Loggerhead and Green Turtles of the South West Pacific: Investigating Foraging Ecology and Migration Using Integrated Analytical Methods

Home , Goenpul, North West Island, Portunidae

Loggerhead and green turtles of the south west Pacific: Investigating foraging ecology and migration using integrated analytical methods

Owen Ieuan Coffee BSc (Hons) Marine Biology

0000-0002-2929-8803

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

Abstract

This study sought to refine the feeding behaviours and foraging regions of resident loggerhead and green turtle populations in Queensland, Australia, using a combination of diet investigatory techniques, satellite telemetry and stable isotope analysis. Discoveries consequent to the development and application of new analytical techniques, highlights the need to re-evaluate longstanding assumptions about marine turtle foraging ecology. The study of marine turtles has historically been limited by the challenges of investigating animals in the marine environment. Due to the complex developmental history of marine turtles, which follow distinct life stages, generally research has focused on sampling at reproductive events where large numbers of female turtles are readily accessible. Consequently, using capture- mark-recapture methods, the approximate migratory range of a sampled nesting population could be established. However, the proportion of the nesting population originating from distinct foraging regions has not yet been resolved. The incorporation of satellite telemetry and stable isotope analysis (SIA) have the potential to document the ecology of marine turtle populations more precisely than was previously possible. The use of these methods in tandem with more traditional foraging ecology tools (e.g. gut content analysis, oesophageal lavage or faecal sampling), provides important information on foraging locations and the food sources that can be used to develop conservation strategies at a local through to a national scale for marine turtles.

Studies conducted in the north-west Atlantic have successfully defined the foraging regions of nesting loggerhead turtles based on differences in the stable isotope ratios δ13C and δ15N from sampled blood and skin tissues. However, despite long-term turtle monitoring programs identifying nesting and foraging populations of green and loggerhead turtles throughout Queensland, the question of how distinct foraging regions contribute to nesting populations has yet to be resolved. In addition, foraging ecology studies of marine turtles using SIA have discovered that within a species, individuals can have very different foraging strategies. This finding contrasts with traditional views that most marine turtle species, once they grow to the size of juveniles, recruit to the near-shore environment and adopt the same benthic feeding strategy. Hence, this study aimed to use SIA methodology on the east Australian populations

i of loggerhead and green turtles to discover more information on their feeding regions and foraging ecology.

Loggerhead and green turtles are found throughout coastal waters, bays and reef structures along the tropical and sub-tropical eastern coast of Australia. Investigating the variation in the foraging ecology of these species will provide information for the development of local management strategies targeting the long-term conservation of marine turtles in Australian waters.

The aim of this thesis was to incorporate SIA and telemetry data with the analysis of faecal and oesophageal samples to:

1) determine habitat use and dietary composition of loggerhead and green turtle foraging populations of south east Queensland;

2) ascertain if δ13C and δ15N stable isotope values from foraging turtles could be used to differentiate local or regional foraging habitats; and

3) identify the foraging regions of green and loggerhead turtles nesting at major nesting sites in Queensland waters.

Following the success of studies that used SIA to define foraging regions on nesting loggerheads in the north-west Atlantic, SIA was used to investigate if the foraging regions of Australian nesting loggerhead and green turtles could be identified from epidermis or blood samples. The isotopic values of nesting loggerhead turtles from Mon Repos, central Queensland were sampled and compared to a cohort of nesting individuals with known foraging locations and a subset of foraging loggerheads from a known foraging region. Unlike comparable studies from the north-west Atlantic, the isotopic values of sampled nesting turtles from the east coast of Australia did not group into potential foraging regions and no correlation was observed between latitude and the isotopic values of sampled turtle tissues. Consequently, foraging grounds of nesting females could not be inferred using SIA of δ13C and δ15N values from epidermis or blood samples. It was hypothesised that the absence of the expected unique δ13C and δ15N values associated with foraging regions was related to the unique oceanic currents along the east coast of Australia and the influence of the Great Barrier Reef and coastal outflows on sea surface temperature and water residence times.

Green turtles were sampled at two geographically and genetically distinct rookeries, Raine Island in the northern Great Barrier Reef (GBR) region and Heron Island in the southern GBR region. It was expected most individuals from these distinct rookeries would have latitudinally separated foraging grounds. Consequently, a hierarchical cluster analyses was used to determine if nesting individuals from these two rookeries could be differentiated by their tissue isotopic values. Nesting individuals from these geographically distant rookeries could not be distinguished based on δ13C and δ15N values from sampled bodily tissue. Consistent with this finding, there was no correlation between δ13C or δ15N and latitude in a cohort of 40 green turtles tracked via satellite telemetry from their Raine Island nesting beach to their foraging grounds. Hence, as with the east Australian population of loggerhead turtles, the foraging grounds of nesting green turtles could not be determined from SIA of sampled epidermis. It was theorised that the absence of identifiable clusters in δ13C and δ15N values for individuals from the same foraging grounds was related the lack of a prevailing oceanic current through the potential foraging regions. In addition, factors such as the influence of oceanic temperate and coastal outflow, which may confound the development of unique isotopic gradients or isoregions, were also attributed to the inability to resolve the foraging regions of the sampled cohort.

An analysis of faecal material from loggerhead turtles foraging in Moreton Bay, southeast Queensland indicated a diet composed predominantly of benthic crustaceans, bivalves and gastropods, consistent with previous observations. However, SIA of blood and epidermis discovered large variations between sampled individuals suggesting that, either the loggerhead diet included a wider range of animals than the faecal sampling method provided, or that the dietary items themselves had highly variable δ13C and δ15N values such that they could not provide an consistent baseline to infer the diets or feeding areas of sampled turtles.

The diets of foraging green turtles in Port Curtis, central Queensland were explored using oesophageal lavage and SIA of blood and epidermis to investigate trends in diet composition from different foraging habitats within this region. While oesophageal lavage samples indicated diets were consistent with the food items available within their foraging habitat, a MixSIAR hierarchical Bayesian mixing model, using δ13C and δ15N isotopic values, identified food items which were under-represented in lavage sampling that had a greater contribution to dietary composition. In addition, animal material appeared to make a significant contribution to the diets small (< 55 cm CCL) green turtles at this location. Elevated δ15N,

iii relative to the values observed in primary producers, in turtles < 55 cm in curved carapace length (CCL), suggested that these turtles continue to forage on macrozooplankton after recruitment to neritic foraging grounds. An elevated δ15N was also observed in individuals > 90 cm CCL, a finding consistent with the increasing reports of omnivory in adult green turtles. Green turtles of distinct sizes were associated with different habitat types, indicating that individuals potentially exhibit ‘developmental migration’ to different foraging grounds within Port Curtis as they grow. Small turtles (< 55 cm CCL) were mostly associated with shallow rocky reef and mangrove habitats, whilst medium (> 55 cm CCL) and large (> 90 cm CCL) turtles were commonly found throughout the subtidal sandbanks. A comparison of epidermis and plasma δ13C values indicated ~ 40 % of turtles may have changed their diet to/from seagrass in the period between the synthesis of their plasma and epidermis tissues, a finding consistent with previous observations from this foraging region.

Importantly, and contrary to findings from studies conducted on loggerhead turtles in the north-west Atlantic, SIA could not be used to confidently identify the foraging region of either loggerhead or green turtle individuals from the east coast of Australia. The reasons why this method failed to identify foraging regions along the east coast of Australia were (1) the large variation in SI values in individuals sampled in the same foraging regions, and (2) the lack of identifiable unique iso-regions or latitudinal gradients in δ13C and δ15N values along the east coast. While this study found the use of carbon and nitrogen stable isotope values in turtle tissue could not be used to identify their foraging region, the incorporation of different isotopic tracers, such as δ 18O or δ 34S which are less influenced by dietary composition, may better reflect regional differences in habitats and improve the ability to identify the foraging region of marine turtles nesting along the east coast of Australia.

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.

Publications included in this thesis

The following publication has been incorporated as Chapter 2. 1. Coffee, O.I., Booth, D.T., Thia, J.A. and Limpus, C.J. (2020). When isotopes fail: the importance of satellite telemetry and multi-site validation when estimating the foraging grounds of migratory species, Mar Ecol Prog Ser.

Submitted manuscripts included in this thesis

No publications included

Other publications during candidature

Peer-reviewed papers

1. Coffee, O.I., Booth, D.T., Thia, J.A. and Limpus, C.J. (2020). When isotopes fail: the importance of satellite telemetry and multi-site validation when estimating the foraging grounds of migratory species, Mar Ecol Prog Ser.

Conference abstracts

1. Coffee, O.I., Limpus, C.J.L., Booth, D. (2018) Insights from stable isotope analysis of a southern and northern Great Barrier Reef green turtle rookery. Proc. 4th Australian Marine Turtle Symposium 2. Coffee, O.I., Limpus, C.J.L., Booth, D. (2018) Inferring the geographic location of foraging grounds from nesting loggerhead turtles in central Queensland, SW Pacific. Proc. 38th International Sea Turtle Symposium 3. Coffee, O.I., Limpus, C.J.L., Thomas, H., Booth, D. (2017) Variation in dietary composition across foraging habitats of green turtles in central Queensland. Proc. 90th Australian Coral Reef Symposium

Book Chapters

The following book chapter, written during candidature but not incorporated in this thesis has been included in the appendices. 1. Limpus, C.J., Coffee, O.I., (2019) Marine turtles in Moreton bay. In: Tibbetts IR, Rothlisberg PC, Neil DT, Homburg TA, Drewer DT, Arthington AH (eds) Moreton Bay Quandamooka & Catchment: Past, present, and future. The Moreton Bay Foundation, Brisbane, Australia, 401-414

Contributions by others to the thesis

Supervisors:

Dr David Booth, the University of Queensland, made significant contributions to the concept, design and draft/proofing of all chapters of this thesis.

Dr Col Limpus, Queensland Government, Department of Environment and Science, provided supervision and guidance and made significant contributions to the design and technical work associated with all data chapters in this thesis.

Dr Janet Lanyon, the University of Queensland, provided supervision and guidance in the design of analyses for chapters 4 and 5, and contributions to the drafting of Chapters 1, 4 and

5 of the thesis.

A/Prof. Neil Coffee and Jane Coffee made significant contributions to the drafting of all chapters in this thesis.

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 Animal Subjects

Capture and handling of turtles followed the procedures approved by the Queensland Department of Environment and Science (Scientific Purposes Permits: WISP15829615 & WITK15830215 and Marine Parks Permit: QS2015/CVL/MAN298) and the University of Queensland Animal Ethics Committee (Approval no: SBS/017/15/SRRF/URG).

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Acknowledgements

I acknowledge the traditional owners of the lands on which this field research was conducted in the Queensland: The Quandamooka people (Nunukul, the Goenpul and the Ngugi) of the Moreton Bay region; The Bailai, Gooreng Gooreng, Gurang and Taribelang Bunda people of the Bundaberg/Gladstone region; and the Wuthathi and Kemerkemer Meriam Nation people. The Raine Island Recovery Project is a five-year, $7.95 million collaboration between BHP, the Queensland Government, the Great Barrier Reef Marine Park Authority, Wuthathi and Kemerkemer Meriam Nation (Ugar, Mer, Erub) Traditional Owners and the Great Barrier Reef Foundation to protect and restore the island’s critical habitat to ensure the future of key marine species. The Wuthathi People and Kemerkemer Meriam Nation (Ugar, Mer, Erub) People are the Traditional Owners and Native Title holders of Raine Island and are an integral partner in the area’s management. Over thousands of years, Wuthathi People and Kemerkemer Meriam Nation People have held cultural connections to Raine Island using its resources and established cultural connections to the land and sea.

I would like to thank the incredible support and input of my supervisors’ Drs David Booth, Col Limpus and Janet Lanyon. David, you welcomed me, from interstate, to study in an area entirely unfamiliar, on a species I had not worked with before which has now become more than an interest but a passion. You have been constantly available to bounce ideas off and offer guidance and without your subtle encouragements to get a move on I would likely still be writing this. Thank you for the opportunities you provided to broaden my experiences and the incredible adventures I have been on under your tutelage. Col (aka Papa Turtle), your wisdom and the experience of working in your shadow in the field has been invaluable. Your stories of the ‘good old days’ of research have been a constant source of amusement and education and your youthful enthusiasm for turtle research have inspired a passion to continue in this field. Janet, your door has always been open, and your guidance and feedback have been instrumental in the development of my research and writing skills. Thank you for all your help.

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Support for collection of tissue samples from the Raine Island turtle rookery was provided by the Raine Island Recovery Project, whilst satellite telemetry data from nesting individuals of Raine Island was kindly donated by their collaborative partner, James Cook University and researchers A/Prof Mark Hamman and Dr Takahiro Shimada of the green turtle telemetry project. Tissue samples from nesting green turtles on the Raine Island turtle rookery were collected on behalf of the Department of Environment and Science Aquatic Threatened Species Unit and donated for analysis by chief scientist Dr Col Limpus.

Thanks to the Queensland Government Department of Environment and Science Aquatic Threatened Species Program and the Gidarjil Land and Sea Rangers for logistical support for works conducted in Gladstone and Mon Repos. Thanks are also given to the volunteers, field assistants and colleagues and friends who assisted in sampling at the foraging grounds and rookeries of this study including H. Barrios-Garrido, S. Chaousis, S. Doell, E. Dover, M. Ellis, K. Finlayson, M. Hamann, K. Jones, J. Sergeev, N. FitzSimmons, T. Shimada, J. Smith, D. Limpus, J. Limpus and R. Pearson for their assistance in sample collection and preparation for analysis. Special thanks to E. Duncan, C. Smith and H. Thomas for their assistance in the analysis of lavage and faecal samples and the preparation of tissue samples for isotopic analyses. I thank K. Baublys and W. Zhou of the Stable Isotope Geochemistry Laboratory, Earth and Environmental Sciences at The University of Queensland for the Stable Isotope Analysis of tissue and diet samples. Thanks to S. Blomberg and J. Thia for statistical advice. Thanks, are also given to the volunteers, field assistants and colleagues of The University of Queensland, the Heron Island and the Moreton Bay Research Stations for their assistance in turtle housing and sample collection.

Lastly, and most importantly I would like to acknowledge the love and unwavering support of my family Emma, Neil, Jane and Gareth. Thank you for your belief in me, it was your encouragement that got me over the line.

Financial Support This research was supported by an Australian Postgraduate Award (now the Australian Government Research Training Program Scholarship).

Research funding for this work was provided by a Sea World Research and Rescue Foundation grant and the University of Queensland, School of Biological Sciences.

Keywords Marine turtles, Diet, Foraging, Stable Isotope Analysis, Nesting, Migration

Australian and New Zealand Standard Research Classifications (ANZSRC)

060205 - Marine and Estuarine Ecology, 50%

060801 - Animal Behaviour, 50%

Fields of Research (FoR) Classification

0602 – Ecology, 50%

0608 – Zoology, 50%

Thesis structure This thesis consists of six chapters, with four chapters written as stand-alone manuscripts for publication in journals. These chapters are bookended by a general introduction and summary/future studies chapters. Despite attempts made to reduce repetition by editing, some material, in the introductory and methods sections of the four manuscript chapters will be repetitious.

This work is dedicated to Cyril (Taid)

From a young age, you sparked a curiosity in me at the wonder and beauty of the marine environment.

Setting me on this path and the incredible opportunities it has presented.

Table of Contents

Abstract ...... i

Declaration by Author ...... v

Publications included in this thesis ...... vi

Submitted manuscripts included in this thesis ...... vi

Other publications during candidature ...... vi Peer-reviewed papers ...... vi Conference abstracts ...... vi Book Chapters ...... vi

Contributions by others to the thesis ...... vii

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 ...... x

Keywords ...... x

Australian and New Zealand Standard Research Classifications (ANZSRC) ...... x

Fields of Research (FoR) Classification ...... x

Thesis structure ...... x

List of Figures & Tables ...... 1

List of Abbreviations ...... 4

Chapter 1 ...... 6

Introduction ...... 7 1.1 Study Species ...... 8 1.2 Methods of Dietary Studies...... 12 1.3 Dietary Composition and Foraging Behaviour ...... 17 1.4 Aims and Significance ...... 20

Chapter 2 ...... 22

When isoscapes fail: the importance of satellite telemetry and multi-site validation when estimating the foraging grounds of migratory species ...... 23 2.1 Abstract ...... 23 2.2 Introduction ...... 24 2.3 Material and methods ...... 27 2.4 Results ...... 31 2.5 Discussion ...... 33 2.6 Conclusion ...... 37

Chapter 3 ...... 38

Nesting green turtles of the southern and northern Great Barrier Reef: insights from stable isotope analysis ...... 39 3.1 Abstract ...... 39 3.2 Introduction ...... 40 3.3 Materials and methods ...... 42 3.4 Results ...... 48 3.5 Discussion ...... 52 3.6 Conclusion ...... 54

Chapter 4 ...... 55

Diet and stable isotopic composition of loggerhead turtles in a subtropical foraging ground...... 56 4.1 Abstract ...... 56 4.2 Introduction ...... 57 4.3 Materials and Methods ...... 58

4.4 Results ...... 63 4.5 Discussion ...... 68 4.6 Conclusion ...... 71

Chapter 5 ...... 72

Dietary composition and foraging ground use by the green turtle (Chelonia mydas) population in Port Curtis, Gladstone, central Queensland...... 73 5.1 Abstract ...... 73 5.2 Introduction ...... 74 5.3 Methods ...... 77 5.4 Results ...... 85 5.5 Discussion ...... 95 5.6 Conclusion ...... 99

Chapter 6 ...... 101

Summary and directions for future research ...... 102

References ...... 106

Appendix ...... 126

Marine turtles in Moreton Bay ...... 127

Permits ...... 141

List of Figures & Tables

Figure 1.1. Breeding units of the Green turtle (C. mydas) around northern Australia. Units (1),(2) and (3) encompass the breeding populations along the Queensland coastline. (Adapted from Limpus 2009)...... 9

Figure 1.2. Breeding stocks of loggerheads (C. caretta), highlighting separate east (1) and west (2) Australian stocks (Adapted from Limpus 2009)...... 10

Table 2.1 Summary data of average (± s.d.) curved carapace length (CCL) of sampled loggerhead turtles identified by sampling cohort, foraging ground location, sex and maturity. STEA = sub-tropical eastern Australia, sGBR = southern Great Barrier Reef, nGBR = northern Great Barrier Reef...... 27

Figure 2.1. End points of nesting turtle migrations with known foraging grounds based on satellite telemetry or capture-mark-recapture studies, and the three defined foraging regions of the study. The end points of satellite tracked nesting turtles are denoted with filled diamonds...... 29

Figure 2.2. Scatterplot of δ13C and δ15N values in the epidermis for nesting loggerhead turtles sampled at Mon Repos and foraging loggerhead turtles sampled in south east Queensland. ‘Unknown’ points represent nesting turtles sampled with no previously identified foraging area...... 33

Table 3.1. Reference δ13C values for green turtle forage items sampled from neritic Queensland waters...... 44

Figure 3.1. Sampled green turtle rookeries and the foraging grounds of satellite tracked turtles from Raine Is. over consecutive nesting seasons. The sampled rookeries for the southern Great Barrier Reef (sGBR) and northern Great Barrier Reef (nGBR), Heron Is. and Raine Is. respectively, are indicated by green circles. The foraging grounds of turtles from Raine Is. in the north Great Barrier Reef region, Torres Strait region, and Gulf of Carpentaria region are distinguished by symbol...... 46

Figure 3.2 Seasonal δ13C and δ15N isotopic values of epidermis from nesting green turtles of the sGBR (Heron Island) and the nGBR (Raine Island). Symbols denote the sampled season; colours represent clusters identified with hierarchical cluster analyses...... 48

Figure 3.3. δ13C and δ15N isotopic values of epidermis from nesting green turtles of the sGBR (Heron Island) and the nGBR (Raine Island). Symbols denote the sampled breeding stock; colours represent clusters identified with hierarchical cluster analyses...... 49

Table 3.2. The summarised means and isotopic ranges of individuals sampled at Raine Island that have their residential foraging grounds in three different regions...... 50

Figure 3.4. δ13C and δ15N isotopic values of epidermis from nesting green turtles of the nGBR (Raine Island) tracked using satellite telemetry to their foraging grounds. Symbols denote the foraging regions determined by satellite track data; colours represent clusters identified with hierarchical cluster analyses...... 50

Figure 3.5. Mean reference δ13C values of seagrasses sampled from foraging grounds along the eastern Australian coastline. Data from the previous studies listed in Table 3.1...... 51

Figure 4.1. Capture locations of foraging loggerhead turtles sampled for SIA and faecal analysis on the eastern banks of Moreton Bay, Qld. Colours indicate the current boundaries and levels of management covering the foraging areas of loggerheads on the eastern banks of Moreton Bay. Numbered areas identify sectors defined by Queensland Turtle Conservation Project protocol...... 59

Table 4.1. Identified prey items in faeces of sampled loggerheads identified to lowest possible taxa. Dietary composition expressed as the proportion of the total dry weight for each sample...... 65

Figure 4.2. Carbon (δ13C ‰) values from sampled epidermis and blood plasma against a theoretical stable diet line (solid line) and ± 30% boundary (dashed lines) for foraging loggerhead turtles in Moreton Bay ...... 67

Figure 4.3. δ13C and δ15N values of plasma from sampled foraging loggerheads in Moreton Bay. Colours delineate k-means clusters identified by hierarchical analysis whilst characters identify the predominant dietary items from faecal sampling. ‘Unknown’ represents the tissue δ13C and δ15N values of foraging individuals that were not sampled for faecal content...... 68

Figure 5.1. Sampled areas within Port Curtis, Central Queensland. Coloured according to habitat; Sandbanks (Green), Estuary (Red), Mangrove (Blue) and Rocky Reef (Purple)...... 78

Table 5.1. Sampled periods and total individuals from each sampling site/habitat within the Port Curtis region of Central Queensland...... 79

Table 5.2. Reference δ13C and δ15N values of potential food items sampled from Central Queensland, categorised by groups determined through oesophageal lavage. These were further grouped based on their mean δ13C and δ15N values and the frequency of occurrence in lavage sampling, into three categories for Bayesian analyses: Mangrove and Rhodophyta (MRh), Seagrass (SG) and animal material (An)...... 81

Table 5.3. Identified species within the seven food items categories observed in the oesophageal lavage samples for foraging green turtles (n=) at each habitat type from Port Curtis, Queensland. The frequency of occurrence (%FO) and mean volume (±SD) were calculated from each species from samples in one of four habitat types; sandbanks (SB), subtidal flats (SF), rocky reef (RR) and mangroves (M)...... 87

Table 5.4. Summary of dietary composition of sampled green turtles according to oesophageal lavage samples. Food items were pooled according to phyla. The total no of species for each food item are summarised for each of the sampled habitats. Frequency of occurrence (%FO) and mean volume were used to calculate and index of relative importance (IRI %) of each food item group for the sampled habitats...... 88

Figure 5.2. Distribution of turtle size (CCL) by foraging habitat. Plots detail the median value within the inter-quartile range (IQR), external points denote outliers from the distribution. .. 89

* identifies significant difference in CCL of the sampled habitat ...... 89

Figure 5.3. Distribution of Carbon (a) and Nitrogen (b) stable isotope values in turtle plasma by foraging habitat. Plots detail the median value within the inter-quartile range (IQR), external points denote outliers from the distribution...... 90

* identifies significant difference in δ13C and δ15N values for individuals from different sampled habitats...... 90

Figure 5.4. Carbon (δ13C ‰) values from sampled epidermis and blood plasma against a theoretical stable diet line (solid line) and ± 30% boundary (dashed lines)...... 91

Figure 5.5. Carbon (δ13C ‰) and Nitrogen (δ15N ‰) values of sampled plasma against the mean reference values from potential food groups (±SD) (Table 5.2.)...... 92

Figure 5.6. Modelled proportions of the food groups contributing to diets in each habitat. Food groups are defined by mean isotopic values of reference food items; Animal, Mangrove/Rhodophyta, Chlorophyta/Ochrophyta and Seagrass...... 94

List of Abbreviations

ANOVA Analysis of Variance CCL Curved Carapace Length CMR Capture-Mark-Recapture DFA Discriminant Functions Analysis EAC East Australian Current EPBC Environment Protection and Biodiversity Conservation FO Frequency of Occurrence GBR Great Barrier Reef nGBR Northern Great Barrier Reef sGBR Southern Great Barrier Reef GoC Gulf of Carpentaria GoM Gulf of Mexico IRI Index of Relative Importance IUCN International Union for Conservation of Nature MCMC Markov Chain Monte Carlo MRh Mangrove/Rhodophyta CO Chlorophyta/Ochrophyta RBC Red Blood Cell RR Rocky Reef SB Sandbank SF Subtidal Flats SG Seagrass SI Stable Isotope SIA Stable Isotope Analysis STEA Sub-tropical Eastern Australia TS Torres Strait VPDB Vienna Pee Dee Belemnite

Chapter 1

Contributor Statement of Contribution Author: Owen I. Coffee (Candidate) Conception and design (100%) Analysis and interpretation (100%) Production (100%)

Introduction

Marine turtles occupy some of the most diverse habitats in the world, inhabiting both neritic and oceanic niches throughout temperate to tropical regions (Bjorndal & Jackson 2002). Once occupying the world’s oceans in massive numbers, widespread anthropogenic exploitation of resident turtle populations and destruction of habitat has drastically reduced numbers, with all but one of the seven remaining turtle species listed in the IUCN Red list of Threatened Species as either Vulnerable, Endangered or Critically Endangered (Seminoff 2004, Abreu-Grobois & Plotkin 2008, Mortimer & Donnelly 2008, Wallace et al. 2013, Casale & Tucker 2017, Wibbels & Bevan 2019). Six of the seven extant species of marine turtles have resident populations in the waters around northern Australia, with Queensland hosting significant nesting aggregations of the south-west Pacific populations of loggerhead (Caretta caretta) and Great Barrier Reef populations of green (Chelonia mydas) turtles (Limpus & Limpus 2003b, Limpus 2009).

In addition to their global Vulnerable status, on a regional scale, loggerhead populations of the south Pacific sub-population are currently listed as Critically Endangered (Limpus & Casale 2017) whilst green turtles, listed globally as Endangered in the IUCN Red list (Seminoff 2004), are considered Vulnerable regionally, by the EPBC Act of Threatened Species (2009). Loggerhead and green turtles perform important roles in the shaping of their ecosystems, serving as primary consumers, predators, prey, competitors and/or hosts (Bjorndal & Jackson 2002, Bjorndal 2003, Burkholder et al. 2011). Nesting populations of green turtles in Queensland appear to have stabilised over the last four decades, with observed increases in some nesting populations, yet despite conservation efforts, populations of loggerheads are in decline (Limpus 2009). Both green and loggerhead species remain vulnerable to increased mortality at all life stages from anthropogenic disturbances. Consequently, there remains a need to maintain and develop conservation measures to reverse population declines.

1.1 Study Species

1.1.1 Chelonia mydas The green turtle, Chelonia mydas, has one of the widest distributions of any marine turtle, with populations found worldwide in tropical and sub-tropical regions (Seminoff et al. 2015). Within Australia, green turtles’ nest from south-east Queensland up along the Great Barrier Reef (GBR), across northern Australia to Ningaloo Reef on the coast of Western Australia and on the Cocos Keeling island. This distribution has been divided into nine genetically separate breeding stocks (FitzSimmons & Limpus 2014, Jensen et al. 2019) (Fig. 1.1). Three of these breeding stocks occur along the Queensland coastline: The southern GBR unit (sGBR), the Coral Sea unit and the northern GBR breeding unit (nGBR). Nesting sites for the sGBR extend from Fraser Island in the south to beyond the Capricornia Cays National Park in the north, while nesting sites for the nGBR centre around the islands on the outer edge of the northern GBR (Raine Island, Moulter Cay, No. 7 & No. 8 Sandbanks) and Torres Strait (Limpus 2009, Seminoff et al. 2015, Jensen et al. 2019). Ongoing management and conservation efforts have seen a stabilisation in numbers of nesting populations at most major breeding aggregations of south-east Queensland, however, green turtle populations remain at risk and ongoing monitoring is required (Limpus 2009).

Upon emergence from their natal beach hatchling green turtles from the Queensland breeding population follow an oceanic carnivorous pelagic life stage, foraging on a variety of macrozooplankton including molluscs, hydrozoans and crustaceans (Boyle & Limpus 2008). Following this early juvenile period individuals greater than 44cm curved carapace length (CCL) typically recruit to shallow feeding grounds, the majority of which, are within the boundaries of the Australian continental shelf (Limpus et al. 2005), exhibiting long-term fidelity to these recruitment areas (Limpus & Chaloupka 1997, Arthur et al. 2008, Shimada et al. 2016b). It was long thought that upon recruitment juvenile green turtles underwent an obligate ontogenetic switch from a pelagic carnivorous diet (macrozooplankton) (Bolten 2002), to a benthic herbivorous feeding strategy (seagrass and/or algae and/or mangrove) when they recruited to inshore foraging habitats (Bjorndal 1997, Limpus & Limpus 2000). Recently, instances of dietary switching between spatially distinct foraging grounds with different food items and migratory behaviour to new foraging grounds have been observed in

9 green turtles (Babcock et al. 2015, Shimada 2015, Prior et al. 2016). In addition, examples of selective foraging on macrozooplankton in neritic foragers, suggest that gelatinous prey may form a significant portion of the diet, challenging previous theories that suggested near exclusive herbivory once individuals recruited to the near-shore habitat (Heithaus et al. 2002, Arthur et al. 2007, Lemons et al. 2011, González et al. 2014).

1.1.2 Caretta caretta Loggerhead turtles, Caretta caretta, of the south-west Pacific display a similarly subtropical to tropical distribution as green turtles (Limpus 2009). Investigations into the phylogeography of global breeding aggregations has indicated that the south-west Pacific nesting populations on the east coast of Australia are genetically distinct from the northern Pacific breeding aggregations on the coast of Japan (Bowen 2003). Furthermore, genetic analyses of the nesting populations on each of the east and west coasts of Australia indicate that these are separate breeding stocks (Fig. 1.2) and should be managed as such (Dutton et al. 2002, FitzSimmons & Limpus 2014, Jensen et al. 2019).

Figure 1.2. Breeding stocks of loggerheads (C. caretta), highlighting separate east (1) and west (2) Australian stocks (Adapted from Limpus 2009). 10

Loggerhead hatchlings spend a protracted period in the open ocean foraging on a similar diet as juvenile green turtles with prey including pelagic hydrozoans, crustaceans, molluscans and fish eggs (Boyle & Limpus 2008). At approximately 15 ̶ 17 years (mean CCL 78.6 cm), they recruit to shallow neritic foraging grounds (Limpus & Limpus 2003a, Arthur et al. 2008, Limpus 2009). For hatchlings originally from the east Australian coastline, this oceanic developmental period occurs in the waters off the west coast of South America before the turtles make their way via major oceanic currents to recruit back into the waters off the coast of Queensland (Alfaro-Shigueto et al. 2004, Boyle et al. 2009, Limpus 2009). Recently recruited individuals are then likely to remain resident in these near-shore foraging grounds for over a decade before they reach sexual maturity (Limpus & Limpus 2003a). The diet of loggerhead turtles recruiting to near-shore foraging habitats appears to shift from a predominantly macrozooplankton diet to one that incorporates substantial benthic invertebrate prey, typically including species of Mollusca, Crustacea and Echinodermata (Preen 1996, Godley et al. 1997, Tomas et al. 2001, Bjorndal 2003, West 2007). However, individuals retaining pelagic foraging behaviours beyond neritic recruitment sizes and into adulthood have been observed in nesting populations in the north-east and north-west Atlantic as well as aggregations in the north-west Pacific around Japan (Hatase et al. 2002, Hawkes et al. 2006, Reich et al. 2009).

1.2 Methods of Dietary Studies

Understanding dietary composition can provide valuable information on how wildlife species utilise foraging areas (Shaver 1991) and may contribute insights into the effects of nutrition, growth and foraging site fidelity on reproductive frequency and output (Bjorndal 1985, Broderick et al. 2003, Jones & Seminoff 2013). Dietary analysis is a long-standing biological tool used to better understand foraging behaviour, movements and trophic status of terrestrial and marine wildlife (Bellwood 1988, Clements & Choat 1993, Sullivan et al. 1994, Raskoff 2002). When used in tandem with other analytical tools (i.e. mark and recapture, sonic and satellite telemetry) dietary analysis has revealed much of what we currently understand about dietary composition, foraging ecology and home ranges of marine vertebrate species (Limpus et al. 1992b, Choat et al. 2004, Al-Maslamani et al. 2007, Ho et al. 2007, Mansfield et al. 2009, Hazel et al. 2012).

1.2.1 Gut Content Analysis Conventionally, dietary studies have used direct visual analysis of gut contents to ascertain composition and proportions of ingested dietary items. In many marine species, including marine turtles, stomach or intestinal samples can be difficult to acquire due to accessibility, as mortalities for observation are typically opportunistically obtained. Consequently, dietary studies necessitated the dissection of euthanised wild-caught or deceased by-catch specimens or harvested specimens (Mortimer 1981, Thompson 1983, Godley et al. 1997). The advantage of this sampling approach was the capacity to sample diverse regions of the gut, providing insight into diet composition during a period equivalent to the individual’s digesta passage time (Thompson 1983). In immature green turtles, digesta may be retained for up to 14 days, with similar retention periods reported in juvenile and sub-adult loggerheads (Brand et al. 1999, Valente et al. 2008). However, sampling methodologies over the last couple of decades have turned toward less invasive (and non-lethal) techniques (Forbes & Limpus 1993, Limpus & Limpus 2000) such as oesophageal lavage and faecal analysis (Seminoff et al. 2002, Arthur et al. 2009).

Oesophageal lavage is an alternative technique for assessing diet that involves live capture and out-of-water restraint of individual turtles. Ingesta samples are flushed from the posterior oesophagus and thus represent the most recently ingested food items, likely just prior to

12 capture but certainly within the last few hours (Forbes & Limpus 1993). Despite sampling of dietary composition through lavage allowing for the sampling of a greater number of individuals within a foraging population than lethal sampling would permit it is limited by the short time frame collected samples represent (Forbes & Limpus 1993). Additionally, variation in the collected sample size can result in the risk that samples may not represent the true diversity of the individual’s diet, and may under-represent gelatinous material such as macrozooplankton (Baker et al. 2014).

Faecal samples can also be collected from sea turtles through sequential collections during captivity (O'Toole 2005, West 2007). Depending upon period of captivity, with digesta passage times previously reported to be approximately 14 days, this method may allow for the collection of an entire gut content, thus representing the diet of a sampled individual up to 14 days prior to capture (West 2007). A drawback of this technique however, is that the recovered faeces are biased towards undigested food portions (i.e. mollusc shells and opercula, crustacean exoskeletons, urchin spines/ tests and fish otoliths) (Casale et al. 2008), as the more easily digestible food items are often under-represented (i.e. polychaetes, annelids, benthic and pelagic cnidarian species and other soft-bodied benthic invertebrates) (Frick et al. 2009, Lemons et al. 2011).

Despite the recognised drawbacks of these methods, when combined with other techniques, they may be useful in building knowledge on how individuals move between and exploit different foraging grounds. For example, gut dissection of carcasses combined with oesophageal lavage and sonic telemetry determined that immature green turtles in Florida moved out of home foraging grounds during periods of low or high temperature and were only feeding in their home foraging range when water temperatures were between 18 ̶ 34 °C (Mendonça 1983).

Advances in technology over the last few decades have led to an increased implementation of new methods in tandem with traditional diet sampling techniques, including the use of animal-borne imaging, telemetry (satellite and sonic) and stable isotope analysis (SIA). These techniques have enabled the review of some long-standing paradigms in marine turtle feeding ecology (Limpus et al. 1992b, Heithaus et al. 2002, Arthur et al. 2007, Katzenberg 2008, Jones & Seminoff 2013, Thomson et al. 2018).

1.2.2 Telemetry and animal-borne imaging

Sonic and/or satellite telemetry allows the tracking of mobile species, providing data on migration paths and movements within foraging grounds in order to investigate habitat use (Polovina et al. 2000, Seminoff et al. 2008, Shillinger et al. 2008, Plotkin 2010, Hazel et al. 2012, Hazen et al. 2012, MacDonald et al. 2012, Shimada et al. 2017). The development of platform terminal transmitters (PTTs) in the early 1980s allowed for the tracking of long- distance movements and a resultant increase in uptake of telemetry to investigate migratory species (Gillespie 2001, Hays et al. 2001, Godley et al. 2008). With the introduction of Fastloc GPS (FGPS) came the ability to obtain detailed positional information using GPS satellite systems (Rutz & Hays 2009), improving the resolution of migratory routes and allowing the investigation of foraging ground use (Da Silva et al. 2011, Foley et al. 2013, Shimada et al. 2016b). Additionally, image recording equipment such as CritterCams, which are attached to the head or carapace of a surveyed individual are being increasingly utilised to investigate foraging ecology. Collected video footage has provided detailed insights into loggerhead foraging behaviour and diets (Narazaki et al. 2013) and highlighted opportunistic foraging of gelatinous prey by adult green turtles (Heithaus et al. 2002, Arthur et al. 2007, Burkholder et al. 2011).

Despite the valuable insights obtained from these methodologies, the associated financial costs require more selective approaches that typically result in small sample sizes relative to the target population (Polovina et al. 2004, Da Silva et al. 2011, Ceriani et al. 2012, Hazen et al. 2012). This highlights the need to adopt integrative sampling approaches in order to obtain representative samples of vulnerable populations and their foraging behaviours.

1.2.3 Stable Isotope Analysis Isotopes are atoms of the same element with a different number of neutrons and a consequent variation in atomic mass (Katzenberg 2008). Stable isotopes, which are heavier or lighter than their comparative element, are present in natural systems and accumulate in predictable patterns into the tissues of organisms by physical processes and chemical reactions. Stable isotope values are expressed using δ notation, defined as parts per mil (‰) and reflect the ratio of heavy to light isotopes in a chosen element (Peterson & Fry 1987, Wassenaar 2019). Analysing the values of stable isotopes in sampled material has become a widely used and

14 powerful analytical tool with applicability in archaeological, geochemical and biological studies (Tieszen et al. 1983, Peterson & Fry 1987, Ben-David et al. 1997, Cherel et al. 2006).

Of relevance to this research, investigating the isotopic ratios assimilated from prey organisms into the tissues of consumer species can be used to infer the diet or feeding location of that species. Typically, biological studies focus on carbon (δ13C) and nitrogen (δ15N) isotopes. In natural systems, primary producers take up carbon and nitrogen for cellular processes, assimilating δ13C and δ15N into tissue and setting an isotopic baseline within specific ecosystems. Consumption by a predator of these primary producers or subsequent consumers results in the assimilation of δ13C and δ15N, in varied levels of abundance due to cellular processes (termed tissue fractionation), from the prey into the predator’s tissue (Peterson & Fry 1987). Nitrogen (δ15N) is primarily used to determine the trophic level of an individual because δ15N is retained over lighter δ14N during the excretion of metabolic waste. This results in a cumulative stepwise enrichment (3-5 ‰) in the ratio of 15N:14N in the bodily tissue from the baseline values expressed in a primary producer up each trophic level to that of the predator (Deniro & Epstein 1978, 1981, Minagawa & Wada 1984, Somes et al. 2010). In contrast, assimilated carbon (δ13C) rarely undergoes significant fractionation in the tissues of the consumer relative to the abundance expressed in baseline primary producers, regardless of trophic position of the consumer. Members within the distinct orders of autotrophs (plants and algaes) assimilate δ13C and δ15N through different cellular pathways, which results in distinct baseline isotopic ratios dependent upon taxa (Deniro & Epstein 1978, 1981, Hobson 2019). Consequently, quantifying the ratio of stable isotopic elements assimilated into proteinaceous animal tissue and comparing these values to food items (plant or animal) in known foraging areas enables the inference of diet in a sampled individual (Tieszen et al. 1983, Peterson & Fry 1987).

The relative abundance of baseline δ13C and δ15N in an ecosystem reflects the abundance of δ13C and δ15N available for assimilation. In an ocean setting, this abundance can be influenced by a variety of factors including; primary productivity, temperature, prevailing currents and the contribution of anthropogenic sources of δ13C and δ15N (Peterson & Fry 1987). Consequently, regional differences in these factors can result in the development of distinct baseline δ13C and δ15N abundance. For example, oceanic phytoplankton preferentially assimilates δ12C during photosynthesis, resulting in higher baseline values of δ13C in upwelling zones and a gradual depletion along the prevailing current creating a δ13C gradient

(Graham et al. 2010). Consequently, the mapping of predictable gradients in δ13C and δ15N produces isoscapes, which enable the inference of a sampled individuals foraging location by comparing their assimilated δ13C and δ15N to identified baseline isotopic values throughout an isoscape (Rau et al. 1982, Rubenstein & Hobson 2004).

In addition to changes in the relative abundance of isotopic values by tissue fractionation, the assimilation of δ13C and δ15N into different bodily tissue is influenced by the metabolic rate relative to the turnover periods of different bodily tissues. This important consideration is necessary for the accurate inference of location or dietary compositions. Due to the varying turnover rates of different tissues, the sampling and analysis of tissues with moderate and slow turnovers as a consequence of different synthetic pathways allows for the investigation of dietary trends over different time periods (Hobson & Clark 1993, Martinez del Rio et al. 2009). However, determining turnover rates of stable isotopes in different tissues of adult marine turtles is a laborious, time consuming and costly enterprise which has not yet been undertaken. The determination of these turnover rates would require the consistent sampling of a substantial sample size of captive animals for a period of months to identify the isotopic shift observed between two isotopically distinct diets. As a consequence, turnover rates quoted in existing research are estimations based on observed turnover rates in other reptilian and avian species as well as a small body of research on turnover rates in juvenile marine turtle species (Hobson & Clark 1993, Seminoff et al. 2007, Reich et al. 2008, Vander Zanden 2012). Within hatchling and juvenile loggerhead and green turtles, turnover rates of epidermis, blood cells and blood plasma were reported to be between 70 ̶ 85 , 35 ̶ 45 and 15 ̶ 20 days respectively (Reich et al. 2008). Currently no data exists on the turnover rates of different tissues in adult marine turtles, however, a turnover of a few weeks is assumed for plasma and between two to six months for blood cells and epidermis (Seminoff et al. 2007, McClellan et al. 2010).

Despite an increase in isotopic studies on foraging and nesting marine turtle populations, targeted studies identifying baseline isotopic values and the variation between distinct oceanic basins, geographic locations, foraging grounds and threatened foraging populations are areas requiring further study (Ceriani et al. 2012, Pearson et al. 2017, Haywood et al. 2019). To ensure findings are not misleading, care must be taken to validate isotopic values against a baseline of values from individuals of known origin determined by alternative methods, such as satellite telemetry or comparing isotope ratios to those obtained by in situ

16 sampling of individuals from known foraging grounds. Studies cognisant of these limitations have successfully incorporated SIA to investigate marine turtle populations, providing insights into the foraging behaviour and habitat usage of a far greater proportion of the population than traditional gut analysis techniques can achieve (Allen et al. 2013, López- Castro et al. 2014).

1.3 Dietary Composition and Foraging Behaviour

The use of SIA in marine turtle dietary studies has significantly increased the knowledge of diet, identification of foraging home grounds, and refined longstanding theories on dietary choice and foraging movements. Traditionally, it had been thought that green turtles recruit to a neritic foraging ground at a body size of > 44 cm CCL, undergoing an obligate ontogenetic shift from their carnivorous oceanic diet of macrozooplankton to one of herbivory (Bjorndal 1997, Bolten 2002). However, observed omnivory in several green turtle populations indicates that gelatinous prey continues to contribute significantly to their diet beyond recruitment of individuals to near shore foraging grounds (Forbes 1996, Burkholder et al. 2011, Lemons et al. 2011, González et al. 2014). In addition, Hatase et al. (2006) concluded that the oceanic to neritic habitat shift may in fact be facultative and not obligate, since a proportion of the adult nesting female green turtles around the Ogasawara Islands use oceanic waters as alternative epipelagic feeding habitats. Alternative foraging strategies have also been inferred through satellite tracking of post-nesting adult female loggerhead and green turtles to their feeding grounds. Such studies have found that most females move to near- shore neritic habitats, but some remain in off-shore oceanic habitats (Hawkes et al. 2006, Seminoff et al. 2008).

In those individuals that recruit to near-shore habitats, current theories assert that juvenile green and loggerhead turtles exhibit fidelity to distinct home ranges, typically 0.5 ̶ 14 km2 (Makowski et al. 2006, Limpus 2009, Hazel et al. 2012, Babcock et al. 2015). Once established in these foraging grounds, individuals rarely venture from these grounds except in times where conditions are unfavourable, or for migration to nesting beaches at reproductive maturity (Limpus et al. 1992b, Limpus 2009). Atlantic juvenile green turtles tracked via sonic telemetry over a period of three months were found to exhibit fidelity to foraging ground sites no larger than 5.5 km2 in shallow reef habitats (Makowski et al. 2006). Similarly, immature green turtles foraging on off-shore tropical reef habits along northern

Australia and tracked for 100 days, exhibited fidelity to foraging grounds of < 1 km2 (Hazel et al. 2012). Discrete foraging sites have also been reported for loggerhead turtles, comprising geographic ranges of < 10 km2 in reef habitat and up to 21 km2 in the seagrass habitats of eastern Moreton Bay, Australia (Limpus 1985, Limpus et al. 2001). Similarly, juvenile and adult green turtles tracked over 370 days in San Diego Bay, USA, had individual foraging grounds that ranged from 2 ̶ 9 km2, displaying dichotomous foraging behaviour, alternating between distinct habitats with different predominant food items (MacDonald et al. 2012).

Green turtles in Central and southern Queensland also display fidelity to home foraging grounds, returning even after displacements of up to 100 km away from their site of capture (Shimada et al. 2016a). However, dichotomous foraging behaviours have been observed with individuals within Port Curtis and Moreton Bay changing foraging locations intermittently, and travelling substantive distances (> 100 km) back and forth between locations, with some individuals moving permanently to new foraging grounds (Hamann et al. 2015, Shimada 2015). In addition, a previous study found that 50 % of sampled individuals in the Port Curtis population travelled between distinct foraging grounds (i.e. rocky reef, sea grass meadows or mangrove habitats ≥ 10 km apart) which host different food types within a period of a few months (reflected in isotopic signatures of sample blood and skin tissue) (Prior et al. 2016). These shifts between foraging habitats could be a consequence of seasonal variability in temperature and food availability (Shimada 2015), because foraging habits and behaviour vary with local conditions (i.e., abiotic disturbances and diel tidal differences in foraging activity), nutritional availability (food type and nutritional value) and size of the individual (Hatase et al. 2002, Limpus et al. 2005, Seminoff et al. 2008, Arthur et al. 2009, Mansfield et al. 2009, McClellan et al. 2010).

In marine turtles, dietary composition typically reflects the local food availability. For example, green turtles found in seagrass meadows have diets dominated by seagrass, and those found in reef areas have diets dominated by algae (Bjorndal 1980, Forbes 1996). However, in areas where both algae and seagrass are available, the selection of food items may be linked to nutritional value or digestibility, although no apparent advantage has been established for either food option (Bjorndal 1985, Garnett et al. 1985, McDermid et al. 2007). A preference for algae species with low levels of fibre but higher relative nitrogen content

18 over seagrass was observed in populations of immature green turtles in Moreton Bay, Queensland, (Brand-Gardner et al. 1999). In contrast, despite an abundance of algal species, a preference for seagrasses was observed throughout size classes for green turtles foraging in the north-west Atlantic and the Caribbean (Bjorndal 1980, Mortimer 1981, Mendonça 1983).

Differences in foraging ground locations and the implications of variations in diet and available nutrition are also likely to influence the growth rate of marine turtles (Bjorndal 1985). A disparity in growth rate and size at reproductive maturity has been observed for green turtles that originated from the same breeding population but inhabit geographically separate sites along the east coast of Australia (Chaloupka et al. 2004). Diet related variation in reproductive frequency occurs between marine turtle species, with herbivorous turtle species typically reaching reproductive maturity at similar ages to their carnivorous counterparts, but exhibiting larger periods between breeding migrations (Frazer & Ehrhart 1985, Hamann et al. 2002, Broderick et al. 2003). This difference in reproductive frequency is possibly a function of trophic status and consequent nutrition (i.e. energy content and quality of diet). Largely herbivorous foragers such as green turtles are limited by the nutritional content of their food items with seagrass and algae typically having lower nitrogen content than prey consumed by carnivorous species (Bjorndal 1985).

Foundational studies on dietary composition in individual turtle populations around the world have reported a diversity of foraging strategies in locally and regionally distinct feeding grounds which influence the rates of growth and development (Bjorndal 1980, Mendonça 1983, Godley et al. 1997, Amorocho & Reina 2007). These results emphasise the ongoing need to re-evaluate our understanding of marine turtle foraging habitats in at risk populations to determine the proportion of nesting individuals from these contrasting foraging strategies and the anthropogenic risks associated with these different foraging habits. The establishment of foraging behaviours in local populations is critical in the development of management strategies for the conservation of local genetic stocks. This is particularly important for populations proximal to potential anthropogenic threats such as industrial and agricultural discharge or commercial and recreational vessels.

1.4 Aims and Significance

The diversification of marine turtle species into genetically separated breeding stocks necessitates a greater understanding of how these different populations function, with respect to their foraging strategies and migratory pathways (Bowen 2003). Queensland hosts foraging grounds and the most significant nesting aggregation of critically endangered loggerhead turtles in the south-west Pacific and supports foraging populations for the largest remaining breeding units of the vulnerable green turtle (Limpus 2009, Limpus & Casale 2017). How individuals in these nesting populations interact and exploit foraging grounds and move between valuable foraging grounds has implications for the management and conservation of these at-risk species.

The relative contributions of spatially distinct foraging populations to nesting rookeries has important conservation implications for vulnerable and endangered species. Determining the origins and relative proportions of nesting individuals from foraging locations enables focused management efforts on foraging sites most valuable to the nesting population. The major loggerhead turtle nesting aggregation on the east coast of Australia is located on the Woongarra coast, centred upon Mon Repos Conservation Park. Substantial numbers of green turtles from the sGBR genetic stock aggregate at the Capricorn-Bunker Island group (Heron, Wreck, North-West Island etc.) and the nGBR genetic stock at Raine Island. Whilst previous migration studies have successfully used capture-mark-recapture (CMR) or satellite telemetry techniques to identify foraging grounds for individuals in these populations, the contributions of distinct foraging regions to these nesting aggregations remain poorly described (Limpus 2009).

By analysing stable isotope ratios in the sampled nesting and foraging loggerhead and green turtles this study aimed to identify the isotopic ranges for the south west Pacific nesting loggerhead population and rookeries from the nGBR and sGBR green turtle genetic stocks. By comparing the isotopic values from nesting individuals of known migratory origin (known via previous CMR or satellite telemetry studies) the common migratory origins of nesting loggerhead and green turtles at Mon Repos, Heron Island and Raine Island was investigated. This research contributes to the growing body of knowledge on stable isotope analytical

20 techniques and support ongoing conservation and management of valuable identified foraging habitats for these nesting populations.

Moreton Bay, Queensland, hosts the greatest concentrations of foraging loggerheads from the south-west Pacific breeding stock (Limpus 2009). While the diets of resident loggerheads have previously been explored, there are currently no studies that incorporate faecal sampling and SIA techniques (Moody 1979, Limpus et al. 2001). The combination of these techniques will enable the exploration of dietary composition to establish dietary trends over a longer period than previous gut analysis methods have allowed and determine the degree of isotopic variation observable within individuals in a foraging region and its relationship to dietary composition. This research aimed to investigate the diets of resident loggerhead turtles in Moreton Bay and whether variation in dietary composition and foraging strategies existed in individuals from different regions within the bay. Understanding the foraging strategies and dietary composition of this species is important in guiding management decisions in Moreton Bay, including the identification of habitat protection zones (i.e. ‘Go Slow Zones’) and Marine Protected Areas.

Substantial breeding populations of green turtles from the Coral Sea and Northern and Southern Great Barrier Reef forage in bay habitats along the coastline of Queensland (Limpus 2009). Port Curtis supports a foraging population that contributes to these breeding units and hosts a diversity of habitats. Previous research on resident foraging populations in south east Queensland has used novel approaches (Animal-borne imaging) and gut content analysis (oesophageal and gut tract) to explore dietary composition (Brand-Gardner et al. 1999, Brand et al. 1999, Limpus & Limpus 2000, Arthur et al. 2007, Arthur et al. 2009). These methods have discovered significant omnivory, shifts in dietary composition and seasonal or age-class related differences in foraging ground site and location within individuals (Limpus et al. 2005, Read & Limpus 2005, Babcock et al. 2015, Shimada 2015, Prior et al. 2016). This study aimed to determine dietary composition, the proportion of the population exhibiting distinct dietary shifts, and the proportion consuming a significant amount of animal material. Further, this study sought to establish if there was an age-class preference for different foraging habitats. The outcomes of this study will inform management strategy in an urbanised foraging environment for the conservation of individuals utilising diverse habitats and foraging strategies.

Chapter 2

Coffee, O.I., Booth, D.T., Thia, J.A. and Limpus, C.J. (2020). When isotopes fail: the importance of satellite telemetry and multi-site validation when estimating the foraging grounds of migratory species, Mar Ecol Prog Ser.

Contributor Statement of Contribution Author: Owen I. Coffee (Candidate) Conception and design (70%) Analysis and interpretation (80%) Drafting and production (70%) Author: David T. Booth Conception and design (20%) Analysis and interpretation (5%) Drafting and production (12.5%) Author: Joshua A. Thia Conception and design (0%) Analysis and interpretation (15%) Drafting and production (12.5%) Author: Col J. Limpus Conception and design (10%) Analysis and interpretation (0%) Drafting and production (5%)

When isoscapes fail: the importance of satellite telemetry and multi-site validation when estimating the foraging grounds of migratory species

2.1 Abstract Integrated analytical approaches utilising satellite telemetry and stable isotope analysis (SIA) have become popular for investigating foraging ground habitat use, diet and migratory behaviour in marine species. For migratory species such as marine turtles, that have distinct nesting and foraging areas, it is valuable to identify the proportions of the nesting population derived from different foraging areas to mitigate potential threats through the incorporation of long-term conservation management strategies. In this study, a combination of turtle tissue δ13C and δ15N isotopes ratios, capture-mark-recapture and satellite telemetry data were used to investigate the foraging locations supporting nesting loggerhead turtles on the Woongarra coastline, south Queensland, Australia. The identification of a latitudinal gradient in the δ13C and δ15N isotopic ratios of sampled bodily tissue led to the successful determination of foraging regions in nesting loggerheads of the north-west Atlantic. In this study, isotopic values of nesting turtles were collected over the course of two nesting seasons. Known foraging grounds were available for a subset of these turtles (encompassing migratory distances up to 2,000 km) and supplemented with samples taken from foraging turtles to determine whether foraging regions could be identified in untracked nesting turtles based on the stable isotopic values of their sampled tissue. Surprisingly, despite the large distances between known foraging regions, no latitudinal gradient was observed in the isotopic values of these turtles. In addition, the isotopic values of foraging individuals from a single site, encompassed the entire range of isotopic values of all loggerhead turtles sampled over the 2,000 km north-south distribution along the east coast of Australia. Consequently, this study demonstrated that assumptions common to δ13C and δ15N stable isotope inference in migratory species are not adhered to globally. Despite the successes of SIA in assigning putative foraging regions in the north-west Atlantic, the results from this study indicate other factors in the south west Pacific such as differing prevailing oceanic currents, temperature regimes and river run-offs may prevent the establishment of region specific unique isozones, a condition needed to be able to identify the foraging region of turtles based on their isotopic values. Therefore, we caution against the use of δ13C and δ15N stable isotopic values as suitable indicators of foraging regions for loggerhead turtles in Australia. These findings

23 potentially highlight the need to re-evaluate when and where the use of isotopic analysis is appropriate for identifying foraging locations in marine turtle species.

2.2 Introduction Understanding the connectivity between breeding areas and resident foraging areas in migratory marine species is desirable for the implementation of long-term conservation management strategies. This is particularly important for species such as marine turtles that have distinct nesting and foraging areas, to understand what proportion of a nesting population is derived from any given foraging area. While marine turtles are easily surveyed at their breeding aggregations, the feeding grounds of these populations may, in some locations, be unknown or difficult to access for detailed survey. Determining the location of these feeding grounds can facilitate the management of high usage feeding areas. Stable isotope analysis (SIA) of tissues from individuals at breeding aggregations is an increasingly used method for identifying the feeding locations of numerous migratory species (Caut et al. 2008a, Caut et al. 2008b, Cherel et al. 2009, Allen et al. 2013, Lorrain et al. 2015, Pethybridge et al. 2015). In marine turtles, other information, such as differential habitat use, variation in habitat condition and consequent differences in dietary composition and migratory distances have also been inferred from SIA (Godley et al. 1998, Hatase et al. 2010, Thomson et al. 2012, Ceriani et al. 2015, Figgener et al. 2019).

Diet and trophic position of a sampled individual within its foraging regions can be inferred using the stable isotopic ratios of δ13C and δ15N from their body tissues (Hobson 2019). The fractionation of these isotopes occurs predictably along a trophic cascade (Deniro & Epstein 1978, 1981, Tieszen et al. 1983, Post 2002). Additionally, the identification of oceanic latitudinal gradients in carbon stable isotopes has aided the determination of migratory routes and foraging areas in several migratory marine species including: marine turtles (Caut et al. 2008b); fur seals (Cherel et al. 2009); and blue crabs (Gelpi et al. 2013). Isotopic gradients are associated with sea surface temperature and productivity in oceanic primary producers, with enriched δ13C values connected to productive regions, such as upwelling zones (Graham et al. 2010). Additionally, depletions are observed with increased latitude in the Pacific-Artic, Indian and Atlantic oceans (Rau et al. 1982, Magozzi et al. 2017), with the lowest δ13C values found in low nutrient or stratified regions (Deniro & Epstein 1978, Peterson & Fry 1987).

These systematic variations in δ13C values within regions are critical for the correct identification of location, habitat use and dietary composition in integrated isotopic analyses.

Because of the insights SIA provides, it has been used in a range of marine species to investigate diet, habitat use and migration, including identifying foraging habitats and trophic positions of pelagic fish species (Lorrain et al. 2015), the wintering habitat of migratory seabirds (Cherel et al. 2006) and quantifying diet of pygoscelid penguins in Antarctica (Polito et al. 2011). Marine turtle SIA studies have identified that many green turtles (Chelonia mydas), which are primarily herbivorous as adults, continued to consume macrozooplankton prey following recruitment to benthic foraging grounds (Hatase et al. 2006, Cardona et al. 2009, Lemons et al. 2011, González et al. 2014, Shimada et al. 2014, Prior et al. 2016). Additionally, SIA has confirmed that a sub-population of nesting loggerhead (Caretta caretta) females in the north-west Pacific retain oceanic foraging strategies into maturity (Hatase et al. 2010). The successful prediction of foraging grounds of north west Atlantic loggerhead turtles based on their tissue stable isotope values has also been demonstrated (Ceriani et al. 2012, Vander Zanden et al. 2015, Ceriani et al. 2017), while isotopic differences between turtles in the north east Pacific and those from the Atlantic identified differential nitrogen cycling processes (Pajuelo et al. 2010).

Because resource acquisition is likely to influence reproductive rates, identifying the foraging grounds of migratory species can be useful in interpreting population trends (Alerstam et al. 2003, Norris 2005, Inger et al. 2010, Authier et al. 2012). In marine turtle populations, differences in foraging strategies, habitats and migratory distances influence a range of fitness metrics for both mother and offspring (Frazer & Richardson 1985, Broderick et al. 2001, Zbinden et al. 2011). Body size of reproductive female loggerhead turtles has been linked with foraging area, with carry over effects on size of clutches and time between subsequent breeding seasons from two nesting populations of the northern hemisphere (Hatase et al. 2013, Vander Zanden et al. 2014). Similarly, large migratory distances may be negatively correlated with reproductive output, as observed in nesting loggerheads on the east coast of north America, suggesting additional energetic costs to breeding in individuals that have long migration pathways (Ceriani et al. 2015).

Major nesting beaches of the south Pacific genetic stock of loggerhead turtles are well known (Bustard 1972, Limpus 1985, Limpus et al. 2013a, FitzSimmons & Limpus 2014, Limpus &

Casale 2017) as is the distribution of foraging areas (Limpus 2009). Despite this, the relative importance of different foraging regions and the proportion of the nesting population that use these areas remains incompletely described.

Following an oceanic developmental period of more than a decade, loggerhead turtles of the south Pacific genetic stock recruit to foraging areas in the Arafura, Coral and Tasman seas within Indonesia, Papua New Guinea, the Solomon Islands, New Caledonia and along the north and east coast of Australia (Limpus 2009, Limpus et al. 2013a). After juveniles have settled to a neritic foraging area, their diet shifts from predominantly pelagic foraging, targeting macro-planktonic prey found at the surface and mid water column (Boyle & Limpus 2008), to a diet of mostly benthic invertebrate species such as crustaceans, gastropods and bivalves (Limpus et al. 2001). Once recruited to the neritic feeding habitat, individuals remain in a localised area for the remainder of their lives, except for periodic migrations for reproduction when sexually mature (Limpus & Limpus 2001, 2003a, Limpus 2009). Turtles intentionally displaced from their foraging areas in south east Queensland have been observed returning to their original foraging region, and satellite telemetry indicates their usual home range size is 15 to 160 km2, highlighting loggerheads of the south Pacific genetic stock exhibit strong fidelity to their foraging regions (Shimada et al. 2016a, Shimada et al. 2017). While the recruitment and fidelity to select foraging regions has been identified for loggerhead turtles of the south Pacific genetic stock (Limpus et al. 1992b, Chaloupka & Limpus 2001), the relative importance of these foraging regions is not known. SIA offers the potential to sample a large number of nesting individuals in order to identify their foraging regions and provides the potential to obtain a more comprehensive indication of the contribution of different foraging areas to the nesting population than has previously been possible using satellite telemetry or capture-mark-recapture (CMR) techniques.

This study aimed to use SIA, CMR and satellite telemetry data to identify the foraging regions of individual females from a major nesting aggregation of the south Pacific genetic stock of loggerhead turtles nesting along the Woongarra coast, central Queensland, Australia. Based on studies that identified the foraging grounds of north-west Atlantic loggerheads using SIA (Ceriani et al. 2012, Vander Zanden et al. 2015), it was hypothesised that a north to south latitudinal gradient would be observed along the Woongarra coast, central Queensland, Australia in the δ13C of sampled nesting turtles. This gradient would facilitate

26 the identification of foraging regions used by nesting turtles, based on their isotopic values, using predictive modelling.

2.3 Material and methods

2.3.1 Study sites and sampling procedures The Woongarra Coast in south east Queensland, Australia, including Mon Repos rookery (24.79611 S; 152.44055 E), hosts the highest nesting numbers of loggerhead turtle from the south Pacific genetic stock listed by IUCN as a critically endangered management unit (Limpus 2009, Limpus & Casale 2017). During the nesting seasons of 2015–2016 (December and February) and 2016–2017 (December and January) adult females were sampled at Mon Repos and the nearby beaches. Over the sampling period, 120 and 188 nesting females were sampled from the 2015–2016 and 2016–2017 seasons respectively. The number of turtles sampled was approximately a third of the total number of females nesting in each season. Of the 308 nesting females sampled, the foraging areas of 15 individuals were established from previous satellite telemetry or capture-mark-recapture (CMR) studies (8 by multi-year CMR records and 7 tracked by satellite to foraging grounds where they were resident for at least 6 months; DES, unpublished data). Shimada et al. (2017) has previously established by satellite telemetry that foraging loggerheads of the south Pacific genetic stock exhibit strong fidelity to their foraging grounds when not undertaking reproductive migrations.

Foraging Mean Cohort Season n= Sex Maturity s.d. Location CCL 2015 - 16 120 - - 94.7 5.2 Unknown* 2016 - 17 188 - - 93.7 6.3 Nesting STEA 9 - - 93.6 6.2 sGBR 3 - - 95.0 4.9 nGBR 3 - - 95.6 4.6 1 SA 77.9 - F 7 A 92.9 2.9 Moreton Bay 3 SA 87.7 6.4 Foraging M (STEA) 11 A 95.74 4.9 20 SA 79.5 4.9 Unk. 3 A 81.8 6.4 * Unknown nesting individuals sampled from Mon Repos turtle rookery

Turtles were sampled immediately following oviposition or while they were returning to the water. Each turtle had its midline curved carapace length (CCL) measured using a fibreglass measuring tape (± 0.2 cm) (Table 1). All turtles were identified using titanium flipper tags and processed following Queensland Turtle Conservation Project protocol (Limpus 1985, 1992, Limpus et al. 1994b). Following swabbing with 70 % ethanol, a 0.5 cm2 skin sample was taken from the trailing edge of the fore flipper between the keratinised scales using a sterile scalpel and stored in 70 % ethanol until stable isotope analysis. Storage in 70% ethanol has no significant effect on δ13C and δ15N isotopic signals (Barrow et al. 2008). Blood samples (3 mL) were taken from the external jugular vein just posterior to the head (commonly termed the dorsal cervical sinus) using a sterile single use syringe and 18 - gauge needle and stored in heparinised containers to prevent clotting (Owens & Ruiz 1980). Heparin has a negligible effect on the nitrogen isotopic value in sea turtle blood (Lemons et al. 2012). Blood samples were then separated into plasma and red blood cells (RBC) by centrifuge at 9000 rpm for 5 minutes and stored at –18 °C until analysed. Blood sampling was not undertaken in the 2016 ̶ 2017 nesting season as skin has a slow tissue turnover rate relative to blood components and was therefore deemed adequate to reference the diet of the home foraging region of a sampled individual (Allen et al. 2013).

Additional blood and epidermal tissue samples were collected from 45 foraging turtles in Moreton bay (south east Queensland), one of the known major foraging areas for loggerheads of the south Pacific genetic stock (Limpus et al. 1994b, Limpus & Limpus 2001). These samples were collected between July 2015 to October 2017 to identify whether baseline isotopic values were observable within one of the potential foraging regions of the sampled nesting cohort. Foraging loggerhead turtles were captured by the rodeo method (Limpus 1978). Upon capture, all turtles were processed following Queensland Turtle Conservation Project protocol (Limpus et al. 1994b), sex and maturity was defined in accordance with the key from (Limpus & Limpus 2003a) (Table 2.1).

The foraging locations of nesting individuals with known foraging grounds (n = 15) spanned the east coast of Australia from northern New South Wales (28.9 °S) to Torres Strait (10.4 °S), covering a distance ~ 2,000 km. The study region was divided into the three broad foraging regions: northern Great Barrier Reef (nGBR); southern Great Barrier Reef (sGBR);

28 and sub-tropical Eastern Australia (STEA) (Fig. 2.1), encompassing migratory distances of ~100 – 1200 km from the Woongarra coast nesting beaches. Regions were defined based on the Great Barrier Reef Marine Park Authority’s reef health survey regions. The nGBR and sGBR regions are separated by a westward oceanic current from the Coral sea that bifurcates at ~ 20 °S, the northward branch feeding equatorial currents following the north east Queensland coastline while the southward current forms the East Australian Current (EAC), the westward boundary of the southern Pacific ocean (Church 1987).

Consequently, it was hypothesised this bifurcation would contribute to isolation of the two foraging regions, with an expected differentiation in carbon isotopic composition in primary producers. The STEA region covers the sub-tropical coastline south of the Great Barrier Reef (Fig 2.1). As this region of the coast is not influenced by the extensive coral reefs of the GBR, instead being dominated by coastal and subtidal foraging habitats, it was anticipated delineation in baseline isotopic values of food items may be influenced by fresh water outflows and/or proximity to anthropogenic carbon and nitrogen sources (Garcia et al. 2007).

2.3.2 Sample preparation and analysis Tissue samples were prepared for SIA following the protocols outlined by Reich et al. (2008). Skin samples were rinsed with distilled water and cleaned with a sterile scalpel blade. Epidermis was separated from the underlying tissue, epiphytic growth was removed, and the epidermis was finely diced. Separated blood components and epidermis samples were then oven dried at 50 – 60 °C for 48 – 72 hours in individual sample tubes. Dried plasma and blood cells were ground with 5 mm glass beads by a Qiagen TissueLyser II (Venlo, Netherlands). Due to the low lipid content (C:N < 3.5), chemical lipid extraction was not performed on the epidermis and blood samples prior stable isotope analysis (Post et al. 2007). Following drying, 1.5 – 2.5 mg of each tissue type was loaded into standard weight tin capsules and analysed using an Elementar Vario Cube (Frankfurt, Germany) elemental analyser coupled with an IsoPrime (Micromass, UK) continuous flow stable isotope ratio mass spectrometer (EA-IRMS). Stable isotope values were expressed using δ notation, defined as parts per mil (‰):

δ = [(Rsample/Rstandard) −1] × 1000 13 12 15 14 Where Rsample is the ratio of heavy to light isotopes ( C: C or N: N) in the sample. Rstandard is the isotope ratio for the corresponding international standards, atmospheric nitrogen and Vienna PeeDee Belemnite (VPDB) for carbon (Peterson & Fry 1987, Wassenaar 2019). Throughout the analysis technical standards were run every 20th sample with a subsequent precision of ± 0.1 ‰ for δ13C and ± 0.2 ‰ for δ15N.

2.3.3 Statistical Analysis All statistical analyses were conducted using the R statistical program (v3.4.0) and RStudio user interface (v1.1) (RStudio Team 2016, R Core Team 2017).

Welch’s two sample t-tests investigated whether CCL or carbon and nitrogen isotopic composition of turtle tissue differed significantly between the sampled seasons to determine whether individuals could be pooled across seasons for further analyses. Additionally, an ANOVA tested for significant differences between CCL and foraging region for individuals with known foraging grounds. Subsequent linear regression analyses considered the hypothesis that δ13C and δ15N exhibit latitudinal gradients using the nesting individuals with known foraging locations.

A discriminant functions analysis (DFA) was used to model the between group differences in δ13C and δ15N for turtles that had previously been tracked to their foraging grounds by satellite telemetry or CMR studies. The lda function in R’s MASS package (Venables & Ripley 2002) was used to discriminate foraging ground by δ13C and δ15N of tracked foragers

(nGBR, n = 3; sGBR, n = 3; STEA, n = 9), with equal priors for each group forming the “training” dataset. The resulting model was then used to generate LD (linear discriminant) scores for all individuals using R’s predict function (R Core Team 2017). If tracked individuals had isotopic values that discriminated their foraging history, it was expected the DFA model could separate individuals with unknown foraging grounds into clusters that reflected their predicted foraging grounds (Ceriani et al. 2012). Hence turtles with unknown foraging grounds represented the “test” dataset to test the predictive power of the DFA model. A leave-one-out cross validation of the model generated from tracked nesting turtles by satellite telemetry was used to determine the predictability of the subsequent model (Ceriani et al. 2012).

2.4 Results A Welch’s two sample t-test demonstrated no difference between δ13C and δ15N values from 13 15 epidermal tissue across sampling seasons (δ C t261 = – 1.09, p = 0.28; δ N t249 = – 0.31, p =

0.76). Similarly, there was no difference in CCL between 2015–2016 and 2016–2017 (t240 = 0.23, p = 0.82). Hence samples were pooled across seasons for subsequent analyses. An ANOVA of the CCL of turtles with known foraging regions found no difference in CCL across the three foraging regions (F2,25 = 0.41, p = 0.67).

The δ13C values of epidermis from nesting turtles with known foraging grounds ranged from –17.8 ‰ to –7.5 ‰, while δ13C values from the sampled nesting cohort with unknown foraging grounds ranged from –17.2 ‰ to –6.7 ‰ (Fig. 2.2). Values of δ15N from the sampled cohort with known foraging grounds ranged from 7.7‰ to 15.9‰ with values for nesting turtles with unknown foraging grounds ranging from 6.9‰ to 16.9‰ (Fig. 2.2). Turtles from a single site in Moreton Bay (STEA region), encompassed the entire isotopic range of satellite-tracked turtles (–15.2 ‰ to –8.5 ‰ for δ13C and 7.5 ‰ to 14.7 ‰ for δ15N), identifying within-site variance comparable to between region variances.

There was no correlation between latitude of foraging area and tissue δ13C values for turtles 2 15 2 with known foraging location (r < 0.01, F1, 12 = 0.04, p = 0.84) or δ N (r = 0.04, F1, 12 = 0.47, p = 0.51), indicating a lack of latitudinal related variation in stable isotopic composition of marine turtle tissue. Consequently, the DFA model derived from individuals with known foraging locations could not accurately identify foraging region of the nesting cohort. Cross- validation indicated that the training dataset (turtles with known foraging grounds) were only correctly assigned to their respective foraging grounds 60 % of the time, suggesting foraging ground location was not the only driver of variation observed in marine turtle tissue isotopic values.

The sample size used to create the DFA model was small (n = 15), limiting statistical power. However, given the observation that the isotopic values measured in the epidermal tissue of turtles’ satellite tracked from across the entire region completely overlapped with all turtles from a single site (Moreton Bay, STEA) (Fig. 2.2), it was concluded that predictive modelling in this system would produce biologically uninterpretable results. Hence, it was not possible to estimate foraging locations of unknown nesting turtles from the Woongarra Coast due to the lack of systematic regional variation in stable isotope values, and high variance in isotopic composition of turtles within known foraging locations.

2.5 Discussion

Stable isotope analysis of marine turtle tissue has successfully identified foraging grounds of loggerhead turtles nesting in the Atlantic (Ceriani et al. 2012, Vander Zanden et al. 2015). However, this study demonstrated that δ13C and δ15N stable isotope values in epidermis were unable to inform the identification of foraging grounds of loggerhead turtles in eastern Australia. The absence of systematic regional variation and high within region variance in marine turtle tissue isotopic values made predicting foraging grounds unreliable. These findings therefore warrant caution in the use of isotopes to infer ecological processes when assumptions of their spatial distribution have not been validated.

2.5.1 Isotopic values and latitudinal gradients in oceans Previous studies, conducted in the northern hemisphere have established there is a strong relationship between δ13C and δ15N isotopic values of foraging loggerhead turtles and latitude of foraging grounds (Ceriani et al. 2012, Allen et al. 2013, Vander Zanden et al. 2015, Bradshaw et al. 2017). In the north-east Pacific a 2 ̶ 3 ‰ depletion in δ13C is associated with the transition from mid to high latitudes while enrichment is linked to higher phytoplankton growth rates in regions of upwelling with nutrient rich waters (Graham et al. 2010). In contrast, Magozzi et al. (2017), found no systematic variation in δ13C in phytoplankton with latitude from 10 – 28 °S in the west Pacific ocean, a finding consistent with our observations.

The non-systematic variation of isotopic values in this dataset may be associated with the difference in oceanic currents and benthic topography of the Australian coastline compared to coastlines in the north-west Atlantic Ocean. The waters inhabited by the north-west Atlantic loggerhead population studied by Ceriani et al. (2012), experienced relatively frequent turnover driven by the prevailing oceanic currents of the Gulf Stream, linked to the Gulf of Mexico by the Loop Current and travelling from near the equator northward toward the Arctic (Lee & Mellor 2003, Reverdin et al. 2003). In contrast, the prevailing currents in eastern Australia originate from the Coral sea, diverging at ~18 °S into a northward current heading toward the equator and a southward current, the East Australian Current, that forms the western boundary of the south Pacific (Church 1987). Additionally, within the bounds of the Great Barrier Reef, where loggerhead turtles forage, the immediate coastal waters are separated from the oceanic currents by the extensive coral reef system along the eastern margin of the GBR. Waters within the GBR lagoon are subjected to east-west currents in the form of eddies, which, depending upon the size of the domain result in turnover/residence times of oceanic water of up to 60 days, greatly influencing water residence and nutrient cycling (Graham et al. 2010, Andutta et al. 2013).

The Great Barrier Reef also has a smaller range of average water temperatures (~21–25 °C) over a comparative latitudinal range compared to the north west Atlantic (~16–25 °C) (NOAA Physical Sciences NOAA 2018). Water temperatures are known to influence latitudinal gradients in the δ13C isotope signal (Graham et al. 2010). Consequently, the lack of an identifiable latitudinal gradient in the δ13C isotope values of marine turtle tissues on the east coast of Australia may, in part, be due to the absence of a strong water temperature

34 gradient. While these factors are probably contributors to confounding the outcomes, the major reason for the poor predictability of loggerhead turtle foraging regions based on tissue stable isotope values is likely associated with the large variation in diet, and the fact that the variation in δ13C and δ15N from a single region can encompass almost the entire range in variation found along the east coast of Australia.

2.5.2 The influence of diet and foraging environment on isotopic values The successful identification of foraging regions using SIA relies not only upon the presence of regionally systematic variation in stable isotope values, but also upon the diet of a sampled individual being reflective of a specific region and being relatively constant over time. Loggerhead turtles in eastern Australian coastal waters are known to prey upon a variety of benthic prey species including, but not limited to: plankton filtering bivalves, algal grazing gastropods, scavenging crustaceans, predatory invertebrates and discarded bycatch from trawl fisheries (Limpus 2009, Limpus & Coffee 2019). In contrast to green turtles, whose diets are readily determinable by distinct isotopic ranges in consumed autotrophic groups (i.e. red algae, seagrass, mangrove etc.) (Thomson et al. 2018, Chapter 3). The primary producers at the base of food webs in which loggerheads are higher level consumers may be highly variable (algae, seagrasses, benthic macroalgae and phytoplankton) (Limpus 1985, Limpus et al. 2001, Limpus et al. 2013a, Limpus & Coffee 2019). Such varied diets in east Australian loggerheads might explain the wide range in carbon and nitrogen isotopic values within tissues from individuals sampled from the same foraging region. Variation in stable isotope values can also be increased by inherent variation within prey items. For example, in Moreton bay (STEA), loggerhead turtles frequently feed on crustaceans such as mud crabs (Scylla serrata), and the stable isotope values of mud crabs in Moreton Bay vary in relation to their proximity to seagrass (Connolly & Waltham 2015), highlighting that within a foraging area, variation may be observed in different prey items of the same species. Variation in baseline δ13C and δ15N isotopic values have also been linked to anthropogenic sources, including the influence of runoff from agricultural practices (Hobson 2019). The foraging regions for nesting loggerheads on the east coast of Australia (e.g. throughout the GBR and subtropical south east Queensland) are in proximity to major freshwater outflows influenced by agricultural runoff, potentially resulting in sporadic increases in baseline isotopic variation associated with carbon and nitrogen cycles. These factors, along with the observation that the range in variation found in a single foraging area, Moreton Bay, encompasses almost the

35 entire range of values found in nesting loggerhead turtles from the Woongarra Coast, means that the epidermis samples from the nesting loggerhead turtles cannot be used differentiate between different foraging regions with any confidence.

2.5.3 Predictive models using isotopic values The observed ranges of δ13C and δ15N in loggerhead turtles foraging within Moreton Bay covered almost the entire range of isotopic values from all the sampled nesting turtles. Had a discriminant function analysis been performed without high sampling of turtles known to forage in Moreton Bay, a weak, but latitudinally uncorrelated, regional structuring in isotopic values might have been inferred. However, given that almost the entire range of stable isotope values from nesting turtles sampled throughout the 2,000 km north to south distribution could be encompassed by the range of isotopic values from Moreton Bay, different regions could not be reliably assigned based on stable isotope values alone. The results of this study are therefore in contrast with previous works from the Atlantic that identified significant among region differences in turtle tissue isotopic composition, following a latitudinal gradient (Ceriani et al. 2012, Vander Zanden et al. 2015). Strong isotopic structuring in the west Atlantic studies provided effective training for a predictive modelling to then assign foraging regions to turtles with unknown foraging locations. These conflicting results highlight the need to establish the presence of systematic regional variation in primary producer isotopic values before attempting to identify predator foraging regions using predictive modelling. The use of additional tracers, such as δ34S or δ18O may assist in the differentiation between foraging regions (Haywood et al. 2019). For example, in contrast to the results of this study, Pearson et al. (2019) successfully distinguished the foraging areas of nesting individuals (> 400 km apart) from the south Pacific loggerhead nesting stock using δ18O and δ13C isotope gradients in the growth layers of commensal barnacles. Similarly, δ34S isotope, which can vary with proximity to shore (Hobson 2019), when used in tandem with δ13C and δ15N, has been used to determine the foraging regions of green turtles nesting in the Mediterranean sea (Bradshaw et al. 2017). However, given the isotopic variation observed in turtles from one foraging area, it is recommended that future studies continue to ground truth with satellite telemetry and/or CMR data until suitable isoscapes have been resolved (Tucker et al. 2014, Haywood et al. 2019).

2.6 Conclusion This study has demonstrated that SIA, using carbon and nitrogen biogeochemical tracers, cannot reliably identify foraging regions of loggerhead turtles along the east coast of Australia. While SIA has been used successfully in the north-west Atlantic, the results from this study indicate that for reasons not completely understood, there is no systematic regional variation in stable isotope values of carbon and nitrogen. Different oceanic currents, temperatures regimes, and river run-off likely prevent the establishment of region specific unique isoregions, a condition required to identify the foraging region of turtles based on their isotopic values. The δ13C and δ15N isotopic values from sampled tissues of loggerheads from the east coast of Australia do not present predictable latitudinal variation as reported for foraging populations located in the north-west Atlantic (Ceriani et al. 2012, Vander Zanden et al. 2015, Ceriani et al. 2017). Hence, caution must be exercised when conducting predictive analyses of stable isotope data with the purpose of identifying foraging ground locations in migratory species, particularly when samples sizes are small in the training dataset, or the assumptions of regional structuring of isotopic values has not been verified.

Chapter 3

Contributor Statement of Contribution Author: Owen I. Coffee (Candidate) Conception and design (70%) Analysis and interpretation (90%) Drafting and production (75%) Author: David T. Booth Conception and design (30%) Analysis and interpretation (10 %) Drafting and production (25%)

Nesting green turtles of the southern and northern Great Barrier Reef: insights from stable isotope analysis

3.1 Abstract

The south Pacific green turtle population has been the focus of long term-monitoring at genetically distinct key nesting grounds along the east coast of Australia. However, despite the identification of specific foraging regions through capture-mark-recapture (CMR) and satellite telemetry studies, the major foraging regions have not been identified for key green turtle rookeries along the east coast of Australia as CMR and satellite telemetry only allow for the assessment of a small proportion of the nesting population. Stable isotope studies (SIA) can infer diet or migratory movements of marine turtles as demonstrated in recent work that successfully identified foraging grounds in the north west Atlantic. Building from this recent work, this study sought to utilise SIA to examine east coast Australian marine turtle populations. Previous CMR and telemetry studies involving nesting green turtles (Chelonia mydas) from Raine Island in the northern Great Barrier Reef (nGBR) and Heron Island in the southern Great Barrier Reef (sGBR) suggest that most of the individuals for these two genetically distinct populations utilise geographically separate foraging regions. Latitudinal gradients have previously been observed in the carbon (δ13C) and nitrogen (δ15N) isotopic values of sampled turtle tissue from the north-west Atlantic. However, analysis of sampled body tissue (blood and skin) identified the carbon (δ13C) and nitrogen (δ15N) isotopic values of nesting green turtles (Chelonia mydas) from Raine Island (nGBR) and Heron Island (sGBR) could not differentiate between these two genetically separate stocks. The δ13C isotopic range of turtles nesting on Heron and Raine Islands, which are more than 1500 km apart, completely overlapped and could not differentiate individuals from each stock. Despite analysis of δ13C values from seagrasses sampled along the east coast of Australia indicating a weak correlation between seagrass carbon isotopic values and latitude, no association was present between latitude, longitude and δ13C or δ15N values for nesting turtles tracked from the nGBR rookery. This contrasted with studies from other regions of the world.

3.2 Introduction

Investigations identifying the connection between foraging regions and breeding grounds are logistically challenging if migratory species are difficult to sample at their foraging grounds. This is particularly evident in migratory marine species such as marine turtles that are relatively easily sampled at nesting aggregations but infrequently encountered during migrations and within feeding grounds. However, investigations with biogeochemical tracers using stable isotope analysis (SIA), have aided the identification of foraging grounds and the relative contributions of distinctly identifiable foraging regions in different nesting populations of marine turtles (Caut et al. 2008b, Bradshaw et al. 2017, Ceriani et al. 2017).

Analysis of stable isotopes (SIA), most commonly carbon (δ13C) and nitrogen (δ15N) in body tissues, is an established method for determining the source of assimilated nutrients (Deniro & Epstein 1978, 1981). Investigating the isotopic ratios assimilated from prey organisms into the tissues of consumer species can be used to infer the diet or feeding location of that species (Rubenstein & Hobson 2004, Hobson et al. 2010). The identification of isoscapes (e.g. gradients in stable isotope abundance related to oceanic phytoplankton productivity, temperature and prevailing currents) is associated with an increased use of SIA for migratory studies (Goericke & Fry 1994, Graham et al. 2010, Magozzi et al. 2017). Isotopic techniques have been used to investigate marine turtles since the early 1980s (Killingley & Lutcavage 1983), with the integration of SIA with satellite telemetry resulting in the successful assignment of nesting turtles to foraging regions throughout the north-west Atlantic (Seminoff et al. 2012, Vander Zanden et al. 2015, Bradshaw et al. 2017, Ceriani et al. 2017). A review of SIA and satellite telemetry is provided in Chapter 1. Despite the increase of integrated SIA and satellite telemetry research, few studies using SIA and satellite telemetry have attempted to identify foraging grounds of nesting marine turtle populations and the relative contributions of distinct foraging regions to the rookeries in Australian waters (Pearson et al. 2019, Chapter 2). Consequently, the presence of isoscapes and regional isotopic baselines, necessary for the successful application of SIA, are poorly quantified for nesting marine turtle populations in Australia.

Off the east coast of Australia there are three genetically distinct breeding stocks of green turtles, the southern Great Barrier Reef (sGBR), Coral Sea and northern Great Barrier Reef (nGBR). Green turtles are listed as Vulnerable under the EPBC Act. Heron Island in the sGBR and Raine Island in the nGBR are index beaches for their respective genetic stocks and

40 have consistent population monitoring. Capture-mark-recapture (CMR) and satellite telemetry studies have demonstrated that females from these rookeries feed across a wide range of foraging habitats (e.g. coastal seagrass beds, estuaries, coral reefs etc.) (Limpus 2009). Despite this, the relative importance of foraging areas along the Queensland coast and what proportions these different foraging grounds contribute to nesting populations has yet to be resolved. Historic tag recoveries and telemetry indicate that green turtles from sGBR and nGBR may share some foraging regions along the Queensland coastline. However, the majority of recovered tags from females of the nGBR stock indicate the foraging grounds of individuals from nGBR stock are throughout the northern extents of the Great Barrier Reef, the Gulf of Carpentaria, Torres Strait and the Arafura sea (Limpus 2009). Consequently, it was hypothesised that the majority of turtles from these two stocks would have geographically separate foraging grounds (Limpus et al. 1992a, Limpus et al. 2003, Dethmers et al. 2006, Limpus 2009) and thus different isotopic signals, as has been previously reported for nesting populations of loggerhead turtles (Caretta caretta) in the northwest Atlantic (Ceriani et al. 2014, Vander Zanden et al. 2015).

The oceanic currents off the east coast of Australia originate from the Coral sea and bifurcate at ~ 18 °S (Church 1987), one branch heading north and the other heading south, potentially facilitating the development of unique baseline δ13C and δ15N values either side of this latitude. Additionally, the currents within the Gulf of Carpentaria (GoC) originate from the west, in the Arafura sea and are effectively isolated from the east coast by Cape York (Wolanski & Hamner 1988). Therefore, if these foraging grounds have regionally distinct baseline isotopic values, then SIA of the body tissue of nesting female could be used to determine the contribution of these feeding areas to their respective nesting populations (Pajuelo et al. 2012, Tucker et al. 2014). This method has been successfully applied to studies of loggerhead turtles along the east coast of the United States, where nesting loggerhead turtles were successfully assigned to one of five distinct foraging regions distributed throughout the Gulf of Mexico (GoM) and the north west Atlantic (Vander Zanden et al. 2015, Ceriani et al. 2017).

The aims of this study were to: (1) examine the stable isotope profiles of green turtles nesting at two geographically distant sites (1500 km apart), one in the nGBR (Raine Island), the other in the sGBR (Heron Island) to determine if the two different genetic stocks can be distinguished based on their stable isotope values; and (2) by comparing the stable isotopic

41 values of nesting turtles with known foraging regions identified by satellite telemetry, establish if within the nGBR nesting population, distinct foraging areas could be inferred from the existence of unique stable isotope profiles.

3.3 Materials and methods

3.3.1 Study sites and sampling procedures Heron Island (23.442 °S, 151.915 °E) in the southern Great Barrier Reef hosts significant numbers of nesting green turtles from the sGBR breeding stock (Limpus 2009). Raine Island (11.590 °S, 144.035 °E) is located on the outer edge of the northern Great Barrier Reef and is part of the Raine Island National Park (Scientific), hosting the largest remaining green turtle rookery in the world and the primary nesting site for green turtle of the nGBR (Limpus et al. 2003). Across four austral summer nesting seasons (2015 ̶ 16, 2016 ̶ 17, 2017 ̶ 18 and 2018 ̶ 19), 176 and 186 nesting females were sampled from Heron and Raine Islands.

Tissue samples were obtained from nesting females prior to egg chamber excavation or directly following oviposition. The midline curved carapace length (CCL) of each turtle was measured using a fibreglass measuring tape (± 0.2 cm). All turtles were identified using numerically-coded titanium flipper tags and processed following Queensland Turtle Conservation Project protocol (Limpus 1992, Limpus et al. 1994b). The trailing edge of the fore flipper between the keratinised scales was swabbed with 70 % ethanol and an 0.5 cm2 skin sample was taken using a sterile scalpel and stored in an aqueous saturated NaCl solution until stable isotope analysis. As observed by Barrow et al. (2008), preservation in NaCl solution has no significant effect on δ13C and δ15N isotopic signals. Although empirical turnover periods have not been determined for adult green turtles, insights from large juvenile loggerheads would suggest an estimated tissue turnover rate in adult turtles epidermis of 4 ̶ 6 months (Reich et al. 2008). Consequently, the δ13C and δ15N values of sampled epidermis were deemed to represent the diet of the home foraging region of sampled individuals.

A review of previous SIA studies on primary producers along the Queensland coastline was conducted to gather reference δ13C values of seagrasses throughout the potential foraging regions of the sampled nesting populations. Identified studies were refined by location and the preservation and analysis methods used. A total of five previous studies were identified

42 with reference δ13C values of seagrasses distributed along the east coast of Queensland including samples collected for Chapter 5. Except for Fry et al. (1983), all collected samples were frozen at ̶ 17°C before being oven dried and ground for isotopic analysis. This analysis highlighted a paucity of SIA studies on seagrass and algae along the coastline of Australia. Consequently, in order to provide an indicative reference value for the Torres Strait, a deviation in the standard preservation method was required. Samples collected and analysed by Fry et al. (1983) were acidified with weak hydrochloric acid before being oven dried and ground for analysis. A subsequent analysis on the influence of acid treatment on δ13C and δ15N ratios determined acidification was attributed to changes of < 1 ‰ but that larger effects could occur (Schlacher & Connolly 2014). As a result, any inference of latitudinal trends of δ13C and δ15N are limited until further plant samples are collected and analysed.

Table 3.1. Reference δ13C values for green turtle forage items sampled from neritic Queensland waters.

Species δ13C Location Latitude Longitude Source

-8.4

-9

-8.6

-9.1

-8.5 Halodule sp. Thursday Is, Torres Strait -10.58 142.2 (Fry et al. 1983) -8.6

-9.1

-7.9

-10

-9.9

-7.8 Cymodocea serrulata -8.1 Ingram Island, Nth Qld -14.43 144.89 Chapter 5 Halophila ovalis -6.6

Zostera capricorni -8.5

Halodule uninervis -10.3 Shoalwater Bay, Cen. Qld -22.33 150.23 (Brine 2008)

Halodule uninervis -11.7

Halophila ovalis -9.6 Port Curtis, Cen. Qld -23.79 151.31 (Prior et al. 2016)

Zostera capricorni -8.6

-13.5

Halodule pinifolia -11.0

-15.2

-11.9

-9.9 Port Curtis, Cen. Qld -23.79 151.31 Chapter 5 Halophila ovalis -12.6

-11.0

-10.4

-12.8 Zostera capricorni -13.2

Halodule uninervis -11.6

Halophila ovalis -12.4 Hervey Bay, Cen. Qld -25.3 152.93 (Cameron 2007)

Zostera capricorni -10.8

Halophila ovalis -12.2 (Brine 2008) Moreton Bay, Sth Qld -27.37 153.38 Zostera sp. -9.9

3.3.2 Satellite telemetry Of the 186 turtles sampled at Raine Island, the locations of the foraging grounds of forty individuals were provided by a collaborative satellite telemetry study which used FastLoc GPS transmitters as part of the Raine Island Recovery Project (Fig. 3.1). (Raine Island Recovery Project, unpublished data). These locations were categorised into three broad geographic foraging regions; Gulf of Carpentaria (GoC, n= 14 turtles), Torres Strait (TS, n= 15 turtles) and the northern Great Barrier Reef between Turtle Head Island (10.92 °S, 142.68 °E) and Cooktown (15.47 °S, 145.25 °E) (nGBR, n = 11 turtles) (Fig. 3.1). These broad foraging regions were defined with an expectation that differences in prevailing currents in this region (Church 1987, Wolanski 1993) would result in region specific isoscapes that would allow green turtles to be assigned to one of these regions based on their epidermal isotope values. Each area encompassed migratory distances from foraging ground to nesting ground of between 100 and 1200 km.

3.3.3 Sample preparation and analysis

Tissue samples were prepared for stable isotope determination as detailed in Chapter 2.

3.3.4 Statistical Analysis All statistical analyses were conducted using R and RStudio user interface (RStudio Team 2016, R Core Team 2017). Hierarchical cluster analyses were used to identify whether δ13C and δ15N isotopic values of turtle epidermis differed between sampling seasons within each nesting cohort (sGBR and nGBR). A subsequent cluster analyses compared pooled seasons for the two nesting cohorts to determine if nesting green turtles from Raine Island (nGBR) could be discriminated from green turtles nesting on Heron Island (sGBR) based on their δ13C and δ15N isotopic profiles. To centre values and reduce bias borne from measurements of variables on different scales, all isotopic values were standardised to z-scores prior to analysis (Suarez-Alvarez et al. 2012). Following the calculation of Euclidean distances, diagnostic plots were produced to identify if groups designated by hierarchical clustering aligned with seasons or with the sampled genetic stocks.

To establish if δ13C and δ15N isotopic profiles from satellite tracked individuals were unique to foraging ground location, a comparison of foraging regions established by satellite telemetry and clusters based on Euclidean distance between the δ13C and δ15N isotopic values of each sampled individual through hierarchical cluster analyses was performed. No association was identified between foraging regions. A consequent regression analysis, using reported δ13C isotopic values of seagrass from along 2300 km of Queensland coastline from Moreton Bay in the south to the Torres Straits in the north (Table 3.1), was used to investigate if isotopic δ13C values varied in a systematic way with latitude as reported for primary producers (i.e. seagrasses and algae) in the north Atlantic ocean (Goericke & Fry 1994, Pajuelo et al. 2012, Vander Zanden et al. 2015).

3.4 Results

3.4.1 Epidermis isotopic variation across season and breeding stocks Hierarchical cluster analysis of δ13C and δ15N isotopic values from turtles sampled over subsequent seasons from Heron Island (sGBR) and Raine Island (nGBR) rookeries indicated that dissimilarities by Euclidean distance were not associated with season, allowing subsequent analyses to pool data from turtles within each rookery across seasons (Fig. 3.2). A cluster analysis was used to classify the δ13C and δ15N isotopic values of all turtles from both the pooled sGBR and nGBR breeding stocks into two clusters. However, these two clusters did not associate with breeding stocks, with each cluster composed of ~ 50 % of turtles from each breeding stock (Fig. 3.3).

Table 3.2. The summarised means and isotopic ranges of individuals sampled at Raine Island that have their residential foraging grounds in three different regions. δ13C (‰) δ15N (‰) Region n = Range Mean (± s.d) Range Mean (± s.d)

northern Great Barrier Reef 11 -15.1 ̶ -9.7 -12.08 (1.69) 2.7 ̶ 9.1 6.41 (1.82)

Torres Strait 15 -17.2 ̶ -9.0 -13.31 (2.58) 5.3 ̶ 7.8 6.67 (0.81)

Gulf of Carpentaria 14 -20.4 ̶ -8.8 -12.64 (3.40) 4.6 ̶ 13.4 7.34 (2.06)

3.4.2 Comparisons of epidermis δ13C and δ15N from different locations within the nGBR stock To identify if the δ13C and δ15N isotopic values of sampled individuals were associated with the location of their foraging grounds, a hierarchical cluster analysis was performed on the 40 satellite tracked turtles from the nGBR stock. Clusters defined by hierarchical analysis using the δ13C and δ15N isotopic values of sampled turtles and the latitude and longitude of their foraging grounds were not wholly associated with the outlined foraging regions (Fig. 3.4). Despite 79 % of turtles from the Gulf of Carpentaria differentiating into two distinct clusters, the remaining individuals from this region were not associated with these two clusters. The isotopic ranges of individuals inhabiting each of the define regions completely overlapped, confounding the determination of unique isoregions (Table 3.2).

3.4.3 Isotopic analysis of primary producers Based on the range of epidermis δ13C values observed in the sampled turtles (Fig. 3.3) and the range of reference δ13C values of seagrasses sampled along the east coast of Australia from previous studies (Table 3.1), > 50 % of turtles had tissue δ13C values consistent with a diet of predominantly seagrasses. A subsequent regression analysis identified a weak correlation between δ13C values of seagrass sampled along the east coast of Australia and 2 13 latitude (r = 0.76, F1, 4 = 12.77, p = 0.02), with a trend of enrichment in δ C values with decreased latitude (Fig. 3.5).

Figure 3.5. Mean reference δ13C values of seagrasses sampled from foraging grounds along the eastern Australian coastline. Data from the previous studies listed in Table 3.1. 51

3.5 Discussion

This study sought to assess consistency of epidermis isotopic profiles taken from green turtles across nesting seasons and to ascertain whether SIA could distinguish between the genetically different breeding stocks of the nGBR and sGBR. However, the range of isotopic values from individuals within these two stocks overlapped entirely, such that nGBR and sGBR female green turtles were unable to be discriminated based on SIA. In addition, by integrating the observed δ13C and δ15N isotopic values with feeding ground location data obtained through satellite telemetry on a subset of turtles nesting on Raine Island, the study aimed to determine if feeding ground region could be identified by isotopic values. A turtle’s foraging region could not be distinguished based on its epidermis δ13C and δ15N values due to the overlapping range of isotopic values from different foraging regions. An analysis of δ13C values from seagrasses sampled along the eastern Australian coast indicated an association between latitude and δ13C values. However, the small sample size of seagrass sampled and the lack of standardised preservation methods means that this apparent relationship must be treated with caution. Despite an association with latitude, the variation in δ13C for seagrasses along the east coast Australia was within the range of SI values observed for satellite tracked green turtles inhabiting the three identified foraging regions and thus not significant enough to aid in differentiating nesting turtles into their respective foraging grounds.

Green turtles nesting on both Heron Island (sGBR stock) and Raine Island (nGBR) had a wide range of both δ13C and δ15N which encompassed the carbon isotopic values reported for seagrasses, algae and mangrove materials observed from previous studies along the east coast of Australia (Fry et al. 1983, Cameron 2007, Brine 2008, Chapter 5). However, hierarchical cluster analysis indicated that these variations were not associated with sampling year. Hence, there were no inter-year differences in the range in diet of turtles from either nesting location, possibly indicating an isotopic consistency in the diet of sampled individuals at foraging grounds across years. The lack of inter-year variation allowed samples to be pooled across years for the comparisons between the Raine Island and Heron Island nesting populations.

A hierarchical cluster analysis was used to independently group turtles based on Euclidean distances of their epidermis δ13C and δ15N values into two clusters. These two clusters were then compared to the turtle’s breeding stock. It was expected the majority of turtles from these two stocks would have geographically separate foraging grounds (Limpus et al. 1992a,

Limpus et al. 2003, Dethmers et al. 2006, Limpus 2009) and thus different isotopic signals, as previously reported for nesting populations of loggerhead turtles (Caretta caretta) in the northwest Atlantic (Ceriani et al. 2014, Vander Zanden et al. 2015). However, the isotopic ranges of sampled tissue did not cluster turtles according to their nesting location, as there was no statistical association between epidermal isotopic values and nesting location.

As no isotopic differentiation was established at a genetic stock scale, subsequent analysis sought to identify if, within the nGBR breeding stock, individuals would cluster according to foraging region. Three broad foraging regions (GoC, TS and nGBR) were chosen with an expectation that these would differentiate because of differences in the prevailing oceanic currents in each region (Church 1987, Wolanski 1993). Despite two of the hierarchical clusters including most of the sampled turtles within the Gulf of Carpentaria foraging ground, no distinction was apparent in isotopic values between clusters. This result supported conclusions drawn from the nGBR and sGBR stock comparison, of a poor association between δ13C and δ15N values in turtle tissue and foraging grounds. Hence, green turtles nesting along the east coast of Australia cannot be located to their feeding grounds based on their epidermis isotopic values. This is in contrast with studies that have successfully used isotopic analyses to identify foraging regions of nesting turtle populations in other regions of the world (e.g. Gulf of Mexico; Vander Zanden et al. 2015, Mediterranean Sea; Bradshaw et al. 2017, North west Atlantic; Ceriani et al. 2017). However, these results are consistent with results from an analysis of nesting loggerhead turtles from the Australian east coast, which concluded that nesting female’s foraging regions could not be identified based on δ13C and δ15N epidermis values (Chapter 2).

For the successful resolution of distinct foraging grounds using SIA, differences in baseline isotopic values need to exist between different foraging regions. For example, along the eastern coast of north America and in the Gulf of Mexico (GoM) regionally significant distinctions in the isotopic ranges of sea turtles based on their geographic location allow the identification of feeding region, with individuals inhabiting foraging grounds within the GoM having depleted δ13C values but enriched δ15N values relative to turtles foraging throughout the subtropical northwest Atlantic and the South Atlantic Bight (Pajuelo et al. 2012, Vander Zanden et al. 2015, Ceriani et al. 2017). The differences in northern hemisphere baseline isotopic values were associated with an increase in latitude following the northward current, which is linked with the loop current of the GoM (Schmitz & Richardson 1991, Lee & Mellor

2003, Reverdin et al. 2003). However, along the east coast of Australia, a significant isotopic gradient may be prevented from forming due to the unique bathymetry of the great barrier reef buffering a unidirectional nutrient flow (Wolanski & Hamner 1988). A persistent current originating in the Coral sea flows westwards and hits the GBR at about 18°S where it bifurcates into north and south flowing currents. Higher resolution of seagrass samples north and south of this bifurcation point would resolve if current direction is associated with seagrass δ13C values.

3.6 Conclusion

This study is the second to report that SIA of tissue from nesting sea turtles cannot be used to identify feeding regions due to the lack of discernable regionally distinct δ13C and δ15N isoscapes along the east coast of Australia (see Chapter 2). This differs from other regions of the world where regionally distinct isoscapes have been identified and used to trace feeding regions of nesting turtles. This study provides the first reference values of the isotopic range in δ13C and δ15N for nesting green turtles along the east coast of Australia. There was no correlation with isotopic values and foraging region identified by satellite tracked turtles from green turtles nesting at Raine Island. This lack of regionally distinct variation in δ13C and δ15N values from the nGBR is why SIA cannot be confidently used to identify foraging regions of green turtles nesting on Raine Island.

Chapter 4

Diet and stable isotopic composition of loggerhead turtles in a subtropical foraging ground.

4.1 Abstract

Baseline isotopic variation within foraging grounds presents a potential confounding element when SIA is used to infer the foraging regions of migratory marine species. Faecal sampling and stable isotope analysis of body tissue was used to explore the dietary composition and isotopic variation of thirty foraging loggerhead turtles in Moreton Bay, Queensland. Faecal samples were obtained during a brief period of captivity from a sub-sample of ten turtles caught on the eastern banks of Moreton Bay and identified Portunid crustacea as the predominant food item. Molluscan prey from the families Batillaridae, Mytilidae and Bivalva were frequently present in the faecal samples as were volumes of gravel consistent with infaunal mining behaviours previously observed in loggerhead turtles foraging in Moreton Bay. Isotopic analysis of blood and epidermis samples identified a broad range of δ13C (-9.4 to ̶ 16.2 ‰) and δ15N (7.1 to 12.4 ‰) suggesting turtles feed on a broad range of food items. However, no associations between SI values and sampling period or location of capture were found. Comparisons of δ13C values, between blood plasma (short turnover) and epidermis (long turnover), suggested most sampled individuals had isotopically similar diets when these tissues were formed. Digesta transit and turnover times of plasma cells are similar for loggerhead turtles, consequently it was hypothesised that δ13C and δ15N values of plasma should correlate with prey observed in faecal samples. Based on this reasoning, a cluster analysis tested if the δ13C and δ15N values of turtles, sorted into groups by k-means, could be related to the food items identified by faecal sampling. However, no such association was found. Faecal samples from individuals with predominantly Portunid prey had isotopic values encompassing the ranges from individuals feeding on other prey taxa. Considering the variety of habitat types within the potential foraging ranges of sampled individuals, these results may reflect the input of more readily digestible prey items not represented in the sampled faecal material. This study is the first to report isotopic values in foraging loggerhead turtles from the south west pacific stock and documents significant variation in isotopic values. If similar degrees of isotopic variation are observable at other key foraging regions of this genetic stock

56 it is unlikely SIA can successfully identify foraging regions based assimilated isotopic values of loggerhead turtle tissue.

4.2 Introduction

In marine turtles, establishing foraging behaviour is particularly important because foraging grounds are increasingly at risk from anthropogenic threats (e.g. commercial and recreational vessels, dredging, fishing, increased runoff and coastal developments). For loggerhead turtles of the south west Pacific, which have historically been affected by anthropogenic activities and are currently listed by the IUCN Red List as Critically Endangered (Limpus & Casale 2017), documenting the dietary composition and associated foraging behaviours of this population is necessary for the identification and management of critical habitat. The relatively few studies which have investigated the foraging and diet composition of loggerhead turtles from this region have documented a diverse and variable array of prey taxa with over 90 benthic and near benthic taxa documented (Preen 1996, Limpus et al. 2001, West 2007, Boyle & Limpus 2008, Limpus et al. 2008). Moreton Bay, in south east Queensland, is surrounded by an urbanised environment, supporting significant recreational and commercial activities which pose a risk to the reasonably high density of foraging loggerhead turtles from the south west pacific genetic stock that inhabit the area (Limpus 2009). Investigations into the dietary compositions of these Moreton Bay residents are valuable for refining management actions to preserve the population from anthropogenic threats.

Diet analysis has traditionally been restricted to sampling of deceased, harvested, or by-catch individuals (Moody 1979, Van Nierop & Hartog 1984, Ross 1985), or more recently, the collection of digesta samples by oesophageal lavage or faecal sampling techniques (Forbes & Limpus 1993, Brand et al. 1999). Despite these methods providing valuable observations on dietary composition, they typically only represent a snap shot of foraging behaviour (Casale et al. 2008, Frick et al. 2009). Previous studies conducted in Moreton Bay have used faecal analysis to examine diet in loggerhead turtles (Limpus et al. 2001, West 2007). The diet of loggerhead turtles included hard shelled molluscs which require strong jaws and jaw muscles to ingest so oesophageal lavage is risky and difficult to perform successfully. Consequently, the collection of faecal material is the preferred method for dietary sampling in this species.

However, faecal content only provides a snap shot and due to digestive processes, typically under-represents soft bodied prey items (Casale et al. 2008). Stable isotope analysis (SIA) has been increasingly used to investigate dietary compositions in sea turtles over longer time frames than oesophageal lavage, or faecal sampling can provide (Arthur et al. 2009, Lemons et al. 2011, Allen et al. 2013, Prior et al. 2016).

Stable isotope analysis can provide information on foraging location and approximate diet (reviewed in Chapter 1). Unfortunately, the baseline isotopic values of the prey items of foraging loggerhead turtles in Moreton Bay have not been determined. In addition to providing insights into longer term dietary trends, establishing baseline isotopic values at foraging grounds will conclude if foraging regions can be defined using SIA on individuals of this genetic stock at nesting rookeries (Chapter 2). Using isotopic analysis and faecal sampling, this study sought to compare the dietary composition and range in isotopic values of sampled tissue for residents of Moreton Bay, Queensland to infer potential baseline isotopic values for this foraging region. Individuals caught foraging were sampled for SIA (blood and skin tissues), with a subset of captured loggerhead turtles briefly held in captivity to determine dietary compositions by faecal sampling. Isotopic values of plasma tissue were used to infer inter-individual variation in diet and compared to prey identified from faecal samples to test for identifiable trends.

4.3 Materials and Methods 4.3.1 Study site Situated on the sub-tropical eastern coast of Australia at the outlet of the Brisbane River, Moreton Bay (27.394 °S, 153.314 °E), is a wedge-shaped embayment sheltered from the south-west Pacific Ocean by North Stradbroke and Moreton Islands (Brand-Gardner et al. 1999). Moreton Bay supports a diverse array of habitats including sandy bottomed seagrass meadows, rocky reefs and fringing mangroves. Resident loggerheads of Moreton Bay belong to the south west Pacific genetic stock and contribute, upon maturity, to the nesting populations of this Critically Endangered stock on the mainland beaches of the Woongarra coast (between Bundaberg and Agnes Water, Central Queensland) and the islands of the southern Great Barrier Reef and New Caledonia (Limpus & Casale 2017, Limpus & Coffee 2019).

4.3.2 Capture procedure Outside of the nesting period, between July 2015 and October 2017, 30 loggerhead turtles were sampled in the Marine Protected Areas of the shallow Eastern Banks to the west of Moreton and North Stradbroke Islands. Loggerhead turtles were captured opportunistically across the Eastern Banks region by the rodeo techniques (Limpus & Reed 1985). Upon capture, if no tags were present, turtles were tagged on the trailing edge of their front flippers with a numerically coded titanium tag and curved carapace length measured (CCL) following the Queensland Turtle Conservation Project protocol (Limpus et al. 1994a). Turtles were classified into age classes based on CCL, with individuals between 65 – 85 cm CCL classified as sub-adult and those greater than 85 cm CCL as adults (Limpus & Reed 1985, Limpus 2009). In both sub-adults and adults, sex was determined by relative tail length

(Limpus and Limpus (2003a). Turtles were sampled aboard the research vessel and, except for those held captive for faecal sampling, released at the point of capture within an hour. A total of twelve faecal samples were collected during two sampling periods (September 2015 & August 2016) from a subset of ten turtles. These individuals were held in captivity to collect faecal material and released within seven days of capture. To investigate if diet was associated with specific location, the feeding location in which a turtle was captured was classified into sectors as defined by the Queensland Turtle Conservation Project (Limpus et al. 1994a) (Fig. 4.1). Most individuals were caught on sandy sub-tidal seagrass beds, except for those captured in sector 4, which is centred on a sink hole surrounded by disused oyster leases and sporadic rocky reef outcroppings.

4.3.3 Tissue Sampling A ~ 0.5 cm2 skin sample was taken from each turtle from the trailing edge of the fore flipper between the keratinised scales using a sterile scalpel following sterilisation of the sample site with 70 % ethanol. All skin samples were stored in 70 % ethanol until analysis. Storage of samples in 70 % ethanol has no significant effect on the δ13C and δ15N isotope signal (Barrow et al. 2008). A 3 mL blood sample was collected from the dorsal cervical sinus (a dorsal branch of the jugular vein) using a sterile single-use syringe connected to an 18-gauge needle, and was stored in a heparinised container to prevent clotting prior to centrifuging (Owens & Ruiz 1980). Heparin does not influence the δ 15N signal in sea turtle blood (Lemons et al. 2012). Within one hour of sampling blood samples were separated into plasma and red blood cells (RBC) by centrifuging at 9000 rpm for 5 min and each subsequently stored at ̶ 18 °C until isotopic analysis.

4.3.4 Faecal Sampling and Analysis A subset of ten loggerhead turtles were transferred to a captive holding facility in order to sample faecal material voided over a seven-day period. These turtles were transported to the University of Queensland’s Moreton Bay Research Station, North Stradbroke Island (27.496 °S, 153.399 °E) where they were held in individual 1.8 m diameter tanks. Each tank was filled to 0.8 – 1.0 m depth with fresh sea water which was changed daily. Turtles were fitted with a Lycra® harness (modified ‘rash’ vest/swim shirt) with a detachable ‘nappy’ attached and positioned over the cloaca to capture eliminated faecal material for the duration of the holding period. The ‘nappy’ vinyl collection bag captured the majority of eliminated faeces

60 with any further suspended faecal material collected from within the tank using nets (2 mm mesh). Captive turtles were not fed during the holding period. Throughout the holding period, nappies were inspected at 3 h intervals, and any defecated material removed immediately and stored in 70 % ethanol until analysis. Over the duration of the holding period at least one faecal sample, though in a few instances multiple, were collected from each captive individual.

4.3.5 Stable Isotope Analysis Blood and skin tissue samples were prepared for stable isotope analysis following the protocols outlined by Reich et al. (2008). Skin samples were rinsed with distilled water and surface fouling (i.e. algae and other epiphytic growth) removed using a sterilised scalpel blade. Dermal tissue was removed, and surface epidermis was finely diced. Plasma, blood cells and epidermal samples were oven dried at 50 ̶ 60 °C for 48 ̶ 72 h in individual sample tubes. Dried plasma and blood cells were each ground with 5 mm glass beads by a Qiagen TissueLyser II (Venlo, Netherlands). The low lipid content (C:N < 3.5) of these tissues indicated that chemical lipid extraction was not necessary prior to stable isotope analysis (Post et al. 2007). Following drying, 1.5 ̶ 2.5 mg of each tissue type was measured into standard weight tin capsules and analysed using an Elementar Vario Cube elemental analyser (Frankfurt, Germany) coupled with an IsoPrime continuous flow stable isotope ratio mass spectrometer (EA-IRMS, Micromass, UK). Stable isotope values were expressed using δ notation, defined as parts per mil (‰) as per: Rsample δ = (( ) -1) × 1000 Rstandard

13 12 15 14 where Rsample is the ratio of heavy to light isotopes ( C/ C or N/ N) and Rstandard is the isotope ratio for the corresponding international standards of Vienna PeeDee Belemnite (VPDB) for carbon, and atmospheric air for nitrogen (Peterson & Fry 1987). Throughout analysis technical standards were run every 20th sample with a subsequent precision of ± 0.1 ‰ for δ13C and ± 0.2 ‰ for δ15N.

4.3.6 Statistical Analysis Faecal analysis Prey items in collected faecal samples from turtles held in captivity were separated into taxonomic groups and identified to the level of family. Family-grouped prey item samples

61 were oven dried at 50-60 °C until constant weight. Dietary composition was calculated as the proportion of each prey grouping’s dry weight divided by the dry weight of the entire sample.

Stable Isotope Analysis (SIA): temporal and spatial variation To investigate the possibility of temporal variation in stable isotopes in the epidermis of sampled loggerhead turtles, ANOVA was used to compare epidermal isotopic ratios across the seven sampling periods (2015 ̶ July, September; 2016 – March, August, September; 2017 – May, September). To determine if stable isotopic variation was associated with capture location, ANOVA and Tukey post-hoc comparisons compared epidermal δ13C and δ15N across the sector locations (Fig. 4.1) within the Eastern Banks region of Moreton Bay.

Stable Isotope Analysis: body tissue variation Plasma δ13C stable isotope values were compared to epidermal δ13C to determine if diet composition had changed significantly between the times when these tissues were formed. To this end, δ13C stable isotope values for plasma and epidermis from each individual turtle were plotted and compared to a theoretical ‘no change in diet’ line (Prior et al. 2016), that predicts epidermal stable isotope values from plasma stable isotope values based on the fractionation values of these tissues (Reich et al. 2008). As tissue fractionation values for plasma and epidermis have not yet been defined for sub-adult and adult loggerhead turtles, discrimination factors from adult green turtles were chosen as the best available factors for analysis (Vander Zanden 2012). Despite their dietary differences, adult green turtle discrimination factors are the only available factors of an adult marine turtle species and consequently were judged as more likely to reflect the slowed metabolic rate of a mature loggerhead turtle than the available discrimination factors for juvenile loggerheads. As a result, recorded significance should be considered with caution until species specific discrimination factors can be established. A difference of more than two standard deviations from the mean (± 30 %) between the observed stable isotope values and the theoretical ‘no change in diet’ value was judged as a sufficient change to constitute a shift in dietary composition between the times that epidermis and blood plasma formed based on the methods described by Prior et al. (2016).

Integrated SIA and faecal analyses Plasma tissue is estimated to have the fastest cell turnover rate of sampled tissues based on tissue turnover periods in hatchling and juvenile loggerhead turtles (ranging 18.5 ± 4.5 to 39.6 ± 9.1 days) (Reich et al. 2008). Digesta takes approximately two weeks to transit through a loggerhead turtle digestive system (Valente et al. 2008). Consequently, it was hypothesised that the observed plasma isotopic ratios most likely represented an integrated assimilation of the recent diet of a sampled turtle (Seminoff et al. 2007, McClellan et al. 2010). It was further hypothesised that isotopic values of turtle plasma were likely to reflect the assimilated isotopic values of the predominant prey items identified in each faecal sample (as identified by remnant undigested material, i.e. body, shells and opercula etc.). A k-means cluster analysis was performed to identify overlay between the isotopic composition of prey in faecal samples and the δ13C and δ15N of sampled plasma. In addition to the individuals used for faecal sampling, the plasma values from all sampled turtles were included to investigate if the clusters predicted the diets for these individuals. A scree plot of the eigenvalues determined by cluster analyses was used to identify the number of clusters that best differentiated similarities in isotopic values (Boyd et al. 1994, Page et al. 2006). These subsequent clusters were compared in a diagnostic plot to determine if the clusters generated from faecal sampling data could be associated with clusters generated from tissue isotopic data.

4.4 Results 4.4.1 Diet composition through faecal analyses Faecal samples from wild-caught loggerhead turtles foraging on the eastern banks of Moreton Bay consisted of diverse hard prey remains that could be identified macroscopically. Faeces included animal remains from 10 different families within Crustacea (e.g. claws and exoskeleton fragments), Mollusca (e.g. shells and opercula), Echinodermata (e.g. test and spines), Tunicata (e.g. test) and Annelida (e.g. setae) (Table 4.1). Exoskeleton from crustacea of the family portunidae were most frequently observed (93 %) in collected faeces. Similarly, molluscan shell fragments were present in 57 % of collected samples with the most common prey family Batillaridae, which was observed in 36 % of samples. Marine detritus (e.g. sand and gravel) (57 % of samples) as well as seagrass (43 %) were commonly observed in collected samples and assumed to be incidentally ingested during foraging activities (Table 4.1). Plastic ingestion was observed in one faecal sample (Q23607). Taxa of the orders,

Echinodermata, Tunicata and Annelida were observed in a single sample from different individuals.

Table 4.1. Identified prey items in faeces of sampled loggerheads identified to lowest possible taxa. Dietary composition expressed as the proportion of the total dry weight for each sample.

Sample ID Collection date Ses Identified Items (Class/Family) Avg Dry Weight (g) Proportion Q23607 10/09/2015 M Portunidae 116.113 0.874 Marine Detritus (sand etc.) ** 6.970 0.052 Batillariidae 6.843 0.051 Seagrass (Zosteraceae) ** 2.843 0.021 Plastic 0.130 0.001 Total 132.900 Q23607 12/09/2015 M Portunidae 31.677 0.721 Seagrass (Zosteraceae) ** 7.540 0.172 Batillariidae 3.713 0.085 Marine Detritus (sand etc.) ** 1.000 0.023 Total 43.930 Q23620 12/09/2015 F Portunidae 41.087 0.725 Marine Detritus (sand etc.) ** 14.787 0.261 Gastropoda* 0.790 0.014

Total 56.663 Q23620 13/09/2015 F Portunidae 36.063 0.993 Marine Detritus (sand etc.) ** 0.260 0.007 Total 36.323 Q23605 12/09/2015 M Mytilidae 479.533 0.983 Seagrass (Zosteraceae) ** 3.420 0.007 Batillariidae 3.200 0.007 Pinnidae 1.867 0.004 Total 488.020 Q23589 12/09/2015 M Batillariidae 50.927 0.885 Holothuriidae 4.577 0.080 Portunidae 1.140 0.020 Seagrass (Zosteraceae) ** 0.923 0.016 Total 57.567 Q23586 13/09/2015 M Portunidae & Diogenidae 77.577 0.985 Echinometridae 1.130 0.014 Marine Detritus (sand etc.) ** 0.083 0.001 Total 78.790

Sample ID Collection date Ses Identified Items (Class/Family) Avg Dry Weight (g) Proportion Q23610 13/09/2015 M Marine Detritus (sand etc.) ** 2.003 0.337 Portunidae 1.233 0.208 Seagrass (Zosteraceae) ** 1.170 0.197 Apluousobranchia 0.797 0.134 Batillariidae 0.737 0.124 Total 5.940 N86078 31/08/2016 M Portunidae 51.909 0.941 Gravel** 2.821 0.051 Gastropoda* 0.280 0.005 Unknown 0.114 0.002 Seagrass (Zosteraceae) ** 0.015 0.000 Total 55.138 N86078 3/09/2016 F Gravel** 204.467 0.917 Portunidae 18.477 0.083 Seagrass (Zosteraceae) ** 0.080 0.000 Total 223.023 N86075 1/09/2016 U Portunidae 31.680 1.000 Total 31.680 N86076 4/09/2016 M Aphroditidae 3.693 0.715 Portunidae 1.470 0.285 Total 5.163 N86075 4/09/2016 U Portunidae 28.723 1.000 Total 28.723 N86077 3/09/2016 U Portunidae 33.493 0.821 Bivalva 7.110 0.174 Seagrass (Zosteraceae) ** 0.210 0.005

Total 40.813 * Insufficient sample for further identification ** Incidental ingestion

4.4.2 Temporal and spatial variation in epidermal isotopic values The mean epidermal δ13C values from the seven sampling periods ranged from -13.0 to -11.5 ‰, whilst δ15N values ranged from 9.9 to 11.8 ‰. There was no difference in mean values of 13 15 δ C (ANOVA, F6, 38 = 1.921, p = 0.102) or δ N (F6, 38 = 1.113, p = 0.373) from epidermal 13 tissue amongst the seven sampling periods, and no difference between δ C (F5, 39 = 0.77, p = 15 0.577) or δ N (F5, 39 = 1.239, p = 0.31) with foraging location, i.e., amongst the sectors on the Eastern Banks.

4.4.3 SIA: Body tissue variation Tissue by tissue comparison of δ13C values of blood plasma and epidermis from 27 turtles were similar, indicating that diet remained unchanged for most of the sampled cohort between the periods represented by turnover rates of the plasma and epidermis (Fig. 4.2). Three of the turtles sampled had δ13C values that fell outside the 30 % confidence limits around the no change diet line (Fig. 4.2), suggesting a change in the composition of diet/ foraging location between the times that plasma and epidermis were formed. Two individuals presented an enrichment in δ13C within their blood plasma compared to their epidermal δ13C whilst a third had depleted δ13C.

4.4.4 Integrated SIA and faecal analyses The assimilated δ13C and δ15N values of tissues from sampled individuals with unknown dietary compositions were compared to the values of individuals with diets inferred from faecal sampling to identify similarities in isotope compositions. Plasma isotopic values from the sampled cohort ranged from – 9.4 to – 16.2 ‰ δ13C and 7.1 to 12.4 ‰ δ15N. Turtles with predominantly Portunidae in their faecal samples had plasma δ13C values in the range – 9.4 to – 14.7 ‰, encompassing the range of δ13C values from turtles with different dominant food items determined by faecal sampling. Consequently, despite conducting a hierarchical cluster analysis on the δ13C and δ15N values of all sampled turtles, that indicated an optimal differentiation of 4 clusters defined by k-means, these clusters were not associated with the dominant prey items identified from faecal samples (Fig. 4.3).

4.5 Discussion This study aimed to identify dietary composition of foraging loggerhead turtles in a subtropical feeding ground. A combination of methods including faecal analysis and stable isotope analysis of blood and skin suggested that the diet of loggerhead turtles sampled in this locality contained species from ten distinct taxonomic families within five phyla (i.e.

Crustacea, Mollusca, Echinodermata, Tunicata and Annelida). Additionally, comparisons of isotopic values from sampled epidermis and blood plasma, which had different turnover periods, indicated that diet appeared consistent over a period of several weeks (Fig. 4.2).

The most prevalent prey observed were Crustacea from the family Portunidae (i.e. blue swimmer crab) which is a common and commercially fished species within Moreton Bay (Clarke & Ryan 2004). Mollusca from the families Batillariidae (i.e. mud whelks), Mytilidae (hairy mussel) and Pinnidae (i.e. Razor clam) were observed in 60 % of samples with these taxa common throughout the intertidal and subtidal banks of the sampled sectors (Stevens & Connolly 2005). These observations are consistent with previous diet studies of inshore feeding loggerhead turtles (Limpus et al. 1994b, Godley et al. 1997, Limpus et al. 2001, Wallace et al. 2009). Interestingly, one turtle excreted two discrete faecal samples, the first was dominated by Portunid crabs (i.e. blue swimmer crab) which inhabit the surface of sediments indicating above sediment foraging, whilst the second sample contained a large amount of large diameter gravel (3 – 8 mm diameter) which may indicate sediment faunal mining feeding behaviour previously described for Moreton Bay loggerhead turtles (Preen 1996). No evidence of prey living within the benthos was observed, however it is possible soft bodied invertebrates were consumed and completely digested and thus were not represented in faecal samples. Hence, there is evidence that the same turtle may forage in a range of habitats and incorporate different feeding strategies, potentially reflecting local prey availability.

The δ13C and δ15N values from epidermis indicated no differences in isotopic value from loggerhead turtles sampled at different times spanning two years across different sampling locations implying the observed isotopic variation in sampled tissues and thus prey items were consistent across the sampled period. Home ranges of loggerhead turtles resident in Moreton Bay are variable with previous studies identifying home ranges ranging from 15 – 160 km2 (Shimada et al. 2017). Consequently, it is likely loggerhead turtles regularly move between the sectors used to classify feeding locations in this study, with sampled individuals caught in different sectors likely to have foraging grounds overlapping several sectors. Given individual loggerhead turtles foraging areas overlap, marked differences in tissue δ13C and δ15N values between individuals, and between tissues of the same individual, are likely to be caused by differences in the prey items consumed by individuals. Following the application of discrimination factors to account for variation in incorporation of δ13C by the different

69 biochemical pathways of sampled tissues (Vander Zanden 2012), the comparison of plasma and epidermis δ13C isotopic values (i.e. tissues with comparatively fast and slow turnover periods) concluded that 90 % of the turtles had diets that were consistent in δ13C values over the time between when plasma and epidermis were formed. However, the discrimination factors used in this analysis, despite being the best available, were derived from fast growing juveniles and may not accurately represent the turnover period of sub-adult and adult loggerheads. Consequently, until species/age specific discrimination factors have been determined, this conclusion should be considered with caution. Previous satellite telemetry studies of foraging loggerhead turtles within Moreton Bay identified differences in seasonal home ranges which may account for the dietary shift observed in 10 % of the sampled cohort (Shimada et al. 2016b).

Given that in most turtles, the diet appeared to remain consistent for at least the recent past, it was anticipated that the diet of individuals might be identified based on clustering of their plasma isotopic values on the assumption that the isotopic values in diet items remain constant. However, the identified k-means clusters based on isotopic values were not associated with the dominant prey types identified by faecal sampling. As such, isotopic values of sampled epidermis could not be used to identify the dominant dietary items of individual loggerhead turtles. The wide range in δ13C and δ15N values in the epidermis of sampled individuals with faecal contents dominated by portunid crabs suggests there might be large inherent variation in the isotopic values within individual prey species inhabiting Moreton Bay or that diet is more varied than can be inferred by faecal analysis. Taking into consideration the limited sample size of this study, further collection of faecal contents and assimilated δ13C and δ15N values from an increased sample size may help to resolve the prevalence and source of observed variation. Had sampled individuals clustered according to observed taxa in faecal sampling, the observation of dietary stability in 90 % of turtles could suggest that individual turtles specialised on feeding on a particular prey type. Even if turtles did feed exclusively on a single prey type, such as Portunid crabs, the tissue isotopic signals may differ between individuals, as observed in the δ13C values of the Portunid, Scylla serrata (giant mud crab), which varied according to their proximity to seagrass beds in Moreton Bay (Connolly et al. 2005). Hence, if feeding on the same giant mud crab species, loggerhead tissue δ13C values may be different depending upon the location of the crabs they feed on. Similarly, studies examining marine invertebrates in the saltmarsh and mangrove habitats of southern Moreton Bay have documented differences in δ13C associated with proximity to

70 mangrove (depleted) or saltmarsh (enriched) habitats (Guest & Connolly 2005). However, because tissue isotopic signal was not associated with the dominant taxa found in faecal samples, it is likely the foraging population of Moreton Bay exhibit a predominantly opportunistic generalist foraging strategy (Limpus et al. 2001) and that, in addition to localised variation in isotopic baselines within the same species, there is poor isotopic differentiation between different prey taxa. Further isotopic studies are needed to develop the baseline isotopic values of prey taxa within the Moreton Bay area to further test these hypotheses.

4.6 Conclusion Based on faecal sampling of loggerhead turtles foraging within Moreton Bay, crustaceans of the family portunidae were the primary prey species, and observations from one individual suggested that prey hunting strategies may be variable, from feeding above the sediment to feeding below the sediment within a short period of time. Shifts in foraging behaviour of individuals deemed to have similar diets based on faecal sampling, may contribute to the relatively large variation in δ13C and δ15N isotopic values. Tissue comparisons between plasma and epidermis of the same individuals identified that the diet composition of most turtles did not change between the times these two tissues formed. Consequently, it was posited that large inherent variation in isotopic values of the same species of prey item were a possible source of the wide range observed in sampled from tissues of loggerhead turtles inhabiting Moreton Bay. The determination of adult loggerhead tissue discrimination factors would increase confidence in the assumption of diet stability over time. Potentially, considering the results of this study and based on previous observations of this foraging population, the loggerhead turtles inhabiting the eastern banks of Moreton Bay are opportunistic generalist predators, that switch from one prey item to another according to prey availability. To validate this hypothesis, further studies incorporating isotopic methods could establish the carbon and nitrogen isotopic baselines in prey species that are found in different habitats within Moreton Bay. This study contributes to the growing isotopic dietary studies of foraging marine turtle populations on east coast Australia and is the first to report on the δ13C and δ15N isotopic ranges of foraging loggerheads in the south west Pacific.

Chapter 5

Contributor Statement of Contribution Author: Owen I. Coffee (Candidate) Conception and design (70%) Analysis and interpretation (85%) Drafting and production (70%) Author: David T. Booth Conception and design (20%) Analysis and interpretation (10 %) Drafting and production (12.5%) Author: Janet M. Lanyon Conception and design (0%) Analysis and interpretation (5 %) Drafting and production (12.5%) Author: Col J. Limpus Conception and design (10%) Analysis and interpretation (0 %) Drafting and production (5%)

Dietary composition and foraging ground use by the green turtle (Chelonia mydas) population in Port Curtis, Gladstone, central Queensland.

5.1 Abstract The development of stable isotope analysis (SIA) techniques has challenged some of the long-held theories of foraging behaviours and dietary compositions in marine turtle species. Previously considered herbivorous following recruitment to near shore foraging habitats, this study examined the dietary composition and foraging behaviours of green turtles in Port Curtis, Central Queensland using SIA and oesophageal lavage to identify patterns of foraging ground use and dietary composition in this foraging population. Based on oesophageal lavage samples, seagrass was the most important food group in the diet of turtles captured on sandbanks (83.3 %), rocky reef (77.6 %) and subtidal (61.8 %) habitats which was consistent with the food items observed at these sites of capture. However, a Bayesian mixing model using δ13C and δ15N stable isotopes identified food groups that were under-represented through lavage sampling, as well as a significant proportion of animal material in the diets of a subset of the sampled turtles. Enriched δ15N values in small turtles (< 55 cm curved carapace length) were attributed to continued foraging on macrozooplankton after recruitment to neritic foraging grounds. Individuals captured on the sandbanks were on average 25.8 cm and 27.4 cm larger (CCL) than turtles from mangrove and subtidal flats (p < 0.001). This observed distinction in turtle size associated with foraging habitat suggested the presence of a developmental shift in foraging ground and associated diet. It would appear smaller turtles occupied and fed in shallow subtidal and mangrove habitats, with larger turtles feeding on rocky reefs or seagrasses in sandbank areas. This potential ontogenetic shift in foraging habitat may represent a shift from shallow intertidal (subtidal flats and mangrove habitats) to deeper subtidal foraging grounds, and a concomitant shift from an algal to a seagrass diet. The diversity of foraging habitats and diets within a small geographic area (such as the confines of Port Curtis) suggests a need to establish management strategies to protect green turtles at different stages of development and in different locations. The findings of this study support the increasing number of observations of consumption of animal prey well beyond recruitment to near-shore foraging habitats and advocates the use of traditional diet sampling techniques (lavage) along with SIA to elucidate long term dietary composition and foraging behaviour.

5.2 Introduction Investigating foraging ecology of a species provides valuable information on how foraging habitats are utilised and the influence of diet on patterns of behaviour, growth and reproduction (Katzenberg 2008, Cherel et al. 2009, Dale et al. 2011). However, gathering this information for migratory species, such as marine turtles, poses distinct challenges. Whilst marine turtles are often accessible ashore at their nesting beaches where they do not forage to any appreciable extent, they are not so easily encountered at their foraging grounds, which may be up to thousands of kilometres from their nesting sites (Plotkin 2002, Limpus 2009). Even when foraging regions are known, different habitats within these locales offer a range of potential food items, such that identifying a broad foraging region does not necessarily provide information on availability of food items and an individual’s likely diet (McClellan et al. 2010, Pajuelo et al. 2016, Prior et al. 2016).

The green turtle (Chelonia mydas) exhibits a life cycle of distinct developmental and ecological stages (Bolten 2002). Following an extended period of carnivory feeding on macrozooplankton in the pelagic zone off the continental shelf (Bolten 2002, Boyle & Limpus 2008, Limpus 2009), most immature green turtles in the south Pacific region recruit to neritic foraging environments; bays, coastal habitats or reef lagoons (Limpus 2009). Having recruited to these nearshore areas, immature green turtles develop long term fidelity to a home foraging ground, such that once sexually mature, they do not venture from these areas except for periodic reproductive migrations (Limpus & Walter 1980, Limpus & Chaloupka 1997, Limpus 2009). Intentional displacement of individuals from their home foraging grounds has demonstrated that they migrate back within several weeks (Shimada et al. 2016a). Depending upon foraging region and habitat, green turtles from the east coast of Australia have home foraging ranges of between 3 – 166 km2 (Shimada et al. 2016b). Upon recruitment to feeding grounds, individuals were thought to undergo a shift in their diets, switching from the carnivorous / planktivorous diet of their open ocean developmental phase to a predominantly benthic herbivorous diet (Bjorndal 1997, Musick & Limpus 1997). However, studies incorporating new sampling techniques have discovered variation in foraging strategies and feeding behaviours in green turtle populations throughout the world that challenge some of these long-held views (Heithaus et al. 2002, Hatase et al. 2006, Arthur et al. 2007, González et al. 2014).

Traditionally, investigations of diet in sea turtles have involved analysis of gut contents of harvested or by-catch specimens, or individuals euthanised for research purposes, to ascertain composition and proportion of dietary items (Garnett & Murray 1981, Garnett et al. 1985, Ross 1985, Bjorndal et al. 1991, André et al. 2005). Dietary composition of the complete gastrointestinal tracts of dead turtles reflects forage consumed over multiple feeding events, likely over the previous few days (Brand et al. 1999). This method applied to green turtles of the west Caribbean revealed continuous selective foraging on new growth turtle grass (Thalassia testudinum)(Mortimer 1981), whilst green turtles of the south west Pacific shifted diet in accordance with tidal availability of forage (Read 1991). However, limitations on sample size and the ethical ramifications of lethal sampling of vulnerable turtle populations has necessitated a shift to non-lethal practices including faecal sampling and/or oesophageal lavage (Forbes & Limpus 1993, Seminoff et al. 2002, Arthur et al. 2009). Analysing diet from faeces is problematic because digestion may render some food particles unrecognisable and easily digestible food items may be under-represented (Casale et al. 2008, Frick et al. 2009). In contrast, oesophageal lavage is fast and repeatable, and produces a small sample of a turtle’s most recent meal, a snap-shot of the most recent foraging activity, so that dietary items can generally be discerned relatively easily (Forbes & Limpus 1993, Baker et al. 2014). Dietary studies utilising oesophageal lavage have assessed diet at the population level or demographics of cohorts through sampling large numbers of individuals, and have observed variations in diet through repeat sampling (Brand-Gardner et al. 1999, Arthur et al. 2009). Oesophageal lavage of foraging green turtles in Queensland Australia has identified populations that principally consume algae (Forbes 1996, Brand-Gardner et al. 1999), mainly seagrasses (Fuentes et al. 2006) and/or mangrove material (Limpus & Limpus 2000). This indicates green turtles forage across a range of food types when available, coupled with preferences for particular foods (Limpus et al. 2013b). However, in addition to only representing a small window of foraging activity, oesophageal lavage generally under- represents ingested gelatinous material (Forbes & Limpus 1993). In an attempt to overcome these limitations, an increasingly common trend for dietary studies is the inclusion of stable isotope analysis (SIA) so that significant shifts in diet over a longer time frame within a single individual may be examined (Arthur et al. 2009, Prior et al. 2016).

As reviewed in Chapter 1, SIA is frequently used to study the ecology of marine turtles, providing insight on the foraging location and in some cases the type and/or trophic level of food that is consumed. SIA of marine turtles has provided valuable insights into diet, foraging

75 habitat and exploitation of foraging home grounds (Arthur et al. 2008, Caut et al. 2008b, Vélez-Rubio et al. 2016, Ramirez et al. 2017). The traditional assumption that all green turtles undergo an ontogenetic shift of diet from oceanic macrozooplankton to become nearshore neritic herbivores has been challenged following SIA analysis (Hatase et al. 2006, Cardona et al. 2009). Rather than undergo such abrupt ontogenetic shifts, many juveniles and adults continue to consume measurable amounts of animal material (indicated by δ15N values) within neritic foraging grounds (e.g. Shark Bay, Western Australia - Heithaus et al. 2002, San Diego Bay, California - Lemons et al. 2011, Samborbón Bay, Argentina - González et al. 2014). As these perceived dietary anomalies become commonplace, there is a need to examine foraging behaviours at regional and local levels to better inform conservation and management strategies.

Port Curtis, a sheltered embayment on the central coast of Queensland, Australia (23.82 °S, 151.29 °E), supports a foraging population of green turtles from the southern Great Barrier Reef stock (FitzSimmons & Limpus 2014). Previous studies on this green turtle population have highlighted dichotomous foraging behaviours and variable foraging ground home ranges, with individuals observed to intermittently shift foraging ground locations up to 100 km or utilise different foraging areas within their home range (Hamann et al. 2015, Shimada 2015), resulting in distinct dietary changes (Prior et al. 2016). Variations in diet and foraging habitat may reflect seasonal variability in food availability or may alternatively indicate selective foraging behaviour (Limpus et al. 2005, Seminoff et al. 2008, Arthur et al. 2009, Mansfield et al. 2009, McClellan et al. 2010, Shimada 2015).

The current study sought to determine the diet and better understand the foraging behaviour previously described for green turtles from distinct foraging habitats within Port Curtis, using a combination of oesophageal lavage and SIA. A further aim was to identify trends in foraging site use across different size/age classes of turtles. Port Curtis hosts significant recreational and commercial vessel traffic and industry, exposing its green turtle population to threats of boat strike and industrial pollutants. Currently, no management strategies are in place to protect this foraging population from anthropogenic threats in Port Curtis. A previous study by Prior et al. (2016) focussed on two foraging sites in the north and north western areas of Port Curtis. To complement that research, this study examined foraging

76 behaviour in previously unsampled regions of the bay, including foraging sites in the eastern and southern extents of the bay. Establishing how the Port Curtis green turtle population utilises its foraging environment is a crucial step in the mitigation of anthropogenic related mortality.

5.3 Methods 5.3.1 Sampling sites and protocols Green turtles were sampled from among the turtles captured for a larger study by the Queensland Department of Environment and Science on the population demographics and health of turtles at Port Curtis, Gladstone (Limpus et al. 2016, Limpus et al. 2017). This large estuarine area within the distributary of the Fitzroy Catchment is on the central Queensland coastline inshore of the Capricorn Bunker group of islands in the southern Great Barrier Reef Marine Park. Covering approximately 115 km2, this estuarine area exhibits a diverse bathymetry and supports a range of different coastal habitats including shallow sandy seagrass meadows, rocky reefs, estuaries, fringing mangroves and the outflow from three large rivers (the Boyne and Calliope rivers and the Fitzroy river via the Narrows). The home ranges of foraging sub-adult and adult green turtles within Port Curtis have previously been defined using GPS satellite telemetry and ranged from 3 – 81 km2 (Hamann et al. 2016). During five sampling trips between mid-2015 to late 2016, conducted outside the nesting period between May and October each year, 174 healthy green turtles were captured from three different sites within Port Curtis: Pelican Banks (23.766 °S, 151.297 °E), Facing Island (23.800 °S, 151.329 °E) and immediately offshore of the Boyne estuary (23.934 °S, 151.356 °E) (Fig. 5.1).

Figure 5.1. Sampled areas within Port Curtis, Central Queensland. Coloured according to habitat; Sandbanks (Green), Estuary (Red), Mangrove (Blue) and Rocky Reef (Purple).

The three sampling sites represent distinct foraging areas for green turtles and are spaced 5 – 20 km apart. Pelican Banks consists of an expanse of intertidal sandbanks with fringing mangroves that are accessible at high tide, predominantly vegetated by seagrass and green algae (Rasheed et al. 2017). Facing Island is located at the eastern extent of Port Curtis and is typified by fringing mangrove habitats interspersed with small rocky reef outcrops; consequently, the primary available food sources are epiphytic red and brown algae growing on mangrove roots and rocky substrate in addition to mangrove plant parts. Situated at the southern end of Port Curtis, off the Boyne estuary, is a shallow (~ 0.5 – 2.0 m deep) subtidal flat, vegetated with red and brown algae interspersed with seagrass and fringed by rocky outcrops. Within these sampled sites, four habitat types were identified; mangrove areas (with predominantly red and brown algae in addition to mangroves), inter- and subtidal sandbanks (with seagrasses), subtidal rocky reefs (with algae) and shallow subtidal flats adjacent to the estuary (with a variety of algae and seagrasses) (Table 5.1).

Table 5.1. Sampled periods and total individuals from each sampling site/habitat within the Port Curtis region of Central Queensland.

Pelican Banks Boyne Estuary Facing Island Sandbanks Mangrove Rocky Reef Subtidal flats Rocky Reef Mangrove July - 2015 34 May - 2016 11 9 16 June - 2016 11 15 3 6 13 11 September - 2016 3 8 4 October - 2016 11 19

Foraging green turtles were captured by the rodeo method in the upper part of the tidal cycle (Limpus and Reed 1985), then transported to the nearby shore for processing. Shallow water meant that upon sighting, only a few turtles evaded capture (Limpus 1985, Read & Limpus 2002). All turtles were tagged on the trailing edge of each of their front flippers with a numerically-coded titanium turtle tag (Limpus 1992) before being weighed and measuring curved carapace length (CCL).

Samples of characteristic and potential forage items were collected opportunistically from each sampling site for dietary comparisons and stored at –18 °C for stable isotopic analysis to establish baseline δ13C and δ15N values of potential food items. In addition to these collected samples, a search of the published literature was conducted to ascertain further baseline

79 values of primary producers, most of which were within a 200 km radius of Port Curtis. Reported values obtained from the published literature included seagrass, algae, mangrove and animal δ13C and δ15N values from within Port Curtis (Prior et al. 2016), Hervey Bay (Cameron 2007), Shoalwater and Moreton Bays (Brine 2008, Coffee unpub. data) (Table 5.2). Macrozooplankton were collected from Moreton bay and their isotopic values assumed to be similar to macrozooplankton in Port Curtis because they are dispersed by the same currents along the south east Queensland coast.

Food Group Species Source δ 13C δ 15N Aegiceras corniculatum Mangrove Prior et al. (2016) -26.5 3.7 (leaves) Avicennia marina (leaves) Prior et al. (2016) -27.2 2.2 Avicennia marina (propagule Cameron (2007) -25.5 1.7 and pericarp) Avicennia marina (propagule) Cameron (2007) -27.4 1.4 Avicennia marina (propagule) Current Study -28.9 1.6 Rhizophora stylosa (apical tip) Current Study -28.9 2.3 Rhizophora stylosa (leaves) Brine (2008) -26.5 1.3 Rhizophora stylosa (leaves) Cameron (2007) -27.1 0.8 Rhizophora stylosa (leaves) Prior et al. (2016) -27.4 3.7 Rhizophora stylosa Brine (2008) -25.9 0.5 (pneumatophore) Rhizophora stylosa (propagule) Cameron (2007) -26.3 0.9 Seagrass Halodule pinifolia Current Study -13.2 2.7 Halodule uninervis Brine (2008) -10.3 3.2 Halodule uninervis Cameron (2007) -11.6 2.6 Halodule uninervis Prior et al. (2016) -11.7 2.1 Halophila ovalis Brine (2008) -12.2 0.5 Halophila ovalis Cameron (2007) -12.4 0.5 Halophila ovalis Current Study -11.1 1.3 Halophila ovalis Prior et al. (2016) -9.6 5.3 Zostera capricorni Cameron (2007) -10.8 1.6 Zostera muelleri subsp. Current Study -13.0 -0.9 capricorni Zostera muelleri subsp. Prior et al. (2016) -8.6 1.5 capricorni Chlorophyta Ulva polyclada Current Study -19.5 4.7 Unidentified sp. (filamentous) Prior et al. (2016) -22.1 3.8 Rhodophyta Catenella nipae Current Study -30.9 4.6 Chondria sp. Prior et al. (2016) -19.0 2.5 Gelidium sp. Current Study -19.7 7.3 Gracilaria sp. Current Study -21.5 6.5 Laurencia sp. Prior et al. (2016) -18.2 3.4 Spyridia sp. Prior et al. (2016) -27.8 2.9 Unidentified sp. Current Study -35.5 7.1 Unidentified sp. Current Study -34.9 6.0 Unidentified sp. Current Study -21.5 5.0 Unidentified sp. Current Study -27.0 7.2 Ochrophyta Dictyota sp. Prior et al. (2016) -21.6 7.5 Sargassum sp. Brine (2008) -17.4 4.4 Sargassum sp. Prior et al. (2016) -15.6 3.1 Coffee (unpublished Animal Catostylus mosaicus -20.7 11.5 data) Ctenophore Current Study -21.1 8.5 Coffee (unpublished Physalia physalis -19.2 10.3 data) Coffee (unpublished Velella velella -19.6 7.8 data)

5.3.2 Diet sampling and analysis From the 174 green turtles captured, recently ingested forage was successfully obtained through oesophageal lavage from 136 turtles, following the method of Forbes and Limpus (1993). Lavage was conducted for no longer than five minutes; if no ingesta was expelled during this period, lavage was abandoned. Successfully collected ingested material was separated from the flushing water using a fine (2 mm) mesh sieve and stored in 70 % ethanol until laboratory analysis.

Ingesta samples were examined by micro stereology to identify contents to the lowest possible taxonomic level using the keys of Lanyon (1986) for seagrass species and Cribb and Cribb (1985) for algae and mangrove fruits. Relative volumes of ingested species were estimated as proportions of the sample volume using the principles of micro-stereology (Read 1991). Each lavage sample was mixed until visually homogenous and a random sub-sample taken and spread to evenly cover a 90 mm diameter petri dish. This sub-sample was examined under the dissecting microscope where the proportion of each food type was estimated with the use of a 19 mm, 42 endpoint Weibel graticule over eight fields of view (Read and Limpus 2005). Ingesta intersecting with the graticule points were identified and recorded, with subsequent relative volumes of each forage item calculated as the proportion of their intersecting points against the total number of graticule points.

5.3.3 Stable isotope analysis A 0.5 cm2 skin sample (n = 174) was taken from between the keratinised scales located on the trailing edge of the fore flipper of each turtle using a sterile scalpel, and then stored in 70 % ethanol until stable isotope analysis (SIA) (Barrow et al. 2008). A 3 mL blood sample (n = 144) was collected from the dorsal cervical sinus (a dorsal branch of the jugular vein) using a sterile single-use syringe connected to an 18-gauge needle, and was stored in heparinised containers to prevent clotting prior to centrifuging (Owens & Ruiz 1980); heparin has no effect on δ15N isotopic values in sea turtle blood (Lemons et al. 2012). Blood samples were separated into plasma and red blood cells (RBC) by centrifuging at 9000 rpm for 5 min within an hour of collection and stored at -18 °C until SIA. Blood and skin tissue samples were prepared for stable isotope analysis following the protocols outlined by Reich et al. (2008). Skin samples were rinsed with distilled water and surface fouling (i.e. algae and other

82 epiphytic growth) removed using a sterilised scalpel blade. Dermal tissue was removed, and the surface epidermis finely diced. Plasma, blood cells and epidermal samples were oven dried at 50 – 60 °C for 48 – 72 h in individual sample tubes. Tissues samples were quantified for stable isotopes ratios of δ13C and δ15N (expressed in δ notation, defined as parts per mil) as described in Chapter 2.

5.3.4 Statistical Analysis Statistical analyses were conducted using the R statistical program and RStudio user interface (RStudio Team 2016, R Core Team 2017).

Lavage analyses Food items were categorised by phyla into one of seven categories: mangrove, seagrass, Chlorophyta (green algae), Ochrophyta (photosynthetic heterokonts), Rhodophyta (red algae), animal material, and ‘other’ which incorporated particulate matter and other items possibly attributed to incidental ingestion (i.e. sand and gravel). An index of relative importance (IRI) was calculated for these food categories for each turtle, with respect to habitat, according to:

푛

%IRI = (FO푖 × M푖/(∑(FO 푖 × M푖))) × 100 푖=1 where FO = frequency of occurrence, M = average volume, n = the number of observed food items, and i = food item. This accounts for potential bias of different food types being under- or over-represented from sampled outliers (Bjorndal 1997).

Turtle size and location of capture To ascertain whether turtle body size differed between foraging habitats, analysis of variance (ANOVA) followed by Tukey post-hoc multiple comparisons was used to compare CCL of individuals from different habitats. Diagnostic plots were produced to test for assumptions of normality and homogeneity of variance and ANOVA was chosen because of its demonstrated resilience to unequal sample sizes and departures from normality (Zar 1999).

Isotope analyses With the exception of tissue to tissue comparisons, blood plasma, which is estimated to have the shortest turnover period (i.e. in the order of weeks)(Seminoff et al. 2007, Reich et al. 2008, McClellan et al. 2010), was used as the representative tissue for SIA as it most likely reflected the integrated stable isotopic composition of food ingested and assimilated in the sampled tissue prior to capture. ANOVA was used to test for significant differences in plasma isotopic values between the five sampling periods. ANOVA and Tukey post-hoc multiple comparisons were used to compare δ13C and δ15N ratios in blood plasma, and foraging habitats (SB – Sandbanks, SF – Subtidal Flats, M – Mangrove and RR – Rocky Reef).

To evaluate if diet changed significantly between the times when blood plasma and epidermal tissues were formed, δ13C stable isotope ratios for plasma and epidermis, which represent the contribution of primary producers to assimilated diet, were plotted against each other, and compared to a theoretical ‘no change in diet’ line (Prior et al. 2016). The “no change in diet” line is a prediction of epidermal stable isotope values from plasma stable isotope values based on the best available published discrimination factors of these tissues in juvenile and adult green turtles (Vander Zanden 2012). A difference of more than two standard deviations (± 30 %) from the ‘no change in diet value’ and the measured value was assumed to indicate a change in diet between the times that epidermis and plasma tissue formed (Prior et al. 2016).

To assess if there was a relationship between turtle body size and isotopic plasma values for both δ13C and δ15N against turtle CCL, turtles were categorized into body size groups, i.e., small (38 – 45 cm CCL, most likely recruited to neritic habitat within the last few years) (Limpus et al. 2013b), medium (45 – 55 cm CCL, juveniles and sub adults) and large (75 – 105 cm CCL, prepubescent to adult). ANOVA with Tukey post-hoc comparisons were conducted to determine whether δ15N and δ13C varied between body size groups.

Inferred diets from SIA and lavage samples To determine whether diet indicated by oesophageal lavage samples was consistent with diet indicated by blood plasma stable isotope values, a hierarchical Bayesian mixing model using a Markov chain Monte Carlo (MCMC) simulation in the R package MixSIAR was used to

84 infer the proportions of different food item groups contributing to the diets of individuals from each of the sampled habitats (Moore & Semmens 2008, Stock & Semmens 2016). Interpretation of the subsequent model relied on the assumptions that: (1) the δ13C and δ15N values of sampled tissue were representative of the predominant prey taxa observed in lavage samples; and (2) tissue discrimination factors incorporated in the model, which were based on the best available published discrimination factors of juvenile green turtles (Vander Zanden 2012), adequately represented the isotopic discrimination of the sampled individuals. To strengthen the interpretive power of the mixing model, which is limited by degrees of freedom and relies on discrimination using δ13C and δ15N, potential food items were grouped according to the predominant items observed from oesophageal lavage and the relative similarities of their isotopic values. Mean isotopic values of potential food items were compiled from values reported in Table 5.2, and further condensed into four groups (mangrove and rhodophyta (MRh), seagrass (SG), chlorophyta and ochrophyta (CO) and animal material (An)) based on frequency of occurrence in lavage samples. Individual turtles were grouped according to the habitat in which they were captured, and then their isotopic values compared to those simulated by iteratively combining different proportions of the δ13C and δ15N values of the four different food groups to estimate dietary composition with a MCMC simulation. A total 3 chains with 100,000 iterations were run following the discard of 50,000 initial iterations to generate a stable prediction (Stock & Semmens 2016). Gelman- Rubin and Geweke diagnostic tests were conducted to ensure convergence of the posterior distributions from the resulting model were satisfactory (Gelman et al. 2013).

5.4 Results 5.4.1 Lavage analyses and foraging ground use Across all four habitat types at the three sampling sites, 29 different food items were identified in the ingesta of the 136 lavaged turtles (Table 5.3). These food items were grouped according to phyla and isotopic value for integrative analyses. Based on IRI calculations, seagrass was the most important food group in the diet of turtles captured on sandbanks (83.3 %), rocky reef (77.6 %) and subtidal (61.8 %) habitats (Table 5.4.), with seagrass species Halodule pinifolia, Halophila ovalis and Zostera muelleri subsp. capricorni most frequently found in lavage samples (Table 5.3). In both the subtidal and mangrove habitats, Rhodophyta was the second most important dietary item at 25.0 % and 48.8 % respectively. The red algal species Bostrychia tenella and Catenella nipae were dominant in

85 mangrove habitats, whilst Gracilaria sp. and Hypnea sp. were predominant in lavage samples from turtles sampled in subtidal flats. Turtles captured in mangrove habitats had diets composed predominantly (49.4 %) of mangrove parts (apical buds, cotyledons and propagules) from two species of mangrove, Rhizophora stylosa and Avicennia marina.

%FO Mean vol. % (SD) Food Item Species SB SF RR M SB SF RR M n = 65 n = 34 n = 6 n = 31 n = 65 n = 34 n = 6 n = 31 Mangrove Avicennia marina 6.2 100.0 1.7(8.0) 47.4 (28.0) Rhizophora stylosa Seagrass Cymodoce rotundata 9.2 32.4 1.6 (7.1) 1.8 (3.0) Halodule pinifolia 66.2 58.8 66.7 5.6 (7.1) 8.4 (19.5) 20.4 (19.2) Halophila ovalis 66.2 11.8 50.0 12.9 12.2 (15.8) 1.0 (4.0) 7.7 (16.4) 0.6 (1.7) Zostera muelleri 98.5 76.5 100.0 32.3 54.6 (32.7) 34.5 (33.8) 36.1 (33.2) 1.3 (2.0) subsp. capricorni Phylum Amansia glomerata 6.2 8.8 0.8 (3.5) 0.4 (1.2) Rhodophyta Audouinella sp. 1.5 5.9 0.0 (0.3) 2.9 (16.4) Bostrychia tenella 93.5 13.8 (13.1) Catenella nipae 1.5 100.0 0.0 (0.3) 31.0 (18.5) Chondria sp. 3.1 1.2 (7.9) Gracilaria sp. 23.1 94.1 33.3 3.2 2.5 (6.7) 25.1 (29.9) 7.8 (15.8) 1.2 (6.6) Herposiphonia 1.5 2.9 0.6 (4.7) 0.2 (0.9) secunda Hypnea sp. 52.3 70.6 50.0 3.2 5.4 (12.1) 17.5 (24.6) 11.5 (18.9) 0.1 (0.3) Hypnea sp. 4.6 0.6 (3.3) Laurencia sp. 7.7 29.4 3.2 2.1 (12.2) 4.4 (9.2) 0.6 (3.3) Sarconema sp. 4.6 5.9 16.7 0.4 (2.2) 0.2 (0.7) 0.8 (1.7) Unidentified sp. 1.5 2.9 3.2 0.1 (0.8) 0.0 (0.2) 0.1 (0.4) Unidentified sp. 1.5 0.5 (3.6) Phylum Ulva lactuca 1.5 8.8 6.5 0.0 (0.1) 0.2 (0.8) 0.6 (2.9) Chlorophyta Ulva polyclada 1.5 0.4 (3.5) Phylum Sargassum flavicans 2.9 0.4 (2.5) Ochrophyta Animal Amphipod 16.9 2.9 16.7 6.5 0.8 (2.5) 0.0 (0.1) 0.6 (1.3) 0.1 (0.5) Cnidaria 1.5 3.2 0.2 (1.8) 1.0 (5.4) Porifera 1.5 0.1 (0.5) Other Epiphytes 43.1 38.2 33.3 16.1 6.4 (11.2) 1.3 (2.3) 9.5 (15.2) 1.1 (3.2) Particulate material 49.2 5.9 2.4 (3.8) 0.2 (1.1) Shell 23.5 33.3 32.3 1.4 (3.1) 5.7 (8.3) 1.1 (1.7)

No. of Species %FO Mean vol. % IRI % Food item SB SF RR M SB SF RR M SB SF RR M SB SF RR M n = 65 n = 34 n = 6 n = 31 n = 65 n = 34 n = 6 n = 31 n = 65 n = 34 n = 6 n = 31 n = 65 n = 34 n = 6 n = 31 Mangrove 2 2 6.2 100.0 1.7 47.4 0.1 49.4 Seagrass 4 4 3 2 100.0 11.6 100.0 35.5 74.0 45.7 64.2 1.9 83.3 61.8 77.6 0.7 Phylum 12 8 3 6 63.1 4.2 66.7 100.0 14.0 50.7 20.1 46.8 10.0 25.0 16.2 48.8 Rhodophyta Phylum 2 1 1 3.1 21.1 6.5 0.5 0.2 0.6 0.0 0.6 0.0 Chlorophyta Phylum 1 27.4 0.4 1.4 Ochrophyta Animal 3 1 1 2 20.0 32.6 16.7 9.7 1.2 0.0 0.6 1.1 0.2 0.0 0.1 0.1 Other 2 3 2 2 64.6 3.2 33.3 41.9 8.8 3.0 15.2 2.2 6.4 11.3 6.1 1.0

* *

CCL (cm) CCL

SubtidalSF Flats Sand banks Mangroves Rocky Reefs Habitat Figure 5.2. Distribution of turtle size (CCL) by foraging habitat. Plots detail the median value within the inter-quartile range (IQR), external points denote outliers from the distribution. * identifies significant difference in CCL of the sampled habitat

Turtle body size differed significantly between sampled habitats (ANOVA F2, 134 = 42.73, p = 0.001) (Fig. 5.2), with Tukey post-hoc comparisons identifying differences between sandbank and/or rocky reef habitats compared to mangrove and subtidal flats. Individuals captured on the sandbanks were on average 25.8 cm and 27.4 cm larger (CCL) than turtles from mangrove and subtidal flats (p < 0.001). Turtles caught on rocky reefs were on average 17.0 and 18.6 cm larger respectively than turtles from mangrove and subtidal flats (p < 0.001). No significant difference was observed in CCL between turtles from sandbank and rocky reef habitats.

5.4.2 Stable isotope analyses Only the Pelican Banks site was sampled on all sampling trips so only turtles caught at this site could have their stable isotope values compared across sampling periods (October 2016 13 was omitted as there were insufficient plasma samples for SIA). Neither δ C (F3, 73 = 1.43, p 15 = 0.24), nor δ N (F3, 73 = 0.26, p = 0.86) varied significantly across the sampled periods at Pelican Banks. The sampled cohort was subsequently pooled for all further analyses.

* *

C (‰) C

13 δ

A .

* *

(‰)

1 δ

B . SubtidalSF Flats Sand banks Mangroves Rocky Reefs Habitat Figure 5.3. Distribution of Carbon (a) and Nitrogen (b) stable isotope values in turtle plasma by for aging habitat. Plots detail the median value within the inter-quartile range (IQR), external points denote outliers from the distribution. * identifies significant difference in δ13C and δ15N values for individuals from different sampled habitats.

13 15 Turtle plasma values of both δ C (F3, 140 = 39.7, p = 0.001) (Fig. 4.3a) and δ N (F3, 140 = 8.759, p = 0.001) varied significantly between the sampled habitats (Fig. 5.3b). Individuals caught in sandbank and subtidal flats had, on average, more enriched δ13C values (-13.9 and -14.9 ‰ respectively) than turtles caught amongst mangroves and rocky reefs (-16.0 and - 19.0 ‰), with samples from sandbanks more enriched in δ13C than turtles from the subtidal flats, based on Tukey post hoc comparisons. Turtles in subtidal and rocky reef habitats had

more enriched δ15N values (9.3 and 9.4 ‰) than those from mangrove (8.6 ‰) or sandbank areas (8.0 ‰).

Rocky reef Subtidal flats Sandbanks Mangrove

Figure 5.4. Carbon (δ13C ‰) values from sampled epidermis and blood plasma against a theoretical stable diet line (solid line) and ± 30% boundary (dashed lines).

The distribution of assimilated epidermis and blood plasma δ13C values around a calculated theoretical ‘no change in diet’ line indicated that ~ 40 % of all sampled individuals had values outside the 30 % boundary which indicated a change in their diet and/or foraging location in the period between the synthesis of their blood and epidermis. Most individuals observed with a shifted diet were caught in mangrove habitats but had plasma values enriched in δ13C compared with epidermal tissue (Fig. 5.4).

There was a significant correlation between turtle body size and blood plasma δ15N values

(One-way ANOVA F2,87 = 14.47, p = 0.001) while a subsequent Tukey post-hoc confirmed that an enrichment of ~ 2.5 ‰ in δ15N values was associated with small turtles (38 – 45 cm CCL). No significant difference was observed between the δ15N values of medium (6.0 ± 2.9

‰) (45 – 55 cm CCL, juveniles and sub-adults) and large (5.1 ± 1.0 ‰) (75 – 105 cm CCL, prepubescent to adult) turtles. Similarly, a significant correlation was observed between 13 turtle body size and blood plasma δ C values (One-way ANOVA F2,87 = 28.39, p < 0.000),

with a Tukey post-hoc analysis identifying large (75 – 105 cm CCL, prepubescent to adult) turtles were ~ 8.0 ‰ lower in δ13C then small and medium sized turtles.

Figure 5.5. Carbon (δ13C ‰) and Nitrogen (δ15N ‰) values of sampled plasma against the mean reference values from potential food groups (±SD) (Table 5.2.).

5.4.3 Comparisons between diets indicated by stable isotope analysis and lavage

A Bayesian mixing model of turtle plasma δ13C and δ15N values, and mean δ13C and δ15N values of potential foods suggested that individual turtles had isotopic values that were mostly consistent with the values of the food items observed in their immediate habitat/site of capture (Fig. 5.5, Table 5.2). Subsequent modelled proportional contributions based on the isotopic values of the four outlined food groups (mangrove/red algae, seagrass, chlorophyta/ochrophyta and animal matter) were generated for the sampled habitats (Fig. 5.6). Like the ~ 60 % seagrass (IRI) for seagrass in lavage samples of turtles foraging on the subtidal flats, a median dietary proportion of 0.45 (with a 95 % CI of 0.28, 0.62) for seagrass was inferred by the model. However, contrary to lavage sampling, a non-trivial median

proportion for animal matter (gelatinous macrozooplankton) 0.19 (with a 95 % CI of 0.01, 0.37) was observed (Fig. 5.6a, Table 5.4). The composition of diet within mangrove habitats was primarily mangrove/rhodophyta (0.57 with a 95 % CI of 0.45, 0.71), followed by seagrass (0.34 with a 95 % CI of 0.20, 0.45), contradicting the predominant dietary items indicated by oesophageal lavage for mangrove habitats (mangrove 49.4 % and red algae 48.8 %) (Fig. 5.6b, Table 5.4). Diverging from the compositions recorded by oesophageal lavage for rocky reef habitats (77.6 % seagrass and 16.2 % rhodophyta), modelled proportions indicated 0.68 (with a 95 % CI of 0.49, 0.85) of the diet was consistent with isotopic values observed in mangrove/rhodophyta with the proportion of the diet derived from seagrass 0.18 (with a 95 % CI of 0.04, 0.35) (Fig. 5.6c). The dietary composition based on SIA for individuals caught in sandbank habitats was consistent with the ~ 80 % seagrass (IRI) composition observed via oesophageal lavage, with a modelled proportion of 0.87 (with a 95 % CI of 0.77, 0.95) (Fig. 5.6d, Table 5.4).

5.5 Discussion Studies that utilise a combination of traditional and contemporary approaches to analyse diet are revealing unexpected feeding behaviours in green turtle populations throughout the world (Hatase et al. 2006, Arthur et al. 2007, Caut et al. 2008b, Lemons et al. 2011). These new insights suggest that past interpretations of turtle diets in relation to ontogenetic life stage and habitat shifts are not universally applicable. Similarly, this study found that dietary compositions of green turtles varied with ontogeny and habitat type at Port Curtis in Central Queensland, Australia.

5.5.1 Dietary composition from oesophageal lavage Oesophageal lavage analysis indicated that dietary composition of the most recent feeding event typically represented the food available in the immediate area of capture (Table 5.4), as reported in other studies (Bjorndal 1980, Forbes 1996). Individuals captured in mangrove habitats within Port Curtis had diets composed mostly of mangrove material from Avicennia marina and Rhizophora stylosa, and epiphytic rhodophytes (principally B. tenella and C. nipae) which are usually associated with the root stocks and trunks of these mangrove trees. In contrast, turtles inhabiting the intertidal sandbanks (Pelican Banks) had diets composed primarily of the seagrass species Zostera muelleri subsp. capricorni and Halophia ovalis which are the dominant plants found in this habitat (Rasheed et al. 2017). These dietary compositions were confirmed by SIA, which identified significant differences in plasma δ13C and δ15N values between the identified food groups (i.e., mangrove and algae, seagrass and animal material) characteristic of each sampled habitat (refer to Fig. 5.3). For example, individuals sampled from subtidal and sandbank habitats had plasma enriched δ13C values compared to individuals inhabiting mangroves or rocky reef sites; reference dietary items from these contrasting habitats align turtles caught in sandbank habitats with seagrass forage. In contrast, individuals in mangroves and rocky reef sites, which have principally algae and mangrove forage (which are depleted in δ13C) had isotopic values closely aligned with mangrove and algae.

Medium sized (45 – 75 cm CCL, juveniles and sub adults) and large (75 – 105 cm CCL, prepubescent to adult) turtles were more commonly captured within rocky reef and sandbank habitats. In contrast, small turtles (38 – 45 cm CCL) were almost exclusively caught within

the subtidal flats adjacent to the Boyne estuary and mangrove habitats fringing Facing island and the Pelican Banks. An apparent dichotomy was observed whereby the lavage samples of smaller turtles were composed almost exclusively of rhodophytes and/or mangrove material from mangrove or rocky reef habitats, whilst large turtles had consumed seagrass from the sandbanks which was consistent with the habitats where these turtles were caught. It is possible that the estuary and mangrove habitats act as nurseries for small turtles that are recent recruits to the foraging grounds, similar to how these habitats provide resources and shelter (including refuge from potential predators) to other marine species (Henriques & Almada 1998, Primavera 1998, Koenig et al. 2007). As posited by Carr (1980), and observed in foraging green turtles of Shoalwater Bay, Central Queensland, these small turtles may be undergoing ‘developmental migration’ (Limpus et al. 2005). These subtidal flats and fringing mangroves are typically tidally accessible and as such their use is somewhat size dependent, but are abundant in forage, offering ease of access to food but necessitating the movement to deeper subtidal habitats with an increase in body size. Similar associations between size and habitat have been recorded for green turtles in the Marquesas Keys, Florida where adult and sub-adult size classes were inhabiting deeper water areas than juveniles (Bresette et al. 2010).

Previous studies have established that foraging populations of green turtles throughout the world often have predominantly algal or seagrass diets, regularly associated with food availability, but with no apparent nutritional advantage to either diet (Bjorndal 1985, Garnett et al. 1985, McDermid et al. 2007). However, the relative digestibility of each food group is dependent upon hindgut microflora, with efficient digestion of seagrasses or algae requiring the acquisition of requisite microflora (Bjorndal 1985). Consequently, upon recruitment, it is reasonable to posit that small turtles inhabiting shallow nursery habitats gradually acquire the gut microflora necessary for the efficient digestion of the forage in their new habitat over time. In Port Curtis this may manifest as recently recruited (small) turtles subsisting on a predominantly algal-based diet, before shifting to a seagrass-dominant diet when their size necessitates a shift to deeper foraging grounds. Observations of shifts in diet with body size have been reported previously for immature (< 65 cm CCL) green turtles from Moreton Bay Australia, preferentially foraging on rhodophyta (e.g., Gracilaria sp.) in shallow subtidal habitats (Brand-Gardner et al. 1999), with a shift in δ13C values more consistent with a seagrass diet along with an increase in CCL (Arthur et al. 2008). Similarly, Burgett et al.

(2018) documented an enrichment in δ13C indicative of a shift toward seagrass diets associated with increasing size of foraging green turtles of the Bermuda platform. Observations of mangrove material in the diet of juvenile and immature green turtles have previously been reported in Shoalwater Bay, Queensland, where it was suggested that higher carbon volume and faster digestibility may be potential reasons for its consumption (Arthur et al. 2009). Consequently, mangrove cotyledons and propagules ingested by the small turtles of this sampled cohort may supplement their predominantly algal diets with nutritionally rich resources when these become seasonally available (Limpus & Limpus 2000). In contrast to the above interpretations, the abundant green turtle populations, encompassing all size classes, that forage on the adjacent outer reefs of the southern Great barrier Reef rarely encounter seagrass and exhibit algae dominated diets across all age classes (Limpus & Reed 1985, Forbes 1996). These observations illustrate variability in diet composition even within individuals of the same genetic stock.

5.5.2 Dietary composition from SIA To determine temporal stability in the diet of individual green turtles, δ13C values of blood plasma and skin tissue were compared. Isotopic values in blood plasma are estimated to represent diet within the last couple of weeks while δ13C isotopic values in the skin are likely to reflect the diet within the previous two to six months (Seminoff et al. 2007, Reich et al. 2008). Of the sampled cohort, ~ 40 % of foraging green turtles had δ13C values of plasma and epidermal tissue indicative of a dietary shift. However, this conclusion is reliant upon the application of correct discrimination factors. Currently, the best available discrimination factors are for juvenile green turtles and it is likely discrimination values would change with maturity (Vander Zanden 2012). Consequently, until discriminations factors for sub-adult and adult green turtles have been produced, inferences from this method should be considered with caution. An enrichment in δ13C was generally observed in individuals captured from mangrove habitats with the carbon isotopic composition of plasma more consistent with a seagrass-based diet, indicative of a shift in the predominant food items toward forage more consistent with seagrass (- 8.0 to - 14.0 ‰) δ13C isotopic values. In contrast, turtles captured on the sandbanks were depleted in δ13C, indicative of a dietary shift tending toward red algae and/or mangroves (- 20.0 to - 30.0 ‰). Incidences of dietary shift in this study were consistent with observations of turtles in neighboring foraging grounds (Prior et al. (2016).

An enrichment in δ15N values of plasma tissue above the reference values for seagrasses and algae was evident in 21 of the 174 sampled individuals. Despite eutrophication being associated with elevations in baseline δ15N values near anthropogenic influenced outflows (e.g. sewage treatment plants)(Bouillon et al. 2012), it was reasoned the sampled foraging regions in this study were far enough from the possible radii of anthropogenic sources of δ15N that anthropogenic enrichment was unlikely to be a significant contributor to observed tissue isotopic values. Consequently, δ15N values of sampled turtle tissue suggested a diet that was supplemented with animal prey of a higher trophic level, at or above reference values of gelatinous zooplankton. An investigation into the relationship between δ15N values and turtle body size suggested that all these omnivorous individuals were less than 55 cm CCL, except for a single adult. These observations concur with increasing reports of delayed shifts away from carnivory in recently recruited neritic juveniles, suggesting that they continue to forage on animal prey for some time in nearshore foraging habitats (Arthur et al. 2008, Prior et al. 2016). A Bayesian mixing model of SIA values from plasma of sampled green turtles inferred the proportional contribution of food groups to the diet of sampled individuals based on their isotopic values. In this study the overlapping isotopic ranges of taxa observed in ingesta samples allowed for their grouping into four potential forage categories (mangrove and rhodophytes, chlorophyta and ochrophyta, seagrass and animal material), suitable for a Bayesian modelling approach with two isotopic tracers (δ13C and δ15N) (Parnell et al. 2010). In contrast to oesophageal analysis, a MixSIAR MCMC hierarchical model identified that animal material was a non-trivial contributor to the diets of sampled individuals from subtidal flats, supporting previous observations of opportunistic supplementation of animal prey in green turtles throughout their neritic life stages (e.g. Greater Caribbean - Vander Zanden et al. 2013, Argentina - González et al. 2014, Japan - Shimada et al. 2014, Bahamas - Gillis et al. 2018).

Additionally, the mixing model indicated that other food groups, e.g., seagrasses or mangroves/rhodophyta may contribute to the diets of sampled individuals at greater proportions than indicated by lavage sampling. This is not surprising given that oesophageal lavage samples represent a small snapshot into the most recent foraging activity of captured turtles whereas SIA represents an integrated assessment of assimilated nutrients. Observed foraging ranges up to 81 km2 have previously been established for individuals in this

foraging population, as such these results may allude to the incorporation of dietary items for other foraging focal points with an individual’s broader foraging ground (Hamann et al. 2016). Additionally, given that capture of sampled turtles always coincided with daytime high tides on these predominantly shallow subtidal/intertidal foraging sites, it is possible that this disparity between lavage and SIA results may reflect variation in foraging behaviour over tidal cycles (Limpus & Limpus 2000). Variation in perceived diet, reflected in both oesophageal samples and tissue isotopic values, could be consistent with short-term shifts from intertidal algae (at high tide) to subtidal seagrasses (low tide) (Arthur et al. 2009), potentially beginning the progress of gut flora acquisition necessary for a transition to a seagrass-dominated diet when approaching maturity.

5.6 Conclusion Green turtles in Port Curtis foraged upon food items characteristic of their habitat of capture, evidenced from oesophageal lavage. Interestingly, a trend was identified in the body size of captured turtles from different foraging habitats, whereby small turtles (38 – 55 cm CCL) were found in shallow subtidal and intertidal habitats, feeding upon a mixture of mangrove material and rhodophytes, along with animal material. In contrast, the subtidal sandbanks characterised by seagrasses predominantly hosted larger immature and adult turtles. Consequently, it was hypothesised that green turtles inhabiting Port Curtis may utilise distinct foraging habitats at different stages of their neritic development and maturation.

The observation of this habitat use strategy is consistent with previous findings of ‘developmental migration’ observed in Shoalwater Bay, Central Queensland (Limpus et al. 2005). Further investigations using capture mark recapture methods and satellite telemetry, to monitor the foraging behaviour and development of these small, recent neritic recruits is required to validate this hypothesis and provide further insight into foraging behaviour. The use of specific foraging habitats at different stages of development highlights the need to ensure that adequate management strategies are in place to minimise the risk of exposing individuals at each of these stages to anthropogenic threats. Of relevance in Port Curtis is the reliance on mangroves as a potential nursery habitat to recent neritic recruits, as these sites are popular for recreational boating and coastal use but also under risk of commercial development. Additionally, the implementation of marine protected areas, or ‘go slow zones’

in areas of established turtle foraging would aid in the protection of foraging individuals from anthropogenic threats. The results of this study follow the increasing observations that foraging patterns in marine turtle species are highly variable, illustrating their ability to adapt to local environments.

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Chapter 6

Contributor Statement of Contribution Author: Owen I. Coffee (Candidate) Conception and design (100%) Analysis and interpretation (100%) Production (100%)

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Summary and directions for future research

This thesis presented data on the foraging ecology of loggerhead and green turtles from important habitats in central and southern Queensland. Using a combination of stable isotope analysis (SIA) and traditional dietary sampling (i.e. oesophageal lavage or faecal sampling) this study outlined discrete foraging habitat usage in a resident green turtle foraging population in Port Curtis and reported large variation in δ13C and δ15N values for loggerhead turtles living in Moreton Bay. In addition, it was the first study to report the lack of a latitudinal isotopic gradient in δ13C and δ15N of turtle tissue along the 2000 km Queensland coastline and the absence of similarities in SI values necessary to identify potential foraging regions of sampled nesting individuals. These two findings cast doubt on the reliability of SIA of δ13C and δ15N to identify the foraging region of loggerhead turtles nesting along the Woongarra coast. This contrasts with the loggerhead turtle nesting aggregations on the east coast of North America, where SIA differentiated regional groupings.

Chapter two investigated whether δ13C and δ15N values of plasma and epidermis from nesting loggerheads at Mon Repos could be used to infer their foraging regions by comparing them to the isotopic values of nesting individuals with known foraging grounds distributed over a 2000 km range along the east coast off Australia. Despite this method working successfully in nesting populations in the north-west Atlantic (Vander Zanden et al. 2015, Ceriani et al. 2017), the δ13C and δ15N values from sampled loggerhead tissue could not be used to differentiate turtles from different foraging regions. The isotopic values of the nesting cohort were compared to δ13C and δ15N values of turtles with known foraging grounds and foraging loggerheads from the Moreton Bay foraging population, most of which nest along the Woongarra coast, and reported no relationship between variations in the isotopic composition of turtle tissue and latitude, in contrast to that observed on the east coast of North America. It was posited that the prevailing oceanic currents of the east Australian coastline, which isolate the northern and southern Queensland coast, hamper the development of a baseline isotopic gradient with latitude. In addition, it was theorised that the lack of a notable temperature gradient and the influence of the Great Barrier Reef on water residence times also contribute to the lack of differences in regional baseline isotopic values.

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Chapter three investigated two green turtle rookeries on the east Australian coastline to establish, whether genetically separate nesting cohorts could be differentiated based on δ13C and δ15N values of epidermis, and if SIA could be used to identify the foraging regions of turtles nesting on Raine Island. Despite the geographic separation of the sampled rookeries, hierarchical cluster analyses could not differentiate turtles from the nGBR and sGBR genetic stocks by their δ13C and δ15N values. Using 40 satellite tracked turtles that nested on Raine Island, hierarchical cluster analysis on their δ13C and δ15N values could not reliably define their feeding region. Reported δ13C values of seagrasses along the east Australian coastline were reviewed and a weak relationship between seagrass δ13C values and latitude was observed. However, the sample size of reported values and the lack of standardised preservation methods necessitate the further collection and analysis of samples to confirm this trend. Hence, foraging regions of green turtles in the nGBR could not be confidently determined using SIA. It is proposed that, as concluded in chapter two, a combination of factors including the lack of a unidirectional prevailing oceanic current in the north Australian region and the potential influence of outflows and anthropogenic sources, prevents the creation of distinct regional isoscapes for δ13C, and consequently making regional identification of turtles based on their tissue SI values not possible.

Investigations into the dietary composition of loggerhead turtles foraging in Moreton bay were described in chapter four. The predominant prey identified through faecal sampling were consistent with previously observed taxa, principal prey were portunid Crustacea and Mollusca from the families Batillaridae, Mytillidae and Bivalva. This study was the first to report δ13C and δ15N isotopic values of foraging loggerheads from this foraging population and observed a large range in values for individuals living within overlapping foraging habitats. It is likely, in addition to the variation in observed diets through faecal analysis, that inherent variation in SI values within individuals from the same prey species contributed to the large variation of loggerhead turtle tissue. Based on best available discrimination factors, tissue to tissue isotopic analyses identified most of the sampled individuals had isotopically consistent diets across the turnover periods represented by their plasma and epidermis tissue. However, despite consistency in diet at an individual level, there was distinct variation in diet across the population. The foraging population utilised a variety of foraging methods, as evidenced by distinctly different faecal contents from subsequent excreta within captive sampled individuals. While these findings provide insight into the diet and the range in tissue

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isotopic values of this loggerhead turtle population, a future study with a larger number of turtles sampled for their faecal content and compared to SI values of potential prey taxa is needed to help explain why such a wide range of SI values were found within turtle tissues from a single foraging location.

Chapter five investigated the dietary composition of green turtles in a central Queensland foraging population and found their diet varied with capture location. Individuals captured amongst mangrove and rocky reef habitats were feeding predominantly on red algae or mangrove material, whereas turtles foraging on shallow sand banks were feeding primarily on seagrass. By comparing isotopic values of tissue with different turnover rates, it was estimated that ~ 40 % of the sampled turtles had shifted to an isotopically different diet (towards/from a seagrass diet), consistent with previous research in the region (Prior et al. 2016). Interestingly, most of the individuals identified as having changed diet were captured in mangrove habitats and had epidermal isotopic values reflective of a mangrove and algae diet in contrast to the food types available at their capture location. This finding may reflect the periodic availability of the mangrove habitats as foraging grounds. Using a Bayesian modelling approach which considered reference δ13C and δ15N isotopic values from potential forage items, this study determined that dietary compositions were largely consistent with oesophageal sampling, although the predominant forage items were likely underrepresented in lavage samples. Similar to previous studies on green turtle foraging populations (Heithaus et al. 2002, Lemons et al. 2011, González et al. 2014, Shimada et al. 2014), δ15N isotopic values indicated animal material continues to constitute part of the diet in these turtles beyond recruitment from their oceanic developmental period.

This study also identified size related differentiation in habitat use, with smaller turtles found amongst mangrove and shallow rocky reef habitats, while medium sized and mature turtles inhabited the seagrass dominated sand banks. This finding highlights that mangrove habitats may be a critical foraging environment for recently recruited green turtles in this region, likely providing protection from predation. Differential habitat usage, based on body condition, has previously been observed among green turtles in Shark Bay, Western Australia (Heithaus et al. 2007). In future studies, acoustic, GPS or satellite telemetry could be used to explore how juvenile turtles use the mangrove habitat over a tidal cycle, as it is not known where these turtles go during low tide when the mangrove habitat is not available.

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Further studies are needed to evaluate the baseline isotopic values of food items within habitats along the east coast of Australia and establish whether differentiation between regions is possible. Studies such as those by Bradshaw et al. (2017) and Pearson et al. (2019) present the possibility that different biogeochemical tracers, like δ34S and δ18O, may be better able to differentiate between different foraging regions.

This research is the first to report isotopic values from sampled tissues for nesting green and loggerhead turtles from the east coast of Australia. The results of analyses indicate that for both species, tissue SI values could not reliably predict the foraging region. These findings support the assertion that SIA is not a universal panacea for resolving migratory pathways in marine turtles (Hobson et al. 2019), and that potential regional oceanographic variations may confound future inferences using SIA methodologies. Studies that incorporate additional tracers (e.g. δ34S and δ18O) may add discriminative power to future isotopic analyses, but the currently used δ13C and δ15N isotopes do not have the resolving power in the east coast Australia region. Unless regionally distinct isoscapes of other isotopes can be confirmed, capture-mark-recapture and satellite telemetry remain the only reliable methods for identifying the regional feeding grounds of sea turtles nesting along the east Australian coast.

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Appendix

Other publications during candidature:

Book

Moreton Bay Quandamooka & Catchment: Past, present, and future

ISBN

978-0-6486690-0-5

Chapter Chapter 5. Habitats, Biodiversity and Ecosystem Function Research Paper Title

Marine turtles in Moreton Bay

DOI

10.6084/m9.figshare.8074349

Publication date

2019

Cite this paper as: Limpus CJ, Coffee OI. 2019. Marine turtles in Moreton Bay. In: Tibbetts IR, Rothlisberg PC, Neil DT, Homburg TA, Brewer DT, & Arthington AH (Eds). Moreton Bay Quandamooka & Catchment: Past, present, and future. The Moreton Bay Foundation. Brisbane, Australia. Available from: https://moretonbayfoundation.org/

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Marine turtles in Moreton Bay

Colin J. Limpus 1, Owen I. Coffee2*

Author affiliations: 1. Queensland Government, Department of Environment and Science, Ecosciences Precinct Dutton Park Qld, 4102; 2.School of Biological Sciences, University of Queensland, St Lucia Qld, 4072. Corresponding author: [email protected]

ORCID Owen Coffee: https://orcid.org/0000-0002-2929-8803

Abstract Six species of marine turtle from two families have been recorded foraging within the waters of Moreton Bay. Of those species, two (green turtle, Chelonia mydas and loggerhead turtle, Caretta caretta) are resident in substantial foraging populations that contribute annually to nesting populations of their southern Great Barrier Reef and South Pacific Ocean genetic stocks, respectively. Capture-mark-recapture studies of resident foraging populations in Moreton Bay commenced in 1990, serving as a platform supporting a wide range of additional studies of turtles in Moreton Bay that have garnered valuable insights into the diet, habitat use, physiology, toxicology, genetics and population dynamics of the resident turtle populations. This paper provides a summary of the research completed over the past few decades on turtle biology within Moreton Bay and highlights areas of future research.

Keywords: capture-mark-recapture, diet, health, physiology, toxicology, population dynamics

Introduction The shallow coastal waters of Moreton Bay have supported marine turtle populations since sea levels rose following the last ice age. They were hunted for food by the local Indigenous people and, following the arrival of European settlers, hunted commercially from 1824 to 1950 (Fig. 1) (1, 2). In recent times, six species of marine turtle from two families have been recorded foraging in the waters of Moreton Bay. Five species of the family Cheloniidae are year-round foraging residents: loggerhead turtle, Caretta caretta, (3); green turtle, Chelonia mydas (4); hawksbill turtle, Eretmochelys imbricata (5); olive ridleyturtle, Lepidochelys olivacea (6); flatback turtle, Natator depressus (6). Leatherback turtles (Dermochelys coriacea), from the family Dermochelyidae, are migratory visitors (6, 7). Marine turtles within Australian waters are afforded protected under the Australian Government's Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) and by state and territory legislations. Two species (green and loggerhead) migrate into the Moreton Bay waters and nest annually at low density on the ocean beaches of the Bay islands (6). Small post-hatchling loggerhead and green turtles travelling south with the East Australian Current from the nesting beaches of the southern Great Barrier Reef (GBR) region pass through the waters offshore Moreton Bay on their way south and east into the South Pacific Ocean (8). This review does not address biological data associated with debilitated or dead marine turtles that have washed in from the pelagic waters of the Coral or Tasman seas.

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In: Tibbetts IR, Rothlisberg PC, Neil DT, Homburg TA, Brewer DT, Arthington AH. (Eds). 2019. Moreton Bay Quandamooka & Catchment: Past, present and future. The Moreton Bay Foundation. Brisbane, Australia. pp. 401 - 414 https://moretonbayfoundation.org

Figure 1. Green turtle (Chelonia mydas) harvest in Moreton Bay circa 1934 (49).

Immature marine turtles recruit from a pelagic foraging life-history phase in the open ocean to benthic foraging in coastal waters at different sizes: loggerhead turtles recruit to benthic feeding in Moreton Bay at a mean curved carapace length (CCL) of 78.2 cm (SD=3.75, n=52) at approximately 16 years of age (9); green turtles similarly recruit to benthic feeding in Moreton Bay at CCL = 44.2 cm (SD=3.97, n=98) and CCL = 45.1 cm (SD=3.24, n=54.0) for females and males respectively. Hawksbill turtles are believed to recruit to Moreton Bay benthic foraging areas at approximately CCL = 36.0 cm (10). Large immature and adult leatherback turtles are not permanent residents of Moreton Bay; they are transient visitors to Moreton Bay during the autumn and winter months. The frequency of encounters with leatherback turtles in the Moreton Bay region has substantially declined in recent decades (11). Most green turtles foraging in Moreton Bay are from the southern GBR genetic stock as defined by FitzSimmons and Limpus (12): > 90% of adult females based on flipper tag recoveries (13), 95% of adults and 85% of immature green turtles based on population genetics analysis (14). A small proportion of the foraging green turtles in Moreton Bay originate from the northern GBR, New Caledonia, Vanuatu, French Polynesia and the eastern Pacific (14). Only loggerhead turtles from the south-west Pacific genetic stock that breed in eastern Australia and New Caledonia have been recorded in eastern Australia, including Moreton Bay (12). There is no clear definition of the genetic stock of origin for hawksbills that forage in Moreton Bay. Systematic Department of Environment and Science (DES) capture-mark-recapture (CMR) studies of foraging marine turtles in Moreton Bay commenced in 1990 and identified that the most abundant species in the Bay were green, loggerhead and hawksbill turtles (3–6). These studies contributed to the development and implementation of the Moreton Bay Marine Park, with the identified high use areas for foraging turtles designated within Marine National Park green zones and mandatory go slow areas for recreational and commercial vessels. Turtles are most commonly

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encountered on the shallow seagrass-dominated Eastern Banks adjacent to Dunwich on North Stradbroke Island northwards along the western face of Moreton Island. Turtles are also encountered along the fringing mangroves and shallow muddy flats at the southern extent of the Bay and throughout Deception Bay in the north-west. The green turtle population in the Moreton Banks has approximately tripled during the 25 years of the CMR study from 1990–2014 (15). Satellite telemetry studies have demonstrated that green turtles maintain long-term fidelity to their respective foraging sites in Moreton Bay (16). Based on satellite telemetry, the home range of green turtles foraging in eastern Moreton Bay was 128.8 km2, 23.7 km2 in southern Moreton Bay and 121.8 km2 in north-western Moreton Bay (17). Adult female green turtles resident in Moreton Bay commenced breeding during 1990–2007 at a mean CCL = 108.7 cm (SD=4.56, n=32) (13). The green turtles in Moreton Bay are on average amongst the largest and fastest growing in eastern Australia (18). Once recruited to benthic foraging residency, the loggerhead turtles show high fidelity to their respective foraging areas across decades (19, 20). These recruited turtles retain fidelity to their foraging areas following displacement (21). Based on satellite telemetry, the home range of loggerhead turtles foraging in eastern Moreton Bay was 155.8 km2, 32.7 km2 in southern Moreton Bay and 15.6 km2 in western Moreton Bay (17). Adult female loggerhead turtles of the south-west Pacific breeding stock nesting at Mon Repos commence breeding at a mean CCL = 93.65 cm (SD=4.25, n=69) (9). Marine turtles that forage in Moreton Bay migrate to breed at widely dispersed and usually distant nesting beaches, with most green turtles that forage in Moreton Bay migrating to breed on the islands of the Capricorn-Bunker Group in the southern GBR between North West Island and Lady Elliot Island. Small numbers of the Moreton Bay green turtles have been recorded nesting at Raine Island in the northern GBR, on islands within the Recifs d'Entrecasteaux in north-western New Caledonia and Vanuatu (Fig. 2a). Most loggerhead turtles that forage in Moreton Bay migrate to breeding grounds on the mainland beaches between Bundaberg and Agnes Water (Woongarra coast being the major breeding site). Smaller numbers of Moreton Bay loggerhead turtles have been recorded on the islands of the southern GBR between the Swain reefs and Lady Elliot Island; isolated nesting records have occurred in northern New South Wales and eastern New Caledonia (Fig. 2b). The CMR studies have been a platform to support a wide range of additional studies of turtles in Moreton Bay, including but not limited to diet, habitat use, physiology, toxicology, genetics and population dynamics. DES CMR studies from the early 1990s to the present demonstrated a robustly increasing green turtle foraging population on the eastern banks of Moreton Bay but a declining population of loggerhead turtles for the same area. The successes for green turtles are attributable to a consistently increasing green turtle nesting population in the southern GBR since strong protection of the species and their habitats commenced in 1950. Recruitment of new immature green turtles taking up residency is a regularly observed feature. The problem for the declining loggerhead population originates from excessive mortality of small post-hatchlings ingesting plastic debris as they travel in the East Australian Current and

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Figure 2 Recorded nesting rookeries of the South Pacific (a) green (Chelonia mydas) and (b) loggerhead (Caretta caretta) turtles that forage in Moreton Bay. Photos by Col Limpus. additional mortality from fisheries bycatch in the eastern Pacific. These post-hatchling mortalities have resulted in a severely depleted recruitment of young loggerheads into residency in Moreton Bay since the early 1990s.

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Diet and habitat use Marine turtles undergo a number of distinct life stages accentuated by changes in foraging habitat and diet (22). For most marine turtle species this begins with a protracted open-ocean foraging period post hatching. Marine turtles exhibiting this oceanic-neritic development pattern subsist on a predominantly carnivorous diet borne of pelagic macrozooplankton; they then shift foraging strategy and diet composition upon recruitment to neritic foraging habitats (23). Boyle and Limpus (8) have documented the diet, including ingested plastic, of the small post-hatchling green and loggerhead turtles passing Moreton Bay on the East Australian Current. Loggerhead turtle (Caretta caretta) Following recruitment to benthic foraging in Moreton Bay, loggerhead individuals occupy a range of habitats including intertidal and subtidal seagrass meadows, coral and rocky reefs, and the soft- bottom, deeper, subtidal habitats. While foraging loggerheads in South East Queensland have been reported feeding on over 100 taxa, in Moreton Bay they are most commonly found to forage on species of portunid crabs and a range of benthic gastropod and bivalve molluscs (Table 1). While loggerheads feed extensively on epifaunal species they will also mine the substrate to obtain infauna prey items (24, 25) and take prey items from the midwater column and at the surface (26). Table 1. Summary of findings from dietary studies on the loggerhead turtle (Caretta caretta) in the Moreton Bay region. Loggerhead turtle (Caretta caretta) Preen (24) 1996 ‘Infaunal mining’ foraging method observed (n=13) Polychaeta, thin-walled Mollusca and Bivalvia Limpus et al. 2001 Gut and faecal content (n=53) (26) 94 benthic and near-benthic taxa Predominantly Mollusca or Crustacea, Echinodermata, Porifera, Cnidaria and Osteichthyes Diet a function of feeding area not sex or size West (25) 2005 Faecal contents (n=24) Predominantly Crustacea and Mollusca Boyle and 2008 Gut content (n=7) of oceanic post-hatchlings Limpus (8) Pelagic Cnidaria, Crustacea and Mollusca > 50% of sampled individuals observed to have ingested synthetic materials Limpus and 2008 Mortalities from predation on porcupine fish (n=12) Limpus (51) Coffee (52) Unpubl. Faecal contents (n=12) data Predominantly Crustacea and Mollusca

Green turtle (Chelonia mydas) Within the Moreton Bay area, foraging populations of green turtle have been observed to feed within tidal and subtidal habitats, grazing primarily on algae (Gracilaria sp. and Hypnea sp.) and seagrass (Zostera capricorni and Halophila ovalis) and opportunistically on mangrove (Avicennia marina) leaves and propagules (Table 1). At higher trophic levels, observations of opportunistic foraging on gelatinous animal material in Moreton Bay (27–29) are consistent with findings from other foraging populations (Fig. 3) (30–33).

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Figure 3. Neritic-foraging immature green turtle prey on jellyfish, northern NSW. Image by Owen Coffee (50)

Table 2. Summary of findings from dietary studies on the green turtle (Chelonia mydas) in the Moreton Bay region Authors Year Dietary observations Brand, Lanyon and 1999 Digestive retention and dietary compositions (n=3) Limpus (53) Predominantly seagrass Halophila ovalis and algae Gracilaria sp. Digestive retentions of 6.5–13.5 days Brand-Gardner, 1999 Oesophageal lavage (n=20) Limpus and Observed preference for Gracilaria sp. Lanyon (54) Inverse relationship with fibre levels and preferred species

Read and Limpus 2002 Oesophageal lavage (n=240) (55) Predominantly seagrass Halophila ovalis and red algae Gracilaria cylindrica and Hypnea spinella Animal material and cotyledons of mangrove Avicennia marina observed Arthur et al. (27) 2007 Animal-borne imaging (n=6) Individuals foraged upon gelatinous animal material in the water column One sampled individual recorded foraging on seagrasses Arthur, Boyle and 2008 Stable isotope analysis (SIA) (n=64) at distinct life stages (hatchlings, Limpus (28) pelagic juveniles, small immature, large immature and adult) Elevated δ15N in recent recruit neritic juveniles consistent with individuals foraging at higher trophic levels Boyle and Limpus 2008 Gut contents (n=31) of oceanic post-hatchlings (8) Observed pelagic Cnidaria, Crustacea (predominantly Malacostraca) and Mollusca Over 65% of sampled individuals observed to have ingested synthetic materials Brine (29) 2008 Oesophageal and SIA (n=24) Lavage identified seagrasses Halophila sp. and Halodule sp. as largest contributors to diet SIA identified elevated δ15N in recent recruits and larger size classes, indicative of higher trophic feeding Townsend et al. 2012 Necropsy (n=2) (56) Multi-stage mass spectrometry identified envenomation from accidental ingestion of blue-ringed octopus (Hapalochlaena fasciata) as cause of death

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Hawksbill turtle (Eretmochelys imbricata) While there are no studies on the foraging ecology of the resident hawksbill turtles of Moreton Bay, individuals foraging off the coast in the Northern Territory and the northern GBR have been recorded foraging on algae (Rhodophytes, Chlorophytes and Phaeophytes), with a significant contribution of sponges and soft corals to their diet (34, 35). These observations are consistent with those from foraging individuals sampled in the Caribbean and the Indian Ocean (36, 37). There have been observations of individual adult size hawksbills selectively feeding on large sea anemones on the subtidal rocky reef on the seaward side of North Stradbroke Island (6). Leatherback turtle (Dermochelys coriacea) Unlike cheloniid marine turtles, the leatherback turtle does not recruit to a benthic, life-history phase. Instead they retain a surface-water foraging habitat whether they are in oceanic or neritic waters throughout their life. In the north-west Pacific and the Atlantic their diet is primarily large, gelatinous, macrozooplankton (cnidarians, ctenophores and colonial tunicates such as Pyrosoma sp.) (38–41). While limited data exist on their foraging ecology in the south-west Pacific, they have been regularly reported to feed on the blue blubber jellyfish (Catostylus mosaicus) in Moreton Bay (11). Olive ridley turtle (Lepidochelys olivacea) Following an oceanic developmental period, olive ridley turtles in Australia have been reported recruiting to neritic foraging environments (42). While there is a paucity of data on the foraging ecology of recruited immature and adult olive ridleys, they are thought to subsist on a carnivorous diet composed primarily of gastropods, cnidarians and benthic crustaceans (42, 43), consistent with observations on the diet of adult olive ridley sampled off the coast of Mexico (44). Flatback turtle (Natator depressus) Forgoing a pelagic developmental period, flatback turtles spend their post-hatchling through to their adult life stages in neritic foraging environments (22). While limited observations exist on the foraging ecology of flatback turtles, it is posited that foraging individuals in the Moreton Bay region have diets consistent with those reported in individuals throughout the east and west coasts of Australia. They subsist on carnivorous diets, composed primarily of soft-bodied invertebrates such as sea pens, soft corals, holothurians and jellyfish (43–46).

Health, physiology and toxicology A substantial marine turtle population lives within the semi-enclosed waters of Moreton Bay, which receives the outflow of five rivers (Albert, Logan, Brisbane, Pine and Caboolture). These rivers receive the chemical discharge associated with more than two million human inhabitants and their urban development, agricultural and pastoral activities, and industry. As such, the turtles of Moreton Bay are more likely to be impacted by river outflow than any other population of marine turtles in Queensland. Elevated levels of heavy metals and organo-halide compounds have been detected in marine turtles resident in Moreton Bay; to date no studies have demonstrated a detrimental impact of these substances on turtle biology (Table 3). The

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associated health, toxicology and physiology related studies on marine turtles within Moreton Bay are summarised in Table 3. Boat strike, entanglement in crab pots and fishing gear and to a lesser extent, the ingestion of synthetic debris, were the primary sources of anthropogenic mortality for turtles within Moreton Bay (9, 13, 47, 48). Indigenous harvest of marine turtles in Moreton Bay is not quantified.

Summary Since the start of capture-mark-recapture studies in 1990, research, in tandem with the state’s tertiary institutes, has determined which species inhabit the Bay, their genetic stocks and population dynamics, and has worked toward the conservation and management of the resident populations. This paper has outlined some of the research achievements of the past few decades, however, as identified, many questions remain. The large numbers of resident foraging turtles within Moreton Bay are ideally situated for ongoing studies by research institutes in the vicinity of the Bay, allowing new research techniques to be developed and the anthropogenic impacts on these species to be quantified into the future.

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UQ Research and Innovation Director, Research Management Office Nicole Thompson 13-Apr-2015 Animal Ethics Approval Certificate Please check all details below and inform the Animal Welfare Unit within 10 working days if anything is incorrect.

Activity Details Chief Investigator: Dr David Booth Title: Using stable isotope analysis to determine foraging groups and reproductive output in sea turtles AEC Approval Number: SBS/017/15/SRRF/URG Previous AEC Number: Approval Duration: 26- Mar-2015 to 26-Mar -2018 Funding Body: URG Group: Native and exotic wildlife and marine animals Other Staff/Students: Col Limpus, Owen Coffee

Location(s): Moreton Bay Research Centre Other Queensland Location

Summary Subspecies Strain Class Gender Source Approved Remaining Terrapins, Tortoises Green Turtle Adults Unknown Natural Habitat 300 300 and Turtles ( Chelonia mydas) Terrapins, Tortoises Loggerhead Turtle Adults Unknown Natural Habitat 20 20 and Turtles ( Caretta carretta ) Terrapins, Tortoises Green Turtle Adults Female Natural Habitat 300 300 and Turtles ( Chelonia mydas) Terrapins, Tortoises Loggerhead Turtle Adults Female Natural Habitat 600 600 and Turtles ( Caretta carretta ) Permits Marine Parks Permit QS2015/MAN298 25-Mar -2015 to 24-Mar -2018 Scientific Purposes Permit WITK15830215 01-Apr -2015 to 31-Mar -2018 Scientific Purposes Permit WISP15829615 01-Apr -2015 to 30-Jun -2018 Provisos Approval Details Description Amount Balance

Terrapins, Tortoises and Turtles (Green Turtle (Chelonia mydas), Female, Adults, Natural Habitat) 26 Mar 2015 Initial Approval 300 300 Terrapins, Tortoises and Turtles (Green Turtle (Chelonia mydas), Unknown, Adults, Natural Habitat) 26 Mar 2015 Initial Approval 300 300 Terrapins, Tortoises and Turtles (Loggerhead Turtle (Caretta carretta), Female, Adults, Natural Habitat) 160

Animal Welfare Unit Cumbrae-Stewart Building +61 7 336 52925 (Enquiries ) [email protected] UQ Research and Innovation Research Road +61 7 334 68710 (Enquiries ) uq.edu.au/research The University of Queensland Brisbane Qld 4072 Australia +61 7 336 52713 (Coordinator ) Page 1 of 2

26 Mar 2015 Initial Approval 600 600 Terrapins, Tortoises and Turtles (Loggerhead Turtle (Caretta carretta), Unknown, Adults, Natural Habitat) 26 Mar 2015 Initial Approval 20 20

Please note the animal numbers supplied on this certificate are the total allocated for the approval duration Please use this Approval Number: 1 . When ordering animals from Animal Breeding Houses 2 . For labelling of all animal cages or holding areas. In addition please include on the label, Chief Investigator's name and contact phone number. 3 . When you need to communicate with this office about the project.

It is a condition of this approval that all project animal details be made available to Animal House OIC. ( UAEC Ruling 14/12/2001)

The Chief Investigator takes responsibility for ensuring all legislative, regulatory and compliance objectives are satisfied for this project. This certificate supercedes all preceeding certificates for this project (i.e. those certificates dated before 13-Apr-2015)

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