposing invertebrates are relatively few (Holdgate 1966). Detritivores on Marion Island, including the European slug Deroceras panormitanum (also herbivorous), the chironomid midge Limnophyes minimus and P. scaber, also process considerable quantities of litter in competition with native species, and substantially alter nutrient turnover (Smith and Steenkamp 1992b; Hänel and Chown 1998; Slabber and Chown 2002; Smith 2008). L. minimus is estimated to ingest litter at a rate that is an order of magnitude more than that consumed by the endemic flightless moth larvae Pringleophaga marioni, the primary native detritivore on the island (Hänel and Chown 1998). The relatively slow rate of litter processing by this native species is thought to represent a nutrient-cycling bottleneck that once released by non-native macro-detritivores will have implications for primary productivity and peat formation in the island’s ecosystem (Smith and Steenkamp 1990; Hänel and Chown 1998; Jones et al. 2003c). The non-native slugs greatly exacerbate rates of nutrient mineralisation from litter and ratios of C:N and N:P released are different than for the native caterpillars on Marion Island (Smith and Steenkamp 1992a, 1992b). This also ultimately affects peat nutrient quality, decomposition rates and primary production, which are important drivers of ecological succession (Smith 2007; 2008). If the nutrient-cycling caterpillars become replaced by non-native slugs (which, unlike the indigenous caterpillar, are not palatable to mice), consequences for ecosystem structure and function are inevitable (Smith 2007, 2008). Though it may be difficult to predict cascading impacts of the non-native detritivores, altered vegetation and soil properties will undoubtedly have implications for native invertebrate life.

Non-native vertebrates

Herbivores and Omnivores

Rabbits, cattle, sheep, Corsican mouflon, pigs, goats and reindeer were introduced to SOI in the 19th century to either provide food for camps of seal-hunters or for farming (Headland 2012). Typically, herbivore introductions on SOI have led to major declines in vegetation cover, particularly of endemic megaherbs and large tussock grasses that are important habitat for invertebrates (Micol and Jouventin 1995; Chapuis et al. 2004; Scott and Kirkpatrick 2008). With the reduction of some plant species through grazing, short grasses and herbs can

27 thrive, associated with expansion of grazing-tolerant non-native plants (Frenot et al. 2005), such as P. annua (Chown and Block 1997; Williams et al. 2013). The largely detritus-based food webs of SOI, which are composed of weakly efficient detritivores (Tréhen et al. 1990; Smith 2008), are further affected by the conversion of plant matter to herbivore dung rather than accumulated litter (Burger 1985; Tréhen et al. 1990).

Rabbits established on many SOI; however, most have been eradicated in recent times or died out (Headland 2012). Rabbits can reach plague proportions on these islands (e.g. Macquarie Island - Terauds et al. 2014) leading to drastic changes in vegetation (Convey and Lebouvier 2009; Scott and Kirkpatrick 2013; Whinam et al. 2014). The flow-on effects of vegetation loss can lead to soil exposure and erosion (Scott 1988; Chapuis et al. 1994; Scott and Kirkpatrick 2008, 2013), degradation of waterways and associated freshwater invertebrate life (Marchant et al. 2011), as well as reduction of seabird nesting habitat (Chapuis et al. 1994; Copson and Whinam 1998). Reduction in seabird nesting habitat ultimately leads to fewer nesting seabirds. In this way, grazing-mediated declines in seabird densities alter the dynamics of terrestrial communities by reducing marine nutrient inputs that underpin vegetation growth, affecting nutrient turnover and soil integrity, with consequences for food webs and invertebrates (Anderson and Polis 1999; Maron et al. 2006; Smith 2008; Pisanu et al. 2011). Such drastic ecosystem changes occurred on Macquarie Island before rabbits were eradicated, where they caused considerable loss of biomass of vegetation such as tall tussock grasslands (dominated by Poa foliosa) and herbfields (dominated by Stilbocarpa polaris and Pleurophyllum hookeri). This led to degradation of seabird habitat, extreme habitat and edaphic modification, landscape denudation, and increased land-slipping and erosion (Copson and Whinam 1998, 2001; Scott and Kirkpatrick 2008; Stevens et al. 2010), and resulted in substantial changes to invertebrate populations (Copson and Whinam 2001). This is especially the case as invertebrate richness is highest in vegetation communities that were impacted by rabbits (Davies and Melbourne 1999; Terauds et al. 2011; Whinam et al. 2014, Errington et al. 2018). Rabbits have had similar impacts on the Kerguelen archipelago, causing erosion and rapid declines in some native plant species, which are often replaced by monospecific communities of the less palatable, and increasingly dominant, Acaena magellanica (Holdgate 1966; Burger 1985; Chapuis et al. 1994). Some studies have suggested that the reduced range and abundance of unique SOI invertebrate fauna is related to herbivore-induced disappearance of natural vegetation communities dominated by Pringlea

28 antiscorbutica and Azorella selago (Holdgate and Wace 1961; Holdgate 1966; Chapuis et al. 1994), but there are no empirical data to support these claims.

Livestock on SOI have caused severe damage to native vegetation (Holdgate 1966; Taylor 1971; Chapuis et al. 1994; Seddon and Maloney 2003), leading to erosion, compaction, elimination of deep organic soils, the spread of non-native plants and presumably, commensurate reductions in associated invertebrates dependant on intact habitat (Holdgate 1966; van Vuren et al. 1992; Chapuis et al. 1994). Many herbivores prefer particular endemic plant species, causing large-scale alteration of plant community composition across a range of islands (e.g. Holdgate 1966; Taylor 1971; Campbell and Rudge 1984; Convey and Lebouvier 2009). Feral cattle, recently eradicated from Iles Amsterdam (Váňa et al. 2014), had major environmental impacts (Micol and Jouventin 1995; Convey and Lebouvier 2009). Monitoring following initial control fencing and cattle removal from half of the island showed some vegetation regeneration (Micol and Jouventin 1995), but there are no published data available that quantify either the initial impacts of livestock on invertebrates, or the benefits of recent livestock control on invertebrates. Pigs remain on Auckland Island where their effects have been described as ‘severe’ (Headland 2012). They eat large amounts of native vegetative matter, particularly megaherbs, and prey directly on annelids (worms – 26% dry weight of stomach content), insect larvae, and amphipods (Challies 1975; Chimera et al. 1995). Eight of the ten species of annelids found on Auckland Island are endemic (Lee 1959). Whether any of these species are threatened with extinction as a result of pigs is unknown (Chimera et al. 1995).

Reindeer are extant on Iles Kerguelen and South Georgia (Courchamp et al. 2003), although they are near eradicated from South Georgia Island at the time of this publication. While feeding on Iles Kerguelen they turn over A. selago cushions (Chapuis et al. 1994), key invertebrate habitat (Phiri et al. 2009; Barendse and Chown 2001). Reindeer grazing and trampling impacts on South Georgia alter soil integrity and destroy large tracts of the dominant vegetation, the grass P. flabellata and herb A. magellanica, which are succeeded by the grazing resistant native grass Festuca contracta, and the grazing tolerant non-native grass P. annua (Vogel et al. 1984; Leader-Williams et al. 1987; Chown and Block 1997). Although the impacts of reindeer-mediated vegetation change have not been quantified at an invertebrate community level, some species-specific impacts have been documented (Vogel et al. 1984; Chown and Block 1997). One example is the increased frequency of sciarid flies

29 in grazed areas (which are possibly non-native), likely due to the ability of their larvae to establish larger populations in deep soil and hardened substrates (a result of trampling - Vogel et al. 1984). Another is reduced abundance of the primary decomposer perimylopid beetle (Hydromedion sparsutum), and increased frequency of their egg parasite Notomymar aptenosoma (Hymenoptera, Mymaridae) (Vogel et al. 1984). Furthermore, trampling may have facilitated a shift in the proportions of Collembola (major prey invertebrates) and spiders (predators) found in pitfall traps - in ungrazed areas the ratio of invertebrates to spiders was 1: 1.3, compared to 1: 0.82 in grazed areas (Vogel et al. 1984).

In general, suppression or extinction of vegetation that invertebrates rely on for food or shelter, strongly influences native invertebrate extinctions (Dunn et al. 2009). Although rodents are omnivorous, here we treat them as predators, given their severe direct impacts on invertebrates as prey. However, rodents on SOI can also affect seedling recruitment and vegetation communities through consumption of seeds and plant material (Shaw et al. 2005; Copson 1986), nesting (Barendse and Chown 2001; Phiri et al. 2009), burrowing, sediment removal and erosion (Gremmen 1981; Eriksson and Eldridge 2014). These activities have consequences for invertebrates dependant on preferred plants or plant communities (Hugo et al. 2004; Phiri et al. 2009; St Clair 2010; St Clair 2011).

Predators

Native terrestrial vertebrate predators are absent from SOI, therefore the introduction of non- native predators has led to severe impacts on a suite of native taxa, predominantly seabirds, that have evolved few defences (Courchamp et al. 2003; Frenot et al. 2005; Convey 2011). These effects have provided the impetus for several eradication programs, both completed and planned (e.g. Angel and Cooper 2006, Russel 2012; Robinson and Copson 2014; Springer 2016). For invertebrates, the impacts of predatory mammals on SOI (such as rodents and cats) are both indirect and direct (Copson 1986; Courchamp et al. 2003; Angel et al. 2009; St Clair 2010; St Clair 2011; McGeoch et al. 2015). Rats and mice have caused extensive damage to SOI ecosystems, including impacts on invertebrate richness and diversity, exemplified by comparative studies of invaded and uninvaded islands, such as those in the Falkland Islands (St Clair et al. 2011), Marion Island and neighbouring Prince Edward Islands (Crafford and Scholtz 1987; Chown and Smith 1993; Treasure and Chown 2014; McClelland et al. 2018) and uninvaded Bollons and Archway islands, which are offshore from Antipodes Island (Marris 2000; McIntosh 2001; Russell 2012). Globally, there

30 are well-documented impacts by rats on terrestrial communities, ecosystem properties, and other native taxa, particularly seabirds (Fukami et al. 2006; Towns et al. 2006; Jones et al. 2008; Drake and Hunt 2009; Mulder et al. 2009; Wardle et al. 2009; Pisanu et al. 2011; Brooke et al. 2018). However, rat impacts on invertebrates are less frequently quantified (St Clair et al. 2011). Towns et al. (2006) cite only nine examples of direct rat-invertebrate interactions in their global review of rat impacts, and only a few published studies directly measure these interactions for SOI (e.g. St. Clair et al. 2011, Pisanu et al. 2011). In general, rats on SOI are found to augment their largely plant-based diet, with large-bodied invertebrates such as caterpillars, worms, beetles and weevils (Pye and Bonner 1980; Copson 1986; Pisanu et al. 2011; St Clair et al. 2011). St Clair et al. (2011) investigated the effects of rats on large-bodied invertebrates in the Falkland Islands (particularly the endemic Falkland camel cricket) across 37 invaded, uninvaded and recently cleared islands. They found uninvaded islands had up to an order of magnitude more camel crickets than invaded or recently rat-free islands, but also that camel cricket populations recover quickly following rat eradication. Alongside their plant diet preferences, the preferences of rats to predate on the most abundant and large bodied terrestrial invertebrates on SOI implicate them in species suppression and ecosystem transformation (St Clair 2010).

By contrast, the predation effects of mice on SOI invertebrates are better documented. Eleven SOI have been invaded by mice and their predatory impacts are considerable (Angel et al. 2009), especially for invertebrate populations on Gough Island (Jones et al. 2003a, 2003b, 2003c), Guillou Island (in the Kerguelen archipelago) (Le Roux et al. 2002), Antipodes Island (Marris 2000), Macquarie Island (Copson 1986) and Marion Island (Gleeson and van Rensburg 1982; Crafford and Scholtz 1987, Smith et al. 2002, McClelland et al. 2018). Where mice are the sole predator, their effects on invertebrates are typically greater, such as on Antipodes, Marion, and Gough islands (Angel et al. 2009; Russell 2012, McClelland et al. 2018). Furthermore, climate warming in the region underpins increases in mice biomass and further exploitation of invertebrate prey (McClelland et al. 2018). A good example is the 197.6 -fold decrease in invertebrate biomass on Marion Island between 1976 and 2006 due to mice, or around 90% loss of biomass each year, linked to climate-driven mice population increases (McClelland et al. 2018). Mice predation is implicated in the extinction of island endemic invertebrate species on Antipodes Island (Marris, 2000) and increases the extinction threat for several species on Gough Island (Jones et al. 2003a) and Marion Island (Crafford and Sholtz 1986; Rowe-Rowe et al. 1989; Angel et al. 2009, McClelland et al. 2018). Where

31 mice are abundant they are responsible for localised extinction of invertebrates in lowland and coastal areas on SOI, restricting once abundant species to upland areas (e.g. Gough Island - Jones et al. 2003b and Antipodes Island - Marris 2000). Large-bodied invertebrates are more at risk to suppression or local extinction through rodent predation than smaller- bodied taxa (Chown and Smith 1993; Pisanu et al. 2011; St Clair 2010; St Clair 2011). Pronounced impacts of size-selective feeding are evident in changes to the size distribution of weevils on Marion (Treasure et al. 2014), and is potentially responsible for the hybridization of two species that may previously have been differentiated by size (Chown 1990; Grobler et al. 2006). Depending on the season and availability of preferred prey, mice can switch preferred food items (Copson 1986; Smith et al. 2002; Russell et al. 2019). For example, on Antipodes Island, mice seem to exhaust their preferred invertebrate prey to the point of severe suppression or local extinction, before moving on to the next preference, thus systematically eating their way through the ecosystem (Russell et al. 2019). Such extirpation of preferred invertebrate prey, particularly during winter on islands with elevated populations of mice as the sole predator, may be a driver behind mice switching diets to seabirds (Russell et al. 2019), such as on Gough Island (Wanless et al. 2012; Dilley et al. 2015) and Marion Island (Jones and Ryan 2010). Through their dynamic dietary preferences, the above studies have shown that mice can drastically modify the structure of ecosystems on SOI.

Mice predation on invertebrates also alters overall ecosystem processes. Suppression of invertebrates influencing nutrient cycling and mineralisation, has profound implications for SOI ecosystems that are already nutrient poor (McClelland et al. 2018). Alteration of ecosystem processes by mice on Marion Island occurs through predation of a keystone nutrient-cycling species, the caterpillar of a flightless moth, P. marioni (Smith and Steenkamp 1992a; Klok and Chown 1998), as well as depletion of other invertebrate prey such as spiders, weevil larvae and weevil adults (Crafford and Scholtz 1987; Rowe-Rowe et al. 1989; Chown et al. 2002). The substantial reduction in the flightless moth caterpillars, which are vital to nutrient supply for primary producers, threatens to slow plant growth, reduce litter quality, potentially affect the formation of peat on the island, and alter vegetation success (Smith and Steenkamp 1990; Smith 2008; Haupt et al. 2014).

Caterpillar declines are also linked to a declining population of lesser-sheathbills (Chionis minor), whose overwintering diet is dependent on them (Huyser et al. 2000). This is a clear example of the cascading ecosystem effects of invertebrate impacts. Potentially similar

32 effects have been documented on Gough Island, where two endemic brachtyperous moths (Dimorphinoctua goughensis and Peridroma goughi), which are key nutrient cycling species, are preferentially eaten by mice (Jones et al. 2002; 2003a). On Macquarie Island, before a successful rodent eradication, amongst a wide variety of invertebrate prey detected in 108 mouse stomachs, spiders were recorded in 67% of them (Copson 1986). Given that all three species on Macquarie Island are major predators of small invertebrates (Greenslade 2006), depletion of spiders by rodents likely had flow on-effects in the ecosystem and the invertebrate community due to the release of small invertebrates from spider predation.

Indirect effects on invertebrates can occur through reduction of seabird populations due to rodent predation. Mice can prey-switch to seabirds as invert biomass falls in winter (Jones and Ryan 2010; Dilley et al. 2015), over time reducing seabird-driven marine inputs to the ecosystem and leading to soil impoverishment. Guano deposition by seabirds leads to increased cover, vitality and growth in plant communities (Smith 1976; 1978; Erskine et al. 1998), which in turn support a disproportionately high biomass of invertebrate detritivores and herbivores compared with areas free of seabirds (Burger 1978; Crafford and Sholtz 1987). In this respect, seabirds act as ‘ecosystem engineers’, influencing the base of food webs (Sanchez-Pinero and Polis 2000; Jones 2010a; Russell 2012; Buxton et al. 2014). Thus, predation of seabirds on islands can reduce soil fertility (Fukami et al. 2006; Wardle et al. 2009), affect vegetation recruitment and growth, litter composition and decomposition (Wardle et al. 2007; 2009), and exert considerable multi-trophic, cascading effects in the terrestrial ecosystem (Croll et al. 2005; Fukami et al 2006; Maron et al. 2006; Wardle et al. 2007; Mulder et al. 2009; Towns et al. 2009). Rodent predation on seabirds can indirectly lead to reduced abundance of major orders of soil and above-ground invertebrates (Fukami et al. 2006; Towns et al. 2009). Furthermore, invertebrate food webs are smaller and less complex on islands not dominated by seabirds, leading to lower trophic-level redundancy and therefore lower ecosystem resistance (Thoresen et al. 2017). These cumulative predator impacts have contributed to severe, sometimes permanent ecosystem alteration (Fukami et al. 2006; Mulder et al. 2009; Towns et al. 2009; Wardle et al. 2009; Jones 2010). In light of these trends, cat eradication success on Macquarie and Marion Islands is predicted to have implications for their ecosystems beyond seabird population increase, including for invertebrates (van Aarde et al. 1996; Raymond et al. 2011). Unexpected consequences of ecosystem change following predator eradication has also been observed, such as the expansion of a non-native on Marion Island, as its preferred habitat, a native grass,

33 responds favourably to recovery of seabirds and associated nutrients since cat removal (Treasure and Chown 2013).

DISCUSSION

Southern Ocean Islands have been visited by scientists for over 100 years. Despite this, some islands and some taxa have received more attention than others (Chown et al. 2008). The significance of such extensive studies in the region is valuable for invertebrate ecology. However, Table 1 in Appendix 1) highlights that research gaps remain for some ecological processes, some taxa and some islands. For example, non-native species on SOI have wide- ranging, sometimes severe, impacts on native invertebrates, either through direct mechanisms (e.g. predation and competition) or indirectly, through habitat modification, changes in soil integrity and reduced nutrient subsides by seabirds. Yet there is still limited understanding of these impacts for invertebrates and empirical data remain scarce. Similarly, non-native plant species are common, and in some instances widespread, on most SOI, yet to date, only three studies have investigated the response of invertebrates to non-native plant expansion. This is despite the fact that we know native invertebrates rely on native plant species for food, habitat and cover (e.g. Hänel 1999; Hugo et al. 2004; 2006) and flow on effects are likely for native invertebrates when non-native plants flourish. Furthermore, whilst numerous studies have referred to the likelihood of considerably altered invertebrate populations associated with extensive damage to soils and native vegetation by grazing mammals (e.g. Chapuis et al. 1994, 2004; Copson and Whinam 2001; Courchamp et al. 2003), few have supported their claims with empirical data. Island-wide modification of habitat and soil through grazing and trampling have had wide-ranging ecosystem impacts (e.g. Courchamp et al. 2003; Chapuis et al 2004; Frenot et al. 2005; Scott and Kirkpatrick 2008). These impacts on lower trophic levels such as among invertebrates, are often implied (e.g. Chapuis et al. 1994; Micol and Jouventin 2002) but rarely quantified. Only two publications explicitly test the indirect effects of herbivore-induced plant community changes and activity on local associated invertebrates – Vogel et al. (1984) through reindeer trampling effects, and Chown and Block (1997), via the effects of grazing-mediated, non-native P. annua grass on native invertebrate fitness (Appendix 1, Table 1). More than fifty years have passed since Holdgate and Wace (1961) noted that elimination of native vegetation by rabbits on Kerguelen is accompanied by ‘the loss of the remarkable invertebrate fauna associated with it’, but there has been few, if any,

34 comprehensive studies measuring invertebrate responses to non-native mammal grazing and vegetation damage on SOI. Even at a global scale, a lack of meaningful reporting on vegetation responses to herbivore eradication persists, which underpins a gap in our understanding for whole-ecosystem conservation benefits (Schweizer et al. 2016), including the fate of invertebrates. As a result, although eradications of mammalian herbivores have occurred on SOI for conservation benefits, to date we can only assume there are associated benefits to invertebrate communities.

While the 17 studies on invasive invertebrates in Table 1 in Appendix 1 include a broad suite of 26 invasive invertebrate species impacting on native fauna and ecosystems, the 20 studies researching the impact of mammalian predators on native invertebrates on SOI is overwhelmingly skewed towards studies of mouse-invertebrate interactions (17 of the 20 predator-related studies). Not only do mice studies dominate predator research for invertebrates, but the native invertebrate taxa studied is skewed heavily towards Coleoptera (beetles – 21 times), and Lepidoptera (moths – 19 times). Within the Coleoptera studies, the weevils Ectemnorrhinus spp. dominated (7 studies) and within the Lepidoptera studies flightless moths, Pringleophaga spp., were the primary focus (14 studies). Some of this research bias is due to the profusion of work on certain islands where these species exist. Marion Island, for example, is the site of 18 of our 45 studies incorporating invertebrate and non-native species interactions, with the second most-studied island, South Georgia, producing only 8 studies. The Kerguelen archipelago, which has a suite of non-native mammal, plant and invertebrate species across numerous islands, is the subject of only six studies that investigate their impacts on native invertebrates. This summary highlights gaps in our knowledge for unknown or under-surveyed invertebrate species on SOI that are impacted by invasive species, and also emphasises the lack of survey effort that persists for some SOI. While it has been widely shown that non-native mammals drastically alter SOI, our review also highlights the considerable impacts of non-native invertebrates on native invertebrates and island ecosystems more broadly. To date these impacts have been underestimated, and their long-term extent is still largely unknown (McGeoch et al. 2015). Moreover, variation remains in the level of survey effort and knowledge among taxonomic groups (Convey et al. 2006b). Despite these impacts and improved biosecurity, non-native invertebrates continue to arrive and establish on SOI (Hughes et al. 2011; Houghton et al. 2016; Phillips et al. 2017). Invasions are expected to increase as the climate warms (Chown et al. 2008; Chown and Convey 2016). Eradications of invertebrates are rare, although recently demonstrated to be

35 possible – for example, a butterfly in the South Island of New Zealand (Department of Conservation 2018); and ants on Tiritiri Matangi, New Zealand (Green 2019), and Lord Howe Island (Boland et al. 2011; Hoffman et al. 2017). Nevertheless, the most cost-effective management strategy to reduce the impacts of invasive invertebrates on SOI is through improved biosecurity. For this reason, extending our knowledge of native and non-native invertebrate interactions in SOI ecosystems is critical, particularly in identifying high-risk taxa and developing targeted biosecurity procedures. Such knowledge increases the likelihood that island managers can reduce or even avoid completely, incursions of taxa likely to establish, invade and have impact. Similarly, improving our understanding of how established invasive invertebrates interact with flora and other invertebrate in SOI ecosystems, and their influence on food webs and nutrient cycling, is critical to our future management of present non-native species and developing responses to future incursions.

We have a good understanding of rodent impacts on SOI invertebrates from a suite of studies (Appendix 1, Table 1). However, the indirect consequences of seabird predation by rodents on above- and below-ground invertebrate communities and food webs can only be assumed from comprehensive studies of the seabird impacts on New Zealand islands (e.g. Fukami et al. 2006; Towns et al. 2009; Thoresen et al. 2017). To date, no published study has measured the consequences of predator-mediated seabird declines for native SOI invertebrates, although the topic is often discussed (e.g. by Crafford and Scholtz 1987 in relation to cat impacts on Marion Island and by Huyser et al. 2000 for cats, mice, seabird invertebrate interactions). Furthermore, although some comparative island studies document rodent impacts on invertebrates on SOI (e.g. Crafford and Sholtz 1986; Marris 2000; McClelland et al. 2018), we still know little about how invertebrate communities respond once the target invasive species is eradicated. Furthermore, we have very little understanding of how these invertebrate responses to such management may influence recovery (or otherwise) of the whole island ecosystem. The study by St Clair et al. (2011) on the Falkland Islands showing camel cricket recovery following rat removal is an exception. How interactions between plants and native invertebrates may change in response to mammal eradications are also not well described (Angel and Cooper 2006).

There are several underlying reasons behind the limited monitoring of SOI invertebrate response to eradications to date. A key contributing factor is that conservation efforts have traditionally focused on large, charismatic megafauna (Samways 2007; Angel et al. 2009,

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Collen et al. 2012). Invertebrate surveys are time-consuming, and often considered too difficult, yielding enormous abundance and diversity of species for which few specialists are available to process and even less to identify (Ward and Larivière 2004). Finally, the dramatic speed of invertebrate responses (e.g. St Clair et al. 2011; Watts et al. 2011) mean that unless surveys are planned and undertaken before and soon after eradications, nuanced changes can be difficult to identify. The consistent lack of invertebrate baseline data on SOI prior to non-native species introductions means that it is rarely clear which (or if any) species have experienced population declines or been lost altogether. In order to quantify change with confidence, invertebrate monitoring must begin with meaningful pre-treatment baseline surveys, accompanied by comprehensive and timely post-treatment monitoring.

The results of our review support and build on the assessments and findings of McGeoch et al. (2015), and Jones et al. (2016) who suggest that the responses of invertebrate fauna on islands are under-reported and poorly understood. Although critical to ecosystem functioning and high in diversity, invertebrates in protected areas and natural landscapes rarely generate interest in conservation funding (Angel et al. 2009). Furthermore, being inconspicuous, with cryptic habits, invertebrates are often overlooked in restoration programmes to date, even though they comprise the base of trophic pyramids and changes in their abundance and distribution can affect the whole ecosystem (Courchamp et al. 2003; Angel et al. 2009; Shaw et al. 2011). More recently, the importance of invertebrates has been recognised in SOI mammal eradication feasibility studies and planning processes, For example, invertebrate recovery was one of the objectives of the Macquarie Island Pest Eradication program (rodents and rabbits; Parks and Wildlife Service, 2008), the Antipodes Island mice eradication (Elliot et al. 2015) and the proposed mice eradication on Gough Island (Parkes 2008). However, given the recent completion or near implementation of these programs (post-eradication monitoring is currently underway on Antipodes and Macquarie Islands, pre-eradication monitoring is underway on Gough), meaningful data and reporting on species interactions and the responses of invertebrates to mammalian predator and herbivore removal remain elusive. While these studies are yet to be completed (or published), they represent an important and necessary shift in thinking by scientists, funders and land managers. As we have highlighted here, the impacts of non-native species on invertebrates are far too wide- ranging to be ignored any longer.

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ACKOWLEDGEMENTS

We thank Paulo A. V. Borges and an anonymous reviewer for their valuable comments on the manuscript. We thank the Australian Academy of Science for their support to MH through the Max Day Environmental Fellowship. This research is also supported by funding from the Australian Government’s National Environmental Science Programme through the Threatened Species Recovery Hub and the Australian Antarctic Science program (AAS 4305).

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Chapter 3 | Methods for monitoring invertebrate response to vertebrate eradication

Houghton, MJ., Terauds, A., and Shaw, JD. (2019) Methods for monitoring invertebrate response to vertebrate eradication. Island Invasives: scaling up to meet the challenge 62. IUCN, Gland, Switzerland, 381-388.

MJH wrote this chapter with editorial advice from all authors. MJH and JDS conceived the idea. MJH collected, sorted and identified invertebrate samples. MJH undertook analyses of the data, with advice from AT and JDS.

ABSTRACT

Once an island vertebrate eradication is deemed successful, it is typically assumed that ecosystem recovery will follow. To date, most post-eradication monitoring focuses on the recovery of key threatened or charismatic species, such as seabirds. Little attention has been given to monitoring and quantifying the response of invertebrate communities. Rabbits (Oryctolagus cuniculus), house mice (Mus musculus), and ship rats (Rattus rattus) impacted sub-Antarctic Macquarie Island for over 140 years, with wide ranging ecosystem impacts. In 2014, the eradication of rabbits and rodents was officially declared successful. To determine whether management objectives are being met, we are investigating the response of invertebrate communities to pest eradication, using both historic data and contemporary surveys to track changes over space and time. To achieve this, we have developed a survey strategy that is effective and efficient. Here we report on the merits of utilising a variety of invertebrate trapping methodologies to establish current baselines for future invertebrate monitoring. We identify sampling techniques that are most effective for specific groups of taxa, particularly those of interest to post-eradication monitoring, and how the implementation of such methods can improve and facilitate effective post-eradication monitoring of invertebrates.

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INTRODUCTION

Island invertebrates are impacted by invasive species, particularly on remote, unpopulated islands in the Southern Ocean (Angel et al. 2009; Chown et al. 2008; St Clair 2011: Russell 2012; Towns et al. 2009; Thoresen et al. 2017). Non-native plants and invertebrates have been unintentionally introduced to Southern Ocean Islands (SOI) (Frenot et al. 2005; Chown, et al. 2008; Convey and Lebouvier 2009). Non-native vertebrates have also been introduced, both intentionally and inadvertently. For example, rabbits (Oryctolagus cuniculus), cats (Felis catus), dogs (Canis lupus familiaris), sheep (Ovis aries), goats (Capra aegagrus hircus), weka (Gallirallus australis), pigs (Sus scrofa domesticus), brown trout (Salmo trutta) and reindeer (Rangifer tarandus) were all intentionally introduced to SOI, whereas ship rats (Rattus rattus), brown rats (Rattus norvegicus) and house mice (Mus musculus), were unintentional introductions (Courchamp et al. 2003; Convey and Lebouvier 2009; McGeoch et al. 2015; Copson and Whinam 2001). Grazing by non-native vertebrates on SOI has led to invertebrate habitat modification (Chapuis et al. 2004; Vogel et al. 1984), and direct predation by rodents has severely modified and depleted invertebrate populations (Copson 1986; Angel et al. 2009; St Clair et al. 2011; Treasure et al. 2014; Chown et al. 1993; Russell 2012.

Macquarie Island (54.62° S, 158.86° E) lies 1500 km southeast of Tasmania, Australia. The island is a World Heritage area managed as a Nature Reserve by the Tasmanian Parks and Wildlife Service (Copson and Whinam 2001). Discovered in 1810, the island’s early human history involved seal and penguin harvesting. Many non-native species of flora and fauna were introduced during this time, both intentionally and inadvertently. Ongoing control of cats and rabbits by various methods and at varying effort led to fluctuating populations (Robinson and Copson 2014; Terauds et al. 2014). Consequently, native fauna and vegetation was impacted by varying levels of predation and grazing (Scott and Kirkpatrick 2008; 2013; Bergstrom et al. 2009; Whinam et al. 2014). Over time, island managers have removed almost all invasive vertebrate species from Macquarie Island (Copson and Whinam 2001), the most recent being cats in 2000 (Robinson and Copson 2014) and rabbits and rodents in 2014 (Springer 2016). The latter were the target of the Macquarie Island Pest Eradication program, which was the largest multi-species project of its kind at the time, costing AU$24.5 million. The project’s overall objective was to ‘…restore Macquarie Island biodiversity and geodiversity to a natural balance - free of the impacts of introduced pest species… [with]

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…vegetation, seabird and invertebrate populations recovered to levels naturally supported by the environment’ (Parks and Wildlife 2009). We developed a study to assess the success of this project for invertebrates; specifically to better understand if they have ‘recovered’ following removal of mammalian herbivores and predators, utilizing both historic data and contemporary surveys.

Invertebrates play a key role in ecosystem function (Gerlach et al. 2013; Kremen et al. 1993; Hutcheson et al. 1999). They drive nutrient-cycling and decomposition processes on SOI (Smith and Steenkamp 1990; 1992; Smith 2007; 2008). Thus, establishing a baseline and measuring their response to ecosystem change informs the state of the island ecosystem. Many types of invertebrates are useful proxies for assessing ecosystem change, reflected in their species richness, species turnover and community composition (Kremen et al. 1993; Hutcheson et al. 1999; Towns et al., 2009). Indicator taxa are particularly useful in monitoring the effects of habitat management at the ground layer (e.g. ants, millipedes, snails, ground beetles, some spiders), in foliage (e.g. ants, leaf beetles, some spiders and moths), and in open habitats (e.g. ants, crickets, grasshoppers, and butterflies) (Gerlach et al. 2013). Moreover, their high density, short life span, ubiquity and rapid response to changing environmental conditions, make invertebrates ideal for long-term monitoring (Samways et al. 2010; McGeoch et al. 2011).

Despite their suitability as indicators, monitoring of invertebrates post-eradication is rarely undertaken, and their response to eradication infrequently determined. Developing appropriate survey methods and sampling strategies is crucial for a monitoring program. Here we test a variety of invertebrate survey techniques and report on the merits of utilising specific invertebrate trapping methodologies to establish baselines for future invertebrate monitoring and to facilitate comparisons with previous surveys. Our recent surveys included most of the invertebrate trapping techniques previously employed on the island by historical surveys. Our survey design aimed to measure invertebrate response to vertebrate eradication and vegetation rehabilitation, track change in invertebrate community composition and numbers, and establish baselines for future monitoring. Specifically, our objectives in this paper, are to 1) compare the efficacy of using different invertebrate trap types in achieving monitoring objectives, 2) assess the effectiveness of historical trapping methods in informing contemporary survey design, and 3) investigate the benefits and limitations of utilising historical data for tracking changes over time. We also discuss how choosing appropriate

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methods is a key process for effective and efficient post-eradication monitoring of invertebrates.

METHODS

Survey Design

Determining invertebrate community changes over time requires definitive and repeatable methods and detailed site information. Our experimental design (i.e. our choice of survey/trapping techniques and site selection) was informed by analysing invertebrate trapping experimental designs, methods and results from historical surveys on Macquarie Island. Following a thorough review of the scientific literature five key resources were selected to inform our experimental trapping design and methods: Watson (1967), Greenslade (1987), Anonymous (1993-94, reported in Stevens et al., 2010), Davies and Melbourne (1999), and Stevens et al., (2010). Each of these historical surveys utilised different combinations of methods ( Table 3-1). Based on this information, the following survey methods were tested in our study: pitfall traps, sweep netting, litter extraction, and timed hand collecting (referred to as ‘20 minute counts’).

Site selection

For this study, sampling was carried out at ten historic and ten new sites (Figure 3-1). This provided 20 sites in total for the 2015/16 post-eradication survey. The ten new sites were selected to ensure broader island coverage and survey additional vegetation communities across the five dominant vegetation structures on Macquarie Island (based on Selkirk, et al., 1990) – feldmark (plateau), lower coastal slopes dominated by Stilbocarpa polaris (Macquarie Island cabbage), tall grassland (tussock) dominated by Poa foliosa, short grasslands (including Deschampsia spp., Festuca contracta, Agrostis magellanica, Luzula crinita, Uncinia spp.), and herbfield dominated by Pleurophyllum hookerii. Most sites were heavily impacted by rabbits in the past (Bergstrom et al. 2009; Whinam et al. 2014). In total, four Stilbocarpa polaris sites were surveyed in 2015/16, three short grassland sites, five tall grass sites, four herbfield sites, and four feldmark sites.

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Sampling techniques

Five pitfall traps were established at each of the 20 sites, in a line transect along a recorded bearing, five metres apart. Expert advice from the Tasmanian Department of Primary Industries, Parks, Water and the Environment (M. Driessen, pers. comm.), informed the pitfall trap preparation, spacing, pattern of positioning, and preservative used. Pitfall traps were constructed of straight sided, plastic jars 7 cm in diameter, approximately 7 cm deep, with ~1 cm of 100% propylene glycol preservative added. Pitfall diameter was selected based on other studies that have proven the effectiveness of larger trap sizes (Ward et al. 2001; Brennan et al. 1999; Woodcock 2005; Work et al. 2002). Propylene glycol was chosen a preservative due to it being environmentally benign, highly viscous and slow to evaporate.

Table 3-1 Trapping methodology employed during invertebrate sampling studies on Macquarie Island – Watson in 1961 (reported in Watson 1967), Greenslade in 1986-87 (reported in Greenslade 1987), Anonymous in 1993-94 (reported in Stevens et al. 2010), Davies and Melbourne in 1996 (reported in Davies and Melbourne 1999), Stevens et al. in 2009-10 (reported in Stevens et al. 2010).

Davies and Stevens, Watson Greenslade Anonymous Melbourne et al., 1961 1986-87 1993-94 1996 2009-10 Length of December - February - October – sampling Year-long January Year-long March January Extent of sampling Island-wide Northern sites Northern sites Island-wide Northern sites # Sites Not specified 8 4 67 41 # Pitfalls/site 0 5 Not specified 3 3 # Pitfall trap days - 5-20 30 ~42 7 - 21 Pitfall 'Large' and 'Large' and diameter (cm) - 1.8 'small' 3 'small' Ethylene Not Glycol/ Pitfall medium - Ethanol specified detergent Ethanol # Yellow pan Yes, # not trap/site specified 0 0 1 0 Vegetation Yes, # not Yes, # not Beating No specified No No specified Vegetation Yes, # not Yes, # not Sweeping specified specified No No No Litter volume Yes, # not (Lt) specified 2 - 4 0 0 1 over 1 m² Litter extraction method Berlese funnels Berlese funnels n/a n/a Berlese funnels Yes, # not # Soil Cores specified 11-16 5 0 0

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20 minute counts (hand collecting) Yes (not timed) Yes (not timed) No Yes No

Pitfall trap holes were dug with a soil corer to ensure a snug fit and the pitfall rim was flush with the ground surface. Where necessary, a small amount of vegetation was cleared from the trap rim. At the 20 sites, pitfall traps were collected approximately every 10 days between October and December and reset upon collection for a total period of up to ~42 days. Further pitfall sampling was repeated monthly in January, February and March for approximately 5- 10 days at eight sites.

For litter sampling, at each site, a 1m² quadrat was used to define the collection area, and three collections were made of one litre of litter at each site. Litter was transported back to the station laboratory for sorting and invertebrate extraction within a maximum of three days from collection. In feldmark sites where litter was scarce, litter collection was over 4 m² and up to 1 litre of material – the exact area and volume was recorded.

Timed counts of 20 minutes were conducted at least twice over the study period at each site, involving focussed searching with an aspirator tube and tweezers, collecting all invertebrates encountered, particularly at the base of vegetation and under stones.

Sweeping of vegetation tops with nets required dry conditions with light winds. Hence, sweeping was conducted opportunistically, at a minimum of twice at each site over the study period, in all vegetation types regardless of the canopy (i.e. also in feldmark), by walking slowly and dragging the net across the vegetation tops 30 times, on three different trajectories in the site area per sampling event.

One temperature logger i-button was installed at each of the 20 sites to monitor microclimate, at the first pitfall trap of each transect. They were attached approximately 10 cm above the ground surface on a stake with a protective housing. At each site, site-specific features such as aspect, altitude, landscape features, vertebrate fauna presence and vegetation were noted.

Processing and identification

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All samples were transferred promptly to 100% ethanol and transported back to the Australian Antarctic Division for identification and storage. Using a dissecting microscope,

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Figure 3-1 Map of 20 invertebrate trapping sites surveyed at Macquarie Island in 2015/16. All historic sites sampled in 1986/87 (indicated by grey diamonds) were resampled in 2015/16.

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specimens were counted and identified to species where possible, except for Acarina, Annelida, and Nematoda, which were identified to Class or Phylum level.

Data Analysis

We undertook preliminary comparisons of the 2015/16 survey data on Order richness and diversity with data from historical sites established in 1986/87 (Greenslade 1987). We calculated taxonomic richness and diversity of invertebrates in different trap types, vegetation groups and in historical data. For these purposes we pooled data from different sites to obtain the total number of taxa trapped in different trap types and vegetation groups. Invertebrate richness was calculated by summing the total number of invertebrate Orders recorded in the trap type or vegetation group of interest. Simpson’s Index of Diversity (SID) was selected to compare diversity, as it takes into account both abundance and richness in each habitat. We compared the Order richness and diversity of our pitfall traps to seven historical sites and also quantified changes in abundance for three target groups (beetles, spiders and moths), using a subset of the historic and contemporary pitfall data.

We analysed data at the level of Order/Class/Phylum (hereafter referred to as ‘Order’) to facilitate preliminary comparison with historic data sorted to Order resolution. For analysis, larval stages and adults were grouped together for Lepidoptera, Thysanoptera, Coleoptera and Diptera.

RESULTS

Contemporary survey

Our preliminary results from the 2015/16 survey demonstrated that pitfall traps collect the largest number of individuals – in particular, Collembola (Table 3-2). Even when Collembola were removed from the analysis, pitfalls still collected more individuals than other trapping methods. Despite the abundance of invertebrates in pitfalls, there was considerable variance in the nature and abundance of taxa caught by the different trapping methods, with some methods proving more effective for specific taxa than others (Table 3-2).

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Table 3-2 The number of individuals from each Order of invertebrates collected via four different trapping methods on Macquarie Island following mammal eradication: Pitfall traps, sweeping, 20 minute counts, and litter collection in the 2015/16 season following mammal eradication.

20 minute Order Common Name Pitfalls Sweep count Litter Gastropoda Snails/slugs 935 2 1294 1019 Psocoptera Booklouse 44 2 0 129 Hemiptera Aphids/Bugs 3 0 0 0 Thysanoptera Thrips 144 21 4 4 Coleoptera Beetles 2512 2 12 240 Diptera Flies 945 61 51 61 Lepidoptera Moths 3 0 4 8 Hymenoptera Wasps 1 0 0 0 Crustacea 209 1 207 636 Araneae Spiders 2467 40 169 380 Platyhelminthes Flatworms 20 0 1 1 Annelida Worms 284 3 493 1489 Copepoda Copepods 3615 0 2 8 Tardigrada Tardigardes 69 0 0 0 Acarina Mites 5219 40 108 340 Siphonaptera Fleas 1 0 0 1 Nematoda Nematodes 19 0 0 0 Collembola Springtails 43641 277 3609 5040 TOTAL 60131 449 5954 9356

Richness (number of different orders caught) and diversity (SID - richness combined with the relative abundance of the different order caught) varied between trapping methods (Figure 3-2). The SID demonstrated that although pitfalls traps yielded the greatest richness, they also had the lowest diversity, attributable largely to the dominance of Collembola. Conversely, sweeping had relatively low species richness but high SID, an indication of the greater relative abundance of different taxa trapped.

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Figure 3-2 Order richness (summed across 20 sites) and Simpson’s diversity of four different trapping methods on Macquarie Island in 2015/16 following mammal eradication.

Pitfalls collected the most species regardless of habitat type (Table 3-2, Figure 3-3). Effectiveness of the other trap types varied by vegetation community (Figure 3-3). Sweeping vegetation was far more effective in tall grassland and S. polaris, which are often characterised by dense protective foliage, than for herbfield and feldmark vegetation, which typically have more prostrate, sparsely distributed plants. Litter collection also yielded high relative Order richness, particularly in tall grassland and short grassland vegetation communities. Twenty-minute counts were effective in feldmark, where richness was proportional to effort. The low number of taxa in this habitat were found more readily through this method of focused searching (disturbing stones and turf), than via passive pitfall trapping or surface litter collection.

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Figure 3-3 Order richness (summed across 20 sites) of four trapping types in five vegetation communities on Macquarie Island in 2015/16 following mammal eradication

The SID of pitfall trap samples across vegetation types was almost the inverse of their richness (Figure 3-4). Across all vegetation types (except for feldmark), pitfall trapping diversity was much lower than for other trap types; a likely reflection of the dominance of the Collembola in pitfall traps except in feldmark. For short grassland, litter sampling proved to be exceptionally diverse. Interestingly, although taxonomic richness of sweeping in herbfield was relatively low, SID was high. Across all vegetation types, 20 minute counts were almost equal in diversity.

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Figure 3-4 Simpson’s Index of Diversity (Order) of four trap types in five vegetation communities on Macquarie Island in 2015/16 following mammal eradication.

Comparisons with historical surveys

Preliminary comparisons of our data on Order richness and diversity data from the 1986/87 sites (Figure 3-5) indicate considerable changes in invertebrate communities since the earlier surveys. Both Order richness and SID were generally lower during the earlier sampling period compared to 2015/16, with the exception of the feldmark F2 site, where 1986/87 samples were more speciose and more diverse. Diversity in the tall grassland site P2 and herbfield H1 were also lower in 2015/16 sampling, though richness was much higher.

Mice prey species that were predicted to respond favourably to mice removal, such as Coleoptera (beetles), Lepidoptera (moths) and spiders (Araneae), were trapped via pitfalls in 1986/87 and again in 2015/16 at seven sites across five vegetation types (Table 3-3). Coleoptera abundance was inconsistently higher in 1986/87, whereas Araneae were trapped in much higher numbers during the 2015/16 sampling. Lepidoptera were rarely trapped in both sampling events, present only in the feldmark F2 site.

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Figure 3-5 a) Order richness (summed across 20 sites) and, b) Simpson’s Index of Diversity of pitfall trapping (Order level) at seven invertebrate monitoring sites at Macquarie Island that were first sampled in 1986/87 (prior to mammal eradication) and repeat sampled in 2015/16 (post mammal eradication).

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Table 3-3 Abundance of Coleoptera, Lepidoptera and Araneae in pitfall traps sampled at seven sites at Macquarie Island in 1986/87 (prior to mammal eradication) and 2015/16 (post- mammal eradication).

Coleoptera Lepidoptera Araneae 1986/87 2015/16 1986/87 2015/16 1986/87 2015/16 P1 Tall grass 25 1909 0 0 151 124 P2 Tall grass 19 7 0 0 105 280 S1 Stilbocarpa 2426 277 0 0 84 175 H1 Herbfield 8 6 0 0 27 123 H2 Herbfield 2 1 0 0 42 191 F1 Feldmark 4 3 0 0 8 120 F2 Feldmark 4 0 1 4 28 127

DISCUSSION

When monitoring ecosystem responses following an eradication, it is critical to first identify the objectives of the management intervention. In this case, the facilitation of the “recovery” of macro-invertebrates on Macquarie Island was explicit. However, no mechanisms were put in place to assess the success (or otherwise) of this objective. Here, our preliminary study tackles the issue of how to effectively survey a suite of invertebrate species on a Southern Ocean island to detect recovery and response of invertebrates after an eradication event, and informs the selection of appropriate survey methods for specific species.

One of the clearest findings of our study was that pitfall traps collect the greatest abundance and richness of invertebrates, particularly Collembola, although they were the least diverse. Despite the difficulties in comparing abundance and sampling effort across different techniques (for example, the longer deployment time of pitfall traps compared to other trapping techniques), it is apparent that different trapping methods are more effective at capturing certain taxonomic groups. This is based on the functional traits, behaviours and preferred habitats of different taxa. For example, Psocoptera were primarily collected from litter samples, as they are detritivores with a preference for damp conditions under vegetation (Greenslade 2006). However, some were also collected during vegetation sweeping, where they occur in smaller numbers under leaves (Greenslade 2006). Tardigrades and Copepods were collected principally via pitfall traps, most likely due their existence in soil or at the soil surface, particularly in moist sites. Their small size makes them unlikely to be detected through other trapping means. Cosmopolitan groups like Coleoptera, Collembola and Acarina

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were detected by all trapping methods. For the Collembola, their ubiquity in many samples exemplified their abundance and diversity on the island, with 35 species recorded (Phillips, et al., 2017). They also occur in a variety of habitats, from soil-dwellers to canopy species (Greenslade 2006; Terauds et al. 2011). Similarly, the collection of predatory Staphylinidae coleopterans across all trapping methods suggests this group are wide-ranging across vegetation, possibly to maximise opportunities to encounter prey. Isopoda, Annelidae and Platyhelminthes were collected by all means except sweeping (with a few exceptions), in line with their cryptic habits under vegetation, close to the soil surface and in litter (Greenslade 2006).

Knowledge of the target group is critical to inform the experimental design of trapping. For example, and perhaps counter-intuitively, sweeping did not yield high numbers of moths or flies. One reason may be that many resident flies on Macquarie Island are flightless and largely stay close to the ground (Greenslade 2006). Furthermore, the endemic moth mawsoni, which is not nocturnal, is known to drop to the ground when dislodged from vegetation (i.e. by sweep nets) (Jackson 1995), and often stays close to the ground, taking shelter in winds over 10 km/hr (Greenslade 2006). Sweeping can only occur during low wind conditions, however winds are typically high on the island (Pendlebury and Barnes 2007), dispersing many taxa (both flightless and flying) (Hawes and Greenslade 2013). The moth’s flight is stimulated by rain, however sweeping is not possible during rains as wet vegetation renders the sweep net ineffective. Such background understanding of target taxa and the environment informs the design and interpretation of trapping surveys.

If the monitoring or management objectives focus on a particular group or species it is important to consider the varying effectiveness of trapping methods (Zou et al. 2012). For example, mice on SOI prey mainly on invertebrates, especially spiders, moths, beetles, aphids, Orthoptera (e.g. crickets), snails and earthworms (Copson 1986; Crafford and Sholtz 1986; Rowe-Rowe et al. 1989; Le Roux et al. 2002; Jones et al. 2003c; Angel et al. 2009; St Clair 2011; Russell 2012). Copson (1986) identified that mice on Macquarie Island had a particular preference for spiders (67% of 108 mouse stomach contents), caterpillars of the endemic moth E. mawsoni and, to a lesser extent, other invertebrates such as beetles and dipteran larvae. Therefore, increases in these taxa following mouse eradication and the removal of predation pressure could be anticipated. Our preliminary comparisons provided some support for this hypothesis (see below). To measure the response of invertebrates

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preyed upon by mice on Macquarie Island, our results indicate that pitfall trapping is effective for spiders and beetles, and is therefore the most efficient mechanism for assessing their recovery. Monitoring of moths will require greater consideration and ongoing effort, as they were not detected in high numbers by any trapping method during the 2015/16 season. Comparisons to historic datasets are vital to detect responses to eradication. It is important to consider there may be different responses and recovery times in different species. Again, although our comparative analyses are only preliminary, they do show a higher abundance of spiders in pitfalls in 2015/16 compared with 1986/87 pitfalls, across all sites. There is a high likelihood that this is related to the eradication of mice, given spiders were a major prey item (Copson 1986). However, beetle abundance did not change consistently between the two trapping events, with numbers trapped varying across sites and between years (Table 3). One possible reason is that Staphylinidae beetles (which comprised all of the beetles caught) can occur in dense numbers where rich detritus or rotting material is present on coastal terraces in vegetation (Greenslade 2006). As a result, they can be very abundant in an individual sample from one event, and then absent in others at the same site. Vegetation recovery is slow, and therefore, if beetle abundance is driven by vegetation, there will be a delay for beetles to respond to eradication. For the moth E. mawsoni, despite anecdotal reports of increased abundance across the island, our preliminary data do not show this. The moth pitfall counts were similar in 1986/87 and 2015/16, with adults rarely trapped, which is consistent with other studies on Macquarie Island (Jackson 1995; Potts 1997; Stevens et al. 2010; Hawes and Greenslade 2013). The low number of adults in our data could be due to the timing of our sampling regime, i.e. our trapping effort was low in late December and early January – the time when adults are most abundant and active (Watson 1967). Davies and Melbourne (1999) captured many adults using yellow pan traps. With this knowledge, we have added this method to our trapping regime for future seasons of the invertebrate monitoring project to identify change. We also extended our future sampling to occur later in the summer, between January-March, to identify seasonal changes in species, improve likelihood of encountering different species, and improve chances of detecting different life stages in species (such as the moths and moth larvae). Species life history must be considered to when designing trapping to inform responses to management.

Terrestrial invertebrate communities that are dependent on or restricted to specific vegetation or habitat type are hypothesised to be most likely to be impacted by rabbit grazing on Macquarie Island (Parks and Wildlife 2009). Vegetation has undergone considerable changes

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between 1986/87 and 2015/16 (Copson and Whinam 1998; Bergstrom et al. 2009; Shaw et al. 2011). Our preliminary results highlight the potential utility of historical data, when combined with targeted and appropriate sampling techniques, to explore the relationship between vegetation and invertebrates. Overall, there appears to be an increase in richness and diversity from 1986/87 to 2015/16. During the period of the initial sampling in 1986/87, rabbit numbers and the commensurate vegetation damage were relatively high (Terauds et al., 2014), which may explain the low numbers of vegetation-dependant invertebrates. Herbfields were favoured by rabbits and heavily impacted by grazing (Scott 1988; Selkirk et al. 1990; Copson and Whinam 1998). Herbfield invertebrate communities were particularly low in richness and diversity in 1986/87. Feldmark communities vary little between 1986/87 and 2015/16, most likely as rabbit impacts were low in this high-altitude vegetation group (Copson and Whinam 1998).

Another important consideration of these comparisons is that the historical survey data we accessed were generally based on higher taxonomic groupings, which may impact our ability to detect subtle changes in invertebrate communities over time (e.g. Grimbacher et al. 2008). Higher taxonomic groupings, unsurprisingly, do not necessarily reflect the finer details of invertebrate community assemblages, nor nuanced changes in their structure and responses (Grimbacher et al. 2008; Driessen and Kirkpatrick 2017) and may aggregate species that have different ecological or functional traits and responses to disturbance (Lenat and Resh 2001; Heino and Soininen 2007; Schipper et al. 2010). A limitation of using historical datasets is that often clarification and further detail is simply not available.

Identification of specimens to fine taxonomic resolution, such as to species level, takes considerable time. While we focussed on higher-level taxon here, our forthcoming analyses at finer taxonomic resolution, (such as to family, and for some groups, species) will provide further insights on trapping efficacy, survey design and most importantly, invertebrate community changes over time. However, there is also good evidence to suggest that higher-level identification can be appropriate surrogates for species and effective for detecting major disturbance events on invertebrate community structure, particularly where there are significant environmental perturbations or gradients (Driessen and Kirkpatrick, 2017; Bevilacqua, et al., 2012; Włodarska-Kowalczuk and Kędra, 2007). Sorting samples to higher taxonomic resolution is often more practical and cost-effective as it requires less training, and maximises the potential for swift sample processing (Driessen and Kirkpatrick,

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2017). The selected taxonomic resolution must be balanced between available resources and the value of results - the decision ultimately depending on the study objectives (Driessen and Kirkpatrick 2017). It is fundamentally important to decide at the outset which invertebrate taxa, (if not all of them), are the focus of the monitoring, and what taxonomic resolution will best meet the objectives of the monitoring. For example, the varying ranges and habitat associations of the five Staphylinidae beetle species on Macquarie Island are not represented when grouped to the Coleoptera order in our data. A second example is the ubiquitous and numerous Collembola (springtails), that when aggregated to Order, fail to highlight the very different species trapped by each medium, such as those that were trapped via sweeping which inhabit the canopy, foliage and flowers in vegetation, and those edaphic groups trapped via pitfalls that either inhabit the soil or live close to the surface. Such details are important to our Macquarie Island monitoring objectives as we assess invertebrate communities in recovering vegetation.

The availability of historical data greatly enhances the power of long-term effective monitoring. In this instance, considerable time was invested in tracking down historical datasets and their metadata. Our future work will include in-depth analysis of contemporary survey results in relation to a broader suite of historical data. Whether historical data are available at the outset or not, establishing a baseline from which to measure changes into the future is critical for long-term monitoring, for making informed management decisions, and assessing management success. Our preliminary results demonstrate that invertebrate monitoring in a post-vertebrate eradication ecosystem can yield important and promising results. Effective monitoring for invertebrates also leads to improved surveillance for non- native species arrivals and potential non-native species impacts. Our future work includes the collection of two additional years of invertebrate surveys (2016/17 and 2018) across Macquarie Island and the establishment of four additional invertebrate monitoring sites to improve island and vegetation community coverage. We also employ additional trapping methods (vegetation beating and yellow-pan trapping), and use Berlese funnels in the 2016/17 and 2018 surveys for more efficient litter processing. These improvements combined, will further develop a baseline knowledge of invertebrate communities on Macquarie Island and inform future monitoring. This work will provide a comprehensive snapshot of ecosystem function and recovery following vertebrate eradication. We will use these results to develop and propose an efficient means of invertebrate monitoring using

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specific taxa or groups as biological indicators of broader ecosystem changes, to enable robust and efficient monitoring into the future.

ACKNOWLEDGMENTS

We thank Michael Driessen for input to research design and analyses. We thank Jasmine Lee for helpful comments on the draft manuscript. We thank Kimberley Mitchell, Marcus Salton, George Brettingham-Moore, Rowena Hannaford, Jacqueline Comery and Penelope Pascoe for their assistance in the field with invertebrate trapping. We thank the Australian Antarctic Division for logistic support and the Tasmanian Parks and Wildlife Service for granting access to the island and permits to collect invertebrates (under Scientific Permits FA15234). This study was supported by funding from the Australian Government’s National Environmental Science Programme through the Threatened Species Recovery Hub and the Australian Antarctic Science program (AAS 4305).

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Chapter 4 | Island invasive mammal eradications and invertebrate conservation

Melissa J Houghton, Aleks Terauds, James C Russell, Michael Driessen, and Justine D Shaw

ABSTRACT

Islands support disproportionally high biodiversity and many unique species. Invasive mammals, particularly rodents, have invaded many of the world’s islands with devastating impacts on their insular ecosystems, particularly rodents. In response, eradications of invasive species have increased in number, scale and success. ‘Recovery’ of the ecosystem is often assumed to follow. However little attention has been given to quantifying the conservation benefit of eradication programs at an ecosystem scale, or monitoring the response of cryptic species such as invertebrates. Although invertebrates rarely incite conservation interest in themselves, they are abundant, diverse and critical to ecosystem function, making them ideal bio-indicators of environmental change. They may be used as tools to assess the return-on- investment for these large-scale conservation programs.

Recent mammal eradications on sub-Antarctic Antipodes Island (New Zealand) and Macquarie Island (Australia), targeted the removal of invasive mammals for conservation benefits. House mice (Mus musculus) were the sole invasive mammal on Antipodes Island, while Macquarie Island was invaded by M. musculus, black rats (Rattus rattus) and the European rabbit (Oryctolagus cuniculus). On both islands, the invertebrate communities are relatively well described, the invertebrate taxa that were preferred prey of rodents is well known, and historic empirical invertebrate data is available. Hence, we conducted pitfall trapping at historically monitored sites to identify fluctuations in invertebrate populations through time and following eradication. We assessed changes in richness, diversity, and abundance of macro-invertebrate groups preferentially eaten by rodents.

We found increased abundance of preferred mouse prey species on Antipodes following mouse eradication, but post-eradication responses of invertebrates on Macquarie Island were more variable. While these findings demonstrate that rodent eradications aid invertebrate conservation on islands, the recovery on Macquarie Island appears complicated by concurrent invasive mammalian herbivore removal and the associated impacts of habitat recovery. Our

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findings suggest that novel ecosystems may arise in the wake of mammal eradications. We conclude that restoration of invertebrate communities may take some time to be realised and that passive restoration may not serve all groups of taxa equally, as non-native invertebrate species can also benefit from the removal of invasive mammals.

INTRODUCTION

Invasive mammal eradications have increased in scale and success (Glen et al. 2013; Jones et al. 2016; DIISE 2018; Martin and Richardson 2017), but monitoring of post-eradication ecosystem responses, or at least the reporting of such monitoring, remains scarce (Courchamp et al. 2003; Zavaleta 2002; Caut et al. 2009; Jones et al. 2016; Towns 2018; Bird et al. 2019). Typically, it is assumed that the removal of target pest species equates to a success, and that ecosystem recovery will follow (Prior et al. 2018). Monitoring of charismatic or threatened species like seabirds sometimes occurs around eradication programs (e.g. Watari et al. 2013; Buxton et al. 2014; Le Corre et al. 2015; Croll et al. 2016; Brooke et al. 2018). However, there are few published examples that document the effects of eradication on invertebrate communities and their function in recovering ecosystems (Houghton et al. 2019a). Invertebrates are speciose, critical to ecosystem function, and sensitive to environmental variations due to their size and short generation times, making them ideal indicators of change (Kremen et al. 1993; McGeoch et al. 2011; Gerlach et al. 2013). For example, they have often been used as tools to assess restoration of rehabilitated mine sites (e.g. Longcore et al. 2003; Smith et al. 2016, Bandyopadhyay and Maiti 2019). Accordingly, invertebrate monitoring could also be a useful tool to assess the ecosystem-scale conservation benefit of eradications.

Invasive rodents have considerable impacts on islands globally (Atkinson 1985; Courchamp et al. 2003; Towns et al. 2006; Jones et al. 2008), including on invertebrates (St Clair 2011; McClelland et al. 2018). Many extinctions on islands can be attributed to rats, whose omnivorous diets affect plants, invertebrates, reptiles, mammals and birds (Towns et al. 2006; Kurle et al. 2008; Drake and Hunt 2009; Fukami et al. 2006; Mulder et al. 2009; Pisanu et al. 2011; Wardle et al. 2009). Mice eat seeds but can be particularly damaging to invertebrate communities (Angel et al. 2009), and also seabirds (Wanless et al. 2007; Dilley et al. 2015). On Southern Ocean Islands (SOI), the impacts of rodents on invertebrates can be severe (Courchamp et al. 2003; Chown et al. 2008; Houghton et al. 2019b). They preferentially prey

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on larger-bodied invertebrates, drastically reducing their abundance (Angel et al. 2009; St Clair 2011). They alter body size ranges (Crafford and Scholtz 1987; Chown and Smith 1993), indirectly effect nutrient cycling and other ecosystem processes (e.g. Smith and Steenkamp 1992a, 1992b; Klok and Chown 1997; Fukami et al. 2006; Smith 2008; Mulder et al. 2009), and transform invertebrate communities, driving some island-endemic invertebrates to local extinction (Marris 2000; Chown et al. 2002). Apart from rodents, numerous other mammals have invaded SOI (Headland 2012), but their effects on invertebrates are largely unknown (Houghton et al. 2019b).

Given the increasing recognition of their conservation benefits, a number of rodent eradications across the SOI have either been implemented (e.g. Campbell Island – McClelland and Tyree 2002; Macquarie Island - Springer 2016; Antipodes Island – Horn et al. 2019; South Georgia Island - Martin and Richardson 2017) or are in preparation (Auckland Island – Russell et al. 2018; Gough Island – Parkes 2008; Cuthbert et al. 2011; Marion Island – Preston et al. 2019). Despite research that indicates considerable impacts on invertebrate communities on SOI (Houghton et al. 2019a), to date there have been no published studies measuring how, or if, they respond when rodents are removed, or how this might affect the recovering ecosystem.

The recent eradications of rodents from Antipodes Island (New Zealand) and Macquarie Island (Australia), provide unique opportunities to investigate invertebrate responses to predator removal and ecosystem restoration, ultimately providing a means to assess conservation benefit. The two islands share numerous taxa and are more similar in flora and insect fauna than most other SOI (Shaw et al. 2010). On Antipodes Island, house mice (Mus musculus) were the sole target of the recent eradication program (Elliot et al. 2015), which was declared a success in 2018 (Horn et al. 2018). Stomach content analysis, scat isotope analysis and pitfall trapping comparisons with uninvaded offshore islands identified the invertebrate taxa that were the preferred prey of mice (Patrick 1994; Marris 2000; McIntosh 2001; Russell 2012; Russell et al. 2020). On Macquarie Island, house mice were eradicated in 2014, concurrently with ship rats (Rattus rattus) and European rabbits (Oryctolagus cuniculus) (Springer 2016). Diet analysis of rodents on Macquarie Island (Copson 1986), and evidence of feeding behaviour (Brothers 1984; Shaw et al. 2005), determined rodent preferred food. Such dietary details for rodents on both islands were complimented by comprehensive documentation of the terrestrial invertebrate fauna (e.g. Patrick 1994, Marris

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2000, McIntosh 2001 for Antipodes Island; Watson 1967, Greenslade 2006 for Macquarie Island). This existing knowledge, combined with the biogeographic similarities between the islands (Shaw et al. 2010) and contemporary survey data, enable us to examine and compare the response of invertebrate communities to island eradication programs.

To test our hypothesis that invasive rodent eradications benefit invertebrates on SOIs, particularly invertebrate taxa preyed upon by rodents, we quantified (at the taxonomic level of order), invertebrate abundance, richness and diversity on Antipodes Island and Macquarie Island before and after rodent eradication. Providing a means of assessing the conservation return for these costly conservation initiatives is important given that eradications on both Macquarie Island and Antipodes Island were undertaken for conservation and restoration. By exploring the effectiveness of the two eradication programs for invertebrate communities on biogeographically similar islands i.e. between a simple, single predator species eradication on small Antipodes Island and a complex multi-species eradication on large Macquarie Island, we quantify how mammal eradication contributes to invertebrate conservation and how two insular invertebrate communities are responding to the management strategy of passive restoration following eradication.

METHODS

The study islands

The Antipodes Island group (49˚41’S; 178˚48’E) consists of seven islands in New Zealand’s sub-Antarctic lying roughly 733 km southeast of New Zealand (Horn et al. 2019), which are less than 0.5 million years old (Scott et al. 2013). They consist of the larger main Antipodes Island (2 205 ha) and several offshore islands and rock stacks, that are listed as World Heritage and managed by the New Zealand Department of Conservation (Elliot et al. 2015; Figure 4-1). Macquarie Island (54.62° S, 158.86° E), is 12 870 ha in area and approximately 0.6-0.7 million years old (Adamson et al. 1996; Figure 4-2Error! Reference source not f ound.). It is situated in the Southern Ocean approximately 1500 km southeast of Tasmania, Australia, 1000 km southwest of New Zealand, and 240 km north of the Antarctic Polar Frontal Zone (Greenslade 2006). It is also a World Heritage area, managed by the Tasmanian Parks and Wildlife Service (Copson and Whinam 2001). On both Macquarie Island and Antipodes Island, cool, wet and windy conditions prevail, with regular periods of cloud, fog

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and rain (Selkirk et al. 1990; Taylor 2006). However, Antipodes Island is one of the warmer and drier of the Southern Ocean Islands (Weigelt et al. 2013), with annual temperatures ranging from 2-13˚C (Taylor 2006), whereas Macquarie Island is distinctly equable at 3-7˚C year round (Pendlebury and Barnes-Keoghan 2007). On both islands, the highest peaks are similar (c. 400 m a.s.l - Greenslade 2006, Russell 2012). Sea surface temperature surrounding the Antipodes Island group is also warmer than at Macquarie Island (Chown et al. 1998). Antipodes Island is dominated by tussock and sedge grasslands (Poa and Carex spp.), with ferns and occasional woody shrubs such as Coprosma spp. (Russell 2012). Macquarie Island lacks woody shrubs, and is dominated by tall tussock grasslands, short grasslands, feldmark and herbfields (Selkirk et al. 1990). Typical of SOI (Convey 2007), these islands have no native land mammals, amphibians or reptiles. However, they host several species of seals and dozens of breeding seabird species, numbering in the millions (Tennyson et al. 2002; Terauds and Stewart 2008). On Antipodes Island, there are also four native land birds, whereas on Macquarie Island the two endemic land birds have become extinct as a result of introduced mammals (Robinson and Copson 2014). Three non-native bird species have naturalised on Macquarie Island, all self- introduced from New Zealand in the last 100 years (Copson and Whinam 2001).

Overview of invertebrates

Marris (2000) reports 150 species of Insecta from 12 orders and 20 species of Arachnida from the Antipodes Islands group, including 16 from the order Araneae (spiders), three Pseudoscorpionodea (pseudoscorpions), and one ixodid Acarina (mites). However, considerably more species are likely to occur from groups not detailed in Marris (2000), such as Chilopoda (centipedes), non-ixodid Acarina, Isopoda (woodlice), Amphipoda (landhoppers), and Collembola (springtails) (Marris 2000) (here we refer to the class Collembola and subclass Acarina, as single invertebrate orders). Thus, 22 taxonomic classes or orders of free-living terrestrial invertebrates are known from Antipodes Island (Figure 4-3) (hereafter referred to as ‘orders’), but the exact number of invertebrate species is not confirmed (this work; Marris 2000). Diptera (flies), Coleoptera (beetles) and Lepidoptera (moths) are the dominant free-living insect fauna (Marris 2000). Ten per cent of insects and 13% of are endemic to the Antipodes Islands (Marris 2000).

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Figure 4-1 The Antipodes Islands. Long-term invertebrate pitfall trapping sites are marked with a star symbol. (Map source: Russell 2012).

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Figure 4-2 Macquarie Island. Long-term invertebrate pitfall trapping sites are marked with a grey circle.

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On Macquarie Island, there are more than 350 invertebrate species across 28 orders (21 orders of arthropods), including 14 aquatic species (Greenslade 2006). Of the terrestrial species, 24 species (nine orders) are from class Insecta, 119 species of Acarina, 34 species of Collembola, three Crustacea and three Araneae (Greenslade 2006; Phillips et al. 2017). Macquarie Island and Antipodes Island share 18 free-living terrestrial invertebrate orders or classes (Figure 4-3), and at least 12 free-living species (of which six are native to both islands), plus the host-dependant species (Acarina - Ixodes uriae)(Marris 2000). More shared species are likely to occur, however greater species-level identification is required for some of the Antipodes Island fauna, particularly for the Acarina and Collembola.

Non-native mammals and impacts

The main island of the Antipodes Island group was invaded by mice, suspected to have arrived via a shipwreck in the 19th century (Taylor 2006). Prior to eradication in 2016, mice were highly abundant and widespread across the island, as the sole established invasive vertebrate species (Russell 2012; Horn et al. 2019). They heavily impacted invertebrate fauna, preferring larger prey species such as beetles, moths, amphipods, centipedes, pseudoscorpions, larvae, spiders and worms (Patrick 1994; Marris 2000; McIntosh 2001; Russell 2012; Russell et al. 2020). As a result, some invertebrate species appear to have become locally extinct or drastically reduced in number, such as the unidentified weta species (Orthoptera), and beetles Loxomerus brevis, Oopterus clivinoides, and Pseudhelops spp. (Marris 2000; Russell 2012).

First discovered in 1810, Macquarie Island’s early human history centred around seal and penguin harvesting, during which time many non-native species were introduced, both intentionally and inadvertently, including rabbits, rodents, cats (Felis catus), dogs (Canis lupis familiaris), and wekas (Gallirallus australis scotti) (Cumpston 1968). All except for rodents and rabbits were removed by 2000 (Robinson and Copson 2014). Mice and rats were first reported on the island at the end of the 19th century (Cumpston 1968). Rats ate mostly plant material, supplemented by vertebrate material (carrion, seabird eggs etc.), small amounts of Oligochaetae (worms), some moth larvae, and spiders (Copson 1986; Shaw et al. 2005). They also preyed upon burrow nesting seabirds (Brothers and Bone 2008). Mice mostly ate invertebrates, supplemented by plant material, preferentially preying on spiders, moths and fly larvae (Copson 1986). Through burrowing and grazing, rabbits caused

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widespread habitat destruction and landscape denudation (Scott and Kirkpatrick 2008; Terauds et al. 2014).

Experimental design

We designed our study to compare pre- and post- eradication invertebrate communities on Antipodes Island and Macquarie Island. Both islands have supported rodents for over 100 years (Cumpston 1968; Taylor 2006). While there are technically no control data for either island (e.g. not surveys were conducted pre-eradication when rodents were not present), previous studies in the Antipodes Island group comparing the main Antipodes Island with uninvaded offshore islands have shown that mice significantly impact invertebrate communities (Marris 2000; McIntosh 2001; Russell 2012; Russell et al. 2020).

Pre-eradication datasets

On Antipodes Island, five sites spanning from the coast to the top of the highest peak on Antipodes (Mt. Galloway) were sampled in summer 2011 (January), and winter 2013 (July) (reported in Russell 2012 and Elliot et al. 2015). These sites were re-surveyed in winter 2016 (July) (just prior to eradication) (Russell et al. 2020).

On Macquarie Island surveys of were concentrated in the north of the island, in close range of the research station (Figure 4-2). The oldest dataset is derived from eight sites surveyed during the 1986-87 season (December- January) by Greenslade (Greenslade 1987; hereafter referred to as 1986 samples/sites). Four of these sites were repeat sampled by Disney in the 1992-93 season (December-January, reported in Stevens et al. 2010, hereafter referred to as 1993 samples/sites). In 2009 (October-November), three 1993 sites and four 1986 sites were resurveyed (Stevens et al. 2010, hereafter referred to as 2009 samples/sites). The total number of trapping days varied during each historical trapping season (more details can be found in Houghton et al. 2019b).

Post eradication datasets

On Antipodes Island, all of the existing survey sites were resurveyed in the summer of 2018 (January-February), approximately 18 months after the mouse eradication program was completed (Figure 4-1).

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Figure 4-3 Free-living terrestrial invertebrate orders/ classes present, trapped and analysed in this study from Antipodes Island and Macquarie Island, illustrating taxonomic groups and species shared between both islands.

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On Macquarie Island, in total, ten historical sites were resurveyed, all in the north of the island (Figure 1). Seven of the 1986 sites established by Greenslade were resurveyed, which also included all four 1993 sites surveyed by Disney. We also resurveyed three sites established by Stevens in 2009. This sampling commenced in 2015 (November-December), approximately 18 months after the 2014 declaration of eradication success, and approximately 4 years since the last rabbit was seen. Contemporary sampling was repeated in 2016 (October-December) and 2018 (January – February).

Sampling

The same sampling method was used on Antipodes Island in 2011, 2013, 2016 and 2018 (Russell 2012, Elliot et al. 2015; Russell et al. 2020). At each site, 10 pitfall traps were deployed (80 mm diameter and 90 mm depth), in a regular 10 m2 grid, spaced more than 10 metres apart, prepared with glycol and a drop of detergent, and collected and reset after 10 days for a further 10 days. Sampling during winter 2013 included a single 10-day trap deployment. The impact of mice on the island’s vegetation over time was considered negligible, and as the vegetation is reasonably uniform across the island (Russell 2012), vegetation was not recorded in pre or post-eradication surveys. Specimens were preserved in ethanol and returned to New Zealand for identification.

Pitfall sampling methodology during 1986, 1993, and 2009 trapping on Macquarie Island varied slightly (see Houghton et al 2019b). For the post eradication sampling pitfall-traps were deployed at the ten historical sites for ~40 consecutive days, with three collection and trap reset events for each trap at each site. At each site, five pitfall traps (70 mm in diameter, 70 mm deep) were placed 5 m apart in a line (a distance apart that mirrored historical sampling), with propylene glycol as a preservative. All specimens were preserved in ethanol and returned to Australia for identification. Given the destructive impact of rabbit grazing on invertebrate habitat on Macquarie Island, site vegetation was recorded for successive historical and contemporary invertebrate surveys. In contemporary surveys, the overall vegetation community was assigned at each site, with further detail obtained by using 10 m x10 m vegetation plots. The five major vegetation communities identified in these sites followed classifications by Selkirk et al. (1990) and included feldmark (plateau), lower coastal slopes dominated by Stilbocarpa polaris (Macquarie Island cabbage), tall grassland (tussock) dominated by Poa foliosa, short grassland (including Deschampsia antarctica,

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Festuca contracta, Agrostis magellanica, Luzula crinita, Uncinia spp.), and herbfield dominated by Pleurophyllum hookeri.

Species identification

Historical samples from both islands were sorted and identified by a range of people using their expert taxonomic skills and available literature. Samples from 2009 were re-identified by Houghton to improve their taxonomic resolution. Nymphs, adults and larvae were identified separately in all historical and contemporary samples, but for the purposes of our analyses they were included in their Order. All contemporary samples from Macquarie Island (2015-2018) and Antipodes Island (2016, 2018) were identified by Houghton.

Many groups of micro-invertebrates identified from Antipodes Island by Houghton in 2016 and 2018 were not consistently identified in the 2011 and 2013 samples. Thus, to facilitate comparisons between years, those groups not consistently identified across years were removed prior to the analyses. These groups included Psocoptera (booklice), Thysanoptera (thrips), and micro-invertebrates. Micro-invertebrates included Acarina (mites), Collembola (springtails), Copepoda (copepods), Nematoda (nematodes) and Tardigrada (tardigrades). Insect groups that are host-dependant (not free-living), such as Siphonaptera (fleas) and Phthiraptera (lice) were also removed from analysis.

Host-dependant Siphonaptera, micro-invertebrates, and species that were not consistently identified between years on Macquarie Island were also removed prior to analyses. These groups included Acarina, Amphipoda (amphipods), Collembola, Copepoda, Nematoda, and Tardigrada.

Statistical analyses

Given that historical samples were largely identified to order level, our analyses were conducted at the taxonomic resolution of order/class (hereafter referred to as ‘order’) to facilitate comparisons between the years. Previous assessments have provided good evidence that higher level taxonomic identifications perform well for invertebrate orders comprising of few abundant species (e.g. Driessen and Kirkpatrick 2017). We found the invertebrate fauna trapped in pitfalls on both islands largely fit this criteria. To counter the variable length of trapping days per season and for different sites, pitfall trap catches on both islands were

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transformed to trap catch-per-day (standardised abundance) (sensu Bowden et al. 2018), by dividing the total catch per taxa by the number of days the trap was open. Where possible, standardised abundance was calculated for each individual trap, over each trapping period (i.e. between setting and re-setting), at each site. Historical data on Macquarie Island had previously been pooled into total catch over each study period. For these data, standardised abundance was therefore calculated for the total study period.

We calculated the percentage representation of taxa per sampling year per island and plotted log transformed standardised abundance for each year to understand how overall pitfall catch differed temporally. Percentage was calculated by dividing the total order catch of the trapping year by the total catch of the year and multiplying by 100. To explore the relationship between year, invertebrate abundance and diversity from trapping on both islands, we used both non-parametric tests (Kruskal-Wallis with post-hoc Wilcoxon-rank- sum test), generalised linear models (GLMs) and generalised additive models (GAMs). The non-parametric tests were used to assess differences between years for standardised abundance and performed in R version 3.5.2 (R Core Team 2017). Non-parametric tests were used because Shapiro-Wilk Normality tests and observations of QQ-plots indicated these data were not normal. GLMs and GAMs were fitted using the mgcv package (Wood 2011). Model fits (i.e. normal distribution and heteroscedasticity of variance) were assessed using standard diagnostic plots (QQ-plots, residuals vs linear predictors, residual histograms). Using GAMs fitted with a negative binomial distribution, we examined how island invertebrate assemblages have changed over time on both islands in the context of order richness. GLMs fitted with a gamma distribution were used to model changes in Simpson’s Index of Diversity (hereafter referred to as ‘diversity’). In these models, ‘richness’ or ‘diversity’ were the response variables, with ‘year’ as the predictor. To determine if the response was similar between the taxonomic groups on each island, we used GAMs with standardised abundance as the response, and the interaction between ‘taxa’ and ‘year’ as the explanatory variable. To compare invertebrate orders that were shared by both islands, we tested the response of standardised abundance with the interaction between ‘taxa’ and ‘eradication status’ (i.e. we pooled pre-eradication samples and post-eradication samples into two groups for each island).

Given the anticipated influence of vegetation on invertebrate communities on Macquarie Island, another suite of GAMs were fitted using standardised abundance, richness and diversity as response variables, with ‘year’, ‘vegetation’ and their interaction term as

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predictors, fitted with a negative binomial distribution. We used partial residual plots to show the relationship between each predictor and the response variable (given the other independent variables are also in the model) and these plots were generated using the R- package visreg (Breheny and Burchett 2013). For interaction models, we used the 95% confidence intervals, as indicated by the partial residual plots, to identify significant differences in abundance classes of invertebrate orders. We present the results of the best models as indicated by the lowest AIC.

RESULTS

Overview

From Antipodes Island, more than 4,200 individual invertebrates from the 2016 winter pre- eradication pitfall trapping and more than 25,000 individuals from 2018 summer post- eradication monitoring were identified in this study. Including samples previously identified from 2011 and 2013, a combined total of 33,855 individuals from 22 orders comprised our initial dataset. Once micro-invertebrates and non-free-living groups had been removed, 13 orders remained for analyses, comprised of 29,088 individuals. Coleoptera (beetles), Diptera (flies), Isopoda (woodlice) and Araneae (spiders) dominated (Table 4-1).

Non-parametric tests confirmed significant differences between the standardised abundance of invertebrates between years on Antipodes Island, (X² (df = 3) = 92.807, p <0.001), with post-hoc results showing significant abundance differences between 2011 and 2013 (p<0.001), and 2016 (p=0.04), and between 2013 and 2016 (p=0.003). Significant differences were found between post eradication abundance in 2018, and all pre-eradication sampling (all p<0.001).

From Macquarie Island, more than 143,830 individuals from 18 invertebrate Orders were identified from historical and contemporary pitfall traps. A total of 59,200 of these were identified from 2015-2018 samples and 86,630 were re-identified from historical pitfall traps (mainly Collembola – springtails) from 2009. The most abundant groups identified across all historical years and 2015 contemporary sampling were the Collembola and Acarina (mites). Due to their exceptionally high numbers and our focus on macroinvertebrates, for practical purposes mites and springtails were not identified or counted in 2016 and 2018 samples.

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Table 4-1 Percentage of 13 invertebrate orders detected each year through pitfall sampling on Antipodes Island for the three years prior to mouse eradication (2011, 2013, 2016) and one year following eradication in 2018.

Order Common name Summer Winter Winter Summer for Antipodes Is. 2011 2013 2016 2018 members of this order Amphipoda Landhoppers 0.1 - 2.1 0.4 Annelida Worms - 0.3 0.3 0.8 Araneae Spiders 7.1 3.4 6.6 6.5 Chilopoda Centipedes 0.2 0.1 0.1 1.4 Coleoptera Beetles 22.8 67.4 39.1 10.5 Diptera Flies 59.3 8.4 17.7 0.9 Mollusca Snails 2.2 1 4.4 0.4 Hemiptera Aphids 0.7 1 0.5 - Hymenoptera Wasps - 0.1 0.1 - Isopoda Woodlice 5.1 16.8 28.2 77.9 Lepidoptera Moths 0.1 - 0.1 - Neuroptera Lacewings - 1.3 - - Pseudoscorpionida Pseudoscorpions 2.4 0.4 0.6 1.2

After removal of micro-invertebrates and non-free-living groups, eleven orders remained for analyses (Table 4-2), comprised of a combined total of 48,106 individuals. Following eradication, pitfall catches were more diverse (Table 4-2). However, beetles and spiders dominated across all years, followed to a lesser degree by flies and molluscs. Spiders made up a high percentage of the 1986 catch compared to other years, as did beetles in 2009-10. By percentage, flies dominated the 1993 catch, were virtually non-existent in the 2009-10 samples, then made up around 10% of the catch in post-eradication years.

Non-parametric tests confirmed significant differences between the abundance of invertebrates between years on Macquarie Island (x² (df = 5) = 76.299, p <0.001). Post-hoc results indicated significant differences in abundance between 1986 and 2009 (p=0.04), 1993 and 2016 (p=0.03), and between 1993 and 2018 (p<0.001). In addition, results of 2009 sampling immediately prior to eradication were significantly different to post-eradication

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results from 2015 (p= 0.03), 2016 (p<0.001) and 2018 (p<0.001). Each contemporary sampling year (2015, 2016, 2018), was different in abundance from the others (all p<0.001).

Table 4-2 Percentage of the catch for 11 invertebrate orders detected each year through pitfall sampling on Macquarie Island for the three years prior to mammal eradication (1986, 1993, 2009) and the three years following eradication (2015, 2016, 2018).

Common name of

Macquarie Island Order members of Summer Summer Summer Summer Summer Summer this order 1986-87 1992-93 2009-10 2015 2016 2018 Annelidae Worms 1.6 1.5 1.4 3.8 2.3 1.8 Araneae Spiders 68.3 38.1 6.1 30.1 20.8 25.4 Coleoptera Beetles 18.0 32.6 87.6 38.6 57.7 51.5 Diptera Flies 8.9 25.2 0.2 10.5 7.3 7.4 Hemiptera Aphids 0.7 - 0.2 0.1 0.1 0.4 Hymenoptera Wasps - - - - 0.1 - Isopoda Woodlice - - 2.4 3.5 2.2 1.1 Lepidoptera Moths 0.2 0.7 - 0.1 0.1 0.2 Mollusca Molluscs 2.1 0.7 1.0 10.6 7.3 10.2 Psocoptera Booklouse - - 0.4 0.7 0.5 1.0 Thysanoptera Thrips 0.2 1.1 0.6 2.0 1.6 1.0

Richness

There was a significant difference in order richness between survey years on Antipodes Island (X² (df = 3) = 61.163, p <0.001), with increased richness in 2018 compared to all previous sampling years (p = <0.001, Z = 3.043) (Figure 4-4). Order richness did not differ significantly between 2011 and 2016.

There was also significant difference in order richness between survey years on Macquarie Island (X² (df = 5) = 32.829, p <0.001). In the years prior to mammal eradication (1986, 1993, 2009), models identified a declining trend in invertebrate richness and an increasing trend in post-eradication years. (Figure 4). Just prior to the mammal eradication program in 2009, invertebrate richness was significantly lower (p = <0.001) than in 1986. Richness was also significantly lower in 2009 than all in post-eradication samples from 2015, 2016 and

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2018 (p<0.001). Significant differences in richness between 1993 and 2016, 1993 and 2018 (both p=0.05) were detected in the post-hoc tests, and pre-eradication invertebrate richness in 2009 was significantly different to all contemporary sampling years (2015, p = 0.002; 2016 and 2018, p <0.001).

Figure 4-4 Predicted invertebrate order richness (log scale) - for Antipodes Island pre-eradication (summer 2011, winter 2013, winter 2016), and following eradication (summer 2018) and for Macquarie Island pre-eradication (summers 1986, 1993, 2009) and post-eradication (summers 2015, 2016, 2018). Grey shading around the mean indicates the size of the 95% confidence intervals. The short blue lines at the upper and lower margin of the plots are indicative of the number of sampling events. The yellow vertical line represents successful eradication.

Diversity

Diversity initially showed an increase on Antipodes Island following eradication, being significantly lower in 2018 post-eradication samples than in all sampling years prior (p<0.001)(Figure 4-5). Given, Simpson’s index of diversity takes into account the relative abundance of each species and the number of species present, the decrease in diversity on Antipodes may be attributable to the dominance of Isopoda (woodlice) in the 2018 catch (Table 4-1). Non-parametric tests confirmed significant differences between the diversity of invertebrates between years on Antipodes Island (X² (df = 3) = 51.64, p <0.001) and the post- hoc test showed that diversity was greater in 2016 than in 2011 (p=0.008) and least in 2018 compared with all other years (all p< 0.001). On Macquarie Island, diversity did not significantly vary between years (X² (df = 5) = 10.252, p = 0.07) or between pre- and post-

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eradication sampling), largely due to high standard errors in the historical data (Figure 4-5). Though not significant, an increase in the mean occurred between the 2009 sampling (immediately prior to the mammal eradication) and the first post-eradication sampling in 2015. Diversity appeared to be on a declining trend in post-eradication samples.

Figure 4-5 Predicted diversity (Simpson’s Index – log scale) of invertebrates for Antipodes Island pre- eradication (summer 2011, winter 2013, winter 2016) and following eradication in 2018 (summer) and for Macquarie Island prior to eradication (summers 1986, 1993, 2009), and following eradication (summers 2015, 2016, 2018). Grey shading indicates the size of the 95% confidence intervals around the mean. . The short blue lines at the upper and lower margin of the plots are indicative of the number of sampling events. The yellow vertical line represents successful eradication.

Abundance

With largely similar survey effort, the total number of invertebrates following the mouse eradication on Antipodes Island (year 2018), was considerably larger compared to other years (~21,500 individuals, the next largest being summer 2011 with ~4,800 individuals). The post- eradication samples were dominated by Isopoda (woodlice), with nearly 17,000 individuals, whereas in previous years beetles and flies made up large components of the catch (Table 4-1). The abundance of some invertebrate groups on Antipodes were found to vary significantly between seasons, with woodlice, centipedes, spiders, worms and pseudoscorpions in significantly higher abundance during summer sampling (Appendix 2, Figure 1). The post-eradication catch of beetles and spiders were two-and five-fold higher respectively compared to pre-eradication samples (Appendix 2, Figure 2). Amphipods, worms, pseudoscorpions and centipedes, also desirable rodent food, were considerably more

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abundant in post-eradication samples than other years – amphipods by more than threefold, centipedes by more than 30 times, pseudoscorpions by more than twofold, and worms more than 35 times greater (Appendix 2, Figure 2). GAMs predicted significantly higher in abundance in 2018 post –eradication samples for spiders, beetles, pseudoscorpions, and worms compared to pre-eradication sampling (p = 0.05, Figure 4-6; for confidence intervals of predicted abundance classes see Appendix 2, Table 1). Centipedes and amphipods also showed dramatic increases following eradication, however greater uncertainty (represented by larger confidence intervals) around pre-eradication data (due to less individuals trapped), meant that these changes were not significant. Flies, also preferred prey, were shown to decrease in abundance over time, as did aphids. In contrast, woodlice were significantly more abundant following eradication.

On Macquarie Island, worms (Annelida) and flies were a large component of macro- invertebrate catch post-eradication (Table 4-2; Appendix 2, Figure 3). Molluscs (snails and slugs) show increased following the eradication, but not significantly. Beetle abundance was generally high but varied between years. GAMs indicated that flies increased significantly immediately in post-eradication samples (p= 0.05, Figure 4-7; for confidence intervals of predicted abundance classes see Appendix 2, Table 2). Beetles significantly decreased in post- eradication samples, whereas aphids increased. Woodlice successively reduced in abundance each sampling year. Spiders, snails and slugs showed incremental changes in abundance through time, particularly immediately after eradication, however, due to the large standard error in the historical data, except for 2018, these changes were not significant at the 0.05 level. Other invertebrate groups showed variable changes over time, or between pre and post eradication samples but again, significant differences were rare due to the high standard errors around the historical data.

Invertebrate orders shared between Antipodes and Macquarie Islands

Fifteen invertebrate orders shared between both Antipodes and Macquarie islands were trapped in pitfall surveys on both islands. Groups that had different levels of taxonomic identification across sampling years on each island were removed and the responses of the remaining nine shared orders were compared. Abundance responses in the shared invertebrate orders indicated few similarities between islands (Appendix 2, Figure 4 and 5). For example, beetles on Antipodes Island were eaten by mice and increased abundance following

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eradication (Appendix 2, Figure 4), whereas the Macquarie Island beetles were all Staphylinidae, not preferred food of mice, and were found to decrease following eradication of mice, rats and rabbits (Appendix 2, Figure 5). Contrasting responses were observed in most of the shared invertebrate orders.

Figure 4-6 Predicted abundance (log scale) of 13 invertebrate orders on Antipodes Island, in three sampling seasons prior to rodent eradication (2011, 2013, 2016), and one sampling season post eradication (2018). The eradication program commenced in 2016 and was declared successful in 2018. DD = data deficient. Grey shading indicates the size of the 95% confidence intervals around the mean. The blue lines at the upper and lower margin of the plots are indicative of the number of sampling events.

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Influence of vegetation community on Macquarie Island

In addition to rodents, Macquarie Island was also impacted by rabbits, particularly since the late 1990s (Terauds et al. 2014). Given that rabbits heavily grazed vegetation, which is key habitat for invertebrates (Davies and Melbourne 1999), vegetation removal and subsequent recovery complicated the assessment of invertebrate trends.

Figure 4-7 Abundance of 11 invertebrate orders on Macquarie Island, in three sampling seasons prior to rodent and rabbit eradication (1986, 1993, 2009), and three sampling seasons post eradication (2015, 2016, 2018). The eradication program commenced in 2011 and was declared successful in 2014. DD = Data deficient. Grey shading indicates the size of the 95% confidence intervals around the mean. . The short blue lines at the upper and lower margin of the plots are indicative of the number of sampling events.

Using partial residual plots from the GAMs that included vegetation as a predictor, predicted changes in invertebrate abundance over time were assessed across the five vegetation communities (Appendix 2, Figure 6). While the standard errors around the historical data

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made identification of significant differences in abundance between some years difficult, model results clearly identified vegetation as a significant factor and there were also clear differences in abundance trends across the different communities (Appendix 2, Figure 6). Vegetation was also identified as a significant factor in models of invertebrate species richness (Appendix 2, Figure 7) and diversity (Appendix 2, Figure 8). However, again, high standard errors in the historical data made trends difficult to identify (for confidence intervals of predicted abundance classes see Appendix 2, Table 3). The relationship between invertebrates and vegetation on Macquarie Island is explored in more detail in Houghton et al. (Chapter 5).

DISCUSSION

For the first time, we have quantified the response of invertebrates to eradication operations on Macquarie and Antipodes Islands. Increases in invertebrate abundance and richness on Antipodes Island, particularly in rodent preferred prey, was consistent with a pattern of recovery following the eradication of mice. These responses were swift, occurring within 2 years of eradication, and regardless of seasonality. However, the absence in both pre- and post- eradication samples of the undescribed weta species (Orthoptera), which was highly palatable to mice, supports the suspicion that mice have driven this species to local extinction (Russell 2012). Despite increases in abundance of many taxa, significantly fewer flies were detected in the 2018 samples compared to earlier samples. This supports findings by Russell et al. (2020) which showed as mice on Antipodes Island exhausted populations of preferred prey (e.g. moths, beetles and amphipods), their diets shifted heavily to their next preference - fly larvae - essentially systemically eating their way through the ecosystem. Flies may need more time to recover following the eradication since they were recently heavily targeted by mice. Isopods dominated the post eradication catch on Antipodes Island, but given they are not preferred prey of mice (Houghton et al. 2019a), the underlying cause of their considerable population increase is unknown.

The responses of invertebrates on Macquarie Island were more nuanced. This occurred despite the fact between the islands many of the invertebrate groups impacted by rodents are shared between (Figure 4-3), and a similar time had elapsed since eradication had occurred (Antipodes – eradication July 2016, post-eradication monitoring January-February 2018;

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Macquarie Island eradication May 2011- April 2014, post-eradication monitoring commenced December 2015). In effect, on Macquarie Island no live rodents had been seen since the conclusion of the baiting (July 2011), and the last live rabbit was detected in November 2011 (pers. observation). Thus, compared to Antipodes Island, considerably more time had elapsed on Macquarie Island since invertebrates and vegetation had suffered the full brunt of impact from the invasive mammals, which makes the obvious explanation of a lag in invertebrate recovery insufficient as the sole explanation. Furthermore, as we have discussed earlier in the introduction to this chapter, invertebrates are generally known for fast response times. The more subtle responses modelled for Macquarie Island, could be attributable to the more complex interactions and impacts of the three invasive mammals that were simultaneously eradicated (see Raymond et al. 2011), and the variability of historical surveys on Macquarie Island (both in nature and effort). The clearest recovery signal was observed in species richness, which significantly increased immediately following eradication. However, the modelled abundance trends were not as definitive. Responses in preferred rodent prey (spiders, moths, flies and worms) were variable, and typically gradual following the eradication. While an increasing trend was observed in most of these model plots, this change in abundance over time was typically not significant. These results are largely due to high uncertainty in pre-eradication model predictions, which are strongly linked to the sampling effort and the amount of data. Although historical data is valuable in determining change over time, care must be taken when interpreting data based on variable survey effort (survey length, trap size and season), as well as different survey teams conducting trapping and invertebrate identification. We accounted for variation in survey effort by standardising abundance to catch per day, and re-identifying some historical samples to improve the dataset. If sampling effort across the historical years on Macquarie Island had matched the contemporary sampling, confidence intervals around the results would likely be smaller, and possibly indicate the presence and direction of change more clearly. While it is crucial to access historical data to inform meaningful long-term monitoring and assess change, this result highlights the inherent difficulties in using such data.

Monitoring ecosystems in recovery can deliver insights on the impacts of biological invasions and the need for further restorative management interventions (Caut et al. 2009; Zavaleta 2002; Prior et al. 2018; Bird et al 2019). However, to date, monitoring of mammal eradication outcomes (and publishing the results) has been limited and sporadic (Jones et al. 2016; Brooke et al. 2018; Towns 2018; Bird et al. 2019), despite the proliferation of such

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programs and their clear conservation benefits (Jones et al. 2016). Invertebrates in particular are rarely monitored regardless of their importance in ecosystems. How invertebrate communities respond following mammal eradication, as we have done here, is central to gaining a broader understanding of the impact of eradication programs across ecosystem levels, explaining unexpected effects, assessing return-on-investment and determining overall conservation benefits for the ecosystem. However, robust and consistent invertebrate monitoring is critical to meaningful interpretation of results. Here, we used pitfall trap data and order-level identification in our analyses to enable comparison between contemporary and historical surveys. Order-level identifications have been widely used to investigate disturbance to invertebrate communities (Driessen and Kirkpatrick 2017). However, whereas order-level identification can be sufficient to indicate major changes, it can be inferior to family and species level identification in discriminating between more subtle effects (Driessen and Kirkpatrick 2017). Moreover, pitfall traps may not adequately sample the range of taxa that were affected by invasive mammals, in this case being dominated by few abundant species of beetles and spiders. Indeed, although Houghton et al. (2019b) reported higher abundance and richness in pitfalls compared to other trapping methods across the five vegetation communities on Macquarie Island, these surveys exhibited comparatively low evenness (i.e. Simpson’s index of diversity), indicating inordinately high abundance by some invertebrate groups (Houghton et al. 2019b). Moreover, pitfalls by design trap surface-active invertebrates, thus their catch is likely to under-represent foliage-active invertebrates and be less sensitive to changes in vegetation than other trapping methods. Such limitations, and others, of pitfall traps, have been widely reported (e.g. Luff 1975; Spence and Niemelä 1994; Koivula et al. 2003; Woodcock 2005; Schmidt et al. 2006), including their effectiveness dependant on habitat structure and considerations necessary to allow comparisons between pitfall catches (Greenslade 1984; Melbourne 1999; Koivula et al. 2003). The effect of habitat structure on pitfall trap effectiveness can result in biased data in studies that compare sites with different habitat structure, or when habitat structure changes over time (Melbourne 1999). Given that our study questions do not relate to absolute population density but relative differences in abundance and community structure at established sites over space and time, the impact of these limitations was minimal (see also Melbourne 1999). Ideally, given island meteorological data does not reflect microclimate conditions in different habitats (pers. observation), our analyses would include micro-climate data for each site over time in order to gauge the influence of weather and vegetation structure on invertebrate abundance and richness as vegetation damage and invasive mammal impacts fluctuated. No such data was

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available for historical surveys, but we investigate environmental drivers of invertebrate abundance in more detail in Houghton et al. (Chapter 5). To counter some of the deficiencies of pitfall trapping, future monitoring must incorporate a variety of trapping methods, or select trapping methods appropriate to the question (Houghton et al. 2019b), and include notes on meteorological conditions, habitat structure and microclimate.

Unlike Antipodes Island, seasonal variation in invertebrates was not a factor in our analyses for Macquarie Island, as both historical and contemporary surveys occurred during the ‘summer’ season (October to January). Although we found distinct differences between seasons for many invertebrates at the relatively low latitude Antipodes Island, seasonal effects are generally not prominent in invertebrate communities on sub-Antarctic islands (Convey 1996a, b; Barendse and Chown 2001), and very little seasonal variation is recorded through summer Macquarie Island (Pendlebury and Barnes-Keoghan 2007). Furthermore, vegetation states differ between the two islands; Antipodes was not subject to vertebrate grazing, and as such could be defined as being in a stable state, while Macquarie Island vegetation is undergoing rapid, variable changes in response to rabbit eradication (Shaw et al 2011; Whinam et al. 2014). The more gradual invertebrate response observed for some taxa on Macquarie Island could be attributable to the extreme vegetation damage by rabbits, perhaps also linked to changes in soil moisture. This could potentially cause invertebrate recovery to lag behind dynamic vegetation regrowth. Invertebrates generally respond quickly to changing environmental conditions, making them good bioindicators (Hutcheson et al. 1999; Gerlach et al. 2013), but the unique traits of sub-Antarctic invertebrates such as slow growth rates and unusually long life cycles (Vernon et al. 1998; Convey et al. 2006a; Chown and Convey 2016) may be responsible for slow responses in this case. Cooler climatic conditions on Macquarie Island relative to Antipodes Island might also be a factor in a lagged response to the changing environment. Energy availability on islands is an important driver of richness and diversity (MacArthur and Wilson 1967), including for SOI (Chown et al. 1998; Leihy et al. 2018). Typically, higher-energy environments increase the number of individuals that can be supported (Evans et al. 2005). The more benign environment on Antipodes Island (Chown et al. 1998; Weigelt et al. 2013) thus equates to more energy in the system, supporting greater diversity of invertebrates. It may also drive faster responses by ecosystem components like invertebrates to environmental changes such as rodent removal.

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The mouse population on Macquarie Island was likely suppressed by rats, as has been found on other islands (e.g. Caut et al. 2007). Conversely mice were the only land mammal on Antipodes Island, and mice density was relatively high (Russell 2012). Although mouse population density on Macquarie Island was never robustly quantified, unpublished trapping trials during winter on the upland plateau, indicate that it was much lower than for similar sites on Antipodes Island (Springer 2005, unpubl. report; JC Russell 2019, unpubl. data). The lack of robust mouse density assessments, despite good knowledge of mice preferred prey, mean the cumulative impact of mice on the invertebrates of Macquarie Island was only ever theorised based on studies from other islands (Parks and Wildlife 2007; 2014). Therefore, it is possible that mouse impacts on invertebrate populations on Macquarie Island were not as prominent as had been suggested. Certainly, mice are known to be particularly destructive on islands where they are the sole predator (Angel et al. 2009); like Antipodes (Marris 2000; Russell 2012), Gough Island (Wanless et al. 2007) and Marion (Dilley et al 2015; 2018; McClelland et al 2018). Yet in the presence of rats on Macquarie Island the mouse population and their respective impacts could have been low. This could, at least partially, also help to explain the post-eradication responses observed on Macquarie Island in groups that were mice preferred prey, i.e. for spiders, moths and fly larvae, a pronounced response to mouse predation release was not detected.

The removal of invasive mammals from Macquarie Island has not unequivocally resulted in immediate and obvious positive responses at lower trophic levels in the post-eradication ecosystem. This is consistent with other studies that have shown that long-term invasion can leave an ecosystem with unexpected, long-lasting, or even permanent changes (Zavaleta et al. 2001; Caut et al. 2009; David et al. 2017), particularly where there are multiple invaders (Zavaleta et al. 2001; Russell and Kaiser-Bunbury 2019). Local species can sometimes take considerable time to recover or may possibly never return to their pre-invasion functional state, especially if novel habitats were created by the now removed invader and were used by natives, or where the ecosystem was irreparably modified through invasive species engineering (Mulder et al. 2009; David et al. 2017). Long-term impacts of both rabbits on Macquarie Island and rodents on both Antipodes Island and Macquarie Island, included seabirds, nutrient deposition, soil moisture, and vegetation cover (Brothers 1984; Imber et al. 2005; Elliot et al. 2015). Particularly on Macquarie Island, detritivorous invertebrates dominate the terrestrial fauna, are reliant on litter and influenced by soil nutrients (Vernon et al. 1998; Chown and Convey 2016). Seabirds, and the nutrients they provide, are returning to

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Macquarie Island following cat eradication (Brothers and Bone 2008), and rodent and rabbit eradication (J Bird, pers. comm.). However, the length of the invasion by multiple mammals on Macquarie Island and other studies that show decades may be required for recovery at lower trophic levels (e.g. Jones 2010b; Koch 2015), suggest there may be delays in invertebrate response. Invertebrates are known to be good bio-indicators (Gerlach et al. 2013), but here we show that in the case of long-term invasions by multiple mammal species, they may be slower to react to eradication than we hypothesised.

Although invertebrates supplemented the plant-based diet of rats on Macquarie Island, on other islands rats have been found to typically, but not exclusively, consume invertebrates that are greater than 5 mm, such as ground beetles, scarabs beetles, spiders, hartvestmen (Opiliones), caterpillars, fly maggots, crickets, and centipedes (e.g. Bremmer et al. 1984; Taylor 1986; Sinclair et al. 2005). On Macquarie Island, few of these invertebrates exist, and those that do are generally small. Native spiders for example, are a maximum of 5 mm in length (Greenslade 2006). Only one relatively small moth species (E. mawsoni) is a permanent resident on Macquarie Island (adults ~11mm, caterpillars ~15mm) (Houghton et al. Chapter 5) and there are no large beetles permanently established. However, while few native invertebrates on the island were palatable to rats, some non-native invertebrates were. The transient beetle species Epichorius sorenseni (~1mm long, Greenslade 2006), was a preferred food for rats on Campbell Island (Taylor 1986). Given that rats and mice are willing to search far and wide for their preferred food, and will continue hunting these prey until they are exhausted (Taylor 1986; Sinclair et al. 2005; McClelland et al. 2018; Russell et al. 2020), there is a possibility that further establishment and spread of E. sorenseni on Macquarie Island was, prior to the eradication, supressed by rats. E. sorensi were trapped during this study but we did not have adequate data to detect population trends. The same scenario is possible for transient moths that have regularly arrived to the island on favourable winds, sometimes in high numbers, but have never established (Greenslade et al. 1999). Amphipods are also preferred food for rodents (Taylor 1986; Russell et al. 2020), but the non-native Amphipod on Macquarie Island (Puhuruhuru patersoni) is currently restricted to the isthmus around the research station (Greenslade et al. 2008). Although P. patersoni has maintained a limited distribution on the island for possibly more than 100 years (Greenslade et al. 2008), in the post-eradication ecosystem lacking predatory rodents, this non-native species has gained an advantage, and is possibly more free to expand its distribution. Given the historical sites

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we resurveyed during this study did not overlap with the known distribution of the Amphipod, we were unable to determine its range since the rodent eradication.

Interactions with remaining non-native vertebrate species on Macquarie Island may also be affecting the recovery of invertebrates. Insectivorous European starlings (S. vulgaris) persist on the island in large flocks, as well as Mallard ducks (A. platyrhnchos) (Copson and Whinam 2001; Robinson and Copson 2014), but we currently have no information on their Macquarie Island specific diet. In the context of an island that once supported a native insectivorous land bird (the now extinct Macquarie Island Rail - Gallirallus philippensis macquariensis) and the non-native omnivorous weka (Gallirallus australis), as well as invertebrate-consuming rats and mice, a consequence of the rodent removal for the remaining non-native insectivorous starlings and ducks, could be an increase in their populations, since competition for invertebrate prey has been removed (Raymond et al. 2011). This post rodent eradication outcome has been seen elsewhere (Sinclair et al. 2005).

There are 41 established non-native invertebrates (including 7 synanthropic species – i.e. breeding inside buildings) remaining on Macquarie Island, and 22 transient species (Houghton et al. Chapter 5). In comparison, only seven non-native species are known from Antipodes Island, plus three transient species (Marris 2000), although more alien species are likely to be present, particularly for the Acarina and Collembola for which a checklist is not currently available. It is also possible that the relatively large number of non-native invertebrate interactions on Macquarie Island are impacting the recovery of invertebrate communities, and that a novel, post-eradication ecosystem is evolving. For example, some non-native invertebrate species may also profit from the removal of predatory rodents, such as non-native worms which are found all over the island, from the coast to the plateau (M. Houghton, pers. obs.; Greenslade 2006) and were preferred invertebrate prey for rats (Copson 1986). Meanwhile the herbivorous molluscs (a non-native slug and an endemic snail), though not preferred rodent prey items, may benefit from improved fodder as the vegetation rebounds. Interactions between and within native and non-native species have been known to produce undesirable outcomes (Roemer et al. 2002; Zavaleta et al. 2001; Bergstrom et al. 2009). However, much of the related research in the region has hitherto typically focussed on more detectable direct species interactions (Houghton et al. 2019a; but also see Gabriel et al. 2001; Terauds et al. 2011). Invertebrates are inherently small and with cryptic habits,

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therefore interactions that may be affecting ecosystem recovery are less perceptible. Furthermore, the greater the number of interacting invaders in an ecosystem, the more likely there will be secondary effects of eradication (Zavaleta et al. 2001; Russell and Kaiser- Bunbury 2019). Further work investigating how interactions with non-native species are affecting native invertebrate communities and ecosystem recovery on Macquarie Island are warranted.

This study has shown the value of monitoring invertebrate community response as an indicator of island ecosystem health and our results underpin broader understanding of how mammal eradications improve conservation outcomes for invertebrates. However, our findings also highlight that invertebrates may not always respond in similar ways to removal of pest mammals. To assess the ecosystem-scale conservation benefits of island conservation actions such as mammal eradications, an understanding of island-specific biotic and abiotic variables and how they interact is required. These interactions may influence the shape and speed of recovery, or the efficacy of the conservation program, in reaching the desired goals for the ecosystem. In post-eradication ecosystems undergoing passive restoration, invertebrate communities can evolve into something novel, particularly in the face of interactions with remaining non-native species, such as invertebrates or land birds, who may have also benefited from the mammal eradication. Given that invertebrates are critical to ecosystem functioning, these changes will likely have long-lasting implications for island ecosystems.

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Chapter 5 | Drivers of macro-invertebrate communities following a mammal eradication on Macquarie Island

Melissa J Houghton, Aleks Terauds, and Justine D Shaw

ABSTRACT

Invertebrates comprise the majority of animal species on Earth. Their abundance, diversity and pivotal ecological roles make then critical to ecosystem function. Yet, they are often overlooked in conservation research, even though they can be useful indicators of biodiversity and environmental changes. They may be suitable for tracking large-scale ecosystem changes following invasive mammal eradications on islands. However, in order to interpret their responses to mammal eradications, we need to understand potential drivers of invertebrate abundance and diversity.

Here we investigate the abiotic and biotic drivers of invertebrate communities on Macquarie Island, where a multi-species invasive mammal eradication has recently taken place. We also assess non-native invertebrate interactions with native invertebrates. We conducted island- wide surveys and clarified the relationship between a range of abiotic and biotic predictors for species richness and abundance of invertebrate taxa.

Vegetation type and year of sampling explained most of the variation in invertebrate richness across trapping methods. Vegetation, elevation, year of sampling, and the presence of non- native species were the main drivers of invertebrate abundance across families and survey methods. Drivers of abundance varied according to (Insecta, non-Insecta), feeding guild and native or non-native status. Non-native species interactions with native species were typically more negative than positive. We used these data to establish a post-eradication baseline and identify bioindicators for future effective monitoring on Macquarie Island.

INTRODUCTION

Invertebrates rarely attract conservation attention despite playing a key role in ecosystem resilience and functionality. Yet, aside from their intrinsic natural values, invertebrates can be useful in ecological studies. They are species rich, ubiquitous, and abundant, with short life

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spans, and respond rapidly to changing environmental conditions (Stevens et al. 2010; Gerlach et al. 2013). Invertebrates can act as good indicators of ecosystem condition, and are ideal for documenting change through long-term monitoring (Danks 1992; Longcore et al. 2003; McGeoch 2007). These characteristics make them a cost effective, ecologically representative group for assessing ecosystem response and conservation benefits. Here, we investigate further their suitability as indicators of ecosystem response to a large-scale island conservation action.

Invasive mammal eradications are a highly successful tool for island conservation. In spite of this, how island ecosystems respond to eradications and how we can effectively monitor these changes remains unclear (Bird et al. 2019). Post-eradication monitoring of island ecosystems is an important component of assessing the conservation benefit and return-on-investment for island conservation programs, informing future conservation planning and management. However, we need to understand what drives ecosystem responses at lower trophic levels, such as invertebrate abundance and richness, and how this affects post-eradication recovery, before we can infer responses to the conservation action.

Two sub-Antarctic islands have recently undergone vertebrate pest eradication – Macquarie Island (Australia) and Antipodes Island (New Zealand). On both, invertebrates were monitored before and after eradication of mammals. It was anticipated, based on the removal of rodent predation pressure that invertebrate abundance and richness on both islands would increase in response to eradication (Houghton et al. Chapter 4). Yet responses differed between the two islands. There was often no significant change on Macquarie Island, while invertebrate responses to rodent eradication on nearby Antipodes Island were strong (Houghton et al. Chapter 4). This raised questions about parameters potentially driving invertebrate abundance and diversity responses, and how they interact on Macquarie Island. Studies of arthropods on other SOI suggest that island-scale abiotic variables, rather than biotic factors, may be more important determinants of invertebrate community structure (Hugo-Coetzee and Le Roux 2018).

Invertebrate abundance and diversity are linked to habitat quality, including interactions with soil moisture, litter accumulation, nutrient availability, temperature, aspect, vegetation cover and many more variables (Davies and Melbourne 1999; Barendse et al. 2002; Fukami et al. 2006; Zhang et al. 2016; Kemp and Ellis 2017; Thoresen et al. 2017; Chown and Convey

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2016; Hugo-Coetzee and Le Roux 2018). Sub-Antarctic invertebrates generally have broad habitat tolerances (Burger 1985; Gressitt 1971; Convey et al. 1999; Hänel 1999; Greenslade 2006; Chown and Convey 2016); however, some studies have found that particular invertebrates are habitat specific (Tréhen et al. 1985; Davies 1973; Davies et al. 2011; Barendse and Chown 2001; Barendse et al. 2002), and that habitat type strongly influences assemblage patterns and abundance (Burger 1978; Gabriel et al. 2001; Barendse et al. 2002; Hugo et al. 2006). The general lack of habitat specificity reflects regional invertebrate characteristics; the prevalence of detritivorous invertebrates, and little host-plant specificity among invertebrate herbivores (Crafford et al. 1986; Chown and Convey 2016). Studies of Collembola in the region have shown that where habitat or plant community specificity exists, it manifests more strongly in native than non-native species (Gabriel et al. 2001; Terauds et al. 2011). Moisture, temperature, and wind speed are important drivers of Collembola abundance and distribution (Convey et al. 1999; Hänel 1999; Hugo et al. 2004; 2006), but native species respond differently to abiotic variables than non-native species, being more abundant in colder and drier conditions on mineral soils with lower organic content than non-native species that prefer the lowland moist, warm, organically-enriched sites (Gabriel et al. 2001). The depth of knowledge of habitat preferences that we have for Collembola is lacking for other invertebrate groups in the region. For other invertebrate groups, habitat interactions remain little investigated, although interactions between native vascular plants and insect diversity have been recently documented (Chown et al. 1998; Leihy et al. 2018). Spatial variation in abundance and range is likely to be influenced by abiotic factors, but for insects this relationship remains speculative across the region (Chown and Convey 2016). In general, abiotic and biotic variables are thought to play substantial roles in community organisation in species-poor and harsh environments such as sub- Antarctic islands (Menge and Sutherland 1987; Menge and Olson 1990; Hugo-Coetzee and Le Roux 2018).

Houghton et al. (Chapter 4) explored the composition and abundance of pre and post eradication invertebrate communities on Macquarie Island. The study was limited to pitfall trapping, confined to historic sites clustered around the north of the island, and was focussed on rodent predation as a driver of change in invertebrate communities in the two island systems over time. Previous work by Davies and Melbourne (1999) investigated the role of various environmental variables in explaining invertebrate distributions on Macquarie Island, aiming to establish a baseline for climate change monitoring of invertebrates (Davies and

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Melbourne 1999). In 1996, while cats, rabbits and rodents persisted on the island (Robinson and Copson 2013), these authors surveyed 69 sites, including a range of abiotic variables in their models - altitude, aspect, wind speed, wetness and vegetation. The authors found that altitude, vegetation and aspect strongly influenced invertebrate community composition and determined the habitat affinities of species groupings. However, their survey extended over a single six-week period (January to February 1996), relied on presence-absence rather than abundance data, and used only two methods of trapping – small pitfalls and yellow pan traps. No invertebrate community baseline following invasive mammal removal has subsequently been established.

More than 40 non-native invertebrate species are established on Macquarie Island (Greenslade 2006; Houghton et al. Chapter 6). Non-native invertebrates are impacting native species and ecosystems across SOI predominantly through competition and predation (Houghton et al. 2019a). Yet some invertebrates show no evidence of negative interactions between native and non-native species locally (Gabriel et al. 2001) and regionally (Chown et al. 1998) and even positive interactions have been found for species richness and density, supporting the ‘rich get richer’ hypothesis (Terauds et al. 2011). Research on SOI has focussed on the ecosystem impact of particular non-native species (e.g. Smith and Steenkamp 1992; Hänel and Chown 1998; Smith 2007) or the impact of a particular non-native invertebrate on a native invertebrate species or taxonomic group (e.g. Ernsting et al. 1999; Laparie et al. 2010), but no study from the region has quantified such interactions across a broad range of insects and other macro-invertebrates, and certainly not with respect to a recent eradication of mammalian predators and herbivores. Reference to the recent eradication is important, as both native and non-native invertebrate species may or may not have been impacted by predatory rodents or the secondary impacts of grazing rabbits, and each may be advantaged or disadvantaged by the removal of mammals to varying degrees. These interactions may influence the trajectory of invertebrate recovery and the ecosystem as a whole.

Here we investigate the importance of habitat and abiotic variables for invertebrates on Macquarie Island. Based on the findings of Davies and Melbourne (1999), I aim to determine if vegetation, altitude and aspect remain the primary drivers of invertebrate abundance and diversity in the Macquarie Island ecosystem recently cleared of mammal pests. In particular,

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did the eradication of rabbits from Macquarie Island indirectly effect invertebrates? And will the invertebrates respond in line with post-eradication vegetation recovery?

Are abiotic variables such as temperature, elevation or moisture important in driving invertebrate communities on Macquarie Island, and are these variables different for native and non-native species? Do non-native invertebrate species benefit from the mammal eradication, and do they interact with native invertebrates? We expected vegetation community to influence abundance and richness of invertebrates. We also expected to find some non-native invertebrates advantaged by the eradication and interacting negatively with native species. With reference to detailed site information derived from a Digital Elevation Model, we use post-eradication invertebrate surveys across three consecutive seasons in five distinct habitats using a range of trapping techniques to determine the drivers of invertebrate community composition. We identify interactions between native and non-native invertebrates and discuss their influence on the island’s post-eradication recovery. We also identify indicator taxa and establish a post-eradication invertebrate community baseline for Macquarie Island that will underpin an effective future monitoring program for island managers. This work provides insights into the utility of invertebrates in assessing environmental change on the island.

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Figure 5-1 The location of 24 invertebrate monitoring sites established on Macquarie Island in 2015, 2016-17 and resampled in 2018.

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METHODS

Invertebrate abundance and richness

Pitfall trapping, litter sampling, vegetation sweeping and 20-minute counts

We used a range of survey methods in order to capture the greatest diversity of invertebrates (Houghton et al. 2019b). In 2015 (November-December), ten sites that had been historically sampled (see Chapter 4) were re-surveyed. In addition, ten new sites were established to increase representation of habitats and environmental variability (Appendix 3, Table 1). Four additional sites were added in the 2016 -17 season (November-January), resulting in a total of 24 sites in 2016-17 and 2018 (January-February) (Appendix 3, Table 1). At each of these sites, pitfall trapping, vegetation sweeping, litter sampling (invertebrates extracted using Berlese funnels), and 20 minute hand counts were also used to sample invertebrates across three Austral summer seasons. Details of these four methods are described elsewhere (Houghton et al. 2019a). All invertebrate samples were preserved in ethanol and returned to Australia for identification.

Vegetation beating

Vegetation beating was undertaken at each site in the 2016-17 season and repeated in 2018. Beating involved placing a tray at the base of vegetation and striking the vegetation above. Invertebrates fall into the tray below. Two rounds of three replicates of 10 beats were performed at each site.

Coloured sticky pan traps

In 2018, yellow pan traps were deployed at each site, specifically to optimise moth capture (see Houghton et al. 2019b). These were yellow plastic plates smeared with Tangle Trap® brush-on, petroleum-based insect trap coating. Three traps were randomly placed at each site and secured to ground using a 10cm nail. They were deployed for the duration of the trapping season. Yellow pan traps were placed in plastic bags and returned to the on-island laboratory for identification of trapped invertebrates.

During the study, some pitfall traps and yellow pan traps were disturbed by Brown Skua (Stercorarius antarcticus). On occasion, skuas were successful in completely removing traps. These disturbances were noted.

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Vegetation surveys

The sites surveyed for invertebrates spanned the five major vegetation communities on the island (Selkirk et al. 1990) (Appendix 2, Table 1) – feldmark (plateau), lower coastal slopes dominated by Stilbocarpa polaris (Macquarie Island cabbage), tall tussock grassland (dominated by Poa foliosa), short grasslands and Pleurophyllum hookeri dominated herbfield. At each site, vegetation community was surveyed using a 10 m x10 m quadrat. In total, there were five Stilbocarpa, four short grassland, seven tall tussock grassland, four herbfield, and four feldmark sites.

Identification

All invertebrates collected were identified to the finest taxonomic resolution possible with reference to The Invertebrates of Macquarie Island (Greenslade 2006). Tardigrades, Nematodes, Copepoda, Collembola and Acarina were extremely abundant (e.g. 1000+ per sample in some instances). As a result, these groups were not consistently counted across years and were excluded from analyses. Siphonaptera (fleas) were captured not included in analyses as they are not free-living.

Analyses were undertaken at the family taxonomic level for most species. The Annelida were an exception, being included at the phylum level. For the purposes of these analyses all groups are hereon referred to as ‘families’. Adults and larvae were grouped together. To standardise trap catches for analyses, we calculated the mean average daily count per trap method per site over the course of each season. For example, the average daily catch by an individual trap at each site is the average daily catch of Pitfall #1 at Site 1, 2015, for trap period 1 of 3 (total abundance caught for 1st trapping period /#days open). The mean average daily count for that trap method for each season is the mean of the average daily catch for each trapping session # 1, 2, 3 at each Pitfall #1, #2, #3, #4, #5 at each site and calculated for each year 2015, 2016-17, and 2018. We refer to this ‘mean average daily count’ as ‘abundance’ hereon. We include richness as a measure of the number of families present per trapping event, per trap, per site.

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Data Analyses

Richness

To determine which variables best explained variation in invertebrate family richness, we used Generalised Additive Models (GAMs) with a negative binomial distribution using the mgcv package version 1.8-17 (Wood 2017) in R (R Core Team 2017) .In these models, richness was the response variable and a range of abiotic variables as well as ‘vegetation’ and ‘year’ as explanatory variables. GAMs were used because they are adaptable to non-normally distributed variables, they are flexible, and they can accommodate non-linear relationships between the response and explanatory variables (Tao et al. 2012). Abiotic variables for each site were derived from the Digital Elevation Model (DEM) for Macquarie Island (Bricher et al. 2013 – Table 5-1). These abiotic variables were all continuous: elevation, ridge, slope, wetness, solar radiation, and wind speed. Vegetation community and year were included as factors (random effects). Except for beat and yellow pan models, all abiotic variables were included in GAMs as smooth terms, with vegetation and year as random effects. Given their later introduction to the trapping regime, beating and yellow pan traps provided less data than other trap methods and in consequence, abiotic variables were could only be included in GAMs as non-smoothed terms. Vegetation and year remained as random effect terms in these models, except that year was excluded from yellow pan trap models, as this trapping occurred only in 2018. For each invertebrate family, a saturated model was fitted first, comprising the seven abiotic variables plus vegetation and year. The ‘dredge’ function in package MuMin was used to find the most parsimonious (best) model, as indicated by the lowest Akaike information criterion (AIC). The fit of the best model was assessed using standard diagnostic plots (QQ-plots, residuals vs linear predictors, residual histograms). The best models for explaining species richness for each survey method were recorded in a model summary table (Appendx 3, Table 2).

Abundance

Given the high number of explanatory variables tested, we used a two-step modelling process to determine the variables that best explained the variation in invertebrate family abundance. The first step involved fitting GAMs and finding the best models as per the richness analyses. In the second step of our modelling process, we added terms representing the abundance of non-native invertebrate families as predictors to the best models identified in the first step.

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Non-native families included Agriolimacidae (slugs), Aphididae (aphids), Janiridae (woodlice), (flatworms), Calliphoridae (blowflies), and (flies - midges). Non-native families were also included in models of other non-native species abundance. Once again, a stepwise process was undertaken using the dredge function to identify the best model. The fit of the final best model fit (i.e. using normal distribution and heteroscedasticity of residuals) was assessed using standard diagnostic plots (QQ-plots, residuals vs linear predictors, residual histograms) and the explanatory power was assessed using the adjusted R² and deviance explained.

We used this same 2-step process to fit GAMS with abundance of each family as the response variable for each trap type. Once again, the best models were identified using a stepwise process based on lowest AICs and the fit of these models assessed using the same diagnostic plots. Partial residual plots of the variables identified in the best models were generated for each family and were used to assess the direction of influence. Trends in the factorial variables ‘year’ and ‘vegetation’ were visualised through partial residual plots generated using the visreg package (Breheny and Burchett 2013) in R. Partial residual plots were also used to visualise the abundance of 22 families according to the five vegetation communities.

The best models for explaining variation in abundance for each method were recorded in a model summary table (Appendix 3, Table 2). Results from this table were then pooled into three classifications for comparison: survey method, functional guild, and higher taxonomic classification. Guilds were assigned according to Greenslade (2006) and Houghton et al. (Chapter 6).

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Table 5-1 Description of the environmental parameters used in this work, derived from the Digital Elevation Model developed for Macquarie Island by Bricher et al. 2013.

Variable Description Ecological relevance Elevation Altitude above sea level. Species distributions for plants (Selkirk et al. 2009) and invertebrates on sub-Antarctic islands often exhibit altitudinal gradients (Hänel 1999; Davies and Melbourne 1999; Gabriel et al. 2001; Davies et al. 2011; Terauds et al. 2011). Elevation is linked to decreased temperature and increased wind speed on Macquarie Island (Davies and Melbourne 1999) Wetness A topographic wetness index was Moisture can be related to increased used to model areas of water invertebrate species richness (Convey et al. accumulation. 1999; Terauds et al. 2011). Precipitation has increased on the island over recent decades (Adams 2009). Wind speed Based on the prevailing wind Flightlessness is unusually common in native direction and the average wind subantarctic invertebrates (Roff 1990), likely speed, a topographically-deflected an adaption to energy constraints in high winds wind speed model was used to and low temperatures, with reproductive trade- estimate the wind speed across offs (Danks 1992; Wanger and Leibherr 1992). Macquarie Island. Wind speeds have increased on Macquarie Island in recently years with climate change, resulting in a drier atmosphere (Adams 2009) Solar radiation Solar radiation function in ArcGIS Species richness is driven by energy 9.3 was used to calculate annual availability on SOI (Chown et al. 1998; 2005; solar radiation. Evans et al. 2005). Sunshine hours, i.e. solar radiation, have increased on the island during the last 40 years (Bergstrom et al. 2015). Slope Surface curvature, or slope, affects As above for moisture-related species richness water flow patterns in times of and increased island precipitation. precipitation. Ridge Ridges are often higher and more As above for moisture related richness. Some exposed sites. A multi-scale landform native invertebrate taxa have been found to classification algorithm in the LandSerf prefer higher, more exposed sites with high package (Wood 1996) was used to mineral content than lower sites with more calculate the proportion of scales at organic material (Hugo et al. 2004; Gabriel et which each cell occurred in a ridge. al. 2001)

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Community

We generated community-based models using the R-package mvabund (Wang et al. 2012) to test the ability of environmental predictors to explain variation in the abundance of the entire community (at the family level). We used mvabund as it does not use distance-based matrices to make the comparisons, which alleviates issues of over-dispersion in the mean-variance relationship (see also Warton et al. 2012). We used the ‘many.glm’ function, to fit models with a negative binomial distribution, with the community abundance data as the response and the six abiotic variables together with year and vegetation as the predictors. We used ‘meanvar.plot’ to test the mean-variance relationship and ran standard model diagnostic tests to test model assumptions.

Indicators

We conducted a species indicator analysis to statistically assess the relationship between species occurrence/abundance and the specific habitats. For this purpose, we used the function ‘multipatt’ in the R package indicspecies (Cáceres and Legendre 2009). Twenty-two families trapped in the study were used for this analysis (Triozidae and Scolytinae were removed due to exceptionally low abundance).

RESULTS

Overview

More than 202,000 individuals from 18 invertebrate orders were identified in this study. Most individuals were identified from the 2015 samples (~115,000), which included ~85,000 Collembola (springtails) and ~9,700 (mites). Collembola and Acari were not identified in 2016-17 and 2018 samples. Once Acarina, Collembola, Copepoda, Tardigrada, Nematoda and Siphonaptera were removed for analyses, ~90,000 invertebrates from 13 orders remained, including 24 families.

Six terrestrial families previously recorded on Macquarie Island were not detected during in our survey (not including families within Acarina and Annelida, for which family level identification was not achieved). These six families included transient or rare species, parasites of birds, or those with specific coastal habitats. For each family that we trapped, we

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detected all species known from Macquarie Island (Greenslade 2006). The one exception was Arthurdendyus vegrandis, a localised non-native species of the family Geoplanidae (flatworms). For seven families inadequate numbers (< 30 individuals) were trapped, and in consequence reasonable models could not be fitted (Appendix 3, Table 2). These included Diapriidae (a native parasitic wasp), Scolytinae (a bark beetle), Byrrhidae (a known transient beetle), Tipulidae (a native crane fly), (a non-native fungus gnat), (native kelpflies), Triozidae (transient leafhoppers). This resulted in 17 families from 12 orders. The stepwise models could not explain variation in Chironomidae and Calliphoridae, and as such they were dropped. Therefore final analyses reports on models for 15 families from 12 orders.

The most abundant six families were Punctiidae (Phrixgnathus hamiltoni – an endemic snail), Staphylinidae (comprised of five native species, but the catch was dominated by Omaliomimus venator and Leptusa antarctica), Linyphiidae (Parafroneta marrineri and Haplinis mundenia – two native spider species), Desidae (Myro kerguelensis –a native spider), Australimyzidae (Australimyza macquariensis – a native fly) and Annelida (10 native and 5 non-native earthworm species). Hemiptera (two non-native species Jacksonia papillata and Myzus ascalonicus) were also highly abundant in the 2018 catch, likely due to the timing of the trapping season. Nine families were comprised of a single species, four comprised of two species, Staphylinidae had five species, and Annelida had 15 species. Four of the 15 families were comprised entirely of non-native species. Annelida included 10 native species and 5 non-native species.

In total, 51 models across the 15 families were generated – 7 families were modelled from pitfall trapping data, 14 from count data, 9 from sweeping, 12 from litter, 9 from beating, and 1 from yellow pan trapping (Appendix 3, Table 2).

Richness

‘Vegetation’ community and ‘year’ of sampling emerged as the most important predictors of invertebrate richness for pitfall, sweep, count and litter trapping methods (Table 5-2). Together with ‘wetness’ in sweeping samples, ‘vegetation’ and ‘year’ described 71.3% of the variation in richness. Together with ‘elevation’ they described 38.9% of the variation in richness in count samples (Table 5-2). No models that satisfied the diagnostic tests could be

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fitted for beat and yellow pan traps, most likely due to data deficiency as beat and yellow pan trapping were not conducted in every season. Partial residual plots of richness in vegetation in pitfall, litter and sweep samples demonstrated very similar trends of richness associated with particular habitats (Figure 5-2) – Stilbocarpa, tall grassland and short grassland being significantly more speciose than feldmark and herbfield habitats. Richness was similar across vegetation types for the count method (Figure 5-2) and there was a trend of increasing richness each year for most methods, except for pitfalls (Figure 5-3).

Abundance

Fifty-one models of variation in family abundance were generated in total. Six models were derived from pitfall traps, which included four families identified as the most abundant and widespread on the island (Desidae, Linyphiidae, Staphylinidae and Australimyzidae). Count and litter sampling produced 14 and 12 models respectively, while sweeping and beating produced nine.

Overview of predictors

Across methods, elevation and vegetation most commonly explained family abundance, followed by year, non-native species and slope (Figure 5-4). More details on the variation found between methods for abundance predictors is provided in Appendix 3, Table 2.

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Table 5-2 Environmental parameters explaining invertebrate richness on Macquarie Island, calculated by generalised additive models in R. Yellow highlighting indicates that the associated environmental parameter was selected by the best model for the trapping method tested.

Predictor variables Distribution, Elevation Slope Solar Wind Wetness Ridge Non- Vegetation Year Method Adjusted R², Radiation speed native (factor) (factor) deviance species explained and p value of best model Pitfall Negative binomial, R2=0.4, Dev=37.5% Sweep Negative binomial, R2=0.66, Dev=71.3% Count Negative binomial, R2=0.39, Dev=38.9% Litter Negative binomial, R2=0.66, Dev=61.2% Yellow NO MODEL pan Beat NO MODEL

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Figure 5-2 Partial residual plots of total invertebrate richness across vegetation communities found in four trapping methods on Macquarie Island; a) pitfall, b) count, c) litter, and d) sweep. Grey shading indicates the 95% confidence intervals.

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Figure 5-3 Partial residual plots of total invertebrate richness across 3 years of sampling (2015, 2016-17, 2018) on Macquarie Island using four trapping methods; a) pitfall, b) count, c) litter, and d) sweep. Grey shading indicates the 95% confidence intervals.

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Figure 5-4 The number of times each environmental parameter was selected in the best model to describe invertebrate family abundance on Macquarie Island for each trapping method.

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Non-native species

The environmental parameters that best explained abundance varied according to native or non-native species status (Figure 5-5). Vegetation, elevation and slope were relatively important for both native and non-native species. Wetness was important for non-native species abundance. Year of sampling was also a major factor for native and non-native species abundance. Ridge and wind speed were more important to native species than non- native species.

3.5

3

2.5

2

1.5

1

0.5 Meannumber times of selected GAMs by 0 Elevation Slope Solar Wind speed Wetness Ridge Non-native Vegetation Year radiation species

Native Non-native

Figure 5-5 The mean number of times each environmental parameter was selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe non- native and native invertebrate family abundance on Macquarie Island.

Guilds

Predators, herbivores and detritivores were significantly influenced by elevation and vegetation (Figure 5-6). Year and slope explained predator abundance more than other variables, and wind speed was also an important factor. Wetness, wind speed and solar radiation were particularly important to detritivore abundance, whereas solar radiation, slope and non-native species were also important for herbivores.

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Higher classifications

The abundance of both Insecta and non-Insecta were largely driven by vegetation and elevation (Figure 5-7). Slope, wetness, year and non-native species were also important to non-Insecta. Abundance of Insecta was more often linked to ridge and wind speed than non- Insecta.

Figure 5-6 The mean number of times each environmental parameter selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe invertebrate family abundance on Macquarie Island according to feeding guild (herbivore, predator, detritivore).

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Figure 5-7 The mean number of times each environmental parameter was selected in the best model (GAMs = generalised additive models), with standard error, across trapping methods, to describe Insecta and non-Insecta family abundance on Macquarie Island.

Key parameters

Elevation

Elevation was a key parameter explaining the variation in invertebrate abundance for most groups. Twenty-six of the best models contained elevation, for all families except Annelida, and across trapping methods. This relationship was typically negative, with decreasing abundance observed with increasing elevation. Anomalies were Desidae (pitfall) (Figure 5-8) and Punctidae (litter) which showed initial increases with elevation, followed by slight declines, and a final rise before flattening out. Staphylinidae (count) (Figure 5-8b) was also an anomaly, falling sharply in abundance with increasing elevation initially and then flattening out. Staphylinidae (litter) and Punctidae (litter) increased with elevation in a non- linear pattern. Geoplanidae (count) and Janiridae (litter) lacked data. Where elevation was a significant predictor for a family by multiple methods, in particular for Agriolimacidae (Figure 5-8c, d) and Australimyzidae, the abundance-elevation response trends were similar

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across methods. Only Staphylinidae and Punctidae showed opposing trends between methods.

Figure 5-8 Examples of partial residual plots derived from generalised additive models and illustrating some of the key invertebrate abundance relationships to elevation (m) on Macquarie Island: a) Desidae (pitfall), b) Staphylinidae (count), c) Agriolimacidae (count), d) Agriolimacidae (pitfall). Grey shading indicates the 95% confidence intervals.

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Slope

Most models that included slope were weakly positive and from native families. Abundance in Aphididae (pitfall, litter, sweep, count), Desidae (count)(Figure 5-9b), Linyphiidae (sweep, pitfall)(Figure 5-9a), Pseudocaelcillidae (litter), Punctidae (count), Pyralidae (count), Thripidae (litter) increased as slope increased. Linyphiidae (count) and Annelida (count) decreased as slope increased. Several responses included increased abundance up to a certain level of slope, but decreased with the steepest slopes (Agriolimacidae, Doliochopodidae and Punctidae – litter (Figure 5-9c); and Desidae - pitfall). Staphylinidae (pitfall)(Figure 5-9d) showed the inverse trend. For four families where multiple methods indicated an abundance response to slope, trends were largely similar, except for the negative relationship found in Linyphiidae (count), which was opposite to the positive relationship found for pitfall, sweep and litter data.

Solar Radiation

Solar radiation was mostly positively correlated with abundance in both native and non- native families. Agriolimacidae (count), Aphididae (litter, sweep, pitfall, count), Desidae (pitfall, count) Doliochopodidae (sweep), Pseudocaeciliidae (litter), Punctidae (count, litter)(Figure 5-10b), and Pyralidae (count) all indicated increases in abundance with increasing solar radiation, while count catches of Annelida (Figure 5-10a) and Linyphiidae decreased (Figure 5-10c). Agriolimacidae (litter) initially decreased before increasing as solar radiation increased.

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Figure 5-9 Examples of partial residual plots generated from generalised additive models and illustrating invertebrate abundance relationships to slope (degree) on Macquarie Island: a) Linyphiidae (pitfall), b) Desidae (count), c) Punctidae (litter), d) Staphylinidae (pitfall). Grey shading indicates the 95% confidence intervals

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Figure 5-10 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to solar radiation (Wh/m²) on Macquarie Island: a) Annelida (count), b) Punctidae (litter), c) Linyphiidae (count), d) Australimyzidae (pitfall). Grey shading indicates the 95% confidence intervals

Wind speed

The relationship between wind speed and abundance was variable across taxa and for specific taxa across methods. Most wind speed relationships were detected for native species. Wind speed was only significant across multiple methods for Australimyzidae flies (litter –Figure

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5-11a, pitfall, sweep; all variable correlations), Doliochopodidae wingless flies (count - positive, litter – negative) and Desidae spiders (sweep – positive, count – positively asymptotic). Australimyzidae (litter) and Staphylinidae (count) (Figure 5-11b) indicated initial decrease in abundance before plateauing at moderate wind speed and finally increasing in abundance with elevated wind speed. Interestingly, Pyralidae (sweep), represented by the native moth Eudonia mawsoni, increased in abundance with increasing wind speed.

Figure 5-11 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to wind speed (kts) on Macquarie Island: a) Australimyzidae (litter) and b) Staphylinidae (count). Grey shading indicates the 95% confidence intervals.

Wetness

The models that included wetness overwhelmingly indicated positive relationships for both native and non-native families. Of the 20 best models that included wetness, only four did not show linear positive correlations. The exceptions were Janiridae (count, litter), and Geoplanidae (count) which showed variable relationships but lacked data, and Doliochopodidae (count) (Figure 5-12a) which initially increased in abundance to a moderate wetness, then decreased as wetness increased. Staphylinidae was the only family not correlated to wetness by any trapping method.

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Figure 5-12 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to wetness (index) on Macquarie Island: a) Doliochopodidae (count) and b) Thripidae (sweep). Grey shading indicates the 95% confidence intervals.

Ridge

Relatively few families indicated relationships with ridge, and in those that did, the relationships were variable. Australimyzidae (litter) were the only group to show a discernible decrease with increasing ridge, while Pyralidae (sweep), Punctidae (count, litter), Thripidae (sweep) all showed increases. Staphylinidae (pitfall) decreased initially, then increased. Aphididae were the family most modelled as responsive to ridge, and the correlations were generally first decreasing, then peaking at a moderate ridge, before decreasing with increasing ridge (Figure 5-13a, b).

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Figure 5-13 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to ridge (‘ridgeness’ index as defined by Bricher et al. 2013) on Macquarie Island: a) Aphididae (sweep) and b) Aphididae (litter). Grey shading indicates the 95% confidence intervals.

Vegetation

Vegetation was an important factor in explaining the variability in abundance for all families except for Aphididae and Staphylinidae. Patterns of abundance in the five vegetation communities were similar across methods for most families - for example in count, litter, pitfall, and sweep data for Australiamyzidae Figure 5-14a, b, c, d) and Thripidae litter (Figure 5-15b) and sweep samples. The Stilbocarpa vegetation community consistently showed high abundance across families often followed by tall grassland. Exceptions were Pyralidae (count)(Figure 5-15a), Punctidae (count, litter) which were higher in abundance in herbfield and/or feldmark and Thripidae (litter, sweep) for which shortgrass held higher abundance.

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Figure 5-14 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to vegetation community on Macquarie Island: a) Australimyzidae (sweep), b) Australimyzidae (pitfall), c) Australimyzidae (litter), d) Australimyzidae (count). Grey shading indicates the 95% confidence intervals.

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Figure 5-15 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to vegetation community on Macquarie Island: a) Pyralidae (count) and b) Thripidae (litter). Grey shading indicates the 95% confidence intervals.

Across all sampling years, some invertebrate groups consistently favoured some habitats, while others were less discriminating (Appendix 3, Figure 1). For example, Diapriidae (wasps) were only found in Stilbocarpa and Tallgrass sites whereas Staphylinidae, Linyphiidae, Punctidae, and Agriolimacidae were found across habitats but were less abundant in feldmark sites. Doliochopodidae and Annelida were prevalent across all habitats more or less equally. Exceptions to strong habitat preferences were Aphididae and Staphylinidae - the former a herbivore characterised by a generalised diet (Hänel 1999), and the latter a widespread group of predatory beetles (Greenslade 2006).

Year

Year occurred as a significant explanatory variable in 20 abundance models including two non-native families and nine native families. According to the 95% confidence intervals in the partial residual plots, the differences between years for many families were not significant, although models consistently showed an increasing trend over time for most families. Exceptions were Staphylinidae (litter) and Thripidae (litter) which both significantly increased between 2015 and 2016-17 (Appendix 3, Figure 2).

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Non-native species

The best models indicated that non-native species were an important predictor in at least one model across all families, with 25 of the 51 models including at least one non-native family interaction. Within these 25 models, 24 non-native family interactions were negative and 14 were positive. Seven of the 25 models with non-native species interactions were non-native species interacting with other non-native species - four Aphididae (3 positive, 1 negative), two Agriolimacidae (1 positive, 1 negative) and one Janiridae (one model including 4 negative interactions with other non-native families). Models for native families Desidae and Australimyzidae most consistently included interactions with non-native families. Only one model included non-native Sciaridae as an interaction, (a positive interaction with native Linyphidae (pitfall)), whereas the other six non-native families occurred in 6-8 models of other families. Across models, where interactions with non-native families Calliphoridae and Aphididae were identified, they were mostly negative (5 negative, 1 positive), except for models including interactions with non-native Chironomidae which were mostly positive (5 positive, 3 negative). Other non-native families that were identified interacting with other native or non-native families were Geoplanidae (2 positive, 4 negative interactions); Agriolimacidae (3 positive, 3 negative); Janiridae (3 positive, 4 negative). Eleven native species models including interactions with non-native families were positive for native families, and seventeen were negative. Annelida (count), as a group comprised of native and non-native species, indicated a positive interaction with non-native Agriolimacidae while Annelida (litter) show a negative interaction with non-native Geoplanidae.

Indicator species

Twelve families, nine Insecta and three non-Insecta, were identified as suitable indicators for one or more vegetation communities (Figure 5-15). Five of these families were non-native. Pyralidae, represented by the endemic moth E. mawsoni, was the only indicator for feldmark together with short grassland, whereas several families were highlighted as indicators for Stilbocarpa and tall grassland. The herbivorous Thripidae (the native thrips species Physemothrips chrysodermus) were indicators in short and tall grasslands. Native Staphylinidae (predatory rove beetles – five species), Agriolimacidae (the non-native slug species Deroceras reticulatum) and Linyphiidae (two native spider species), all abundant and

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widely distributed families, were indicators of multiple vegetation communities. The indicator analysis did not produce any specific indicators for herbfield.

Table 5-3 Invertebrate families identified as indicators of different vegetation communities found at Macquarie Island (via Inval indicator analysis).

Vegetation Indicators Test statistic Significance

Stilbocarpa 0.805 0.001 Geoplanidae 0.384 0.002

Feldmark – Short grass Pyralidae 0.598 0.001

Short grass – Stilbocarpa Aphididae 0.564 0.001 Janiridae 0.381 0.001

Shortgrass – Tall grass Thripidae 0.745 0.001

Stilbocarpa – Tall grass Australimzidae 0.89 0.001 Pseudocaeciliidae 0.697 0.001 Diapriidae 0.257 0.037

Short grass – Stilbocarpa – Tall grass Linyphiidae 0.88 0.001

Herbfield – Short grass – Stilbocarpa – Tall grass Staphyliniidae 0.743 0.001 Agriolimiacidae 0.735 0.001

Community

Community based models indicated that both vegetation and year were significant predictors (p<0.001) of variation in community composition, indicating that community composition differed in relation to different vegetation types and across time. All environmental parameters except for ridge were significant (p<0.001) drivers of community composition.

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This was consistent with abundance models in which relatively few families indicated a relationship to ridge.

DISCUSSION

Macquarie Island provides an ideal and unique environment to examine the relationship between invertebrates and their environment. In this study, we undertook research to clarify these complex relationships, and highlight the potential of invertebrates as bioindicators. Bioindicators are taxa or functional groups that are used as proxies to ‘indicate’ the state of the environment, monitor specific ecological characteristics or stresses, or reflect levels of biodiversity (McGeoch 1998; 2007; Hutcheson et al. 1999; Gerlach et al. 2013). Bioindicators can be particularly useful for monitoring the effects of habitat management and the progress of restoration (Kremen et al. 1993; Towns et al. 2009; Gerlach et al. 2013). In Chapter 4, we explored the suitability of invertebrates as biodindicators to document ecosystem restoration following a multi-species invasive mammal eradication program on an island. Here, we follow on from this work to explain and interpret the observed response. We utilised data from more comprehensive surveys, using multiple trapping techniques and modelling, to understand what factors drive invertebrate richness and abundance.

Chapter 4 highlighted that invertebrate abundance is influenced by multiple ecosystem variables. We expected that vegetation and elevation would be important drivers of invertebrate communities, as previous modelling had suggested for Macquarie Island (Davies and Melbourne 1999; Terauds et al. 2011), elsewhere in the region (Gabriel et al. 2001; Davies et al. 2011), and for similar tundra-like environments in the high Arctic (Bowden and Buddle 2010; Rich et al. 2013; Hansen et al. 2016b; Hein et al. 2019). Here, our more comprehensive study confirmed elevation and vegetation as significant drivers of invertebrate richness and abundance across families, guilds and trapping methods, particularly for native species. However, we found key model predictors interacted to drive the abundance of invertebrate groups depending on status – i.e. Insecta and non-Insecta, non-native species and native species, and between different feeding guilds. The exception was vegetation, which was an important predictor for all families across both Insecta and non-Insecta, and regardless of feeding guild. Vegetation was also found to be more important for native species than non- native species, which is consistent with previous modelling for Collembola on Macquarie

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Island (Terauds et al. 2011) and Marion island (Gabriel et al. 2001). The highest richness and abundance of invertebrates were found in tall grassland, short grassland and Stilbocarpa polaris herbfield (we refer to as ‘Stilbocarpa’), which could be considered the most productive habitats and were historically most impacted by rabbits (Scott and Kirkpatrick 2008; Whinam et al. 2014). Stilbocarpa supports a distinct invertebrate assemblage (Davies and Melbourne 1999), and we found it to hold the greatest abundance and diversity of invertebrates. Other than this habitat providing direct resources, the microclimate Stilbocarpa creates could be responsible for its favourability to particular taxa (Davies and Melbourne 1999). For example, a S. polaris dominated community creates a moist, low wind environment under its closed canopy (Davies and Melbourne 1999), and such moisture-rich environments are preferable to some invertebrates. Indeed, we found positive correlations with wetness for most invertebrate families on Macquarie Island, but particularly for non- native species (Figure 5-12).

Increased wetness was the strongest driver of non-native species abundance, occurring in even more models than vegetation. This is finding is consistent with results of Collembola research elsewhere in the SOI region (Convey et al. 1999; Gabriel et al. 2001), whereby non- species prefer more moist habitats, and native species are found in higher abundance in drier, more mineral soils (Convey et al. 1999; Gabriel et al. 2001; Hugo et al. 2004). Indeed, we also found native invertebrates were more likely to be positively correlated with increased slope and ridge, variables both related to improved drainage. In the Arctic, soil moisture is also identified as a strong driver of local-scale assemblage patterns (Hansen et al. 2016a, b; Høye et al. 2018), although the relationship between this variable and native and non-native invertebrate abundance seemingly remains to be determined. Identifying correlations between invertebrate abundance and wetness has important implications for understanding invertebrate recovery following mammal eradication as there is some evidence that soil moisture increases in some habitats with both the removal of dominant vegetation by rabbits (Brothers and Bone 2008), and reductions in seabird disturbance through rodent-driven population declines (Fukami et al. 2006; Mulder et al. 2009). Accordingly, our results show that habitat moisture changes associated with invasive mammals would have impacted both native and non-native invertebrates, in positive and negative ways respectively, via their relationship with habitat wetness. However, the return of burrowing seabirds and recovery of vegetation cover following eradication of invasive mammals may decrease soil moisture and surface water transport in the post-eradication ecosystem, restoring natural soil hydrology. In

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this instance, native invertebrates that prefer drier, more mineral sites (Convey et al. 1999; Gabriel et al. 2001; Hugo et al. 2004), may be advantaged in the short term. However in the long term, given the current and project changes to the island’s climate including increased but sporadic rainfall matched with atmospheric warming and drying (Adams 2009; Bergstrom et al. 2015), non-native invertebrates with their preference for wetter sites, in combination with their superior ability to survive desiccation (Chown et al. 2007), will likely outcompete native invertebrates.

While wetness was an especially strong predictor of non-native species abundance, elevation was an equally strong predictor of abundance for all families. The decline in invertebrate richness and diversity with increasing elevation has been observed on Macquarie Island and elsewhere across the SOI region (Convey et al. 1999; Davies and Melbourne 1999; Gabriel et al. 2001; Davies et al. 2011; Terauds et al. 2011; Hugo-Coetzee and Le Roux 2018). Similar results have been found for spiders in comparable habitats in the Arctic region (Bowden and Buddle 2010; Dahl et al. 2018; Hein et al. 2019), although more unique species are found at higher elevation plots (Høye et al. 2018). Measured effects of elevational gradients on alpine arthropods have been found to be more complex (Hodkinson 2005; Jing et al. 2005). Increased elevation on SOI is associated with declining environmental favourability (Davies and Melbourne 1999; Chown and Convey 2016; Hugo-Coetzee and Le Roux 2018; Ouisse et al. 2020), with temperature decreases and wind speed increases observed along the elevation gradient. However, the ability of some invertebrates to be collected via traps at higher elevations is also compromised by reduced mobility with declining temperature (Chown et al. 2004) and interactions between elevation and other variables (e.g. aspect and vegetation - Davies and Melbourne 1999; Hugo-Coetzee and Le Roux 2018) makes interpreting species responses more complex. For example, Desidae spiders (in pitfalls) and Punctidae snails (in litter) were the two groups that showed definitive increases in abundance with elevation, which is possibly due to their cold tolerance, but also possibly due to their tolerance to wind speed given they are slow-moving, non-flighted and often close to the ground. In contrast, the winged endemic moth E. mawsoni was positively correlated with wind speed, but this may reflect its preference for habitat types found on the elevated and invariably windier plateau. Indeed, the indicator analysis selected the moth as the best indicator of short grassland and feldmark communities, which dominate the higher elevations (Selkirk et al. 1990). The trend of Staphylindae beetle abundance, which fell sharply with increasing elevation initially and then flattened out at moderate elevation, could be indicative of the multiple species within

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this group with different habitat preferences and distributions. Four of the species - Omaliomimus venator, O. albipennis, Sulcithorax helmsi, S. sulcithorax – are found exclusively in lowland, coastal sites (Greenslade 2006), whereas Leptusa antarctica is widespread from the coast to the plateau, but most common between 100-200 m a.s.l (Davies and Melbourne 1999). In the context of this potential complex interplay between parameters, local and functional knowledge are key to interpreting responses to elevation.

Another key variable was solar radiation. Both native and non-native species abundance showed a generally positive relationship with solar radiation, which is a proxy for aspect. Higher solar energy areas (indicating higher energy availability) are known to support more individuals and species (Evans et al. 2005). Just as temperature is a strong driver of invertebrate abundance and diversity in the northern polar high Arctic tundra (Loboda et al. 2017; Bowden et al. 2018), energy availability is known as a major correlate of abundance and diversity in both native and non-native species in the southern polar region, i.e. warmer SOI are more speciose (Chown et al. 2005; Leihy et al. 2018). Climate change on SOI manifests as increases in temperature, higher mean wind speed, changes to solar radiation, and decrease in mean annual precipitation (Smith 2002; Davies and Melbourne 1999; le Roux and McGeoch 2008a; Adams 2009; Lebouvier et al. 2011; Bergstrom et al. 2015). The interaction of these variables can have flow on effects on native invertebrates, as they affect altitudinal patterns of native vascular species richness and community composition (le Roux and McGeoch 2008b), drive soil moisture and peat accumulation,(Smith and Steenkamp 1990; Gabriel et al. 2001), and can transform habitats at higher elevations that were previously sub-optimal into conditions progressively more suitable to invasive species (Ouisse et al. 2020). However, in contrast to other SOI, the precipitation trend on Macquarie Island in the last ~40 years has been one of significant increase (up 35% on annual precipitation), albeit mostly as winter rainfall, and characterised by increased storm events with intermittent dry spells (Adams 2009; Bergstrom et al. 2015). These dry spells are associated with reduced cloud cover, increased sunshine hours, and warmer temperatures (Adams 2009; Bergstrom et al. 2015). Endemic high-altitude plant species are already being impacted (Bergstrom et al. 2015). Although native invertebrates perform equally to non- native invertebrates up to certain temperature thresholds, their upper thermal tolerance is generally lower than non-natives (Janion et al. 2010; 2018), which out-perform native species through superior reproductive performance and enhanced phenotypic plasticity (Chown et al. 2007; Slabber et al. 2007; Janion et al. 2010; Janion et al. 2018; Ouisse et al. 2020). Thus, a

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warmer future climate on SOI will benefit non-native invertebrates and disadvantage native invertebrates. Native species with a preference for cooler conditions in elevated habitats will have no room to expand their range, while non-native species will expand their range attitudinally and also outcompete low-elevation native species with their high reproductive rates in the warmer environment (Janion et al. 2010; Ouisse et al. 2020). Already, some of the most invasive invertebrates on SOI, reach exceptional abundances in lowland areas, sometimes displacing native species (Convey et al. 1999; Gabriel et al. 2001; Frenot et al. 2005). Invasive carabid beetles on Kerguelen have already been observed adapting and advancing to higher elevations with ameliorating climatic conditions (Ouisse et al. 2020).

In addition to the environmental variables, we also detected interactions between the abundance of non-native invertebrates and native invertebrate species. This is the first time a test of such interactions across a broad suite of invertebrates has been performed in the region. Previously, positive relationships have been identified between native and non-native Collembola species richness and density on Macquarie Island (Terauds et al. 2011) and for insects in the SOI region (Chown et al. 2005). Here, for both Insecta and non-Insecta on Macquarie Island, we found non-native species typically interacted negatively with native species, particularly with herbivores. In some instances, this negative interaction might reflect competing requirements for micro-environmental conditions, such as moisture preferences of native Punctidae, non-native Janiridae and Agriolimacidae (Greenslade 2006), or direct competition for food, such as negative interactions with the endemic moth E. mawsoni (Pyralidae) and the aphids, generalist herbivorous feeders (Aphididae). Other negative correlations we detected may not be interactions at all, but more likely reflect the habits or ranges of one invertebrate group directly opposing the other (e.g. Pyralidae and Janiridae). Janiridae for example, are not only restricted in distribution on the island, but prefer moist sites with high levels of humus under vegetation (Greenslade 2006), which are not the preferred sites of Pyralidae. More work is required to determine whether relationships between native and non-native invertebrates vary depending on vegetation type (Terauds et al. 2011). We also found that the abundance of some non-native species were correlated with the abundance of another non-native species. Interestingly, this correlation was also mostly negative, which might indicate competition between non-native species. Such interactions provide some explanation for the variable responses in Macquarie Island invertebrate fauna detected by Houghton et al. (Chapter 4) following the recent mammal eradication. The results of this chapter show that some invertebrate responses may be influenced by negative

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interactions, or competition with, non-native invertebrate species, thereby influencing the trajectory of the island ecosystem recovery. Further species-specific investigations of these interactions are necessary to understand the full nature and extent of their impact.

Understanding temporal variation in invertebrate abundance and richness is a critical aspect of monitoring environmental change, particular following management interactions like eradications. The benefit of sampling over successive seasons while an ecosystem is in post- eradication flux, is that yearly changes may indicate annual increments of recovery following eradication, perhaps as vegetation and associated canopy cover rebounds (Scott and Kirkpatrick 2013; Whinam et al. 2014). Significant differences were highlighted by the community analysis between invertebrate communities in all habitats, and between each sampling year, and we detected an increasing trend in richness over time. It is possible that some of this increase could be attributable to improvements made to our survey design each year, as vegetation beating was incorporated into the trapping regime in 2016-17, and yellow pan traps in 2018. Both these methods are likely to have increased the diversity of the overall catch, although for yellow pan traps macro-invertebrate catches were typically low.

The final compilation of best models included a relatively low number of pitfall models, consistent with the findings in Houghton et al. (2019b), that pitfalls, although they trap high abundance of some taxa, do not typically reflect overall invertebrate diversity. Indeed, the only method by which richness did not increase over time was for pitfalls. This is important when analysing historical data (such as Davies and Melbourne 1999, or Houghton et al. Chapter 4) or in designing future monitoring. Pitfall traps are simple, inexpensive, easy to deploy, and yield high numbers of specimens, thus they are the most frequently and widely used invertebrate trapping method (Ward et al. 2001; Woodcock 2005; Skvarla et al. 2014). However, a range of limitations have been identified in their use, including the effect of surrounding vegetation structure, biases towards particular taxa and larger taxa, and differing catches according to trap diameter (see discussion in Chapter 4). We used a range of trapping methods to counter some of these biases, allowing for detailed analysis of abundance that was not possible in in historical surveys (such as for Davies and Melbourne 1999).

Our study also provided important insights into understanding invertebrate drivers on Macquarie Island in the context of vegetation changes related to rabbits (Scott and Kirkpatrick 2008; Whinam et al. 2014). We found highly rabbit-damaged vegetation

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communities, namely short and tall grass lands and Stilbocarpa habitats (Scott and Kirkpatrick 2008; Whinam et al. 2014), held the highest invertebrate richness and abundance. Several invertebrate families were highlighted as specific indicators for rabbit-impacted habitats, and ubiquitous invertebrate species on the island appeared as indicators of multiple habitats, demonstrating their wide distribution. While useful, the indicator analysis also had some limitations, as some groups were identified as indicators of a specific habitat despite their prevalence in other habitats (e.g. Geoplanidae), perhaps reflecting high numbers caught at specific sites. Some were also identified as specific habitat indicators despite their locally restricted distribution (e.g. Janiridae). To be effective, the implementation of future monitoring programs, and the bioindicators used, should incorporate local knowledge.

Our finding, that habitat quality (i.e. the degree to which it is impacted by invasive mammals) is a key driver of species richness and abundance for invertebrates on Macquarie Island, greatly assists in the evaluation of post-eradication ecosystem responses discussed by Houghton et al. (Chapter 4). However, our study also suggests that some non-native invertebrates have also benefitted from the mammal eradication and are impacting on native species. By establishing an invertebrate community baseline on Macquarie Island, in the relatively recent absence of invasive mammals, selecting key taxa as indicators of vegetation communities, and in combination with detailed trapping advice as recommended by Houghton et al (2019b), we now possess the knowledge and tools to effectively monitor outcomes for both non-native and native invertebrates on the island in key habitats as they change over time. This work contributes to the body of knowledge which develops and assesses terrestrial invertebrate indicators for conservation planning and management – an under-explored field with enormous potential application for land managers (Kremen et al. 1993). Implementing a long-term monitoring plan for invertebrates on Macquarie Island will provide further insights into the magnitude of impact exerted by non-native invertebrates in the ecosystem, a realm in which many questions remain. In conclusion, we have highlighted many interactions between native and non-native species on Macquarie Island, but the extent of their ecosystem impact is still unknown. This finding reinforces the importance of biosecurity in preventing further incursions of non-native invertebrates into the Macquarie Island environment.

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Chapter 6 | Species traits can predict invertebrate invasions on Southern Ocean Islands

Melissa J Houghton, Aleks Terauds, David Merritt, Steven Chown and Justine D Shaw

ABSTRACT

Invasions are contingent on the initial dispersal and subsequent establishment of a species into a new environment. Biosecurity is the most effective and economic way to manage unwanted dispersal. Historically, dispersal to the islands of the Antarctic region has been limited by their isolation and low ambient air temperatures. However, accelerating human activity in the region, coupled with climate change, increases the likelihood that alien species, especially invertebrates, will be introduced and establish. Alien invertebrates are already established and having impact in the Antarctic and Southern Ocean Islands. While the pathways and vectors of alien invertebrate transport to the Antarctic have been relatively well-investigated, our ability to identify high-risk taxa to inform targeted biosecurity has not been tested.

We test the hypothesis that invertebrate species traits – body size, vagility and guild – determine their capacity to establish on remote, sub-Antarctic Macquarie Island. We identified these traits for invertebrates occurring on Macquarie Island as indigenous, established-aliens and transient-aliens. We also examined the traits of taxa that have been ‘detected’ – i.e. being transported to the island through Australian Antarctic Program cargo and personnel transport. In total, 270 taxa were included in the analyses. Generalised additive models indicated that established taxa were significantly smaller in body size taxa that had not established. However, this varied according to feeding guild. Detected and transient-alien taxa were generally winged, larger in size, and comprised of high proportions of herbivorous invertebrates. Indigenous species and established-aliens shared similar traits. Established taxa were more likely to be wingless, detritivorous and relatively small.

This is one of the few examples of an empirically-based assessment of the establishment risk of multiple invertebrate species on an isolated, biogeographically distinct region. Despite low detections of small, non-vagile taxa in standard biosecurity processes implemented through

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the Australian Antarctic Program, it is these taxa that are most likely to establish. We use these findings to identify and propose future mitigation measures.

INTRODUCTION

Invasive alien species affect ecosystems worldwide. Species that are ‘alien’ are those introduced to a novel location, usually via human activity (Frenot et al. 2005). They can drive biodiversity loss, species extinctions and cause irreversible changes in ecosystem structure and function (Mooney and Cleland 2001; Simberloff et al. 2013). Globally, and particularly for the Antarctic region, climate warming and increased human activity are likely to reduce barriers to invasion, enabling the colonisation of (Chown et al. 1998; Frenot et al. 2005; Walther et al. 2009; Janion et al. 2010; Chown et al. 2012, Nielsen and Wall 2013; Duffy et al. 2017). Almost all Southern Ocean Islands (SOI - for biogeographic definition, see Shaw et al. 2010) are climatically suitable for many of the world’s 100 worst invaders, and are predicted to be suitable for more species with climate change (Duffy et al. 2017). Hundreds of species have been introduced to SOI with over 280 plant and 180 insect species now established (Frenot et al. 2005; Shaw et al. 2010; McGeoch et al. 2015). Many of these species have deleterious impacts on the island ecosystems (Convey et al. 2006b; Terauds et al. 2011; Chown and Convey 2016). Terrestrial ecosystems in the region are characterised by high levels of endemism, low species richness, narrow habitat ranges and simple community structures (Convey 1996; Convey et al. 2006b; Chown and Convey 2016). Native invertebrates have adversity-selected life history traits that limit their capacity to compete with alien species (Convey 1996; Convey et al. 2006a; Chown and Convey 2016). It is difficult to quantify the full extent of alien invertebrate impacts on ecosystem structure and function on SOI (although see Houghton et al. 2019 for a summary of the literature).

The paucity of knowledge regarding alien invertebrate impacts on SOI means that risks associated with new introductions are largely unknown (Houghton et al. 2019). While there is an existing body of knowledge on alien invertebrate propagule pressure, pathways and vectors (e.g. Whinam et al. 2005; Lee et al. 2009; Chwedorzewska et al. 2012; Hughes et al. 2010), biosecurity efforts can be further improved by identifying and targeting high-risk taxa (Frenot et al. 2005; Houghton et al. 2016; Newman et al. 2018). While Newman et al. (2018) call for improved biosecurity surveillance through pre-emptive identification of potential

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invaders (e.g. Duffy et al. 2017), improved identification of high-risk taxa is still required (McGeoch et al. 2016; Duffy et al. 2017; Greve et al. 2017; Hughes et al. 2019). Such identification is also called for by the ’s Committee for Environmental Protection (CEP 2011) and SOI management plans. A risk-ranking strategy was developed for a small subset of invertebrates (Collembola) by Greenslade (2002) and Greenslade and Convey (2012), but a traits-based assessment that identifies predictors of introductions and establishment across all invertebrates has yet to be undertaken. Such an assessment is needed to help prevent future invasions of the SOI.

Comparisons between invasive and non-invasive species traits can contribute to our understanding of the role of traits in invasion success (Hayes and Barry 2008; Zenni and Nuñes 2013). Due to the volume and diversity of invertebrate species, it is challenging to undertake broad-scale, trait–based approaches, particularly since many species are undescribed or have not been studied (Clark and May 2002). There is a deficit of knowledge on life-history and other traits for invertebrates globally, with the exception of some crop pests, which are often more thoroughly studied (Hutcheson and Kimberley 1999). Consequently, obtaining comprehensive traits information for the large suite of invertebrates that could be potentially introduced to the SOI is challenging. Identifying a set of easily identifiable, representative traits is an important step to developing targeted biosecurity, and understanding the risks invertebrates pose across the region.

Specific characteristics or traits can make some species more prone to invasion that others (Sol 2008; Su et al. 2013). Thus, traits analyses have been found to be useful for determining the underlying risk of invasion for key species or groups in a wide range of contexts (e.g. for fish – Kolar et al. 2002; mammals - Capellini et al. 2015; aphids - Mondor et al. 2006; plants – Whitney and Gabler 2008, van Kleunen et al. 2010; invasive species to the European Union – Roy et al. 2019). Invasion theorists widely accept that propagule pressure – ie increased introductions of high numbers of individuals is the major contributing factor to increased chance of establishment and invasion success across the globe (Rouget and Richardson 2003; Lockwood et al. 2005; Coulatti et al. 2006; Drury et al 2007; Sol 2008; Simberloff et al. 2009; Blackburn et al. 2013; Su et al. 2013). Amongst many other attributes, adaptability, high reproductive capacity, good dispersal ability, and association with human activity, are regarded as potential contributors to a species’ invasive potential (Su et al. 2013). Alien species that fill novel roles or functions within an invaded ecosystem may also be more likely

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to be successful (Colautti et al. 2014; Fetahi et al. 2011), and/or they interact in novel ways with other non-native species (Simberloff and Von Holle 1999) and/or they are able to use resources not exhausted by natives (Case 1990). Such traits-based invasion theory and risk analyses are in largely based on plants (e.g. Whitney and Gabler 2008; van Kleunen et al. 2010; Tecco et al. 2010; Bennet 2013), for which it has proven difficult to identify traits that consistently predict invasive potential (Catford et al. 2009; Pyšek and Richardson 2007; van Kleunen et al. 2010). Determining which traits facilitate invasion success in invertebrates is further complicated by the lack of detailed information for many of the diverse range of species (Hutchenson et al. 1999; Clark and May 2002). To date, little research has tested test trait-based invasion theory for invertebrates on SOI (although it has been undertaken for plants on Marion Island – Mathakutha et al. 2019). This is despite there being far more invasive invertebrates than plants and vertebrates in the region (McGeoch et al. 2015). Although there have been no comprehensive trait assessments of SOI invertebrates, some small studies have looked at key attributes. For example, thermal tolerances of indigenous and alien springtail survival were assessed under future climate warming scenarios (Slabber et al. 2007; Janion-Scheepers et al. 2018). Other studies have determined that polyphagy (Hullé et al. 2010, for aphids), broad thermal tolerance (Frenot et al. 1992, for slugs; Laparie and Renault 2016, for beetles), parthenogenesis (Frenot et al. 2005; Lee et al. 2007; Hullé et al. 2010; Hughes et al. 2019) are all linked to invasion success of invertebrates in the region. Alien invertebrates can represent novel guilds or functional groups on SOI, being absent or under-represented in indigenous invertebrate assemblages; for example pollinators (Convey et al. 2010), predators (Lebouvier et al. 2011; Laparie et al. 2010; Ernsting et al. 1999; Greenslade et al. 2007), and macro-detritivores (Smith and Steenkamp 1992; Jones et al. 2003b; Greenslade et al. 2008). Dispersal ability is also an important trait in species establishment across the region (Gressit 1970; Greve et al. 2005; Hughes et al. 2019).

Body size is widely used as proxy for a range of other traits as it is relatively easy to measure and indicative of other complex life history and ecological features (Peters 1983; Woodward et al. 2005). It is linked to numerous physiological and ecological characteristics (Roff 1981; Peters 1983; Gaston et al. 2001; Savage et al. 2004; Kingsolver and Huey 2008; Gouws et al. 2011; Chown and Gaston 2010) and is known to influence species interactions (Cohen et al. 1993; 2003; Woodward and Hildrew 2002; Loeuille and Loreau 2006). Body size relationships exist between temperature and metabolic rate, growth and reproduction, survival probability, abundance and dispersal (Peters 1983; Lawton and Brown 1986; Brown et al.

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1993; 2004; Gaston et al. 2001; White et al. 2007). Body size is also thought to influence establishment spread and in a new location (e.g. theory - Lawton and Brown 1986; Brown and Silby 2006; birds - Veltman et al. 1996; marine bivalves - Roy et al. 2002; and fish - Schröder et al. 2009). Although small organisms are typically more populous and widespread (Gaston and Lawton 1988), larger individuals usually have fitness advantages over smaller ones (Reim et al. 2006, and references within; Moya-Laraño et al. 2007; Kingsolver and Huey 2008), and the probability of establishment increases with body size (Lawton and Brown 1986).

Here, we develop a trait-based assessment of establishment risk for invertebrates introduced to sub-Antarctic Macquarie Island (54.62° S, 158.85° E), via the activity of the Australian Antarctic Program, which is the primary agency responsible for transport of cargo and visiting expeditioners. We examine assemblages of invertebrates along all stages of the introduction pathway to Macquarie Island – i) detected at the point of entry and in transit (‘detected’), ii) transported and arrived at the destination but not established (‘detected’ and ‘transient aliens’) iii) self-introduced but not established (‘transient aliens’), iv) transported, arrived and established (‘established aliens’), and v) self-introduced and colonised (indigenous).

The Australian Antarctic Program has stringent biosecurity protocols, involving multi-layered fumigation of cargo, insect trapping and inspections prior to loading and upon arrival at the island (Bergstrom and Shaw 2016). Macquarie Island has limited human settlement and a relatively comprehensive published record of indigenous and alien invertebrate species, incursions and detections (e.g. van Klinken and Green 1992; Richardson and Jackson 1995; Greenslade 2006; Greenslade et al. 2007; 2008; Houghton et al 2016). We use multivariate models to test the hypothesis that three invertebrate traits – body size, guild and vagility - determine invasion status. We use body size and guild to infer resource use and competition in a species-poor, low energy ecosystem and clarify the relationship and interactions between body size, feeding guild (e.g. predator, herbivore), dispersal ability and establishment status on Macquarie Island. We discuss the utility of these traits as predictors of invasion, and identify high-risk taxa to inform the development of regional biosecurity protocols.

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METHODS

Status

Invertebrates for this study came from two sources - those found on Macquarie Island and those detected en route or upon arrival to Macquarie Island. We defined the status of taxa in two ways. First, a categorisation was made based on their status at different points of the invasion pathway - ‘Detected’, ‘Transient-alien’, ‘Established-alien’, and ‘Indigenous’ (Table 6-1). ‘Taxa’ describes operational taxonomic unit, identified to the finest resolution possible with available resources. ‘Detected’ taxa were invertebrates collected at the initial barrier stage, during biosecurity surveillance associated with the Australian Antarctic Program in buildings, cargo, the cargo facility, aircraft, supply ships and upon arrival at the destination through cargo inspections (see Houghton et al. 2016 for details). ‘Transient-aliens’ describe a group of taxa that have either been intercepted alive in the island environment, often repeatedly, arriving either through human transport or natural means, that may have persist temporarily but have not established a breeding population. ‘Established-aliens’ are taxa at the end-point of the invasion pathway, having been transported to the island and established breeding populations either in the natural environment, or within human associated structures (synanthropic – see below). ‘Indigenous’ taxa have arrived by natural mechanisms throughout the island’s history and established breeding populations in the natural environment.

Second, we formed two broad groups: ‘Established’, and ‘Not-established’. ‘Established’ taxa were categorised as those breeding on the island, encompassing indigenous invertebrates and established-alien invertebrates. We also include in this category taxonomically related- detected taxa - a subset of the detected group, i.e. where the taxonomic family includes indigenous or established-alien taxon. This group was necessary due to the many detected taxa that were identified to family level only and where establishment could not be ruled out if the family was the same as known established-alien or indigenous taxa on the island. The second group - ‘Not-established’ – includes transient-aliens and ‘detected’ taxa, that have been intercepted at the source (wharf-Hobart), transit (supply ships) or end-point (island) of the invasion pathway, but have not established a breeding population.

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Table 6-1 The status of invertebrates on Macquarie Island and en route to Macquarie Island.

STATUS Non-indigenous Indigenous References/ Sources “Not- Transient alien:  Greenslade 2006 established” detected occasionally on the island. No evidence of a breeding population Detected: found en  Houghton et al. 2016 route on ships or in cargo “Established” All indigenous  Greenslade 2006 species occurring on the island Established-alien:  Greenslade 2006; found in the natural  Phillips et al. 2017; island  Greenslade 2010; environment, or  Surveys conducted by living in buildings Houghton et al. Chapter associated with 3-5. humans. A breeding population has been established. Related-detected:  Houghton et al. 2016; Thirty-one taxa  Greenslade 2006 only, sharing taxonomic family with an indigenous species or established-alien

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Status categories were delineated based on a range of sources, including The Invertebrates of Macquarie Island (Greenslade 2006), unpublished survey results and author observations. Some records in Greenslade (2006) were updated and/or synonymised, and alien taxa that were only described to order in Greenslade (2006) were removed from the analysis. Non- arthropod taxa were scarce in the detected and transient groups, such as annelids (worms), flatworms, nematodes and molluscs (snails and slugs). Hence, we removed them entirely from our analysis in order to make meaningful comparisons between status groups. Siphonaptera (fleas), although arthropods, were also removed from analysis for similar reasons. Arthropods that were recorded as being ‘synanthropic’ in Greenslade (2006) (i.e. established only alongside human activity, inside buildings, stored food etc. but not in the outside environment), were included in the ‘established’ group, given their potential to establish in the natural environment with changing environmental and climatic conditions, as has occurred previously (see for example, Volonterio et al. 2013; Phillips et al. 2017).

Vagility

For vagility we identified taxa as ‘winged’ or ‘wingless’, rather than strictly vagile (able to fly). This meant that some taxa were classified according to the presence of their wings, regardless of how often they fly. In this context, vagility was documented for each taxon either by direct observation from field survey samples, from an insect reference collection or from the literature.

Guild

We defined guild as a group of organisms that exploit one or more resources in a similar way (as per Root 1967; MacMahon et al. 1981; Blondel 2003). Guild is one facet of the ‘functional group’ concept describing how resources are processed, and the ecosystem services these species provide (Blondel 2003). Guild is independent of phylogenetic relationships but species of a common guild are often closely related and share similar life history traits through their common evolutionary history and adaptations to resources and habitats (Blondel 2003). Including guild as a trait is useful as it groups species involved in a competitive interaction, regardless of their taxonomic relationship (Root 1967). However, variation in resource use and guild allegiance can occur in species of the same taxonomic group (e.g. Hawkins and McMahon 1989). Grouping by guild captures an invertebrate’s

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interaction with existing species, its trophic position and resources required for successful establishment.

To assign guilds, we searched the primary literature for terms such as ‘herbivore’ or ‘detritivore’ for each taxon (Table 6-2). Where this was not clearly defined we searched further for descriptions of the taxon’s feeding behaviour, references to feeding, preferred food, or material processing. Where possible, this information was gathered for species. Otherwise, information on the genus or family was used. In a few cases, descriptions of the activity and behaviour were used (e.g. ‘compost-dwelling’, ‘abundant in decaying material’). We consolidated the range of feeding terminology into seven guild categories (Table 6-2). Many arthropods have different life stages that consume different resources. In these instances, i.e. where adult and larval stages occupied different guilds, we used guild combinations (e.g. herbivore-detritivore). In summary, including the combined categories, eleven guilds and guild combinations were determined for 130 detected taxa and 136 taxa from Macquarie Island (indigenous, established-aliens and transient-aliens).

Body Size

Body size measurements of ‘detected’ taxa were made using a Leica microscope model MZ95, with a Leica camera 10447367 063x attached and a Plan 1.0x 10446275 lens. ‘Body size’ was measured as the length from the front of the head to the end of the main body (i.e. insubstantial parts such antennae, anal spines, hairs etc. not included, but snouts included [e.g. weevils], and the large rear pincers of earwigs due to their substantive size). For beetles and spiders, it was usually possible to measure total body length in one measurement, dependant on the animal’s structure and/or state of dehydration. For irregularly shaped taxa or those deformed due to preservation, multiple measurements along the length of the body were taken across the angled segments. These measurements were then added to obtain total body length. Only whole animals were measured. Where more than one specimen of a taxon was found in a sample, each individual’s body size was recorded (up to 20 individuals per sample) and used to calculate the range, mean, and maximum body size. The mean of body size measurements of individuals from the same taxonomic unit or species that occurred in different samples was also calculated.

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Body size for indigenous, transient-alien and established-alien invertebrates found on Macquarie Island were either taken from published records or physically measured from field survey collections using the method above. Where neither of these options were available, individuals were measured from the Tasmanian insect collection at Biosecurity Tasmania, Department of Primary Industries, Parks, Water and Environment, Tasmania.

The ‘maximum’ size refers to the largest measured individual, or the maximum size given by the published range for the species. For smaller taxa such as mites and springtails, published size reports are often given as an ‘up to’ measurement. We recorded this as the maximum size and no mean was recorded. The size of single physically measured specimens that were only identified to family level resolution were recorded as the ‘maximum’. Due to the taxonomic resolution of most of these taxa we could not refer to a museum insect collection, instead relying on this single measurement. Using this approach we were able to source maximum body sizes for all 270 taxa, and a mean body size for 164 taxa. Here, we present analyses on the more comprehensive maximum body size data, but include analyses on mean body size in Appendix 4 (Figures 1-5). Table 3 and Table 4 in Appendix 4 include the full dataset with associated references for body size, guild and vagility.

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Table 6-2 Classifications used for our guild analyses including incorporated terms from the literature.

Guild Incorporated terms: Feeding includes: Detritivore Saprophagous  Feeding on decaying organic matter, Carrion-feeding detritus or gaining nutrition from liquid or Necrophagous solid decaying plants and animals Scavengers  Often generalist, opportunistic feeders of a Microbivorous wide range of materials, dried animals or insect remains and bacteria within, clothes, wool, feathers and fur. Herbivore Root-feeders  Feeding on any part of live plants, including Wood-borers roots, wood, leaves, algae, epiphytes, pollen Sap-feeders or nectar Pollen-feeders Nectarivores Algivores Microphytophagous Micro-epiphytye Not included - stored-product pests Predator Nematophagous  Hunting, preying and consuming other invertebrates (not microbes) Fungivore Phytophagous  Consume fungal parts, including spores Mycophagous Granivore Stored-product pest  Consuming dried foodstuff such as nuts, seeds, grains and flours Parasite Haematophagous  Majority of their lifecycle these animals live Blood-sucking inside or outside of the animals they feed on Ectoparasite  Some capture prey for their larvae to Endoparasite parasitise Parasitoids Predator-parasitoid Omnivore Generalist  Indiscriminately eat other animals, Herbivore-predator invertebrates, carrion or plants as both a Opportunistic grazer and a predator Polyphagous

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RESULTS

In total, 1280 individuals comprised the detected suite of invertebrates. Within this group, 626 were intact specimens available for body size measurement, and 134 arthropod taxa were identified. The Macquarie Island indigenous, established-alien, and transient-alien groups made up 134 arthropod taxa (Figure 6-1). In the detected group, six taxa were identified to Order only, and 63 to family level. Across all status groups, 115 were identified to genus, and 155 to species. A total of 126 taxa comprised the ‘Not established’ group, while there were 144 ‘Established’ taxa, including 31 from the detected group with taxonomic affinities to island established species Figure 6-1).

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134 144 41 126 22

Indigenous Established alien Transient alien Detected Established Not Established

Figure 6-1 Total number of taxa identified and analysed in each status group along the invasion pathway.

Eighteen arthropod orders were identified in total. The taxonomic richness of the detected and transient-aliens (i.e. species or genera or families that have not yet established on Macquarie Island) was higher than established-aliens and indigenous taxa. After considering the taxonomic affinities of detected and established species on the island, only nine orders had members in both the established and not-established groups (Table 6-1). More families of arthropods (from thirteen orders) were identified in the not-established group (75), than the established group (57), including 114 genera and 84 species – representing considerable colonisation pressure on Macquarie Island. The not-established arthropods comprised a mixture of taxa, whereas the established group was dominated by smaller taxa from Acarina and Collembola (Table 6-3).

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Body size overview

In total, 270 taxa were examined for body size. Maximum body size varied between status groups (Figure 6-2). Established-aliens on Macquarie Island ranged in size from 0.25-20 mm, with 88% being <5 mm (푥̅= 2.79, s = ± 3.66). Indigenous invertebrates on Macquarie Island were also small, ranging from 0.25-11mm (푥̅= 2.03, s = ± 2.13), with 90% < 5mm. Transient-aliens ranged from 0.3 – 31.5mm, with 55% < 5 mm (푥̅= 9.19, s = ± 9.25). The body size range of detected invertebrates was 0.37-51mm, with 41% < 5 mm (푥̅= 8.18, s = ±7.63).

Table 6-3 Proportional representation of taxonomic Orders per status group on Macquarie Island.

Order Common name Status %

Detected Established Indigenous Transient aliens aliens Acarina Mites 1 37 42 - Amphipoda Amphipods - 2 - - Araneae Spiders 12 - 4 9 Blattodea Cockroaches 1 - - - Coleoptera Beetles 27 12 7 9 Collembola Springtails 1 24 30 14 Dermaptera Earwigs 2 - - 5 Diptera Flies 22 7 14 23 Hemiptera True bugs 7 7 - 5 Hymenoptera Ants/wasps 7 - 1 5 Isopoda Woodlice - 2 - - Julida Millipedes 1 - - - Lepidoptera Moths 17 2 1 27 Neuroptera Lacewings 1 - - - Orthoptera Grasshoppers/crickets 1 - - - Psocoptera Booklice 1 - 1 - Thysanoptera Thrips - 2 1 5 Zygenotoma - 2 - -

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The Kruskal-Wallis test indicated significant differences between the maximum body size of the different status groups: X² (df = 3) = 96.39, p <0.001) (Figure 6-2). Post-hoc Wilcoxon- rank-sum results confirmed highly significant differences between the maximum body size of detected and indigenous taxa (p<0.001) and between detected and established-aliens (p<0.001), but not between detected and transient-aliens (p=0.66). Transient-aliens were likewise significantly different in size to the indigenous taxa (p<0.001) and established-aliens (p=0.002). Indigenous species and established-aliens were not significantly different in size (p=0.39).

For each order of arthropods, body size differed depending on status (Appendix 4, Table 1). Overall, orders within status groups indicated that taxa established on the island were smaller than non-established taxa. For example, transient-alien spiders and detected spiders ranged to greater maximum size (25.0 mm and 21.6 mm respectively) than indigenous spiders (6.5 mm). Similar results were found comparing detected and transient-alien Coleoptera and Lepidoptera to established aliens and indigenous species. The maximum and mean body size for indigenous Collembola (2.3 mm and 1.01 mm respectively) was smaller than the maximum and mean size of the ten established-alien Collembola (3.4 mm and 1.58mm respectively)(Appendix 4, Table 1).

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Figure 6-2 Variation in (log) maximum body size per status group along the invasion pathway; ‘detected’, ‘transient-alien’, ‘established-alien’, ‘indigenous’ and invertebrates associated with Macquarie Island.

Vagility

Indigenous taxa had relatively few winged species (19%) compared to transient taxa (73%) (Figure 6-3). Thirteen of the 41 established alien taxa had wings (32%), as did 100 of the 134 detected taxa (75%). There were 47 winged taxa in the established group (or 48%). Most of the 31 related-detected taxa that were considered established were winged (70%). The relationship between establishment and vagility was highly significant: x² (df = 1, N = 264) = 50.751, p <0.001), confirming that established invertebrates were significantly less likely to have wings than not-established taxa. Established-aliens and indigenous species were also found to comprise fewer winged arthropods than transient-aliens and detected arthropods: X² (df = 3, N = 264) = 118.57, p <0.001) (Figure 6-3).

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Figure 6-3 Percentage of winged and wingless arthropods in each of the four status groups: ‘Detected’, ‘Transient alien’, ‘Established alien’, and ‘Indigenous’

The GAMs showed that there were significant differences in body size of winged or wingless established taxa (as indicated by non-overlapping 95% confidence intervals in the term plots - Figure 6-4). The size class of established arthropods that were wingless were significantly smaller (1.83-2.70 mm) than winged established arthropods (3.86-6.55mm), and also significantly smaller than both winged and wingless taxa that were not-established (6.06- 11.01 mm and 8.0-11.17 mm respectively).

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Figure 6-4 Partial residual plots, from the model of maximum body size (mm) vs vagility, status and their interaction, showing predicted (log) body size for both ‘established’ and ‘not established’ groups and both winged or wingless arthopods. The vertical blue dashes present at the upper and lower margins of the plot represent the number of data points.

The proportion of winged taxa varied per guild. Detritivore-predators were all wingless, whereas granivore-detritivores and granivore-herbivores were 100% winged. Predators were only 16% winged, while herbivore-fungivores were 67%, herbivores 73%, and herbivore- detritivores 83%. In other guilds, vagility varied between 40-60% of members. We also used partial residual plots for each term in the GAM, to explore predictions of maximum body size in the context of both vagility and status (Figure 6-5). Confidence intervals from these plots also highlighted clear differences in the predicted size of winged or

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wingless taxa in relation to their status. Indigenous taxa were the only group that showed significant variation in body size between winged and wingless taxa. Winged indigenous species were predicted to be larger (3.2-10.26mm), than wingless (1.21-2.05mm). Figure 6-5 also shows that wingless indigenous species were smaller than both winged and wingless detected and transient-alien taxa, but not significantly smaller than winged or wingless established-alien taxa.

Guild

Guild was identified for 264 taxa across the four status groups (excluding six taxa identified to order level). The diversity and proportion of functional guilds of arthropod taxa varied between established and not-established groups (Figure 6-6), and also between the detected, indigenous, established-alien and transient-alien taxa (Table 6-2,Figure 6-7). Established arthropods were comprised mostly of detritivores (30%), predators (30%) and herbivores (17%), whereas not-established taxa were dominated by herbivores (33%), predators (20%), detritivores (15%) and omnivores (15%) (Figure 6-6). At the more detailed status level - indigenous taxa and established-aliens on Macquarie Island were predominantly detritivores (40%), predators (29%), and herbivores (Table 6-4, Figure 6-7). In contrast, most transient- aliens were herbivores (45%), detritivores (18%), and omnivores. The detected suite of arthropods were also dominated by herbivores (28%), but also predators (22%), detritivores, and omnivores.

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Figure 6-5 Partial residual plots, from the model of maximum body size (mm) vs vagility, status and their interaction, showing predicted (log) body size for each status group (Detected –D, Transient – T , Established – E, and Indigenous – I) and both winged and wingless taxa. The vertical blue dashes present at the upper and lower margins of the plot represent the number of data points.

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Table 6-4 Percentage of ‘indigenous’, ‘transient aliens’, ‘established aliens’ and ‘detected’ invertebrates represented by each of the eleven guild categories.

Indigenous Transient Established Detected alien alien Detritivore 40 18 22 17 Detritivore/ Predator 1 - 7 - Parasite 3 - 2 3 Grainivore/ - - 7 2 Detritivore Grainivore/ - 5 7 2 Herbivore Herbivore 15 45 15 28 Herbivore/ 1 9 5 5 Detritivore Herbivore/ 1 - - 2 Fungivore Omnivore 8 14 2 13 Predator 29 9 22 22 Fungivore 1 - 10 5

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Figure 6-6 The percentage of invertebrates found in eleven guild categories that are either ‘established’ on Macquarie Island or ‘not-established’.

Guilds also varied by size. As a group, herbivores were the largest. They ranged in size from 0.5mm to 40mm (푥̅= 9.69, s = ±10.39). Detritivores and predators were smaller, ranging 0.25 – 20mm for detritivores (푥̅= 3.64, s = ± 4.51), and 0.25-22mm for predators (푥̅= 4.79, s = ± 5.36).

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Figure 6-7 Percentage of invertebrates found in status groups along the invasion pathway ‘detected’, ‘transient-aliens’, ‘established-aliens’ and ‘indigenous’ from eleven guild categories.

We also used partial residual plots to explore predictions of maximum body size in the context of both establishment status and guild (Figure 6-8). Confidence intervals from these plots highlighted clear differences in the predicted size in some guilds in relation to their establishment status. For three guilds, body size of the established taxa were significantly smaller than their non-established counterparts: predators (established 1.79-3.35 mm, not- established 6.02-11.22 mm); herbivores (established 2.26-4.62 mm, not-established 10.77- 17.10 mm), and detritivores (established 1.74-3.04 mm, not-established 4.31-9.04 mm).

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Figure 6-8 Partial residual plots, from the model of maximum body size (mm) vs establishment status, guild and their interaction, showing predicted (log) body size for the 11 guilds either ‘Established’ and ‘Not established’. A star symbol denotes a statistically significant variation (p< 0.05).

Figure 6-9 shows differences in predicted size across the four status groups for each guild. There are clear differences in the predicted size of taxa in some guilds depending on their status (Appendix 4, Table 2). Indigenous detritivores were significantly smaller (1.38-2.8 mm) than detected detritivores (4.15-7.95mm). Transient herbivore-detritivores were smaller (0.09-4.54 mm) than detected taxa of the same guild (4.81-14.42 mm). Indigenous omnivores were smaller (0.51-3.02 mm) than both transient (4.45-23.05 mm) and detected omnivores (5.39-10.98 mm). Indigenous and established-alien herbivores were both smaller (1.02- 3.29mm and 1.03-4.64 mm respectively), than detected herbivores (9.96-15.77 mm) and

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Figure 6-9 Partial residual plots, from the model of maximum body size (mm) vs establishment status, guild and their interaction, showing predicted (log) body size for the 11 guilds in each of the status groups along the pathway (Detected –D, Transient – T , Established – E, and Indigenous – I). A star symbol denotes a significant variation (p< 0.05).

transient herbivores (7.92-19.19 mm). Similarly, predatory established aliens (0.4-2.03 mm) and indigenous species (1.62-3.56 mm), were significantly smaller than detected (5.42-9.47 mm) and transient (5.18-38.32 mm) predators.

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DISCUSSION

Southern Ocean Islands have limited human history; as such they are relatively pristine (de Villiers et al. 2006; Shaw 2013). Even so, alien plants, vertebrates and invertebrates have established across the region through unintentional and deliberate introductions (Frenot et al. 2005; Headland 2012; McGeoch et al. 2015). Invertebrates and plants continue to be introduced despite biosecurity (e.g. Whinam et al. 2005; Houghton et al. 2016). While eradications are costly but effective for vertebrates (Springer 2016), the same cannot be said for invertebrates or plants, and invertebrates are inherently more difficult to remove once established. To date, there have been no successful invertebrate eradications of invertebrates outside of buildings on SOI (see Bergstrom et al. 2017), although attempts are currently underway on Marion Island (Greve et al. 2017). In consequence, improving biosecurity is a key element in protecting SOI from invertebrate invasions.

Unsuccessful invasions are inherently difficult to detect (Lawton and Brown 1986), and rarely reported (Zenni and Nuñez 2013). Here we tackle this problem by comparing alien taxa that have established on Macquarie Island with those that are transported to the island but fail to establish. This has provided a suite of important insights. Firstly, alien spiders have never established on the island (ignoring our ‘related-detected’ spiders that we considered ‘established’ in models), despite being repeatedly introduced (seventeen spider incursions totalling 50 individuals – see Houghton et al 2016). These intercepted spiders are often larger in size than the three indigenous species on the island, and easily detected. The two transient spider species that have historically been repeatedly found on the island, were also repeatedly detected en route to Macquarie Island but are very different in size - Oecobius navus (Oecobiidae, ~3.2 mm) and Delena canerides (Sparassidae, ~25 mm), suggesting factors other than size limit their establishment. The failure of these spiders to establish may be due to unfavourable environmental conditions or unsuitable food. Elsewhere in the region, on Crozet and Kerguelen Islands, several spider species have established, but are currently restricted to station buildings (Frenot et al. 2005).

Alien species that are closely related to indigenous species are often more likely to be successful invaders (Li et al. 2015). Preconditioning to invasiveness via phylogenetic influences is therefore important to consider in trait assessments (Capellini et al. 2015) as

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there is high potential to inform biosecurity. For example, spiders from the families Desidae and Linyphiidae have been detected en route to Macquarie Island, but have not yet established. Given that both these families have indigenous species on the island, increased vigilance is warranted for these taxa. Likewise, (Collembola) are a large and diverse group globally (Potapov 2001), and the most populous family on Macquarie Island with 15 species. However, one third of the island’s species are established-aliens. Three other families established on the island also have both indigenous and alien representatives - (Acarina), Pyralidae (Lepidoptera), and Thripidae (Thysanoptera).

Low biosecurity detection rates of taxa that are already established on the island, suggests that these groups are being transported to the island unnoticed. Invertebrates that persist and breed on Macquarie Island are significantly different from transient-aliens and detected taxa across all traits; body size, vagility and guild. Firstly, indigenous and established-aliens were relatively small in comparison to transient-aliens and detected taxa – providing strong evidence that small alien species are evading biosecurity. A good example are the smaller Collembola and Acarina, which are rare in the detected suite yet are found in relatively high numbers as established-aliens. Indeed, 24% of Collembola and 37% of Acarina on the Macquarie Island are established-aliens. Not only does this highlight a weakness in biosecurity procedures, it also underpins the question as to whether the small number of transient taxa (22 spp.), whom are all relatively large, is also a result of detectability. Aerial dispersal by small species such as springtails is proven in the region (Hawes et al. 2007; Hawes and Greenslade 2013) and may also be an important mechanism here. Known transient-aliens are all large. However, via human agency and aerial dispersal, smaller, transient organisms may be arriving repeatedly but go unnoticed, existing for some time in the environment but ultimately failing to establish. Alternatively, they may already be established, perhaps with localised distribution and are as yet undetected. For example, the recent identification of the minute invasive springtail (Isotomidae: notabilis) on Macquarie Island (Phillips et al. 2017), which is likely to have been established for some time, was an unanticipated result of more detailed springtail molecular work. Also unanticipated, Phillips et al. (2017) discovered two alien springtail species established in the environment that were thought extinct on the island, since the greenhouses they were apparently restricted to had been demolished (Greenslade 2006). Identifying new arrivals and established species of invertebrates on an isolated island is difficult, particularly for small species, and requires ongoing and widespread surveys.

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In order to meaningfully interpret our body-size results, it is importat to understand our terminology. We used body length measurements as a determinant of body size, rather than body mass as some body size studies have used (e.g. Gaston et al. 2001). This was because it simply was not possible to acquire body mass for many of the taxa used in this study - most specimens identified from historical collections of detected invertebrates were preserved or dried, making length the only meaningful, obtainable metric of size. In other instances, specimens of transient species or cryptic species on the islands were often not available (hence the extensive use of literature to confirm body length). While use of length (or width) can be problematic when comparing species of different body shapes (and therefore different mass-length relationships), its use a proxy for body size in arthropods is well recognised (e.g. for insects – Kirk 1991; ladybirds – Dixon and Hemptinne 2001; aphids – Dixon et al. 1995; spiders – Lee et al. 2012; weevils - Chown and Smith 1993).

Previous studies have shown that there is a lack of consistent correlation between size and establishment in alien invertebrates (e.g. Lawton and Brown 1986; Peacock and Worner 2008). The skew to smaller body size in the distribution of indigenous and established-alien species we found on Macquarie Island is also found on Marion Island (Gaston et al. 2001), and is similarly driven by high numbers of Acarina. Gaston et al. (2001) found that the 20 established-alien invertebrate species on Marion Island were on average significantly larger than the indigenous species - though, as Lawton and Brown (1986) found, these differences were largely driven by a few specific taxa. For example, the alien Collembola on Marion Island were marginally larger than the indigenous, whereas the ten alien insect species were on average smaller. Although our models showed no overall significant difference in size between indigenous and established-alien invertebrates on Macquarie Island across six shared orders, within order differences show that indigenous taxa were consistently smaller (Appendix 4, Table 2). In summary, smaller introduced taxa survive on Macquarie Island more than larger ones prevalent in the detected and transient-alien suites. Being large generally has competitive advantages (Blanckenhorn 2000; Reim et al. 2006, and references within), including lower per-unit body mass metabolic rate (Peters 1983). Hence, larger organisms might have a better chance of surviving transport (Gaston et al. 2001). However, there are expense trade-offs in being a larger individual, such as viability costs of long juvenile development times, increased predation, reduced agility and mating success due to high energy requirements, faster growth and metabolic demands, which lead to increased starvation risk in resource limited environments (Blanckenhorn 2000).

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Being larger also increases chances of biosecurity detection. Transport time to Macquarie Island is three days from Tasmania, Australia, which is short compared to other SOI. This may explain why smaller individuals have been able to survive the voyage. Smaller organisms may also have some competitive advantages (Mclachlan 1986; Moya-Laraño et al. 2007; Chown and Gaston 2010; Parker et al. 2013). These reflect the larger organisms’ disadvantages, including starvation resistance (Reim et al. 2006), increased agility and reproductive success (Mclachlan 1986; Neems et al. 1990; Blanckenhorn 2000), and reduced energy requirements (Blanckenhorn 2000). Although indigenous species of the SOI generally exhibit adversity-selected traits such as limited dispersal abilities, low reproductive investment, stress tolerance, and extended life cycles (Chown and Convey 2016), it is plausible that many of the traits we have discussed being exhibited by smaller organisms would also be advantageous to establishment in the region. In this context, we hypothesise that introduced smaller invertebrates have competitive advantages over larger introduced taxa on SOI.

Some studies suggest that species from functional groups not currently present in an area, may have a higher chance of successful invasion (e.g. Bergstrom and Chown 1999). The concept of ‘vacant ecological niches’ presented in previous studies from SOI, describes ecosystems where many functional groups are absent or underrepresented (e.g. Chown et al. 1998; Vernon et al. 1998; Jones et al. 2003c; Whinam et al. 2005; Convey 2007). For invertebrates, this translates to high numbers of detritivores, and low numbers of herbivores and predators (Vernon et al. 1998). As predicted by Vernon et al. (1998), and found on Marion Island (Crafford et al. 1986), we found a relatively high number of indigenous detritivores, and relatively low numbers of indigenous herbivores on Macquarie Island, although more predators were found than expected (due primarily to large numbers of predatory mites). The relatively low numbers of indigenous herbivores in the recipient ecosystem, could mean that introduced herbivorous invertebrates might find little competition for resources, which could assist their establishment and spread. This has already occurred for other guilds on other SOI (e.g. Lee et al. 2007; 2016; Convey et al. 2010; Laparie et al. 2010). However, we also detected higher establishment success for generalist feeding guilds, namely predators and detritivores that are able to exploit resources widely. The fact that transient-aliens and detected taxa comprised of many herbivores while very few established- aliens were herbivores, suggests unsuitable plant resources limit invertebrate herbivore establishment. Indeed, a wide host range is critical for successful arthropod herbivore

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invasions (Peacock and Worner 2008) and the established-alien herbivores on the island (mainly aphids) all have a wide host plant range (Greenslade 2006). Conversely, the establishment of the repeatedly detected transient diamond-backed moth, Plutella Xylostella, a world-wide crop pest and invasive species on sub-Antarctic Marion Island, is host limited on Macquarie Island, given it feeds almost exclusively on brassicas () which are absent but for a tiny cress-like species, Cardamine corymbosa (Greenslade 2006). Our results also highlighted that established-aliens were comprised of similar guilds and ratios to the indigenous taxa. The guild similarities between the established-aliens and indigenous taxa suggest that the ecological ‘niches’ the established-aliens are occupying include un-utilised or at least readily available resources (in line with ‘the rich get richer’ hypothesis – Case 1990). It also suggests that these could be directly competing for resources with the indigenous species.

Resource competition exists only if that resource is limiting, and different ways of using the resources can reduce the effect different species have on one another (Simberloff and Dayan 1991). It may be that resources are not limiting on Macquarie Island, thus carrying capacity has not been reached and competition is limited. However, the arrival of new predatory species could also exploit indigenous and established-alien taxa, as occurs with the established predatory alien flatworms on Macquarie Island (Greenslade et al. 2007), carabid beetles on South Georgia (Ernsting et al. 1999), and the multitude of invasive vertebrates introduced across the region (Courchamp et al. 2003). More research measuring the direct impact of established-alien species on the indigenous species is warranted to clarify their impact having on ecosystems.

Indigenous invertebrates of SOI are noted for their flightlessness (Crafford et al. 1986; Roff 1990; Greve et al. 2005). We found non-established taxa were significantly more likely to be winged than established-aliens and indigenous taxa. This is despite high numbers of winged arthropods detected in transit to Macquarie Island and transient-alien species such as the Noctuid moths Agrotis ipsilon and Persentania ewingii arriving intermittently in favourable strong winds (Greenslade et al. 1999). Low numbers of winged established-aliens again may relate to their detectability – i.e. although winged organisms can fly to and from ships while at anchor (Lee et al. 2007), winged organisms made up the majority of the largest organisms in our data, and are thus more easily detected.

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Detection of invertebrates at quarantine borders can be a poor predictor of successful incursions – a combined result of poor inspection sensitivity, inadequate identification and reporting, or undetected and contaminated pathways (Caley et al. 2015). There have been several approaches to predicting invasive invertebrate species distributions in the SOI by assessing climatic suitability (e.g. Duffy et al. 2017), habitat characteristics (Gabriel et al. 2001; Terauds et al. 2011), and assessing a range of other traits of a particular invertebrate group (e.g. Greenslade 2002). Here our approach differed in that we conducted a large-scale assessment of traits for a diverse group of invertebrates to try and predict establishment risk. Models suggested that establishment of introduced species on Macquarie Island is linked to small body size (i.e. low detectability), absence of wings, and the presence of appropriate resources. In essence, wingless, detritivorous species of small body size (< 5 mm) are the most likely to become established. None of the taxa classified as transient and only three taxa of the detected suite - Oribatid mites (Acarina), and two springtails (Collembola) - fit this description. Therefore it is clear that there is a mismatch between the traits of taxa detected through current biosecurity and those of the taxa we found arriving and establishing on Macquarie Island.

In this context, and like invertebrate surveillance elsewhere (e.g. Caley et al. 2015), it seems likely that biosecurity in the region is failing to detect invertebrate species that are most likely to become invasive. Biosecurity procedures around the handling and treatment of cargo through the Australian Antarctic Program have improved over the years, and markedly improved since our detected suite of invertebrates was collated (Houghton et al 2016). Yet, species continue to be introduced and establish through the program (Bergstrom et al. 2017) and questions remain on how to optimally manage undetected small invertebrates that are being transported. Biosecurity surveillance for the region should focus on cargo and transport environments likely to harbour smaller, more cryptic invertebrates that are difficult, if not impossible, to detect visually. A review of the current fumigation regime could provide more effective approaches. Improving our understanding of which zones of resupply vessels harbour cryptic invertebrates on ocean crossings could also assist in targeted fumigation treatment, both on resupply and tourist vessels once at sea.

Isolation and limited human activity in many SOI has ensured the persistence of their high conservation values (Chown et al. 2008; Shaw 2013). Despite their reserve status, alien invertebrates have established in the region, and continue to arrive (Houghton et al. 2016;

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Newman et al. 2018), and are impacting biodiversity (Frenot et al. 2005; Chown et al. 2008; McGeoch et al. 2015; Houghton et al. 2019). Compared to other regions globally, effective biosecurity has considerable potential to ensure the future protection of these islands. Increased understanding of high-risk taxa will inform this. Our work highlights that targeting fumigation and other biosecurity measures to small, non-flying species will greatly assist in protecting these wilderness areas from alien invertebrate invasions.

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Chapter 7 | General Discussion

Global biodiversity is under threat due to the combined pressures of invasive species, climate change and habitat destruction (Millennium Ecosystem Assessment 2005; Maxwell et al. 2016; Watson et al. 2016; Wilson et al. 2009). This includes invertebrates, which make up the majority of animal species on Earth (Stork 2018). Invertebrates are diverse, abundant and drive ecosystem function, making them intrinsically important components of global biodiversity, and also ideal biological indicators of environmental change (McGeoch 1998; Gerlach et al. 2013). Reductions in insect numbers, upon which the vast majority of plant and animal life directly and indirectly depends, has economic implications associated with ecosystem-services (e.g. pollination for agriculture), but also spells an accelerated extinction threat for many species and impoverishment of global biodiversity (Wagner 2019). In the context of limited conservation funding, effective monitoring is critical to informing prioritisation of resources, conservation planning and effective management in rapidly changing global environments. My research demonstrates that monitoring terrestrial invertebrates can be both informative and effective in assessing ecosystem change, specifically ecosystem change following large-scale conservation initiatives such as mammal eradications.

Invasive species are one of the greatest drivers of ecosystem disruption and biodiversity loss (Mooney and Hobbs 2000; Clavero and García-Berthou 2005; McGeoch et al. 2010; Tershy et al. 2015; McCreless et al. 2016). Chapter 2 of this thesis shows that on the Southern Ocean Islands (SOI), despite their remoteness, high conservation value and reserve status, native invertebrates are at risk from invasive species. Native invertebrates are particularly at risk from non-native invertebrates which influence ecosystem processes in numerous ways and are difficult or impossible to eradicate. During this review I found taxonomic and research biases for SOI. Although millions of dollars have been invested in to the removal of mammalian herbivores, omnivores and predators, invertebrate community response, and its influence on ecosystem recovery, is largely unknown. Knowledge gaps can be addressed through invertebrate surveys that utilise a range of trapping techniques to collect the appropriate data which answers specific questions also appropriate to the local island environment (Chapter 3). In Chapter 3, to explore the invertebrate community response over time on Macquarie Island as the ecosystem underwent drastic changes due to mammalian

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invasive species, I determined the best approach for incorporating historical data and designed a survey to resample historical sites.

On SOI there are relatively few species in each taxonomic order, yet invertebrates are abundant. In consequence, order-level analysis of long-term invertebrate monitoring data from both prior and post mammal eradication can provide important insights into major perturbations in invertebrate community assemblage and associated environmental changes. This was quantified in Chapter 4. In Chapter 5, I further explored more complex and finer scale interactions between invertebrates, their habitat and invasive mammal impacts on Macquarie Island where three vertebrate species were eradicated and associated vegetation changes had occurred. Conducting analyses at a finer taxonomic resolution and investigating the abiotic drivers of invertebrate community assemblage in detail, I showed that ecosystem response can vary not only between islands, but even within an island system (Chapter 5). Often invasive mammal eradications are seen as opportunities to ‘restore’ pre-existing communities and ecosystem processes (Towns et al. 1997; Atkinson 2001; Townes and Broome 2003; Campbell and Donlan 2005; Carrion et al. 2011; Kappes and Jones 2014; Latofski-Robles et al. 2014). However, other more cryptic invasive species such as non- native invertebrates may remain in the environment after invasive mammals have been removed. These cryptic invasive species (non-native invertebrates), may benefit from invasive mammal eradication as much or more than native species, and their interaction with native species can influence restoration outcomes. This potential impact by non-native invertebrates highlights the importance of preventing further species from establishment in order to ensure the future conservation of Macquarie Island. In Chapter 6, I show that small, non-flying, detritivorous invertebrates are the most likely to be transported and establish on Macquarie Island. This knowledge highlighted opportunities to tailor more specific biosecurity protocols. Here, in this general discussion, I highlight key results to emerge from this thesis and identify developing themes and conclusions derived from the body of work as a whole. I discuss research limitations and identify future research directions.

Key findings

Chapter 2 is a literature review investigating the impacts of non-native vertebrates, plants and invertebrates on the invertebrates of Southern Ocean Islands (SOI). I detected gaps in our knowledge of the impacts of non-native plants, herbivorous mammals, and many non-native

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invertebrates on native invertebrates, and a taxonomic and regional bias on where invertebrate research has focused. For example, one island (Marion Island) and certain charismatic groups of invertebrates such as moths and beetles, are more consistently studied. While I found the impacts of mice predation on invertebrates of SOI are well-studied, the effects of habitat destruction by invasive mammalian herbivores on invertebrate communities is poorly known, as are the broader ecosystem impacts of non-native invertebrates. In line with the lack of conservation interest and funding for invertebrate research globally, this review found that despite their critical importance to ecosystem function, invertebrate fauna on SOI are not well understood nor are their responses to change well studied. Although climate change and invasive species are both impacting biodiversity of SOI, monitoring of invertebrate responses to environmental change is rare, even when large-scale, whole-island conservation programs, such as invasive mammal eradications, are being undertaken across the region. When rodents were eradicated from Campbell Island in 2000, baseline invertebrate monitoring did not occur (A. Fergus pers. comm.), and even more recently on South Georgia Island when rodents (Martin and Richardson 2017) and reindeer (Anon 2013, 2014) were recently eradicated, baseline invertebrate monitoring was either not included or not reported in the program summaries. However, baseline invertebrate monitoring is occurring on Gough Island ahead of the anticipated mouse eradication program in 2020 (J. Cleeland pers. comm.), and ahead of a proposed eradication of mice, pigs and cats from Auckland Island (Russell et al. 2018). Limited ongoing long-term monitoring of invertebrates on SOI is reported (but see Lee and Chown 2016). Given invertebrates are at the lower trophic levels of ecosystem, driving ecosystem processes, a lack of understanding for their response to these costly eradication programs, translates into a lack of capacity to accurately assess the conservation benefit of eradications, or to implement management and monitoring programs, or gauge island restoration. Furthermore, the impacts of non-native species on invertebrates of SOI are broad-ranging and varied, linked to trophic cascades within SOI ecosystems. They therefore cannot be ignored in these island conservation programs.

Monitoring invertebrates can give insight into broad ecosystem changes. They are quick to reflect environmental perturbations and are abundant in the landscape. In order to establish a baseline from which to detect long-term changes, it is essential to have robust and accurate survey design and trapping methodology, as ultimately these data inform management decisions, management success and subsequent conservation action. In Chapter 3, I tested survey design and trapping methods to monitor the responses of invertebrates to fluctuations

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of invasive mammal populations and their associated impacts on invertebrate habitat. Unearthing historical data and metadata took considerable effort, yet it ensured my work took maximum advantage of existing knowledge and facilitated long-term monitoring of invertebrates on Macquarie Island. By repeating a selection of historical trapping sites and replicating historical trapping methods this work showed that different trapping methods were more effective for specific taxa, and certain trapping methods were more effective in some habitats. Other methods such as litter and count sampling were diverse in their catch, and across habitats. These findings highlighted the importance of trap selection and well- chosen identification of bioindicators to answer research questions and reinforced that well- designed monitoring and surveillance can assist in distinguishing species interactions and fluctuations in the ecosystem, and detecting new arrivals.

In Chapter 4, I investigated how mammal eradications impact invertebrate community assemblages. I used SOI as model systems, examining two biogeographically similar sub- Antarctic islands that have recently undergone mammal eradications. I collated and utilised historical invertebrate data from pre-mammal eradication surveys, identified a selection of sites that had been repeatedly sampled over time, and re-established these sites to conduct post-eradication surveys. I quantified the temporal change in invertebrate community richness, abundance and diversity prior to and following mammal eradications. I determined which groups had been effected by rodent predation, and specifically examined their response to eradication. I found significant positive responses in invertebrate abundance and richness on Antipodes Island following eradication, where mice were the sole predator with minimal impact on vegetation or habitat. This was in contrast to Macquarie Island, where mice, rats and rabbits were simultaneously eradicated, and where large scale habitat destruction had occurred due to rabbit grazing on vegetation and burrowing. Sampling methods had been more consistent on Antipodes than on Macquarie Island, leading to greater variability and uncertainty in the Macquarie Island monitoring results. Nevertheless, the disparity in invertebrate responses between the two islands suggested factors other than release from rodent predation were influencing the observed responses in invertebrate on Macquarie Island. Influencing factors likely include habitat changes over time as a consequence of heavy rabbit grazing, climatic change, and/or interactions with remaining non-native species (invertebrates). The order level analysis and use of a single trap type (pitfalls) was necessary for this chapter, as a means of incorporating historical data which relied on pitfalls and order level identification of trap catches. , However, these allowances may have contributed to

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sample biases and a failure to capture subtle variations in invertebrate communities over time. Nevertheless, this chapter highlights the value of monitoring invertebrates to track ecosystem change, and for the first time, quantified the benefits to invertebrates of mouse eradication on Antipodes Island. Although the situation was more complex on Macquarie Island with multiple invasive mammal species eradicated at once, conservation benefits were detected for invertebrates through increases in species richness following the eradication program.

In Chapter 5, I conducted an in-depth examination into the drivers of invertebrate communities on Macquarie Island, and I examined the results in relation to observed invertebrate responses found in Chapter 4. Using ecologically important environmental parameters derived from a high-resolution island-wide digital elevation model, comprehensive island-wide invertebrate surveying, and a suite of trapping methods, I identified key abiotic and biotic drivers of Macquarie Island invertebrates. These included clarifying the interactions between native invertebrates and non-native invertebrates. Models indicated increases in richness in successive post-eradication trapping years and showed that vegetation type and elevation were key drivers of abundance and richness across invertebrate families. Furthermore, I found subtle differences in responses between native and non-native invertebrates, between feeding guilds, and between insects and non-insects. For example, native invertebrates were more reliant on vegetation than non-native invertebrates, and the latter were more abundant in wetter habitats. Also possibly linked to habitat wetness, abundance of non-insects were often linked to slope, while insect abundance was influenced by ridge. Abundance in predatory invertebrates (which on Macquarie Island are mostly spiders, beetles and mites), were more often explained by sampling year, wind speed and slope compared to other guilds. The ecological mechanisms underlying these patterns, particularly in the context of a changing climate on the island (Adams 2009, Bergstrom et al. 2015), require further exploration. Consistent with previous studies, models also showed that non-native invertebrate abundance can influence native species abundance, usually in a negative manner. How these interactions affect ecosystem recovery on Macquarie Island are also largely unknown and represent an important area of future study.

Through Chapter 5, I established a comprehensive baseline of invertebrate community assemblage on an island now devoid of invasive vertebrate mammals. This research will underpin and facilitate the effective monitoring of ecosystem change, and impacts of non- native invertebrates into the future. Using an array of trap types and family-level analysis

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allowed the detection of more subtle changes in invertebrate communities over time than Chapter 4, and also provides a means of selecting bioindicator taxa that are representative of vegetation change. This chapter delivers advice for effective monitoring for Macquarie Island and enables improved surveillance of non-native species and their impacts on the island and provides a means to assess how ecosystem recovery is progressing into the future. Given the extent and gravity of the impact of non-native invertebrates remains unquantified, this work also reinforces the importance of biosecurity in preventing further non-native invertebrate establishment in the Macquarie Island environment.

In Chapter 6, I examined the invasion risk of invertebrates to Macquarie Island. Non-native invertebrates continue to be transported to Macquarie Island through cargo operations. In Chapter 2, I identified gaps in our understanding of non-native invertebrate impacts on native species, and in Chapter 5 demonstrated interactions occurring between them. Yet the impacts of non-native invertebrate species on the broader ecosystem are still poorly understood, underlining the importance of preventing non-native invertebrates from establishing in the Macquarie Island environment. My previous work (Houghton et al. 2016) detected invertebrate incursions along the invasion pathway, from the source point at the wharf in Hobart, in transit on ships, to the end point at the destination at Macquarie Island. In Chapter 6, I built on this existing dataset and also created a new dataset, by incorporating three other groups of Macquarie Island invertebrates: indigenous species, non-native species established in the Macquarie Island environment and transient species i.e. those regularly arriving to the island either by natural or human-mediated means, surviving temporarily, but never establishing a breeding population. For both data sets, I used carefully selected traits of body size, vagility, and guild as proxies for establishment risk and compared traits for invertebrates across the invasion pathway, ultimately identifying traits linked to successful establishment on Macquarie Island. I found that small, wingless, detritivorous individuals are more likely to become established. Unfortunately the results also suggested that these taxa are least likely to be detected during biosecurity surveillance. These results will be fundamental to informing and improving Antarctic biosecurity screening across all national programs. Given the findings relate directly to the Australian Antarctic Division, this work will be of particular relevance to biosecurity practices of the Australian Government.

My thesis presents a comprehensive investigation into threats imposed on terrestrial invertebrate communities within protected island areas and solutions to mitigate these threats.

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For the first time, incorporating broad suite of taxa, this work delivers an understanding of the pressures exerted by non-native species on invertebrates of SOI, and the methods required to effectively monitor invertebrates. It quantifies the benefits of invasive mammal eradications for invertebrates, how their responses reflect the trajectory of ecosystem recovery, and how non-native invertebrates influence native invertebrate community assemblages. In the context of the current biodiversity crisis, particularly given limited conservation funding globally, this work reinforces the utility of invertebrates as ecosystem indicators and their effectiveness in assessing conservation benefits of management actions and conservation programs. These insights inform the planning of other programs and the design of more effective and efficient management of conservation estates. Through the identification of invertebrate taxa transported to Macquarie Island that have a high risk of establishment, Chapter 6 also provides recommendations for regional protection as outlined by the Committee for Environmental Protection to the Antarctic Treaty System, and directly contributes to improved regional biosecurity surveillance.

Limitations and opportunities for terrestrial invertebrate indicators

Aside from their exceptional sensitivity to environmental change, an advantage of using invertebrates as a monitoring tool is that even with a short amount of time in hard-to-reach locations, samples can be collected quickly and yield enormous number of species (Greenslade and Greenslade 1984; Rosenberg et al. 1986; Kremen et al. 1993; McGeoch 1998; Andersen et al. 2002). Pitfall traps are simple and commonly used in invertebrate monitoring (Woodcock et al. 2005), particularly by non-experts, but yield results plagued by a number of sampling biases (New 1996; Spence and Niemelä 1994; Woodcock 2005). This thesis highlighted that other trap types less commonly used can be more effective in capturing invertebrate diversity. Pitfall traps require site preparation, materials such as cups and preservative, and must be set and collected after an adequate period or days. On the other hand, litter collection is instantaneous, involving only a quadrat and a collection container of the desired volume. Following collection however, Berlese or Tulgren funnels in a warm laboratory setting are necessary to extract invertebrates from litter samples, and this must be done within a few days of collecting to ensure litter invertebrates are alive. Nevertheless, my thesis shows that for the least field time, litter sampling delivered the most abundant and evenly distributed catch across all vegetation types. Based on this work, I recommend that as

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a substitute to pitfall traps, which are so often the default trapping method, consideration be given to litter sampling for broad scale invertebrate monitoring.

One of the notable benefits of invertebrate monitoring is the high volume of species and individuals involved. However, although large-scale invertebrate trapping may initially inexpensive to set up, and be relatively easy to deploy by non-experts, one of its limitations is that sorting of samples can be time-consuming, and specialist skills are often required for identification of samples (New 1996; Niemi and McDonald 2004; Ward and Lariviere 2004). Fortunately the Southern Ocean Island region is characterised by low numbers of invertebrate species per higher taxonomic group, which permitted the use of higher levels for analyses used in this research. For my research, identifying invertebrate indicators for Macquarie Island required considerable survey effort across multiple seasons and significant time was spent in identifying specimens. Such effort is not always possible in a funding poor conservation ‘industry’. Indeed, the quality of some of the historical data used in this research suffered from biases due to multiple collectors and identifiers over the years. Although the data was imperfect at finer taxonomic resolution, order level analysis permitted comparison of invertebrate communities over time, and meaningful results were extracted that underpinned important insights. Willingness to work with imperfect historical data, and finding ways to compensate when data are scare, are sometimes critical to the interpretation of long-term monitoring and to establish baselines for future monitoring.

Ideally, here I would offer a suite of invertebrates useful as indicators of restoration across the SOI region. However, although a comprehensive list of invertebrate species existent on SOI is available (see Chown and Coney 2016), as I reported in Chapter 2, little is known of the interactions between many of these species, their habitats, climate and other non-native species. Until this knowledge has been collated for each island, and associated impacts quantified, proposing suitable indicators of change for each island remains difficult. Unlike the Arctic region where groups such as spiders are repeatedly identified as surrogates for arthropod diversity (Hein et al. 2019; Gillespie et al. 2020) or as indicators of environmental change (Bowden et al. 2018; Høye et al. 2018), a list of species or groups useful as indicators across the SOI biogeographical region is possibly untenable, as despite their similarities, each island is characterised by unique features, species and interactions. During my thesis a considerable amount of time was invested in field surveys, identification, and interpretation of historical data, in order to propose indicators groups for restoration of Macquarie Island

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and Antipodes Island (Chapter 4 and Chapter 5). Comparable survey effort would be required for each SOI to make island-specific recommendations.

Entomological training and advancements in identification tools

More research is required that tests the effectiveness of higher-level analyses for broad scale assessment of environmental change. How best to represent invertebrate data, using proxies, higher taxonomic levels, and using indicator groups or taxa that present communities as a whole, has been sporadically evaluated (e.g. Andersen 1995; Báldi 2003; Andersen and Majer 2004; Cardoso et al. 2004; Nakamura et al. 2003, 2007; Włodarska-Kowalczuk and Kędra 2007; Timms et al. 2012; Driessen and Kirkpatrick 2017). While some studies have found higher levels unreliable as surrogates for species richness (e.g. Andersen 1995), other research has found meaningful interpretation in higher-level analyses for habitat characterisation and restoration purposes (Andersen et al. 2002; Pik et al. 2002; Nakamura et al. 2003; Bevilacqua et al. 2012; Driessen and Kirkpatrick 2017). Indeed, an increase in taxonomic resolution does not always provide a commensurate increase in the observed sensitivity of the invertebrate community response (Nakamura et al. 2007). In my thesis, I investigated taxonomic resolution, I tested order level and family level analysis across a broad range of taxa, but for comparatively small invertebrate faunal assemblages, with few species per high taxonomic level. This is unusual; in other ecosystems there can be hundreds or thousands of species associated with each higher level. In a time when we are rapidly losing species, the use of higher orders or even morphospecies by non-experts must be encouraged, alongside research which assists in interpretation of data collected at coarser resolution (Oliver and Beattie 1996a, 1996b; New 1996; Nakamura et al. 2007; Wheeler et al. 2004; Bevilacqua et al. 2012; Driessen and Kirkpatrick 2017).

Biodiversity assessments of invertebrates are not only hampered by their sheer volume and diversity, but reliance on high levels of taxonomic expertise. For distinguishing between habitats and tracking biodiversity, species knowledge is thought superior (Costello et al. 2003). However, funding support for taxonomic training has waned just as the need for taxonomists to identify global diversity accurately has increased (New 1996; Hopkins and Freckleton 2002; Wheeler et al. 2004; Drew 2011). Future conservation of biodiversity in the era of an extinction crisis, must be underpinned by investment in invertebrate taxonomic training.

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During the course of this research project, I sampled and identified more than 270,000 invertebrates, had to privilege of working with a number of skilled taxonomists and ecologists, and gained experience in developing species identification keys (e.g. Janion- Scheepers and Houghton et al., in prep.). An invertebrate monitoring PhD project spans several years, allowing for dedicated time to learn taxonomic skills, and tackle the enormous task of sorting and identifying invertebrates. Such luxury of dedicated time is often not possible for invertebrate biodiversity assessments. Time-consuming manual processing of insect samples and expert identification of taxa is a significant bottleneck for invertebrate monitoring-related projects (Ärje et al. 2020). These strong limitations often compel operators of long-term monitoring assessments to resort to morphospecies or higher taxonomic groupings of trap catches (e.g. Russell 2012; Timms et al. 2012; Rich et al. 2013; Vergara Parra 2018), or biomass weighting of trapped samples (Hallmann et al. 2017), or selecting only specific taxa to proceed with analyses (Ernst et al. 2016; Loboda et al. 2017; Hansen et al. 2016b; Gillespie et al. 2020), all methods with their own advantages and drawbacks. Alternative, cost-efficient, more effective methods are urgently needed to support the increased demand for biological surveys, to quantify invertebrate abundance and diversity to address the gaps in our knowledge around the state of global populations, especially given that taxonomic experts are declining in number (Hebert et al. 2003; Gaston and O’Neill 2004; Hansen et al. 2019; Seibold et al. 2019; Wagner 2019). Given the advancements in machine learning and artificial intelligence it is increasingly likely that manual sorting will be replaced by computer driven microscopes and smart software, which will dramatically expedite our ability to assess invertebrate abundance and diversity, and improve the attractiveness of invertebrates as bioindicators. Indeed, machine-learning tools such as convolutional neural networks, and robot-enabled image-based identification machines that automate routine sorting and identification processes are currently being tested with promising results (Favret and Sieracki 2016; Joutsijoki et al. 2014; Marques et al. 2018; Wäldchen and Mäder 2018; Hansen et al. 2019; Ärje et al. 2017; 2020). Genetic testing and molecular approaches, while expensive and not yet suitable for abundance or biomass estimates, are more frequently being used in invertebrate diversity assessments, yielding comparable results to field surveys and morphological identification (Raupach et al., 2010; Aylagas et al. 2016; Kermarrec et al. 2014; Elbrecht et al. 2017; Zimmermann et al. 2015). Automated invertebrate monitoring is also being developed, such as sophisticated camera trap methods (Collett and Fisher 2017; Hansen et al. 2019) and portable computer vision systems that are able to attract, detect,

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classify live insects that can then, using a computer vision algorithm based on deep learning analysis of captured images, count and identify species (Ding and Taylor 2016; Bjerge et al. 2020).

In the process of developing this thesis, I learned the value of taxonomic skills and have relished in the joy of discovery at the microscopic level. In an era in which we are losing species before they are described, the support for taxonomy, and understanding the world of small fauna, ‘the silent majority’ (Gibbs 1990), should not be underestimated.

Support for invertebrate conservation

Invertebrate conservation as a discipline is largely ignored, and rarely attracts funding (Hafernik 1992; Black et al. 2001; Angel et al. 2009). Biological conservation is undeniably underfunded across all taxa, given low priority in the face of global and economic and social pressures (James et al. 1999; Bottrill et al. 2008; Wilson et al. 2009; Auerbach et al. 2014). Yet, we are rapidly losing species across the globe, and the environment is changing in a multitude of ways – conservation action is urgently needed (James et al. 1999; Watson et al. 2016, 2018; Ward et al. 2019). In this context, optimising conservation actions to ensure maximum benefits is essential and the need to develop cost-effective methods to efficiently monitor ecosystems has never been more critical (McDonald-Madden et al. 2010. Possingham et al. 2012, 2015; Ward et al. 2019).

The need to undertake conservation actions with limited funding is perhaps the primary reason that uncharismatic terrestrial invertebrates are often overlooked in monitoring programs. Yet, this thesis argues that even if overlooking their intrinsic ecological function, conservation values and diverse beauty could be justified, their immense value as conservation tools cannot. The protection of habitats and preservation of ecosystem integrity is often touted as a priority for conservation (Martin and Watson 2016; Watson et al. 2016; 2018a, 2018b), but understanding how complex entities such as ecosystems are tracking over time is difficult. Traditionally, indicator species for terrestrial management have been large vertebrates (Landres et al. 1988) which are often considered ‘umbrella’ species in conservation research (Simberloff 1998), on the basis that saving their large habitats automatically saves many other species in that ecosystem (Ferris and Humphrey 1999; Ward et al. 2019). As discussed throughout this thesis, many of the merits of invertebrates as

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indicators make them preferable to vertebrates for rapid detection of change (Rosenberg et al. 1986; Kremen et al. 1993; Andersen and Majer 2004: McGeoch 2007; Gerlach et al. 2013).

Even so, as I have highlighted repeatedly, monitoring terrestrial invertebrates as indicators of environmental change has been underutilised in conservation planning and land management (Kremen et al. 1993; Andersen and Majer 2004), although some examples do exist (e.g. Pearson and Cassola 1992; Andersen 1993; Rainio and Niemelä 2003; Niemelä et al. 2000). Whereas in aquatic systems invertebrates are routinely used for biological and environmental monitoring (Rosenberg et al. 1986; Andersen and Majer 2004; e.g. Harig and Bain 1998; Hawkins et al. 2000), even on Macquarie Island (Marchant et al. 2011), the use of invertebrates in terrestrial management has been more circumspect, with managers intimidated by the volume of invertebrates, associated taxonomic challenges and lack of standard protocols (New 1996; Andersen and Majer 2004; Niemi and McDonald 2004). A consequence of this reticence is that the constraints of using terrestrial invertebrate assemblages for such purposes have not been comprehensively identified, and methodologies have not been fully developed or tested (Kremen et al. 1993). Until efficient protocols have been developed to assist land managers in the application of terrestrial invertebrate bioindicators, such as exist for aquatic systems (e.g. Norris and Morris 1995), they remain underdeveloped (Andersen 1999). Research such as this thesis, provide evidence for the advantages and drawbacks, the deliberations and methods required, to select meaningful terrestrial invertebrate indicators of habitat and ecosystem change associated with mammal eradications. This work encourages the use of invertebrate monitoring for relatively rapid assessments of ecosystem response to conservation programs, which is crucial to prioritising and evaluating conservation goals and management objectives.

Future directions

While my research was based on remote Southern Ocean Islands with comparatively small inventories of invertebrate species, it has broader relevance and application. More efficient approaches to ecosystem monitoring assist in assessments of management successes, inform future ecosystem management and optimise conservation funding (Prior et al 2018; Tulloch et al. 2011; Bird et al. 2019). Chapter 5 confirmed that for islands on which a single mammalian predator exists, the abundance and distribution of larger invertebrates such as beetles, moths and spiders are good indicators of predation pressure (and predation release

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following eradication). In combination with the trapping recommendations outlined in Chapter 3, this provides a blueprint for the design of monitoring for future land eradications. Indicator species for Macquarie Island identified in Chapter 5, were more strongly reflective of habitat changes (rabbit grazing) than direct predation pressure, which is particularly relevant for herbivorous invertebrates and those linked to habitat wetness and vegetation cover. Such taxa are good candidates for indicating long-term ecosystem trends on islands undergoing vegetation change. Future island eradication projects should consider how to select appropriate indicators of change and the appropriate level of taxonomic resolution at which to detect change. It is critical to the conservation of SOI to understand how environmental variables and non-native species interactions shape invertebrate communities, particularly in the context of a climate changing rapidly in the region (Adams 2009; Bergstrom et al. 2015).

This thesis highlights the challenges and nuances of ecosystem response to eradications by undertaking ecological research at lower tropic levels. The modification of the abiotic environment by invasive mammal species is rarely studied, but can affect species across multiple scales and trophic levels in the ecosystem, especially those recycling organic material (Hutcheson et al. 1999), with cascading consequences throughout the ecosystem. For example, mice contribute to reduction in soil moisture and minerals (Hänel 1999; Gabriel et al 2001), and non-native plants effect soil chemistry (Gremmen et al. 1998). Meanwhile, the depletion of seabirds through the long-term presence of invasive mammals, such as the islands examined in this thesis (Antipodes Island - Imber et al. 2005, and Macquarie Island by Brothers 1984; Brothers and Copson 1988; Brothers and Bone 2008) equates to loss of critical marine-derived nutrients and bio-perturbation activity in island ecosystems. This can lead to reduced plant biomass, altered leaf chemistry and nitrogen release in decomposition, and changes in soil moisture nutrient profiles and litter accumulation rates, with substantial subsequent effects on soil and above-ground litter invertebrates (Erskine et al. 1998; Siemann 1998; Anderson and Polis 1999; Fukami et al. 2006, Mulder et al. 2009; Towns et al. 2009; Wardle et al. 2009; Thoresen et al. 2017). Given the proportionally high number of insect herbivores and the prevalence of detritivorous invertebrates in invertebrate assemblages on SOI that are reliant on foliage and soil nutrients (Vernon et al. 1998; Chown and Convey 2016), any change to plant and soil chemistry as a result of invasive mammals will impact on invertebrate community assemblages. Hence, one of the limitations of this thesis, is that soil chemistry between habitats and over time was not analysed. However, soil cores in replicate

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were collected from each invertebrate trapping site in the final sampling year on Macquarie Island as post-eradication baseline samples. Analyses of these, alongside detailed vegetation surveys at each site, and coupled with the invertebrate community data included in this thesis, represent an opportunity for future, complimentary, research to assess the evolution of soil chemistry over time as the ecosystem recovers, thereby determining the implications for plant and invertebrate communities. In conjunction with effective invertebrate monitoring and existing vegetation monitoring, soil chemistry analyses will provide new insights on the island’s recovery following the mammal eradication.

Despite the length of my project, it was necessary to exclude invertebrate groups that yielded extraordinary high numbers of individuals - such as Collembola, Acarina, and Copepoda – from some analyses in order to minimise identification time and count effort and permit the completion of this research within the required time-frame. This did not diminish my research, but temporal and spatial changes of these super abundant micro-arthropods remain unexamined. Collembola are the most comprehensively studied arthropod in the SOI region, with research identifying links between Collembola communities and site moisture, soil chemistry and habitat (e.g. Convey et al. 1999; Hänel 1999; Barendse and Chown 2001; Gabriel et al. 2001; Terauds et al. 2011). Thus, the Collembola, Acarina, and Copepoda collected from Macquarie Island as part of this research, provide an ideal opportunity for future research to explore detailed species responses to soil and habitat changes as the ecosystem recovers from invasive mammals and continues to evolve with changing climate.

Globally, non-native invertebrates have dispersed widely, easily stowed as hitchhikers with global trade and movement of people. Many are of significant concern to human society as agricultural pests, vectors of disease, destroyers of infrastructure or nuisances as household pests, costing billions of dollars in economic damage globally (Bradshaw et al. 2016). Yet the impacts of naturalised invasive invertebrates on ecosystem processes are less widely known, being perhaps less visible than those of invasive mammals or birds, but their activities have been shown to substantially alter ecosystem condition and resilience (Kenis et al. 2009). This thesis frequently cited the high numbers of non-native invertebrates found in the SOI region relative to other non-native species. Conversely to the global situation, the SOI invertebrate inventory are often well-known. In Chapter 5, I found that non-native invertebrate abundance influenced the abundance of native invertebrate species, but the detailed nature of these interactions and how they influence the condition of the Macquarie Island ecosystem remain

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untested. The isolation of SOI such as Macquarie Island and their relatively small size provide the ideal environment to study such interactions between non-native invertebrates with native species, and assess consequences for the ecosystem. This knowledge could be extrapolated to explain the effect of non-native invertebrates on ecosystems more broadly. Thus, combined with an understanding of habitat preferences and ideal trapping method for target taxa, as I have outlined for Macquarie Island in Chapters 3 and 5 of this thesis, it is possible to monitor these non-native invertebrate interactions into the future to answer some of these questions. Future research in the region should be prioritised accordingly.

CONCLUSION

My research demonstrates that terrestrial invertebrates can be integral in the measurement and assessment of environmental change. This is particularly important in this era of the Anthropocene, which is defined by a rapidly changing environment. To date, terrestrial invertebrates are underutilised as environmental indicators. Comprehensive baseline surveys are not common, particularly for invertebrates. This thesis establishes baseline invertebrate surveys on two high conservation islands that have undergone large scale conservation initiatives. My work presents the first assessment of the conservation outcomes of these programs on lower trophic organisms, critical to ecosystem function. Non-native invertebrate impacts on ecosystems are not well known, and this work has quantified some of these impacts. I have shown that improvements to biosecurity of the Antarctic and Southern Ocean Island region are needed, particularly focused on high-risk taxa. Southern Ocean Islands represent some of the last remaining wildernesses in the world. Their protection through superior conservation management is important, not just for millions of seabirds and marine mammals that depend on them, but for the weird, wonderful, and often underappreciated invertebrate creatures that also call them home.

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APPENDICES

Appendix 1 | Supplementary material for Chapter 2

Table 1 - Studies that directly measure or observe impacts of non-native species on native invertebrates on Southern Ocean Islands, including method of observation, impacted orders and species, the classification of the impacting species (plant, invertebrate, herbivore, omnivore, predator) and suspected impact of this species on native invertebrates. The abbreviation ‘NN’ in the impacted species column signifies an impacted ‘non-native’ invertebrate species.

Impacting Method of Impacted Impacted invasive species Impact Author Year observation/conclusion Orders Species studied group Suspected impact Island

Pye and Peritmylops antarcticus Suppression of South Georgia, Bonner 1980 Scat analysis Coleoptera Hydromedion sparsutum Rattus norvegicus predator preferred prey United Kingdom

Araneae Coleoptera Diptera Suppression of Macquarie Copson 1986 Stomach content analysis Lepidoptera Unspecified Mus musculus predator preferred prey Island, Australia

Suppression Fossil remains and Mus musculus and/or local Kuschel historical reports Rattus rattus extinction of Auckland Island, and Worthy 1996 analysed. Coleoptera Oclandius spp. Rattus norvegicus predator preferred prey New Zealand

Stomach content analysis Isotope analysis of liver Antipodes Invertebrate trapping Annelidae Suppression Island, New Compared Amphipoda and/or local Zealand Russell et invaded/uninvaded Coleoptera extinction of Bollons Island, al. 2020 island(s) Lepidoptera Unspecified Mus musculus predator preferred prey New Zealand

Antipodes Invertebrate trapping Amphipoda Suppression Island, New Compared Araneae Oopterus clivinoides and/or local Zealand invaded/uninvaded Coleoptera Loxomerus brevis extinction of Bollons Island, Russell 2012 island(s) Collembola Others unspecified Mus musculus predator preferred prey New Zealand

Gromilus insularis antipodarum Quediocafius insolitus Antipodes Invertebrate trapping Pseudhelops clandestinus Suppression Island, New Compared Tormissus guanicola and/or local Zealand invaded/uninvaded Loxomerus sp. extinction of Bollons Island, Marris 2000 island(s) Coleoptera Others unspecified Mus musculus predator preferred prey New Zealand

Stomach content analysis Antipodes Invertebrate trapping Oopterus clivinoides Suppression Island, New Compared Araneae Pseudhelops clandestinus and/or local Zealand invaded/uninvaded Coleoptera Loxomerus brevis extinction of Bollons Island, McIntosh 2001 island(s) Lepidoptera Others unspecified Mus musculus predator preferred prey New Zealand

Severe Invertebrate trapping Parudenus falklandicus suppression of Compared Lissopterus spp. large-bodied St Clair et invaded/uninvaded Coleoptera Caneorhinus biangulatus island endemic Falkland Islands, al. 2011 island(s) Orthoptera Cylydrorhinus lemniscatus Rattus norvegicus predator invertebrates United Kingdom

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Myro pancispinosis Myro kerguelensis Erigone vagans Gleeson Invertebrate trapping Araneae Pershomma antarctica and van Soil cores Coleoptera Ectemnorrhinus similis Suppression of Marion Island, Rensburg 1982 Stomach content analysis Lepidoptera Pringleophaga marioni Mus musculus predator preferred prey South Africa

Suppression and/or local extinction of preferred prey Trophic Marion Island, implications from South Africa Compared cat-seabird- Prince Edward Crafford invaded/uninvaded Coleoptera Pringleophaga spp. Mus musculus nutrient Island, South and Scholtz 1987 island(s) Lepidoptera Curculionidae larvae, unspecified Felis catus predator relationship Africa Marion Island, Stomach content analysis South Africa Compared Ectemnorrhinus spp. Prince Edward Rowe-rowe invaded/uninvaded Coleoptera Bothrometopus randi Suppression of Island, South et al. 1989 island(s) Lepidoptera Pringleophaga marioni Mus musculus predator preferred prey Africa

Araneae Ectemnorrhinus spp. Coleoptera Bothrometopus randi Suppression and Diptera Pringleophaga spp. decrease in body Chown and Hemiptera Apetanus litoralis size of preferred Marion Island, Smith 1993 Scat analysis Lepidoptera Others unspecified Mus musculus predator prey South Africa

Annelidae Dendrodrilus rubidus tenuis (NN) Araneae Ectemnorrhinus spp. Stomach content analysis Coleoptera Bothrometopus randi Diet preference Diptera Pringleophaga spp. Suppression of Marion Island, Smith et al. 2002 experiment Lepidoptera Others unspecified Mus musculus predator preferred prey South Africa

Pringleophaga marioni Ectemnorrhinus marioni Ectemnorrhinus similis Notodiscus hookeri Deroceras caruanae (NN) Microscolex kerguelarum Annelidae Microscolex kerguelenensis Araneae Dendrodrilus rubidus Coleoptera Myro paucispinosus van Aarde Experiment using Lepidoptera Myro kerguelensis Mus musculus Marion Island, et al. 2004 exclosure plots Mollusca Erigone sp. Felis catus predator Negligable effects South Africa

Ectemnorrhinus spp. Analysed long-term data Bothrometopus randi Body size Treasure in beetle body size and Bothrometopus parvulus increases in Marion Island, and Chown 2014 climate Coleoptera Bothrometopus elongatus Mus musculus predator preferred prey South Africa

Pringleophaga marioni Embryonopsis halticella Annelidae Microscolex kerguelarum Suppression Diet analysis Araneae Myro spp. and/or local McClelland Invertebrate trapping Coleoptera Prinerigone vagans extinction of Marion Island, et al. 2018 Soil cores Lepidoptera Others unspecified Mus musculus predator preferred prey South Africa

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Suppression of large body-sized Ile de la terrestrial Possession invertebrates (Kerguelen Pisanu et Isotope analysis stomach, Implications for archipelago), al. 2011 feaces, and liver Lepidoptera Pringleophaga spp. Rattus rattus predator nutient cycling France

Dendrodrilus rubidus tenuis (NN) Guillou Island Annelidae Microscolex kerguelensis (Kerguelen Le Roux et Coleoptera Pringleophaga kerguelensis Suppression of archipelago), al. 2002 Stomach content analysis Lepidoptera Ectemnorrhinus spp. Mus musculus predator preferred prey France

Competition with primary detritivores Implications for Invertebrate trapping Dimorphinoctua goughensis nutrient cycles and surveys and monitoring Annelidae Peridroma goughi formation of peaty Gough Island, Jones et al. 2002 Stomach content analysis Lepidoptera Unspecific Lumbricid worms (NN) Mus musculus predator soils United Kingdom

Competition with primary detritivores Dimorphinoctua goughensis Implications for Annelidae Peridroma goughi nutrient cycles and Chilopoda Lithobius melanops (NN) formation of peaty Gough Island, Jones et al. 2003a Stomach content analysis Lepidoptera Unspecified Lumbricid worms (NN) Mus musculus predator soils United Kingdom

Suppression and/or local Annelidae extinction of Auckland Island, Challies 1975 Stomach content analysis Amphipoda Unspecified Sus scrofa omnivore preferred prey New Zealand

Suppression and/or local Chimera et Annelidae extinction of Auckland Island, al. 1995 Stomach content analysis Amphipoda Unspecified Sus scrofa omnivore preferred prey New Zealand

Increased frequency of parasites and non- native Araneae invertebrates Ratio Experiment using Coleoptera shift between exclosure plots and Collembola Hydromedion sparsutum collembola and South Georgia, Vogel et al. 1984 control plots Diptera Others unspecified Rangifer tarandus herbivore spiders United Kingdom

Controlled experiment. Affects foraging Observed and measured dyanamics of beetle larve development native fauna, Chown and on four different grass growth rates and South Georgia, Block 1997 ypes Coleoptera Hydromedion sparsutum Poa annua plant nutrition United Kingdom

Community composition changes Declines Compared invertebrate in species Gremmen and plant densities Agrostis population Marion Island, et al. 1998 between a series of plots Unspecific Unspecified stolonifera plant densities South Africa

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Assists non-native invertebrate establishment which mutally assists its own spread Implications for Invertebrate monitoring reduced native surveys habitat quality for Convey et Observed activities Taraxacum native Marion Island, al. 2010 Prior research Unspecific Unspecified, species reliant on native habitat officinale plant invertebrates South Africa

New ecological functional group - arthropod predator Reduced abundance and increase in body Trechisibus size of endemic 1993, Invertebrate monitoring antarcticus beetle prey Ernsting et 1995, surveys Oopterus Implications for South Georgia, al. 1999 Laboratory experiment Coleoptera Hydromedion sparsutum soledadinus invertebrate nutrient cycling United Kingdom

Hypogastrura Outcompetes and viatica Convey et displaces native South Georgia, al. 1999 Invertebrate field surveys Collembola antarctics invertebrate species United Kingdom

New ecological functional group – pollinators Assists the spread of non-native pollinating plants thereby effecting native invertebrate habitat Alters soil nutrient cycling Diptera Eristalis processes Convey et Invertebrate field surveys Other - Paractora trichosterna croceimaculata Competes with South Georgia, al. 2010 and observations Unspecific Unspecific species reliant on native habitat Calliphora vicina invertebrate indigenous species United Kingdom

New trophic Puhuruhuru group: macro- patersoni detritivore, Alters Greenslade Invertebrate field surveys Styloniscus soil nutrient Macquarie et al. 2008 and observations Unspecific Unspecific competing soil species otakensis invertebrate cycling processes Island, Australia

Suppression of preferred invertebrate prey Annelidae with knock-on Collembola Dendrodrilus rubidus tenuis (NN) andersoni effects for soil Greenslade Invertebrate field surveys Other - Microscolex macquariensis Arthurdendyus nutrient cycling Macquarie et al. 2007 and observations Unspecific Others unspecific vegrandis invertebrate processes Island, Australia

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New functional Lee and 2007, Invertebrate field surveys Aphidius group: parasatoid. Marion Island, Chown 2016 and observations Hemiptera Rhopalosiphum padi (NN) matricariae invertebrate Spreads rapidly South Africa

Alters carbon and Microcosm study inorganic nutrient measuring rates of organic Lepidoptera mineralisation 2002, and inorganic nutrient Other - Pringleophaga marioni Deroceras Outcompetes Marion Island, Smith 2007 mineralisation Unspecific Unspecific competing soil species panormitanum invertebrate native detritivores South Africa

Competes with primary detritivores Implications for nurtient cycling Invertebrate surveys and Lepidoptera processes and Slabber & observations Other - Pringleophaga marioni formation of peaty Marion Island, Chown 2002 Stomach content analysis Unspecific Unspecific competing soil species Porcelio scaber invertebrate soils South Africa

Alters nutrient cycling Lepidoptera Outcompetes Hanel and Other - Pringleophaga marioni Limnophyes native primary Marion Island, Chown 1998 Invertebrate surveys Unspecific Unspecific competing soil species minimus invertebrate detritivores South Africa

Competition for Crafford Unspecified Drosophilid plant food Marion Island, and Chown 1990 Invertebrate surveys Diptera Dusmoecetes similis Plutella xylostella invertebrate resources South Africa

Suppression and/or local Laparie et Invertebrate surveys and Coleoptera Anatalanta aptera Merizodus extinction of Ile Kerguelen, al. 2010 observations Diptera Calycopteryx moseleyi soledadinus invertebrate preferred prey France

Macrosiphum euphorbiae Myzus ascalonicus Myzus cymbalariae Aulacorthum New ecological circumflexum niche - sap-feeders Ile Amsterdam, Aulacorthum Indirectly effects France solani native Ile de la Macrosiphum invertebrates Possession ornatus through reduction (Crozet), France Macrosiphum of native habitat Ile Saint-Paul, euphorbiae Risk of France 2003, Invertebrate surveys and Rhopalosiphum phytopathogen Ile Kerguelen, Hullé et al. 2010 observations Unspecific Unspecific species reliant on native habitat padi invertebrate virus transmission France

Chevrier et Invertebrate surveys and Competes with Ile Kerguelen, al. 1997 observations Diptera Anatalanta aptera Calliphora vicina invertebrate native detritvores France

Competion with primary detritivores implications for nurtient cycling processes and formation of peaty Lepidoptera Pringleophaga marioni Porcelio scab er soils Invertebrate surveys and Other - Unspecific competing detritivore species Quedius Supression of Marion Island, Jones et al. 2003c observations Unspecific Unspecific prey species mesomelinus invertebrate preferred prey South Africa

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Appendix 2 | Supplementary material for Chapter 4

Figure 1 Abundance of invertebrate orders by season on Antipodes Island as predicted by a generalised additive model.

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Antipodes Island 1.4

1.2

1

0.8

0.6

0.4 Abundance (Log10 +1)

0.2

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2011 2013 2016 2018

Figure 2 Total abundance (log10 + 1) of macroinvertebrates from pitfall catches on Antipodes Island in three years preceding mouse eradication (summer 2011, winter 2013, winter 2016) and one year following eradication (summer 2018)

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Figure 3 Total abundance (log10 + 1) of macroinvertebrates from pitfall catches on Macquarie Island in three years preceding mouse, rat and rabbit eradication (1986, 1993, 2009) and three years following eradication (2015, 2016, 2018).

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Figure 4 Pre- and post-eradication standardised pitfall trap abundance of invertebrates across five sites on Antipodes Island in the nine invertebrate orders shared with Macquarie Island.

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Figure 5 Pre- and post-eradication standardised pitfall trap abundance of invertebrates on Macquarie Island across ten sites in the nine invertebrate orders shared with Antipodes Island.

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Figure 6 Standardised abundance of pitfall trapped invertebrates across five habitat types on Macquarie Island in years prior to mammal eradication (summers 1986, 1993, 2009) and in years following eradication (summers 2015, 2016, 2018).

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Figure 7 Richness of pitfall trapped invertebrates across five habitat communities on Macquarie Island in years prior to mammal eradication (summers 1986, 1993, 2009) and in years following eradication (summers 2015, 2016, 2018).

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Figure 8 Simpson’s diversity of pitfall trapped invertebrates across five habitat communities on Macquarie Island in years prior to mammal eradication (summers 1986, 1993, 2009) and in years following eradication (summers 2015, 2016, 2018)

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Table 1 Generalised additive model predictions (as upper and lower confidence intervals) for standardised abundance of pitfall trapped invertebrates on Antipodes Island in four different years (summer 2011, winter 2013, winter 2016 pre-eradication, summer 2018 post-eradication), with significant differences (p = 0.05) indicated by a ‘*’. Visreg Visreg Significance Taxa Year Lwr Upr p = 0.05 Amphipods x2011 0.00 0.11 Amphipods x2013 DD DD Amphipods x2016 0.00 0.11 Amphipods x2018 0.05 0.20 Aphids x2011 0.01 0.10 Aphids x2013 0.00 0.15 Aphids x2016 0.00 0.10 Aphids x2018 0.00 0.18

Beetles x2011 0.82 1.42 * <2018 Beetles x2013 0.84 1.38 * <2018 Beetles x2016 0.66 1.30 * <2018 >2011, 2013, Beetles x2018 1.93 3.15 * 2016 Centipedes x2011 0.00 0.07 Centipedes x2013 0.00 0.99 Centipedes x2016 0.00 0.23 Centipedes x2018 0.22 0.51 >2013, 2016, Flies x2011 2.23 3.53 * 2018 Flies x2013 0.06 0.29 * <2011, 2016 Flies x2016 0.49 1.02 * <2011 Flies x2018 0.13 0.35 * <2011,2016 Lacewings x2011 DD DD Lacewings x2013 DD DD Lacewings x2016 0.00 0.23 Lacewings x2018 DD DD Moths x2011 0.00 0.07

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Moths x2013 DD DD Moths x2016 0.00 0.15 Moths x2018 0.00 0.08 Pseudoscorpions x2011 0.06 0.21 Pseudoscorpions x2013 0.00 0.32

Pseudoscorpions x2016 0.00 0.10 * <2018 Pseudoscorpions x2018 0.17 0.42 * >2016 Snails x2011 0.05 0.20 Snails x2013 0.00 0.15

Snails x2016 0.03 0.19 Snails x2018 0.04 0.18 Spiders x2011 0.14 0.36 * <2018 Spiders x2013 0.02 0.18 * <2016, 2018 Spiders x2016 0.10 0.33 * <2018 Spiders x2018 1.16 1.97 * >2011,2013, 2016 Wasps x2011 0.00 0.50

Wasps x2013 0.00 0.99 Wasps x2016 0.00 0.23 Wasps x2018 0.00 0.08 Woodlice x2011 0.15 0.38 * <2016, 2018 Woodlice x2013 0.16 0.44 * <2016, 2018 Woodlice x2016 0.50 1.03 * <2018 >2011, 2013, Woodlice x2018 14.68 22.48 * 2016 Worms x2011 0.06 0.20 Worms x2013 0.00 0.32 Worms x2016 0.00 0.12

Worms x2018 0.11 0.31

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Table 2 Generalise additive model predictions (as upper and lower confidence intervals) for standardised abundance of pitfall trapped invertebrates on Macquarie Island in six different years (summers 1986, 1993, 2009 pre-eradication, and summers 2015, 2016 and 2018 post-eradication), with significant differences (p = 0.05) indicated by a ‘*’. Visreg Visreg p = Significance Year Taxa Lwr Upr 0.05 x1986 Aphids 0.00 9.77 x1993 Aphids DD DD x2009 Aphids 0.00 0.58 * <2018 x2015 Aphids 0.00 0.02 * <2016, 2018 x2016 Aphids 0.03 0.08 * <2018 >1993, 2009, 2015, 2016, x2018 Aphids 0.61 0.92 * 2018 x1986 Beetles 0.09 1.94 * <2009 x1993 Beetles 0.10 0.88 * <2009, 2016 >1986, 1993, 2015, 2016, x2009 Beetles 3.62 10.66 * 2018 x2015 Beetles 0.55 0.77 * <2009, 2016, 2018 x2016 Beetles 1.37 1.77 * >1993, 2015, 2018; < 2009 x2018 Beetles 0.86 1.27 * >2015; <2016, 2009 x1986 Booklouse DD DD x1993 Booklouse DD DD x2009 Booklouse 0.00 0.54 x2015 Booklouse 0.00 0.04 * <2018 x2016 Booklouse 0.01 0.05 * <2018 x2018 Booklouse 0.05 0.05 * >2015, 2016 x1986 Flies 0.02 1.46 x1993 Flies 0.07 0.75 x2009 Flies 0.00 0.58 x2015 Flies 0.33 0.49 * <2018 x2016 Flies 0.34 0.48 * <2018 x2018 Flies 0.53 0.82 * >2015, 2016

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x1986 Moths 0.00 141428.17 x1993 Moths 0.00 1.79 x2009 Moths DD DD x2015 Moths 0.00 0.02 x2016 Moths 0.00 0.02 x2018 Moths 0.00 0.04 Snails & x1986 Slugs 0.00 1.68 Snails & x1993 Slugs 0.00 7.05 Snails & <2018 x2009 Slugs 0.01 0.40 * Snails & <2018 x2015 Slugs 0.28 0.41 * Snails & x2016 Slugs 0.36 0.50

Snails & >2009, 2015 x2018 Slugs 0.45 0.70 * x1986 Spiders 0.61 5.56 x1993 Spiders 0.10 1.14 x2009 Spiders 0.18 0.99 x2015 Spiders 0.70 0.95 x2016 Spiders 0.79 1.05 x2018 Spiders 0.91 1.33 x1986 Thrips 0.00 703.20 x1993 Thrips 0.00 3.03 x2009 Thrips 0.00 0.38 x2015 Thrips 0.03 0.07 x2016 Thrips 0.03 0.08 x2018 Thrips 0.03 0.09 x1986 Wasps DD DD x1993 Wasps DD DD x2009 Wasps DD DD

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x2015 Wasps DD DD x2016 Wasps 0.00 0.02 x2018 Wasps 0.00 0.03 x1986 Woodlice DD DD x1993 Woodlice DD DD x2009 Woodlice 0.09 0.34 x2015 Woodlice 0.02 0.10 x2016 Woodlice 0.05 0.05 x2018 Woodlice 0.01 0.04 * <2009, 2016 x1986 Worms 0.00 2.25 x1993 Worms 0.00 1.88 x2009 Worms 0.02 0.44 x2015 Worms 0.07 0.14 * <2016 x2016 Worms 0.17 0.26 * >2015 x2018 Worms 0.05 0.13 * <2016

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Table 3 Generalised additive model predictions (as upper and lower confidence intervals) for standardised abundance of pitfall trapped invertebrates in five different vegetation communities on Macquarie Island in size different years (1986, 1993, 2009 – pre-eradication, and 2015, 2016, 2018 post-eradication), with significant differences (p = 0.05) indicated by a ‘*’. Visreg Visreg Significance Year Vegetation Lwr Upr p=0.05 x1986 Feldmark 0.00 0.90 x1993 Feldmark 0.01 0.20 x2009 Feldmark 0.00 0.23 x2015 Feldmark 0.06 0.10 x2016 Feldmark 0.08 0.13 * <2018 x2018 Feldmark 0.13 0.22 * >2016 x1986 Herbfield 0.04 0.50 x1993 Herbfield 0.01 0.18 x2009 Herbfield 0.01 0.23 x2015 Herbfield 0.15 0.22 x2016 Herbfield 0.12 0.18 x2018 Herbfield 0.12 0.20 x1986 Short grass 0.00 13.91 x1993 Short grass 0.02 5.53 x2009 Short grass 0.07 0.30 * <2018 x2015 Short grass 0.12 0.19 * <2018 x2016 Short grass 0.19 0.27 * <2018 x2018 Short grass 0.54 0.78 * >2009, 2015, 2016 x1986 Stilbocarpa 0.03 0.94 x1993 Stilbocarpa 0.07 0.39 x2009 Stilbocarpa 0.03 0.33 x2015 Stilbocarpa 0.23 0.33 x2016 Stilbocarpa 0.32 0.43 x2018 Stilbocarpa 0.32 0.47 x1986 Tall grass 0.19 1.13 <2009 x1993 Tall grass 0.02 20.39

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x2009 Tall grass 1.48 3.62 <1986, 2009, 2016, x2015 Tall grass 0.29 0.37 * 2018 x2016 Tall grass 0.51 0.61 <2009 x2018 Tall grass 0.46 0.61 <2009

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Appendix 3 | Supplementary material for Chapter 5

Table 1 Locations of invertebrate sampling sites, with reference to vegetation community, aspect, zone and altitude across the three contemporary sampling periods (2015, 2016, 2018).

Historic site Island zone Site Location Aspect Vegetation Community Altitude (m) * North 1 Wireless Hill North Short Grassland 9 * North 2 Wireless Hill North Tall grass (tussock) 93 * North 3 Gadget's Gully East Feldmark 166 * North 4 Wireless Hill North Herbfield 90 * North 5 Halfway Hill East Short Grassland 46 * North 6 Razorback Northeast Stilbocarpa 7 * North 7 Razorback Northeast Tall grass (tussock) 7 * North 8 Doctors North Tall grass (tussock) 162 * North 9 Island Lake Track West Feldmark 242 * North 10 Island Lake Track Southwest Herbfield 235 Central 11 Green Gorge Southeast Short Grassland 25 Central 12 Green Gorge East Stilbocarpa 20 Central 13 Rockhopper Bay Top West Tall grass (tussock) 189 Central 14 Tiobunga lake West Feldmark 198 South 15 Links Track South Feldmark 236 South 16 West of Overland Track Southwest Herbfield 302 South 17 Hurd Point South Tall grass (tussock) 15 South 18 Waterfall Bay Southeast Stilbocarpa 35 Central 19 Bauer Bay West Stilbocarpa 30 Central 20 Bauer Bay West Herbfield 44 North 21 Handspike Northwest Tall grass (tussock) 40 North 22 Handspike Northwest Short Grassland (mire) 26 Central 23 Sandell Bay West Tall grass (tussock) 12 Central 24 Lusitania Bay Southeast Stilbocarpa 29

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Table 2 Summary of best models (as indicated lowest AIC) using a stepwise selection process. Predictor variables that were selected in the best model are shaded.

Predictor variables Adjusted R² Elevation Slope Solar Wind Wetness Ridge Non-native Vegetation Year Method and Radiation speed species (factor) (factor) deviance Order: Species Guild explained of Response best model. variables All are Negative Binomial distribution, Australimyzidae Diptera: Herbivore Pitfall R2=0.64, Australimyza Deviance Flies macquariensis explained: 53.1% Calliphoridae (+) Sweep R2=0.77, Chironomidae Deviance (+) explained: 79.1% Calliphoridae (-) Count R2=0.23, Deviance explained: 66.1% Geoplanidae (+) Litter R2=0.67, Deviance explained: 89% Agriolimacidae Beat R2=0.86, (-) Deviance Calliphoridae (-) explained: Chironomidae (-) 81.6% Agriolimacidae Mollusca: Herbivore Pitfall R2=0.3, (NN) Derocerus Deviance reticulatum explained: Slugs 16.4%

Janiridae (-) Count R2=0.73, Deviance explained: 85.1% Litter R2=0.46, Deviance explained: 69.8%

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Chironomidae Beat R2=0.57, (+) Deviance explained: 52.9% Punctidae Mollusca: Janiridae (-) Count R2=0.68, Phrixgnathus Herbivore Agriolimacidae Deviance Snails hamiltoni (-) explained: 77.4% Litter R2=0.74, Deviance explained: 75.8% Beat R2=0.44, Deviance explained: 61.4% Aphididae Hemiptera: Herbivore Chironomidae Pitfall R2=0.99, (NN) Myzus (+) Deviance ascalonicus, explained: Aphids Jacksonia 93.5% papillata Calliphoridae (-) Sweep R2=0.99, Deviance explained: 97.9% Agriolimacidae Count R2=1, (+) Deviance explained: 99.6% Litter R2=0.62, Deviance explained: 92.4% Chironomidae Beat R2=0.99, (+) Deviance explained: 96.6% Staphylinidae Coleoptera: Pitfall R2=0.97, Omaliomimus Predator Deviance Rove beetles venator, O. explained: albipennis, 87.3% Stenomalium sulcithorax, Stenomalium helmsi, Leptusa Antarctica

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Count R2=0.46, Deviance explained: 63.8% Janiridae (+) Litter R2=0.57, Deviance explained: 67.7% Beat R2=0.68, Deviance explained: 46.3% Psychodidae Diptera: Sweep R2=0.47, Psychoda Detritivore Deviance Moth flies surcoufi (NN), explained: Psychoda 53.6%7 parthenogenetica (NN)

Agriolimacidae Beat R2=0.94, (+) Deviance Chironomidae (-) explained: 90.4% Litter R2=0.26, Deviance explained: 85.2% Dolichopodidae Diptera: Aphididae (-) Sweep R2=0.73, Thinophilus Predator Deviance Wingless flies pedestris explained: pedestris 72.9% Count R2=0.39, Deviance explained: 49% Litter R2=0.26, Deviance explained: 85.2% Beat R2=0.89, Deviance explained: 70.3% Yellow pan R2=0.73, Deviance explained: 42.1%

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Pyralidae Lepidoptera: Sweep R2=0.66, Eudonia Herbivore Deviance Moths mawsoni explained: 58.4% Aphididae (-) Count R2=0.65, Janiridae (-) Deviance explained: 67.8% Janiridae (-) Litter R2=0.6, Deviance explained: 60.9% Janiridae Isopoda: Agriolimacidae Count R2=0.66, (NN) Styloniscus (-) Deviance otakensis Calliphoridae (-) explained: Woodlice Chironomidae (-) 97.4% (slaters) Geoplanidae (-) Litter R2=0.79, Deviance explained: 98.8% Desidae Araneae: Aphididae (-) Pitfall R2= 0.63, Myro Predator Chironomidae Deviance Spiders kerguelensis (+) explained: 61.4% Aphididae (-) Sweep R2=0.88, Calliiphoridae (-) Deviance explained: 74.2% Geoplanidae (-) Count R2=0.74, Deviance explained: 88.4% Litter R2=0.44, Deviance explained: 78.7% Linyphiidae Araneae: Sciaridae (+) Pitfall R2=0.69, Parafroneta Predator Deviance Spiders marrineri, explained: Haplinis 49% mundenia Sweep R2=0.13, Deviance explained: 26.5%

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Aphididae (-) Count R2=0.62, Geoplanidae (+) Deviance Janiridae (+) explained: 74.6% Litter R2=0.68, Deviance explained: 91.7% Beat R2=0.29, Deviance explained: 51.9% Thripidae Thysanoptera: Sweep R2=0.63, Physemothrips Herbivore Deviance Thrips chrysodermus explained: 69.2% Geoplanidae (-) Litter R2=0.54, Janiridae (+) Deviance explained: 79.7% Beat R2=0.32, Deviance explained: 51%, Annelidae Oligochaeta: Agriolimacidae Count R2=0.27, (N and NN) Many species Detritivore (+) Deviance explained: Earthworms 50.9%

Geoplanidae (-) Litter R2=0.28, Deviance explained: 40.9% Pseudocaeciliidae Psocoptera: Sweep R2=0.3, Austropsocus Detritivore Deviance Booklice insularis explained: 73.5% Aphididae (+) Litter R2=0.56, Deviance explained: 86.1% Geoplanidae Platyhelminthes: Predator Count R2=0.42, (NN) Kontikia Deviance andersoni explained: Flatworms 78.8% Arthurdendyus vegrandis (not

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trapped during study this period)

Calliphoridae Diptera: No model (NN) Xenocalliphora Herbivore/detritivore sp. Blowflies Chironomidae Diptera: Herbvire/detritivore No model (NN) Smittia sp.

Flies (midges) Sciaridae Diptera: Detritivore No model (NN) Bradysia strenua

Flies (fungus gnats) Tipulidae Diptera: Detritivore No model Timicra pilipes Crane flies

Triozidae Hemiptera: Herbivore No model (NN) Undet sp.

Leaf hoppers

Scolytinae Coletopera: Herbivore No model (NN) Undet sp.

Bark beetles Byrrhidae Coletopera: Herbivore No model (NN) Epichorius sorensi Pill beetles Coelopidae Diptera: Detritivore No model Coelopella Kelp flies curvipes Icaridion nigrifrons Diapriidae Hymenoptera: Parasite No model Antarctopria Parasitic wasps latigaster

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Figure 1 Partial residual plots generated by generalised additive models illustrating abundance relationships to five vegetation communities for 19 invertebrate families on Macquarie Island; Feld = Feldmark, Herb = Herbfield, Shtgr = Shortgrass, Stilbo = Stilbocarpa, Tallgr = Tallgrass. Families with low overall catches were data deficient for the model and were removed (Triozidae, Scolytinae, Byrrhidae, Sciaridae, Plutellidae). Grey shading indicates the 95% confidence intervals. DD = data deficient, i.e. where no individuals were caught in that vegetation community for that family.

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Figure 2 Partial residual plots generated from generalised additive models illustrating invertebrate abundance relationships to year of sampling on Macquarie Island: a) Staphylinidae (litter) and b) Thripidae (litter). Grey shading indicates the 95% confidence intervals.

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Appendix 4 | Supplementary material for Chapter 6

Table 1 Maximum size (mm) and mean size (mm) of taxa from eighteen invertebrate Orders from four status groups ‘Detected’, ‘Transient alien’ ‘Established alien’, and ‘Indigenous’ at Macquarie Island.

Order Detected Transient alien Established alien Indigenous Maximum Mean Maximum Mean Maximum Mean Maximum Mean Acarina 1.1 0.48 1.1 0.52 1.5 0.83 Amphipoda 9.0 8.5 Araneae 21.6 5.99 25.0 12.2 6.5 4.64 Blattodea 12.0 9.09 Coleoptera 28.1 6.85 9.4 5 4.2 3.16 4.0 3.45 Collembola 1.4 1.103 1.2 1.55 3.4 1.58 2.3 1.01 Dermaptera 18.0 13.71 13.2 Diptera 22.2 4.55 5.0 2.31 11.0 4.02 8.0 3.77 Hemiptera 8.6 3.6 5.0 3.8 2.5 1.75 Hymentoptera 16.0 6 16.0 13 3.3 2.4 Isopoda 5.5 4.25 Julida 28.3 Lepidoptera 51.1 19.84 31.5 15.98 9.0 7 11.0 10.3 Neuroptera 6.4 4.78 Orthoptera 34.1 27.98 Psocoptera 1.1 0.85 2.5 2 Thysanoptera 1.3 1.05 1.2 0.85 1.8 1.55 Zygenotoma 20.0 16

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Table 2 Significant differences detected (p=0.05), indicated by an ‘*’, in the mean estimate of the maximum body size predicted by generalised linear modelling: D=Detected, I = Indigenous, T=Transient alien, E = Established alien

D-E D-I D-T E-I E-T I-T

Detritivore *

Detritivore/Predator

Fungivore

Grainivore/Detritivore Grainivore/Herbivore Herbivore * * * *

Herbivore/Detritivore * Herbivore/Fungivore Omnivore * *

Parasite Predator * * * *

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Figure 1 Partial residual plots, from the model of mean body size (mm) vs vagility, status and their interaction, showing predicted (log) body size for both ‘established’ and ‘not established’ groups for winged and wingless taxa.

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Figure 2 Partial residual plots, from the model of mean body size (mm) vs vagility, status and their interaction, showing predicted (log) body size each of the status groups along the pathway (Detected –D, Transient – T , Established – E, and Indigenous – I) for winged and wingless taxa.

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Figure 3 Partial residual plots, from the model of mean body size (mm) vs status, guild and their interaction, showing predicted (log) body size for the 11 guilds and status. A star symbol denotes a significant variation.

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Figure 4 Variation in (log) mean body size for each status group; ‘detected’, ‘transient- alien’, ‘established-alien’, ‘indigenous’ invertebrates associated with Macquarie Island

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Figure 5. Partial residual plots from the model of mean body size (mm) vs status, guild and their interaction, showing predicted (log) body size for the 11 guilds and different status groups (D = Detected, T = Transient-alien, E = Established-alien, I = Indigenous).

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Table 3 Body size measurements, methods and references plus feeding guilds for invertebrates detected in cargo, on ships and on stations in association with the Australian Antarctic Program.

Order Family Genus Species Number of Range per Mean Max Establishe Vagile Guild Guild Guild Individuals TOU d Macq notes Reference per OTU Y/N

Diptera Anisopodi Sylvicola undet 1 NA NA 6.435 No Yes Detritivore 'live in Colless & dae organic McApline matter' 1970 Coleoptera Anobiidae Anobium undet 1 NA NA 3.461 Yes Yes Herbivore wood-borer Britton 1970 Coleoptera Anthribida undet undet 1 NA NA 8.668 No Yes Herbivore/Fu wood-borer Britton 1970 e ngivore Hemiptera Aphididae undet undet 1 NA NA 0.735 Yes Yes Herbivore sap feeding Daley 2007, Woodward et al. 1970 Hymenopter Apidae Apis mellifera 2 11.054- 13.5275 16.001 No Yes Herbivore Nectarivore Daley 2007, a 16.001 Riek et al. 1970 Hemiptera Aradidae undet undet 1 NA NA 4.439 No No Fungivore Woodward et al. 1970 Araneae Araneidae Araneus undet 1 NA NA 16.434 No No Predator Hawkeswood 2003 2003 Araneae Araneidae undet undet 4 2.801-6.007 4.5105 6.007 No No Predator Hawkeswood 2003 Lepidoptera Arctiidae Castulo doubledayi 1 NA NA 10.172 No Yes Herbivore Daley 2007 Blattodea Blattellida undet undet 6 5.315- 9.092167 12.068 Yes Yes Omnivore El Sharbasy et e 12.068 al. 2014 Hymenopter Braconida undet undet 1 NA NA 6.041 No Yes Parasite Parisatoid/ Daley 2007, a e Nectarivore Riek et al. 1970 Diptera Calliphori Calliphora stygia 1 NA NA 10.336 Yes Yes Herbivore/De Detritivore/ Daley 2007, dae tritivore Nectarivore Colless & (adults) McApline (final class. 1970 Herbivore/d etritivore) Diptera Calliphori Calliphora undet 3 13.969- 14.70667 16.085 Yes Yes Herbivore/De Detritivore/ Daley 2007, dae 16.085 tritivore Nectarivore Colless & (adults) McApline (final class. 1970 Herbivore/d etritivore)

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Diptera Calliphori Calliphora vicina 1 NA NA 9.912 Yes Yes Herbivore/De Detritivore/ Daley 2007, dae tritivore Nectarivore Colless & (adults) McApline (final class. 1970 Herbivore/d etritivore) Coleoptera Cantharid Chauliognath lugubris 1 NA NA 12.369 No Yes Omnivore Predator/Ne Daley 2007, ae us ctarivore Britton 1970 Coleoptera Cantharid Hypothalamu undet 4 3.484-5.462 4.16 5.462 No Yes Predator Britton 1970 ae s Coleoptera Carabidae Mecylothorax ambiguus 1 NA NA 4.91 No No Predator Britton 1970 Coleoptera Carabidae undet undet 3 8.963-9.82 9.33 9.82 No No Predator Britton 1970 Coleoptera Carabidae Microlestes undet 1 NA NA 1.418 No Yes Predator Britton 1970 Diptera Cecidomyi undet undet 1 NA NA 1.552 No Yes Herbivore/De Detritivore/ Colless & dae tritivore Nectarivore McApline (adults) 1970 Coleoptera Cerambyci Phoracantha undet 1 NA NA 28.144 No Yes Herbivore Britton 1970 dae Coleoptera Cerambyci undet undet 3 12.534- 15.16367 16.887 No Yes Herbivore Britton 1970 dae 16.887 Diptera Chironomi undet undet 13 1.602-7.752 3.759417 7.752 Yes Yes Omnivore Detritivore/ Daley 2007 dae Predator/Ne ctarivore (adults); (final class. Omnivore - opportunisti c) Diptera Chloropid undet undet 8 2.363-3.937 2.8395 3.937 Yes Yes Herbivore Colless & ae McApline 1970 Coleoptera Chrysomel undet undet 1 NA NA 3.488 No Yes Herbivore Daley 2007, idae Britton 1970 Hemiptera Cicadellida undet undet 1 NA NA 2.512 No Yes Herbivore Woodward et e al. 1970 Araneae Clubionida Clubiona undet 2 9.676- 11.757 13.838 No No Predator Hawkeswood e 13.838 2003 Hemiptera Coccidae undet undet 10 1.459-2.031 1.6863 2.031 No No Herbivore Woodward et al. 1970 Coleoptera Coccinellid Cleobora mellyi 2 8.107-8.257 8.182 8.257 No Yes Predator Daley 2007, ae Britton 1970 Coleoptera Coccinellid Coccinella transversali 1 NA NA 5.271 No Yes Predator Daley 2007, ae s Britton 1970 Coleoptera Coccinellid Coccinella undecimpu 11 4.397-6.06 5.085429 6.06 No Yes Predator Daley 2007, ae nctata Britton 1970

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Diptera Coelopidae undet undet 11 4.651-7.476 5.387455 7.476 Yes Yes Detritivore Colless & McApline 1970 Coleoptera Corylophi undet undet 3 0.978-1.11 1.058667 1.11 No Yes Fungivore Britton 1970 dae Lepidoptera Cosmopter undet undet 1 NA NA 2.29 No Yes Omnivore Common 1970 ygidae Lepidoptera Cossidae undet undet 2 39.828 45.466 51.104 No Yes Herbivore Daley 2007, Common 1970 Coleoptera Cryptopha Cryptophagu undet 1 NA NA 1.495 No Yes Fungivore Britton 1970 gidae s Diptera Culicidae Culex undet 2 5.098-7.218 6.158 7.218 No Yes Parasite Ectoparasit Colless & e, Blood- McApline sucking 1970 Coleoptera Curculioni Gonipterus undet 5 6.385- 10.408 11.967 Yes No Herbivore Daley 2007, dae 11.967 Britton 1970 Coleoptera Curculioni Mandalotus undet 1 NA NA 3.794 Yes No Herbivore Daley 2007, dae Britton 1970 Coleoptera Curculioni Merimnetes undet 2 7.617-8.09 6.680667 8.09 Yes No Herbivore Daley 2007, dae Britton 1970 Coleoptera Curculioni undet undet 3 4.628- 8.035 12.267 Yes No Herbivore Daley 2007, dae 12.267 Britton 1970 Hemiptera Cydnidae undet undet 2 6.445-8.624 7.5345 8.624 No Yes Herbivore root Woodward et feeding al. 1970 Coleoptera Dermestid Anthrenus verbasci 1 NA NA 2.914 No Yes Herbivore/De Detritivore/ Booth et al., ae tritivore Nectarivore Britton 1970 (adults) (final class. Herbivore/d etritivore) Coleoptera Dermestid undet undet 1 NA NA 1.791 No Yes Herbivore/De Detritivore/ Booth et al., ae tritivore Nectarivore Britton 1970 (adults) (final class. Herbivore/d etritivore) Araneae Desidae Badumna insignis 7 3.913- 7.836429 10.243 Yes No Predator Hawkeswood 10.243 2003 Araneae Desidae Badumna undet 1 NA NA 6.219 Yes No Predator Hawkeswood 2003 Araneae Desidae undet undet 3 3.785-6.041 4.198 6.041 Yes No Predator Hawkeswood 2003 Hymenopter Diapriidae undet undet 1 NA NA 2.763 Yes Yes Parasite Parisatoid Riek et al. a 1970 Diptera Drosophili undet undet 3 2.248-2.665 2.488333 2.665 No Yes Fungivore Colless & dae McApline 1970

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Coleoptera Elateridae Agrypnus undet 1 NA NA 11.759 No Yes Omnivore Detritivore/ Calder 1996, Predator/Ne Daley 2007, ctarivore Britton 1970 (adults); (final class. Omnivore - opportunisti c) Coleoptera Elateridae Conoderus undet 1 NA NA 9.468 No Yes Omnivore Detritivore/ Calder 1996, Predator/Ne Daley 2007, ctarivore Britton 1970 (adults); (final class. Omnivore - opportunisti c) Coleoptera Elateridae undet undet 1 NA NA 3.474 No Yes Omnivore Detritivore/ Calder 1996, Predator/Ne Daley 2007, ctarivore Britton 1970 (adults); (final class. Omnivore - opportunisti c) Diptera undet undet 3 2.535-6.075 4.524333 6.075 No Yes Predator Colless & McApline 1970 Collembola Entomobr undet undet 2 1.34-1.408 1.374 1.408 Yes No Detritivore Hopkins 1997 yidae Dermaptera Forficulida Forficula auricularia 1 NA NA 11.381 No No Omnivore Giles 1970 e Hymenopter Formicida Iridomyrmex undet 5 3.787-5.034 4.3606 5.034 No No Omnivore Daley 2007, a e Riek et al. 1970 Hymenopter Formicida Linepithema humile 1 NA NA 3.708 No No Omnivore Daley 2007, a e Riek et al. 1970 Hymenopter Formicida Pheidole undet 1 NA NA 3.708 No No Omnivore Daley 2007, a e Riek et al. 1970 Hymenopter Formicida undet undet 2 2.288-4.743 3.5155 4.743 No No Omnivore Daley 2007, a e Riek et al. 1970 Lepidoptera Gelechiida undet undet 1 NA NA 3.243 No Yes Herbivore Common 1970 e Lepidoptera Geometrid Larentiinae undet 1 NA NA 5.087 No Yes Herbivore Daley 2007, ae Common 1970

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Araneae Gnaphosid undet undet 1 NA NA 3.394 No No Predator Hawkeswood ae 2003 Orthoptera Gryllidae Teleogryllus commodus 6 21.835- 27.9765 34.055 No Yes Herbivore Daley 2007 34.055 Hymenopter Halictidae Lasioglossum undet 1 NA NA 9.654 No Yes Herbivore Nectarivore Riek et al. a 1970 Diptera Heleomyzi undet undet 5 1.892-6.417 4.4928 6.417 No Yes Detritivore ref. for Garnett and dae genus Foote 1966 Neuroptera Hemerobii Micromus tasmaniae 6 4.071-6.434 4.780667 6.434 No Yes Predator Riek 1970 dae Hymenopter Ichneumon undet undet 1 NA NA 7.863 No Yes Parasite Parisatoid Daley 2007, a idae (larvae)/Ne Riek et al. catarivore 1970 (adults) Julida Julidae Ommatoiulus moreleti 1 NA NA 28.272 No No Detritivore Hopkin and Read 1992 Dermaptera Labidurid undet undet 1 NA NA 12.972 No No Omnivore Giles 1970 ae Dermaptera Labidurid Labidura 20 10.385- 13.70589 17.961 No No Omnivore Giles 1970 ae 17.961 Coleoptera Latridiidae Aridius nodifer 1 NA NA 2.272 No Yes Fungivore Britton 1970 Coleoptera Latridiidae undet undet 1 NA NA 1.486 No Yes Fungivore Britton 1970 Diptera Lauxaniid undet undet 6 2.52-6.033 3.9948 6.033 No Yes Detritivore Daley 2007, ae Colless & McApline 1970 Araneae Linyphiida undet undet 1 NA NA 1.88 Yes No Predator Hickman 1967 e Diptera Lonchopte undet undet 1 NA NA 2.563 No Yes Detritivore 'live in Colless & ridae decaying McApline matter' 1970 Araneae Lycosidae Artoria undet 2 2.55-4.465 3.51 4.465 No No Predator Hawkeswood 2003 Araneae Lycosidae undet undet 1 NA NA 1.444 No No Predator Hawkeswood 2003 Hemiptera Lygaeidae Cryptorhamp orbus 1 NA NA 6.069 No Yes Herbivore seed Woodward et us feeding al. 1970 Hemiptera Lygaeidae Nysius vinitor 13 3.13-4.438 3.571385 4.438 No Yes Herbivore seed Woodward et feeding al. 1970 Hemiptera Lygaeidae undet undet 3 2.847-5.026 3.71 5.026 No Yes Herbivore seed Woodward et feeding al. 1970 Lepidoptera Lymantrii undet undet 1 NA NA 7.643 No Yes Herbivore Daley 2007, dae Zborowski and Edwards 2007 Diptera Fannia undet 3 2.811-7.887 4.810667 7.887 No Yes Detritivore ref. for Martinez 2007 genus

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Diptera Muscidae Helina undet 3 7.218-9.102 8.08 9.102 No Yes Predator ref. for Martinez 2007 genus Diptera Muscidae Musca undet 5 5.517-7.309 6.2434 7.309 No Yes Detritivore Colless & McApline 1970 Diptera Muscidae undet undet 5 6.228-8.499 7.466 8.499 No Yes Detritivore Daley 2007, Colless & McAplpne 1970 Diptera Mycetophil undet undet 7 2.524-6.077 4.000143 6.077 No Yes Fungivore Colless & idae McApline 1970 Coleoptera Nitidulidae Carpophilus undet 3 4.127-4.918 4.430667 4.918 No Yes Grainivore/Herbivore Britton 1970 Coleoptera Nitidulidae undet undet 1 NA NA 2.128 No Yes Omnivore Britton 1970 Lepidoptera Noctuidae Agrotis infusa 14 15.571 19.83429 25.921 No Yes Herbivore Daley 2007, Common 1970 Lepidoptera Noctuidae Agrotis munda 1 NA NA 15.144 No Yes Herbivore Daley 2007, Common 1970 Lepidoptera Noctuidae Agrotis porphyricol 3 14.539- 15.81533 16.803 No Yes Herbivore Daley 2007, lis 16.803 Zborowski and Edwards 2007 Lepidoptera Noctuidae Heliothis punctifer 1 NA NA 15.81 No Yes Herbivore Daley 2007, Common 1970 Lepidoptera Noctuidae Larentiinae undet 1 NA NA 1.581 No Yes Herbivore Daley 2007, Zborowski and Edwards 2007 Lepidoptera Noctuidae Persectania ewingii 19 7.603- 17.58447 23.004 No Yes Herbivore Daley 2007, 23.004 Common 1970 Lepidoptera Noctuidae Proteuxoa sanguinipu 14 16.05- 21.35914 27.319 No Yes Herbivore Daley 2007, ncta 27.319 Zborowski and Edwards 2007 Lepidoptera Noctuidae undet undet 1 NA NA 28.297 No Yes Herbivore Daley 2007, Common 1970 Araneae Oecobiidae Oecobius undet 7 0.887-2.193 1.896857 2.193 No No Predator Ref. for Líznarová et genus al. 2015, Garcia et al. 2014 Lepidoptera Oecophori Philobota undet 1 NA NA 8.218 No Yes Herbivore/Fungivore Daley 2007, dae Common 1970 Acarina undet undet 31 0.37-1.075 0.483548 1.075 Yes No Detritivore for Greenslade oribatida 2006 superfamily , inc mycophyto phgous

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Diptera Megaselia undet 16 1.445-2.59 2.170188 2.59 No Yes Detritivore Colless & McApline 1970 Diptera Phoridae undet undet 3 1.488-3.236 2.313667 3.236 No Yes Detritivore Colless & McApline 1970 Lepidoptera Pieridae Pieris rapae 1 NA NA 18.024 No Yes Herbivore Common 1970 Diptera Psychodid undet undet 4 1.39-1.926 1.75175 1.926 Yes Yes Detritivore Colless & ae McApline 1970 Hemiptera Psyllidae undet undet 2 1.361-1.688 1.5245 1.688 No Yes Herbivore sap feeding Daley 2007, Woodward et al. 1970 Coleoptera Ptinidae Ptinus tectus 43 2.688-5.571 3.118146 5.571 Yes Yes Grainivore/Detritivore Britton 1970 Coleoptera Ptinidae undet undet 69 2.729-3.525 3.148071 3.525 Yes Yes Grainivore/Detritivore Britton 1970 Lepidoptera Pyralidae Ephestia undet 1 NA NA 6.117 Yes Yes Grainivore/Detritivore Common 1970 Lepidoptera Pyralidae undet 1 NA NA 5.716 Yes Yes Grainivore/Herbivore Common 1970 Lepidoptera Pyralidae Plodia interpunctel 5 2.364-7.195 5.6586 7.195 Yes Yes Grainivore/Herbivore Common 1970 la Diptera Rhagionid undet undet 1 NA NA 22.224 No Yes Predator Colless & ae McApline 1970 Araneae Salticidae Breda jovialis 2 2.341-3.635 2.988 3.635 No No Predator Hawkeswood 2003 Araneae Salticidae undet undet 4 4.542-7.099 5.56 7.099 No No Predator Hawkeswood 2003 Coleoptera Scarabaeid Adoryphorus couloni 4 12.314- 13.133 13.974 No Yes Herbivore Britton 1970 ae 13.974 Coleoptera Scarabaeid Aphodius fimetarius 1 NA NA 6.947 No Yes Detritivore Britton 1970 ae Coleoptera Scarabaeid Phyllotocus macleayi 5 7.475- 8.6972 10.288 No Yes Herbivore Herbivore(l Daley 2007, ae 10.288 arvae)/Nect Britton 1970 arivore (adults) Coleoptera Scarabaeid Sericesthis nigrolineat 1 NA NA 15.726 No Yes Herbivore/Detritivore Daley 2007, ae a Britton 1970 Diptera Sciaridae Lycoriella ingenua 20 2.694-3.533 2.99615 3.533 Yes Yes Detritivore Colless & McApline 1970 Diptera Sciaridae Sciara undet 11 2.625-3.484 3.008182 3.484 Yes Yes Detritivore Colless & McApline 1970 Diptera Sciaridae undet undet 10 1.986-3.031 2.4728 3.031 Yes Yes Detritivore Colless & McApline 1970

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Araneae Sparassida Delena cancerides 3 17.251- 19.16367 21.562 No No Predator Hawkeswood e 21.562 2003 Coleoptera Staphylini undet undet 4 1.837-2.619 2.1475 2.619 Yes Yes Predator Greenslade dae 2006, Britton 1970 Coleoptera Tenebrioni undet undet 1 NA NA 3.43 No Yes Detritivore Daley 2007, dae Britton 1970 Diptera Tephritida undet undet 1 NA NA 5.647 No Yes Omnivore ref. for Aluja et e genus, al.2001 'Polyphago us' Araneae Theridiida undet undet 2 1.393-4.078 2.7355 4.078 No No Predator Hawkeswood e 2003 Lepidoptera Tineidae Monopis undet 1 NA NA 8.097 No Yes Detritivore clothes, Zborowski and wool Edwards 2007 feathers, fur etc fungi within Lepidoptera Tineidae Opogona undet 1 NA NA 5.632 No Yes Detritivore clothes, Zborowski and wool Edwards 2007 feathers, fur etc fungi within Diptera Tipulidae undet undet 2 3.475-4.481 3.978 4.481 Yes Yes Omnivore Daley 2007 Araneae undet undet undet 9 0.722-4.504 1.742889 4.504 NA No Predator Hawkeswood 2003 Collembola undet undet undet 2 0.575-0.718 0.6465 0.718 NA No NA NA Diptera undet undet undet 2 2.228-2.519 2.3735 2.519 NA Yes NA NA Hymenopter undet undet undet 2 1.875-3.351 2.613 3.351 NA Yes NA NA a Lepidoptera undet undet undet 3 7.809- 13.149 16.037 NA Yes NA NA 16.037 Psocoptera undet undet undet 4 0.412-1.103 0.851 1.103 NA Yes Detritivore Smithers 1970 Lepidoptera Yponomeu Zelleria undet 1 NA NA 7.489 No Yes Herbivore Daley 2007, tidae Common 1970 Table 4 Body size measurements, methods and references, plus feeding guilds and references for invertebrates indigenous to Macquarie Island, as well as transient-alien and established-alien invertebrates found on Macquarie Island.

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Status (I=indigenous , No. specimen E=established measure alien, T = No. Reference (field survey Body Size transient Collection or biosecurity Body size Body size Guild Order Family Genus Species range (mm) Mean (mm) Max (mm) alien measure detected) reference notes Established Vagile Guild Guild notes reference Pseudocaecilii Greenslade Herbivore/Fun Greenslade Psocoptera dae Austropsocus insularis 1.5-2.5 2.00 2.50 I 2006 Established No givore 2006 Greenslade 2006, Greenslade Woodward et Hemiptera Aphididae Jacksonia papillata 1-2.5 1.75 2.50 E 2006 Established Yes Herbivore al. 1970 Greenslade 2006, Greenslade Woodward et Hemiptera Aphididae Myzus ascaloliscus 1-2.5 1.75 2.50 E 2006 Established Yes Herbivore al. 1970 Greenslade 2006, Rhopalosiphu Greenslade Woodward et Hemiptera Aphididae m padi 1-2.5 1.75 2.50 E 2006 Established Yes Herbivore al. 1970 Not Woodward et Hemiptera Lygaeidae Nysius undet 3-5 3.80 5.00 T 13 Established Yes Herbivore Seed feeding al. 1970 Greenslade Greenslade 2006, Watson 2006, Watson Thysanoptera Thripidae Physemothrips chrysodermus 1.3-1.8 1.55 1.80 I 1967 Established No Herbivore 1967 Not Thysanoptera Thripidae Thrips imaginis 0.8-1.3 1.05 1.30 T Steiner 2008 Established Yes Herbivore Reed 1970 Andaloro & Shelton, 1983; Thrips tabaci (onion thrips), Invasive Species Compendium, CABI. http://web.ento mology.cornel l.edu/shelton/v eg-insects- global/english/ thrips.html. Greenslade Retrieved 2006, Reed Thysanoptera Thripidae Thrips tabaci 0.5-1.2 0.85 1.20 E 21/1/19 Established Yes Herbivore 1970 cf. Not Greenslade Coleoptera Hydraenidae Meropathus undet 1.6-2.6 1.90 2.60 T Ordish 1971 Established Yes Herbivore Algivore 2006 Not Greenslade Coleoptera Byrrhidae Epichorius sorenseni 6.8-9.4 8.10 9.40 T Watt 1971 Established Yes Herbivore Algivore 2006 Leptusa Greenslade Coleoptera Staphylinidae (Halmaeusa) antarctica 2.5-4 3.25 4.00 I 21 Steel 1964 Established No Predator Algivore 2006 Greenslade Coleoptera Staphylinidae Omaliomimus venator 2.75-4 3.5 4 I 21 Steel 1964 Established No Predator Algivore 2006 Greenslade Coleoptera Staphylinidae Omaliomimus alibipennis 2.75-4 3.5 4 I Steel 1964 Established No Predator Algivore 2006 Greenslade Coleoptera Staphylinidae Stenolmalium sulcithorax 3.25-4 3.5 4 I 20 Established No Predator Algivore 2006 presumed as Greenslade Coleoptera Staphylinidae Stenolmalium helmsi 3.25-4 3.5 4 I 'sulcithorax' Established No Predator Algivore 2006 Ojo & Grainivore/He Lawrence and Coleoptera Curculionidae Sitophilus zeamais 3.3-4.2 3.75 4.20 E Omoloye 2016 Established Yes rbivore Britton 1994 Booth et al. 1990, Lawrence and Booth et al. Grainivore/He Britton 1994, Coleoptera Bostrychidae Rhizopertha dominica 2.5 -3 2.75 3 E 1990 Established Yes rbivore Britton 1970 Grains plus Booth et al. Booth et al. Grainivore/De museum 1990, Coleoptera Ptinidae Ptinus tectus 2.5-4 3.42 4.00 E 16 1990 Established Yes tritivore species, fur, Lawrence and

242

wool, feathers Britton 1994, etc Britton 1970 Grains plus Booth et al. museum 1990, species, fur, Lawrence and Grainivore/De wool, feathers Britton 1994, Coleoptera Ptinidae 3-3.5 3.00 3.50 E 8 Established Yes tritivore etc Britton 1970 Grains plus Booth et al. museum 1990, species, fur, Lawrence and Grainivore/De wool, feathers Britton 1994, Coleoptera Anobiidae cf. Stegobium paniceum 2-3.5 2.90 3.50 E 22 Established Yes tritivore etc Britton 1970 Colless & McAlpine 1970, Greenslade Greenslade Diptera Tipulidae Timicra pilipes 5-8 6.5 8 I 2006 Established Yes Detritivore 2006 Detritivore/Ne Xenocalliphor Herbivore/Det ctarivore Diptera Calliphoridae a undet 6.5-11 8.75 11.00 E Dear 1986 Established Yes ritivore (adults) Dear 1986 Detritivore/Ne Greenslade Leader 1975, Herbivore/Det ctarivore 2006, Watson Diptera Chironomidae Smittia undet 1.2-1.5 1.35 1.50 E Watson 1967 Established Yes ritivore (adults) 1967 Bryophaenocl Jones et al. Not Diptera Chironomidae adius undet NA NA 1.50 T 2003c Established Yes Detritivore Delette 2000 Greenslade Greenslade Diptera Chironomidae Telmatogeton macquariensis 4.5-5 4.75 5.00 I 2006 Established No Herbivore 2006 for 'Psychoda' Duckhouse Diptera Psychodidae Psychoda surcoufi 1.39-2.657 1.99 2.66 I 17 sp. Established Yes Detritivore 1985 Not Duckhouse Diptera Psychodidae Psychoda alternata 1.39-2.657 1.99 2.66 T 17 for 'Psychoda' Established Yes Detritivore 1985 Not Duckhouse Diptera Psychodidae Psychoda pencillata 1.39-2.657 1.99 2.66 T 17 for 'Psychoda' Established Yes Detritivore 1985 parthenogeneti Duckhouse Diptera Psychodidae Psychoda ca 1.39-2.657 1.99 2.66 I 17 for 'Psychoda' Established Yes Detritivore 1985 Watson 1967, Colless & Greenslade McAlpine Diptera Sciaridae Lycoriella ingenua 1.7-2.2 1.95 2.20 E 2006 Established Yes Detritivore 1970 Greenslade, 2006, Bickel Detritivore(lar and Dyte Thinophilus Greenslade Detritivore/Pre vae)/Predator 1989, Waston Diptera Dolichopidae pedestris pedestris 2-3 2.5 3 I 2006 Established No dator (adults) 1967 Greenslade 2006, Greenslade McQuillan and Diptera Coelopidae Coelopella curvipes 3.1-7 5.05 7.00 I 2006 Established Yes Detritivore Marker 1984 Greenslade 2006, Greenslade McQuillan and Diptera Coelopidae Icaridion nigrifrons 4.5-7 5.75 7.00 I 2006 Established Yes Detritivore Marker 1984 Greenslade Greenslade Australimyzid 2006, Watson Herbivore/Det Microepiphyte 2006, Watson Diptera ae Australimyza macquariensis 2-2.5 2.25 2.50 I 1967 Established Yes ritivore s 1967 Greenslade Greenslade Diptera Ephydrididae Ephydrella macquariensis 3.4-5 4.20 5.00 I 2006 Established Yes Detritivore 2006 Greenslade 2006, Watson 'Live in dung Diptera Tethinidae Apetaenus watsoni 2.5-3 2.75 3.00 I 1967 Established No Detritivore and mud' Watson 1967 Colless & for Not McAlpine Diptera Chloropidae Thyridula nr. centralis 1.5-5 3.25 5.00 T Sabrosky 1989 chloropidae' Established Yes Herbivore 1970 Not Diptera Chloropidae Tricimba undet 2-2.2 2.00 2.20 T 7 Established Yes Detritivore Nartshuk 2014 ipsilon Not Greenslade Lepidoptera Noctuidae Agrostis aneituma 17-21.5 20.00 21.50 T 27 Established Yes Herbivore 2006 Not Greenslade Lepidoptera Noctuidae Dasypodia selenophora 26-31.5 29.65 31.50 T 23 Established Yes Herbivore 2006

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Not Greenslade Lepidoptera Noctuidae Persentania ewingii 7.6 - 23 17.58 23.00 T 19 Established Yes Herbivore 2006 Herbivore/Nec Greenslade Not tarivore 2006, Lepidoptera Nymphylidae Vanessa kershawi 9-17 14.30 17.00 T 13 Established Yes Herbivore (larvae, adults) Common 1970 Not Greenslade Lepidoptera Plutellidae Plutella xylostella 4.9-7 6.10 7.00 T 16 Established Yes Herbivore 2006 Greenslade Lepidoptera Pyralidae Eudonia mawsonii 9-11 10.30 11.00 I 10 Established Yes Herbivore 2006 Not Grainivore/He Lepidoptera Pyralidae Ephestia undet 6-10 8.25 10.00 T 18 Established Yes rbivore Common 1970 Grainivore/He Lepidoptera Pyralidae Plodia interpunctella 5-9 7 9 E 20 Established Yes rbivore Common 1970 Greenslade Parisatoid/Her Greenslade Hymenoptera Diapriidae Antarctopria latigaster 1.5-3.3 2.40 3.30 I 2006 Established No Parasite bivore 2006 Martinez 2007, Daley Not 2007, Riek et Hymenoptera Vespidae Vespula germanica 10.5-16 13.00 16.00 T 8 Established Yes Omnivore al. 1970 Greenslade Greenslade et Amphipoda Taltridae Puhuruhuru undet 8-9 8.5 9 E 2006 Established No Detritivore al. 2008 Greenslade Greenslade et Isopoda Janiridae Styloniscus otakensis 3-5.5 4.25 5.50 E 2006 Established No Detritivore al. 2008 Greenslade Araneae Desidae Myro kerguelensis 2.8 - 5.6 4.20 5.60 I 2006 Established No Predator Forster 1970 Greenslade Araneae Lynphiidae Haplinis mundenia 1.986-5.346 3.82 5.35 I 20 Established No Predator 2006 Greenslade Greenslade Araneae Lynphiidae Parrafroneta marrineri 5.3-6.5 5.90 6.50 I 2006 Established No Predator 2006 Líznarová et al. 2015, Not Garcia et al.

Araneae Oecobiidae Oecobius navus 0.88-3.17 1.90 3.17 T 7 for 'Oecobius' Established No Predator for genus 2014 Hawkeswood Not

Araneae Sparassidae Delena cancerides 20-25 22.50 25.00 T (2003) Established No Predator Hawkeswood Greenslade 2006, Hopkin Rusek 1998, Collembola Friesea tilbrooki NA NA 2.00 I 1997 Established No Predator Hopkin 1997 Greenslade 2006, Deharveng 1981, Hopkin Rusek 1998, Collembola Neanuridae Friesea bispinosa 0.6-1 0.80 1.00 I 1997 Established No Predator Hopkin 1997 Greenslade Euedaphic Collembola Tullbergiidae Tullbergia bisetosa NA NA 1.50 I 2006 Established No Detritivore family' Rusek 1998 Wise 1970, Deharveng Euedaphic Collembola Tullbergiidae Tullbergia templei 0.8-1.5 1.15 1.50 I 1981 Established No Detritivore family' Rusek 1998 Rusek 1998, Not Herbivore/Det Detritivore/Al Greenslade Collembola Onychiuridae Mesaphorura macrochaetae 0.6-0.7 0.65 0.70 T Fjellberg 1998 Established No ritivore givore 2006 Chahartaghi et al. 2005, Greenslade Greenslade Collembola Onychiuridae Protophorura fimata NA NA 1.00 E 2006 Established No Herbivore 2006 Greenslade Collembola Isotomidae Archisotoma brucei NA NA 1.00 I 2006 Established No Detritivore for genus Christian 1989 Greenslade Collembola Isotomidae Archisotoma undet NA NA 1.00 I 2006 Established No Detritivore for genus Christian 1989 Family abundant in litter, soils, Greenslade decaying Collembola Isotomidae Parisotoma insularis 0.786-1.25 0.94 1.25 I 7 2006 Established No Detritivore materials' Potapov 2001 Family Deharveng abundant in Collembola Isotomidae Folsomotoma punctata 0.8-1.2 1.00 1.20 I 1981 Established No Detritivore litter, soils, Potapov 2001

244

decaying materials'

Chahartaghi et Collembola Isotomidae Parisotoma notabilis NA NA 1.00 E Potapov 2001 Established No Detritivore al. 2005

Collembola Isotomidae palustris 2-3.4 2.60 3.40 E Potapov 2001 Established No Herbivore Algivore Rusek 1998 Family abundant in litter, soils, Greenslade & decaying Collembola Isotomidae Arizotoma macquariensis 0.48–1 0.74 1.00 I Potapov 2008 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, Deharveng decaying Collembola Isotomidae Cryptopygus antarcticus 1-2 1.50 2.00 I 1981 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, Deharveng decaying Collembola Isotomidae Cryptopygus tricuspis 0.8-1.3 1.05 1.30 I 1981 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, Greenslade decaying Collembola Isotomidae Cryptopygus lawrencei NA NA 0.70 I 2006 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, decaying Collembola Isotomidae Mucrosomia ceaca 1.3-1.9 1.60 1.90 I Potapov 2001 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, Deharveng decaying Collembola Isotomidae Cryptopygus dubius 0.9-1.2 1.05 1.20 I 1981 Established No Detritivore materials' Potapov 2001 Family abundant in litter, soils, Greenslade decaying Collembola Isotomidae turbotti NA NA 1.50 E 2006 Established No Detritivore materials' Potapov 2001 Compost- Greenslade dwelling, Collembola Isotomidae 0.466-1.155 0.79 1.16 E 2006 Established No Detritivore ruderal Potapov 2001 Entomobryida Greenslade for'epedaphic Collembola e Lepidobrya mawsonii 0.87-2.28 1.36 2.28 I 10 2006 Established No Omnivore springtails' Hopkin 1997 for'epedaphic Collembola Katiannidae Polykatianna davidii 0.6-1.3 0.93 1.30 I 23 Established No Omnivore springtails' Hopkin 1997 Greenslade and Ireson for'epedaphic

Collembola Katiannidae mime 0.525-0.95 0.82 0.95 I 17 1986 Established No Omnivore springtails' Hopkin 1997 Greenslade cf. and Ireson for'epedaphic

Collembola Katiannidae Sminthurinus tuberculatus 0.6-1 0.80 1.00 I 21 1986 Established No Omnivore springtails' Hopkin 1997 Greenslade for'epedaphic Collembola Katiannidae Sminthurinus nr. granulosus NA NA 0.65 I 2006 Established No Omnivore springtails' Hopkin 1997 Greenslade 2006, Greenslade Not Herbivore/Det Chahartaghi et Collembola Katiannidae Sminthurides cf malmgreni 0.3-0.6 0.45 0.60 T 2006 Established No ritivore Microbivore al. 2005 Frans Janssens (Global Collembola): https://buggui de.net/node/vi ew/102983/bgi quadrimaculat mage accessed Not for'epedaphic

Collembola Katiannidae Sminthurinus us NA NA 1.20 T 22/1/19 Established No Omnivore springtails' Hopkin 1997 Greenslade for'epedaphic Collembola Katiannidae Katianna banzarei 0.83-1.275 1.05 1.28 I 20 and Wise 1986 Established No Omnivore springtails' Hopkin 1997

245

Fjellberg 1998 (2), Schneider for'euedaphic Collembola Neelidae Megalothorax nr. minimus 0.25-0.5 0.38 0.40 I et al. 2016 Established No Detritivore springtails' Hopkin 1997 Greenslade et al. 2014, Hypogastrurid Fjellberg 1998 Detritivore/Pre Chernova et Collembola ae Hypograstrura viatica 1.344-2.258 1.75 2.26 E (1) Established No dator al. 2007 Fjellberg 1998 (1), Hypogastrurid Greenslade et Greenslade et Collembola ae Hypogastrura purpurescens NA NA 2.00 E al. 2014 Established No Detritivore al. 2014 Greenslade et al. 2014, Hypogastrurid Fjellberg 1998 Detritivore/Pre Chernova et Collembola ae Ceratophysella denticulata 1 - 1.73 1.31 1.73 E 22 (1) Established No dator al. 2007 Chernova et al. 2007, Potapov 2001 Detritivore/Pre (detritous Collembola Isotomidae tigrina NA NA 2.10 E Potapov 2001 Established No dator living) Entomobryida Fjellberg 1998 Chahartaghi et Collembola e Lepidocyrtus violaceus 1.2-1.7 1.45 1.70 E 17 (2) Established No Detritivore al. 2005 Minimum measure made in this work, CSIRO max =CSIRO Australia Australia http://www.ent http://www.ent o.csiro.au/edu o.csiro.au/edu cation/insects/t cation/insects/t hysanura.html hysanura.html accessed accessed Zygenotoma Ctenolepisma undet 11.9-20 16 20 E 1 21/1/19 21/1/19 Established No Omnivore Generalist Lindsay 1940 Not Sunderland Dermaptera Forifculidae Forficula auricularia 0.7-1.85 13.20 13.20 T 11 Established No Omnivore 1975 for Womersley 'Eugamasus' Greenslade Acarina Eugamasus 1 undet NA NA 0.93 E 1956 genus Established No Predator 2006 for Womersley 'Eugamasus' Greenslade Acarina Parasitidae Eugamasus 2 undet NA NA 0.93 E 1956 genus Established No Predator 2006 for Womersley 'Eugamasus' Greenslade Acarina Parasitidae Eugamasus 3 undet NA NA 0.93 E 1956 genus Established No Predator 2006 for Womersley 'Eugamasus' Greenslade Acarina Parasitidae Eugamasus 4 undet NA NA 0.93 E 1956 genus Established No Predator 2006 for Womersley 'Eugamasus' Greenslade Acarina Parasitidae Eugamasus 5 undet NA NA 0.93 E 1956 genus Established No Predator 2006 for 'Pergamasus' Greenslade Acarina Parasitidae Pergamasus 1 undet NA NA 1.00 E Bowman 1987 genus Established No Predator 2006 for 'Pergamasus' Greenslade Acarina Parasitidae Pergamasus 2 undet NA NA 1.00 E Bowman 1987 genus Established No Predator 2006 for Digamasellida Womersley 'Digamasellus' Greenslade Acarina e Digamasellus schusteri NA NA 0.78 I 1960 genus Established No Predator 2006 for Digamasellida Womersley 'Digamasellus' Greenslade Acarina e Digamasellus watsoni NA NA 0.78 I 1960 genus Established No Predator 2006

Greenslade Acarina Laelapidae Androlaelaps pachyptilae NA NA 0.65 I Watson 1967 average Established No Predator 2006

246

Greenslade Acarina Laelapidae Ayersacarus gelidus 1.101-1.121 1.11 1.12 I Watson 1967 Established No Predator 2006

Greenslade Acarina Laelapidae Ayersacarus plumapilpus 0.962-1.128 1.05 1.13 E Watson 1967 Established No Predator 2006

Greenslade Acarina Laelapidae Ayersacarus strandtmanni 0.88-1.031 0.96 1.03 I Watson 1967 Established No Predator 2006

Haemogamasi Haemogamasu Haemogamasu Predator/Ectop Greenslade

Acarina dae s s pontiger 0.681-0.856 0.77 0.86 I Watson 1967 Established No Parasite arasite 2006

Leptolaelapida Greenslade

Acarina e Stevacarus evansi NA NA 1.07 I Watson 1967 Established No Predator 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes anatarcticus NA NA 0.24 I Proctor 1999 genus Established No Herbivore Algivore 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes bellus NA NA 0.25 I Proctor 1999 genus Established No Herbivore Algivore 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes macquariensis NA NA 0.25 I Proctor 1999 genus Established No Herbivore Algivore 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes marianae NA NA 0.25 I Proctor 1999 genus Established No Herbivore Algivore 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes rounsevelli NA NA 0.25 I Proctor 1999 genus Established No Herbivore Algivore 2006 for Nanorchestida Walter & 'Nanorchestes' Greenslade Acarina e Nanorchestes watsoni NA NA 0.25 I Proctor 1999 genus Established No Herbivore Algivore 2006 Greenslade Acarina Rhagidiidae Rhagidia macquariensis NA NA 1.00 I Watson 1967 Established No Predator 2006 Greenslade Acarina Ereynetidae Ereynetes macquariensis 0.25-0.345 0.30 0.35 E Watson 1967 Established No Predator 2006 Greenslade Acarina Ereynetidae Ereynetoides watsoni NA NA 0.30 I Watson 1967 Established No Predator 2006 Greenslade 2006, Walter Acarina Bdellidae macquariensis NA NA 1.50 I Watson 1967 Established No Predator et al. 1999 Greenslade 2006, Walter Acarina Bdellidae Bdellodes watsoni NA NA 1.12 I Watson 1967 Established No Predator et al. 1999 Greenslade Acarina Cheyletidae Cheyletus eruditus NA NA 0.71 I Watson 1967 Established No Predator 2006 Archeonothrid Greenslade Acarina ae Stomacarus watsoni 0.415-0.45 0.43 0.45 E Watson 1967 Established No Detritivore 2006 Greenslade Acarina Crotoniidae Holonothrus foliatus NA NA 0.76 I Watson 1967 Established No Fungivore 2006 Macquarioppi Greenslade Acarina Metrioppiidae a striata NA NA 0.65 I Watson 1967 Established No Detritivore 2006 Austroppia Microphytoph Greenslade Acarina Oppiidae crozetensis crozetensis 0.612-0.6476 0.63 0.65 I Watson 1967 Established No Herbivore agous 2006 Austroppia Microphytoph Greenslade Acarina Oppiidae crozetensis anareensis NA NA 0.31 I Watson 1967 average Established No Herbivore agous 2006 Ameronothrid antarcticus Greenslade Acarina ae Alaskozetes grandjeani 0.9949-1.0287 1.01 1.03 I Watson 1967 Established No Detritivore 2006

247

Ameronothrid belgicae Greenslade Acarina ae Halozetes belgicae 0.5236-0.5554 0.54 0.56 I Watson 1967 Established No Detritivore 2006 Ameronothrid Greenslade Acarina ae Halozetes intermedius 0.6711-0.7245 0.82 0.72 I Watson 1967 Established No Detritivore 2006 Ameronothrid Greenslade Acarina ae Halozetes macquariensis NA NA 0.832.3 I Watson 1967 Established No Detritivore 2006 Ameronothrid Greenslade Acarina ae Halozetes marinus 0.7918-0.8401 0.82 0.84 I Watson 1967 Established No Detritivore 2006 Greenslade Acarina Protoribatidae Totobates anareensis NA NA 0.36 I Watson 1967 average Established No Detritivore 2006 Greenslade Acarina Mycobatidae Cryptobothria monodactyla NA NA 0.37 I Watson 1967 average Established No Detritivore 2006 Parakalummat Greenslade Acarina idae Neomycobates tridentatus NA NA 0.44 I Watson 1967 average Established No Detritivore 2006 Greenslade Acarina Acarus siro 0.32-0.65 0.49 0.65 E Watson 1967 Established No Fungivore 2006 Greenslade Acarina Acaridae Tyrophagus longior NA NA 0.61 E Watson 1967 Established No Fungivore 2006 Glycyphagida Greenslade Acarina e Glycyphagus domesticus 0.32-0.75 0.54 0.75 E Watson 1967 Established No Fungivore 2006 Greenslade Acarina Acaridae Schwiebia talpa 0.266-0.32 0.29 0.32 E Watson 1967 Established No Fungivore 2006 Greenslade Acarina Listrophoridae Listrophorous gibbus NA NA 0.56 E Watson 1967 Established No Parasite Ectoparasite 2006

248