Sustained Prehistoric Exploitation of a Marshall Islands Fishery

Sustained prehistoric exploitation of a Marshall Islands fishery: ichthyoarchaeological approaches, marine resource use, and human- environment interactions on Ebon Atoll

Ariana Blaney Joan Lambrides BA (Hons)

A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2017 School of Social Science Abstract

Atolls are often characterised in terms of the environmental constraints and challenges these landscapes impose on sustained habitation, including: nutrient-poor soils and salt laden winds that impede plant growth, lack of perennial surface fresh water, limited terrestrial biodiversity, and vulnerability to extreme weather events and inundation since most atolls are only 2-3 m above sea level. Yet, on Ebon Atoll, Republic of the Marshall Islands in eastern Micronesia, the oceanside and lagoonside intertidal marine environments are expansive, with the reef area four times larger than the land area, supporting a diverse range of taxa. Given the importance of finfish resources in the Pacific, and specifically Ebon, this provided an ideal context for evaluating methods and methodological approaches for conducting Pacific ichthyoarchaeological analyses, and based on this assessment, implement high resolution and globally recognised approaches to investigate the spatial and temporal variation in the Ebon marine fishery. Variability in landscape use, alterations in the range of taxa captured, archaeological proxies of past climate stability, and the comparability of archaeological and ecological datasets were considered. Utilising a historical ecology approach, this thesis provides an analysis of the exploitation of the Ebon marine fishery from initial settlement to the historic period—two millennia of continuous occupation.

The thesis demonstrated the importance of implementing high resolution methods and methodologies when considering long-term human interactions with marine fisheries. Improving methods and data quality of Pacific fishing studies included using vertebral morphometrics for fish size reconstructions and the utilisation of all cranial and postcranial remains for taxonomic identifications. Spatial analysis of habitation sites spread across three islets representing the windward-leeward gradient indicated that marine environments local to each site were not influencing taxonomic composition, but the variability in richness and evenness identified is likely a reflection of fishing technology and site function. There was no indication of significant human impact to the inshore reef taxa, which may be a reflection of the flexible foraging strategies implemented and the resilience and structure of these marine environments. As such, the shifts in the relative abundance of skipjack (K. pelamis) in the archaeological sites were attributed to the potential influence of ENSO variability over the last two millennia.

With the implementation of these comprehensive methods and the use of historical ecology as a conceptual framework the range of research questions that could be explored was expanded. Consequently, this thesis was able to address some of these questions, including: the identification of variability in foraging practices across small spatial scales, the usefulness of ichthyoarchaeological data for tracking environmental stability, and distinguishing between changes

i in resource availability and signals of human impacts or marine habitat degradation. It is hoped that research efforts in the tropical Pacific Islands will see the continued integration of ecological and archaeological datasets for addressing not only archaeological research questions, but to provide potentially useful contributions to modern biological conservation and restoration efforts.

Declaration by author

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

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

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

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

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Publications during candidature

Peer-reviewed papers Lambrides, A. B. J., and Weisler, M. I. (2017). Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean. The Journal of Island and Coastal Archaeology (accepted March 2017). Giovas, C. M., Lambrides, A. B. J., Fitzpatrick, S., and Kataoka, O. (2017). Reconstructing prehistoric fishing zones in Palau, Micronesia using fish remains: A blind test of interanalyst correspondence. Archaeology in Oceania 52: 45-61. Weisler, M. I., Lambrides, A. B. J., Quintus, S., Clark, J. and Worthy, T. (2016). Colonisation and Late Period Faunal Assemblages from Ofu Island, American Samoa. Journal of Pacific Archaeology 7: 1-19. Harris, M., Lambrides, A. B. J., and Weisler, M. I. (2016). Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands. Journal of Archaeological Science: Reports 6: 221-229. Lambrides, A. B. J., and Weisler, M. I. (2016). Pacific Islands ichthyoarchaeology: Implications for the development of prehistoric fishing studies and global sustainability. Journal of Archaeological Research 24: 275-324. Lambrides, A. B. J., and Weisler, M. I. (2015). Applications of vertebral morphometrics in Pacific Island archaeological fishing studies. Archaeology in Oceania 50: 53-70. Lambrides, A. B. J., and Weisler, M. I. (2015) Assessing protocols for identifying Pacific Island archaeological fish remains: The contribution of vertebrae. International Journal of Osteoarchaeology 25: 838-848.

Publications included in this thesis

Chapters of this thesis are manuscripts accepted for publication in peer-reviewed journals. I am the lead author of four of these publications. I was responsible for conception and design of the research, analysis and interpretation of data, and the writing, submission and revision of all manuscripts. I was the second author on a fifth manuscript. I worked closely with the lead author on conception and design of the research, analysis and interpretation of data and the writing of the manuscript.

Chapter 2, “Pacific Islands ichthyoarchaeology: Implications for the development of prehistoric fishing studies and global sustainability” has been peer-reviewed and accepted for publication in Journal of Archaeological Research.

Contributor Statement of contribution A.B.J. Lambrides (Candidate) Collation and review of literature (100%) Wrote and edited the paper (70%) M.I. Weisler Wrote and edited the paper (30%)

Chapter 3, “Assessing protocols for identifying Pacific Island archaeological fish remains: The contribution of vertebrae” has been peer-reviewed and accepted for publication in International Journal of Osteoarchaeology.

Contributor Statement of contribution A.B.J. Lambrides (Candidate) Research conception and design (50%) Analysis and interpretation of data (100%) Wrote and edited the paper (65%) M.I. Weisler Research conception and design (50%) Wrote and edited the paper (35%)

Chapter 4, “Applications of vertebral morphometrics in Pacific Island archaeological fishing studies” has been peer-reviewed and accepted for publication in Archaeology in Oceania.

Contributor Statement of contribution A.B.J. Lambrides (Candidate) Research conception and design (60%) Analysis and interpretation of data (100%) Wrote and edited the paper (80%) M.I. Weisler Research conception and design (40%) Wrote and edited the paper (20%)

Chapter 5, “Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands” has been peer-reviewed and accepted for publication in Journal of Archaeological Science: Reports.

Contributor Statement of contribution A.B.J. Lambrides (Candidate) Research conception and design (40%) Analysis and interpretation of data (50%) Wrote and edited the paper (40%) M. Harris Research conception and design (40%) Analysis and interpretation of data (50%) Wrote and edited the paper (50%) M.I. Weisler Research conception and design (20%) Wrote and edited the paper (10%)

Chapter 6, “Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean” has been peer-reviewed and accepted for publication in The Journal of Island and Coastal Archaeology.

Contributor Statement of contribution A.B.J. Lambrides (Candidate) Research conception and design (80%) Analysis and interpretation of data (100%) Wrote and edited the paper (80%) M.I. Weisler Research conception and design (20%) Wrote and edited the paper (20%)

Contributions by others to the thesis

Marshall Weisler was my principal supervisor and is the director of the Marshall Islands archaeological research program initiated in 1993. Weisler contributed to the development of the research framework and research questions, and provided direction and feedback throughout the production and publication of all peer-reviewed manuscripts that contribute to this thesis.

Matthew Harris was another member of the project team who investigated the mollusc assemblages. We collaborated on a single manuscript (Chapter 5) allowing a broad assessment of marine resource exploitation on Ebon Atoll utilising both the archaeological mollusc and fish bone assemblages.

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

The archaeological fish bone assemblage used in Chapter 3 was originally analysed as part of a BA Honours, The University of Queensland, 2011, degree awarded 15 December 2011. However, the assemblage was entirely re-analysed during my candidature to address research questions specific to my thesis, and as such these results have not been submitted elsewhere.

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Acknowledgements

There are a number of people that I must offer my sincere thanks for their tireless efforts in supporting me through this research. I was very grateful and fortunate to have as my academic advisors Professor Marshall Weisler and Dr. Tiina Manne. This research would not have been possible without the support offered by Marshall who introduced me to Pacific archaeology, made the fieldwork on Ebon a reality, and provided guidance throughout all stages of my candidature. Thank-you kindly. I must thank Josepha Maddison (Historic Preservation Office, Ministry of Internal Affairs) and Lajan Kabua (former mayor, Ebon Atoll) for granting permission to conduct the fieldwork, the people of Ebon that welcomed us to their home, and thanks to Lyn, Dom, Riem, Josen, Frankie, Nashir, Lister, Jolie, and Jin for their assistance in the field.

This research was supported by The University of Queensland School of Social Science through a number of travel and research bursaries, by an Australian Government Research Training Program Scholarship, and by the Donald Tugby Archaeological Research Award. The Ebon fieldwork was supported by a grant to Marshall Weisler from the Office of the Deputy Vice Chancellor (Research).

I must thank my fellow archaeology PhD candidates Matt Harris, Aleisha Buckler, Xavier Carah, Tam Smith, Emma James, and Dale Simpson. This support network was invaluable and to each of you I am deeply grateful. Thanks must also go to Dr. Glenys McGowan for providing mentorship throughout my candidature, particularly when I began co- lecturing/course-coordinating the Summer Semester offering of the Forensic archaeology course in 2015, as Glenys generously shared her extensive knowledge of teaching and provided constant support.

To my family, Matt, my parents, Chris and Pamela, Jack, Charlie, Jo-anne, Lisa, Ross, Laura, Bonny, Mike, Jen, Billy, and Ellen that each offered love and support over many years. Heartfelt thanks! Lastly, I was privileged to have had Anne and Joan as my Grandmothers, they offered me unwavering support, so this thesis is for them.

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Keywords atoll archaeology, historical ecology, ichthyoarchaeology, island and coastal archaeology, marine subsistence, Marshall Islands, Micronesia, Pacific Islands, prehistoric fishing, vertebrae analysis

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 210106, Archaeology of New Guinea and Pacific Islands (excl. New Zealand), 50% ANZSRC code: 210102, Archaeological Science, 40% ANZSRC code: 210199, Archaeology not elsewhere classified, 10%

Fields of Research (FoR) Classification

FoR code: 2101, Archaeology, 100%

Table of Contents

Page

Abstract i

Declaration by author iii

Publications during candidature iv

Publications included in this thesis iv

Contributions by others to the thesis vii

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

Acknowledgements viii

Keywords ix

Australian and New Zealand Standard Research Classifications (ANZSRC) ix

FoR Classification ix

List of Figures xii

List of Tables xv

Chapter 1. Introduction 1

Rationale 2

Thesis Research Aims 3

Thesis Structure 5

References Cited 7

Chapter 2. Pacific Islands Ichthyoarchaeology: Implications for the 14 Development of Prehistoric Fishing Studies and Global Sustainability

Chapter 3. Assessing Protocols for Identifying Paciﬁc Island Archaeological 82 Fish Remains: The Contribution of Vertebrae

Chapter 4. Applications of vertebral morphometrics in Pacific Island 105 archaeological fishing studies

Chapter 5. Windward vs. leeward: Inter-site variation in marine resource 146 exploitation on Ebon Atoll, Republic of the Marshall Islands

Chapter 6. Late Holocene Marshall Islands archaeological tuna records 170 provide proxy evidence for ENSO variability in the western and central Pacific Ocean

Chapter 7. Conclusion 213

Main Findings 213

Future Objectives for Enhancing Research Outcomes 220

Concluding Remarks 221

References Cited 122

Appendix A: Ebon Atoll fish bone sample information 229

Appendix B: Taxonomic assignments and relative abundance by test pit and 233 site for Moniak Islet and Enekoion Islet

Appendix C: Taxonomic assignments and relative abundance by site and 236 cultural layer for Ebon Islet Appendix D: Correspondence analysis data (column and row scores) 254

Appendix E: Fish bone size data: Kruskal-Wallis one way analysis of variance 262 and effect size and bootstrapping around the median

List of Figures

Page

Chapter 1. Introduction

Figure 1. Map of the Republic of the Marshall Islands, with Ebon Atoll 13 and the location of sites MLEb-1, MLEb-5, MLEb-31, and MLEb-33 labelled.

Chapter 2. Pacific Islands Ichthyoarchaeology: Implications for the Development of Prehistoric Fishing Studies and Global Sustainability

Figure 1. Map of the Pacific with islands and archipelagos mentioned in 78 the text.

Figure 2. Coastal environments of the Pacific Islands. 79

Figure 3. Cranial elements used for identification to lowest taxon. 80

Figure 4. A generalised diagram of the vertebral column illustrating the 81 position of vertebrae types.

Chapter 3. Assessing Protocols for Identifying Paciﬁc Island Archaeological Fish Remains: The Contribution of Vertebrae

Figure 1. Map of the South Pacific with Henderson Island (Pitcairn 103 Group) and the location of site HEN-5.

Figure 2. Articulated Acanthuridae (surgeonfish, Acanthurus lineatus) 104 vertebral column with the eight vertebrae types marked.

Chapter 4. Applications of vertebral morphometrics in Pacific Island archaeological fishing studies

Figure 1. A map of the Republic of the Marshall Islands, with Ebon Atoll 137 and the location of site MLEb-1.

Figure 2. Vertebrae types as characterised by yellowfin tuna (Thunnus 138 albacares, Scombridae).

Figure 3. The honeycomb grouper (Epinephelus merra, Serranidae) first 139 thoracic vertebra.

Figure 4. The percentage contribution to total NISP by taxon and sieve 140 size (vertebrae only).

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Figure 5. The distribution of the maximum mediolateral widths of the 141 centrum (M2) for all vertebrae types identified to taxon.

Figure 6. The range of vertebral measurements (mm) for all identified 142 taxa and vertebrae types grouped from site MLEb-1.

Figure 7. The range of vertebral measurements (mm) for the three top- 143 ranked taxa according to NISP: (a) Scombridae, (b) Scaridae and (c) Carangidae.

Figure 8. The range of vertebral measurements (mm) for Scombridae 144 caudal vertebrae, from site MLEb-1.

Figure 9. Global Rachidian Profiles: (a) Selar crumenophthalmus (M1, 145 M2 and M3 from modern specimen no. 325); (b) Selar spp. M1 measurements of all vertebrae types from MLEb-1.

Chapter 5. Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands

Figure 1. Map of the Republic of the Marshall Islands, with Ebon Atoll 167 and the location of sites MLEb-1, MLEb-31 and MLEb-33, and photos depicting intertidal marine habitats characteristic of each islet.

Figure 2. The percent contribution to total MNI and NISP by taxon, site 168 and screen for mollusc shell 6.4 mm samples and fish bone 6.4 mm and 3.2 mm samples.

Figure 3. Correspondence analysis of taxonomic abundance. 169

Chapter 6. Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean Figure 1. Map of the Pacific Islands with key archaeological sites 209 mentioned in text.

Figure 2. Map of Ebon Atoll with the location of archaeological sites 210 mentioned in text labelled.

Figure 3. Chord distance analysis across sequential pairs of cultural 211 layers, ordered chronologically within and between sites: (a) 6.4 mm only, and (b) 6.4 mm and 3.2 mm.

Figure 4. (a) Correspondence analysis of taxonomic composition across 212 all cultural layers at MLEb-1 and MLEb-5, and for brevity, major taxa are defined as those represented by at least 10 individuals, and (b) axis 1 scores ordered from the oldest assemblage (MLEb-5) to the most recent historic assemblage xiii

Chapter 7. Conclusion

No Figures

xiv

List of Tables

Page

Chapter 1. Introduction

No Tables

Chapter 2. Pacific Islands Ichthyoarchaeology: Implications for the Development of Prehistoric Fishing Studies and Global Sustainability

No Tables

Chapter 3. Assessing Protocols for Identifying Paciﬁc Island Archaeological Fish Remains: The Contribution of Vertebrae

Table 1. The dominant elements used to make archaeological fish 99 identifications from Pacific assemblages from the 1970s to contemporary literature.

Table 2. Fish bone MNI and NISP from TP 12, Henderson Island as 100 represented by three separate identification protocols.

Table 3. Rank-order abundance based on NISP and MNI for five paired 101 cranial bones and ‘specials’, expanded number of cranial bones and vertebrae for all cultural layers from TP 12, Henderson Island.

Table 4. Distribution of vertebrae types used for the identification of TP 102 12, Henderson Island fish bone assemblage.

Chapter 4. Applications of vertebral morphometrics in Pacific Island archaeological fishing studies

Table 1. (a) The rank order abundance of fish taxa from site MLEb-1, 133 TP17, 18, 19 and 20 (aggregated by test pit). (b) Rank order abundance of fish taxa from site MLEb-1, TP17 (aggregated by test pit).

Table 2. Vertebral measurements (mm) (M1, M2 and M3) with all 134 identified taxa and vertebrae types grouped from site MLEb-1.

Table 3. Vertebral measurements (mm) (M1, M2 and M3) for top three 135 ranked taxa by NISP (Scombridae, Scaridae and Carangidae) with vertebrae types grouped from site MLEb-1.

Table 4. Vertebral measurements (mm) (M1, M2 and M3) for Scombridae 136 caudal vertebrae, from site MLEb-1.

Chapter 5. Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands

Table 1. Measures of taxonomic heterogeneity as calculated for mollusc 165 shell and fish bone assemblages retained in the 6.4 mm and 3.2 mm sieves for all sites (MLEb-1, MLEb-31 and MLEb-33).

Table 2. Chord distance values for mollusc shell and fish bone 166 assemblages retained in the 6.4 mm and 3.2 mm sieves for each site pair.

Chapter 6. Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean

Table 1. Quantification of fish remains from MLEb-1 and MLEb-5 (6.4 202 mm only).

Table 2. Quantification of fish remains from MLEb-1 and MLEb-5 (6.4 204 mm and 3.2 mm).

Table 3. Measures of taxonomic heterogeneity: (a) 6.4 mm only, and (b) 206 6.4 mm and 3.2 mm.

Table 4. MTL analysis of fish remains from MLEb-1 and MLEb-5 by 207 cultural layers (6.4 mm and 3.2 mm) and Spearman’s rho calculations to asses sample size effects.

Table 5. Quantification of fish remains from MLEb-1 and MLEb-5 by 208 cultural layers for Acanthuridae, Scaridae and Scombridae (6.4 mm and 3.2 mm), by NISP and MNI reported in brackets.

Chapter 7. Conclusion

No Tables

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CHAPTER 1: Introduction

Dispersed across the tropical and subtropical Pacific Ocean, the 22 Pacific Island countries and territories—consisting of Melanesia, Micronesia, and Polynesia—are biologically, culturally, geologically, and socially diverse. The archaeology of this region is uniquely positioned to contribute key datasets relevant to globally pertinent issues of food security, sustainable exploitation of fisheries, and the role of changing climates in marine ecosystem stability. The utility of applied zooarchaeology and specifically ichthyoarchaeology have been increasingly demonstrated over the last decade (Broughton et al. 2015; Butler and Delacorte 2004; Jackson et al. 2001; Kittinger et al. 2014; Rick and Lockwood 2013; Rick et al. 2014; Wolverton and Lyman 2012). A key directive for these research objectives has been the use of historical ecology to integrate ecological and archaeological datasets that vary on temporal and spatial scales (Armstrong et al. 2017), thereby providing a unique contribution to the contemporary resource conservation discourse (Rick and Lockwood 2013). Globally, these approaches have provided insights into long-term anthropogenic and climatic alterations to marine ecosystems, population baseline data, and generated key directives for restoration frameworks (e.g., Barrett et al. 2004; Jackson et al. 2001; McClanahan and Omukoto 2011; McKechnie et al. 2014; Miller et al. 2011; Speller et al. 2012; Thornton et al. 2010; Wake et al. 2013). Similar research agendas have been implemented within the Pacific (e.g., Aswani and Allen 2009; Dalzell 1998; Kittinger et al. 2011; Morrison and Hunt 2007), however, these themes are yet to be considered using ichthyoarchaeological data from the Republic of the Marshall Islands (RMI).

The RMI, situated in eastern Micronesia, is comprised of 29 coral atolls and five limestone islands without a lagoon that are dispersed across 2 million km2 of ocean (Figure 1). In 1993, Weisler established a research program in the RMI with an aim to consider the regional variation in the archaeology of the archipelago as it correlates with the north-south rainfall gradient (Christensen and Weisler 2013; Pregill and Weisler 2007; Weisler 1999a, b, 2001a, b, c, 2002; Weisler and Swindler 2002; Weisler et al. 2012). The earliest time that atolls in the RMI could have been inhabitable is by ~2000 cal BP (Dickinson 2003; Kayanne et al. 2011; Weisler et al. 2012), which is in agreement with the earliest human colonisation dates for the archipelago (Kayanne et al. 2011; Weisler 1999a, 2001b; Weisler et al. 2012, in prep). Ebon Atoll at the southernmost extent of the archipelago is comprised of 22 islets with a total land area of 5.75 km2, which encircles a 104 km2 lagoon and 22 km2 reef platform. The reef to terrestrial land area (4:1) is high, and the reef supports 800 species of fish within a 60 m ocean depth (Myers 1999). Analyses of fish bone remains from four key prehistoric sites on Ebon Atoll provides the first dedicated analysis of long-term exploitation of the marine fishery in the RMI. This research contributes to key archaeological themes, including: methods and methodological approaches for prehistoric fishing studies (Lambrides and Weisler 2015a, b; Lambrides and Weisler

2016), marine resource exploitation (Harris et al. 2016; Lambrides and Weisler 2017), archaeological proxies of past climate stability, and comparability of archaeological and ecological datasets (Lambrides and Weisler 2017) in order to address key gaps in the literature.

Rationale

Island and coastal settings have well demonstrated significance for addressing key anthropological, archaeological, and ecological research topics (Erlandson and Fitzpatrick 2006; Erlandson and Rick 2010; Kirch and Weisler 1994). Specific research agendas include: colonisation sequences and timing, maritime technologies, concepts of ‘isolation’ and associated cultural responses, long-term anthropogenic and ecological impacts to marine ecosystems, spatial and temporal variation in resource procurement and subsistence strategies employed, and the role of historical ecology in conservation biology and ecosystem management (Erlandson and Fitzpatrick 2006; Rick et al. 2014). Historically, atoll archaeology was neglected due to the perception that intact cultural deposits would be unlikely given the susceptibility of these environments to extreme weather events, specifically wave inundation as atolls are commonly situated only 2-3 m above sea level (Weisler et al. 2012). Excavations on Nukuoro Atoll (Davidson 1971), Kapingamarangi Atoll (Leach and Ward 1981), and in the RMI (Rosendahl 1987) indicated that intact cultural deposits were present, demonstrating richer occupational sequences than originally anticipated. Over the last several decades atoll archaeology has offered insights into variability in settlement history, resource procurement, and land use across small spatial scales, given that the terrestrial land area is minimal when compared to the expansive marine environments (e.g., Beardsley 1994; Davidson and Leach 1996; Harris et al. 2016; Harris and Weisler 2016; McAlister 2002; Ono and Addison 2009, 2013; Weisler 2001b, 2004).

On RMI atolls there is limited terrestrial fauna available for exploitation (e.g., crabs, sea birds, and the commensal dog and rat); however, the marine environment is rich and diverse, with extensive reef ecosystems on the lagoon and oceanside of the islets providing abundant protein (e.g., fish, molluscs, and sea turtles) (Hiatt and Strasburg 1960; Wiens 1962). Given marine resources were and still are fundamental to subsistence systems on atolls, these settings are ideal for assessing long-term human interactions with the marine environment, particularly human impacts to these resources (Weisler 2001b), critical when establishing ‘culturally informed management strategies in coral reef conservation efforts’ (Aswani and Allen 2009: 614).

To be able to address these broad island and coastal archaeology research objectives, methods and methodologies are needed for contending with interdisciplinary (e.g., archaeological, biological, ecological, ethnographic, etc.) sources of data that vary not only on temporal and spatial scales, but also in terms of the kinds of data that are collected, making comparison and integration challenging

(e.g., Armstrong et al. 2017). Ichthyoarchaeology in the Pacific can make important contributions to these global aims, however, there is a need to develop and utilise high quality methods that are both transparent and replicable, and allow the integration of archaeological and ecological datasets through the use frameworks such as historical ecology. This approach then enables consideration of human resource selection and how it can be mediated by local and regional environmental processes, whether variability in resource exploitation at small spatial scales can be detected, and the importance of these factors for considerations of long-term human-environment interaction and the implications for contemporary management and conservation of coral reef ecosystems.

Thesis Research Aims

Small islands such as atolls of the RMI can be conceptualised in terms of the environmental constraints and associated challenges these landscapes offered to long-term habitation, such as nutrient-poor soils and salt laden winds that hindered plant growth, the absence of perennial surface freshwater, limited terrestrial biodiversity, and vulnerability to extreme weather events (Fosberg 1990; Weisler 2001b; Wiens 1962). However, the oceanside and lagoonside marine environments are expansive and support a diverse range of marine flora and fauna (Gratwicke and Speight 2005; Harris et al. 2016; Kohn 1987). On Ebon Atoll the reef area is four times larger than the terrestrial land area available for settlement. Given the importance of marine resources, and specifically finfish, the Pacific and specifically Ebon provide an ideal context for: (1) reassessing methods and methodological approaches for conducting Pacific ichthyoarchaeological analyses, and, (2) implementing high resolution methods to understand long-term exploitation of the marine fishery. This thesis provides the first dedicated consideration of prehistoric fishing in the RMI, an avenue of research that has been limited to a few studies thus far (e.g., Weisler 1999b, 2001b).

This thesis has two major aims. Firstly, to assess the historical development of archaeological Pacific fishing studies in light of contemporary global standards, and as such implement high resolution and globally recognised approaches for understanding long-term records in marine resource exploitation, to inform not only archaeological research aims, but to contribute datasets useful for resource and environmental management into the future. To address this aim the following research questions (RQ) were posed:

RQ1: How do the analytical methods implemented by Pacific ichthyoarchaeologists constrain our understanding of past human behaviour?

RQ2: How do the taxonomic identification protocols used for analysing Pacific fish bone assemblages influence our understanding of the range and relative abundance of taxa exploited?

RQ3: Given the high biodiversity of fish species found in the tropical Pacific and the limited range of osteological elements utilised for fish size reconstructions archaeologically, can changes in fish size through time be accurately assessed in the region?

The second major aim was to investigate both spatial and temporal variation in the exploitation of finfish resources on Ebon Atoll by considering variability in landscape use and alterations in the range of taxa captured. As part of this aim, the usefulness of ichthyoarchaeological datasets, specifically the bones of migratory species such as tuna, as proxies for past environmental stability are considered. To address this aim the following RQ were posed:

RQ4: Are there spatial distinctions in taxonomic composition of fish species as reflected by windward vs. leeward islet variation?

RQ5: Is there evidence for alterations in foraging behaviour and/or human impacts to the marine fishery through time?

RQ6: To what extent can migratory fish species, such as tuna, be used as proxies for past environmental stability?

To address these questions, fish bone assemblages from four sites (MLEb-1, MLEb-5, MLEb-31, and MLEb-33), across three islets (Ebon, Enekoion, and Moniak), of Ebon Atoll, RMI were assessed (Appendix A). Radiocarbon determinations document continuous atoll occupation since initial settlement to the historic period spanning two millennia (Weisler et al. in prep). Sites were selected based on the concentration of fish bones recovered and to allow for both spatial and temporal consideration of human-environment interactions.

The conceptual framework used here is historical ecology, a multidisciplinary approach for understanding long-term human-environment interactions, with proven utility for investigating prehistoric and historic alterations to marine ecosystems, and considered fundamental for producing culturally informed resource management strategies (e.g., Armstrong et al. 2017; Barrett et al. 2004; Erlandson et al. 2011; McKechnie et al. 2014; Rick and Lockwood 2013; Rick et al. 2014; Thornton et al. 2010). Over the last two decades, ecological frameworks, particularly historical ecology, have been increasingly utilised in Pacific zooarchaeology and specifically ichthyoarchaeology, due to its emphasis on drawing together disparate datasets across multiple disciplines for understanding the historical processes which have shaped and will continue to shape marine ecosystem productivity, reef health, and resource availability (e.g., Aswani and Allen 2009; Fitzpatrick and Donaldson 2007; Jones 2009; Jones and Quinn 2009; Kirch and Hunt 1997; Lambrides and Weisler 2016; Ono and Addison 2013; Ono and Clark 2012; Walter 1991). For these reasons this conceptual framework is

4 ideal for considering the archaeology of Ebon Atoll and long-term anthropogenic and environmental impacts to the marine fishery.

Thesis Structure

This thesis is comprised of seven chapters, an introduction (Chapter 1), five papers either published or accepted for publication in peer-reviewed journals (Chapters 2-6), and a conclusion (Chapter 7).

Chapter 2 reviews the ichthyoarchaeological literature for the Pacific and evaluates historical developments in methods and methodologies within a global context. Specifically, recovery methods, reference collections, taxonomic identifications, quantification, taphonomy and site-formation processes, ethnoarchaeology, approaches to diet and subsistence reconstructions, sustainability, and the importance of applied zooarchaeology for fisheries management and conservation. Research questions addressed: RQ1, RQ2, and RQ3.

Chapter 3 assesses the historical development of fish bone identification protocols in the Pacific. A pilot study was conducted utilising a single test pit from an archaeological assemblage that had been analysed twice previously (Henderson Island, Pitcairn Group), in accordance with developments in methods of the previous two decades. Therefore, three identification protocols were compared: (1) the most commonly identified five paired cranial bones and ‘specials’ or unique elements; (2) an expanded number of cranial bones; and (3) the less common inclusion of all vertebrae. The impact of the methods on rank-order abundance was evaluated. This allowed an assessment of the utility of this method prior to application to the Ebon archaeological assemblages, given the time investment required when considering all cranial and post cranial elements for identification. Research question addressed: RQ2.

Chapter 4 considers the use of vertebral morphometrics in archaeological Pacific fishing studies for conducting fish length and weight reconstructions. Specifically, the outcomes of utilising measurements of unidentified fish vertebrae, traditionally adopted in the Pacific, vs. using only vertebrae that have been identified to taxon and type for determining alterations in fish size over time are tested. This research was important for assessing human impacts to marine fisheries, capture technology, and environmental change. Research question addressed: RQ3.

Chapter 5 assesses windward vs. leeward islet site variation in taxonomic composition of fish species using assemblages from three sites (MLEb-1, MLEb-31, and MLEb-33), distributed across three islets (Ebon, Moniak, and Enekoion). These patterns have not been explored on low coral atolls previously and are critical for understanding variability in resource procurement across small spatial scales. Research question addressed: RQ4.

Chapter 6 investigates whether temporal variability in the exploitation of the Ebon Atoll marine fishery can be detected. There is also a consideration of the utility of migratory fish species, such as tuna, as proxies for identifying environmental stability across millennia, which is of relevance to resource conservation and management. Research questions addressed: RQ3, RQ5, and RQ6.

Finally, Chapter 7 is a summary of the main research findings, implications of the research and future research objectives.

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McAlister, A. J. (2002). Prehistoric Fishing at Fakaofo, Tokelau: A Case for Resource Depression on a Small Atoll. Masters thesis, Department of Anthropology, University of Auckland, Auckland. McClanahan, T. R., and Omukoto, J. O. (2011). Comparison of modern and historical fish catches (AD 750–1400) to inform goals for marine protected areas and sustainable fisheries. Conservation Biology 25: 945-955. McKechnie, I., Lepofsky, D., Moss, M. L., Butler, V. L., Orchard, T. J., Coupland, G., Foster, F., Caldwell, M., and Lertzman, K. (2014). Archaeological data provide alternative hypotheses on Pacific herring (Clupea pallasii) distribution, abundance, and variability. Proceedings of the National Academy of Sciences 111: E807-E816. Miller, J. A., Butler, V. L., Simenstad, C. A., Backus, D. H., and Kent, A. J. R. (2011). Life history variation in upper columbia river chinook salmon (Oncorhynchus tshawytscha): A comparison using modern and ~500-year-old archaeological otoliths. Canadian Journal of Fisheries and Aquatic Sciences 68: 603-617. Morrison, A. E., and Hunt, T. L. (2007). Human impacts on the nearshore environment: An archaeological case study from Kaua‘i, Hawaiian Islands. Pacific Science 61: 325-345. Myers, R. F. (1999). Micronesian Reef Fishes: A Comprehensive Guide to the Coral Reef Fishes of Micronesia, Coral Graphics, Barrigada. Ono, R., and Addison, D. (2009). Ethnoecology and Tokelauan fishing lore from Atafu atoll, Tokelau. SPC Traditional Marine Resource Management and Knowledge Information Bulletin 26: 23- 22. Ono, R., and Addison, D. (2013). Historical ecology and 600 Years of fish use on Atafu Atoll, Tokelau. In Ono, R., Morrison, A. E. and Addison, D. (eds.), Prehistoric Marine Resource Use in the Indo-Pacific Regions, ANU E Press, Canberra, pp. 59-83. Ono, R., and Clark, G. (2012). A 2500-year record of marine resource use on Ulong Island, Republic of Palau. International Journal of Osteoarchaeology 22: 637-654. Pregill, G. K., and Weisler, M. I. (2007). Lizards from prehistoric sites on Ebon Atoll, Marshall Islands. Micronesica 39: 107-115. Rick, T. C., and Lockwood, R. (2013). Integrating paleobiology, archeology, and history to inform biological conservation. Conservation Biology 27: 45-54. Rick, T. C., Sillett, T. S., Ghalambor, C. K., Hofman, C. A., Ralls, K., Anderson, R. S., Boser, C. L., Braje, T. J., Cayan, D. R., Chesser, R. T., Collins, P. W., Erlandson, J. M., Faulkner, K. R., Fleischer, R., Funk, W. C., Galipeau, R., Huston, A., King, J., Laughrin, L., Maldonado, J., McEachern, K., Muhs, D. R., Newsome, S. D., Reeder-Myers, L., Still, C., and Morrison, S.

A. (2014). Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene. BioScience 64: 680-692. Rosendahl, P. H. (1987). Archaeolgy in eastern Micronesia: Reconnaissance survey in the Marshall Islands. In Dye, T. S. (ed.), Marshall Isands Archaeology, Bernice P. Bishop Museum, Pacific Anthropological Records, Number 38, Honolulu, pp. 17-168. Speller, C. F., Hauser, L., Lepofsky, D., Moore, J., Rodrigues, A. T., Moss, M. L., McKechnie, I., and Yang, D. Y. (2012). High potential for using DNA from ancient herring bones to inform modern fisheries management and conservation. PLoS One 7: e51122. Thornton, T. F., Moss, M. L., Butler, V. L., Hebert, J., and Funk, F. (2010). Local and traditional knowledge and the historical ecology of Pacific herring in Alaska. Journal of Ecological Anthropology 14: 81-88. Wake, T. A., Doughty, D. R., and Kay, M. (2013). Archaeological investigations provide late Holocene baseline ecological data for Bocas del Toro, Panama. Bulletin of Marine Science 89: 1015-1035. Walter, R. (1991). Fishing on Ma'uke: An archaeological and ethnographic study of fishing stategies on a Makatea Island. New Zealand Journal of Archaeology 13: 41-58. Weisler, M. I. (1999a). The antiquity of aroid pit agriculture and significance of buried A horizons on Pacific Atolls. Geoarchaeology: An International Journal 14: 621-654. Weisler, M. I. (1999b). Atolls as settlement landscapes: Ujae, Marshall Islands. Atoll Research Bulletin 460: 1-53. Weisler, M. I. (2001a). Life on the edge: Prehistoric settlement and economy on Utrōk Atoll, northern Marshall Islands. Archaeology in Oceania 36: 109-133. Weisler, M. I. (2001b). On the Margins of Sustainability: Prehistoric Settlement of Utrok Atoll Northern Marshall Islands, BAR International Series, Oxford. Weisler, M. I. (2001c). Precarious landscapes: Prehistoric settlement of the Marshall Islands. Antiquity 75: 31-32. Weisler, M. I. (2002). Archaeological Survey and Test Excavations on Ebon Atoll, Republic of the Marshall Islands, Historic Preservation Office, Republic of the Marshall Islands. Weisler, M. I. (2004). Contraction of the southeast Polynesian interaction sphere and resource depression on Temoe Atoll. New Zealand Journal of Archaeology 25: 57-88. Weisler, M. I., and Swindler, D. (2002). Rocker jaws from the Marshall Islands: Evidence for interaction between eastern Micronesia and west Polynesia. People and Culture in Oceania 18: 23-33. Weisler, M. I., Yamano, H., and Hua, Q. (2012). A multidisciplinary approach for dating human colonization of Pacific Atolls. The Journal of Island and Coastal Archaeology 7: 102-125. 11

Weisler, M. I., Yamano, H., Hua, Q., and Harris, M. (in prep). Islet size of Pacific atolls constrains the timing of human colonisation: an example from Ebon Atoll, Marshall Islands. Wiens, H. J. (1962). Atoll Environment and Ecology, Yale University Press, New Haven. Wolverton, S., and Lyman, R. L. (2012). Conservation Biology and Applied Zooarchaeology, University of Arizona Press, Tucson.

Figure 1. Map of the Republic of the Marshall Islands, with Ebon Atoll and the location of sites MLEb-1, MLEb- 5, MLEb-31, and MLEb-33 labelled (after Harris et al. 2016).

CHAPTER 2: Pacific Islands Ichthyoarchaeology: Implications for the Development of Prehistoric Fishing Studies and Global Sustainability

Note: This is the final version of a peer-reviewed article published in the Journal of

Archaeological Research.

Ariana B.J. Lambrides and Marshall I. Weisler

School of Social Science, The University of Queensland, St Lucia, Qld 4072 Australia.

Corresponding author: Ariana Lambrides, School of Social Science, The University of Queensland,

St Lucia, Qld 4072 Australia. Telephone: +61 7 3365 3038. Fax: +61 7 3365 1554. Email: [email protected]

Pacific Islands Ichthyoarchaeology: Implications for the Development of Prehistoric Fishing Studies and Global Sustainability

Abstract: The Pacific Islands—consisting of culturally diverse Melanesia, Micronesia, and Polynesia—is the ideal region to investigate the development of prehistoric fishing studies, as nowhere else on Earth is there such environmental contrasts among island types and their marine environments. We review the ichthyoarchaeological literature for the Pacific and assess developments in recovery methods, reference collections, taxonomic identifications, quantification, taphonomy and site-formation processes, ethnoarchaeology, approaches to diet and subsistence reconstructions, sustainability, and the importance of applied zooarchaeology for fisheries management and conservation. Ichthyoarchaeologists are beginning to work more closely with resource managers, fisheries biologists, policy makers, and indigenous communities to produce holistic studies of conservation management, resource sustainability, and assessments of human impacts on marine ecosystems over centuries to millennial time scales.

Keywords: fisheries management, historical ecology, ichthyoarchaeology, Pacific Islands, zooarchaeology

Introduction

The antiquity of fishing and the exploitation of marine and freshwater resources have been significantly extended in recent years (Erlandson and Rick 2010). 1.95 million years ago, Early Pleistocene hominins were exploiting freshwater resources (catfish and turtles) in the Turkana Basin in Kenya (Archer et al. 2014). Marine fisheries were more routinely exploited along the western coast of South Africa by ca. 50,000 BP during the Late Stone Age, and possibly even earlier in the Middle Stone Age (e.g., Henshilwood et al. 2001; Klein et al. 2004). There is evidence of fishing at Jerimalai shelter in East Timor by 42,000 BP (O’Connor et al. 2011) and the exploitation of marine mollusks and fish in the western Pacific, at Buang Merabak, Papua New Guinea, by ca. 40,000 BP and at Matenkupkum, New Ireland, by ca. 33,000 BP (Allen 2003; Gosden and Robertson 1991; Leavesley et al. 2002; Szabó and Amesbury 2011).

Erlandson and Fitzpatrick (2006) have explicitly synthesised the broader anthropological, archaeological, and ecological significances of island and coastal archaeology, where research agendas range from the antiquity of coastal adaptations, to the development of maritime technologies, cultural responses to ‘‘isolation,’’ and human impacts on coastal resources (e.g., Montenegro et al. 2014; Weisler et al. 2012). Ichthyoarchaeology is a vital component of island and coastal archaeology research and is essential for addressing fundamental questions in Pacific Islands prehistory. In this article, we globally contextualise our review of the Pacific Islands ichthyoarchaeological literature, focusing on recovery, analysis, and the interpretation of archaeological fish remains.

The Pacific Islands

The Pacific Ocean is the largest and deepest of the world ocean basins. We use ‘‘Pacific’’ to refer to the geographic region that comprises Melanesia, Micronesia, and Polynesia. The 22 Pacific Island countries and territories are dispersed across the tropical and subtropical Pacific Ocean, an area that exceeds 27 million km2 (Figure 1). The distinction between Near Oceania—New Guinea, the Bismarck Archipelago, and the Solomon Islands as far east as San Cristobal—and Remote Oceania— all other Pacific Islands—was first proposed by Pawley and Green (1973). Near Oceania has the greatest biogeographic diversity (marine and terrestrial) and the earliest evidence of human occupation, and both Austronesian and non-Austronesian languages are spoken; in contrast, only Austronesian languages are spoken in Remote Oceania (Green 1991). Beyond the Solomon Islands, eastward across Remote Oceania, the distance between islands increases, which reduces intervisibility (Montenegro et al. 2014); this posed a natural constraint on human colonisation and influenced the later settlement of Remote Oceania (ca. 3,000 BP) compared to Near Oceania (ca. 50,000 BP) (Irwin 1992; Kirch 2000; Summerhayes et al. 2010).

Dispersed across the Pacific Ocean are island-arc islands (New Zealand is the largest), high volcanic islands (of midplate hotspot origin such as Hawai‘i), low coral atolls, and makatea (raised limestone) islands; each support diverse biota (Figure 2; Springer 1982; Stoddart 1992). The western Pacific is a vast region of island-arc and high volcanic islands (e.g., Fiji, New Caledonia, Solomon Islands, and Papua New Guinea). The coastal waters surrounding these islands are highly productive due to terrestrial runoff, the upwelling created by the deflection of large-scale ocean currents around the islands, and vast coral cover (Bell et al. 2011). When high volcanic islands are relatively young, they lack developed coral reefs, but over time these reefs develop into fringing reefs, then barrier reefs separated from the island by a lagoon. In contrast, atolls (distributed 10,000+ km from Palau in the northwest to Ducie Atoll, Pitcairn Islands in the southeast; Figure 1) are rarely more than 2–3 m above sea level and have poor coralline soils, consistent exposure to salt-laden winds, and an absence of surface freshwater. Importantly for occupation, atolls have the highest area of reef to land size of all island types. Finally, makatea islands are raised reef islands and are most common in the Solomons, New Guinea, Palau, Marianas, Fiji, and Tonga; on average, biodiversity is higher on these islands as is endemicity; however, due to phosphate mining (e.g., Banaba and Makatea Islands), it has been difficult to reconstruct native biota (Stoddart 1992).

In general, from west to east across the Pacific, terrestrial and marine diversity decreases. The Coral Triangle is situated in the Indo-West Pacific Ocean (Figure 1), where the high species diversity (e.g., 1660 fish species from Papua New Guinea; Froese and Pauly 2014) is particularly evident compared to the Caribbean Sea, the centre of diversity in the Atlantic Ocean, where only about 700 species of fish are reported (Rocha 2003: 1165).

Modern Fisheries, Conservation Biology, and Applied Zooarchaeology

Wolverton and Lyman’s (2012) edited volume explores avenues of applied research over the past decade that contribute to the conservation and management of modern terrestrial and aquatic populations. Applied zooarchaeology is a broad theme that globally links archaeology across geographic regions, and we use it to synthesise the key issues in Pacific ichthyoarchaeology research as well as broader issues in archaeology.

Goods and services from coral reefs provide more than $375 billion to the global economy per annum (Pandolfi et al. 2005: 1725), yet reefs across the globe are in decline. With the loss of turtles, sharks, groupers, and long-lived corals, which support diverse fish and invertebrate populations, a return of trophic structure and clear conservation goals are a necessity. Just as the Pacific Islands are geologically, biologically, culturally, and socially diverse, so too is the archaeology of the region and its ability to inform globally relevant issues—food security, sustainable exploitation of fisheries

17 resources, and the impact of changing climates on the world’s marine ecosystems. Within the marine sciences, global initiatives are devoted to these concerns, such as the Sea Around Us Project (www.seaaroundus.org), which assesses the impact of fisheries on marine ecosystems, and the History of Marine Animal Populations (HMAP) (www.coml.org/projects/history-marine-animal- populations-hmap), which considered both historical and environmental datasets to evaluate marine populations before and after significant human impact. More recently, social scientists, archaeologists, sociologists, anthropologists, and economists have developed research links with marine scientists to provide complementary data that evaluate human–environment interactions and contribute culturally informed conservation and management strategies (e.g., Aswani et al. 2012; Erlandson and Rick 2010; Johannes 2002; Jones 2009; Kittinger et al. 2014; McKechnie et al. 2014; Morrison and Hunt 2007; Wake et al. 2013). Even minor variations in climate or biodiversity on a time scale of years to decades can significantly alter marine ecosystems (e.g., Hughes et al. 2007). Archaeology provides data to highlight these long-term trends by tracking changes in species size and composition and fisheries productivity. Fish are critical to food security in subsistence fisheries and market-based economies across the Pacific Islands (Bell et al. 2009); the region is ideal for discussing changing themes and future research directions for archaeological studies of marine fishing globally (Aswani and Allen 2009; Butler 1994; Gifford 1951; Jones 2009; Leach 1986; Nagaoka 2005).

Schwerdtner Máñez et al. (2014: 1) highlight promising advancements in marine historical research, but these research agendas are yet to be integrated into a multidisciplinary global history of human– ocean interactions. The Oceans Past Initiative (OPI) was awarded a grant from the European Union to establish the Oceans Past Platform; the collaboration draws on expertise from history, archaeology, social science, and marine science to assess human–environment interactions primarily in European waters over the last two millennia (http://hmap.sea.ee/index.php/eu-cost-action-network). Schwerdtner Máñez and colleagues have proposed establishing a global research network for marine historical research, the OPI, which would act as a virtual network to connect researchers globally. We contribute to this discourse by highlighting contributions and future directions of archaeological faunal research to broader marine management studies in the Pacific Islands and globally.

Archaeology of Pacific Fishing

Twenty years ago Kirch and Weisler (1994: 285) wrote that the rapid expansion in the archaeology and prehistory of the Pacific Islands likely would lead to increased regional specialisation. Indeed, over the last two decades Pacific archaeologists have continued to produce high-resolution chronologies for regions, archipelagos, islands, and key sites. There also has been increased emphasis on multidisciplinary research—matching worldwide trends—and a movement toward subdisciplinary 18 specialisation. Following the early emphasis on material culture, the analysis of finfish and shellfish remains garnered the most attention as Pacific archaeologists recognised that marine subsistence is fundamental to island economies (e.g., Ambrose 1963; Smart 1962). Over the past 70 years the analysis of Pacific archaeological fish remains has developed into a discrete subdiscipline with changing field collection methods, identification procedures, quantification protocols, and progressively more comprehensive research agendas.

The major analytical themes and issues shared across Pacific archaeology are colonisation and settlement, human impacts on island environments, prehistoric economic systems, exchange and interisland contacts, and the development of complex societies (Kirch and Weisler 1994: 286). Human interaction with the marine environment (especially prehistoric fishing practices) is a critical component. Methods for inferring past subsistence systems are fundamental in archaeology, and the themes we discuss are relevant to broader zooarchaeological studies (e.g., Lupo 2007; Twiss 2012).

We review the zooarchaeological and ichthyoarchaeological literature that provides analytical and methodological contributions rather than descriptive site reports (i.e., list of taxa only or ‘‘laundry lists,’’ see Lyman 2015). References are primarily English, although some relevant non-English articles are included.

We review the highpoints and trends in more than 70 years of fishing studies in the Pacific with an eye to suggesting future research directions. We address key themes including an introduction to Pacific fishing studies (material culture and fish bone analysis), recovery methods, reference collections, taxonomic identifications, quantification, taphonomy and site formation processes, diet and subsistence reconstructions, ethnoarchaeology, sustainability, and fisheries management and conservation.

Early Approaches to Pacific Fishing Studies: Material Culture

Prior to World War II, the limited archaeological research that had been conducted in the Pacific focused on the classification of material culture informed by ethnographic observations. Pioneering works provided syntheses of fish capture techniques and material culture, primarily in Polynesia (e.g., Anell 1955; Best 1929; Buck 1927; Hamilton 1908).

The early focus in Pacific archaeology and anthropology on fishing resulted in culture-historical sequences based on fishhook form (i.e., style and function). In the eastern Pacific, typologies were based on hook form and associations with cultural groupings, such as, ‘‘Pacific types,’’ ‘‘Polynesian type,’’ and ‘‘western Polynesian culture’’ (e.g., Beasley 1928; Burrows 1938; Skinner 1942). Influenced by Fishhooks, the pioneering publication by Emory et al. (1959), more systematic and

19 formal methods of fishhook classification were developed. The volume detailed a formal typology for classifying Hawaiian fishhooks and investigation of temporal variation in fishhook form. A methodological shift occurred between the 1920s and 1970s, as analytical and quantitative methods were formalised. Archaeological research focused on a new interest in the economic significance of prehistoric fishing through fish bone analysis.

New Directions in Pacific Archaeology: Fish Bone Analysis

In Fish Remains in Archaeology and Paleo-Environmental Studies, Casteel (1976) demonstrated the significance of archaeological fish bone analysis, addressing seasonality, morphometric studies, subsistence reconstructions, and fish mortality profiles (i.e., age of fish when captured). Casteel influenced the development of archaeological fish bone analysis worldwide (e.g., Thieren and Van Neer 2014; Zohar et al. 2008), but these analyses occurred earlier in America and Europe than in the Pacific Islands. Gifford (1951) reported the first study of prehistoric diet using fish bone from Fiji archaeological sites, with taxonomic identifications by the ichthyologist Fowler (1955). Gifford and Shutler (1956) and Gifford and Gifford (1960) employed standardised excavation techniques, which documented preliminary taxonomic identifications of fish bone.

Archaeological fish bone often was acknowledged but not identified to taxon (e.g., Golson 1961; Suggs 1961; Trotter 1955). Gifford’s pioneering Pacific work lapsed until the 1960s, when Shawcross (1967, 1972) carried out a diet-breadth study at Galatea Bay and assessed population dynamics based on reconstructed caloric values of archaeological fish remains. In Hawai‘i, Kirch (1971, 1975, 1979) completed preliminary taxonomic identifications of fish dentaries from cultural resource (heritage) management and research projects.

Although fish bone was not routinely collected and analysed in the Pacific Islands until the early 1970s, these early pursuits demonstrate a methodological shift from predominately material culture to holistic research agendas. By the early 1970s, fish bone analysis was still underdeveloped in Pacific archaeology, and Davidson (1971) stressed the necessity for specialist work given the importance of fishing in the region, including the establishment of fish bone comparative collections and the development of systematic taxonomic identification protocols (Green and Kelly 1970: 184).

Recovery Methods

The first systematic use of screening in the Pacific, on Fiji, was by Gifford (1951), who used 3.2 mm (1/8’’) sieves to address settlement history, diet, and subsistence. The use of screens for recovering archaeological material was inconsistently adopted in the Pacific before the 1970s (e.g., Allo 1970), with some later instances recorded outside the region (e.g., Seeman 1986). Archaeologists are still

20 evaluating the implications of screening protocols on reconstructions of prehistoric subsistence (e.g., Gordon 1993; James 1997; Nagaoka 2005; Vale and Gargett 2002; Wake 2004a; Zohar and Belmaker 2005). Gobalet and Jones (1995) suggested that an absence of fine-mesh sieving impacts the accuracy of fish bone analysis; consequently, there was a movement away from 6.4 mm (1/4’’) screens in North America during the 1970s; 3.2 mm screens are most commonly used today, but

1.6 mm (1/16’’) mesh is ideal. Cooke and Ranere (1999: 105) state that 6.4 mm screens are sufficient for recovering bones of large mammals, but the recovery of fish remains requires a minimum size of 3.2 mm mesh. Partlow (2006) queried the emphasis on the use of finer-mesh screens within the global fisheries literature, given that a more pressing concern is the inconsistent use of screen sizes across a region. In Pacific archaeology, there has been a preference toward 3.2 mm and/or 6.4 mm screens since 1960.

Ichthyoarchaeologists recognised that screen size influenced fish bone recovery and subsequent subsistence reconstructions, so efforts have been directed toward improving data quality (Casteel 1972: 382). Butler (1987, 1988, 1993, 1994), Nagaoka (1994, 2005), and others (Gordon 1993; Jones O’Day 2001; Weisler 1993) have highlighted the impact of screen size on the recovery of fish remains, research that led to the adoption of systematic recovery protocols in Pacific archaeology. Butler (1987), in a North American study, water screened all excavated material through nested 1.6, 3.2, and 6.4 mm screens and demonstrated that the number of identified specimens (NISP), richness, and relative abundance were affected by screen size. Butler (1988: 104) then reviewed fish bone data from Pacific Island Lapita sites and identified taxon body size as a major factor that affects the recovery of fish bone elements. The relationship between screen size and element representation also has been used to distinguish between natural and cultural salmonid deposits (Butler 1993). Using both archaeological fish remains and experimental analogues, Nagaoka investigated the impact of 3.2 and 6.4 mm screens on fish bone recovery (1994) and of element representation (2005) in a Pacific context. Ono and Clark (2012) argue that the elements used for taxonomic identification are more critical than screen size for representing species diversity and that regional syntheses are problematic when inconsistent screen sizes have been used across studies.

Currently 3.2 mm screens are considered the most useful for the recovery of fish remains (e.g., Fitzpatrick et al. 2011; Weisler et al. 2010). Fine mesh screening (<3.2 mm) has been more widely implemented outside the Pacific (e.g., Erlandson et al. 2005; Robson et al. 2013). Selective fine screening can provide representative data (e.g., Weisler 2001) that establish a benchmark to determine bone loss through the larger screens (e.g., 6.4 mm) and to assess the effects of screen size on species richness and abundance. It is up to the researcher, however, to decide whether to reduce the area excavated in order to conduct more systematic fine mesh screening. 21

Reference Collections

Before reference collections were established, ichthyology manuals were the primary source for aiding taxonomic identification of archaeological fish bone (e.g., Clothier 1950). Prior to the 1980s, Fowler’s (1955) volume of illustrations of select elements was the most widely used resource in the Pacific (e.g. Davidson 1971; Kirch 1973), but more comprehensive manuals are available for New Zealand (Leach 1997) and Hawai‘i (Dye and Longenecker 2004). Although faunal reference collections for taxonomic identification are preferable (Hamilton-Dyer 2013), Pacific fish bone studies during the 1970s and early 1980s were hindered by reference collections that did not adequately represent the species diversity of a region. Reference collections are no longer the primary issue restricting archaeological fish bone identifications in the Pacific and elsewhere. Archaeologists rarely report the taxa held within a reference collection, and data quality is rarely discussed in faunal analysis. There also are inconsistencies in the recording of biological (e.g., age and sex) and environmental variables (e.g., local ecology, water depth, and temperature), for fish used as reference specimens.

The use of incomplete reference collections for analysing archaeological fish bone assemblages can bias measures of diversity, limit interpretations, and impact data quality (Wolverton 2013: 385–389). A list of taxa in a reference collection should be published with each site analysis as supplementary material or on a dedicated university or museum website (e.g., Allen 1992a; Gobalet 2001; Wake 2004a: 175; Walter et al. 1996; Weisler 2001). It is not sufficient to list only the university or institute where the collection is held (e.g., Amundsen et al. 2005; Enghoff et al. 2007; Jones and Kirch 2007).

Gobalet (2001) conducted a blind study among experts in archaeology, zoology, and fisheries biology to assess differences in taxonomic identification of a fish bone assemblage from California; the differences in taxonomic identifications ranged from predominately family level to mainly species level. The quality of taxonomic identifications is rarely tested (Driver 1992: 41; Wolverton 2013). Wolverton (2013: 392) suggests a statement of data quality in scholarly publications may be useful, but first laboratory procedures must be assessed and existing standards accepted or improved (e.g., Gobalet et al. 2005). The identification of the number of specimens required in a reference collection to ensure confidence for each identification level is useful for mitigating overidentification of archaeological bones.

An ideal reference collection contains at least half a dozen examples of each species, representing a variety of ages, sex, and capture environments. However, it is the identification criteria and protocol standards established in zooarchaeology that provide quality assurance (Wolverton 2013: 393). It is useful for ichthyoarchaeologists to work closely with ichthyologists and fisheries departments when

22 establishing reference collections to ensure accurate species identification and determinations of age and sex of the reference fish. For example, when analysing an assemblage from Pakistan, Desse and Desse-Berset (1999: 345) noted a change in morphology of sciaenid otoliths from juvenile to adult that was consistent with taxonomic assignments of two different species. Even though comprehensive reference collections may facilitate higher-level taxonomic assignments, species richness is ultimately dependent on sample size (Lepofsky and Lertzman 2005; Lyman and Ames 2007).

Digitised reference material complements physical reference collections. Pacific-focused online resources similar to OsteoBase (www.mnhn.fr/osteo/osteobase/), hosted by the Natural History Museum in Paris, or Archaeological Fish Resource (http://fishbone.nottingham.ac.uk/), hosted by the University of Nottingham in the UK, can enhance identifications of Pacific archaeological fish bones given the high biodiversity in the region (see Hamilton-Dyer 2013: 81–82, for a comprehensive list of online reference collections and osteology reference works). Establishing open-access online fish bone reference collections will improve data quality and also the capacity of archaeologists to contribute to research outside our immediate focus, including conservation biology and food security.

Taxonomic Identifications

Lockerbie’s (1940: 407) excavations at Kings Rock, Otago, New Zealand, provided one of the earliest reports of fish bone in the Pacific. Taxonomic identifications were not completed but the likely taxa present were suggested based on local knowledge and included barracuda, grouper, and cod.

Initially, zoologists and ichthyologists completed taxonomic identifications of Pacific archaeological fish bone; examples include Fowler for Gifford (1951) in Fiji and Woods for Spoehr (1957) in the Mariana Islands. No formal identification protocols were implemented, and primarily mouthparts (i.e., dentary and premaxilla) were identified. Parrotfish (Scaridae)—closely followed by wrasse (Labridae)—were commonly reported as the dominant taxa (e.g., Kirch 1975, 1979); because of the high bone density and unique morphology of their upper and lower pharyngeal grinding plates, they are easily identified to family. Not until the late 1970s did Leach and Davidson (1977) develop the first systematic protocol for the taxonomic identification of Pacific archaeological fish bone.

Element Selection

The first stage of analysis is determining the fish bone elements that have preserved in the assemblage (Driver 1992). The researcher should attempt to identify all elements. Because mouthparts of Pacific fish were considered the most useful for taxonomic identifications (Fowler 1955), taxonomic identification has been based on a limited range of fish bone elements (e.g., five paired cranial elements, Leach 1986). There has been a movement away from a focus on primarily mouthparts and

23 other paired cranial bones to including more postcranial elements, including vertebrae across a diverse range of taxa (e.g., Lambrides and Weisler 2013; Ono and Clark 2012). Perhaps due to lower taxonomic diversity—in some cases—or the influence of historical precedent, all fish elements were systematically identified in assemblages across Europe, the Mediterranean, Middle East, North America, and South America decades earlier than in the Pacific Islands (e.g., Desse-Berset and Desse 1994; Moss 2011; Rick et al. 2001; Robson et al. 2013; Wake 2004b). This comprehensive analysis of elements was linked to studies of butchery practices or processing techniques, element representation and preservation, variability between site use, and trade and movement of resources (Barrett 1997; Colley 1984; Enghoff 1997; Lauwerier and Laarman 2008; Tourunen 2008)—analyses that have not been as widely investigated in the Pacific.

Leach and Davidson (1977: 166–168) were the first to develop routine fish bone taxonomic identification protocols in New Zealand. This new protocol incorporated five paired cranial elements (dentary, premaxilla, maxilla, quadrate, and articular; see Figure 3) and ‘‘specials’’ (e.g., pharyngeal grinding plates, unique anal and dorsal spines, and some vertebrae; see Weisler 2001: 110, fig. 7.4). The method focused on elements considered diagnostic across all taxa and excluded most other elements (Leach 1986). Conversely, Butler (1988: 108–109) argued that reconstructions of prehistoric human behaviour would be influenced by differential impacts of taphonomy between taxa and post depositional processes when only a restricted number of elements are identified (also Nicholson 1992, 1996). Variations in fish processing between taxa may result in different elements being deposited at a site; therefore, it is critical to analyse elements from both the cranium and postcranium (Butler and Chatters 1994: 416–417; Masse 1989: 383; Walter 1998: 64).

Recent developments in Pacific fish bone identification protocols include more cranial elements used for taxonomic identifications and the routine consideration of all vertebrae. Initially, analyses documented the implications of an expanded range of identified cranial elements, with results confirming alterations to richness and abundance of identified fish taxa (e.g., Jones O’Day 2004; Ono and Clark 2012; Vogel 2005; Weisler 2001; Weisler et al. 2010). The most commonly identified of these expanded cranial elements in Pacific fishing studies include basipterygium, ceratohyal, cleithrum, coracoid, epihyal, hyomandibular, interopercle, opercular, palatine, parasphenoid, posttemporal, preopercular, scapula, subopercular, supracleithrum, supraoccipital, and urohyal (Figure 3; see also Leach 1997: 7, fig. 1). Not all of these elements are technically cranial elements; the posttemporal, supracleithrum, cleithrum, and scapula are elements of the pectoral girdle, but for consistency across the Pacific fishing literature they are referred to as expanded cranial elements. Fishing studies outside the Pacific Islands still identify a greater range of the so-called cranial

24 elements—e.g., elements of the neurocranium, hyopalatine arch, opercular series, infraorbital series (Amundsen et al. 2005; Desse-Berset and Desse 1994; Thieren and Van Neer 2014).

The identification of all vertebrae, which has lagged behind studies in other regions, has been the most recent advancement in Pacific fishing research (e.g., Morales 1984). Only unique or special vertebrae were identified in early Pacific archaeology (e.g. Davidson 1971; Wallace and Wallace 1969). X-ray identification—a method more commonly used outside the Pacific to identify all fish vertebrae (e.g., Desse and Desse 1983; Desse and Desse-Berset 1997)—was employed only for distinguishing between black-tipped and white-tipped sharks in the Pacific (e.g., Leach and Davidson 1977). The analysis of vertebrae was most commonly restricted to the identification of the distinctive shark, ray, and skate (Elasmobranchii) vertebrae (e.g., Clark and Szabó 2009; Weisler and Green 2013), and the ultimate vertebrae of tuna, mackerel, and bonito (Scombridae) (e.g., Fraser 1998). More specific identification of sharks, rays, and skates beyond subclass Elasmobranchii are uncommon in Pacific fishing literature. Ono and Intoh (2011: 256) relate this to the element types (vertebra, teeth, spines, and dermal denticles) that preserve in archaeological sites, which are morphologically similar and difficult to identify even to family. Significantly, Ono and Intoh (2011: 267–268) were able to classify some elasmobranch vertebrae based on morphology to family— Carcharinidae and Lamnidae—and those vertebrae identified as Carcharinidae were further divided into five distinct taxa; more specific identifications are critical for assessing the contribution of shark to prehistoric diet (Rick et al. 2002).

Ono (2003, 2004) demonstrated that the systematic identification of all vertebrae can alter the taxonomic abundance and richness of fish bone assemblages by identifying six additional taxa (Acanthuridae, Caesionidae, Carangidae, Belonidae, Ephippidae, and Scombridae) in an assemblage from the Bukit Tenkorak site, Borneo Island (Ono and Clark 2012). Lambrides and Weisler (2013, table 2) explicitly documented this trend by tracing the development of fish bone identification protocols in three datasets: the five paired cranial bones and ‘‘specials,’’ expanded cranial bones, and all vertebrae. Including vertebrae doubled the minimum number of individuals (MNI) for surgeonfish (Acanthuridae) and replaced groupers (Serranidae) as the top ranked taxon at a Henderson Island (Pitcairn Group) site (Lambrides and Weisler 2013, table 3). Clearly, regional syntheses can be problematic when fish bone assemblages have been analysed using an inconsistent range of elements.

The analysis of archaeological vertebrae has been extensive outside the Pacific, due to superior preservation of vertebrae in some regions (e.g., along the northwest coast of North America), their usefulness for seasonality studies, and analyses of butchery patterns. To facilitate accurate osteometric reconstructions, it is critical that archaeological vertebrae are identified to type (e.g., thoracic, precaudal, caudal; see Figure 4) and that their position along the vertebral column is 25 determined (Enghoff 1994; Gabriel et al. 2012). Morales (1984) and Butler (1993) recognised the importance of distinguishing between specific vertebrae types rather than grouping archaeological vertebrae into precaudal and caudal (e.g., de Jong 1994; Van Neer 1986) or considering vertebrae as a single type (e.g., Cerón-Carrasco 1994; Seeman 1986). Comprehensive vertebrae identification should be routinely incorporated in Pacific fish bone analyses to improve interpretations of assemblages and to keep abreast with global trends in methods (e.g., Barrett et al. 2011; Van Neer et al. 2007).

Otoliths—hard calcareous bodies found in the neurocranium (see Weisler 1993: 131, fig. 1)—and scales have not been consistently identified in Pacific archaeology compared to other regions (e.g., Carenti 2013; Joslin 2011). Weisler demonstrated the importance of identifying otoliths (see also Allen 1972; Frimigacci 1980) by providing the first identification of mullet (Mugilidae) for the Hawaiian Islands (Weisler 1993: 145), flying fish (Exocoetidae) for the Marshall Islands (Weisler 2001: 109), bonefish (Albulidae) and whiting (Sillaginidae) from New Caledonia (Weisler 2002: 208), 14 species of fish never found before in New Zealand middens (Weisler et al. 1999: 43), and new fish records for Australian waters (Crouch et al. 2007: 57; Weisler and McNiven 2015). Fish scales are not commonly identified in Pacific archaeology, with the exception of triggerfish and box fish (e.g., Allen 1992a; Weisler 2001); however, reference collections are yet to be developed.

Recent changes to Pacific fish bone taxonomic identification protocols are starting to reflect global trends, including the introduction of comprehensive vertebrae analysis (e.g., Gabriel et al. 2012; Huber et al. 2011). Given the increasing demand for high-quality archaeological faunal analyses for archaeology and to inform modern conservation and management strategies, it is paramount that Pacific ichthyoarchaeologists continue to use all elements for taxonomic identification.

Identification Level

The taxonomic level—family, genus, or species—of archaeological fish bone identifications impacts reconstructions of prehistoric fishing practices. Positive under identification is better than tentative overidentification. Family-level identifications have dominated the tropical Pacific fishing literature; this partly relates to high marine biodiversity, incomplete reference collections, experience of the analyst, and greater analytical expediency. With the expansion of comparative collections, more specific identifications have been achieved in the tropical Pacific (e.g., Butler 2001; Jones and Quinn 2009; Weisler et al. 2010) in contrast to temperate New Zealand where greatly reduced biodiversity facilitates routine species-level identifications (e.g., Anderson 1986; Davidson et al. 2000; Leach et al. 1995). Outside the Pacific, there has been an emphasis on genus- and/or species- level identifications (e.g., Archer et al. 2014; Carder et al. 2007; Cooke and Ranere 1999; Joslin 2011;

Makowiecki and Van Neer 1996; Rick and Erlandson 2011; Villagran et al. 2011; Zangrando 2007). For example, given the importance of salmon (Oncorhynchus spp.) in Pacific Northwest prehistory, morphometric measures have been used to facilitate species-level identifications of vertebrae (Huber et al. 2011; but see Moss et al. 2014).

Taxonomic assignments to family, genus, or species impact the resolution of data used to infer prehistoric capture methods. A recent example is the debate surrounding the evidence for offshore fishing at Jerimalai shelter (East Timor) given that only family-level taxonomic identifications of Scombridae (tuna, mackerel, and bonito) were completed. Half of the identified fish bone assemblage from the earliest deposits of Jerimalai shelter was argued by the authors to be from pelagic fish (specifically tuna) (O’Connor et al. 2011). Anderson (2013: 880) disagrees with this assertion given that Scombridae is a large and diverse family that comprises many species—in addition to tuna—so it is not possible to know specific ecological information and common capture techniques with only family-level identifications. This debate highlights the importance of having adequate reference collections, or incorporating additional techniques such as aDNA analysis and peptide mass fingerprinting (PMF), which facilitate species-level identifications when morphological attributes are indistinguishable for a family or genus, or when taphonomic factors impede finer taxonomic identification.

DNA Analysis, Peptide Mass Fingerprinting, and Morphological Analysis: Complementary Techniques?

Globally, concerns have been raised over the certainty of taxonomic identifications (skeletal element and taxon) and the need for objective frameworks to allow comparisons between assemblages (e.g., Gobalet 2001; Lernau 1996). With the development of PMF and modern/ancient DNA extraction protocols, species-level taxonomic identifications are enhanced (e.g., Butler and Bowers 1998; Hlinka et al. 2002; Moss et al. 2014; Richter et al. 2011; Speller et al. 2005; Yang et al. 2004). The application of aDNA analysis for the taxonomic identification of Pacific archaeological fish bone was investigated by Nicholls et al. (2003) using an assemblage from Aitutaki, in the southern Cook Islands. Previous molecular studies of ichthyoarchaeology remains completed by Butler and Bowers (1998) in North America and Hlinka et al. (2002) in Australia reported variable outcomes. Nicholls et al. (2003) provided more promising results by DNA sequencing modern grouper (Serranidae) samples and then extracting useful aDNA from 21 of the 29 tested archaeological cases, which resulted in 19 species-level identifications. These methods complemented traditional morphological identification techniques by facilitating genus- and species-level identifications. Despite a reduction in aDNA costs, the survivability of aDNA is variable, and universal primer sites for fish can be challenging to locate (Richter et al. 2011: 1503). 27

The ubiquity of salmon remains at some Pacific Northwest sites led to the development and application of aDNA analysis to facilitate species-level identifications. Because of high analytical costs, only small samples can be analysed (e.g., Ewonus et al. 2011; Moss et al. 2014; Speller et al. 2005; Yang et al. 2004), which can produce conflicting interpretations of the same site (Ewonus et al. 2011; Grier et al. 2013). In these cases, it is necessary to use a method that is cost effective and enables large samples to be analysed, such as peptide fingerprinting.

Zooarchaeology by mass spectrometry (ZooMS) uses PMF for the rapid and cost- effective taxonomic identification of archaeological bone; species are identified to taxon by differences in the mass of the peptides, hence, the identification of bone is achieved using a ‘‘molecular barcode’’ (Buckley et al. 2009; Doorn et al. 2011; Richter et al. 2011). This method aids traditional zooarchaeological analyses and is particularly useful when bone is too fragmented for morphological identification (Richter et al. 2011: 1508). ZooMS has not been extensively implemented for fish bone identifications, and despite the work involved to establish regional databases to facilitate taxonomic identifications, it has the potential to contribute to all marine and freshwater fishing studies.

Quantification

Appropriate formal methods for quantification of zooarchaeological material have received significant global attention (e.g., Binford 1981; Casteel and Grayson 1977; Grayson 1984; Harris et al. 2015; Marshall and Pilgram 1993), but these methods were not routinely incorporated in Pacific fishing studies until the late 1970s (e.g., Leach and Davidson 1977). In some early studies, qualitative measures such as presence/absence or classifications of ‘‘some,’’ ‘‘few,’’ or ‘‘many’’ were recorded (e.g., Davidson 1971; Gifford and Shutler 1956). Weights of unidentified archaeological fish bone have been reported (e.g., Davidson 1969; Kirch 1971; Skjølsvold 1972), but this did not continue beyond the 1970s, as weight is a problematic measure for quantifying temporal changes in abundance and richness of fish taxa and for estimating dietary contribution.

Exhaustive critiques of the benefits and limitations of MNI, NISP, and weight calculations have been discussed elsewhere (Grayson 1979, 1984; Lyman 2008: 21–140). Within the Pacific ichthyoarchaeology literature, it is rare for MNI, NISP, and weight to be reported in the same study (e.g., Weisler and Green 2013— examples outside the Pacific include Erlandson et al. 2005; Joslin 2011; LeFebvre 2007; Rick et al. 2001; Villagran et al. 2011; Wake 2004b). In general, the quantification of archaeological fish remains is regionally specific (e.g., North America, Pacific Islands, and Africa).

MNI allows taxonomic abundance and species richness to be determined, but MNI values increase with the number of aggregation units (Adams 1949: 23–24; Grayson 1979: 203–205). There was an 28 early preference in the Pacific fishing literature to report only MNI values (e.g., Allo 1970; Anderson 1981; Goto 1984; Leach and Intoh 1984; Masse 1986); this trend was less common outside the Pacific (e.g., Desse and Desse-Berset 1994; Morales 1984).

Allen and Guy (1984) discounted MNI values as they only provide minimum numbers—of a subset of the original deposit that has survived—rather than the complete assemblage. To address this limitation, a formula was developed to determine the possible number of individuals within a confidence interval. Allen and Guy (1984: 44) used left and right parrotfish (Scaridae) dentaries from a Papua New Guinea site to predict within 98% confidence that the original number of individuals was between 1.6 and 4.9 times greater than the MNI of 123. Masse (1989: 411) incorporated the number of weighted individual elements (NIEwt), a measure that does not quantify fragments but rather elements; the ‘‘weighting factor’’ adjusts element counts based on the type and number of elements used to identify each species. This predicted the number of individuals that produced the archaeological fish bone assemblage, but given the limited number of elements used for taxonomic identification and the weighting protocol, no additional information was provided over traditional MNI. Formulae or models that derive theoretical values of the original number of individuals, which produce an archaeological faunal assemblage, do not improve the quality of subsistence reconstructions. In contrast, Orchard (2005) and Gabriel et al. (2012) maximised MNI values by using key measurements of fish bone and derived fish length reconstructions. The identification of element size mismatches has been applied in the Pacific to maximise MNI values (Anderson 1981; Ono and Intoh 2011), but Allen (1986: 67) argued that it can be difficult to determine size differences between elements. Lyman (2008: 80–81) has convincingly reasoned that MNI is redundant with NISP, as ‘‘interdependence of identified specimens is randomly distributed across taxa,’’ and since MNI is a derived value and heavily affected by aggregation, NISP is a more suitable method of measuring taxonomic abundance (Grayson 1984). These conclusions assume that all bone fragments or elements are considered equally for identification, which in Pacific fishing studies is not exclusively the case, given inconsistences in the identification of ‘‘special’’ elements between taxa (e.g., scales of only triggerfish and boxfish are consistently identified in Pacific fishing studies). Because the number of identifiable elements varies between fish taxa, this increases the chances of identifying those taxa that have a larger number of identifiable elements (Grayson 1979: 201). As such, when NISP is considered independently, it can be a problematic measure of both abundance and the economic significance of each taxon to the overall assemblage (e.g., Rick et al. 2002: 111, discusses the economic significance of elasmobranchs in prehistory). The potential inflation of NISP from the identification of a variable number of elements between taxa including the ‘‘specials’’ could be reduced by dividing the number

29 of elements used to make the identifications for a particular taxon by the total NISP of identified archaeological specimens for the same taxon.

Grayson (1979) argues that despite the problems associated with NISP (also with MNI), it is possible to introduce other lines of complementary evidence, such as taphonomic studies. There are limited examples in Pacific fishing studies where only NISP was reported (e.g., Allen 1992a; Kirch 1988; Pearson et al. 1971; Weisler 1999, 2004), unlike fishing studies outside the Pacific, where NISP values are more commonly used as the only measure of taxonomic abundance (e.g., Amundsen et al. 2005; McKechnie 2007; Moss 2011; Rick and Erlandson 2011; Robson et al. 2013; Zangrando 2007).

Grayson (1979) and Lyman (2008) concur that NISP is the most useful measure of taxonomic abundance, and there has been strong historic precedent for this in North American zooarchaeological analysis. The consensus in the Pacific fishing literature has been to report both MNI and NISP, which allows for comparison between all Pacific fish assemblages, and these measures are complementary (e.g., Allen et al. 2001; Clark and Szabo´ 2009; Davidson et al. 2000; Goto 1986; Kataoka 1996; Leach et al. 1999b; McAlister 2002; Ono and Intoh 2011; Weisler and Green 2013). Looking to the future, it is critical that all fish bone elements are equally considered for identification. Using MNI, NISP, and weight (including bone-to- meat weight measures) to analyse faunal assemblages provides more complete reconstructions of the economic importance of different taxa, which allows for comparisons between all fish and faunal classes, for assessment of fragmentation and postdepositional alterations, and the comparison of regional comparisons of datasets (Rick et al. 2002: 112). Studies outside the Pacific have utilised a wide range of quantification measures (MNI, NISP, weight, etc.) to analyse archaeological fish bone (e.g., Archer et al. 2014; Carder and Crock 2012; Carenti 2013; de Jong 1994; Wake and Steadman 2010; Wigen and Stucki 1988).

Standardising quantification protocols for application to all faunal analyses or specifically fish bone analysis is problematic, with researcher preference, geography, depositional context, and research framework each influencing these decisions. For this reason, transparency is paramount, as it allows assessment of quantification protocols implemented by analysts working in the same region and its impact on subsistence reconstructions. We are not advocating for a single universal approach or even for progress toward a specific outcome; rather, we encourage the use of a variety of quantification measures. Ideally, all raw data should be available as either supplementary data or by direct contact with the authors.

Taphonomy and Site Formation Processes

Due to its chemical composition, fish bone is more susceptible to degradation in archaeological sites than mammalian bone and therefore is less likely to be recovered from archaeological deposits (Szpak 30

2011: 3358). The preservation of faunal remains is influenced by a complex number of factors, including soil chemistry, bone density, burial time, and pre- and postdeposition mechanical breakage (Masse 1989: 428; Nicholson 1996).

In the pre-1980s Pacific ichthyoarchaeology, the problems associated with taphonomy and site formation processes were acknowledged but rarely addressed; these include the impact of soil pH on fish bone preservation (e.g., Allo 1970), the general friability of fish bone in archaeological deposits (e.g., Kirch and Rosendahl 1973; Pearson et al. 1971; Shawcross 1975), the effects that high oil content of tuna bone has on preservation (e.g., Davidson et al. 1998; Severance 1986), and the effects of scavengers such as dogs and pigs (Davidson 1971). There has been more intensive research on taphonomy and site formation processes outside the Pacific as it relates to storage and preservation (e.g., Carenti 2013; Jones 1984; Smith et al. 2011), butchery and processing techniques (e.g., skeletal element representation; Cerón-Carrasco 1994; Colley 1984; Van Neer et al. 2007; Zohar et al. 2001), trade and resource movement (e.g., Barrett 1997; Broughton et al. 2006; Carvajal-Contreras et al. 2008; Perdikaris et al. 2007), and cultural versus natural site accumulation (e.g., Van Neer and Morales 1992; Zohar et al. 2014).

The first formal taphonomic study of a Pacific fish bone assemblage was by Gordon (1993: 454), in Hawai‘i, where the completeness of each bone, presence/ absence of burning, and other modifications were reported. Taphonomic studies of Pacific fish bone commonly focus on preservation and representation of elements. Bilton (2001) noted similarities between breakage patterns of the five paired cranial elements and different taxa to demonstrate the influence of differential preservation on the representation of taxa from archaeological sites (Rick and Erlandson 2011; Wichman 2006). By considering all elements for taxonomic identification, we can assess the influence of differential preservation between elements and taxa on species richness and evenness. For example, the analysis of vertebrae—in some instances more readily preserved than cranial elements of the same taxon— can provide a more accurate representation of taxonomic abundance (Lambrides and Weisler 2013; Ono and Clark 2012; Wigen and Stucki 1988).

It is necessary to assess the representation of different fish bone elements archaeologically and the influence of processing techniques and animal ingestions (Butler and Schroeder 1998), bone density mediated attrition of Pacific fish remains—are the most dense bones surviving, or is the relationship more complicated (see Lyman et al. 1992; Smith et al. 2011), and cut mark studies (Archer and Braun 2013; Willis and Boehm 2014; Willis et al. 2008). Controlled experiments should be undertaken to investigate the impact of trampling, burning, different substrates, and pH on the preservation of fish bones commonly found in Pacific assemblages. Pacific ichthyoarchaeologists should implement a

31 research agenda weighted more toward taphonomy and site formation processes to realign with global approaches.

Diet and Subsistence Reconstructions

Prehistoric human subsistence is a holistic interpretation of the wider sociocultural, technological, ecological, and taphonomic factors that influence human food procurement. This is linked to a thorough understanding of human diet, that is, what is eaten, how much, and the net energy returns and nutritional value of food items (Dennell 1979: 122). As zooarchaeologists, the theoretical and philosophical assumptions that underlie our research process and the methods we use to infer diet and subsistence practices are critical in shaping reconstructions of past human behaviour.

We focus on the disciplinary shift toward ecological approaches for inferring fishing practices in Pacific archaeology and specifically three key methodological approaches that have been adopted in the Pacific fishing literature and globally for understanding prehistoric diet and subsistence practices—behavioural ecology, cultural ecology, and historical ecology. While these approaches are not distinct paradigms or the only approaches for investigating prehistoric diet and subsistence practices, we discuss the literature according to these theoretical approaches.

Early Approaches

Few Pacific Islands fishing studies prior to the early 1970s discussed the implications of fish bone to aid reconstructions of prehistoric diet (e.g., Lockerbie 1940; Shawcross 1967). Even fewer studies completed taxonomic identifications of archaeological fish bone for diet and subsistence reconstructions (e.g., Gifford 1951; Wallace and Wallace 1969). Increases or decreases in fish bone assemblages, or more commonly, the relationship between marine and terrestrial diets over time was discussed, but since the quantities of fish bone identified to taxon were often low, temporal change was difficult to assess (e.g., Kirch 1971; Kirch and Rosendahl 1973; Pearson et al. 1971; Skjølsvold 1972).

More intensive fish bone analysis was completed by Shawcross (1967, 1972, 1975) at the Galatea Bay site in New Zealand to determine prehistoric population dynamics based on reconstructions of meat weight and calculated caloric values, research that has not been widely replicated. Approaches for reconstructing Pacific prehistoric fishing practices followed a different trajectory from that in other regions due to broad distinctions in research outcomes. In Europe and the United Kingdom, there has been an intensive focus on trade, the development of commercial fisheries, the growth of urbanisation, and the eventual globalisation of these fisheries (e.g., Barrett et al. 2004a, b, 2011; Orton et al. 2014; Perdikaris et al. 2007; Perdikaris and McGovern 2009). While these research outcomes

32 are not directly comparable to Pacific fishing studies, the broader thematic and methodological implications are pertinent to this review.

Ecological Approaches and Capture Techniques

In contrast to the early culture history focus in the Pacific literature, ecology-framed research dominated the 1970s. The exploitation of prehistoric marine habitats was investigated in conjunction with modern fisheries data, including fish feeding behaviour and ecology (Butler 1994). Fish capture techniques were assessed as part of wider enquiries of resource availability and prey choice using cultural and environmental datasets (e.g., Allen 1986; Allo 1970; Masse 1986).

Using fish bone assemblages from southern New Zealand sites, Anderson (1986: 151–160) investigated factors affecting the distribution of inshore taxa on the south and east coast; variation in local ecology and selective use of capture technologies were attributed to distinctions in species abundance and richness. Smith (2002) argued that early studies in New Zealand failed to emphasise the relative importance of fishing to other subsistence practices. These early New Zealand studies were the first in the Pacific to consider ecology and human agency to infer fish capture techniques and broader subsistence reconstructions.

The link between fish behaviour, marine ecology, and capture method was first determined in the Pacific in the 1980s; archaeological fish bone was analysed in conjunction with fishing-related artefacts and ethnography to infer fish capture methods (e.g., Goto 1984; Leach et al. 1995). The relationship between cod/grouper to parrotfish was assessed to determine dominant capture technique, with cod and grouper associated with deep water and baited hooks while parrotfish were likely netted inshore (e.g., Leach and Intoh 1984; Leach et al. 1984). It can be problematic to use family-level identifications to assess fish capture techniques. Multiple methods of capture may be utilised for an individual taxon, and extensive numbers of genera and species comprise most families, with each inhabiting different ecological zones. This is further complicated by fish growth stage; for example, fish larvae initially settle in a nursery habitat (e.g., mangroves) that is relatively protected, then juvenile fish migrate to the coral reef, often occupying benthic habitats as adults. This influences habitat choice and consequently resource availability and capture method by prehistoric fishers (e.g., Masse 1986: 112; Rolett 1989: 226–237); for these reasons Bertrando and McKenzie (2011) used measurements of archaeological precaudal vertebrae (from California sites) to distinguish between capture techniques (see Ono 2010; Pletka 2011). It also has been demonstrated that screen size has implications for the detection of different capture techniques (Bertrando and McKenzie 2011: 174, table 12.3). Butler (1994) considered the implications of assessing fish dietary preferences and behaviour to infer capture techniques, as this suggested the use of techniques that were capable of

33 catching, for example, carnivorous or herbivorous taxa (see also Allen et al. 2001). Given the difficulty in determining capture techniques, ethnoarchaeology and ethnobiology provide useful comparative datasets for conceptualising this complicated issue (e.g., Dye 1983; Johannes 1981; Jones 2011; Kirch and Dye 1979). Ethnoarchaeological research on Borneo Island by Ono (2010) suggests that season, wind direction, and tidal cycle are important factors for determining prehistoric capture techniques.

Multiple lines of evidence are used to infer fish capture techniques, including modern ecological data (e.g., fish feeding behaviour), age and size profiles as determined by archaeological fish remains, material culture, modern observations of indigenous fishers, and ethnography. Reconstructing fish capture techniques is one of the most difficult aspects of investigating prehistoric fishing practices as a single capture technique is rarely associated with an individual taxon. With a continued focus on experimental archaeology, our understanding of fishing strategies, method, and techniques can improve (e.g., McKenzie 2007).

Cultural Ecology

Cultural ecology is the study of human adaptation to an environment as mediated by culture (Sutton and Anderson 2010: 3–4). This approach, which suggests that a colonising population or culture will develop along the same trajectory across an archipelago of environmentally similar islands (Rolett 1989: 21), garnered popularity in Pacific archaeology during the 1980s, as analysts shifted from traditional artefact-centric approaches to address questions of prehistoric adaptation to marine environments (e.g., Goto 1984; Kirch 1980).

Kirch’s (1979, 1980, 1982) work in Hawai‘i demonstrated the importance of ecological approaches for interpreting marine exploitation. Fish remains and their capture methods reflect behaviours dictated by local environmental constraints, ‘‘to which the population must respond in order to maintain its adaptedness—that is, a viable existence’’ (Kirch 1980: 39). While these approaches allow cultural adaptations to the environment to be better understood by moving beyond interpretations of culture as static, cultural ecology tends toward environmental determinism, suggesting that human action is dictated in large part by the local environment (Balée 1998). Given the limitations of a cultural ecological approach for understanding the past, Rolett (1989: 25) analysed Marquesas Islands faunal assemblages to determine whether similar patterns of change could be tracked between island groups or whether ecological distinctions were an important factor that mediated change. Ecological, ethnographic, material culture, and modern catch data were used to understand both capture method and targeted fish, but similar environments did not produce similar subsistence adaptations, as variation in prehistoric fish assemblages was identified at both the local level and between the islands

34 of the Marquesas. Dye (1990: 70) argues that these early ecological approaches are limiting and it is important to consider the social and historic processes that influence change.

Human Behavioural Ecology

The interpretation of zooarchaeological remains through the application of foraging models derived from behavioural ecology has become increasingly popular globally (e.g., Bird et al. 2002; Broughton 1997; Butler 2001; Nagaoka 2002a; Stiner et al. 2000). Behavioural ecology models are often viewed as constrained by the premise of optimality, which suggests that humans interact with their environment in ways that will maximise short-term reproductive fitness (Binford 1978). Human behavioural ecology (HBE) assesses how ecological factors can mediate variability in human behaviour (Lupo 2007: 145). Consequently, these models can be environmentally deterministic, and the application of prey choice models (what to select and what to pass over) and patch choice models (where to forage and for how long) must be completed using comprehensive datasets that acknowledge a wide set of inclusive variables (Kennett 1998; Stephens and Krebs 1986). Only then can archaeologists begin to disentangle the processes of culture change, with human decision making viewed ‘‘as a source of variation, rather than a force of change’’ (Allen 1992b: 184).

In her analysis of Cook Islands fishing strategies, Allen (1992a, b) evaluated the evolution of subsistence systems and associated adaptive strategies, demonstrating the complex relationship between fitness-maximising behaviours and the overall subsistence regime. Butler’s (2001) investigation of resource depression was one of the first to apply the prey choice model in the Pacific (see Butler 2000, for application in North America). Body size was used as a proxy for determining prey rank, and while the implications of mass harvesting were not incorporated in the model, technological changes and environment were considered (Butler 2001: 88). HBE models were applied in the Pacific by Butler (2001), Nagaoka (Nagaoka 2001, Nagaoka 2002a, b), and McAlister (2002). These analysts did not consider only species richness but the complex processes and strategies that mediate culture change and persistence. Fish size can be problematic for determining prey rank, but this is not to challenge its usefulness for informing prey selection strategies and particular capture techniques (e.g., Pletka 2011).

West (2009: 224) has argued that two major problems limit studies grounded in behavioural ecology: regional rather than local environmental data have been used to argue that climate change was not responsible for resource depression, and there are limited datasets that document prehistoric faunal abundance independent of the archaeological record. Investigating Alaska’s Kodiak Archipelago, West (2009: 232) developed fine-grained local climatic data using stable isotopes from archaeological fish otoliths and suggested that changes in fish population structure over time could not be attributed

35 to the abundance of salmon in the Karluk River or by local marine conditions; consequently, prehistoric subsistence practices are not always environmentally determined. A more diverse series of cultural and environmental factors must be investigated to develop these models, including dietary preferences and changes in the role of fish within the subsistence regime over time, changes in fishing technology, fish bone recovery methods and analytical techniques used, and local environmental data (e.g., Butler and Campbell 2004).

Jones (2011) and Leach and Davidson (2000) argue that models of optimal foraging derived from behavioural ecology are not suitable for understanding prehistoric fishing practices in the Pacific, as there is an overemphasis on maximising return for effort (for the North American Pacific Northwest, see Campbell and Butler 2010b). Jones (2011: 73) argues that these models are based on western constructions of optimality rather than on local definitions of success and value (Cannon 1998). Yet to what extent modern constructions of success and value can be applied to prehistoric populations is questionable, as it implies culture is temporally static. Still, Jones’ (2011) discussion of optimality cannot be overemphasised. The major limitations of optimal foraging theory described by Jones (2011) and Leach and Davidson (2000) as it relates to Pacific prehistoric fishing practices are that fish are very abundant throughout the Pacific and easily captured in mass using nets and since humans cannot live on protein alone, plant carbohydrates must be considered. People do not seek out only larger-bodied prey and select larger over small fish. In addition, most of the assumptions are based on collecting and processing shellfish and terrestrial resources that generally require greater handling time than reef vertebrates.

Food procurement decisions are not necessarily determined by concepts of optimisation; resource availability, ease of procurement, the community or population size to be fed, types of technology available, and marine environments for exploitation are all important considerations (Erlandson et al. 2009: 721), as are the relationships between all faunal classes (e.g., fish, shellfish, domesticates, and birds). In regards to conservation behaviour, Campbell and Butler (2010b: 176) suggest the HBE approach fails to recognise the diversity of factors that are central to inferences of human subsistence strategies and how these systems may remain stable or change over time. When used appropriately and the limitations are clearly acknowledged, models derived from behavioural ecology are an excellent means of hypothesis testing, especially for assessing whether people were maximising short-term reproductive fitness. Although these models do not reflect the complexity of human behaviour, these simple frameworks highlight anomalies in the data, which may warrant further analysis.

Historical Ecology

Historical ecology is a conceptual framework that considers human interactions with landscapes as an integrative phenomenon where interactions are a means of understanding the formation of past cultures and human modified environments (Balée 2006: 76; Jones 2009: 618; Rick and Lockwood 2012: 46–47). Unlike optimality or systems theory models, historical ecology considers human agency, as variable socioeconomic, political, and cultural phenomena influence landscapes differently. Humans are not genetically presupposed to operate according to expected trajectories that manifest in predictable environmental outcomes. Historical ecology is a multidisciplinary approach that does not consider one dataset to be more valid than another—it is a ‘‘holistic engagement of knowledge’’ (e.g., Balée 1998, 2006; Erlandson et al. 2009; Fitzpatrick and Donaldson 2007; Jones 2009; Kirch and Hunt 1997; Ono and Clark 2012; Rick et al. 2014; Walter 1991). Archaeologists have noted the potential of historical ecology to provide unique and inclusive interpretations of human–environment interactions across broad temporal and spatial scales (Fitzpatrick and Intoh 2009: 463). Historical ecology focuses on the creation of the ‘‘landscape,’’ which is both a product of culture and environment and is inherently meaningful. Perhaps one of the most influential historical ecology studies of marine subsistence is the ongoing research on California’s Channel Islands (e.g., Erlandson et al. 1999, 2005, 2011; Rick et al. 2001, 2005). Similar work has been completed by Jones (2009, 2011) for Fiji’s Lau Group where modern and long-term marine biodiversity and human interactions with the local environment have been investigated using ethnography and biological surveys.

The earliest consideration of a historical ecological framework for analysing Pacific fishing practices was by Walter (1991), at Ma‘uke, Cook Islands. Instead of drawing conclusions between the archaeology and modern ethnographic data, he emphasised the historical trends that shaped Ma‘uke culture. Within Pacific archaeology and more specifically Pacific fishing studies in the last decade, historical ecology has provided a framework to engage the archaeology and to consider the interrelationships with local climate, ethnography, modern marine surveys, and historical records (e.g., Fitzpatrick and Donaldson 2007; Jones and Quinn 2009; Ono and Addison 2013).

A historical ecology approach provides archaeologists with a ‘‘best practice guide’’ for completing Pacific fishing studies, with multiple lines of evidence to provide a holistic interpretation of the past (Weisler and Walter 2002). As historical ecology successfully frames analyses of prehistoric fishing practices globally, a network of literature can inform our understanding of human interactions with marine environments over thousands of years and contribute to the conservation and fisheries management discourse (e.g., Barrett et al. 2004b; Cooke and Ranere 1999; Johannes 1978; McKechnie et al. 2014; Thornton et al. 2010).

Seasonality Studies 37

Determining seasonal exploitation of resources or seasonal occupation of a site is a fundamental component of prehistoric subsistence reconstructions (Monks 1981), but it is a research pursuit that has been more intensively studied outside the Pacific. In the Pacific fishing literature, stable isotope analysis and sclerochronology—shell growth pattern analysis (e.g., Burchell et al. 2013) and fish vertebral and otolith growth ring analysis (e.g., Desse and Desse-Berset 1997; Enghoff 1994; Perdikaris and McGovern 2009; Van Neer et al. 1999)—have not been as thoroughly used. We discuss approaches for inferring seasonality in the Pacific and suggest future research avenues grounded in the global literature.

Primarily in Pacific archaeology, seasonality of fish capture was inferred from fish behaviour data. Shawcross (1967) used the condition of archaeological snapper teeth as it relates to seasonal feeding behaviours. Kirch (1979) reconstructed caloric value based on midden constituents to determine the number of ‘‘man-years’’ represented by the archaeological assemblage and to infer seasonal versus permanent site occupation. Leach (1979) used modern catches and ecological data to determine if a specific fish species could be caught in a particular month at the Washpool Midden site in New Zealand. Oxygen isotope analysis was applied only in the late 1980s in the Pacific as a method for assessing seasonality. The reanalysis of Otago archaeological sites in New Zealand using marine shell carbonate demonstrated that fishing may have been a winter activity, which suggests closer reassessment of prehistoric seasonality (Till and Blattner 1986: 175). Red cod otoliths were sectioned to examine annual and seasonal growth rings for comparison with modern samples at the Shag River Mouth site in New Zealand (Higham and Horn 2000); however, Carlson (1988) and Van Neer et al. (2004) have demonstrated that seasonality studies based solely on incremental data of fish otoliths can be problematic.

In the Pacific, stable isotope analysis has commonly been used to analyse human, pig, and dog bone (e.g., Allen and Craig 2009; Jones and Quinn 2009; Leach et al. 1998, 2003; McGovern-Wilson and Quinn 1996; Valentin et al. 2006). These data have contributed to prehistoric subsistence studies, but there has been little in-depth application of these methods to seasonality studies. Similarly, sclerochronological analysis (e.g., Andrus 2011) has been applied outside the Pacific using both shellfish (e.g., Mannino et al. 2007) and fish otoliths (e.g., Geffen et al. 2011; Hufthammer et al. 2010; Van Neer et al. 2004) to ascertain season of capture, but it has not been consistently incorporated in Pacific fishing studies. These procedures require regionally specific environmental data (e.g., water temperatures, salinity, and tidal movement across all seasonal cycles) to determine how seasonal/annual cycles affect the environment, and a detailed understanding of fish biology, such as thermal tolerances and migration patterns, in order to comprehensively determine how a species reacts to its environment. As technologies and methods are rapidly improving, these techniques need

38 to be incorporated into Pacific subsistence studies (and specifically fishing studies); in most cases the only discussion of seasonality relates to ethnographic fishing lore (e.g., Ono and Addison 2009, 2013) or modern catch data and the occurrence of seasonal runs (e.g., Olmo 2013). These methods of seasonality studies seem warranted in the Pacific based on global applications.

Resource Sustainability and Fisheries Management

The investigation of resource sustainability within the social sciences is a diverse and multidisciplinary endeavour. Sustainability relates to broader processes of globalisation, sustainable development, and policy making, and how these may be negotiated by communities on local and global levels (e.g., Almas and Lawrence 2003; Kishigami and Savelle 2005; Lawrence et al. 2010; Redclift 2005). In archaeology, ‘‘sustainable’’ does not necessarily refer to the conservation of resources, rather it is an assessment of the interrelationship between the resources exploited and the environment in which they are exploited, and whether the carrying capacity of the environment sustained human populations over time. Resource sustainability and depression often are determined by changes in fish species abundance, richness, and size over time, as well as trophic-level analysis (e.g., Fitzpatrick et al. 2011; Jones 2011; Kennett et al. 2008; Morrison and Addison 2009; Weisler 2004; Weisler and Green 2013). Humans do not have unidirectional impacts on local resources, and the dialogue between climate, environment, and people must be considered.

Assessments of the sustainability of fish exploitation throughout prehistory has been utilised by archaeologists to inform sustainable fisheries management plans (e.g., Butler and Delacorte 2004), in an attempt to address growing awareness of global declines in fish stocks and coral reefs. This relates to the impact of the ‘‘shifting baseline syndrome,’’ a term defined by Pauly (1995) whereby a generation of fisheries experts accept as a baseline the abundance and species composition recorded at the beginning of their careers, with often little acknowledgement that, historically, the fish stocks were managed at a depleted state. It has been demonstrated that zooarchaeology offers pertinent insights into the long-term dynamics of fish populations and exploitation in the past, which is not temporally constrained to historical records (e.g., Aswani and Allen 2009; Dalzell 1998; McClanahan and Omukoto 2011; Pinnegar and Engelhard 2008; Rick and Fitzpatrick 2012). These studies also have considered traditional ecological knowledge, as it can meaningfully inform modern fisheries management (e.g., Campbell and Butler 2010a; Hamilton 2003; Jones 2007; McKechnie 2007; Thornton et al. 2010). The application of diversity indices, measures of trophic alteration, aDNA analysis, and stable isotope analysis not only track changes in fish community structure and range as represented in the archaeological record but contribute unique perspectives to modern fisheries research (e.g., Butler and Delacorte 2004; Erlandson et al. 2009; Morrison and Addison 2009; Pauly et al. 1998; Reitz 2004; Van Neer and Ervynck 2009). A balance between marine research and social 39 science datasets is required, but the emphasis on establishing multidisciplinary research projects (e.g., Sea Around Us Project and Oceans Past Platform; see also Barrett et al. 2004a; Jackson et al. 2001; Kittinger et al. 2011; Miller et al. 2011; Speller et al. 2012) will continue to redirect this discourse and ideally provide holistic conservation and management outcomes (Christie 2011).

Fisheries Management

Just as modern fisheries studies inform prehistoric reconstructions of Pacific fishing (e.g., Edwards et al. 2014), so too can the archaeology of fishing contribute to globally relevant questions of resource sustainability and the effects of climate change through the establishment of ecological baseline data (e.g., Carder and Crock 2012; Carder et al. 2007; Gobalet 2012; Gobalet and Jones 1995; Kittinger et al. 2014; McKechnie et al. 2014; Rick et al. 2014; Schmölcke and Ritchie 2010; Wolverton and Lyman 2012). Given the diverse environments that comprise the Pacific Islands, archaeologists conducting zooarchaeological research have a unique opportunity to provide an unmatched record of the relationship between humans and marine/terrestrial fauna distributions over variable temporal and spatial scales (Butler 2010: 150) and thus provide a unique perspective on current debates about biological conservation.

A pioneer for the implementation of traditional marine conservation methods in the Pacific Islands, Johannes (1978, 1981, 1994, 2002, 2003) demonstrated the value of indigenous knowledge and community-based management systems. In an archaeological context, Dalzell (1998) suggested that in regions such as the Pacific Islands, where expensive resources for conducting fisheries management schemes are not readily available, archaeological data can provide useful outcomes. Given the importance of culturally informed management strategies in coral reef conservation efforts (Johannes 2002), it is surprising that more Pacific fishing studies do not implement integrative approaches in collaboration with marine biologists (e.g., Aswani and Allen 2009; Jones 2009).

Globally, historical ecological approaches have been used to assess long-term anthropogenic and climatic alterations to ecosystems, generating population baseline data and restoration frameworks (e.g., Braje et al. 2012; Kittinger et al. 2011; Lotze and McClenachan 2014; McClanahan and Omukoto 2011; McClenachan et al. 2012; Newsome et al. 2010; Rick and Lockwood 2012; Rick et al. 2014). Stable isotope, aDNA, and DNA analysis have become critical components of interdisciplinary historical ecology research and provide insight into changes in population structure, interaction, adaptation, population size estimates, trophic ecology, and alterations to prey, habitat, and foraging preferences of taxa over time—also including humans.

Speller et al. (2012) used aDNA to study genetic diversity and population structure of prehistoric herring populations, research key to understanding temporal and spatial genetic variations in fish 40 populations (see Pääbo et al. 2004; Willerslev and Cooper 2005). aDNA can be utilised to identify species introductions and translocations, particularly relevant to island archaeology (Rick et al. 2014: 688), and effectively estimate population sizes across temporal scales, which is useful for addressing the shifting baseline syndrome (e.g., analyses of prehistoric European sturgeon remains by Ludwig et al. 2008).

Carbon (δ13C) and nitrogen (δ15N) stable isotope ratios have been used to compare human bone collagen with food consumption remains to determine wider dietary patterns, particularly diet composition (e.g., Jones and Quinn 2009; Leach et al. 1998, 2003). Nehlich (2015) reviews δ34S analysis and its usefulness for reconstructing dietary, ecological, temporal, and spatial trends. The advantages of completing isotopic analysis of archaeological fish remains have been demonstrated, which include refined assessments of diet composition (Vika and Theodoropoulou 2012), identification of trophic niches, feeding habits, and habitats of exploited fish species (Fuller et al. 2012; Häberle et al. 2015; Miller et al. 2010), as well as determining provenance and catch regions to identify trade and resource movement (Barrett et al. 2011; Orton et al. 2011). Stable isotope analysis is a powerful tool for restoration and conservation efforts, as it can provide high resolution and locally representative trophic ecology data useful for assessing long-term human–environment interactions.

The importance of this integrative research agenda has been clearly demonstrated, but it should be developed as part of global approaches to ichthyoarchaeological analyses. It is important to characterise the history of an ecosystem prior to the development of management programs (Jackson et al. 2001: 636). Significant archaeological contributions include aDNA and stable isotope analyses of ichthyoarchaeological remains, assessments of fish population structure, historic biogeography, and understanding human impacts over millennial time spans. Finally, the implementation of more collaborative projects between archaeologists, indigenous communities, marine/conservation biologists, economists, and social scientists (e.g., Glazier 2011) should provide new interdisciplinary perspectives on the globally relevant issue of fisheries management.

Metric Reconstructions, Sustainability, and Resource Depression

Overharvesting, alterations to subsistence strategies, environmental change, and resource sustainability each produce diverse archaeological signatures and these complex processes are often difficult to disentangle. Temporal alterations in subsistence fishing have been documented as a decrease in fish diversity (e.g., Fitzpatrick and Kataoka 2005), an increase in fish diversity (e.g., Ono and Clark 2012), alterations to fish species archaeologically present in response to climate change (e.g., sea surface temperatures; Enghoff et al. 2007; West et al. 2011), trophic level stability and/or

41 decline (Blick 2007; Kennett et al. 2008; Morrison and Addison 2009; Pestle 2013; Quitmyer and Reitz 2006; Wing 2001), and an increase and/or decrease in average fish size over time (e.g., Amundsen et al. 2005; Bartosiewicz and Takács 1997; Carenti 2013; Desse and Desse-Berset 1993; Owen and Merrick 1994; McKechnie 2007; Weisler 2004).

Casteel (1976) completed pioneering work on the applicability of metric reconstructions of live fish weight and length as determined by key measurements of fish bone, and Shawcross (1967, 1972, 1975) was one of the first to consider fish bone morphometric measures in Pacific archaeology (also Allo 1970). There has been an intensive focus in Pacific archaeology—particularly between 1970 and 2000—on the use of metric reconstructions of fish size to determine changes in prehistoric fishing practices and human impacts over time (e.g., Butler 2001; Davidson et al. 2000; Leach and Boocock 1995). Yet, a variety of datasets are integral for disentangling the multitude of processes (i.e., cultural, social, environmental) that mediate temporal shifts in prehistoric fishing practices; these include measures of diversity and evenness, fish density, rank-order abundance, metric reconstructions (applicability is a function of sample size), aDNA analysis, isotope analysis, and trophic-level analysis (e.g., Carder and Crock 2012; McClanahan and Omukoto 2011; Wing 2001). The focus here is the development and use of morphometric measures in Pacific fish bone analysis given their popular usage, but we also assess other methods that are routinely used globally to evaluate sustainability and resource depression in the past.

In Pacific archaeology, by the 1990s, it was acknowledged that fish size reconstructions could provide a statistically rigorous method to assess temporal changes in fish size; yet formal and replicable protocols had not been developed utilising Pacific taxa (Leach and Davidson 1981: 115; Nichol 1986: 185). Measurements of archaeological fish bone were recorded and changes in size were noted, yet the factors driving this change were not determined (e.g., Goto 1984: 60; Kirch 1982: 468–469; Masse 1989: 498–515). Though not widely acknowledged in the early Pacific literature, the contribution of the Desse’s to the development of fish osteometry in archaeology cannot be overemphasised (e.g., Desse and Desse 1983; Desse and Desse-Berset 1994, 1996c). They determined that key bone measurements and fish length/weight were highly correlated (Desse and Desse-Berset 1996b: 172). These allometric relationships are a powerful tool for archaeologists assessing resource sustainability and prehistoric changes to fish population dynamics.

Leach and colleagues published an extensive literature on the protocols, implications, and benefits of fish osteometry with assemblages from New Zealand and used predominantly the five paired cranial elements and ‘‘special’’ bones (e.g., Davidson et al. 2000; Leach and Boocock 1994, 1995; Leach et al. 1999a, b). The caudal peduncle or ultimate vertebra of tuna, mackerel, and bonito (Scombridae) were measured to analyse temporal distinctions in the raw measurement values, but reconstructions 42 of fish length or weight were not regularly completed (e.g., Leach et al. 1997: 60–61; but see Fraser 1998: 128–142). Outside the Pacific Islands a wider range of cranial and postcranial elements have been used for decades to complete fish length and weight reconstructions (e.g., Desse and Desse- Berset 1996c; Enghoff 1994; Gabriel et al. 2012; Makowiecki and Van Neer 1996; Orchard 2003; Van Neer et al. 1999).

Vertebral morphometrics has had limited applications in Pacific archaeology (e.g., Desse and Desse- Berset 1996a; Ono and Intoh 2011). Ono and Intoh (2011: 267–271) assessed the applicability of determining fish weight and size from the diameter of tuna and shark vertebrae but suggested further work was needed to understand the variables that affect fish size, such as sexual dimorphism, individual variation, allometric scaling, and ecological factors (e.g., temperature). General comparisons were made between the vertebrae diameters of archaeological and modern specimens to determine live fish weights and length (Ono and Intoh 2011). Due to variability in vertebra diameter across the vertebral column of an individual specimen, it is problematic to consider vertebrae as a single and uniform element category, an issue often compounded by the difficulties of distinguishing between shark vertebrae types. Further analysis completed by Lambrides and Weisler (2015) demonstrated that archaeological fish vertebrae should be identified to taxon and type (e.g., atlas, precaudal) and, prior to fish size reconstructions, the position of each vertebra along the vertebral column should be determined (Desse and Desse-Berset 1996c; Gabriel et al. 2012; Makowiecki and Van Neer 1996).

The usefulness of morphometric measures for identifying temporal changes in fish size cannot be overestimated, but given the variability in faunal body size, prey availability, human predation, local climate, and environment, additional lines of evidence should be considered (e.g., Carder and Crock 2012; Jones and Quinn 2009; LeFebvre 2007; Ono and Clark 2012). To evaluate temporal changes in fishing practices in the Pacific, morphometric measures and simple comparisons of MNI values should not be the only analytical methods implemented. The assessment of taxonomic composition using indices of structure and similarity allows simple but informative questions to be addressed (e.g., Carder and Crock 2012; Fitzpatrick et al. 2011; Jones 2009; Joslin 2011; LeFebvre 2007; Lyman 2008). There has been a recent emphasis on the identification of trophic level alterations, which ranks marine organisms based on feeding behaviour (Pauly et al. 1998). Described as ‘‘fishing down the food web,’’ similar archaeological signatures also have been identified (Erlandson et al. 2009; Pestle 2013; Reitz 2004; Wake et al. 2013). Investigating fish exploitation in American Samoa, Morrison and Addison (2009) observed no change in the mean trophic level of the prehistoric fishery over time. Isotope and aDNA analysis are important datasets to be considered in Pacific ichthyoarchaeological analyses of resource sustainability as they facilitate high-resolution inferences of trophic ecology.

In the Pacific ichthyoarchaeological literature, there has been a focus on using osteometry and simple comparisons of MNI to evaluate changes in fishing over time. It is encouraging that a more diverse range of analytical protocols are being implemented, including changes in diversity and richness (e.g., Fitzpatrick et al. 2011), trophic analysis (e.g., Morrison and Addison 2009), and stable isotope analysis (e.g., Jones and Quinn 2009). These analyses can be integrated with material culture studies, locally specific environmental data, modern biological surveys, fish ecology and behaviour data, and ethnography to provide a fuller understanding of alterations to marine environments over time, which informs modern conservation agendas.

Ethnoarchaeology

‘‘With special attention focused on material culture, objects, technology and all material associated with daily life, ethnoarchaeological studies document what ethnographic research often leaves undescribed’’ (Jones O’Day 2004: 54). From the early anthropological work in New Guinea by Malinowski (1922) and Powdermaker (1933) of the functionalist school of anthropology, to the more recent integrative approaches by Kirch and Dye (1979) and Dye (1983) in Tonga, and Jones (2007) in Fiji, ethnography has remained an important component of Pacific fishing studies. Ethnoarchaeology should produce an ‘‘interpretive history’’ (Jones O’Day 2004: 60) that draws on indigenous knowledge and traditions, archaeology, and western histories. Although these may provide competing constructions of the past, these interrelationships offer more holistic reconstructions of ancient lifeways. The incorporation of ethnohistorical records must still be used cautiously, for example, the disparity between archaeological and ethnographic records regarding the importance of salmon fishing along the California coast (Gobalet et al. 2004; Whitaker 2011). Ethnography can usefully inform HBE approaches as archaeologists can consider decision-making processes and determine possible costs, risks, and benefits associated with different fishing strategies (Colley 1986; Hoffman et al. 2000; Keegan 1986). Ethnoarchaeology is one possible approach to investigating the past, and the consideration of ethnographic data is a valuable component of a historical ecology approach; Jones O’Day (2004: 54–57) reviews the development of ethnoarchaeology as a subfield and its contribution to both archaeology and anthropology.

Titcomb’s (1972; also Kahā‘ulelio 2006) key ethnographic study demonstrated the economic and cultural importance of fishing to native Hawaiians and the contribution of ethnography to archaeological inference. Ethnography provides interesting insights into missing archaeological evidence as in the case of eel fishing in prehistoric New Zealand, where Marshall (1987: 75) investigated contemporary and historic ethnographies to infer the social and political dimensions of prehistoric eel fishing. Local language dictionaries also provide useful information on fishing techniques and strategies. The Marshall Islands dictionary (Abo et al. 1976) lists 66 words for fishing 44 techniques, describing, in many instances, the tools and bait used, time of day practiced, location on reef, inside or outside the lagoon, depth of water, and whether the technique is an individual or group pursuit (Weisler 2001: 106). Weisler’s (1999: 31–33, 2001) study of Ebon, Maloelap, and Utrōk Atolls in the Marshall Islands emphasised the importance of participant observation in archaeological analysis of prehistoric fishing practices as, for example, parrotfish bones are far more numerous in the Marshallese archaeological record than in the modern diet. Modern Marshallese fishers also related the location of important fishing grounds, tackle and bait used, and the number of people that would typically engage in a particular fishing strategy. However, there is not always a clear link between the ethnography and the archaeology of a region; despite the ethnographically documented sociocultural significance of pelagic fish in Kapingamarangi and Nukuoro, they were archaeologically absent (Davidson and Leach 1996).

Ethnobiologists, such as Johannes (1981, 2002), have emphasised the importance of traditional knowledge for understanding human–environment interactions and long-term resource conservation. Ono and Addison (2009: 18) considered Tokelauan fishing lore from an ethnoecological perspective to determine how people in the past and present conceptualise and exploit the marine ecosystem (see also Huntsman and Hooper 1996; Ono 2010). Ethnography provides archaeologists a means of looking beyond the economics of subsistence (faunal analysis) to investigate the intrinsic relationship between the economic and social paradigms surrounding food and subsistence in the past (e.g., Weisler and McNiven 2015). With regards to Pacific Island zooarchaeology, Jones has produced some of the most comprehensive and focused ethnoarchaeological studies, which evaluate social issues related to foodways, hierarchy, and identity in Pacific prehistory, primarily in Hawai‘i and Fiji (e.g., Jones O’Day 2001, 2004; Jones 2007, 2009; Jones and Kirch 2007; Jones and Quinn 2010). This research has specifically targeted changes in marine diversity, population declines, and size changes in exploited species, and has directly linked this research to global themes of climate change and overfishing to provide long-term data for conservation and management regimes.

The Pacific is a culturally and environmentally diverse region, and when ethnography is articulated with archaeology it can be a powerful tool for understanding prehistory. Ethnography should continue to be incorporated in research approaches, such as historical ecology, to provide multifaceted reconstructions of prehistoric fishing practices, as it also foregrounds indigenous knowledge to produce sustainable fishing outcomes in a modern context.

Future Directions for the Archaeology of Marine Fishing

Refining Ichthyoarchaeology Methods and Methodologies

Field recovery techniques have progressed from the 1950s when fish bone was not routinely collected (if at all) to today where there is a near-universal preference for finer mesh (≤3.2 mm) screening. We hope to see Pacific archaeologists continue to implement screening and identification protocols that align with worldwide disciplinary ichthyoarchaeological trends for enhancing comparative analyses in the human exploitation of fishes. While there is no universal protocol for recovering faunal remains from Pacific archaeological sites, we concur with Colley (1990) who emphasises the importance of transparency over standardisation in fish bone analysis.

The analytical limitations of reference collections must be acknowledged. Reference collections that include most of the range of possible taxa in an archaeological assemblage can provide more specific taxonomic identifications; however, the establishment and curation of extensive comparative collections is a time-consuming task. Ultimately, zooarchaeological identification criteria and protocol standards provide quality assurance, which is preferable to more specific taxonomic identification.

Pacific ichthyoarchaeologists, until quite recently, have used a narrow range of elements for identification of taxa, yet recent studies have clearly demonstrated that incorporating all archaeological fish remains adds significantly to tallies of species richness and diversity. aDNA and ZooMS facilitate species-level identifications, but the added expense and time required for these techniques must be justified in reference to research questions.

Archaeological fish remains should be quantified using a range of measures (e.g., MNI, NISP, weight, bone-to-meat weight measures, etc.), as this provides more complete reconstructions of the economic importance of different taxa, which allows for comparisons between all fish and faunal classes, assessments of fragmentation and postdepositional alterations, and more reliable regional comparisons of datasets. This allows analysts to assess the influence of quantification measures on determinations of species abundance, richness, and evenness that underpin reconstructions of human behaviour.

Taphonomy and site formation also should be more intensively studied in Pacific archaeological settings. This could include the impact of trampling and burning as well as the effects of depositional context and substrates, pH, and bone density on the preservation of fish bones found in Pacific archaeological sites. Understanding these processes will provide useful insights for interpreting zooarchaeological remains from tropical settings and globally.

Three key theoretical approaches have shaped discourses in Pacific Islands zooarchaeology: cultural ecology, behavioural ecology, and historical ecology. Given the emphasis on interdisciplinary research, frameworks of historical ecology have proven worldwide utility. Historical ecological 46 approaches are not only relevant to archaeological fishing studies but are useful for examining the spatial and historical dialogues between humans and the environment. Given the global concerns relating to the depletion of fisheries and the continued demise of long-term sustainability of marine biota across all oceans, archaeologists have a unique opportunity to provide century-to-millennial historical perspectives that can inform modern fisheries conservation and management practices.

Ichthyoarchaeology and Fisheries Management

Schwerdtner Máñez et al. (2014) proposed five key areas of research for a ‘‘global marine historical research agenda,’’ which include the characteristics of a pristine environment, the different drivers (e.g., climate change, human predation, etc.) that contribute to changes in the marine environment over time, the cultural significance of marine resources over time and between human groups, the circumstances that cause people to exploit or abandon particular marine habitats, and the ways that historical datasets can be incorporated into conservation and management agendas. In order for ichthyoarchaeology to contribute to these global aims, we suggest a number of important considerations. Archaeologists should engage with relevant parties (e.g., indigenous communities, resource managers, fisheries biologists, policy makers, etc.) to frame initial research objectives, which will ensure that the data produced (e.g., species specific, region specific, habitat specific, etc.) can be utilised by these researchers. The ability to complete timely, cost-effective, and species-level taxonomic identifications of archaeological fish bone is critical to ensure relevance to the widest audience. Archaeologists must acknowledge the limitations and utility of faunal data. For example, measures of relative abundance may not have the greatest relevance for conservation management, but data relating to anthropogenic influences on the presence or absence of species over long periods of time and varying spatial scales (e.g., island, archipelago, and region) may be extremely informative. Furthermore, we cannot overestimate the benefits of archaeology that has the unique ability to assess long-term change in human–environment interactions and to generate datasets that can address archaeological research questions as well as contribute to conservation and management agendas; topics may include aDNA and stable isotope analyses of ichthyoarchaeological remains, assessments of fish population structure, historic biogeography, and human impacts over millennial time spans. Finally, increasing dialogue between disciplines and developing collaborative, interdisciplinary projects are essential to the successful use of archaeological data in management and conservation planning and policy as exemplified in the Oceans Past Platform COST Action.

Acknowledgements

We thank the five anonymous reviewers, Linda Nicholas, and Gary Feinman for constructive feedback. Lambrides’ graduate studies were funded by an Australian Postgraduate Award. Weisler

47 thanks Wenner-Gren for Anthropological Research, the Australian Research Council, the US National Park Service, and gratefully acknowledges the special funds from the Universities of Queensland and Otago for supporting more than 25 years of Pacific Islands research that allowed exploration of a diverse range of marine habitats and countless fishing sorties with indigenous peoples that have shaped some of the ideas expressed here. We thank Matthew Harris for preparing the figures.

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Figure 1. Map of the Pacific with islands and archipelagos mentioned in the text. The highest species diversity is within the Coral Triangle with a marked decline in taxa from west to east across the Pacific.

Figure 2. Coastal environments of the Pacific Islands. (A) Island-arc or continental island with the Shag River Mouth 14th century AD archaic site (centre of frame) situated along the east coast of the South Island, New Zealand showing the estuary to right and sandy marine shore (photo: M. Weisler); (B) A portion of Ebon Atoll, Marshall Islands with small islets atop the reef platform ringing the central lagoon to left (photo: M. Harris); (C) The south, leeward shoreline of the high volcanic island of Moloka‘i, Hawaiian Islands with a 1-km-wide fringing reef and prehistoric walled fishpond (photo: M. Weisler); (D) Makatea (raised limestone) Henderson Island, Pitcairn Group with typically narrow reef platform (here, only 30 m wide) and near-uniform island elevation of 33 m (photo: courtesy Sir Peter Scott Commemorative Expedition to the Pitcairn Islands, used with permission).

Figure 3. Cranial elements used for identification to lowest taxon. Dark-shaded elements are the routinely used five paired bones, while all the other cranial elements are now more commonly used for identification. This is a generalised diagram of the cranium to illustrate the position of elements (after Gregory 1959: 87).

Figure 4. A generalised diagram of the vertebral column illustrating the position of vertebrae types (after Cannon 1987: 21).

CHAPTER 3: Assessing Protocols for Identifying Paciﬁc Island Archaeological Fish Remains: The Contribution of Vertebrae

Note: This is the final version of a peer-reviewed article published in the International Journal of Osteoarchaeology.

Ariana B.J. Lambrides and Marshall I. Weisler

School of Social Science, The University of Queensland, St Lucia, Qld 4072 Australia.

Corresponding author: Ariana Lambrides, School of Social Science, The University of Queensland,

St Lucia, Qld 4072 Australia. Telephone: +61 7 3365 3038. Fax: +61 7 3365 1554. Email: [email protected]

Assessing Protocols for Identifying Paciﬁc Island Archaeological Fish Remains: The Contribution of Vertebrae

Abstract: Three fish bone identification protocols used for determining taxa composition for Pacific island archaeofaunal assemblages are evaluated. The protocols include using the following: (1) the most commonly identified five paired cranial bones and ‘specials’ or unique elements; (2) an expanded number of cranial bones; and (3) the less common inclusion of all vertebrae. Explicit identification and quantification protocols are outlined for systematically incorporating all vertebrae which, predictably, increases the number of identified specimens for an assemblage, thus providing more bones useful for reconstructing live fish biomass (weight and length). Significantly, a range of unique archaeological vertebrae are useful for calculating minimum number of individuals. Using a well-preserved assemblage from Henderson Island, Pitcairn Group, southeast Polynesia, numbering 6480 fish bones (concentration index = 21 580 m3), we demonstrate differences in rank-order abundance from three taxon identification protocols. For example, when using all vertebrae grouper (Serranidae) and surgeonfishes (Acanthuridae) are more numerically equivalent than when relying mostly on cranial bones for identification for minimum number of individuals and number of identified specimens. This has important implications for making comparisons between sites or across regions where different identification protocols were used. This pilot study demonstrates that using all vertebrae for taxon identification and quantification, not just unique hypurals (terminal vertebrae) or those from sharks and rays (Elasmobranchii), should be standard practice for identifying a greater number of bones to taxon and thereby providing better reconstructions of prehistoric fishing and subsistence practices in the Pacific.

Keywords: ﬁsh vertebrae analysis, prehistoric ﬁshing, Henderson Island, Polynesia

Introduction Fish bone is the most ubiquitous vertebrate faunal class recovered from Pacific archaeological sites, and its study offers insights into subsistence practices, diet, economy and ritual. The analysis of Pacific archaeological fish bones was initially undertaken by zoologists or ichthyologists, such as Fowler’s (1955) analysis of Gifford’s (1951) Fiji assemblage. However, the importance of making taxonomic identifications of archaeological fish bone was not acknowledged in the Pacific until the early 1970s. Initially, taxonomic identifications of Pacific archaeological fish bone were restricted to ‘dental jaws’ or ‘dental plates’ (e.g., Davidson 1971; Kirch 1979), now referred to as dentaries or premaxillae. Leach and Davidson (1977) developed the first systematic and formalised fish bone identification protocol using an assemblage from Paremata, New Zealand (see also Leach 1986). Taxa were identified using five paired cranial bones—dentary, premaxilla, maxilla, articular and quadrate—as well as ‘specials’ (e.g., scutes, pharyngeal grinding plates, unusual vertebrae, unique anal and dorsal spines, etc.). These elements were considered the most useful for identifying fish taxa given their common occurrence in Pacific archaeological sites.

Recently, a more diverse range of cranial elements has been used in identifications of fish bone from Pacific archaeological sites increasing the richness and abundance of identified taxa (e.g., Ono and Clark 2010; Vogel 2005; Walter 1998; Weisler and Green 2013). These paired elements include: basipterygium, ceratohyal, cleithrum, coracoid, ectopterygoid, epihyal, hyomandibular, interopercle, metapterygoid, opercle, palatine, posttemporal, preopercle, scapula, subopercle, supracleithrum, supraoccipital and symplectic as well as single elements parasphenoid and urohyal. Currently, fish bone identification protocols used by most Pacific archaeologists include the common five paired bones, an expanded set of cranial elements and the specials.

Fish bone identification protocols over the last four decades in Pacific archaeology have entirely focused on the cranial elements (Table 1), with the exception of unusual spines and vertebrae considered under the category of specials. Despite the fact that vertebrae preserve in a range of depositional site contexts, their use most commonly extends to those easily identifiable vertebrae of sharks, rays and skates (Elasmobranchii; e.g., Clark and Szabó 2009; Vogel and Anderson 2012) or hypurals (terminal vertebrae) of tuna, mackerel and bonito (Scombridae; e.g., Fraser 1998, 2001). Only Ono (2003, 2004) has emphasised the importance of considering all vertebrae in Pacific archaeological fishing studies.

Following Casteel (1976: 83–87) and Fraser (1998: 128–142), Ono and Intoh (2011: 267–271) have assessed the applicability of reconstructing live ﬁsh weight from the diameter of archaeological Scombridae vertebrae from comparisons with modern specimens. However, as vertebrae size and

84 shape are highly variable within an individual fish, we argue that the type of archaeological vertebrae (e.g., atlas, thoracic, precaudal, etc.) must be identified prior to allometric reconstructions of size and weight and not used as a single and uniform element class (e.g., Rolett 1998: Figure 6.2). Ono and Intoh (2011: 268) acknowledged the preliminary state of vertebrae size analysis in Pacific archaeology and assert the need for its future development. Our study expands on previous work and reviews limited studies of vertebrae in Pacific archaeology.

We contrast the contribution of different fish bone identification protocols towards documenting relative taxonomic abundance by using the following: (1) only the commonly identified five paired cranial bones and specials or unique elements; (2) an expanded number of paired cranial bones; and (3) the inclusion of all vertebrae. We show that these protocols can result in different interpretations of prehistoric subsistence practices and diet, which has important implications for making comparisons between sites or across regions where different identification protocols were used.

The quality of bone preservation is an important consideration when determining the most useful elements for taxonomic identification, and it cannot be assumed that preservation is consistent across the elements of different fish taxa. Therefore, for our study, we used a well-preserved fish bone assemblage from Henderson Island, Pitcairn Group, southeast Polynesia, to evaluate the efficacy of each identification protocol.

Archaeological context of the study assemblage

Henderson (24.37°S, 128.33°W) is a 33 m high raised limestone or makatea island (37 km2), one of four islands in the Pitcairn Group, southeast Polynesia. An island-wide archaeological survey was conducted by Weisler in 1990–1992, where 28 habitation sites, mostly rock shelters, were found concentrated immediately above the east and north beaches, with associated gardening zones just back from the cliff edge (Figure 1; Weisler 1995, 1998). A total of 42 m2 were excavated in all the major habitation sites. The only coastal midden (HEN-5), ~30 m wide and some 300 m along the leeward north coast, was defined by nine transects consisting of 16 1 m2 units and 20 auger holes (Weisler 1998: Figure 4). The primary cultural layer, ~35 cm thick, consisted of calcareous midden- stained black (2.5Y N2/0) sediments with a neutral pH grading to sterile pale brown (10YR 6/3) subsoil. Features included scoop hearths, earth ovens, post holes, refuse dumps, a flat beachrock pavement and a basalt adze working area (Weisler 1995: 387). Eleven radiocarbon age determinations bracket occupation from ~1100 to 400 BP, making the basal deposits amongst the oldest in southeast Polynesia. All excavations recovered more than 150 000 well-preserved bones of mostly fish, rats, pigs, turtles and humans (Collins and Weisler 2000; Stefan et al. 2002) but also elements of extinct birds (Wragg 1995). Fish bone reported here came from TP (test pit) 12 situated towards the west end

85 of the site and about an equal distance from the beach and base of the cliffs (Weisler 1998: Figure 4). These are amongst the densest bone concentrations found at any of the Henderson sites (concentration index = 21 580 bones per m3).

Methods

All bones from HEN-5 were retained following field wet-screening through 6.4 mm sieves and sampling through 3.2 and 1.6 mm sieves. Only the fish bone retained in the 6.4 mm screens from TP 12 is reported in this paper. Initially, all fish bones were analysed by Weisler in the early 1990s using the traditional five paired cranial bones and specials, then Weisler used an expanded set of cranial bones to determine if more identifications could be added (Weisler and Green 2013: Table 1). Weisler’s identifications used comparative collections he developed over the past 30 years (Weisler 2001: Appendix 3) and those at the University of Otago (Walter et al. 1996). All vertebrae were identified by Lambrides recently to investigate changes in assemblage composition across the three protocols discussed in the previous text. Lambrides also used the comparative collections listed in Weisler (2001: Appendix 3), in addition to more than 75 new specimens. For the vertebrae analysis, reference was made to 73 fish specimens, representing eight families, 35 genera and 54 species, together comprising over 2000 vertebrae.

Some 6480 archaeological fish bones weighing 957 g were sorted into elements and identified to the lowest possible taxonomic level. Comparisons between the three identification protocols were made at the family level. It is important to acknowledge that on the basis of the two separate analyses of all the cranial bones and specials, the most abundant eight families of fish (Acanthuridae, Carangidae, Holocentridae, Labridae, Mullidae, Scaridae, Scombridae and Serranidae) recovered from HEN-5 were used to complete the vertebrae analysis. These families were chosen to facilitate the development of identification protocols utilising vertebrae against previously accepted methods of fish bone identification in the Pacific. The other taxa identified utilising all cranial bones and specials represented only 27 minimum number of individuals (MNI) from seven families including Balistidae, Belonidae, Carcharhinidae, Cirrhitidae, Diodontidae, Kuhliidae and Pempheridae; consequently, they are not explicitly discussed in this study. No formal taphonomic study was conducted when analysing the fish bone from HEN-5. However, fragmentation (defined as less than 50% of an individual vertebra) was quantified. Fragmented vertebrae could not be assigned a specific element type (see the succeeding text for explanation) and identified.

The initial stage of analysis required the identification of the five paired cranial bones: dentary, premaxilla, maxilla, articular and quadrate. These elements are the most commonly identified in Pacific literature on prehistoric fishing (Leach 1986). Furthermore, specials such as the dorsal and

86 anal spines of acanthurids, the scutes of carangids, and superior and inferior pharyngeal grinding plates of scarids and labrids, were all identified for their distinctiveness when conducting family-level identifications (e.g., Weisler and Green 2013). The second identification protocol incorporated an expanded number of cranial bones (listed previously). These less commonly used elements have been found to increase both species abundance and richness indices in archaeological fish bone assemblages (e.g., Jones O’Day 2004; Vogel 2005; Weisler et al. 2010).

The final stage of analysis used all vertebrae, which were divided into eight groups: proatlas, atlas, thoracic, precaudal, caudal, antepenultimate, penultimate and ultimate (after Casteel 1976: 77–78) (Figure 2). Antepenultimate (also known as the third to last vertebra) was useful for identification to taxon but is usually grouped with the caudal vertebrae in the biological literature. Our identification order went from proatlas, atlas, ultimate, penultimate to antepenultimate. These elements are the most easily identified as an individual fish has only one of each proving ideal for calculations of MNI. On the basis of these identifications, a list of known families was compiled to facilitate identification of thoracic, precaudal and caudal vertebrae. These three vertebrae groups are the most difficult to identify because of intra-group variation; an extensive reference collection will, however, facilitate their identification. In this regard, all Carangidae vertebrae have considerable variability across genera, whereas the other seven families in our study presented less genera level variation.

Vertebrae counts for thoracic, precaudal and caudal vertebrae—based on family, genus and species— were recorded for comparison with the archaeological assemblage. For example, the Acanthuridae comparative specimens used for these analyses each comprised two thoracic, six precaudal and 10 caudal vertebrae; therefore, 50 archaeological caudal vertebrae represents an MNI of five (after Casteel 1974). The list of all cranial elements and specials is provided to assess the distribution of elements used for the identification of each taxon (e.g., Weisler et al. 2010: Table 1). Vertebrae types are also included to ensure the transparency of quantification calculations and replication of methods to facilitate comparisons between studies.

Weisler et al. (2010: 135) provided a detailed account of the strengths and weaknesses of quantifying archaeological fish bone using MNI or number of identified specimens (NISP); Grayson (1984) has shown the strong correlation between these values. Lyman (2008: 80–81), however, has argued that MNI is redundant with NISP as ‘interdependence of identified specimens is randomly distributed across taxa’, and as MNI is a derived value and heavily affected by aggregation, NISP is a more suitable method to measure taxonomic abundance. Nonetheless, Lyman’s conclusions were largely based on the analysis of mammalian remains; in contrast, ‘special’ elements are commonly used for taxonomic identification as well as vertebrae, which significantly inflate NISP. The inflation of NISP resulting from the identification of specials and vertebrae can be corrected by dividing the NISP for 87 each taxon by the number of unique elements used to make the identifications. The implications for fishing studies require further analysis, as MNI is predominately utilised to discuss taxonomic abundance in the Pacific literature. In this study, both quantification methods are reported to facilitate better comparisons between all Pacific fishing literature irrespective of whether MNI or NISP were calculated (Allen et al. 2001: 61; Weisler et al. 2010: Table 2).

Results

Tables 2 and 3 present the NISP, MNI and rank-order abundance determined by the three identification protocols—five paired cranial bones and specials, expanded set of cranial bones and vertebrae—based on the eight dominant fish families identified from the HEN-5, TP 12 assemblage. Of the 6480 fish bones in our study, 1773 (27%) were vertebrae (including fragments) weighing 268 g and 4707 other elements weighing 689 g.

Five paired cranial bones and specials

A total of 547 fish bones (28% of the total NISP across the three identification protocols) were identified using the five paired cranial bones and specials. Of the eight families identified, the dominant fish taxa, in rank order, were Serranidae, Acanthuridae and Carangidae, contributing 95% of NISP and 86% of MNI. Serranidae accounted for 51% of total NISP and 55% of total MNI; Acanthuridae had only 28% of total NISP and 24% of total MNI; Carangidae inventoried 17% of total NISP and 7% of total MNI.

The NISP for both Acanthuridae and Carangidae were significantly increased by the identification of ‘special’ elements; these included dorsal and anal spines (94% of identified elements) and scutes (84% of identified elements), with only ~7–15% of total identified elements for Acanthuridae and Carangidae represented by the commonly used five paired cranial bones. Importantly, only the five paired cranial bones were used for identifying Serranidae, which only has two special elements, parasphenoid and vomer, utilised for taxonomic identification in the Pacific fishing literature.

Expanded set of paired cranial bones

The expanded set of cranial bones added 201 NISP (10% of the total NISP across the three identification protocols). Identical to the distribution of taxa inventoried by the five paired cranial bones and specials, the two highest ranked taxa were Serranidae and Acanthuridae, together representing 81% of total NISP and 78% of total MNI. Serranidae accounted for 54% of total NISP and 51% of total MNI, and Acanthuridae contributed 28% of total NISP and 26% of total MNI. Significantly, the MNI for Carangidae, Labridae, Scaridae, Scombridae and Serranidae was not increased by the identification of the expanded set of cranial bones. However, the NISP for

Carangidae, Scaridae and Serranidae was increased between 10% and 45% (some percentage increases are inﬂated by small sample size, for example, the NISP for Scaridae increased from three to four).

The MNI of Acanthuridae, Holocentridae and Mullidae had small increases of only one to three, with the inclusion of an expanded set of cranial bones but, signiﬁcantly, an approximate doubling in NISP values (from 151 to 206, 1 to 3 and 13 to 23, respectively). Importantly, these results demonstrate that including the expanded set of cranial bones significantly increases the taxonomic abundance for Acanthuridae, Holocentridae and Mullidae.

Vertebrae

Some 1246 vertebrae from eight families (62% of the total NISP across the three identification protocols) were identified (Table 4). As inventoried by all cranial bones (five paired and expanded) and specials, the dominant taxa using vertebrae remained Serranidae and Acanthuridae, representing 85% of total NISP and 78% of total MNI. Significantly, the highest ranked taxon changed to Acanthuridae, accounting for 45% of total NISP and 40% of total MNI, whereas the second ranked Serranidae, contributed 39% of total NISP and MNI. Acanthuridae and Serranidae clearly dominated the TP 12, HEN-5 assemblage across all three identification protocols (Table 2). The use of vertebrae for taxonomic identifications documents that, at least in our sample, Acanthuridae and Serranidae are more economically equivalent than was originally determined by all the inventoried cranial bones and specials. For Acanthuridae, there was a significant increase in both NISP (206 to 907) and MNI (20 to 40) values when the vertebrae were routinely identified. In contrast, the MNI and NISP across all three identification protocols remained similar for Serranidae, which suggests that the five paired cranial bones are adequate for its taxonomic identification. Similar rank-order abundance based on MNI and NISP was noted for Carangidae, Labridae, Mullidae, Scaridae and Scombridae across all three identification protocols (Table 3). Conversely, Holocentridae, when represented by all cranial bones and specials, had low NISP (3) and MNI (2) values but markedly increased to 36 NISP and 4 MNI with the inclusion of vertebrae. The overall increase in NISP and MNI for Holocentridae following the inclusion of vertebrae is not as pronounced as the change noted for Acanthuridae but still warrants the inclusion of vertebrae for documenting abundance values for archaeological fish bone assemblages. Significantly, using vertebrae for determining the taxonomic abundance for our study assemblage more than doubled the NISP counts (Tables 2 and 3).

The distribution of archaeological vertebrae was largely equivalent to the natural distribution of vertebrae counts in an individual ﬁsh (Table 4). Accordingly, the most commonly identiﬁed vertebra type was the caudal and is likely to be the most highly represented in an archaeological assemblage.

Discussion

Several studies of archaeological fish bone assemblages have suggested that increasing the kind of elements used for taxa identification increases the abundance and diversity of reported species (Butler 1994; Ono and Clark 2010; Vogel 2005). None of these studies have systematically compared the results from using the three identification protocols on the same assemblage. It is especially important to know the limitations and contributions of each protocol when comparing regional studies that used different protocols. For example, Ono and Clark (2010: 650) compared NISP and MNI values when eight and 19 elements are used for taxonomic identification; the former comprised the five paired cranial bones and some specials, and the latter an increased number of specials, as well as vertebrae and some additional cranial elements. This study examined the use of these protocols in the Pacific over time and the corresponding effect on taxa identification.

Limits of using only cranial bones

Butler (1994) and Ono and Clark (2010) have argued that increasing the number of cranial elements identified in conjunction with the traditional five paired cranial bones and specials does not change relative faunal abundance of the most dominant fish taxa. (However, this is not the case when all vertebrae are analysed.) Similarly, this analysis has demonstrated that total MNI of our study assemblage was not significantly affected by the inclusion of an expanded number of cranial elements for taxonomic identification, aside from a minimal increase in the abundance of Acanthuridae, Holocentridae and Mullidae. This limits interpretations based on potentially underrepresented taxa by restricting element selection for fish bone analysis.

It has been demonstrated that reconstructions of taxonomic abundance are limited when utilising predominantly cranial elements, especially if a dominant economic taxon, such as Acanthuridae, has fragile mouth parts that are more susceptible to post-depositional and taphonomic processes, and even differential recovery (e.g., Leach et al. 1988; Nagaoka 2005; Weisler and Green 2013). Conversely, a bias towards taxa with larger and denser cranial bones, such as Serranidae, will occur when only utilising these elements for taxonomic identification (Table 2 and 3). An overall increase in NISP of ~37% was reported following the inclusion of an expanded set of cranial elements (Table 2). The significance of this increase in NISP has often been underemphasised in the Pacific fishing literature as the focus has been whether rank-order abundance of dominant taxa is affected by element selection (e.g., Butler 1994: 85–86). There are two major benefits of increasing NISP: (1) a more comprehensive analysis of taphonomic and site formation processes can be completed and (2) an increase in the frequency of elements available for size reconstructions is available. The incorporation of an expanded set of cranial bones to the traditional five paired cranial bones and specials resulted

90 in an overall increase in MNI and NISP for the TP 12 assemblage but did not signiﬁcantly inﬂuence rank-order abundance (Table 3).

Beneﬁts of vertebrae

The use of vertebrae has contributed to a more comprehensive understanding of relative taxonomic abundance for the HEN-5, TP 12 assemblage. Importantly, the total MNI for Acanthuridae increased by 100%, from 20 to 40, surpassing the total MNI of Serranidae, which remained 39 across all three identiﬁcation protocols. MNI using the ﬁve paired cranial elements for Acanthuridae contributed 42%, expanded cranial elements added 8%, whereas, significantly, vertebrae added a further 50%. This is an important increase and highlights the robust nature of Acanthuridae vertebrae in contrast to their paired cranial bones. In our study, the results document that the rank-order abundance was changed by the inclusion of vertebrae (Table 3).

A complete analysis of vertebrae at HEN-5 is beyond the parameters of this pilot study, but future analyses of the more than 100 000 fish bones recovered from the site may highlight more pronounced distinctions in taxonomic richness and evenness, as well as rank-order abundance. The inclusion of vertebrae in Pacific archaeofish bone assemblages allows a much larger portion of an assemblage to be analysed and, as such, provide a larger sample to access species variation and reconstructed live fish size within and across taxa at a site. By analysing elements from the entire fish skeleton, differential preservation and processing/ butchering of fish can be more accurately inferred. The application of archaeological vertebrae analysis has been further developed outside the Pacific, with a focus on the use of morphometrics for size reconstructions and taxonomic identifications (e.g., Desse-Berset and Desse 2008; Gabriel et al. 2012; Huber et al. 2011). In the Pacific fishing literature there has been a trend towards completing morphometrics of unidentified fish vertebrae to ascertain broad changes in fish size over time (e.g., Jones 2009; Jones and Quinn 2009; Rolett 1998; Weisler et al. 2010). ‘This procedure is based on the assumption that both the identified and unidentified fish vertebrae represent a cross section of the species present in the assemblage’ (Jones 2009: 622), an assumption that may not be true for all assemblages due, at least, to varying taphonomic conditions within the same site. A generalised decline in fish vertebrae size is less meaningful than a specific analysis of the abundance and changes in the size of individual taxa over time. A method of analysis that utilises unidentified fish vertebrae fails to incorporate assemblage composition as a critical factor influencing fish size reconstructions; consequently, vertebrae should be identified to taxon prior to estimating overall reconstructed fish size between layers and across sites. Estimating fish size at the family level may inform that specific families demonstrate a change in size over time that is masked when all vertebrae are grouped together.

Furthermore, Jones’ (2009: 625) analysis of the Na Masimasi, Lapita site produced a low overall MNI (59) for fish but a comparatively high NISP (7570), as ‘the low number of MNI from Na Masimasi is due to an extremely high frequency of vertebrae in the assemblage and the somewhat preliminary nature of fish bone identifications’. Jones’ analysis did not utilise vertebrae to the full extent to significantly increase the MNI values at the Na Masimasi site.

It is also important to include the distribution of vertebrae types used to complete taxonomic identifications. There are two main issues regarding the analysis of vertebrae in the Pacific fishing literature: (1) vertebrae are often presented as a uniform category when presenting the distribution of identified elements (e.g., Ono and Clark 2010: Table 2) and (2) measurements of vertebral centra are completed without specifying the distribution of vertebrae types (e.g., Jones 2009: Table 5). This is significant as there is natural size variation along a fish vertebral column, and by treating archaeological vertebrae as a uniform class, the variation in a vertebrae assemblage may not be accurately determined. It is argued that by analysing and reporting archaeological vertebrae on the basis of type (Figure 2), there can be standardisation in the use of vertebrae in Pacific archaeology and an improvement in the overall replicability of results.

Implications for prehistory: the Henderson case study

Weisler et al. (2010, 2013) commented that the fish bone assemblages from raised limestone (makatea) islands such as Henderson are usually dominated by Serranidae, unlike the majority of other Pacific island fish assemblages, where Scaridae have been reported as the most abundant taxa (Leach and Davidson 2000: 414). Consequently, the dominance of Serranidae may be ‘a unique signature of makatea assemblages’ (Weisler et al. 2010: 130). Given the ecology of makatea islands and frequency of fishhooks in the Henderson assemblage, it was inferred that angling was probably the dominant capture technique for Serranidae. Yet, based on the distribution of taxa for TP 12 as determined by the inclusion of vertebrae, Acanthuridae is the most dominant fish taxon (commonly captured by netting).

Conclusions

This paper provided a detailed identification and quantification protocol for the consistent application of vertebrae analysis in prehistoric Pacific fishing studies. Archaeological vertebrae should be identified to the highest taxonomic level and vertebra type prior to allometric reconstructions of live fish size and weight. Vertebrae should not be considered as a single uniform element class. The distribution of vertebrae types used for identifications requires inclusion in tables to ensure the transparency of quantification calculations and replication of methods to facilitate comparisons between studies. 92

In our study for Henderson Island, the inclusion of vertebrae suggested that angling may have been a less important capture technique, with netting more common than previously interpreted. We agree with Ono and Clark (2010: 652) that only when more comprehensive methods are implemented for the identification of archaeological fish bone across the Pacific can archaeologists begin to assess the dialogue between humans and their marine ecosystems throughout prehistory. As such, our comprehensive vertebrae analysis demonstrated that by considering a wider number of elements for the analysis of archaeological fish bone assemblages, relative taxonomic abundance can be more accurately determined, thereby leading to more accurate interpretations of prehistoric human behaviour with the marine ecosystem. Furthermore, regional syntheses must be approached cautiously when using older studies that utilised a limited number of fish elements for identification. We therefore suggest that identification of all vertebrae become standard practice for archaeological fish bone studies in the Pacific.

Acknowledgements

Henderson Island field work was conducted as part of the Sir Peter Scott Commemorative Expedition, which was generously supported by the Royal Society, International Council for Bird Preservation, British Ornithologists’ Union, J. A. Shirley, Foreign & Commonwealth Office UK and UNESCO. Much of the original lab work was funded by the Wenner-Gren Foundation for Anthropological Research to Weisler. We thank Matthew Harris for preparing the figures.

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Table 1. The dominant elements used to make archaeological fish identifications from Pacific assemblages from the 1970s to contemporary literature.

Time Period Elements 1970s 1980s 1990s 2000 - present ‘Dental jaws’, ‘mouth parts’, (Davidson 1971; Kirch 1971, (Allen 1986; Best 1984; Goto ‘head bones’, or ‘dental plates’ 1975, 1979; Kirch and 1986; Nichol 1986) etc. (= dentary/ premaxilla) Rosendahl 1973) Five paired cranial bones + (Leach 1976; Leach and (Anderson 1981; Davidson and (Allen 1992; Davidson et al. (Allen et al. 2001; Clark 2005; ‘specials’ Davidson 1977) Leach 1988; Green 1986; 1998; Leach et al. 1997; Davidson et al. 2000; Leach et al. 1988; Masse 1989) Weisler 1999) Fitzpatrick and Kataoka 2005; Weisler 2001) Five paired cranial bones (excl. (Leach and Davidson 1988; (Allen and Steadman 1990; articular and/or quadrate) Rolett 1989) Dye 1990; Rolett 1998; Walter + ‘specials’ 1991) Expanded number of cranial (Walter 1998) (Jones O'Day 2004; Ono 2003, bones 2004; Ono and Clark 2010; Ono and Intoh 2011; Vogel 2005; Weisler et al. 2010; Weisler and Green 2013)

Vertebrae ‘special’ a (Davidson 1971; Leach and (Davidson and Leach 1988; (Davidson et al. 1999; (Clark and Szabó 2009; Jones Davidson 1977) Leach 1989; Leach et al. 1988) Davidson et al. 1998; Fraser O'Day 2004; McAlister 2002; 1998; Leach et al. 1994; Leach Vogel and Anderson 2012; et al. 1997; Weisler 1999) Weisler 2001; Weisler and Green 2013) Vertebrae b (Ono 2003, 2004; Ono and Clark 2010; Ono and Intoh 2011) a A select range of vertebrae that were considered under the category of ‘specials’, which predominately refer to Elasmobranchii (sharks, rays and skates) vertebrae and Scombridae (mackerels, tunas and bonitos) ultimate vertebrae. b All vertebrae are analysed and identified (where possible) in an assemblage, beyond what would be considered as ‘specials’.

Table 2. Fish bone MNI and NISP from TP 12, Henderson Island as represented by three separate identification protocols: (1) the five paired cranial bones and ‘specials’, (2) an expanded number of cranial bones; and (3) vertebrae (Acanthuridae, Carangidae, Holocentridae, Labridae, Mullidae, Scaridae, Scombridae and Serranidae only).

Five paired cranial bones + ‘specials’ Expanded number of cranial bones Vertebrae Layer IA Layer IB Layer III Layer IA Layer IB Layer III Layer IA Layer IB Layer III Taxon MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) MNI (NISP) Acanthuridae 1 (4) 15 (145) 1 (2) 2 (8) 17 (195) 1 (3) 2 (42) 37 (855) 1 (10) Carangidae 1 (3) 4 (89) 0 1 (3) 4 (98) 0 1 (7) 5 (175) 1 (2) Holocentridae 0 1 (1) 0 1 (1) 1 (2) 0 1 (4) 3 (32) 0 Labridae 0 3 (8) 0 0 3 (8) 0 0 3 (14) 0 Mullidae 1 (1) 2 (11) 1 (1) 1 (2) 3 (20) 1 (1) 1 (3) 3 (41) 1 (1) Scaridae 0 1 (3) 0 0 1 (4) 0 0 1 (10) 0 Scombridae 1 (2) 0 0 1 (2) 0 0 1 (3) 1 (11) 0 Serranidae 5 (11) 33 (264) 1 (2) 5 (18) 33 (381) 1 (2) 5 (38) 33 (739) 1 (7) Total identified 9 (21) 59 (521) 3 (5) 11 (34) 62 (708) 3 (6) 11 (97) 86 (1877) 4 (20) Total unidentified 250 5593 84 237 5406 83 174 4237 69 Total bones

(including vert.) 271 6114 89 271 6114 89 271 6114 89 % identified 7.7 8.5 5.6 12.5 11.6 6.7 35.8 30.7 22.5

Note that MNI for Acanthuridae doubled when using vertebrae, in contrast to all cranial bones and ‘specials’.

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Table 3. Rank-order abundance based on NISP and MNI for five paired cranial bones and ‘specials’, expanded number of cranial bones and vertebrae for all cultural layers from TP 12, Henderson Island (Acanthuridae, Carangidae, Holocentridae, Labridae, Mullidae, Scaridae, Scombridae and Serranidae only).

Five paired cranial Expanded number of Vertebrae bones + ‘specials’ cranial bones Taxon NISP MNI NISP MNI NISP MNI Acanthuridae 2 2 2 2 1 1 Carangidae 3 3 3 3 3 3 Holocentridae 8 6 7 5 5 5 Labridae 5 5 5 4 6 6 Mullidae 4 4 4 3 4 4 Scaridae 6 6 6 6 7 8 Scombridae 7 6 8 6 6 7 Serranidae 1 1 1 1 2 2 Total ID bones 547 71 748 76 1994 101

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Table 4. Distribution of vertebrae types used for the identification of TP 12, Henderson Island fish bone assemblage (Acanthuridae, Carangidae, Holocentridae, Labridae, Mullidae, Scaridae, Scombridae and Serranidae only).

Taxon Proatlas Atlas Thoracic Precaudal Caudal Antepenultimate Penultimate Ultimate Numberof types Acanthuridae 14 54 217 396 15 5 6 Carangidae 2 21 15 36 3 1 5 7 Holocentridae 1 7 19 6 4 Labridae 1 4 1 3 Mullidae 3 12 5 1 1 5 Scaridae 2 3 1 3 Scombridae 1 1 2 8 4 Serranidae 10 23 66 71 186 5 14 8 8 Unknown 3 21 23 192 1 7 6 Total 12 42 173 362 836 24 23 21 1493

Note that proatlas, atlas, antepenultimate, penultimate and ultimate are single elements useful for MNI calculations.

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Figure 1. Map of the South Pacific with Henderson Island (Pitcairn Group) and the location of site HEN-5.

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Figure 2. Articulated Acanthuridae (surgeonfish, Acanthurus lineatus) vertebral column with the eight vertebrae types marked. Note that proatlas, atlas, antepenultimate, penultimate and ultimate are single elements useful for MNI calculations.

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CHAPTER 4: Applications of vertebral morphometrics in Pacific Island archaeological fishing studies

Note: This is the final version of a peer-reviewed article published in Archaeology in Oceania.

Ariana B.J. Lambrides and Marshall I. Weisler

School of Social Science, The University of Queensland, St Lucia, Qld 4072 Australia.

Corresponding author: Ariana Lambrides, School of Social Science, The University of Queensland,

St Lucia, Qld 4072 Australia. Telephone: +61 7 3365 3038. Fax: +61 7 3365 1554. Email: [email protected]

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Applications of vertebral morphometrics in Pacific Island archaeological fishing studies

Abstract: Significant differences between fish bone identification protocols in Pacific Island archaeology and other regions (e.g., Europe and North America) have influenced the use of vertebral morphometrics for the reconstruction of fish length and weight. Fish vertebral morphometrics using vertebrae identified to taxon and type (e.g., caudal, thoracic) are routinely reported in the archaeological literature outside of the Pacific Islands. Conversely, in Pacific Island archaeological fishing studies, vertebrae that are not identified to taxon have been utilised to assess change in average fish vertebrae size, and to reconstruct changes in fish length and weight over time. Using a fish bone assemblage from a prehistoric habitation site on Ebon Atoll, Republic of the Marshall Islands, we report false trends when vertebrae—not identified to taxon and type—are used to assess differences in average vertebrae size among cultural layers. These results are compared to the same assemblage where taxon and vertebra type are used to more accurately determine fish size. It is essential that vertebrae from Pacific Island fish bone assemblages are identified to taxon and type prior to assessing change in fish size over time, especially when investigating human impacts to finfish resources, capture technology or charting environmental change.

Keywords: faunal analysis, fish vertebrae, morphometric measures, Marshall Islands, Pacific fishing

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Introduction

Protocols for archaeofaunal identifications and the subsequent quality of these analyses structure all inferences regarding prehistoric subsistence systems, diet, foraging patterns and human impacts to terrestrial and marine ecosystems. Fish bone identification protocols in Pacific Island archaeology are unique when compared to other regions (e.g., the United Kingdom (UK), Europe and North America) as only a restricted range of cranial elements, the so-called “five-paired cranial elements”— dentary, premaxilla, articular, quadrate and maxilla—and “special” or unique bones have been routinely used for taxonomic identification. More recently, Pacific Island faunal analysts have incorporated an expanded range of cranial elements, resulting in more complete determinations of species richness and diversity (e.g., Jones O’Day 2004; Vogel 2005; Walter 1998; Weisler and Green 2013; Weisler et al. 2010). The routine taxonomic identification of fish vertebrae is the latest advance in Pacific fishing studies (e.g., Lambrides and Weisler 2013; Ono and Clark 2012). Yet, in other regions, a wider range of cranial and post-cranial elements have been routinely incorporated into identification protocols for decades (e.g., Butler 1993; Colley 1984; Desse-Berset and Desse 1994; Joslin 2011; Morales 1984; Moss 2011; Robson et al. 2013; Van Neer 1986; Zohar et al. 2001).

The distinction between taxonomic identification protocols used in the Pacific Islands and other regions can be attributed to a few key reasons:

1. The emphasis outside of the Pacific Islands on identifying butchery and processing techniques, with element representation central to these analyses; for example, the removal of fish heads for preservation (Bruschi and Wilkens 1996; Carenti 2013; Desse-Berset 1993), the pickling of fish (Van Neer et al. 2007) or the use of cut mark morphology to determine the presence of stockfish (i.e., unsalted fish that were dried for preservation) (Brinkhuizen 1994; Cerón-Carrasco 1994).

2. The preservation of a restricted range of elements at certain sites, which has directed the development of taxonomic identification protocols specific to a region; for example, the frequent representation of salmon vertebrae from sites in the North American Pacific Northwest, which has resulted in the development of methods focused predominately on vertebrae for assessing human diet, site occupation and seasonality (e.g., Butler and Chatters 1994; Campbell and Butler 2010; Cannon 2000; Ewonus et al. 2011; Gobalet 2012; Gobalet et al. 2004; Moss 2011; Orchard and Szpak 2011).

3. The effectiveness of vertebrae for conducting seasonality studies through the establishment of age profiles and growth rates (e.g., Cannon 1988; Casteel 1976; Desse and Desse-Berset 1992; Grier et al. 2013; Van Neer et al. 1999, 2004).

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4. Finally, distinctions in regional methodologies can also be attributed to historical precedent, as disciplinary leaders (e.g., Casteel in the Pacific Northwest, Wheeler in the UK and Leach in the Pacific Islands) have advocated for variable fish bone taxonomic identification protocols, which has produced regional training legacies. This is evident in Pacific archaeology, where Leach (1986) advocated for the identification of the five-paired cranial elements and “special” bones to the exclusion of other bones, including most vertebrae.

Fish vertebral morphometrics are routinely reported in the archaeological fishing literature outside of the Pacific Islands, given the ubiquity of vertebrae in cultural deposits and their use for reconstructing fish length and weight based on specific measurements (e.g., Casteel 1976; Colley 1990; Desse and Desse-Berset 1996c; Enghoff 1994; Gabriel et al. 2012; Gobalet 1989; Huber et al. 2011). Yet, in Pacific Island archaeological fishing studies, vertebrae that are not identified to taxon, but rather to the category of “fish” or group (Osteichthyes), have been utilised to assess change in average fish vertebrae size, and reconstruct changes in fish length and weight over time (e.g., Jones 2009; Jones and Quinn 2009; Rolett 1998). This approach is argued to provide a cross-section of the sizes of fish represented in the archaeological deposit (following Newsom and Wing 2004: 52–3, 67–72). Rigorous protocols exist for the systematic application of vertebral morphometrics, but species-level identifications are often required to provide accurate fish size (weight and length) reconstructions. Given that some regions of the tropical Pacific have more than 3000 marine fish taxa, which is amongst the highest biodiversity in the world (Briggs 2005; Veron et al. 2009), reconstructive methods that require species- or genus-level identifications of vertebrae cannot always be directly applied to Pacific Island archaeological assemblages, where family-level identifications are more routine.

In this paper, we briefly review the global literature on fish vertebral morphometrics and contrast these methods with those applied to Pacific Island assemblages. Using a fish bone assemblage from Ebon Atoll, Republic of the Marshall Islands, we contrast three protocols that use fish vertebrae to estimate fish size: (1) all taxa and vertebrae types to simulate methods commonly used in Pacific Island archaeology; (2) controlling for the taxon (i.e., Scombridae, Scaridae and Carangidae) but including all vertebrae types as a single category; and (3) controlling for both taxon and vertebra type (i.e., caudal vertebrae from Scombridae only). We show that combining all vertebral measurements irrespective of taxon or vertebra type—a method routinely used in the Pacific Islands—can produce false trends. Differences in vertebrae size among cultural layers commonly associated with decreases in fish size over time in the Pacific fishing literature are more likely tracking alternative trends (e.g., change in species composition across cultural layers). We therefore suggest future research directions

108 for the systematic incorporation and development of vertebral morphometrics in Pacific Island archaeology.

Background

Global applications of vertebral morphometrics

Casteel (1974a, b, 1976) and Morales and Rosenlund (1979) provided systematic and replicable methods for measuring archaeological fish bones for reconstructing live fish weight and length. Since these pioneering works, pursuits have focused on refining approaches for assessing changes in fish populations over time, including seasonality, resource depression and changes in trophic structure (e.g., Desse and Desse-Berset 1996a, b; Gabriel et al. 2012; Leach et al. 1997a; Van Neer et al. 1993). Fishing studies outside of the Pacific Islands from the 1980s onwards routinely incorporated vertebral morphometrics using only those vertebrae identified to taxon and in some cases, most importantly, with type identified (i.e., atlas, caudal, precaudal etc.). Yet, these protocols were inconsistently applied across regions (i.e., variations in the taxonomic level vertebrae were identified prior to fish size reconstructions). For example, using an archaeological assemblage from Spain, Morales (1984: 53–6) acknowledged the variability of fish vertebrae along the vertebral column and recorded measurements of only those vertebrae that were identified to taxon and type prior to size reconstructions. Furthermore, Enghoff (1994), when investigating Danish fishing practices during the Ertebølle period, consistently measured only the first and second vertebrae of those identified to species to reconstruct fish size. In contrast, Gobalet (1989) identified minnows and carps (Cyprinid) to family and reconstructed fish size based on vertebral width measurements, without identifying vertebra type (see also Bertrando and McKenzie 2011; Broughton et al. 2000; Butler and Delacorte 2004; Zabilska 2013).

Nathalie Desse-Berset, George Desse and Jean Desse have each made exceptional contributions to the development and systematisation of archaeofish bone morphometrics and, of particular relevance here, vertebral morphometrics (e.g., Desse 1984; Desse and Desse 1983; Desse and Desse-Berset 1992, 1993, 1997, 1999b, 2000; Desse-Berset 1997, 2011). Desse and Desse-Berset (1996c) argued that vertebrae should be identified to species with vertebra type and position on the vertebral column known (i.e., first thoracic, tenth caudal) prior to making allometric reconstructions of weight and length. Desse and Desse-Berset (1989, 1994, 1999a) also developed the “Global Rachidian Profiles” (GRP) method, which maximised the calculation of the minimum number of individuals (MNI) values and size reconstructions based on vertebral morphometrics. Determining the exact position of vertebrae along the vertebral column is critical to the application of the GRP method. More recently, Radu et al. (2008: 361–2) applied the GRP method at Tappeh Hessar (Damghan, Iran) and using 29

109 cyprinid vertebrae were able to isolate small (174–250 mm) and large (400–500 mm) individuals based on fork length measurements (see also Clavel and Arbogast 2007). While Radu et al. (2008) only completed family-level identifications of the archaeological vertebrae, Desse and Desse-Berset (1996b: 176) argue for what they term “taxonomic proximity”, as “the relationship estimated between various bone measurements and fish length, is a general one for the species, often valid for the genus and, occasionally, for a whole family as well”. The GRP method is an improvement on earlier approaches in the Pacific Islands that utilised morphometrics of unidentified fish vertebrae, and by considering only measurements of identified vertebrae, it can provide coarse-grained reconstructions of fish size; for this reason, it should be considered by researchers working in the Pacific Islands.

It is critical that the exact position of each vertebra along the vertebral column be determined prior to reconstructions of fish length and weight (e.g., Desse and Desse-Berset 1989, 1999a). Gabriel et al. (2012) investigated meagre (Argyrosomus regius), a taxon common in many archaeological sites in Portugal, Spain, Greece, the eastern Mediterranean, Mauritania and the North Sea. Extensive identification criteria were provided to ensure that each meagre vertebra could be distinguished along the vertebral column and the appropriate regression equation was applied to reconstruct total length (TL) (Gabriel et al. 2012: table 1). Furthermore, Ritchie (2010: 177) measured the width of the posterior centrum of all atlas vertebrae identified to species to calculate weight and length determinations (see also Carder and Crock 2012; Carder et al. 2007; Orchard 2003). In contrast, Pletka (2011: 154) incorporated all “caudal” vertebrae measurements and did not determine the exact position along the vertebral column; however, statistical protocols were implemented to distinguish vertebrae from separate individuals (see also LeFebvre 2007).

At a number of Pacific Northwest sites, the ubiquity of salmon (Oncorhynchus spp.) vertebrae has provided the opportunity to develop innovative methods for obtaining high-resolution data from the analysis of vertebrae. Discussion has focused on methods for completing species-level identifications of salmon, critical for reconstructions of diet, site use, seasonality studies, and conservation and management practices (e.g., Gobalet 2012). Radiographic analysis, once used for identifications of salmon vertebrae (Cannon 1988), has been shown to be of limited use (Cannon and Yang 2006: 128). Subsequently, Huber et al. (2011) developed a method for making species-level identifications of salmon using vertebral morphometrics (for application of the identification protocol, see Lubinski and Partlow 2012). While aDNA has been successfully extracted to identify Pacific Northwest archaeological assemblages of salmon vertebrae, its application is often limited to small samples due to cost (Butler and Bowers 1998; Cannon and Yang 2006; Ewonus et al. 2011; Grier et al. 2013; Kemp et al. 2014; Moss et al. 2014; Speller et al. 2005; Yang et al. 2004; for related work on herring DNA, see also McKechnie et al. 2014; Speller et al. 2012). According to Moss et al. (2014), aDNA

110 methods still appear to be the most accurate method of identifying salmon vertebrae to species, with the morphometrics protocols of Huber et al. (2011) requiring further refinement. Given the difficulties of species-level identifications in the Pacific Islands, a combination of morphometrics and aDNA or peptide mass fingerprinting may be required to confidently implement fish size reconstructions (Richter et al. 2011).

Pacific Island fishing studies and vertebral morphometrics

Although not widely adopted in the tropical Pacific Islands, morphometric analysis of cranial elements in temperate New Zealand is more routine, particularly measurements of the five-paired cranial elements as well as key “special” bones, such as the upper and lower pharyngeal grinding plates of parrotfish (Scaridae) and wrasse (Labridae). New Zealand has a greatly reduced marine biodiversity compared to the subtropical and tropical Pacific Islands, where the species richness of ichthyofauna hinders species-level identifications that are ideal for accurate size reconstructions (e.g., Leach and Boocock 1994, 1995; Leach and Davidson 2000; Leach et al. 1997a,c, 1999a,b,c). However, these methods have been applied in other regions of the Pacific Islands (e.g., Fraser 1998; Leach et al. 1997b; Masse et al. 2006; Ono and Clark 2012; Weisler 2004).

There has been limited application of vertebral morphometrics in Pacific Island archaeology. Commonly, maximum width measurements of unidentified vertebrae are used to document vertebrae size and then to infer fish size changes over time (Jones O’Day 2001; Rolett 1998: 142; Weisler et al. 2010: 139–40). Conversely, Jones and Quinn (2009: 2745) measured the anterior width of unidentified vertebrae and reconstructed average weight, as “this procedure is based on the assumption that the fish vertebrae represent a cross-section of the species present in the assemblage”. This method was adapted from Wing (2001: 116–7) and Newsom and Wing (2004: 68–71) for application in the Caribbean based on a known allometric formula (log Y = 2.53(log X) + 0.872, where Y is the body weight and X is the vertebral width) developed using local fish species. The use of this allometric formula for Pacific Island archaeological assemblages is problematic, given that a unique regression equation is required for each vertebra along the vertebral column for every identified taxon (Gabriel et al. 2012; Seymour 2004).

These protocols have been acknowledged as coarse-grained (Weisler et al. 2010: 139–40), as the inclusion of unidentified elements can not only create false trends but also mask actual trends in the size of fish taxa over time. These approaches do not place sufficient focus on individual variation (at the family, genus and species level), sexual dimorphism and ecological factors that can influence growth rates and sizes (e.g., Robertson 1998). For example, male Mediterranean rainbow wrasse (Colis julis) are larger than females of the same age due to their sequential hermaphroditism;

111 specifically, the fish that change sex are already the larger individuals in their age group and a growth spurt also occurs after the sex change (Linde et al. 2011). Ecological factors can also affect fish growth rate, with research on the bicolour damselfish (Stegastes partitus) suggesting that temperature shapes growth-related traits and can influence the intensity of selective mortality (Rankin and Sponaugle 2011). For these reasons, it is critical that an extensive fish reference collection be available for morphometrics; ideally, this would include male and female specimens of a variety of ages and also captured from variable ecological zones (e.g., juvenile fish from sheltered habitats such as mangrove forests and seagrass beds and adults from exposed coral reefs). Furthermore, issues of bone preservation must be considered, including bone structure, processing, ingestion, weathering and dissolution (Gabriel et al. 2012: 2864).

Given the influence of ontogenic growth and depositional and post-depositional taphonomic factors, it is critical that elements are identified to taxon prior to assessing changes in fish populations over time. For these reasons, Ono and Intoh (2011: 267) measured the width of identified tuna, bonito and mackerel (Scombridae) vertebrae only, but as only family-level identifications were possible, size reconstructions were not completed. The most comprehensive application of vertebral morphometrics in Pacific Island archaeology using identified vertebrae was conducted by Fraser (1998: 131–4), who used only the ultimate vertebra of Scombridae to reconstruct live fork length (FL) (see also Leach et al. 1997b). The importance of species-level identifications for the improvement of osteometric reconstructions was emphasised by Fraser (1998), as only family-level identifications were implemented in the study. Critically, Fraser (1998) considered change in reconstructed fork length (as determined by ultimate vertebrae measurements) to evaluate change over time rather than analysing change using the raw measurement data (but see Jones and Kirch 2007; Jones O’Day 2001; Rolett 1998). According to Gabriel et al. (2012: 2862–4), there is substantial variability in the relationship between bone size and fish size, and as such comprehensive reference collections that represent a variety of growth stages/age, sex and capture environments are required to develop “mathematical models that explicitly account for such variability” and will facilitate reconstructions of fish length and weight and assessments of change.

Methods are required that allow broad trends to be investigated if position along the vertebral column cannot be consistently determined for all taxa. For example, the average number of vertebrae varies between 31 and 66 for Scombridae and of that total, an average of 20 + are caudal vertebrae. In such cases it can be difficult to determine the precise location along the vertebral column. This issue is compounded by the often poor preservation of Scombridae remains in Pacific Island archaeological fish bone assemblages. Alternatively, the use of only those vertebrae types that can be confidently

112 identified to a position on the vertebral column due to unique morphology may be necessary, such as proatlas, atlas, antepenultimate, penultimate and ultimate.

It has been demonstrated that fish vertebrae identified to taxon are routinely used for fish size reconstructions outside of the Pacific Islands and it is critical that Pacific Island vertebral morphometrics adopt similar protocols.

Case Study

Comprising 29 coral atolls and five limestone islands without a lagoon, the Republic of the Marshall Islands (RMI) has a total land area of 181 km2, spread over 2000000 km2 of ocean in eastern Micronesia, and is situated 3850 km south-west of Hawai‘i. Ebon Atoll (4°38′24.67″N, 168°42′23.56″E) is the southernmost atoll in the Marshall Islands and has 22 islets, with a total land area of 5.75 km2, surrounding a 104 km2 lagoon (Figure 1). Prehistoric village sites in the RMI are generally located parallel to the lagoon shoreline and characterised by surface and subsurface deposits of marine shellfish, fish bone, shell artefacts and coral gravel pavements. Aroid pit systems, for the cultivation of giant swamp taro (Cytosperma sp.), are often located at the inland extent of habitation zones, near the centre of larger islets (Weisler 1999, 2001). Site MLEb-1 is situated 25 to 200 m from the lagoon beach and, along with other habitation sites, forms a near-continuous∼ site that parallels the islet for nearly 2 km. A 2 × 2 m unit (TP 17, 18, 19 and 20, each 1 m2) was excavated just back from the lagoon beach. Cultural deposits were encountered to a depth of 1.75 m (Weisler 1999: fig. 4; Weisler 2002: 20). The stratigraphy was divided into three main prehistoric layers, capped by thin 4 cm thick relatively sterile beach sand with historical artefacts and midden. Layer

I is a black (Munsell∼ 5Y2.5/1, taken moist in shade) gravelly sand with dense prehistoric midden and humanly transported gravel spread for village pavements. This layer was further divided into an upper layer IA, which was slightly darker and compact than IB. These combined layers were 60 cm thick.

Layer II, which was also divided into an upper IIA and lower IIB based on increasing∼ sand and mottled pockets with depth, is a very dark grey (5Y3/1) sandy gravel midden with a combined thickness of 118 cm. Layer IIIA consists of grey (5Y5/1) sand that is almost completely sterile. This overlies palaeo∼ -beach deposits of coarse sand and coral chunks to 190 cm below surface. The densest fish bone recovered during the 2011/2012 field season was in ∼the 2 × 2 m unit, so it was the most suitable for the application of morphometrics. The fish bone concentration index was 6782 bones per m3 (6.4 mm and 3.2 mm combined).

Materials and Methods

Taxonomic identifications

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The following analyses are based on the fish bone retained from the 6.4 mm sieves from the 2 × 2 m unit (total volume of excavated cultural layers = 4.1 m3) from site MLEb-1, Ebon Islet and the 3.2 mm material retained from TP 17 (total volume of excavated cultural layers = 1 m3). Only TP 17 was sampled using 3.2 mm sieves, due to time constraints on the fieldwork. Wet-sieving was consistently used during the excavations for all deposits. Faunal remains were sorted into major categories: fish, rat, bird, other vertebrates (e.g., sea turtle, lizard, dog etc.) and shell; only fish bone is discussed here.

Fish remains were identified by Lambrides to the lowest taxonomic level, however, only the vertebrae are relevant to this paper. Identifications are presented to family level only, for ease of comparison between datasets and to effectively demonstrate the implications of utilising unidentified vertebrae for size reconstructions of an assemblage; more specific taxonomic identifications are required for accurate fish size reconstructions. Taxonomic identifications were completed using comparative collections held by Weisler (2001: appendix 3) at the University of Queensland, including additional specimens added to the collection over the past decade. The Pacific Islands fish reference collection currently comprises 45 families, 93 genera and 168 species. The number of individuals represented in the collection for a given species ranges from 1 to 20; on average there are 2–3 individuals for a given species. In the comparative collection there is a good representation of fish size, geographical variability (e.g., Hawai‘i, Marshall Islands, Pitcairn Group etc.), ecological variability and capture technique. There are targeted efforts to expand the comparative collection and improve the representation of species, sex and size.

Definitions of vertebral types were adapted from Casteel (1976: 77–8) and include the following: (1) proatlas, the vertebral face on the posterior end of the basioccipital; (2) atlas, the vertebra immediately posterior to the proatlas; (3) thoracic, those vertebrae with a fused neural spine and usually lacking haemal spines (cf. Acanthuridae); (4) precaudal, those vertebrae with a fused neural spine and with well-developed parapophyses; (5) caudal, those vertebrae with fused neural and haemal arches; (6) antepenultimate—this vertebra is known in the ichthyology literature as the last caudal vertebra and is immediately anterior to the penultimate vertebra, and it was incorporated due to observed variation between reference specimens (Lambrides and Weisler 2013); (7) penultimate, the vertebra (in most cases) lacking a permanently attached haemal spine, and posterior to the antepenultimate and immediately anterior to the ultimate vertebra; and (8) ultimate, the last vertebra along the vertebral column, also defined as the urostyle. Figure 2 illustrates the individual characteristics of each vertebra type, but also see Lambrides and Weisler (2013: fig. 2) for an articulated vertebral column with the eight types marked.

All vertebrae were considered for identification based on protocols outlined in Lambrides and Weisler (2013), with the exception of those identified as fragmented. Fragmentation (defined as < 50% of an 114 individual vertebra) was quantified for all vertebrae. Fragmented vertebrae could not be assigned to a specific type (e.g., atlas, thoracic, caudal etc.) and identified to taxon. The proatlas (basioccipital), atlas, antepenultimate, penultimate and ultimate can be particularly useful for vertebral morphometrics, as their position on the vertebral column can be accurately determined. Only the number of identified specimens (NISP) was calculated for each taxon and used to complete the morphometric analyses to assess differences among cultural layers.

Morphometric protocols

For each archaeological vertebra, three measurements were recorded to the nearest 0.01 mm using digital calipers (Mitutoyu Digimatic). Recorded measurements of the anterior centrum face include the maximum dorso-ventral height of the centrum (M1) and the maximum mediolateral width of the centrum (M2). The maximum craniocaudal length of the centrum (M3) was also recorded. Only M1 and M2 could be measured on the ultimate vertebra (or urostyle) (after Desse and Desse-Berset 1996a; Gabriel et al. 2012) (Figure 3). M1, M2 and M3 were each measured three times, and the mean of each of the three measurements was used for the analysis and to address measurement error. Given the high correlation between measurements on the same fish bone (Desse and Desse-Berset 1996b: 172), in future it may not be necessary to measure M1, M2 and M3 for each archaeological vertebra. However, relationships between fish size (length and weight) and bone size (M1, M2 and M3) should be developed for each taxon based on reference specimen metrics (e.g., Gabriel et al. 2012: table 12) to increase the likelihood that a measurement can be recorded (M1, M2 or M3) given the influence of pre- and post-deposition alterations to bone (e.g., fragmentation, dissolution, processing etc.). All statistical analyses were run using IBM SPSS Statistics Desktop 20.0 and Past version 3.2.

Results

The fish vertebrae remains of MLEb-1 (TP17, 18, 19 and 20)

Rank order abundance, taxonomic diversity and evenness (6.4 mm and 3.2 mm)

A total of 10245 (6.4 mm) and 17559 (3.2 mm) fish bones was recovered from a 2 × 2 m unit from site MLEb-1. The assemblage recovered from the 6.4 mm sieves comprised (including fragments) weighing 475 g; this is compared to the material recovered from the finer mesh sieves (3.2 mm) with 15115 non-vertebrae weighing 357 g and 2444 vertebrae (including fragments) weighing 77 g. Of all vertebrae, 35% (6.4 mm) and 58% (3.2 mm) were identified as fragmented. A high proportion of the archaeological vertebrae were identified to taxon: 63% (6.4 mm) and 40% (3.2 mm).

Table 1 lists key distinctions in rank order abundance between the two recovery methods as determined by the identification of vertebrae (6.4 mm and 3.2 mm), with data aggregated from all

115 test pits of the 2 × 2 m unit. The most abundant taxa by NISP for the 6.4 mm sieves were tuna, mackerel and bonito (Scombridae), parrotfish (Scaridae), jack (Carangidae) and grouper (Serranidae). Based solely on the material recovered from the 3.2 mm sieves (TP 17), flying fish (Exocoetidae, NISP = 252) were the top-ranked taxon and mojarras (Gerreidae) were added to the taxonomic list (Figure 4).

Taxonomic evenness was determined using the complement of Simpson’s index (1 – D) and the Shannon–Weiner indices of diversity (H′) and evenness (e = H’/ln S) (Hayek and Buzas 2010; Lyman 2008; Magurran 2004). Values of 1 – D range from 0 to 1, with higher values suggesting that the assemblage is more even and not dominated by a single taxon. The Shannon–Weiner index of diversity tends to vary between 1.5 and 3.5, with higher values indicating greater heterogeneity in a faunal assemblage; however, these values can be affected by sample size (Lyman 2008: 192). Finally, the Shannon–Weiner index of evenness ranges from 0 to 1, with a value of 1 suggesting that all taxa are equally abundant. These measures of diversity and evenness were considered for the entire fish bone assemblage from the 2 × 2 m unit (both 6.4 mm and 3.2 mm) to assess the entire assemblage irrespective of cultural layer. It was determined that the assemblage was diverse or heterogeneous (H′= 2.734), but also very even, with both many taxa represented and many individuals from each taxon (1 – D = 0.915; H′/ln S = 0.849). This is significant as one taxon is not dominating the archaeological fish bone assemblage from the site, when compared to sites from other regions that are dominated by a single taxon or few taxa, such as the high abundance of salmon remains in the Pacific Northwest (Moss 2012), carp in Hungary (Bartosiewicz et al. 1994: 55), or snapper and barracouta in many South Island, New Zealand sites (Leach and Boocock 1995; Leach et al. 1999c). This may have implications for the application of morphometrics to tropical and subtropical Pacific Island assemblages, as a statistically meaningful sample size is critical for assessing change in fish assemblages over time.

Vertebral morphometrics

Sieve size and vertebral morphometrics

Figure 5 illustrates the distribution of the maximum mediolateral widths of the centrum (M2) for all vertebrae types recovered from the 6.4 mm and 3.2 mm sieves; of the identified vertebrae, it was not possible to measure M2 (n = 2436) for 183 specimens. The mean maximum width of the 6.4 mm vertebrae is 6.58 ± 2.76 mm (range = 1.07–30.89 mm) and the 3.2 mm mean maximum width is reported as 3.47 ± 0.98 mm (range = 1.44–6.95 mm). It is evident that finer mesh sizes (i.e., ≤ 6.4 mm) are critical for determining variation in vertebrae size and to accurately represent the contribution of each size category in the archaeological assemblage. As all cultural layers of the 2 ×

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2 m unit were systematically sampled with 6.4 mm sieves, this larger assemblage was used for vertebral morphometrics.

Impact of data resolution

The following section demonstrates the importance of determining taxon, vertebra type and position along the vertebral column prior to conducting vertebral morphometrics and assessing temporal changes in fish size. Prior to exploratory data analyses, initial data analysis was implemented to ensure that all statistical assumptions were met. Datasets were each examined for normality (skewness and kurtosis). As the data was not normally distributed, non-parametric statistics (i.e., Kruskal–Wallis one-way analysis of variance and effect size) were used. A key assumption of Kruskal–Wallis is that homogeneity of variances is met; this assumption was tested and not violated for any of the tested datasets. An effect size (η2) was also calculated to assess the magnitude of the difference between groups based on the sorting variable (i.e., taxon or vertebra type). Post hoc tests were not run, as it was not necessary to determine pairwise differences (i.e., follow up tests between pairs of groups, often using Mann–Whitney U tests) or if there was temporal ordering to the differences, as change over time in fish populations was not being tested. Rather, it was an attempt to track the presence of trends as they relate to data resolution and demonstrate the problems of considering unidentified vertebrae.

All taxa and all vertebrae types: The analysis of all vertebrae types and taxa combined provided a proxy for methods applied in Pacific Island archaeology; that is, the measurement of unidentified vertebrae that, irrespective of type, are collapsed into a single category for analysing change over time in fish size. In the Pacific fishing literature only descriptive statistics (e.g., range, mean and standard deviation) are used to assess changes in average vertebrae size over time. A general decrease in M1, M2 and M3 vertebrae measurements over time (cultural layers: IIIA to Historical) is evident when analysis is restricted to descriptive statistics (Table 2 and Figure 6). A Kruskal–Wallis test was conducted to evaluate differences among the six cultural layers (Historical, IA, IB, IIA, IIB and IIIA) on median change in vertebrae measurements (M1, M2 and M3) (i.e., are there statistically significant differences in M1, M2 and M3 vertebrae measurements between cultural layers?). Each test was significant: M1, χ2(5, N = 1478) = 114.09, p ≤ 0.0005; M2, χ2(5, N = 1479) = 133.68, p ≤ 0.0005; M3, χ2 (5, N = 1415) = 100.84, p ≤ 0.0005, but with comparatively low effect sizes – M1, η2 = 0.08; M2, η2 = 0.09; M3, η2 = 0.07.

Individual taxon and all vertebrae types: A comparison of datasets where the taxon was known but all vertebrae types were grouped as a single “uniform” category was completed. The three top-ranked taxa (Scombridae, Scaridae and Carangidae) as determined by NISP were used to provide examples

117 of this approach (Table 3 and Figure 7). Kruskal–Wallis tests were conducted to evaluate differences among the six cultural layers (Historical, IA, IB, IIA, IIB and IIIA) on median change in vertebrae measurements (M1, M2 and M3), but controlling for taxon (i.e., Scombridae, Scaridae and Carangidae). The tests for each taxon provided variable outcomes across the three measurements. For Scombridae, only M2 and M3 were significantly different based on median change among cultural layers: M1, χ2(4, N = 364) = 6.91, p = 0.141; M2, χ2(4, N = 366) = 15.26, p = 0.004; M3, χ2(4, N = 355) = 14.36, p = 0.006, with low effect sizes – M1, η2 = 0.019; M2, η2 = 0.042; M3, η2 = 0.041. For Scaridae, only M1 and M3 were significantly different based on median change among cultural layers: M1, χ2(4, N = 210) = 10.12, p = 0.039; M2, χ2(4, N = 210) = 9.40, p = 0.052; M3, χ2(4, N = 201) = 12.91, p = 0.012, with low effect sizes – M1, η2 = 0.048; M2, η2 = 0.045; M3, η2 = 0.065. Finally, for Carangidae, only M1 was significantly different based on median change among cultural layers: M1, χ2(3, N = 134) = 10.83, p = 0.013; M2, χ2(3, N = 133) = 7.72, p = 0.052; M3, χ2(3, N = 127) = 5.00, p = 0.172, with small effect sizes – M1, η2 = 0.081; M2, η2 = 0.058; M3, η2 = 0.040. The variability in the outcomes of the Kruskal–Wallis tests for each taxon based on the measurements recorded (M1, M2 and M3) is problematic, as theoretically each of the measurements should correlate well with live fish size and should be tracking similar trends. While the M1, M2 and M3 measures for each taxon are correlated (p ≤ 0.05), there is variation in the r2 values, which we suggest relates to the error introduced by grouping non-congruent variables: (1) family, genera and species; and (2) all vertebrae irrespective of type.

Individual taxon and individual vertebra type: The final stage of analysis controlled for taxon and vertebra type. Scombridae was the top-ranked taxon and Scombridae caudal vertebrae were the most abundant by NISP (Table 4 and Figure 8). The genera present among the Scombrids are all tribe Thunnini: cf. Katsuwonus sp. (skipjack) and Thunnus spp. (Marshall Islands: albacore, bigeye, Pacific bluefin and yellowfin). Ideally, the proatlas (NISP = 0), atlas (NISP = 4), antepenultimate (NISP = 8), penultimate (NISP = 6) or ultimate vertebra (NISP = 11) would have been used for this analysis, given the importance of determining position along the vertebral column prior to size reconstructions. However, due to small sample sizes across all cultural layers and the difficulty in determining the position along the vertebral column for Scombridae caudal vertebrae, the type was grouped to provide coarse-grained outcomes. Yet, this approach is appropriate for analysing the implications of considering a single vertebra type, which is necessary for this study. Kruskal–Wallis tests were conducted to evaluate differences among the five cultural layers that had Scombridae (IA, IB, IIA, IIB and IIIA) on median change in vertebrae measurements (M1, M2 and M3), but testing for the impact of controlling taxon and vertebra type. No tests were statistically significant: M1, χ2(4, N = 213) = 2.48, p = 0.649; M2, χ2(4, N = 213) = 7.35, p = 0.119; M3, χ2(4, N = 215) = 6.22, p = 0.184,

118 with low effect size – M1, η2 = 0.012; M2, η2 = 0.035; M3, η2 = 0.030. Therefore, there is no evidence based on key measurements of Scombridae caudal vertebrae that there is a statistically significant difference in vertebrae size among cultural layers.

Importantly, the successive refinement in analytical protocols when controlling for taxon and type resulted in a reduction in sample size. To determine whether sample size was sufficient to detect such a small effect when controlling for taxon and type (i.e., Scombridae caudal vertebrae) subsampling procedures were implemented. First, using the dataset that contained all vertebrae irrespective of taxon and type, we randomly drew specimens until the sample size was equivalent to the subset, which controlled for taxon and type. For example, from the original dataset of M1 measurements (Table 2), 98 specimens were randomly sampled from Layer IA, 28 from Layer IB, 23 from Layer IIA, 62 from Layer IIB and 2 from Layer IIIA, which is equivalent to the sample size of measured Scombrid caudal vertebrae (Table 4). This process was repeated 1000 times. The Kruskal–Wallis test was then run on each of the subsampled assemblages to verify if it is possible to detect such a small effect (i.e., statistically significant outcome) with reduced sample sizes. For each analysis (or Kruskal–Wallis test of the subsampled population), the outcome was still highly significant (p ≤ 0.0005). This suggests that the reduction in sample size does not explain why we fail to get a significant result when we control for taxon and type.

An application of the “Global Rachidian Profiles” method: The “Global Rachidian Profiles” (GRP) method proposed by Desse and Desse-Berset (1989, 1999a) maximises the calculation of MNI and, relevant here, size reconstructions based on vertebral morphometrics. Further analysis of the GRP method may provide a more useful approach for incorporating vertebral morphometrics into Pacific Island fishing studies. The archaeological assemblage of Selar spp. (Carangidae) from the 2 × 2 m unit was used to provide an example of the GRP approach. There are two species of Selar found in the Marshall Islands, bigeye scad (S. crumenophthalmus) and oxeye scad (S. boops). Figure 9 provides an example of the GRP method for a bigeye scad reference specimen (no. 325) graphed using the M1, M2 and M3 measurements (S. boops is not represented in the comparative collection).

Based on determinations of standard deviation (σ) and the coefficient of variation (Cv) for each of the three measurements (M1, M2 or M3), the most suitable was used to predict the fork length of measured Selar spp. archaeological vertebrae. Ideally, the recorded measurement (M1, M2 or M3) with the least deviation from the mean—this can be supported by graphing the measurements—will be used to examine the archaeological vertebrae. In this example, M1 was determined as the most suitable measurement to analyse the archaeological vertebrae and predict fork length (no. 325, σ =

0.501; Cv = 0.095; no. 406, σ = 0.384; Cv = 0.091). The archaeological vertebral measurements (M1) recorded for Selar spp. were plotted over the equivalent vertebra type (i.e., T1 = first thoracic, P2 =

119 second precaudal, C7 = seventh caudal etc.) as determined by measurements of vertebrae from reference specimens with known length measurements (in this case, fork length) (Figure 9). Therefore, the archaeological Selar spp. vertebrae probably derived from specimens that range between 23 and 29 cm in fork length with a few outliers; this example was grouped at the level of TP, so change over time cannot be assessed.

Discussion

Data resolution and vertebral morphometrics in Pacific Island archaeology

Analyses were completed to document the implications of controlling for taxon and vertebra type when investigating changes in vertebrae size over time. These were as follows: (1) all taxa and vertebrae types to simulate methods commonly used in Pacific Island archaeology, (2) controlling for the taxon (i.e., Scombridae, Scaridae and Carangidae) but including all vertebrae types as a single category; and (3) controlling for both taxon and vertebra type (i.e., Scombridae caudal vertebrae only).

When all vertebrae were considered together, irrespective of taxon and vertebra type, the results of the Kruskal–Wallis test were statistically significant for each of the three measurements (M1, M2 and M3), suggesting that there are differences in vertebrae size among the groups (i.e., cultural layers); however, post hoc tests are required to determine whether there is temporal ordering to these differences. As the taxonomic composition of the sample and variation in vertebral morphometry were increasingly controlled for, the outcomes of the analyses became increasingly variable. When evaluating the three top-ranked taxa according to NISP—Scombridae, Serranidae and Carangidae— the outcomes of the Kruskal–Wallis tests were inconsistent with comparatively low effect size determinations, indicating a relatively low magnitude of difference between the cultural layers based on each measurement (M1, M2 and M3). Finally, when only a single vertebra type for a taxon was evaluated (i.e., Scombridae caudal vertebrae), there was no observed variation among cultural layers for the key vertebrae measurements (M1, M2 and M3).

The comparison between these three datasets highlights the importance of identifying the exact position of a vertebra on the vertebral column prior to reconstructions of fish size (Desse and Desse- Berset 1996c; Gabriel et al. 2012). In the case of Scombridae, it is often difficult to distinguish caudal from precaudal archaeological vertebrae due to preservation, let alone determine position of an individual caudal vertebra along the vertebral column. There was not a sufficient sample of the other vertebrae types (i.e., atlas, penultimate etc.) to track change in vertebrae size among cultural layers for an individual vertebra type. This analysis has demonstrated that it is problematic to use unidentified fish vertebrae for assessing changes in fish size over time, as it is possible to document 120 false trends using a method that is routinely used in the Pacific Islands (e.g., Jones and Quinn 2009; Jones O’Day 2001; Rolett 1998). This issue is enhanced in Pacific Island archaeology due to the number of taxa represented in archaeological fish bone assemblages and the need for comprehensive reference collections to facilitate species-level identifications. These approaches have been acknowledged as “coarse-grained”, but we suggest that it is better to exclude measurements of unidentified vertebrae if taxonomic identifications cannot be made.

Methods for reconstructing fish size based on vertebral morphometrics require species-level identifications, which is difficult given the high biodiversity of fish in the tropical Pacific Islands. Desse and Desse-Berset (1996b: 176) argue for “taxonomic proximity”, where relationships between a bone measurement and fish length are generally consistent for the species, and often (cautiously) applicable to the genus and family. Therefore, a method of vertebral morphometrics is required that can be applied to Pacific Island fish bone assemblages even when species-level identifications are not possible. The GRP method can provide “coarse-grained” reconstructions of fish length based on vertebral measurements. In this example, only two reference specimens were considered (nos. 325 and 406) for comparison with the archaeological vertebrae; however, the inclusion of more reference specimens will improve the accuracy of archaeological fish length predictions by accounting for intra- taxonomic variation (e.g., age, sex etc.) (Bartosiewicz and Takács 1997).

Conclusions

Outside of the Pacific Islands, unidentified vertebrae are rarely used for fish size reconstructions. Unidentified vertebrae have been utilised only as an adjunct to data obtained from identified vertebrae to provide a coarse-grained method of assessing change over time (e.g., LeFebvre 2007; Newsom and Wing 2004; Wing 2001). Prior to reconstructions of fish length and weight: (1) all vertebrae should be identified to taxon and assigned to type; and (2) the exact position on the vertebral column should be determined. This ensures that any changes in reconstructed fish size are identified using a specific vertebra type. Consequently, variability across a vertebra type (i.e., thoracic, precaudal and caudal) is not influencing trends. As previously discussed, certain vertebra types are easier to identify (i.e., accurately determine their position on the vertebral column), thereby enhancing their utility for size reconstructions (i.e., proatlas, atlas, antepenultimate, penultimate and ultimate).

Species-level identifications are preferable but, in regions with high biodiversity, even genus-level identifications can be difficult with extensive comparative collections. For archaeological fish bone assemblages that are taxonomically rich, such as the Pacific Islands, or where species-level identifications are critical (e.g., the Pacific Northwest), a combination of approaches may be necessary, such as aDNA analysis/peptide mass fingerprinting and morphometrics. We encourage

121 archaeologists working in the Pacific Islands to continue developing and implementing methods for identifying fish bone to species (e.g., aDNA analysis: Nicholls et al. 2003) to ensure high-resolution assessments of both temporal change in fish size and the contribution of finfish to prehistoric diet. Ideally, the protocols used by Gabriel et al. (2012) are the optimum and while we currently do not have the ability to replicate this study in the tropical Pacific, it should be the objective of future research. However, the GRP method does produce “coarse-grained” reconstructions of fish length, which are more useful for assessing changes in fish size over time than an analysis of unidentified vertebrae.

In this paper, we have demonstrated that false trends can be produced when unidentified vertebrae are measured to infer changes in fish size among cultural layers, which is a method routinely used in Pacific Island archaeology. Differences in vertebrae size across cultural layers commonly associated with decreases in fish size over time in the Pacific fishing literature are more likely to be tracking alternative trends (e.g., change in species composition across cultural layers). It is hoped that future collaboration between researchers will enhance these methods through the development of an open source database where morphometric data from modern comparative collections can be shared. Finally, it is important to acknowledge the limitations of morphometrics: (1) adequate samples of archaeological vertebrae are required for assessing fish or vertebrae size over time; and (2) a comprehensive comparative collection—with multiple specimens of each species representing a variety of ages and sex—is essential for size reconstructions. It is possible that vertebral morphometrics will not be suitable for all regions and archaeological assemblages. However, a clear rationale for its use should be made in addition to presenting a detailed account of the methods of measurement and the quality of the reference collection for conducting the fish size reconstructions.

Acknowledgements

Permission to conduct archaeological research in the Republic of the Marshall Islands was granted to Weisler by the Historic Preservation Office, Ministry of Internal Affairs and on Ebon Atoll, former mayor Lajan Kabua. The Marshall Islands fieldwork was supported by a grant to Weisler from the Office of the Deputy Vice Chancellor (Research), University of Queensland. Lambrides’ postgraduate studies are supported by an Australian Postgraduate Award. We thank the peer reviewers for their suggestions, Tyler Faith for comments on an earlier version of this paper, and Matthew Harris for the preparation of the figures.

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Table 1. (a) The rank order abundance of fish taxa from site MLEb-1, TP17, 18, 19 and 20 (aggregated by test pit). Identifications are family-level only and represent the vertebrae remains recovered from the 6.4 mm sieves. A total of 37% of all vertebrae were unidentified. (b) Rank order abundance of fish taxa from site MLEb-1, TP17 (aggregated by test pit). Identifications are presented to family- level and represent the vertebrae remains recovered from the 3.2 mm sieves. Some 60% of all vertebrae were unidentified.

(a) (b)

Taxon NISP Taxon NISP Scombridae 440 Exocoetidae 252 Scaridae 228 Serranidae 102 Carangidae 169 Carangidae 74 Serranidae 160 Lutjanidae 61 Siganidae 84 Holocentridae 59 Acanthuridae 81 Lethrinidae 58 Lutjanidae 76 Mullidae 54 Lethrinidae 62 Acanthuridae 53 Mullidae 62 Belonidae 42 Kyphosidae 58 Cirrhitidae 38 Balistidae 54 Muraenidae 27 Exocoetidae 51 Bothidae 26 Labridae 24 Kyphosidae 22 Holocentridae 21 Balistidae 15 Bothidae 15 Kuhliidae 15 Fistulariidae 10 Scaridae 13 Sphyraenidae 10 Scombridae 13 Chaetodontidae 9 Pomacentridae 12 Belonidae 8 Siganidae 10 Mugilidae 6 Fistulariidae 7 Cirrhitidae 5 Gerreidae 6 Kuhliidae 4 Labridae 6 Pomacentridae 4 Mugilidae 5 Muraenidae 3 Chaetodontidae 4 Total 1644 Sphyraenidae 1 Total 975

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Table 2. Vertebral measurements (mm) (M1, M2 and M3) with all identified taxa and vertebrae types grouped from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

Layer n Mean (mm) Range ± s.d. (σ) (mm) M1 M2 M3 M1 M2 M3 M1 M2 M3 Historical 55 55 52 4.88 5.11 6.16 2.24 - 8.28 ± 1.59 2.28 - 8.90 ± 1.75 3.44 - 10.24 ± 1.76 IA 1072 1070 1025 5.94 6.35 7.21 0.82 - 24.16 ± 2.41 1.07 - 30.89 ± 2.67 0.84 - 36.55 ± 2.89 IB 167 167 158 5.69 6.21 6.69 2.23 - 13.56 ± 2.28 2.31 - 12.54 ± 2.52 1.80 - 12.58 ± 2.54 IIA 53 54 52 7.06 7.91 8.13 2.51 - 11.73 ± 2.45 2.73 - 14.56 ± 2.95 2.91 - 12.47 ± 2.69 IIB 122 124 119 8.21 9.11 9.40 2.18 - 13.20 ± 2.40 2.20 - 14.35 ± 2.59 2.77 - 12.93 ± 2.46 IIIA 9 9 9 6.48 7.11 6.80 3.78 - 11.02 ± 2.44 4.83 - 10.74 ± 2.32 3.27 - 11.30 ± 2.79

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Table 3. Vertebral measurements (mm) (M1, M2 and M3) for top three ranked taxa by NISP (Scombridae, Scaridae and Carangidae) with vertebrae types grouped from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

Layer n Mean (mm) Range ± s.d. (σ) (mm) M1 M2 M3 M1 M2 M3 M1 M2 M3 Scombridae IA 188 187 182 8.40 9.12 9.45 4.29-24.16 ± 2.13 3.64-30.89 ± 2.61 3.24-36.55 ± 2.70 IB 41 41 37 8.14 9.12 9.05 4.64-12.16 ± 1.73 4.30-12.54 ± 1.82 2.76-12.58 ± 1.90 IIA 34 35 36 8.37 9.51 9.17 5.68-11.73 ± 1.65 5.81-14.56 ± 1.90 2.91-12.13 ± 1.95 IIB 98 100 97 8.82 9.79 9.73 4.52-13.20 ± 2.02 4.77-14.35 ± 2.14 2.77-12.93 ± 2.26 IIIA 3 3 3 9.16 9.94 9.89 6.44-11.02 ± 2.41 8.41-10.74 ± 1.33 7.44-11.30 ± 2.13

Scaridae Historical 6 6 6 7.74 7.25 8.10 4.59-7.97 ± 1.51 5.18-8.90 ± 1.59 6.24-10.24 ± 1.66 IA 185 185 176 6.78 7.49 8.18 2.73-10.54 ± 1.59 2.82-13.62 ± 1.91 2.39-12.53 ± 2.21 IB 12 12 12 7.31 7.94 9.07 3.49-9.75 ± 1.73 3.59-11.04 ± 2.11 4.66-11.93 ± 1.93 IIA 3 3 3 7.56 8.66 8.10 6.83-8.45 ± 0.92 7.20-9.43 ± 1.27 7.39-9.33 ± 1.06 IIB 4 4 4 9.30 9.94 11.61 8.80-10.72 ± 0.95 9.09-10.68 ± 0.66 11.30-12.06 ± 0.32

Carangidae IA 107 106 100 5.87 6.46 8.32 3.21-11.14 ± 1.58 3.31-11.93 ± 1.67 2.73-18.17 ± 3.03 IB 17 17 17 4.84 5.60 6.95 3.24-6.80 ± 0.78 4.63-8.53 ± 0.95 3.36-9.36 ± 1.70 IIA 1 1 1 N/A N/A N/A 5.78 6.59 3.85 IIB 9 9 9 4.97 5.67 7.98 4.25-6.03 ± 0.54 5.24-6.95 ± 0.53 5.58-10.97 ± 1.62

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Table 4. Vertebral measurements (mm) (M1, M2 and M3) for Scombridae caudal vertebrae, from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

Layer n Mean (mm) Range ± s.d. (σ) (mm) M1 M2 M3 M1 M2 M3 M1 M2 M3 IA 98 97 97 8.75 9.60 9.90 5.59-24.16 ± 2.51 6.72-30.89 ± 3.01 6.10-36.55 ± 3.31 IB 28 28 27 8.57 9.63 9.51 5.43-12.16 ± 1.58 6.58-12.54 ± 1.31 6.04-12.58 ± 1.31 IIA 23 24 24 8.47 9.73 9.55 6.18-11.73 ± 1.79 7.56-12.38 ± 1.68 7.41-12.13 ± 1.31 IIB 62 62 65 8.96 10.04 10.07 4.52-13.20 ± 2.13 5.53-14.35 ± 1.96 5.75-12.93 ± 1.65 IIIA 2 2 2 8.24 9.58 9.37 6.44-10.03 ± 2.54 8.41-10.74 ± 1.65 7.44-11.30 ± 2.73

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Figure 1. A map of the Republic of the Marshall Islands, with Ebon Atoll and the location of site MLEb-1.

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Figure 2. Vertebrae types as characterised by yellowfin tuna (Thunnus albacares, Scombridae): (a) dorsal and (b) lateral views of the basioccipital with a proatlas vertebral face; (c) anterior and (d) dorsal views of the atlas; (e) anterior and (f) lateral views of the first thoracic; (g) anterior and (h) lateral views of the second precaudal; (i) anterior and (j) lateral views of the 14th caudal; (k) a lateral view of the antepenultimate; (l) a lateral view of the penultimate; (m) a lateral view of the ultimate (or hypural).

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Figure 3. The honeycomb grouper (Epinephelus merra, Serranidae) first thoracic vertebra. Vertebral measurements after Desse and Desse- Berset (1996a) and Gabriel et al. (2012): the maximum dorso-ventral height of the centrum (M1), the maximum mediolateral width of the centrum (M2) and the maximum craniocaudal length of the centrum (M3).

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Figure 4. The percentage contribution to total NISP by taxon and sieve size (vertebrae only).

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Figure 5. The distribution of the maximum mediolateral widths of the centrum (M2) for all vertebrae types identified to taxon from 6.4 mm and 3.2 mm (n = 2436).

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Figure 6. The range of vertebral measurements (mm) for all identified taxa and vertebrae types grouped from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

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Figure 7. The range of vertebral measurements (mm) for the three top-ranked taxa according to NISP: (a) Scombridae, (b) Scaridae and (c) Carangidae, with all vertebrae types grouped from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

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Figure 8. The range of vertebral measurements (mm) for Scombridae caudal vertebrae, from site MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers.

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Figure 9. Global Rachidian Profiles: (a) Selar crumenophthalmus (M1, M2 and M3 from modern specimen no. 325); (b) Selar spp. M1 measurements of all vertebrae types from MLEb-1 (TP17, 18, 19 and 20), 6.4 mm, all cultural layers. No. 325, fork length = 290 mm; no. 406, fork length = 230 mm: T, thoracic; P, precaudal; C, caudal; AP, antepenultimate; P, penultimate; U, ultimate.

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CHAPTER 5: Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands

Note: This is the final version of a peer-reviewed article published in the Journal of

Archaeological Science: Reports.

Matthew Harris, Ariana B.J. Lambrides and Marshall I. Weisler

School of Social Science, The University of Queensland, St Lucia, Qld 4072 Australia.

Corresponding author: Matthew Harris, School of Social Science, The University of Queensland, St

Lucia, Qld 4072 Australia. Telephone: +61 7 3365 3038. Fax: +61 7 3365 1554. Email: [email protected]

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Windward vs. leeward: Inter-site variation in marine resource exploitation on Ebon Atoll, Republic of the Marshall Islands

Abstract: The variation in windward and leeward marine environments has been linked to distinctions in marine subsistence on large, high volcanic Pacific Islands, but these patterns have not been explored on low coral atolls. We document windward vs. leeward islet site variation in the taxonomic composition of fish bone and mollusc shell assemblages from three archaeological sites at Ebon Atoll, Republic of the Marshall Islands, to elucidate the relationship between local environment, archaeological site type and the taxonomic composition of marine archaeofaunal assemblages. While the representation of taxa at each site was broadly similar in terms of measures of taxonomic heterogeneity (richness, evenness and dominance), chord distance and correspondence analysis reported variation in taxonomic composition at each site. For mollusc shell assemblages, variation in taxonomic abundance indicates the influence of the marine environments adjacent to each site and the relative exposure of these coastlines to heavy surf, wind, waves and extreme weather events. Fish bone assemblages recovered from 6.4 mm screens had less inter-site variation in richness, evenness and rank order, but differences were noted in the rank order of fish taxa recovered from selective 3.2 mm screening of archaeological deposits when compared between sites. In contrast to patterns for molluscs, variation in the taxonomic composition of fish bone assemblages likely relates to site function, rather than the marine environments adjacent to each site. These trends highlight for the first time the complex range of factors that influenced the prehistoric acquisition of marine resources between leeward and windward islets, and document variation in prehistoric marine subsistence within one atoll.

Keywords: atoll archaeology, marine subsistence, Marshall Islands, Micronesia, Paciﬁc ﬁshing, shell midden studies, zooarchaeology, archaeomalacology, ichthyoarchaeology

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Introduction Marine resources were a critical component of prehistoric subsistence systems across the Pacific Islands (Allen 2012; Fitzpatrick et al. 2011; Jones 2009; Leach and Davidson 1988; Ono and Clark 2012; Szabó and Amesbury 2011; Thomas 1999; Weisler et al. 2010). Finfish and molluscan remains are ubiquitous in Marshall Islands archaeological sites (Beardsley and Athens 1994; Dye 1987; Riley 1987; Rosendahl 1987; Shun and Athens 1990; Weisler 1999b, 2001b), and ethnographic and linguistic evidence highlights the varied and complex ways that Marshallese interact with the marine landscape (Abo et al. 1976; Erdland 1914; Kramer and Nevermann 1938; Spoehr et al. 1949; Tobin 2002). The intertidal reef platforms of the Marshall Islands host at least 1000 species of mollusc (Vander Velde and Vander Velde 2008), and over 800 fish taxa occur within 60 m ocean depth (Myers 1999). These expansive reefs—often greater in area than the terrestrial zone of atolls—provided predictable and possibly sustainable yields of marine subsistence resources throughout prehistory (e.g., Ono and Addison 2013; Thomas 2014); indeed, on Utrōk Atoll situated at the northern limit of permanently-inhabited atolls in the Marshall Islands, an 1800-year occupation sequence points to human populations, albeit in low numbers, with no indications of marine resource depression (Weisler 2001b: 128).

The degree of wave exposure has been recognised as a key factor influencing a range of important ecological processes which are critical for structuring faunal composition in tropical intertidal environments (Drumm 2005) and has been related to variation in human behaviour in archaeological contexts. However, determining whether taxonomic composition of archaeofaunal assemblages is driven by ecological conditions and/or human agency is undoubtedly a complex endeavour. Patterned variation in site use and diet as it relates to site location (windward vs. leeward) has been documented on large, high volcanic Pacific Islands (e.g., Bayman and Dye 2013; Kirch and Dye 1979: 58; Palmer et al. 2009; Weisler and Kirch 1985). In the Hawaiian archipelago particular agricultural practices are more commonly associated with leeward or windward locations, with rainfed agriculture and sweet potato cultivation associated with dry, leeward landscapes, and irrigated taro cultivation better suited to wetter windward regions (Palmer et al. 2009: 1444, Earle 1977: 224, Weisler and Kirch 1985). The differences in windward and leeward environments have also been recognised as influencing the exploitation of marine fauna.

Ethno-archaeological research into Niuan fishing strategies (Niuatoputapu, Polynesia) recognised the relationship between fishing practices and distinctions in reef structure, tidal activities and faunal communities that were related to windward or leeward location (Kirch and Dye 1979). Similarly, Kirch (1982) noted variation in exploitation of fishes from three Hawaiian archaeological sites that was inferred to be driven by local environment. Also in Hawai'i, fishponds are more common on the 148 leeward coasts than on the exposed windward zone (Weisler and Kirch 1985). Distinctions in taxonomic composition between two assemblages, Tangarutu (leeward) and Akatanui 3 (windward), from Rapa Island were attributed to their windward/leeward location, and while similar species were identified at each site, their rank-ordering was variable, with pomacentrids more common at the windward site of Akatanui 3 (Vogel and Anderson 2012).

Mollusc assemblages from large, high volcanic Pacific Islands also demonstrate a link between site location and taxonomic composition. Assemblages from windward sites in Hawai'i are dominated by limpets (Cellana spp.) and turban shells (Turbo spp.), characteristic of rocky shores, but are rare in leeward sites (Kirch 1982, Morrison and Hunt 2007). Similarly, mollusc assemblages from Vanuatu (Bedford 2007), Fiji (Szabó 2009) and Rapa (Szabó and Anderson 2012) reflect local environmental conditions across the windward/leeward divide and have been interpreted as the result of non- selective foraging strategies operating in varying environments. On atolls, the configuration of marine environments and the distribution and relative abundance of fauna is determined by geological history, exposure to wind, waves and currents as well as myriad stochastic, local ecological, biological and abiotic factors and relates to the windward and leeward exposure of each islet (Wiens 1962). However, atoll settlement patterns and subsistence practices reflected in the variation between windward and leeward environments have not been investigated.

We explore inter-islet and inter-site variation in the taxonomic composition of ﬁsh bone and mollusc shell assemblages from archaeological deposits on three islets on Ebon Atoll, Marshall Islands to elucidate the relationship between human foraging behaviour, site function, site location (windward v. leeward) and local environment. A range of statistical techniques are employed to investigate whether differences in the taxonomic composition of the assemblages is a reﬂection of ecological variability and site location (windward vs. leeward marine habitats) or site function (village vs. camp site). Future research avenues for exploring spatial variation in atoll settlement patterns and subsistence are then suggested.

Sites and samples

Ebon Atoll is the southernmost atoll in the Marshall Islands. Consisting of 22 islets encircling a 104 km2 lagoon, the total land area is approximately 5.4 km2 (Figure 1). The reef platform totals over 22 km2, roughly a 4:1 ratio of reef to land area. Two ﬁeld seasons (1995/1996 and 2011/2012) of survey and excavation were conducted on Ebon Atoll as part of a larger project directed by Weisler to investigate regional variation in Marshall Islands archaeology as it relates to the 700+ km north-south rainfall gradient, as well as documenting intra-atoll differences in settlement patterns and subsistence (Weisler 1999a, b, 2000, 2001a, b, 2002; Weisler and Swindler 2002; Weisler et al. 2012). We report

149 results from the analyses of the ﬁsh bone and mollusc shell remains retained in 6.4 mm and 3.2 mm screens at three sites excavated during the 2011/2012 Ebon Atoll ﬁeld season. A total of 68 m2 was excavated across seven archaeological sites on three islets, one situated on the leeward rim (Ebon Islet), one with windward exposure (Moniak Islet) and Enekoion Islet located between the two extremes. The archaeological sites chosen for analysis here include two lagoonside villages (MLEb- 1 and MLEb-33) (Weisler 2001b) and a much smaller, shorter-term occupation site (MLEb-31) on Moniak (Weisler 2002). Lagoonside deposits were explicitly selected at all three sites to minimise diachronic effects on these analyses as they all represent a later phase of Marshallese prehistory in which habitation sites occur adjacent to the lagoon, in contrast to earlier phases where deposits are in the interior and associated with horticultural pits (Weisler 2001a: 129).

The following description of mollusc and finfish habitats on oceanic atolls derives from: Carpenter and Niem (1998); Demond (1957); Hiatt and Strasburg (1960); Kohn (1987) and Wiens (1962). The largest islets and widest reef platforms are on the leeward south-eastern, western and north-western rim of Ebon Atoll. MLEb-1 and MLEb-33 lie in this zone, relatively sheltered from waves, winds and currents and feature high-rugosity coral reefs, and fine grained interreefal sand flats and seagrass beds on the lagoonside, and expansive, low relief pavements on the oceanside. Habitat complexity is highest on leeward islets, with a corresponding increase in faunal diversity predicted (Gratwicke and Speight 2005; Kohn and Leviten 1976). While mollusc taxa are generally sessile, and strongly associated with particular benthic habitats, finfish taxa are more difficult to associate with windward or leeward environments. Fish often track across multiple habitats with day/night cycles, tides, and during feeding. However, some taxa are strongly associated with certain substrate types, which vary in predominance between leeward and windward reef habitats as described below.

Leeward oceanside mollusc communities are highly diverse, with colonies of macroalgae and shallow tide pools hosting large numbers of cowries (Cypraeidae) drupes and other murex shells (Muricidae) top shells (Trochidae), cone shells (Conidae) and nerites (Neritidae). These reef platforms are also associated with large schools of parrotfish (scarids), surgeonfish (acanthurids), wrasse (labrids), goatfish (mullids), and small bodied sharks (carcharhinids), and algal turfs provide grazing for rabbitfish (siganids), sea chubs (kyphosids), butterflyfish (chaetodontids), acanthurids, damselfish (pomacentrids) and triggerfish (balistids).

The lagoonside reefs, seagrass beds and sand flats host communities of giant clams (Tridacna spp. and Hippopus spp.), spider conchs (Lambis spp. and Harpago spp.) Conidae, mitre shells and auger snails (Terebra spp. and members of the family Mitridae). The upper intertidal sand flats provide habitat for the easily accessible sand dwelling bivalves including the violet asaphis (Asaphis violascens), venus clams (Gafrarium spp.), cockles (Vasticardium spp.), ark clams (Arca spp.) and 150 surf clams (Atactodea striata). Areas of coral growth on the lagoonside are associated with diverse herbivorous, carnivorous, and omnivorous fish communities including scarids, balistids, chaetodontids, pomacentrids, moray eel (muraenids), squirrelfish and soldierfish (holocentrids), grouper (serranids), snapper (lutjanids), labrids, filefish (monacanthids), and pufferfish (tetraodontids).

MLEb-31 is located on a windward islet, which is smaller and generally more exposed to winds, waves and currents. The intertidal zone is primarily composed of poorly sorted coral rubble washed from the ocean facing subtidal reefs, wave cut erosional channels, and coarse, gravelly sands on the lagoonside. Habitat complexity is generally lower on windward islets, with a decrease in richness and diversity of mollusc and fish communities predicted (Gratwicke and Speight 2005; Kohn and Leviten 1976). Mollusc communities characterised by large and robust Turbo, drupes (Drupa spp.), Cypraeidae, Conidae, vase shells (Vasum spp.), polished nerites (Nertia polita) and frog shells (Bursa spp.). Finfish communities on windward islets are varied and complex, but taxa characteristic of exposed surge channels include muraenids, carcharhinids, hawkfish (cirrhitids), serranids, lutjanids, acanthurids, pomacentrids, labrids, scarids, combtooth blenny (blenniids), and balistids.

The following analyses are based on all fish bone and mollusc shells retained in the 6.4 mm screens from lagoonside deposits on Ebon Atoll; Test Pit (TP) 17–20 at site MLEb-1, TP 2–6 at site MLEb- 31 and TP 2 and 8 at site MLEb-33 (Figure 1). A single unit from each site—MLEb-1 (TP 17), MLEb- 31 (TP 2) and MLEb-33 (TP 8)—was sieved with 3.2 mm screens during the 2011/12 fieldwork. All excavated sediments were wet- sieved. Hereafter, the single-unit sub-samples of fish bones recovered from nested 3.2 mm and 6.4 mm screens are described as the 3.2 mm samples.

MLEb-1

MLEb-1 is located at the centre of a ~ 2 km long village system on Ebon Islet (Weisler 2002). Ebon Islet is the largest islet of the atoll, featuring high-rugosity coral reefs and sand flats in the lagoon intertidal and expansive, relatively calm intertidal reef flats on the oceanside (Figure 1a). Cultural material, including molluscan remains, fish bone, charcoal, oven (um) stones and worked shell artefacts were recovered from a 2 × 2 m unit (TP 17, 18, 19 and 20) excavated into a low mound, built by the accumulation of successive coral pavements, located 40 m inland of the current lagoon shore and 20 m northwest of the Primary School. Cultural deposits extend to a depth of 1.75 m. Cultural material retained in the 6.4 mm screens yielded 3464 fragments of mollusc shell (MNI [Minimum Number of Individuals] = 1258), and 4188 fish bones (MNI = 509), with 94.1% and 39.3% of fragments, respectively, identified to family, genus or species. The 3.2 mm fish bone samples (TP

151

17) yielded a NISP (Number of Identiﬁed Specimens) of 2655 (MNI = 378), with 14.4% of fragments identiﬁed to family, genus or species.

MLEb-33

Situated on Enekoion Islet, MLEb-33 is a sparse to dense midden deposit surrounding a large aroid pit situated from 100 m to 25 m from the lagoon shore. A 1 × 2 m trench was excavated on the lagoonward side of the aroid pit where cultural deposits extended to 40 cm below surface. The oceanside reef flat is generally wider than at Ebon or Moniak, but is mainly composed of coral rubble, boulders and eroded beachrock slabs, more similar to the exposed reef flat of Moniak than Ebon Islet. The lagoonside environment features expansive seagrass meadows (Thalassia spp., Figure 1b) and sand flats, and some coral growth in the intertidal, similar to the lagoon environments at Ebon Islet. Cultural material retained in the 6.4 mm screens yielded 617 fragments of mollusc shell (MNI = 230), and 144 fish bones (total MNI = 67), with 96.8% and 60.5% of fragments, respectively, identified to family, genus or species. The 3.2 mm fish bone samples (TP 8) yielded a NISP of 98 (MNI = 34), with 20.1% of fragments identified to family, genus or species.

MLEb-31

The small midden site MLEb-31 is located ~ 75 m from the lagoon shore on the windward islet of Moniak (Weisler 2002). Cultural deposits extend to a maximum depth of 70 cm. The oceanside intertidal is characterised by coral boulder ramparts and cobbles deposited by extreme weather events (Figure 1c), in contrast to the relatively protected oceanside of Ebon and Enekoion Islets. The lagoonside sands of Moniak are coarse and the shore declines steeply to the lagoon floor. Cultural material retained in the 6.4 mm screens yielded 1740 fragments of mollusc shell (MNI = 650), and 1084 fish bones (MNI = 326), with 95% and 53.5% of fragments, respectively, identified to family, genus or species. The 3.2 mm fish bone samples (TP 6) yielded a NISP of 648 (MNI = 192), with 20.4% of fragments identified to family, genus or species.

Methods

Identiﬁcation and quantiﬁcation protocols

Fish remains were identified by Lambrides (Appendix B and C) and mollusc remains by Harris; all identifications were completed to the lowest taxonomic level using Indo-Pacific comparative reference collections housed at The University of Queensland archaeology laboratory (see Lambrides and Weisler 2015a: 5; Weisler 2001b: appendix 3, for a description of the fish reference collection). Reference manuals were also used for molluscan identification, including: Abbott and Dance (1990); Poppe (2008); Röckel et al. (1995) and Burgess (1985). Due to the richness of Indo-Pacific marine

152 fauna, all fish bone (see Lambrides and Weisler 2015b) and mollusc shell fragments were attempted for identification, but lower order taxonomic identifications (e.g., genus and species) were assigned with caution to avoid over-identification (Driver 1992; Wolverton 2013). Taxonomic abundance of archaeological fish bone and mollusc shell were quantified by NISP and MNI. For fish remains, MNI values were calculated following standard zooarchaeological protocols for vertebrate fauna (Grayson 1984; Lyman 2008; Reitz and Wing 2008) and for molluscs following Harris et al. (2015). The quantification methods used here allow comparison of fish and mollusc taxonomic abundance as MNI values were consistently determined using the most frequently occurring Non Repetitive Element (NRE).

Statistical analyses

Both mollusc shell and fish bone samples were aggregated at the site level. The NRE frequency for each taxon was summed by cultural layer for calculating MNI. Relative taxonomic abundance is used here to examine differences in the taxonomic composition of fish bone and mollusc shell assemblages from the three sites to explore the interaction between windward vs. leeward islets, local environment and the extraction of marine fauna. A range of statistical tests were utilised including taxonomic richness and diversity as measured by NTAXA, the Shannon-Weiner index of diversity (H′), Shannon's evenness (E), Simpson's dominance (1-D), and Fisher's α. Similarity and difference in faunal composition was analysed using chord distance analysis, and correspondence analysis (CA). These statistics have proven utility for examining similarities and differences in taxonomic composition for archaeological assemblages, including faunal (Faith 2013) and archaeobotanical samples (Wright et al. 2015). All statistical analyses reported below were carried out using MNI values for comparability with other Pacific Island assemblages, but it should be noted that statistical analyses of NISP values were tested and revealed similar trends (Grayson 1984; Lyman 2008). All statistical analyses were completed using PAST Paleontological Statistics Package, version 3.06 (Hammer et al. 2001).

Species richness (the number of species in an analytical unit) was assessed using NTAXA. Evenness, being the relative abundance of species in the assemblage, was measured using the Shannon-Weiner index of diversity (H′) and Shannon's evenness (E). H′ values range between 0 and a theoretical maximum of 5, but values between 1.5 and 3.5 are most common. Higher H′ values indicate greater species diversity and richness. E values range between 0 and 1, with 0 indicating assemblages dominated by a single taxon, and values closer to 1 indicating rich, even assemblages (Lyman 2008: 195; Reitz and Wing 2008: 111). The dominance of few species in the assemblage was assessed using Simpson's index of diversity (1-D). 1-D values range from 0 to 1, with lower values indicating assemblages dominated by a single taxon (Magurran 2004: 116). Fisher's α, a measure of diversity, 153 was also utilised as Shannon's indices and NTAXA can be inﬂuenced by sample size (Faith 2013). Fisher's α values are considered to be relatively independent of sample size (Hayek and Buzas 2010: 295–296). Fisher's α tracks the occurrence of taxa represented by single individuals as a measure of overall diversity (Karlson et al. 2004). Signiﬁcant difference between diversity indices calculated for each sample were also carried out using random permutation tests of relative abundance data.

Chord distance and exploratory CA analyses were conducted using non-aggregated (i.e., not collapsed by NTAXA) relative abundance data. NTAXA quantifies richness by collapsing taxa at the highest common taxonomic level for each assemblage. NTAXA values are generally correlated with sample size and can be influenced by identification protocols, but do ensure richness values are not inflated by species that are more easily identified to lower taxonomic levels. Chord distance analysis is a scaled measure of Euclidean distance for examining the dissimilarity between samples in relative abundance of species, such as sites or cultural units (Faith et al. 1987; Legendre and Gallagher 2001). Chord distance values range from 0, indicating samples with no difference in relative abundance, up to 2 indicating no species in common between samples. Chord distance values are useful measures of √dissimilarity for the assemblages examined here, as species represented by single individuals are not highly weighted.

This suite of statistical tests allows an exploration of the role of site location (windward vs. leeward marine habitats) and site function (village vs. camp site) on the taxonomic composition of the assemblages. Taxonomic measures of heterogeneity and chord distance are complementary analyses which can be used to assess human collection strategies (i.e., non-selective or selective behaviours) that are linked to local faunal community structure (i.e., number of species, dominance of particular taxa, etc.) and site function. Correspondence analysis is used to further explore the relationship between particular taxa, ecological variables, and site function, and provides useful data for comparison with the results of the other statistical analyses used here.

Results

Figure 2 presents the relative abundance of mollusc and fish taxa identified from the 6.4 mm and 3.2 mm screened assemblages at sites MLEb- 1, MLEb-31 and MLEb-33. To highlight broad trends in taxonomic composition at each site, quantification data are aggregated at the family level. Characteristic of Indo-Pacific marine archaeofaunas, many species are represented (e.g., Morrison and Addison 2009; Ono and Intoh 2011; Riley 1987; Szabó 2009; Weisler 2001b). The molluscan assemblage is dominated by gastropods (x = 84.2% MNI/81.7% NISP), with bivalves contributing minimally to MNI and NISP. Both 6.4 mm and 3.2 mm fish bone assemblages are dominated by

154 piscivores and omnivores/benthic carnivores, which account for 75.2% and 84.4% of total MNI, respectively.

Taxonomic measures of heterogeneity for all samples report high richness and evenness and low dominance overall (Table 1). Random permutation tests for significant difference between index values at each site reported significant values only for 1-D values for molluscs between MLEb-1 and MLEb-31 (p = 0.0002) and E values for 3.2 mm fish bone samples from MLEb-1 and MLEb-31 (p = 0.0264). 1-D values are sensitive to differences in the relative abundance of the top ranked taxa, explaining the significant result for mollusc samples. E values are sensitive to alterations in the relative abundance of all taxa, once again explaining the significant difference reported for 3.2 mm fish samples from MLEb-1 and MLEb-31.

Chord distance was used to measure the dissimilarity between the relative abundance of taxa in each assemblage. The greatest faunal dissimilarity as measured by chord distance was reported for molluscan assemblages from site pairs MLEb-1/MLEb-31 and MLEb-1/MLEb-33. Minimal dissimilarity was reported for the mollusc assemblage from MLEb-31/MLEb-33, 6.4 mm fish bone assemblages from all site pairs and 3.2 mm fish bone assemblage from site pair MLEb-1/MLEb-31. Moderate dissimilarity was noted for 3.2 mm fishbone assemblages from site pairs MLEb-1/MLEb- 33 and MLEb-31/MLEb-33. Chord distance analysis indicates that molluscan assemblages tend to be more taxonomically dissimilar than fish bone assemblages across all site pairs, except for MLEb- 31/MLEb-33. Both taxonomic measures of heterogeneity and chord distance analysis indicate that all assemblages were relatively similar in terms of richness, evenness, and relative abundance of taxa, with the most pronounced differences generally between mollusc assemblages from MLEb-1 and MLEb-31.

CA of taxonomic abundance (6.4 mm data) was used to investigate whether differences in the taxonomic composition of the assemblages as initially determined by the results of the diversity measures, and chord distance, was better explained by local ecological variability (windward vs. leeward marine habitats) or site function (village vs. camp site). Figure 3a–c plots CA axis 1 and 2 for all samples, which account for 77.8% and 22.2% of the variance in taxonomic abundance, respectively. Axis 1 discriminates between windward and leeward islets, with MLEb-1, on the most leeward islet, reporting the lowest axis 1 score and MLEb-31, on the most windward islet, reporting the highest axis 1 score. MLEb-33, which is moderately exposed to windward waves, currents and wind, reports an intermediate axis 1 score. The negative axis 1 score that characterises MLEb-1 is associated with 43 mollusc taxa and six fish taxa (Carcharhinus spp., Decapterus spp., Elagatis bipinnulata, Ostraciidae, Sphyraena spp., and Thunnus spp.) that occur only at that site, and account for 11% and 4.3% of total site MNI, respectively. MLEb-31 is characterised by positive axis 1 scores, 155 and is associated with 34 mollusc taxa and a single fish taxon (Zebrasoma sp.) that occur only at that site, and account for 7.7% and 0.3% of total site MNI, respectively. MLEb-33 is characterised by negative axis 2 scores, and is associated with five molluscan taxa (Conus leopardus, Conus lividus, Corculum cardissa, Harpa spp., Periglypta spp.) that occur only at that site (2.5% of total site MNI), but no distinct fish species. Axis 1 scores are negatively loaded by reef flat pavement dwelling gastropod taxa, the most common habitat exploited for mollusc gathering at MLEb-1 (Harris and Weisler, in review). Conversely, axis 2 scores are negatively loaded by sand-dwelling gastropod and bivalve taxa. Interestingly, the extant lagoon environment adjacent to MLEb-33 is predominately turtle grass (Thalassia spp.) beds and sand flats. Habitat proclivities are more difficult to assess for the non-sessile fish but, generally, the representation of feeding behaviours (piscivores, omnivores/benthic carnivores and herbivores) for non-distinct taxa were broadly similar at each site. In contrast, the CA of 3.2 mm fish bone taxonomic abundance data (Figure 3d) report similar levels of variance for both axis 1 and axis 2, 58.2% and 41.8%, respectively. This suggests that there is less taxonomic similarity between sites than represented by the 6.4 mm data, which is also reflected by the chord distance scores (Table 2). Similar to the 6.4 mm fish bone CA, distinct taxa from all sites only accounted for a small percentage of the assemblage, specifically 5.6% of total MNI. CA results reflect the substantially different rank ordering of taxa at each site as represented by the 3.2 mm data.

Discussion

Spatial variation in marine subsistence as it relates to windward and leeward settlement patterns on a single atoll has not previously been assessed in Paciﬁc Island archaeology. A range of statistical analyses were implemented using mollusc shell and ﬁsh bone relative taxonomic abundance data reported from three habitation deposits on Ebon Atoll. All sites were located adjacent to the extant lagoon shore, with one a temporary habitation site (MLEb-31), and the other two large villages (MLEb-1 and MLEb-33).

The taxonomic composition of archaeological mollusc and ﬁsh bone assemblages from each site evidenced a similar suite of families with assemblages characterised by highly rich and even measures of taxonomic diversity, and no strongly dominant taxa, despite probable differences in habitat complexity at each site. All mollusc assemblages are dominated by gastropods, with bivalves contributing minimally to MNI. The dominance of gastropods is characteristic of macrobenthic mollusc communities recorded for other atolls in the Marshall Islands (Kay and Johnson 1987), potentially indicating a generalised molluscan foraging strategy at all sites (Harris and Weisler, in review, Szabó 2009, Kirch 1982). Richness was generally greatest at MLEb-1, which is unsurprising as this is both the largest sample, and from the most complex habitat (Gratwicke and Speight 2005).

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Mollusc assemblages at each site have relatively high ranks for nerites, muricids (Drupa spp. and Thais spp.), Conus spp., Cerithidae, Cypraeidae, Turbo spp. and A. violascens. Fish bone assemblages recovered from the 6.4 mm screens are generally dominated by piscivorous species (e.g., serranids, lutjanids and carangids) followed in rank order by omnivorous/benthic carnivorous species (e.g., holocentrids, lethrinids and balistids) and herbivorous species (e.g., acanthurids and scarids). Fish bone assemblages recovered from the 3.2 mm screens reported increased dominance of omnivores/benthic carnivores (e.g., holocentrids, exocoetids and mullids) which may be related to average ﬁsh bone size for these taxa, bone density and taphonomy. For ﬁsh bone assemblages from the 6.4 mm screens, scarids and serranids are rank 1 and 2, respectively, at MLEb-1 and MLEb-31, and rank 2 and 3 at MLEb-33. However, the 3.2 mm samples, while similar in taxonomic composition, showed greater variation in the rank ordering of these taxa when compared to the 6.4 mm samples, similar trends were noted from Rapa Islands archaeological sites, where 2 mm screens were utilised (Vogel and Anderson 2012).

Mollusc assemblages reported generally greater inter-site variation in taxonomic abundance than fish bone assemblages. The statistical analyses utilised here indicate variation in relative taxonomic abundance of mollusc assemblages is due to differences in the local environment at each site. At MLEb-1, the majority of the molluscan assemblage could have been gathered from the oceanside reef flat and coral reefs (Harris and Weisler, in review). Conversely, CA shows that those molluscan taxa that prefer sandy lagoon substrates are most strongly associated with MLEb-33, a marine environment today which is characterised by large lagoonal sand flats and turtle grass beds. Furthermore, assemblages at MLEb-31 consist principally of those taxa which either inhabit the boulder ramparts, typical of windward islets (i.e., N. polita), or those taxa which are suitably adapted to constant exposure to wind, waves and currents on the reef edge (i.e., Mauritia mauritiana, Vasum turbinellus, and Thais armigera). The variability in the relative abundance of Nerita plicata, N. polita and the ranellids (Monoplex intermedius, M. nicobaricus and Gutturnium muricinum) likely explains the significant difference in measures of dominance between molluscan assemblages from MLEb-1 and MLEb-31. This result also potentially indicates the influence of local environment, as Ranellidae are most common in areas of coral growth (Govan 1995), which are characteristic of Ebon Islet (MLEb- 1), but are rare at Moniak (MLEb-31). The correlation between local environment and the molluscan taxa in the assemblage, in addition to the even, rich and diverse taxonomic composition indicates that a non-selective foraging strategy, mediated by local environment, operated at each site. These patterns are broadly similar to mollusc assemblages from other oceanic islands where richness and evenness are high, and taxonomic composition varies predominately with changes in site location and local environment (e.g., Szabó 2009). Fish bone assemblages, however, generally have lower values of

157 dissimilarity between sites and are harder to link to marine environments adjacent to each site as fish track across different habitats while foraging, unlike molluscs that are generally sessile. For example, Katsuwonus pelamis, a pelagic-oceanic dwelling species, is dominant at the largest village site, MLEb-1 but rare at the campsite, MLEb-31 indicating that variation in fish bone assemblages may be related to site function rather than the marine environments adjacent to the sites. This trend requires further analysis (e.g., assessment of temporal variation and inclusion of additional sites), but could relate to a number of variables, including settlement patterns and fish capture strategies operating at each site. Variability in inter-site taxonomic composition for 3.2 mm samples was generally greater than 6.4 mm fish bone assemblages. Mesh size has been linked to alterations in species richness and diversity (e.g., Nagaoka 2005; Ono and Clark 2012) and inferences made regarding capture methods, morphometric reconstructions of fish size, ontogenetic growth and associated live fish behaviour can be useful for predicting fishing technology (Bertrando and McKenzie 2011).

Conclusion

Exploratory data analyses were implemented to determine whether there are differences and/or similarities in the taxonomic composition of mollusc shell and fish bone assemblages from three archaeological sites situated on windward and leeward islets at Ebon Atoll, Marshall Islands. Results indicate broad similarity in assemblage composition, reflected in similar richness, evenness and dominance scores at each site, regardless if the sites were small intermittently occupied habitations on windward islets or large villages on leeward islets. Where variation in taxonomic composition occurs, the configuration of marine environments at each site may account for much of the differences in the mollusc assemblages, while fishing technology (capture techniques) and site function (i.e., village sites v. campsites) could account, in part, for the variation in fish bone assemblages at each site. Intra-islet variation in taxonomic abundance, metric analysis of fish bone to assess body size over time and possible effects of human impacts to marine fisheries, studies of associated material culture and temporal analysis of alterations to foraging strategies will provide additional datasets for testing the influence of local marine environments and human settlement patterns on relative taxonomic abundance of mollusc shell and fish bone assemblages from Ebon Atoll.

This study has shown that even within a single atoll, human foraging patterns can differ over small spatial scales. The observed patterns follow documented evidence from other Pacific Islands where molluscan assemblages broadly reflect local environmental conditions. In contrast, fishbone assemblages possibly reflect capture methods and site function. The results presented here highlight the importance of atolls for examining the dialogue between human behaviour and local marine environments when investigating long-term trajectories of human-environment interaction. Assessing variation in the composition of archaeofaunal assemblages from windward and leeward islets can 158 yield useful information for understanding variation in settlement patterns and intra-atoll subsistence practices—the latter previously not recognised. These intra-atoll analyses are critical for assessing variability in marine subsistence practices and are applicable to other island types across the Pacific.

Acknowledgements

Permission to conduct archaeological research in the Republic of the Marshall Islands was granted to Weisler by the Historic Preservation Office, Ministry of Internal Affairs and on Ebon Atoll, former mayor Lajan Kabua. Marshall Islands fieldwork was supported by a grant to Weisler from the Office of the Deputy Vice Chancellor (Research), University of Queensland. Harris' and Lambrides' postgraduate studies are supported by an Australian Postgraduate Award. We thank the peer reviewers for their constructive feedback and suggestions.

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Table 1. Measures of taxonomic heterogeneity: NTAXA, Shannon's index of diversity (H') and evenness (E), Simpson's dominance (1-D) and Fisher’s α, as calculated for mollusc shell and fish bone assemblages retained in the 6.4 mm and 3.2 mm sieves for all sites (MLEb-1, MLEb-31 and MLEb-33).

Index 6.4 mm samples 3.2 mm samples molluscs fish bone fish bone MLEb-1 MLEb-31 MLEb-33 MLEb-1 MLEb-31 MLEb-33 MLEb-1 MLEb-31 MLEb-33 NTAXA 47 37 26 27 25 18 29 25 18 1-D 0.887 0.859 0.869 0.921 0.926 0.909 0.936 0.940 0.919 H’ 2.648 2.528 2.512 2.780 2.822 2.605 2.968 2.972 2.705 E 0.687 0.700 0.711 0.844 0.877 0.901 0.881 0.923 0.936 Fisher’s α 9.631 8.508 7.534 6.803 6.306 8.071 7.316 7.670 15.51

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Table 2. Chord distance values for mollusc shell and fish bone assemblages retained in the 6.4 mm and 3.2 mm sieves for each site pair.

Site pair 6.4 mm samples 3.2 mm samples molluscs fish bone fish bone MLEb-1/MLEb-31 1.085 0.463 0.481 MLEb-1/MLEb-33 1.045 0.538 0.732 MLEb-31/MLEb-33 0.373 0.566 0.741

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Figure 1. Map of the Republic of the Marshall Islands, with Ebon Atoll and the location of sites MLEb-1, MLEb- 31 and MLEb-33, and photos depicting intertidal marine habitats characteristic of each islet (a) Ebon Islet oceanside, view northwest showing expansive reef flat (Photo: A. Lambrides), (b) Enekoion Islet lagoonside, view northeast showing seagrass beds in the intertidal (Photo: M. Harris), (c) Moniak Islet oceanside, view east of coral cobble and boulder intertidal (Photo: M.Weisler).

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Figure 2. The percent contribution to total MNI and NISP by taxon, site and screen for mollusc shell 6.4 mm samples and fish bone 6.4 mm and 3.2 mm samples. Family level identifications, but note Selachii (modern sharks), which is a superorder/clade.

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Figure 3. Correspondence analysis of taxonomic abundance. (a) 6.4 mm bivalve shell, (b) 6.4 mm gastropod shell and (c) 6.4 mm fish bone samples are displayed on separate plots for clarity, (d) 3.2 mm fish bone samples. Key taxa are annotated and distinct taxa are not displayed due to minimal contribution to total MNI at each site.

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CHAPTER 6: Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean

Note: This is the final version of a peer-reviewed article accepted for publication in the Journal of Island and Coastal Archaeology.

Ariana B.J. Lambrides and Marshall I. Weisler

School of Social Science, The University of Queensland, St Lucia, Qld 4072 Australia.

Corresponding author: Ariana Lambrides, School of Social Science, The University of Queensland,

St Lucia, Qld 4072 Australia. Telephone: +61 7 3365 3038. Fax: +61 7 3365 1554. Email: [email protected]

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Late Holocene Marshall Islands archaeological tuna records provide proxy evidence for ENSO variability in the western and central Pacific Ocean

Abstract: Tuna will have increased importance to Pacific Island nations in coming decades for food security and economic needs; consequently, sustainable fisheries management policies are imperative. The frequency and temporal distribution of tuna bones from tropical Pacific archaeological sites is essential for documenting millennial scale records that detail the responses of tuna stocks to anthropogenic fishing pressure and climatic variability. We highlight the potential impacts of El Niño-Southern Oscillation (ENSO) variability on the western and central Pacific Ocean skipjack (Katsuwonus pelamis) fishery over the last 2000 years. Ebon Atoll (4°38′24.67″N, 168°42′23.56″E), Republic of the Marshall Islands (RMI) archaeological data and regional western and central Pacific Islands archaeological tuna fishery data are evaluated. These datasets are compared to palaeoclimate records, which track hydroclimate variability during the last 2000 years, and recent historic capture records, which document associations between ENSO and skipjack abundance and range throughout the tropical Pacific Ocean. Results suggest that regional and temporal trends in archaeological scombrid/skipjack abundance provide proxy evidence for western and central Pacific Ocean ENSO variability, while prehistoric human impacts to the tuna fishery appear to be negligible. Future research should include species-level identification of all archaeological tuna bones and establish fine-grained local climate data across the region that is tied to well-dated archaeological sequences, thus enhancing our understanding of how regional climate influences the geographic distribution and relative abundance of tuna species over millennia.

Keywords: El Niño-Southern Oscillation, historical ecology, Katsuwonus pelamis, Pacific Islands, zooarchaeology

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Introduction

Zooarchaeological datasets have enabled the global investigation of alterations in resource availability in response to both anthropogenic factors and climate variability, indicated by changes in relative abundance of taxa across centuries to millennial time scales (e.g. Andrus et al. 2002; Aswani and Allen 2009; Barrett et al. 2011; Broughton 1997; Butler and Campbell 2004; Erlandson et al. 2009; Faith 2014; Fitzpatrick and Donaldson 2007; Giovas et al. 2016; Grayson 2001; Lyman 2016; Moss 2012; Nagaoka 2002; Reitz 2004; West 2009). We highlight the potential impact of ENSO variability on the western and central Pacific Ocean skipjack (Katsuwonus pelamis) fishery over the last 2000 years. Focusing on Ebon Atoll at the southern extent of the Republic of the Marshall Islands (RMI), the frequency and distribution of archaeological tuna bones are evaluated in conjunction with regional trends in the western and central Pacific Islands archaeological tuna fishery data. These datasets are then compared to palaeoclimate records, which track hydroclimate variability over the last 2000 years, and recent historic capture records, which document the impact of ENSO on skipjack abundance and range throughout the tropical Pacific Ocean.

Tuna will have increased importance to Pacific Island nations over the next several decades, given tuna must supply ~25% of fish required for food security by 2035 (Bell et al. 2015). The RMI has an industrial purse-seine tuna fishery that exceeds 47,000 tons per year (2004-2008), worth > USD 56.7 million. Fishery efforts predominately target the southern RMI, with skipjack accounting for 74% of the total catch in 2012 (Bell et al. 2011; Western and Central Pacific Fisheries Commission 2014). Under low and high emissions scenarios for the RMI, predictions suggest there will be increases in average sea surface temperature (SST), sea levels, and ocean acidification and reductions in primary production and zooplankton biomass (Bell et al. 2011). Catches of skipjack and yellowfin (Thunnus albacares) are expected to initially increase with these conditions (>20%), but big eye tuna (Thunnus obesus) will decrease under both scenarios (~30% by 2100 under the A2 scenario); skipjack biomass is predicted to stabilize by 2050, then begin decreasing from 2060, which is associated with less favorable spawning conditions (Bell et al. 2011; Lehodey et al. 2013: 95).

Given the contemporary importance of tuna fisheries in the RMI, archaeological data from this region is essential for establishing tuna fisheries responses to both anthropogenic fishing pressure and climatic variability throughout the entire 2000 year-long culture-historical sequence of the archipelago. Nicol et al. (2013: 132) have argued ‘fisheries management policies that are resilient and can be adapted to climate change’ are needed. Migratory fish, such as tuna, are valuable for investigating human responses to climate variability both locally (e.g. Ebon Atoll) and for providing proxy evidence for regional climatic variability (e.g. western and central Pacific Ocean). These analyses have only recently become possible in the Pacific given more specific taxonomic 172 identifications of archaeological tuna bones and the implementation of more rigorous methods and analytical frameworks such as historical ecology used to frame this study (Lambrides and Weisler 2016; Rick and Lockwood 2013).

Background

Ethnography of Pacific skipjack fishing

Schools of skipjack were commonly located by tracking seabird flocks (e.g. Buck 1957; Burrows 1936; Johannes 1981), and were viewed as a sacred fish in many regions (e.g. Akimichi 1986; Huntsman and Hooper 1996; Ivens 1927; Ono and Addison 2009). Trolling for tuna was common (Buck 1950; Dye 1983; Kirch and Dye 1979), but no longer practiced in some areas by the early 20th century (Burrows 1936, 1937). Tuna fishing carried a great deal of social and cultural significance (e.g. Davenport 1971; Kennedy 1931; Nordhoff 1930a, b), as in the southeast Solomon Islands where skipjack were considered the ‘king of fish’ (Iven 1926: 130) and its capture was ‘imbued with ritual and mystical significance’ (Walter and Green 2011: 10).While tuna fishing was often described as the least economically important mode of fishing (e.g. Lieber 1994), ‘when the tuna are there, the pace of island life quickens’ (Johannes 1981: 91). On Ifaluk Atoll, Caroline Islands, skipjack trolling was the most celebrated, with five of the 16 known fishing songs associated with this activity; significantly, no other kind of fishing had more than two songs (Burrows and Spiro 1957:105). In Samoa, Buck (1930: 124) reports the ceremonial division of skipjack, where the chiefs were given the most important portions or in Tokelau the catch was distributed if communally obtained, known as inati (Hooper and Huntsman 1991; Ono and Addison 2009). Seine net, purse net, or coconut frond sweeps—depending on the region—were considered the most successful techniques for capturing schools of skipjack. On Ifaluk Atoll, multiple seines were stretched end to end, often up to ~800 m long, to surround the school once it entered the lagoon; the whole community would participate and get a portion of the catch (Burrows and Spiro 1957). Similar strategies have been reported elsewhere in the Pacific, including the RMI (e.g. Akimichi 1986; Erdland 1914; Krämer and Nevermann 1938; Lieber 1994; Severance 1986; Tinker 1950).

Archaeology of Pacific tuna fishing

Most Pacific archaeologists do not analyze tuna fisheries in detail due to identification protocol bias (but see Fraser 1998; Fraser 2001; Lambrides and Weisler 2015a; Ono and Intoh 2011); consequently, family level identifications are most often reported in the literature, the shortcoming of which have been critiqued by Anderson (2013). Our review focuses on those sites where scombrids contributed ~20% of minimum number of individuals (MNI) at an archaeological site although we acknowledge that MNI protocols may not have been consistently reported in the early Pacific fishing literature and 173 this may impact intersite comparisons. Throughout this paper all radiocarbon age determinations from the published literature have been converted to cal BP for comparability.

Within Polynesia, sites from the Marquesas Islands, including Hane, Ua Huka (Davidson et al. 1999; Fraser 1998: 81-92), Te Anapua, Ua Pou (Fraser 1998: 92-101; Leach et al. 1997), and Hanamiai, Tahuata (Rolett 1998), and the Vaito‘otia/Fa‘ahia complex, Huahine in the Society Islands (Fraser 1998: 102-114; Leach et al. 1984) provide the most detailed records of tuna fishing in the eastern Pacific Ocean (Figure 1). These assemblages were initially dominated by scombrids and other mostly piscivorous taxa (feeding on fish), which were associated with offshore environments, and then at some sites, inshore taxa (e.g. acanthurids and scarids) increased during late prehistory. A lack of high resolution dating at these sites makes it difficult to correlate site chronologies and changing scombrid abundance to regional climatic trends.

The archaeological record of the western and central Pacific Ocean is especially relevant for documenting long-term trends in the exploitation of the tuna fishery as displacement of the equatorial Pacific warm pool, due to ENSO events, influences tuna recruitment and range (Lehodey et al. 1997). Sites from Palau and the Caroline Islands provide the western Pacific records and Tokelau, American Samoa, and Samoa (formerly, Western Samoa) are the most detailed for the central Pacific Ocean.

Masse et al. (2006) reported a decline in skipjack between 750 and 350 cal BP at the Rock Islands, Palau, attributed to a shift from angling to the use of nets and basket traps, argued to be more reliable due to the climatic variability associated with the Medieval Warm Period (MWP)/Little Ice Age (LIA) transition. On Fais Island, Caroline Islands, Ono and Intoh (2011) provide a well dated sequence, which tracks variability in the prehistoric tuna fishery over ~1800 years. The initial increase in scombrid abundance in Phase IIA occurs at ~1550-1350 cal BP, abundance counts peak in Phase IIB (~1350-1150 cal BP), with scombrids reported as the highest ranked taxon by MNI. Abundance then declines from ~750-550 cal BP (Phases III and IV). Overall, scombrids account for 11.1% of total site MNI. Cultural and climatic factors were suggested as driving these changes including dietary preference, social control, and the ‘AD 1300 Event’ discussed by Nunn (2000a).

For the central Pacific Ocean, Ono and Addison (2013) report increased abundances of pelagic taxa, such as scombrids, at ~600 cal BP on Atafu Atoll, Tokelau. Across the eight excavated 1m2 units, scombrids were ranked third after scarids and acanthurids, accounting for 12.1% of total MNI. The most recent deposits were dated to ~200 cal BP, and had higher abundances of inshore taxa. Some skipjack were identified at this site, but abundance was not reported. Weisler et al. (2016), documented three cultural phases on Ofu Island, American Samoa, with first occupation at 2700- 1500 cal BP. Skipjack were only identified in the post-800 cal BP deposits and while this taxon was

174 low ranking overall, the timing of tuna in the sequence closely aligns with the Atafu Atoll data. Lastly, at Si‘utu, Savai‘i Island, Samoa, a late prehistoric site, occupied post ~650 cal BP, Ishimura and Inoue (2006) reported scombrid remains (number of identified specimens [NISP]=19) although the abundance and distribution of skipjack, while identified to taxon, was unclear. The data available for the central Pacific Ocean is not as comprehensive, but scombrids and in some cases K. pelamis— where specific identifications have been reported—are more prevalent in assemblages that post-date ~850-650 BP while, at a similar time, this taxon is decreasing at western Pacific sites (Ishimura and Inoue 2006; Masse et al. 2006; Ono and Addison 2013; Ono and Intoh 2011; Weisler et al. 2016). More archaeological data are needed to explore these regional trends, particularly from central Pacific locations.

Tuna biology, fisheries and climate variability

Approximately 70% of the world’s annual tuna catch is from the Pacific Ocean (Lehodey et al. 1997). Continued capture of skipjack and yellowfin through intensive commercial fishing have had substantial consequences given their prominent role in the food web (Evans et al. 2015). Primary productivity in the tropical Pacific is strongly influenced by ENSO events, which influence vertical and horizontal habitat conditions (Lehodey et al. 1997; Nicol et al. 2014), and while these climatic effects are global reaching, the strongest signatures have been measured between 10ºN and 10ºS in the tropical Pacific Ocean (Nicol et al. 2014). Tropical tuna species such as skipjack and yellowfin have higher recruitment during El Niño, compared to subtropical albacore species (Thunnus alalunga), which have higher recruitment during La Niña (Lehodey et al. 2003). Preferences in habitat between tuna species results in differential responses to climate variability and ocean conditions (Nicol et al. 2014).

Skipjack is the primary focus, given its prominence in the Ebon Atoll archaeological assemblages. Spawning occurs throughout the year, with no obvious seasonal trends; minimum size at maturity is around 35-40 cm fork length (FL) and ~1-3 kg, and maximum FL is ~108 cm with weights of 32.5 to 34.5 kg; this is relatively small compared to Thunnus spp. (e.g., bigeye and yellowfin) with maximum recorded FLs of 200+ cm and weights of ~180-200 kg (Ashida et al. 2010; Collette and Nauen 1983; Hoyle et al. 2011). They are a schooling species, foraging during the day for fish, squid and crustaceans, which are usually a few millimeters to several centimeters (Lehodey 2001). Skipjack swim constantly as a means of counterbalancing their negative buoyancy, and therefore travel significant distances, resulting in high foraging demands. Temperature and dissolved oxygen concentration are highly correlated with tuna behavior, given the specialized morphological and physiological adaptations that enable thermoregulation and high efficiency oxygen extraction (Ganachaud et al. 2013). Skipjack occur in waters ranging between 20 and 30ºC, with a lower limit 175 of 15ºC, and as optimal spawning conditions peak between 26 and 30ºC, there are higher larval abundances in the western and central Pacific Ocean, which increase tuna recruitment (Ganachaud et al. 2013; Hoyle et al. 2011; Lehodey 2001; Schaefer 2001). Seasonal factors can extend skipjack range, for instance the development of a seasonal fishery off the coast of Japan around summer (May to August) due to sub-tropical warming of surface waters (Lehodey 2001). However, highest catch per unit effort (CPUE) comes from the surface mix layer of the western equatorial and subtropical Pacific Ocean where SST is more consistently ~28-29ºC. Maximum skipjack biomass is situated in the Pacific warm pool, a region that features low primary productivity rates, with the exception of coastal waters, in contrast to the central equatorial Pacific cold tongue, a strong divergent upwelling that produces high levels of primary productivity (Lehodey et al. 1997; Nicol et al. 2014). Tuna abundance throughout the Pacific Ocean is counterintuitive due to the relationship between primary productivity and tuna biomass. The warm pool provides skipjack with the most suitable environmental conditions (i.e. temperature, oxygen and water clarity), but lower secondary production than the eastern Pacific, which has less optimal habitats (Lehodey 2001).

Historically, during La Niña phases, the Pacific warm pool contracts and sits around the Philippines to 160ºE in a low primary productivity state, which corresponds to a westward displacement of the cold tongue (extending as far west as 160ºE). In contrast, during El Niño phases, the cold tongue is displaced east to around ~180º, which extends the warm pool into the central Pacific thus increasing primary production between the Philippines and 160ºE-180º (Lehodey 2001; Lehodey et al. 1997). The location of the warm pool shifts according to these ENSO phases, and influences the distribution and abundance of skipjack, but seasonal factors also have an impact on the position of the warm pool (Lehodey et al. 1997; Nicol et al. 2014). During the La Niña periods of 1988-1989, late 1990 to early 1991, and 1995, the purse seine fleets remained west of 160ºE, west of the RMI, but during El Niño (1992-1994), fishing efforts were extended east to 160ºW, the approximate location of the Cook Islands (Lehodey et al. 1997: 715-716). Following the 2009-2010 El Niño event, higher skipjack recruitment occurred in 2010, but as a result of the high intensity La Niña event that developed in 2010-2011, lower skipjack recruitment was reported in early 2011 (Lehodey et al. 2011). Long-term, time series data has the potential to refine our understanding of the complicated relationship between tuna fisheries and these climatic variables.

Pacific Ocean late Holocene palaeoclimate records

Relevant palaeoclimate records are reviewed for the last ~2000 years, including a discussion of the MWP or Medieval Climate Anomaly (MCA), LIA, frequency of El Niño and La Niña events, changes in SSTs, and shifts in the Intertropical Convergence Zone (ITCZ). These hydroclimate records are

176 still widely contested, especially marine palaeo-ENSO indicators, however, more recent research has started to address these inconsistences (e.g. Griffiths et al. 2016; Rustic et al. 2015; Yan et al. 2015).

There is significant variability in the reported date ranges of the MWP or MCA (~1050-500 cal BP) and LIA (~500-100 cal BP); we report the upper and lower limits to capture this variability (e.g. Griffiths et al. 2016; Jones et al. 2001; Nunn 2012; Rustic et al. 2015). Nunn (2000a, b) argues the transition between the two periods brought rapid cooling, sea-level fall, and increased precipitation in certain areas of the Pacific basin. This has been supported by Oppo et al. (2009), who reported warmer SSTs between ~950 and 700 BP—during the MCA—and 0.5 to 1ºC colder than modern averages in the warm pool during the LIA, a decrease in SST that began ~650 cal BP and peaked in the middle of the LIA. In contrast, Allen (2006) considered late Holocene climate variability in the central Pacific by reviewing palaeoclimate records and suggests that while the rest of the world was experiencing the MCA, conditions in the tropical Pacific were cool and possibly dry, and during the LIA the central (equatorial) Pacific was comparatively warm and wet, with stormy conditions more common.

Most recently, Griffiths et al. (2016) reconstructed the western Pacific hydroclimate using speleothem records and suggested that a poleward expansion of the ITCZ and weakening of the Pacific Walker circulation (PWC) occurred between ~950 and 450 cal BP, in contrast to an equatorial contraction of the ITCZ and strengthening of the PWC from ~450 – 50 cal BP. Shifts in the ITCZ, which occur in a north-south direction, broadly impact precipitation and the records from Flores—in the western Pacific—suggest a drier climate at the following periods: ~1950-1550 cal BP; ~950-550 cal BP, which roughly corresponds with the MCA, and ~50 cal BP-present and a wetter climate at ~1550- 950 cal BP and ~550-50 cal BP (Griffiths et al. 2016). Records from Washington Island (or Teraina Island, northern Line Islands) in the central Pacific Ocean indicate wet conditions during the MCA (Sachs et al. 2009). This supports the model proposed by Yan et al. (2015) for an ITCZ expansion during the LIA and contraction during the MCA. The PWC, an east-west pressure gradient, alters trade winds, deep convection, extends the reach of ENSO events, and can impact global temperatures (Griffiths et al. 2016). Records suggest the western Pacific was generally drier during the MCA, whereas the central and eastern Pacific experienced wetter conditions, which can be equated to a weakening PWC producing a more ‘El Niño-like’ mean state. Conversely, the western Pacific was generally wetter during the LIA and the central and eastern Pacific experienced drier conditions, similar to modern La Niña events, indicating strengthening of the PWC (Griffiths et al. 2016; Thompson et al. 2013; Yan et al. 2011). These trends described by Griffiths et al. (2016) are in opposition to some earlier published ENSO reconstructions that suggest the MCA was associated

177 with ‘La Niña-like’ conditions, which produced wetter conditions in the central Pacific (e.g. Cobb et al. 2003; Oppo et al. 2009).

While marine palaeo-ENSO signals are still widely contested, a recent reconstruction of eastern Pacific SSTs by Rustic et al. (2015) suggests that the MCA was associated with warm SSTs, consistent with Griffiths et al. (2016) western Pacific hydroclimate records. Critically, ‘modern observations do not yet distinguish between the PWC’s response to global warming’, which can confound interpretation of the palaeoclimate records (Griffiths et al. 2016: 5-6), and additionally, inconsistencies in the palaeoclimate records themselves, further complicate our understanding of long-term tropical Pacific Ocean climate variability and its associated effects on tuna fisheries (Yan et al. 2015).

Sites and Samples

Beginning just north of the equator and 3850 km southwest of Hawaiʻi, the RMI is comprised of 29 atolls and five limestone islands without a lagoon (total land area of 181 km2), dispersed over 2,000,000 km2 of ocean (Figure 1). There is a pronounced north-south rainfall gradient across the RMI, with annual precipitation at ~1500 mm in the dry north, and ~4000 mm in the wet south, where Ebon Atoll is situated at the southernmost end of the archipelago. Ebon Atoll is comprised of 22 islets (total land area of 5.75 km2), encircling a 104 km2 lagoon, and a 22 km2 reef platform. The reef to terrestrial land area is high (4:1), and hosts 800 fish taxa within 60 m ocean depth (Myers 1999).

Weisler initiated a research program in 1993 to assess regional variation in the RMI archaeology as it relates to the north-south rainfall gradient, with broad project aims addressing chronology, sea level change and islet development, material culture, marine subsistence, terrestrial production, human impacts, and anthropogenic landscape change (Christensen and Weisler 2013; Pregill and Weisler 2007; Weisler 1999a, b, 2001a, b, c, 2002; Weisler and Swindler 2002; Weisler et al. 2012). Similar to the general chronology of atoll emergence for the RMI (Dickinson 2003; Kayanne et al. 2011; Weisler et al. 2012), 2000 BP appears to be the earliest date Marshall Islands atolls were inhabitable— although some reef islands are appreciably older (Kench et al. 2014)—and this matches closely with the earliest human colonization dates for Utrōk Atoll (Weisler 2001b), Majuro Atoll (Kayanne et al. 2011), Maloelap Atoll (Weisler 1999a: 640; Weisler et al. 2012: 117), and Ebon Atoll (Weisler et al. in prep).

Two field seasons (1995-1996, 2011-2012) of survey and excavation were directed by Weisler (2002) on Ebon Atoll. Ebon Islet as the largest islet, with the most developed Ghyben-Herzberg fresh water lens, hosts the most extensive village and horticultural systems and the oldest habitation sites (Weisler 2001a; Weisler et al. 2012). With 11 documented archaeological sites on Ebon Islet, we focus on 178

MLEb-1 and MLEb-5 (Figure 2), as these sites provide well-preserved early, middle, and late period prehistoric faunal assemblages. Only four AMS radiocarbon dates from the sites discussed here were included, but the comprehensive Ebon Atoll chronology developed from 59 radiocarbon and U-series dates (Weisler et al. in prep) supports a model of continuous occupation over two millennia. The dates, reported here, are all on coconut husk or shell and calibrated to two standard deviations (with median reported) using IntCal09 curve and the OxCal program (Reimer et al. 2009). All excavated sediments were wet-screened through 6.4 mm mesh, and only TP 6 and TP 17 (MLEb-1) and TP 13 (MLEb-5) were sieved using 3.2 mm mesh. As very few scombrid bones were reported in the 3.2 mm screens, these sampling protocols did not influence the observed trends. However, variability between assemblages screened with 6.4 mm and 3.2 mm mesh and those screened with only 6.4 mm mesh are discussed in the results section.

MLEb-1

Site MLEb-1 covers 30 m2 between 25 m from the lagoon beach to 200 m inland and, along with other habitation sites, including MLEb-5, forms a near-continuous prehistoric village that runs parallel to the lagoon shore of Ebon Islet for nearly 2 km. Excavated 40 m inland of the lagoon shore and 20 m northwest of the current primary school, a 2 x 2 m unit (TP 17, 18, 19 and 20, each 1 m2) was excavated over a low artificial mound developed by successive living floors or coral pavements. Cultural deposits were encountered to a depth of 1.75 m. Three main prehistoric layers, capped by a ~4 cm thick layer containing historic artefacts and sparse midden, were encountered. Layer I, ~60 cm thick, consists of black (Munsell 5Y2.5/1, taken moist in shade) gravelly sand with dense prehistoric midden and gravel transported for village pavements. This layer, divided into an upper layer IA, was darker and more compact than IB. Layer II, also divided into an upper IIA and lower IIB due to increasing sand and mottled pockets with depth, was ~118 cm thick and a very dark grey (5Y3/1) sandy gravel midden. Layer IIIA is grey (5Y5/1) sand that is almost completely sterile. Radiocarbon age determinations from Layer IIIA of TP 17 and 19 were 925-790 cal BP (median = 855 cal BP, OZP-927) and TP19/12; IIIA 920-775 cal BP (median = 850 cal BP, OZP928), respectively. These layers overlie palaeo-beach deposits of coarse sand and coral gravel, encountered to ~ 190 cm below surface.

TP 6 is located ~150 m inland of the lagoon shore and cultural material was encountered to a depth of ~1 m. Three layers were each divided into sub-layers based on differences in sediment texture, color and compaction. Layer IA was a black (5Y2.5/1), gravelly sand matrix with dense water- rounded coral gravel and abundant shellfish midden, bone and artefacts. Layer IB had similar cultural content, but with less gravel and lighter sediment color (5Y3/1, very dark grey). Layer IIA was a dark grey sand (2.5Y4/1) with combustion features with less shellfish midden, bone and artefacts, grading 179 to Layer IIB which was light grey (2.5Y7/1) with dispersed charcoal and a combustion feature, otherwise relatively sterile. Layer III was divided into an upper Layer IIIA (5Y7/1, light grey) that was nearly sterile, but with dispersed charcoal and few oven stones. Layer IIIB (2.5Y7/1, light grey) was completely sterile sand differentiated from Layer IIIC (7.5YR8/2, pinkish white) which was slightly cemented, but otherwise similar. A radiocarbon age determination towards the base of the cultural deposit, from within Layer IIIA, dated to 1895-1730 cal BP (median = 1840 cal BP, OZP925).

MLEb-5

Site MLEb-5 is ~670 m east of MLEb-1, along the main village path. The site is situated ~40 to 250 m from the lagoon beach. A 3 x 5 m unit (TP 1, 13 and 15-27, each 1 m2) was excavated ~120 m from the lagoon shore. The main cultural deposit, Layer I, consisted of dense, water-rounded gravel in a sticky, gravelly black (5Y2.5/1), sandy matrix extending to ~0.5 m below surface in most TPs. Aside from the fish bone reported here, there was dense marine shellfish, plentiful shell artefacts (adzes, beads, worked pearlshell, arm rings, fishhook tabs), coral abraders, and combustion features. The sterile subsoil (Layer II), was a pinkish white (7.5YR8/2) sand. One radiocarbon age determination returned the oldest dated habitation remains for the atoll at 2295-1995 cal BP (median = 2085 cal BP, OZP932).

Methods

Identification and quantification protocols

Fish remains were identified to the lowest taxonomic level using the comparative collection curated at The University of Queensland archaeology laboratory (Lambrides and Weisler 2015b: 57; Weisler 2001b: appendix 3, for a description of the fish comparative collection). All cranial and post-cranial fish bone elements were attempted for identification (Lambrides and Weisler 2015a); genus- and species-level identifications were assigned cautiously to avoid over-identification given the richness of tropical western Pacific marine fish species (Driver 1992; Gobalet 2001; Lambrides and Weisler 2016; Wolverton 2013). Species-level identifications of Katsuwonus pelamis were achieved using few cranial elements (i.e., basypterygia, dentaries, scapulae, and quadrates), but caudal vertebrae were found to be the most useful, particularly C21-C25. Taxonomic abundance was quantified by NISP and MNI, with MNI values quantified using established zooarchaeological protocols for vertebrate fauna (Grayson 1984; Reitz and Wing 2008). For each reported cultural layer, MNI was calculated using the most frequent non repetitive element (NRE) for each side (left or right) for cranial elements and for post cranial elements, type and number along the vertebral column was used. For the units sampled with 6.4 and 3.2 mm mesh screens, the assemblages for each cultural layer were pooled prior

180 to MNI calculation. Fish bone size was considered in all MNI calculations. Contiguous TPs were consolidated as single deposits to minimize aggregation issues.

Statistical analyses and measurement protocols

Relative taxonomic abundance was utilized to evaluate variation in composition of fish bone assemblages that extend from the initial human colonisation of Ebon Atoll to the historic period; specifically, to determine the contributing factors driving the variation over time in the relative taxonomic abundance of scombrids, particularly Katsuwonus pelamis. All TPs from MLEb-5, represent the early prehistoric period (~2085 cal BP, median date), MLEb-1, TP 6, the middle prehistoric period (~1840 cal BP, median date), and MLEb-1, TPs 17-20, the late prehistoric and historic periods of atoll occupation (~850 cal BP, median date – historic). All statistical analyses were conducted using MNI and NISP values. As similar trends were revealed, MNI values were used for comparability with other Pacific Island assemblages. All statistical analyses were completed using Past, version 3.11 (Hammer et al. 2001) and IBM SPSS Statistics, version 20.0.

For all richness and evenness calculations taxa were aggregated based on mutually exclusive categories. NTAXA (number of taxa) was calculated to assess taxonomic richness for each cultural layer. Shannon-Weiner index of diversity (H′) and Shannon’s evenness (E) are measures of evenness, the proportional representation of taxa in an archaeological assemblage H’ values can range between 0 and a theoretical maximum of 5, but commonly values are between 1.5 and 3.5, with greater species diversity and richness indicated by higher H’ values. E values range between 0 and 1, assemblages dominated by single taxa are indicated by 0 and those that are rich and even are closer to 1 (Lyman 2008; Reitz and Wing 2008). Simpson’s index of diversity (1-D) allowed an assessment of dominance, as values ranging between 0 and 1, low values indicate assemblages dominated by a single taxon (Magurran 2004). As NTAXA and Shannon’s indices can be influenced by sample size (Faith 2013), Fisher’s α was calculated to examine diversity as it is considered to be independent of sample size effects (Hayek and Buzas 2010). By tracking the occurrence of taxa represented by single individuals, Fisher’s α provides a measure of overall diversity (Karlson et al. 2004). After Harris et al. (2016), chord distance analysis was employed using relative abundance data grouped by NTAXA and CA using non-aggregated (i.e. not aggregated by NTAXA) relative abundance data. Chord distance analysis is a measure of taxonomic dissimilarity and is useful for examining the degree of taxonomic change between successive cultural layers (Faith et al. 1987; Legendre and Gallagher 2001). Values range from 0 for assemblages with similar relative taxonomic abundances to 2 for assemblages with no taxa in common. Chord distance was calculated across sequential pairs√ of cultural layers, which were ordered chronologically within and between sites (e.g. between MLEb-5

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I and MLEb-1 TP 6 IIIA, MLEb-1 TP 6 IIIA and IIA, etc.). CA allowed the associations between taxonomic composition and site/cultural layers to be examined. These statistics have been successfully implemented to examine variations in taxonomic composition of archaeological faunal and archaeobotanical assemblages (Faith 2013; Harris et al. 2016; Wright et al. 2015).

Mean trophic level (MTL) for each cultural layer was estimated using MNI following the formula adapted by Reitz (2004: 70) after Pauly and Christensen (1995) (see also Wing and Wing 2001). Trophic levels were assigned using data obtained from FishBase (Froese and Pauly 2016). Assessments of mean trophic level have been utilized to assess the productivity and overall sustainability of marine fisheries (e.g. Pauly et al. 1998; Pauly et al. 2000). The limitations of trophic level analysis have been discussed in both modern fisheries literature (e.g. Branch et al. 2010) and archaeological contexts (e.g. Carder and Crock 2012), given the importance of tracking true ecosystem abundance rather than using proxy catch-based trends. Archaeologically, it is important to demonstrate whether declines in trophic level actually reflect human overexploitation of the fishery and to be aware of the configuration of the marine environments as alterations through time can influence trophic interactions (Keegan 2009). Here, we do not use the MTL data to directly assess fishery productivity or food web stability as this would require additional ecological and zooarchaeological datasets, rather, this data is used to examine whether there is variation in the feeding guilds targeted through time. The relationship between any given taxon and trophic level is complex, for instance, fish size is not always an accurate indicator of trophic level (e.g., Jennings et al. 2001; Layman et al. 2005; Yasuno et al. 2016). Therefore, results of the MTL analysis should be treated as indicative of broad assemblage trends rather than a complete representation of trophic level through time.

In addition to MTL, we provide a preliminary assessment of trophic interactions through time by testing Houk and Musburger’s (2013) model of modern coral reef stability in response to anthropogenic presence in the RMI. They report a higher biomass of large-bodied piscivores in the absence of major human populations, and under significant human exploitation a doubling in the density and biomass of small-bodied surgeonfish/unicornfish and a halving of large-bodied parrotfish (Houk and Musburger 2013: 23). In testing this model, several restrictions were dictated by sample size. Because there were insufficient samples from MLEb-1, TP 6 (6.4 mm) and from the 3.2 mm assemblages (all sites), trends between successive cultural layers for each site (MLEb-1 and MLEb- 5) could not be tested, and given the limited number of measurable acanthurid bones, alterations in abundance rather than size had to be assessed. Given these parameters, the most suitable approach for testing Houk and Musburger’s (2013) model was a comparison of early (MLEb-5, all TPs) and late (MLEb-1, TPs 17-20) assemblages. Alterations in fish bone size have been assessed according

182 to methods described by Lambrides and Weisler (2015a). Scombrids identified to species, in this case, Katsuwonus pelamis, and scarids aggregated at the family-level, were used for this analysis. There was insufficient sample size to consider the specimens identified to genera (Calotomus spp., Chlorurus spp., Hipposcarus longiceps, and Scarus spp.) individually, and while there is a similar distribution of these reported genera in the early and late assemblages, the aggregation of scarids at the family-level is problematic so the results for this taxonomic group are considered preliminary. Vertebrae were the most highly represented element for the scombrids and scarids and measurement protocols follow Lambrides and Weisler (2015a: 58). Three measurements were recorded for each vertebrae M1, M2, and M3 (Lambrides and Weisler 2015b: Figure 3). Changes in fish bone size were assessed using both Kruskal-Wallis one way analysis of variance and effect size (η2) (Lambrides and Weisler 2015b) and bootstrapping around the median (Giovas et al. 2016) to determine whether there are statistical differences between the early (MLEb-5, all TPs) and late (MLEb-1, TP 17-20) assemblages.

Results

Tables 1 and 2 provide the quantification of fish remains from sites MLEb-1 and MLEb-5, all TPs, and 6.4 and 3.2 mm screened samples. The MNI and NISP values have been aggregated by site or, in the case of MLEb-1, spatially distinct areas of the site (TP 6 and TPs 17-20) for brevity in the text (Appendix C, provides taxonomic assignments and relative abundance grouped by site and cultural layer). Across all sites (6.4 mm only), 5959 (NISP) specimens were identified to taxon, comprising 817 (MNI) individuals; for the 6.4 mm units that also had 3.2 mm sampled assemblages, 3995 (NISP) specimens were identified to taxon, comprising 657 (MNI) individuals. Identification rates were high, with 43.1% of recovered fish specimens identified from the 6.4 mm only assemblages, and 13.2% of the 6.4 mm and 3.2 mm sampled assemblages. High identification rates were likely facilitated by the comprehensiveness of the comparative collection and consideration of all cranial and postcranial elements for identification. For example, 95% of K. pelamis identifications were on vertebrae. All statistical analyses reported below were completed using MNI values for comparability with other Pacific Island assemblages, but statistical analyses utilizing NISP values were tested and revealed similar trends.

Across all cultural layers of the MLEb-1 assemblages (6.4 mm samples only), the middle and late prehistoric assemblages are rich and even, with no evidence of taxonomic dominance (Table 3). However, trends for TP 6 (MLEb-1) are likely influenced by sample size effects. This is compared to MLEb-5, which dates to the earliest occupation phase, with lower values of 1-D, H’, E, and Fisher’s ɑ reported. These higher dominance values may be indicative of the increased relative abundance of tuna compared to other taxa at the site. The 6.4 and 3.2 mm sampled assemblages (all sites), were 183 rich and even, with no evidence of taxonomic dominance, similar to the MLEb-1 6.4 mm sampled assemblages. These outcomes are influenced by the occurrence of taxa represented by a single individual, particularly the increased identification of rare taxa for the 3.2 mm samples.

Chord distance analysis (Figure 3) provided a means of assessing the dissimilarity between cultural layers at each site (MLEb-5) or area of the site (MLEb-1 TP 6 and TPs 17-20). For the 6.4 mm sampled assemblages, limited change in faunal community composition across cultural layers for each site was documented. However, the greatest changes are reported across the transition from MLEb-1, layers IIB and IIIA (TPs 17-20) and layers IIA and IIIA (TP 6), a trend that can be attributed to the significant decline in NTAXA in the basal layers (Table 3). The deposits were also ordered temporally based on radiocarbon dates to determine any further patterning in the data. Inter-site comparisons were hindered by the low number of individuals represented in the basal layers, resulting in high accounts of dissimilarity between temporally ordered site transitions. Generally, there was less dissimilarity between sequential pairs of cultural layers that were associated with the historic and late prehistoric periods. When comparing the assemblages sampled by 6.4 mm only and those sampled by 6.4 and 3.2 mm screens, less dissimilarity between successive pairs of cultural layers is apparent, which likely relates to the higher identification of rare taxa for the 3.2 mm samples.

To further elucidate the outcomes of the diversity indices and chord distance analysis, temporal variation in taxonomic composition at MLEb-1 and MLEb-5 were considered using CA. We investigated whether variation in the abundance of tuna at the sites may be contributing to these documented trends. For 6.4 mm only assemblages, Figure 4a illustrates the CA on fish bone abundances, with axis 1 accounting for 35.5% of variance and axis 2 accounting for 12.7% of variance (Appendix D, provides the CA raw data). Assemblages with positive axis 1 scores are associated with a higher number of taxonomic categories and are generally late prehistoric and historic. In contrast, assemblages with negative axis 1 scores are most associated with Scombridae and K. pelamis and generally early prehistoric. Seriola sp. is represented by one individual from MLEb-5. Figure 4b illustrates the broad changes in axis 1 scores through time; however, scores for layer IIIA (MLEb-1: TP 6 and TPs 17-20) are likely driven by low analytical samples, as a wide range of taxa, each represented mostly by a single individual, are reported for these cultural layers. Middle and late prehistoric assemblages are generally characterized by negative axis 1 scores that increase through time until they peak in the historic period. For the 6.4 mm and 3.2 mm assemblages, axis 1 accounts for 18.0% of variance and axis 2 accounts for 16.0% of variance (Appendix D, provides the CA raw data). While less pronounced than trends noted for the 6.4 mm only sampled assemblages, due to the low relative absence of tuna remains in TP 17 (MLEb-1), Scombridae, K. pelamis, and Thunnus spp.

184 are more associated with earlier prehistoric assemblages as are sharks (Selachii, Carcharhinus spp., Nebrius ferrugineus), however, the MNI is low for these taxa.

MTL tends to be highest for the earlier prehistoric assemblages, with a broad decline in MTL over time noted across the sites (Table 4). The highest MTL was reported from the MLEb-5 (6.4 mm only) assemblage, which likely relates to the high abundance of K. pelamis. We also report a corresponding decline in the relative abundance of this taxon over time (MLEb-1 TP 6 and TPs 17-20) compared to scarids, serranids, acanthurids, balistids, and holocentrids (Appendix C). MTL was not correlated with sample size, with the exception of TP 17 (6.4 mm and 3.2 mm); however, when layer IIIA—due to small sample size—was excluded from the Spearman’s rho calculations, a non-significant result was reported (rs = 0.60, p = 0.23) (Table 4).

Preliminary assessments of trophic interactions through time in response to anthropogenic factors were tested using Houk and Musburger’s (2013) model of modern RMI coral reef stability. Changes in fish bone size were assessed using both Kruskal-Wallis one way analysis of variance and effect size (η2) and bootstrapping around the median (Appendix E). Due to insufficient sample size, changes in acanthurid bone size could not be tested, but acanthurids are more associated with historic and late prehistoric assemblages (Table 5). For the scarids, median caudal measurements (M1, M2, and M3) for C1 and C2, were compared between the early (MLEb-5, all TPs) and late (MLEb-1, TPs 17-20) deposits, with overlap at the 95% and 99% levels reported, suggesting no statistical difference between the assemblages, which is further supported by non-significant Kruskal-Wallis test results. These outcomes are also influenced by the aggregation of genera identifications at the family-level. K. pelamis, median caudal measurements (M1, M2, and M3) for C21-C25 produced variable outcomes, but at this stage there is no evidence to support size change between the early and late assemblages.

Discussion

Alterations in the Ebon Atoll prehistoric tuna fishery

Analyses of two sites—MLEB-1 and MLEb-5—on Ebon Islet, have provided a continuous ~2000 year occupation sequence that tracks alterations in fish exploitation from initial colonisation of the atoll. Skipjack are more associated with the earliest prehistoric assemblages, and the highest MTL was also reported from the earliest habitation context at MLEb-5 where skipjack was ranked highest. A broad decline in MTL is noted over time, and likely relates to the declines in the relative abundance of skipjack and specimens only identified to Scombridae, when compared to scarids, serranids, acanthurids, balistids, and holocentrids. Based on the Pacific Islands archaeological studies reviewed previously, the MLEb-5 Ebon Islet site, provides the highest contribution to total MNI by scombrids 185 for any recorded site in the region, but we acknowledge that this is likely influenced by the large area excavated, comprehensive nature of the comparative collection, range of cranial and postcranial elements used for taxonomic identification, screen sizes used with either wet and/or dry sieving, taphonomic condition of the bone, and experience of the analyst. Comparatively, fish bone assemblages from the other excavated islets on Ebon, such as the temporarily-occupied campsite on Moniak Islet and the small village site on Enekoion Islet, reported a low contribution of scombrids to the total fish catch (Harris et al. 2016). The distinctions in the spatial distribution of this resource are potentially a reflection of both site function and the assigned importance or value of scombrids. Ebon Islet has the largest village on the atoll (prehistorically and today) and it is where the Irooj (chief) currently lives, so it is possible, as Buck (1930) described for Samoa, that skipjack was also a high status food in the Marshall Islands. Both social and/or environmental factors were considered possibilities for driving these observed trends in archaeological scombrid abundance, but with a particular focus on skipjack fishing.

As a means of assessing coral reef stability in response to human occupation on Ebon Atoll, we tested Houk and Musburger’s (2013) model that was developed using modern observations in the RMI. A higher biomass of large-bodied piscivores in the absence of major human populations was reported, and under significant human exploitation a doubling in the density and biomass of small-bodied acanthurids and a halving of large-bodied scarids. For these reasons, we assessed alterations in skipjack size over time (as a large-bodied piscivorous taxon), and using scarid and acanthurid remains, explored the potential for trophic cascades or other markers of human impacts to coral reefs driving this archaeological trend in skipjack abundance. Based on the available data, Houk and Musburger’s (2013) model was not supported, and while we broadly see a decline in the relative abundance of scombrids, specifically skipjack, there is no evidence to support a change in fish size between the early and late assemblages. Houk and Musburger (2013: 30-32) reported reductions in the biomass of sharks and large-bodied piscivores due to human predation, with associated prey release of acanthurids, and while acanthurids were more prominent in the historic/late prehistoric archaeological assemblages, there was no evidence for a decline in scarid body size. While scarids are extremely susceptible to overfishing, given their high visibility day and night and preference for shallower inshore reef habitats, these life-history traits do not directly predict the probability of overexploitation for all scarid species. For instance, slow growing and large-bodied species are the most susceptible to stock depletion, but resilient life history strategies, as displayed by the tan-faced parrotfish (Chlorurus frontalis), can mitigate these threats and decrease the likelihood of overexploitation (Taylor et al. 2014). For these trends to be comprehensively assessed on Ebon Atoll and broadly across the Pacific Islands, more specific taxonomic identifications are required.

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Based on the available samples and given the limitations discussed previously regarding the scarid and acanthurid size analysis data, at this stage there are no obvious indications of significant human impact to the inshore reef taxa Houk and Musburger (2013) identified as being susceptible, nor is there evidence for alterations in food web stability influencing skipjack abundance through time. As skipjack are a migratory species that congregate in large schools, it is unlikely that localized human predation pressure could produce the reported outcomes; that is, there was no indication that skipjack body size varied between the early and late assemblages and the frequency of these remains archaeologically does not suggest intensive exploitation of the skipjack fishery through prehistory. Thomas (2014) has stated that there is little evidence that prehistoric atoll dwellers needed to implement conservation strategies to ensure marine resource availability, due to the size and productivity of reef habitats available for resource extraction (see also Weisler 2001b). Expanding on these principles, Giovas (2016) suggested that sustainability is not merely a function of the abundance of marine resources available for exploitation, but flexible foraging practices that target a broad range of taxa, as well as the resilience and structure of exploited marine environments are all key to long- term sustainability on small islands (see also Campbell and Butler 2010; Reitz 2014). Trends documented by Houk and Musburger (2013), may actually reflect a decline in reef resilience that has developed from a combination of millennial-long human-environment interactions (e.g. Erlandson and Fitzpatrick 2006; Rick et al. 2013) and the effects of modern climate change (e.g. Graham et al. 2013; Hughes et al. 2007; van Oppen et al. 2015). However, McKechnie et al. (2014: E807) described a 10,000 year archaeological sequence of Pacific herring exploitation as ‘an example of long-term sustainability and resilience in a fishery known for its modern variability’ that, today, is associated with industrial harvesting and influenced by climatic factors, disease, and alterations in predator-prey interactions.

The changes in relative abundance of skipjack tuna could potentially be explained by a shift in capture strategies through time. For instance, a decrease in the relative importance of offshore trolling relative to other inshore strategies, such as netting, spearing, and fish traps. Historic records describe large schools of skipjack entering the lagoon that were surrounded by coconut frond sweeps, then driven to shore (Erdland 1914; Krämer and Nevermann 1938; Tinker 1950); this capture method is practiced today on Ebon. For the Ebon archaeological assemblages, there is limited evidence to support changes in capture strategy or shifts from targeting offshore to inshore resources through time, given taxonomic composition remains relatively consistent both temporally and spatially, with the exception of scombrid relative abundance, and there are no indications of relative declines in associated ‘offshore’ taxa. Fishing gear included one trolling lure fragment, two whole rotating pearlshell fishhooks and several fragments, so it is not possible to meaningfully discuss chronological

187 trends in these artefacts. As outlined previously, ethnographic and historic accounts of tuna fishing in the Pacific, and specifically the RMI, indicate the economic, cultural, and social importance of this resource and we are not aware of any instance of avoiding tuna for cultural reasons. Given tuna are migratory fish, archaeological trends may indicate changes in the availability of this particular resource through time

The western and central Pacific tuna fishery and ENSO variability over the last 2000 years

Historical ecology is considered to be ‘the use of historic and prehistoric data to understand ancient and modern ecosystems, often with the goal of providing context for contemporary conservation’ (Rick and Lockwood 2013: 46-47). Using a historical ecological approach, we evaluated the Ebon Atoll archaeological data, provided links to regional trends in the western and central Pacific Islands archaeological tuna fishery data, and assessed these within the context of palaeoclimate records, which track hydroclimate variability over the last 2000 years, and recent historic capture records, which document the impact of ENSO on skipjack abundance and range throughout the tropical Pacific Ocean. This approach tested the applicability of utilizing archaeological records that document the exploitation of migratory fish to assess human responses to climate variability, both locally and to establish proxy evidence for regional models. Archaeological data from Fais Island (western Pacific) and Atafu Atoll, Ofu Island, and Savai‘i Island (central Pacific) was considered in addition to the Ebon Atoll data (Figure 1). With the exception of the Ofu Island assemblage, only family level identifications were reported by analysts, and as discussed previously, responses to ENSO variability differ depending on the species of tuna, and while problematic for considering regional trends, this does not detract from highlighting the utility of this approach.

Given the predominance of skipjack in the Ebon Atoll archaeological deposits, broad trends in historic skipjack abundance and range as they relate to ENSO variability as well as relevant palaeoclimate data is summarized briefly prior to evaluating the regional archaeological context (Griffiths et al. 2016; Lehodey 2001; Lehodey et al. 1997; Lehodey et al. 2011; Nicol et al. 2014; Thompson et al. 2013; Yan et al. 2011). The following trends relate to the western Pacific, but inverse relationships were noted for the central and eastern Pacific (Griffiths et al. 2016: Figure 4). Drier climate was recorded at ~1950-1550 cal BP and ~950-550 cal BP, with the latter period roughly corresponding to the MCA; these periods were associated with El Niño-like conditions. Based on historic records, these conditions bring an eastward displacement of the warm pool to around ~180º, corresponding to a high productivity state that expands modern commercial fisheries efforts east near 160ºW (Figure 1). Wetter climate was recorded at ~1550-950 cal BP and ~550-50 cal BP, with the latter period roughly corresponding to the LIA, similar to La Niña-like conditions, which historically see contraction of the warm pool to west of 160ºE; given its low productivity state, modern commercial fisheries 188 commonly remain west of 160ºE. There was variability within these hydroclimate records and this needs to be considered when correlating this data with time averaged archaeological data (Figure 1).

On Ebon Atoll, skipjack are mostly associated with the earliest prehistoric assemblages, particularly MLEb-5 (~2085 cal BP), and this roughly corresponds to the dry climatic conditions and potential El Niño-like mean state that occurred between ~1950 and 1550 cal BP. While negative impacts on catchability have been reported in the west Pacific Ocean during El Niño phases, at the warm pool- cold tongue convergence zone, which is associated with an eastward displacement of the warm pool, there are increases in catchability (Lehodey 2001). Ebon Atoll is located closer to this convergence than Fais Island. This could have contributed to the comparatively delayed increase in scombrids on Fais Island between ~1550 and 1150 BP (Ono and Intoh 2011), as eventually El Niño events have a favorable impact on recruitment in the west (Lehodey 2001). However, these alterations in tuna recruitment usually operate on much smaller time scales (monthly/annually), and depend on ENSO intensity (Lehodey et al. 2011), making archaeological detection challenging. Nonetheless, given the location of Fais Island, even during La Niña events when the warm pool is at a low productivity state, historically, modern fisheries target this zone west of 160ºE, in response to the shifts in ENSO. Accordingly, the increase in scombrids represented archaeologically between ~1550 and 1150 BP, would be consistent with modern commercial fishing practices, given it is within a region that historically would contain the highest biomass of skipjack during these climatic conditions.

The Ebon Atoll results demonstrate a decline in relative abundance of scombrids/skipjack between ~850 cal BP and the historic period; specifically, scombrids are still present at the site, but do not remain the top ranked taxon. This decline is consistent with the MCA/LIA transition, with El Niño- like conditions associated with the period from ~850 to ~550 cal BP, similar conditions associated with the earliest prehistoric Ebon assemblages. Following the transition to the LIA, associated with La Niña-like conditions, the warm pool potentially contracted west, resulting in a low productivity state that would have reduced biomass in the region and had associated effects on skipjack catchability—relative to other taxa—through to the historic period. Declining abundance of scombrids between ~750 and 550 cal BP on Fais Island (Ono and Intoh 2011), was also potentially consistent with the timing of the MCA, a dry period associated with an El Niño-like mean state, suggesting the warm pool was highly productive, associated with less favorable habitats (see also Masse et al. 2006). Based on historical trends, these conditions result in an extension of commercial fisheries as far east as 160ºW, and counterintuitively these conditions negatively impact skipjack catchability in the west (Lehodey 2001), but to what extent this can be detected archaeologically requires further exploration. The sample size of archaeological tuna bones for the central Pacific is even smaller than for the western Pacific, but based on available data from Atafu Atoll, Ofu Island

189 and Savai‘i Island, scombrids are more prevalent in assemblages that post-date ~850-650 cal BP (Ishimura and Inoue 2006; Ono and Addison 2013; Weisler et al. 2016), a period associated with the MCA/LIA transition. This is consistent with El Niño-like conditions, increasing the catchability of scombrids/skipjack around the warm pool/cold tongue convergence zone.

Conclusion

The likelihood that ENSO variability is driving the observed trends in skipjack relative abundance on Ebon Atoll is enhanced by the corresponding regional similarities identified. The archaeological and palaeoclimate records were difficult to correlate, given that regional climate data and local/site specific archaeological fishing trends were compared. There is a need for high-resolution local palaeoclimate data, since only then can specific ecological factors be assessed (e.g. seasonality, rainfall variability, island accretion rates, reef calcification rates, etc.), prior to establishing links to regional models of climate change and resource abundance. Additional radiocarbon dating of the sites, and especially direct dating of tuna bones, could also refine the chronology and allow assessment of fine-scale temporal changes in tuna abundance.

Cultural factors undoubtedly influenced these archaeological trends in tuna fishing, as the occurrence of scombrids at these sites is a direct reflection of human subsistence practices, decision making, and social dictates. However, in this region of the Pacific we have highlighted the potential influence of ENSO variability on the skipjack fishery over the last 2000 years and the relevance of utilizing archaeological abundance data to contribute to our understanding of long term patterning in tuna biogeography. Moving forwards there is a need to complete species-level identifications of archaeological tuna remains, coupled with new high-resolution, local climatic data throughout the late Holocene for assessing long term trends in the western and central Pacific Ocean tuna fishery. By utilizing archaeological data, past trends in tuna abundance and distribution in relation to climate models may provide useful insights for managing sustainable fisheries into the future.

Acknowledgements

Permission to conduct archaeological research in the RMI was granted to Weisler by Josepha Maddison, Historic Preservation Office, Ministry of Internal Affairs and on Ebon Atoll, former mayor Lajan Kabua. We thank Christina Giovas for helpful comments on an earlier version of this manuscript and also two anonymous reviewers for their comments. Matthew Harris is thanked for preparing the figures.

Funding

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RMI fieldwork was supported by a grant to Weisler from the Office of the Deputy Vice Chancellor (Research), University of Queensland. Radiocarbon dates were funded by the Australian Institute of Nuclear Science and Engineering grant (ALNGRA 12004) to Weisler. Lambrides' studies are supported by an Australian Government Research Training Program Scholarship.

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Table 1. Quantification of fish remains from MLEb-1 and MLEb-5 (6.4 mm only).

MLEb-1 MLEb-5 Late (TP 17-20) Middle (TP 6) Early (All TPs) Taxon NISP (%) MNI (%) NISP (%) MNI (%) NISP (%) MNI (%) Actinopterygii (unid. to element) 129 3 31 Selachii (sharks) 8 (0.2) 2 (0.4) 17 (20.0) 2 (5.3) 9 (0.6) 1 (0.4) Carcharhinidae (requiem sharks) Carcharhinus cf. longimanus 1 (<0.1) 1 (0.2) 1 (1.2) 1 (2.6) Carcharhinus cf. melanopterus 1 (<0.1) 1 (0.2) Muraenidae (moray eels) 16 (0.4) 7 (1.4) Acanthuridae (surgeonfishes) 103 (2.5) 26 (5.1) 9 (0.6) 5 (1.9) Acanthurus spp. 43 (1.0) 7 (1.4) 5 (0.3) 1 (0.4) Ctenochaetus spp. 11 (0.3) 4 (0.8) 1 (0.1) 1 (0.4) Naso spp. 9 (0.2) 3 (0.6) 5 (0.3) 4 (1.5) Balistidae (triggerfishes) 587 (14.0) 23 (4.5) 1 (1.2) 1 (2.6) 29 (1.8) 9 (3.3) Belonidae (needlefishes) 13 (0.3) 6 (1.2) 4 (0.3) 2 (0.7) Bothidae (lefteye flounders) 18 (0.4) 5 (1.0) 1 (1.2) 1 (2.6) 3 (0.2) 1 (0.4) Carangidae (jacks) 83 (2.0) 15 (2.9) 1 (1.2) 1 (2.6) 9 (0.6) 1 (0.4) Carangoides spp. 8 (0.2) 3 (0.6) 2 (0.1) 1 (0.4) Caranx spp. 45 (1.1) 8 (1.6) 1 (1.2) 1 (2.6) 18 (1.1) 3 (1.1) Decapterus spp. 32 (0.8) 6 (1.2) 1 (1.2) 1 (2.6) 8 (0.5) 4 (1.5) Elagatis bipinnulatus 27 (0.6) 3 (0.6) 1 (0.1) 1 (0.4) Selar spp. 87 (2.1) 7 (1.4) 2 (0.1) 1 (0.4) Seriola spp. 1 (0.1) 1 (0.4) Chaetodontidae (butterflyfishes) 9 (0.2) 1 (0.2) Cirrhitidae (hawkfishes) 43 (1.0) 8 (1.6) 7 (0.4) 3 (1.1) Diodontidae (porcupinefishes) Diodon spp. 192 (4.6) 6 (1.2) 5 (0.3) 1 (0.4) Exocoetidae (flying fishes) 54 (1.3) 6 (1.2) 2 (0.1) 2 (0.7) Fistulariidae (cornetfishes) Fistularia commersonii 24 (0.6) 5 (1.0) 11 (0.7) 2 (0.7) Holocentridae (squirrelfishes) 88 (2.1) 26 (5.1) 1 (1.2) 1 (2.6) 8 (0.5) 5 (1.9) Myripristis spp. 22 (0.5) 3 (0.6) 6 (0.4) 2 (0.7) Neoniphon spp. 11 (0.3) 3 (0.6) Sargocentron spp. 78 (1.9) 12 (2.4) 1 (1.2) 1 (2.6) 13 (0.8) 2 (0.7) Kuhliidae (flagtails) Kuhlia spp. 8 (0.2) 3 (0.6) 1 (0.1) 1 (0.4) Kyphosidae (sea chubs) Kyphosus spp. 72 (1.7) 5 (1.0) 5 (0.3) 1 (0.4) Labridae (wrasses) 75 (1.8) 13 (2.6) 16 (1) 6 (2.2) Lethrinidae (emperors) 37 (0.9) 6 (1.2) 3 (3.5) 2 (5.3) 9 (0.6) 1 (0.4) Gnathodentex aureolineatus 2 (<0.1) 2 (0.4) 1 (0.1) 1 (0.4) Lethrinus spp. 110 (2.6) 15 (2.9) 41 (2.6) 4 (1.5) Monotaxis grandoculis 35 (0.8) 9 (1.8) 23 (1.5) 7 (2.6) Lutjanidae (snappers) 145 (3.5) 14 (2.8) 1 (1.2) 1 (2.6) 9 (0.6) 2 (0.7) Lutjanus spp. 137 (3.3) 16 (3.1) 46 (2.9) 4 (1.5) Lutjanus cf. kasmira 42 (1.0) 13 (2.6) 2 (2.4) 2 (5.3) 13 (0.8) 4 (1.5) Mugilidae (mullets) 16 (0.4) 5 (1.0) 2 (0.1) 1 (0.4) Mullidae (goatfishes) 25 (0.6) 4 (0.8) Mulloidichthys spp. 55 (1.3) 7 (1.4) 4 (0.3) 1 (0.4) Parupeneus spp. 24 (0.6) 5 (1.0) 8 (0.5) 1 (0.4) Ostraciidae (boxfishes) 58 (1.4) 1 (0.2) Pomacentridae (damselfishes) 11 (0.3) 1 (0.2) 1 (0.1) 1 (0.4) Scaridae (parrotfishes) 233 (5.6) 37 (7.3) 12 (14.1) 5 (13.2) 216 (13.6) 16 (5.9) Calotomus spp. 9 (0.2) 4 (0.8) Chlorurus spp. 47 (1.1) 12 (2.4) 39 (2.5) 7 (2.6) Hipposcarus longiceps 103 (2.5) 14 (2.8) 4 (4.7) 2 (5.3) 103 (6.5) 9 (3.3) Scarus spp. 104 (2.5) 10 (2.0) 35 (2.2) 5 (1.9) Scombridae (mackerels and tunas) 75 (1.8) 15 (2.9) 19 (22.4) 5 (13.2) 161 (10.2) 42 (15.6) Katsuwonus pelamis 387 (9.2) 27 (5.3) 11 (12.9) 5 (13.2) 567 (35.8) 83 (30.7) Thunnus spp. 13 (0.3) 5 (1.0) 3 (0.2) 1 (0.4) 202

Serranidae (groupers) 550 (13.1) 33 (6.5) 6 (7.1) 4 (10.5) 100 (6.3) 7 (2.6) Anyperodon leucogrammicus 10 (0.2) 2 (0.4) 1 (0.1) 1 (0.4) Cephalopholis spp. 9 (0.2) 4 (0.8) 1 (0.1) 1 (0.4) Epinephelus spp. 19 (0.5) 7 (1.4) 10 (0.6) 3 (1.1) Plectropomus spp. 7 (0.2) 2 (0.4) 2 (0.1) 2 (0.7) Variola louti 18 (0.4) 5 (1.0) 1 (1.2) 1 (2.6) 7 (0.4) 3 (1.1) Siganidae (rabbitfishes) Siganus spp. 118 (2.8) 11 (2.2) 1 (1.2) 1 (2.6) 2 (0.1) 1 (0.4) Sphyraenidae (barracudas) Sphyraena spp. 21 (0.5) 5 (1.0) 2 (0.1) 1 (0.4) Total identified 4188 509 85 38 1586 270 Total bones 10666 154 2761 Total weight (g) 1590.8 56.1 850.0 % identified 39.26 55.2 57.4

203

Table 2. Quantification of fish remains from MLEb-1 and MLEb-5 (6.4 mm and 3.2 mm).

MLEb-1 MLEb-5 Late (TP 17) Middle (TP 6) Early (TP 13) Taxon NISP (%) MNI (%) NISP (%) MNI (%) NISP (%) MNI (%) Actinopterygii (unid. to element) 310 66 31 Selachii (sharks) 2 (0.1) 1 (0.3) 28 (2.7) 2 (0.9) Carcharhinidae (requiem sharks) Carcharhinus cf. amblyrhynchos 1 (<0.1) 1 (0.3) Carcharhinus cf. melanopterus 1 (<0.1) 1 (0.3) 39 (3.7) 4 (1.9) 6 (2.1) 1 (1.5) Triaenodon obesus 1 (0.1) 1 (0.5) Ginglymostomatidae (carpet sharks) Nebrius ferrugineus 1 (0.1) 1 (0.5) Muraenidae (moray eels) 54 (2.0) 11 (2.9) 37 (3.5) 7 (3.3) 1 (0.3) 1 (1.5) Acanthuridae (surgeonfishes) 78 (2.9) 16 (4.2) 18 (1.7) 5 (2.3) Acanthurus spp. 25 (0.9) 8 (2.1) 2 (0.2) 2 (0.9) 1 (0.3) 1 (1.5) Ctenochaetus spp. 5 (0.2) 3 (0.8) 1 (0.1) 1 (0.5) Naso spp. 4 (0.2) 2 (0.5) 4 (0.4) 2 (0.9) 1 (0.3) 1 (1.5) Balistidae (triggerfishes) 255 (9.6) 11 (2.9) 69 (6.6) 9 (4.2) 10 (3.4) 1 (1.5) Belonidae (needlefishes) 50 (1.9) 5 (1.3) 60 (5.7) 8 (3.7) 21 (7.2) 1 (1.5) Bothidae (lefteye flounders) 31 (1.2) 5 (1.3) 13 (1.2) 2 (0.9) 5 (1.7) 1 (1.5) Caesionidae (fusiliers) 1 (<0.1) 1 (0.3) Carangidae (jacks) 84 (3.2) 8 (2.1) 46 (4.4) 6 (2.8) 12 (4.1) 2 (3.1) Carangoides spp. 9 (0.3) 2 (0.5) 1 (0.3) 1 (1.5) Caranx spp. 11 (0.4) 7 (1.9) 4 (0.4) 2 (0.9) 2 (0.7) 1 (1.5) Decapterus spp. 49 (1.8) 11 (2.9) 23 (2.2) 8 (3.7) 7 (2.4) 2 (3.1) Elagatis bipinnulatus 10 (0.4) 3 (0.8) Scomberoides Iysan 1 (0.1) 1 (0.5) Selar spp. 27 (1.0) 8 (2.1) 3 (0.3) 2 (0.9) Seriola spp. 1 (0.1) 1 (0.5) Chaetodontidae (butterflyfishes) 8 (0.3) 2 (0.5) 2 (0.2) 1 (0.5) 1 (0.3) 1 (1.5) Cirrhitidae (hawkfishes) 67 (2.5) 9 (2.4) 21 (2.0) 8 (3.7) 10 (3.4) 3 (4.6) Diodontidae (porcupinefishes) Diodon spp. 78 (2.9) 3 (0.8) 11 (1.0) 1 (0.5) 1 (0.3) 1 (1.5) Exocoetidae (flying fishes) 267 (10.1) 12 (3.2) 78 (7.4) 7 (3.3) 20 (6.9) 1 (1.5) Fistulariidae (cornetfishes) Fistularia commersonii 11 (0.4) 3 (0.8) 1 (0.1) 1 (0.5) 2 (0.7) 1 (1.5) Gerreidae (mojarras) Gerres spp. 6 (0.2) 4 (1.1) Holocentridae (squirrelfishes) 76 (2.9) 19 (5.0) 35 (3.3) 7 (3.3) 8 (2.8) 3 (4.6) Myripristis spp. 47 (1.8) 8 (2.1) 18 (1.7) 5 (2.3) 3 (1) 1 (1.5) Neoniphon spp. 6 (0.2) 2 (0.5) 2 (0.2) 1 (0.5) Sargocentron spp. 103 (3.9) 12 (3.2) 35 (3.3) 9 (4.2) 16 (5.5) 2 (3.1) Kuhliidae (flagtails) Kuhlia spp. 18 (0.7) 5 (1.3) 7 (0.7) 2 (0.9) Kyphosidae (sea chubs) Kyphosus spp. 36 (1.4) 7 (1.9) 5 (0.5) 2 (0.9) 2 (0.7) 1 (1.5) Labridae (wrasses) 31 (1.2) 8 (2.1) 20 (1.9) 5 (2.3) 4 (1.4) 2 (3.1) Lethrinidae (emperors) 60 (2.3) 8 (2.1) 45 (4.3) 5 (2.3) 8 (2.8) 1 (1.5) Lethrinus spp. 84 (3.2) 12 (3.2) 19 (1.8) 8 (3.7) 3 (1.0) 1 (1.5) Monotaxis grandoculis 43 (1.6) 7 (1.9) 22 (2.1) 2 (0.9) 17 (5.9) 4 (6.2) Lutjanidae (snappers) 106 (4) 12 (3.2) 31 (3.0) 5 (2.3) 11 (3.8) 2 (3.1) Aprion virescens 1 (<0.1) 1 (0.3) 1 (0.3) 1 (1.5) Lutjanus spp. 66 (2.5) 11 (2.9) 3 (0.3) 2 (0.9) 10 (3.4) 2 (3.1) Lutjanus cf. kasmira 9 (0.3) 4 (1.1) 2 (0.2) 2 (0.9) 3 (1.0) 2 (3.1) Mugilidae (mullets) 8 (0.3) 2 (0.5) 5 (0.5) 2 (0.9) 4 (1.4) 1 (1.5) Mullidae (goatfishes) 17 (0.6) 5 (1.3) 18 (1.7) 5 (2.3) 10 (3.4) 1 (1.5) Mulloidichthys spp. 35 (1.3) 7 (1.9) 14 (1.3) 4 (1.9) 7 (2.4) 1 (1.5) Parupeneus spp. 18 (0.7) 5 (1.3) 3 (0.3) 2 (0.9) 4 (1.4) 1 (1.5) Ostraciidae (boxfishes) 50 (1.9) 4 (1.1) 12 (1.1) 2 (0.9) Pomacentridae (damselfishes) 24 (0.9) 5 (1.3) 2 (0.2) 1 (0.5) 4 (1.4) 1 (1.5) 204

Scaridae (parrotfishes) 99 (3.7) 11 (2.9) 87 (8.3) 9 (4.2) 10 (3.4) 2 (3.1) Chlorurus spp. 9 (0.3) 4 (1.1) 13 (1.2) 3 (1.4) 3 (1.0) 1 (1.5) Hipposcarus longiceps 25 (0.9) 9 (2.4) 12 (1.1) 5 (2.3) 1 (0.3) 1 (1.5) Scarus spp. 16 (0.6) 6 (1.6) 7 (0.7) 4 (1.9) Scombridae (mackerels and tunas) 56 (2.1) 11 (2.9) 43 (4.1) 8 (3.7) 9 (3.1) 5 (7.7) Katsuwonus pelamis 64 (2.4) 10 (2.6) 14 (1.3) 5 (2.3) 9 (3.1) 2 (3.1) Thunnus spp. 6 (0.2) 3 (0.8) 3 (0.3) 3 (1.4) Serranidae (groupers) 336 (12.7) 22 (5.8) 81 (7.7) 12 (5.6) 34 (11.7) 3 (4.6) Anyperodon leucogrammicus 2 (0.1) 2 (0.5) 1 (0.3) 1 (1.5) Cephalopholis spp. 6 (0.2) 2 (0.5) 4 (0.4) 2 (0.9) Epinephelus spp. 13 (0.5) 5 (1.3) 4 (0.4) 3 (1.4) 2 (0.7) 1 (1.5) Variola louti 2 (0.1) 2 (0.5) 4 (0.4) 3 (1.4) Siganidae (rabbitfishes) Siganus spp. 20 (0.8) 5 (1.3) 9 (0.9) 2 (0.9) 1 (0.3) 1 (1.5) Sphyraenidae (barracudas) Sphyraena spp. 29 (1.1) 5 (1.3) 7 (0.7) 2 (0.9) 4 (1.4) 1 (1.5) Total identified 2655 378 1050 214 290 65 Total bones 18480 9168 2727 Total weight (g) 591.17 268.93 64.52 % identified 14.4 11.5 10.6

205

Table 3. Measures of taxonomic heterogeneity: NTAXA, Shannon-Weiner index of diversity (H′) and Shannon’s evenness (E), Simpson's index of diversity (1-D) and Fisher's α: (a) 6.4 mm only, and (b) 6.4 mm and 3.2 mm. No fish bones were recovered from the TP 6 IIB (6.4 mm only) assemblage.

(a)

MLEb-1 MLEb-5 Early Late (TP 17-20) Middle (TP 6) (All TPs) Index Historic IA IB IIA IIB IIIA IA IB IIA IIB IIIA I NTAXA 13 27 23 19 22 7 10 4 4 - 4 24 1-D 0.891 0.909 0.925 0.922 0.888 0.857 0.880 0.694 0.667 - 0.720 0.749 H' 2.362 2.676 2.799 2.729 2.600 1.946 2.207 1.277 1.242 - 1.332 2.032 E 0.921 0.812 0.893 0.927 0.841 1 0.959 0.921 0.896 - 0.961 0.640 Fisher's ɑ 7.490 7.351 10.710 13.750 12.350 0 7.959 3.878 5.245 - 9.284 6.364

(b)

MLEb-1 MLEb-5 Early Late (TP 17) Middle (TP 6) (TP 13) Index Historic IA IB IIA IIB IIIA IA IB IIA IIB IIIA I NTAXA 13 29 28 20 20 10 26 21 15 9 7 25 1-D 0.882 0.928 0.936 0.931 0.919 0.876 0.930 0.934 0.924 0.880 0.840 0.932 H' 2.340 2.897 2.968 2.823 2.752 2.205 2.887 2.850 2.636 2.164 1.889 2.906 E 0.912 0.860 0.891 0.942 0.919 0.958 0.886 0.936 0.974 0.985 0.971 0.903 Fisher's ɑ 8.721 10.560 12.420 18.530 16.470 19.860 10.520 12.010 17.120 43.450 14.490 14.870

206

Table 4. MTL analysis of fish remains from MLEb-1 and MLEb-5 by cultural layers (6.4 mm and 3.2 mm) and Spearman’s rho calculations to assess sample size effects. Non-significant Spearman’s rho results (α = >0.05) indicate there was no correlation between sample size and MTL. No fish bones were recovered from the TP 6 IIB (6.4 mm only) assemblage and no historic material was recovered from TP 6.

6.4 mm only 6.4 mm and 3.2 mm MLEb-1 Layer Late (TP 17-20) Middle (TP 6) Late (TP 17) Middle (TP 6) Historic 3.16 - 3.20 - IA 3.31 3.78 3.44 3.56 IB 3.61 3.60 3.57 3.49 IIA 3.53 3.83 3.38 3.51 IIB 3.63 - 3.63 3.73 IIIA 3.53 2.78 3.63 3.44

rs = 0.20, p = 0.72 0.70, p = 0.23 1.00, p = 0.00 0.30, p = 0.52

MLEb-5 Early (All TPs) Early (TP 13) I 3.75 3.62

207

Table 5. Quantification of fish remains from MLEb-1 and MLEb-5 by cultural layers for Acanthuridae, Scaridae and Scombridae (6.4 mm and 3.2 mm), by NISP and MNI reported in brackets.

MLEb-1 MLEb-5 Taxon Hist. IA IB IIA IIB IIIA IA IB IIA IIB IIIA I Early (All (6.4 mm only) Late (TP 17-20) Middle (TP 6) TPs) Acanthuridae 9(2) 87(19) 3(1) 3(3) 1(1) 9(5) Acanthurus spp. 17(3) 25(3) 1(1) 5(1) Ctenochaetus spp. 4(1) 6(2) 1(1) 1(1) Naso spp. 7(1) 1(1) 1(1) 5(4) Scaridae 3(2) 205(28) 12(2) 3(1) 10(4) 5(2) 3(1) 3(1) 1(1) 216(16) Calotomus spp. 1(1) 6(1) 1(1) 1(1) Chlorurus spp. 2(1) 40(8) 4(2) 1(1) 39(7) Hipposcarus longiceps 85(9) 8(1) 3(2) 7(2) 3(1) 1(1) 103(9) Scarus spp. 4(1) 89(5) 7(2) 2(1) 1(1) 35(5) Scombridae 36(4) 9(3) 5(1) 25(7) 9(2) 8(2) 2(1) 161(42) Katsuwonus pelamis 207(9) 46(6) 35(4) 95(7) 4(1) 6(2) 3(1) 2(2) 567(83) Thunnus spp. 5(1) 5(2) 1(1) 2(1) 3(1)

Early (TP (6.4 mm and 3.2 mm) Late (TP 17) Middle (TP 6) 13) Acanthuridae 14(2) 38(7) 21(4) 2(1) 2(1) 1(1) 12(2) 5(2) 1(1) Acanthurus spp. 9(3) 12(3) 3(1) 1(1) 1(1) 1(1) 1(1) Ctenochaetus spp. 2(1) 3(2) 1(1) Naso spp. 3(1) 1(1) 3(1) 1(1) 1(1) Scaridae 3(1) 71(6) 15(2) 4(1) 6(1) 65(5) 15(2) 5(1) 2(1) 10(2) Calotomus spp. Chlorurus spp. 6(2) 2(1) 1(1) 9(2) 4(1) 3(1) Hipposcarus longiceps 16(5) 3(1) 5(2) 1(1) 1(1) 9(2) 1(1) 1(1) 1(1) Scarus spp. 3(1) 6(2) 6(2) 1(1) 4(3) 3(1) Scombridae 32(4) 17(3) 3(1) 4(3) 29(5) 11(2) 3(1) 9(5) Katsuwonus pelamis 33(3) 6(2) 8(2) 16(2) 1(1) 8(2) 3(1) 3(2) 9(2) Thunnus spp. 3(1) 2(1) 1(1) 3(3)

208

Figure 1. Map of the Pacific Islands with key archaeological sites mentioned in text (Davidson et al. 1999; Fraser 1998; Ishimura and Inoue 2006; Leach et al. 1997; Leach et al. 1984; Masse et al. 2006; Ono and Addison 2013; Ono and Intoh 2011; Rolett 1998; Weisler et al. 2016). The dotted lines provide the approximate extent of the warm pool under La Niña and El Niño conditions recorded historically (Lehodey 2001; Lehodey et al. 1997). The shaded areas indicate the location of the highest recorded skipjack CPUE concentration for the western and central Pacific Ocean under La Niña and El Niño conditions recorded in the late 20th century (after Lehodey et al. 1997:Figure 1).

209

Figure 2. Map of Ebon Atoll with the location of archaeological sites mentioned in text labelled.

210

Figure 3. Chord distance analysis across sequential pairs of cultural layers, ordered chronologically within and between sites: (a) 6.4 mm only, and (b) 6.4 mm and 3.2 mm.

211

Figure 4. (a) Correspondence analysis of taxonomic composition across all cultural layers at MLEb-1 and MLEb-5, and for brevity, major taxa are defined as those represented by at least 10 individuals, and (b) axis 1 scores ordered from the oldest assemblage (MLEb-5) to the most recent historic assemblage.

212

CHAPTER 7: Conclusion

In the opening chapter the rationale and major research aims were introduced. Given the overall importance of marine resources, and specifically finfish, throughout Pacific prehistory, Ebon Atoll provided an ideal context for: (1) reassessing methods and methodological approaches for conducting Pacific ichthyoarchaeological analyses, and based on these assessments, (2) implementing high resolution methods for investigating the long-term exploitation of the Ebon marine fishery. Consequently, the first dedicated consideration of prehistoric fishing in the RMI was provided building on initial studies by Weisler (1999, 2001). The utility of historical ecology as a conceptual and interpretive framework for this study was also presented, and demonstrated throughout the thesis, as it enabled the consideration of both prehistoric and historic datasets (e.g., modern fishery and climatic records) when assessing human-environment interactions over millennia. The main body of this thesis is comprised of five journal articles, four that have been published and one that has been accepted for publication (Chapters 2-6). Here, a summary of the main findings as they relate to each of the six research questions posed in the first chapter, a discussion of future research objectives, and some concluding remarks are provided.

Main Findings

How do the analytical methods implemented by Pacific ichthyoarchaeologists constrain our understanding of past human behaviour?

The historical development of the analytical methods used by Pacific ichthyoarchaeologists was assessed within a global context, which allowed a consideration of data quality, and an exploration of the impact of methods on the range of research questions that can be addressed. The implications of utilising archaeological data when investigating modern reef health and management, human impacts to marine resources, and the effects of changing climate on resource exploitation were also addressed as archaeology offers a unique culturally mediated perspective. Both methods and methodologies were evaluated, including: excavation and sampling, analysis of archaeological fish bone, and interpretations of diet and subsistence. However, the importance of transparency over standardisation is emphasised regarding the analytical methods implemented by Pacific ichthyoarchaeologists (see also Colley 1990). Critical to these aims is a detailed account of the methods adopted in each study, which will directly address the issue of replication and transparency of results in the published literature.

Outside of the Pacific, fine mesh screening (≤3.2 mm) for the recovery of archaeological fish bones has been more widely utilised (e.g., Butler 1987; Erlandson et al. 2005; Gobalet and Jones 1995; Robson et al. 2013). Screen size directly impacts the range of taxa that are identified, particularly the 213 recovery of rare taxa, and as a result, the use of larger screen sizes (≥3.2 mm) can over-estimate the contribution of large-bodied taxa represented in an archaeological assemblage (Lambrides and Weisler 2016; Nagaoka 2005). Perhaps even more problematic are inconsistences in screen sizes utilised across a region or archipelago (Partlow 2006) or the limited range of osteological elements used for taxonomic identification (Lambrides and Weisler 2015b; Ono and Clark 2012).

The comprehensiveness of a comparative collections and the taxonomic identification protocols— range of elements used, taxonomic level of the identifications, and quantification protocols—directly impact data quality and the range of research questions that can be addressed. The decisions that researchers make regarding these issues can directly affect measures of richness and evenness, constrain interpretations, and negatively impact data quality (Wolverton 2013). Regions with high biodiversity, such as the tropical Pacific, are challenging for establishing representative comparative collections for ichthyoarchaeological analyses due to the number of specimens required, limiting the range of taxa that can be identified. However, quality assurance in taxonomic identifications rests solely on the protocols and identification criteria implemented by researchers (Driver 1992). Until recently, only a limited number of elements were used for taxonomic identifications in the region, which can influence rank-order and the visibility of certain taxa (Lambrides and Weisler 2015b, 2017). When quantifying archaeological fish bone assemblages, a range of quantification measures (e.g., NISP, MNI, and weight) should be incorporated, as this allows the economic importance of a taxon to be assessed, facilitates the integrative analysis of fish bone assemblages with other recovered faunal classes, and supports taphonomic studies and regional comparisons (e.g., Rick et al. 2002). Ultimately, there is a need for consistency—or accepted common standards—in the laboratory protocols adopted in Pacific ichthyoarchaeology to ensure replication and comparability of results. Blind testing is a good approach for identifying limitations in current methods and protocols that require further refinement (e.g., Giovas et al. 2017; Gobalet 2001).

In Pacific ichthyoarchaeology, cultural ecology, human behavioural ecology, and historical ecology have provided interpretative and theoretical frameworks for decades (e.g., Butler 2001; Jones 2011; Kirch 1982; Nagaoka 2002). In recent years, historical ecology has become increasingly relevant in the Pacific and globally, given its emphasis on interdisciplinary research. Historical ecology is a powerful approach for considering the spatial and historical processes that have shaped human- environment interactions over millennia (e.g., Fitzpatrick and Donaldson 2007; Jones 2009; McKechnie et al. 2014; Ono and Clark 2012; Rick and Lockwood 2013). Given the utility of the data generated utilising a historical archaeological approach, this thesis included an investigation of current methods, specifically taxonomic identification protocols and fish size reconstructions, to offer

214 possible refinement of these methods useful for Pacific ichthyoarchaeology. Furthermore, these high quality methods were then implemented when analysing the Ebon Atoll fish bone assemblages.

How do the taxonomic identification protocols used for analysing Pacific fish bone assemblages influence our understanding of the range and relative abundance of taxa exploited?

The development of methods used to identify Pacific fish bone assemblages was considered, specifically the range of elements used for fish bone identifications from the 1970s, when fish bone analysis started becoming standard practice, to the present (Anderson 1973; Leach and Davidson 1977). Three taxonomic identification protocols were examined: (1) the most commonly identified five paired cranial bones and ‘specials’, (2) an expanded number of cranial bones, and (3) the least common practice of including all vertebrae.

There has been an intensive focus on utilising predominately cranial elements when analysing archaeological fish bone assemblages recovered from Pacific sites (Anderson 1973; Leach and Davidson 1977; Ono and Clark 2012; Vogel 2005; Walter 1998; Weisler and Green 2013), with the exception of few unique spines and vertebrae that would be considered under the category of ‘specials’ (e.g., Clark and Szabó 2009; Vogel and Anderson 2012). Ono (2003, 2004) emphasised the need for vertebrae to be considered in Pacific fish bone studies, but no investigation had explicitly considered the impact of identifying all vertebrae. The assemblage from Henderson Island was ideal for testing the utility of identifying all cranial and postcranial fish bone elements as it had been analysed twice previously in accordance with advancements in methods; specifically, the identification of only a restricted number of cranial elements and then a more expanded range (Weisler et al. 2010: Table 4). It was necessary to consider the benefits of identifying all vertebrae, prior to analysing the significantly larger sample of fish bone recovered from Ebon Atoll.

It had been previously argued that identifying an increased range of cranial elements does not impact relative abundance of dominant taxa (Butler 1994; Ono and Clark 2012), and while supported by this study, this assessment does not acknowledge the importance of identifying rare taxa or the benefits of increasing NISP counts. This study reported a ~37% increase in NISP associated with the identification of an expanded range of cranial elements. This increased sample size is useful for considering taphonomic effects and site formation processes (Nicholson 1992a, b, 1993a, b, 1996a, b, 1998), and variability in the recovery rates of osteological elements from the same taxa (Nagaoka 1994, 2005).

The identification of all vertebrae impacted both abundance and rank-order of identified taxa. Most noteworthy was a doubling in reported MNI for acanthurids, surpassing serranids as the top-ranked taxon. MNI remained consistent for serranids across all three tested identification protocols. These 215 outcomes have implications for considering capture technology, processing and butchery practices, as well as providing an increased number of identified bone available for measurement and fish size reconstructions (Lambrides and Weisler 2015a).

Outcomes of this pilot study demonstrate the benefit of identifying all vertebrae, and the utility of attempting the identification of all cranial and postcranial remains recovered from all Pacific archaeological sites, and as such all fish bones recovered from Ebon Atoll were attempted for identification. Alterations in fish size could not have been assessed from Ebon archaeological sites without first identifying each vertebrae to taxon and type (Lambrides and Weisler 2015a, 2017). Vertebrae were also reported to have high identification rates, for example 63% (6.4 mm only) and 40% (6.4 mm and 3.2 mm) of all recovered vertebrae from the MLEb-1 (TPs 17-20) assemblage were identified to taxon. Furthermore, consideration of the Ebon archaeological tuna records would not have been possible without the identification of vertebrae, with 95% of K. pelamis identified by vertebrae, and only a few cranial elements facilitating species-level identifications (Lambrides and Weisler 2017). The identification of vertebrae is recommended when analysing all Pacific fish bone assemblages, as it has a demonstrated impact on relative abundance determinations, associated implications for inferences of exploited capture technology, the range and intensity of marine habitats exploited, and long-term impacts to these marine ecosystems.

Given the high biodiversity of fish species found in the tropical Pacific and the limited range of osteological elements utilised for fish size reconstructions archaeologically, can changes in fish size through time be accurately assessed in the region?

In the Pacific, there has been an emphasis on using predominately cranial elements for fish size estimations, which tracks historical developments in fish bone identification protocols in the region (Davidson et al. 2000; Leach and Boocock 1995; Leach et al. 1999a, b). Outside of the Pacific a wide range of cranial and postcranial elements have been utilised for decades when completing fish length and weight reconstructions (e.g., Enghoff 1994; Gabriel et al. 2012; Orchard 2003; Van Neer et al. 1999).Vertebral morphometrics have had limited application in the Pacific (e.g., Desse and Desse- Berset 1996; Fraser 1998; Ono and Intoh 2011). However, in most instances, unidentified vertebrae have been measured to determine whether changes in fish size through time can be detected (Jones 2009; Rolett 1998; Weisler et al. 2010). To assess methods that could more accurately determine fish size from Pacific fish bone assemblages, three distinct protocols using fish vertebral morphometrics were tested, given the underutilisation of vertebrae for fish size determinations in the region. This includes: (1) all taxa and vertebrae types grouped to simulate methods commonly used in Pacific archaeology, (2) controlling for the taxon but including all vertebrae types as a single category, and (3) controlling for both taxon and vertebra type. 216

When evaluating the methods routinely used in Pacific archaeology, it was determined that by combining all vertebrae measurements irrespective of taxon and type resulted in false trends. The differences in vertebrae size noted among cultural layers, which are commonly attributed to changes in fish size over time in the Pacific fishing literature, are more likely tracking other changes, such as changes in taxonomic composition and their relative abundance represented across cultural layers. This thesis demonstrated the utility of identifying vertebrae from Pacific fish bone assemblages to taxon (Lambrides and Weisler 2015b), but there are also benefits for determining fish size, as indicated by approaches outside of the region (e.g., Gabriel et al. 2012).

Based on these results, two methods for assessing relative changes in fish size from Pacific fish bone assemblages were proposed that account for high biodiversity in the region and the limited genus- and species-level identifications of archaeological fish bones. Vertebrae were found to be the most useful element for considering changes in fish size through time, as they provided the largest sample size across all cultural layers for most sites. The first method proposed utilises the Global Rachidian Profiles (GRP) method, first developed by Desse and Desse-Berset (1989, 1994, 1999). This is a ‘coarse-grained’ method of reconstructing fish length, but does still require a comprehensive reference collection and more specific taxonomic identifications of archaeological specimens to enhance its efficacy. Secondly, and the most accurate for assessing alterations in fish size from Pacific archaeological sites, is the use of raw bone measurements of only those elements identified to taxon (Giovas et al. 2016; Lambrides and Weisler 2017). This method allows an assessment of changes in bone size through time, a method useful for estimating changes in fish size through time, when fish size determinations are not possible. Key to this approach is ensuring that all vertebrae have been identified to taxon and type and the exact position along the vertebral column is determined prior to considering changes in bone size through time (Lambrides and Weisler 2015a).

The major challenge identified by this thesis is the need for species-level taxonomic identifications of Pacific archaeological fish bone specimens, to then keep abreast of methods and approaches that have been implemented in other regions (e.g., Butler and Bowers 1998; Grealy et al. 2016; Moss et al. 2014; Richter et al. 2011; Speller et al. 2012). There is an issue of collecting adequate reference samples so that comparative collections are representative of the biodiversity of the study region as well accommodating the range of intra-taxonomic variation (Bartosiewicz and Takács 1997). This issue would be aided by the establishment of an open source database that would allow researchers to share morphometric data associated with comparative collections that would otherwise require physical access. Without access to these data, approaches for understanding alterations in fish size associated with Pacific archaeological assemblages will lack precision. Only utilising elements

217 identified to taxon is an improvement in approach for the region, but the limitations should be acknowledged in the published literature.

Are there spatial distinctions in taxonomic composition of fish species as reflected by windward vs. leeward islet variation?

Spatial distinctions in taxonomic composition of fish species reflected by windward and leeward islet variation on atolls has not previously been explored on atolls (but see references here for discussion of windward vs. leeward distinctions on other island types, Bayman and Dye 2013; Kirch 1982; Kirch and Dye 1979; Vogel and Anderson 2012; Weisler and Kirch 1985). To explore this question, three lagoonside habitation sites, from three islets were utilised: MLEb-1, Ebon Islet, situated on the leeward rim, the windward exposed Moniak Islet (MLEb-31), and Enekoion Islet (MLEb-33) between the windward and leeward extremes. Marine habitat complexity is highest on leeward islets (Gratwicke and Speight 2005), but unlike molluscs (e.g., Harris and Weisler 2016), fish taxa are difficult to link to specific windward/leeward marine environments, as they track across many marine habitats daily, seasonally, and annually. However, certain fish taxa are strongly associated with certain substrate types, which vary in dominance between windward vs. leeward marine habitats, and this variability can be assessed (e.g., Giovas et al. 2017).

For the mollusc assemblages, variation in relative abundance and taxonomic composition between sites was linked to the marine environment adjacent to each site and exposure to extreme weather events and heavy surf (Harris et al. 2016). However, in the case of the fish bone assemblages, lower values of dissimilarity between sites was reported, with the variability in assemblages being difficult to link to the composition of marine environments adjacent to each site as fish track across different habitats while foraging. Rather than marine environments local to each site influencing taxonomic composition, the variability noted is more likely a reflection of exploited fishing technology (or capture techniques) and site function (village sites vs. campsites). Most notable is the distinction in relative abundance of K. pelamis between sites, particularly its relative absence at MLEb-31, a temporary campsite situated on the windward Moniak islet. This trend was further explored given that the spatial and temporal variability in K. pelamis relative abundance was notable in the Ebon fish bone assemblages.

Is there evidence for alterations in foraging behaviour and/or human impacts to the marine fishery through time?

To assess alterations in foraging behaviour and/or human impacts to the Ebon marine fishery through time, assemblages from Ebon Islet (MLEb-1 and MLEb-5) were utilised as these sites provided a near continuous sequence from the earliest evidence of habitation on the atoll (~2000 cal BP) through to 218 the historic period. The methods utilised included: measures of taxonomic heterogeneity: NTAXA, Shannon-Weiner index of diversity (H′) and Shannon’s evenness (E), Simpson's index of diversity (1-D) and Fisher's α to test for differences in taxonomic richness, diversity, and evenness within and between sites. Chord distance analysis and correspondence analysis (CA) were employed to assess the similarities and differences in faunal composition between sites and cultural layers. Mean trophic level (MTL) was estimated to detect alterations in the feeding guilds represented by captured taxa. Measurements of archaeological fish bone were used to test Houk and Musburger’s (2013) model that documented modern human impacts on RMI coral reef ecosystems.

Results indicated that K. pelamis were more associated with the earliest prehistoric assemblages; additionally, the highest MTL was reported from the earliest dated habitation context at MLEb-1 where the taxon was also the highest ranked. Furthermore, a broad decline in K. pelamis abundance was identified relative to other taxa, such as, scarids, serranids, acanthurids, balistids, and holocentrids. The relationship between coral reef stability and anthropogenic exploitation or interaction with the marine environment was assessed using a model developed from research of modern RMI coral reefs (Houk and Musburger 2013). The key markers for significant human impact posited by Houk and Musburger (2013) were not identified in the analysis of the Ebon archaeological fish bone data. Furthermore, there was no distinction in the size of K. pelamis recovered from the early and late prehistoric assemblages. Therefore, based on the available archaeological data, there is no indication of significant human impact to the inshore reef taxa identified as being susceptible by Houk and Musburger (2013), nor was there any evidence for changes in food web stability being responsible for the relative abundance of K. pelamis over time. According to modern accounts of atoll marine ecosystems, not only are these environments expansive and productive (Thomas 2014), but it’s possible that throughout prehistory the adoption of flexible foraging strategies that targeted a variety of resources, coupled with the resilience and structure of these marine environments, would have mitigated against significant human impact to the marine fishery (see Campbell and Butler 2010; Giovas 2016; Reitz 2014). While beyond the scope of this thesis, these themes need to be considered archipelago-wide to enable further interpretive refinement and consideration.

There was no indication that changes in exploited capture technology or a shift from targeting offshore to inshore resources were driving the observed trends in K. pelamis relative abundance. Finally, there are no published examples of tuna resources being avoided in the Pacific for cultural reasons. Given tuna are a migratory species, it was argued that changes in the availability of this resource through time may account for the observed archaeological trends.

To what extent can migratory fish species, such as tuna, be used as proxies for past environmental stability? 219

Through the integration of disparate interdisciplinary datasets, historical ecology is a powerful interpretative framework for considering long-term human-environment interactions (Armstrong et al. 2017; Rick and Lockwood 2013). Given the strong relationship between skipjack habitat range and ENSO variability, archaeological abundance of this taxon provides a useful proxy for understanding century scale ENSO variability and its impact on resource availability. In this thesis the utility of utilising archaeological proxies for assessing past environmental stability was demonstrated, a potential method utilising the relative abundance of migratory fish species, such as tuna, was proposed, and the context for future research efforts was demonstrated.

Datasets considered in this study include: archaeological data, from Ebon Atoll (local), as well as other archaeological sites situated in the western and central Pacific, palaeoclimate records that track hydroclimate variability of the last two millennia, and recent historic capture records, which demonstrate the relationship between ENSO and K. pelamis abundance/range throughout the tropical Pacific Ocean (Griffiths et al. 2016; Ishimura and Inoue 2006; Lehodey 2001; Lehodey et al. 1997; Lehodey et al. 2011; Masse et al. 2006; Nicol et al. 2014; Ono and Addison 2013; Ono and Intoh 2011; Thompson et al. 2013; Weisler et al. 2016; Yan et al. 2011). Through the use of a historical ecological approach, this thesis highlighted the potential influence of ENSO variability on the K. pelamis fishery over the last two millennia and the benefit of utilising archaeological abundance data to enhance our understanding of long-term patterning in tuna biogeography and past environmental stability. The methods presented here have provided promising outcomes, and continued targeted archaeological research across the region may provide increased understanding of human responses to climate variability in the past and the long-term management of these fisheries.

Future Objectives for Enhancing Research Outcomes

In regards to extending the analytical methods utilised in this thesis, the establishment of an online open source database that contains key details from existing Pacific Island fish bone comparative collections would be useful. This database would include: an inventory of taxa from each reference collection; images of osteological elements; key measurements of fish bones useful for fish size reconstructions; live specimen data (length, weight, etc.); sex and age; and details of capture. By collaborating and integrating information from multiple collections, the ability for Pacific ichthyoarchaeologists to conduct fish size reconstructions and account for intra-taxonomic variation when conducting taxonomic identifications of fish bone assemblages will be greatly enhanced.

The utility of utilising migratory fish as proxies for past environmental stability has been demonstrated in this thesis. The next stage of research requires additional archaeological data to be collected from the western, central, and eastern Pacific, which will likely require reanalysis of existing

220 collections and targeted excavation efforts. Additionally, species-level identifications of archaeological fish bones and the acquisition of local high-resolution environmental data is required. Other migratory species should also be considered, as multi-species proxies will strengthen the model.

Concluding Remarks

This thesis considered the historical development of Pacific fishing studies, the strengths and limitations of analytical approaches within a global context, and suggested some means of improving methods and data quality. For instance, the incorporation of vertebral morphometrics and utilisation of all cranial and postcranial remains for taxonomic identifications. With the implementation of high quality methods and the use of conceptual frameworks such as historical ecology, the kinds of research questions that can be addressed expands (Armstrong et al. 2017; Lambrides and Weisler 2016; Schwerdtner Máñez et al. 2014). This thesis highlighted some of the questions that can be addressed, such as: identifying variability in foraging across small spatial scales, the usefulness of ichthyoarchaeological data for tracking environmental stability, and methods for distinguishing between changes in resource availability and signals of human impacts or marine habitat degradation. Moving forwards it is critical that there is increased dialogue between archaeology and other disciplines, as the establishment of multidisciplinary projects with multifaceted research objectives is key to investigating long-term human-environment interactions in the Pacific, as well as providing potentially useful contributions to modern biological conservation and restoration efforts.

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APPENDIX A

Ebon Atoll fish bone sample information

229

6.4 mm samples 6.4 mm and 3.2 mm samples Islet Site Unit Spit Layer n Weight (g) n Weight (g) Ebon MLEb-1 6 1 IA 13 5.8 982 28.3 Ebon MLEb-1 6 2 IA 18 9.3 1583 45.52 Ebon MLEb-1 6 3 IA 18 10.7 2747 45.97 Ebon MLEb-1 6 4 IA 26 8.2 1369 37.33 Ebon MLEb-1 6 5 IB 15 5.3 472 15.36 Ebon MLEb-1 6 6 IB 18 8.1 1340 24.36 Ebon MLEb-1 6 7 IIA 9 3.3 261 5.61 Ebon MLEb-1 6 8 IIA 2 0.6 66 3.57 Ebon MLEb-1 6 9 IIB 4 0.9 93 3.04 Ebon MLEb-1 6 10 IIIA 31 3.9 101 3.77 Ebon MLEb-1 17 1 Historic 110 8.6 458 8.28 Ebon MLEb-1 17 2 IA 33 23.4 1123 32.92 Ebon MLEb-1 17 3 IA 279 42.6 4184 107.76 Ebon MLEb-1 17 4 IA 182 29.8 3570 88.75 Ebon MLEb-1 17 5 IB 58 8.8 2435 52.17 Ebon MLEb-1 17 6 IB 70 8.2 1838 41.73 Ebon MLEb-1 17 7 IB 19 1.7 691 15.48 Ebon MLEb-1 17 8 IB 32 3.9 608 15.74 Ebon MLEb-1 17 9 IIA 25 6.4 854 21.96 Ebon MLEb-1 17 10 IIB 69 14.8 969 31.17 Ebon MLEb-1 17 11 IIB 36 7.4 697 14.75 Ebon MLEb-1 17 12 IIIA 8 1.3 132 3.56 Ebon MLEb-1 18 1 Historic 38 6.2 Ebon MLEb-1 18 2 IA 121 40.5 Ebon MLEb-1 18 3 IA 2264 265.4 Ebon MLEb-1 18 4 IA 1648 197.4 Ebon MLEb-1 18 5 IA 320 34.6 Ebon MLEb-1 18 6 IA 198 22.5 Ebon MLEb-1 18 7 IB 163 19.2 Ebon MLEb-1 18 8 IB 53 8.4 Ebon MLEb-1 18 9 IIA 66 6.9 Ebon MLEb-1 18 10 IIB 122 24.5 Ebon MLEb-1 18 11 IIB 53 10.6 Ebon MLEb-1 18 12 IIB 23 3.0 Ebon MLEb-1 19 1 Historic 58 7.5 Ebon MLEb-1 19 2 IA 185 26.7 Ebon MLEb-1 19 3 IA 839 136.1 Ebon MLEb-1 19 4 IA 298 46.6 Ebon MLEb-1 19 5 IA 419 46.6 Ebon MLEb-1 19 6 IB 387 33.2 Ebon MLEb-1 19 7 IB 43 18.2 Ebon MLEb-1 19 8 IIA 56 9.6 Ebon MLEb-1 19 9 IIA 82 6.2 Ebon MLEb-1 19 10 IIB 134 23.0 Ebon MLEb-1 19 11 IIB 67 16.3 Ebon MLEb-1 19 12 IIIA 21 3.7 Ebon MLEb-1 20 1 Historic 74 8.0 Ebon MLEb-1 20 2 IA 344 54.4 Ebon MLEb-1 20 3 IA 458 69.8 Ebon MLEb-1 20 4 IA 227 43.1 Ebon MLEb-1 20 5 IA 98 13.0 Ebon MLEb-1 20 6 IA 147 14.5 Ebon MLEb-1 20 7 IB 50 9.9 Ebon MLEb-1 20 8 IB 41 7.6 Ebon MLEb-1 20 9 IIA 53 11.3 Ebon MLEb-1 20 10 IIB 106 21.7 Ebon MLEb-1 20 11 IIB 51 12.6 Ebon MLEb-1 20 12 IIIA 17 4.7 Ebon MLEb-5 1 1 I 62 17.6 230

Ebon MLEb-5 1 2 I 249 74.3 Ebon MLEb-5 1 3 I 124 31.6 Ebon MLEb-5 1 4 I 44 10.1 Ebon MLEb-5 13 1 I 3 1.6 1246 26.86 Ebon MLEb-5 13 2 I 10 4.6 999 25.77 Ebon MLEb-5 13 3 I 5 1.9 411 10.54 Ebon MLEb-5 13 4 I 5 1.9 71 1.35 Ebon MLEb-5 13 5 I 1 0.3 Ebon MLEb-5 15 1 I 36 8.7 Ebon MLEb-5 15 2 I 32 6.9 Ebon MLEb-5 15 3 I 13 3.9 Ebon MLEb-5 15 4 I 4 1.3 Ebon MLEb-5 15 5 I 1 0.1 Ebon MLEb-5 16 1 I 21 4.5 Ebon MLEb-5 16 2 I 61 15.1 Ebon MLEb-5 16 3 I 60 13.7 Ebon MLEb-5 16 4 I 36 10.4 Ebon MLEb-5 16 5 I 10 1.4 Ebon MLEb-5 17 1 I 9 2.9 Ebon MLEb-5 17 2 I 30 11.1 Ebon MLEb-5 17 3 I 14 5.7 Ebon MLEb-5 17 4 I 1 0.9 Ebon MLEb-5 18 1 I 26 12.1 Ebon MLEb-5 18 2 I 43 15.2 Ebon MLEb-5 18 3 I 18 4.5 Ebon MLEb-5 19 1 I 10 3.7 Ebon MLEb-5 19 2 I 63 20.6 Ebon MLEb-5 19 3 I 33 12.2 Ebon MLEb-5 19 4 I 26 4.7 Ebon MLEb-5 20 1 I 20 12.0 Ebon MLEb-5 20 2 I 51 20.0 Ebon MLEb-5 20 3 I 35 12.0 Ebon MLEb-5 20 4 I 26 10.0 Ebon MLEb-5 20 5 I 15 2.6 Ebon MLEb-5 20 6 I 1 0.2 Ebon MLEb-5 21 1 I 7 1.7 Ebon MLEb-5 21 2 I 30 10.9 Ebon MLEb-5 21 3 I 271 79.9 Ebon MLEb-5 21 4 I 62 11.5 Ebon MLEb-5 21 5 I 11 2.3 Ebon MLEb-5 22 1 I 52 16.7 Ebon MLEb-5 22 2 I 37 11.0 Ebon MLEb-5 22 3 I 11 5.6 Ebon MLEb-5 23 1 I 8 1.6 Ebon MLEb-5 23 2 I 19 5.3 Ebon MLEb-5 23 3 I 48 16.6 Ebon MLEb-5 23 4 I 92 20.9 Ebon MLEb-5 23 5 I 53 13.4 Ebon MLEb-5 24 1 I 4 0.7 Ebon MLEb-5 24 2 I 9 3.5 Ebon MLEb-5 24 3 I 82 25.6 Ebon MLEb-5 24 4 I 5 1.3 Ebon MLEb-5 24 5 I 1 0.2 Ebon MLEb-5 25 1 I 4 1.3 Ebon MLEb-5 25 2 I 7 2.0 Ebon MLEb-5 25 3 I 18 6.7 Ebon MLEb-5 25 4 I 40 8.1 Ebon MLEb-5 25 5 I 31 7.7 Ebon MLEb-5 26 1 I 5 1.1 Ebon MLEb-5 26 2 I 28 6.5 Ebon MLEb-5 26 3 I 77 31.9 Ebon MLEb-5 26 4 I 155 43.2

231

Ebon MLEb-5 26 5 I 32 4.8 Ebon MLEb-5 27 1 I 1 6.6 Ebon MLEb-5 27 2 I 50 60.0 Ebon MLEb-5 27 3 I 102 33.4 Ebon MLEb-5 27 4 I 194 43.5 Ebon MLEb-5 27 5 I 15 3.5 Moniak MLEb-31 2 1 IA 4 0.3 Moniak MLEb-31 2 2 IB 36 7.7 Moniak MLEb-31 2 3 IB 86 8.1 Moniak MLEb-31 2 4 IC 93 9.4 Moniak MLEb-31 2 5 IIA 144 35.0 Moniak MLEb-31 2 6 IIA 37 17.5 Moniak MLEb-31 2 7 IIA 45 7.7 Moniak MLEb-31 2 8 IIB 4 0.9 Moniak MLEb-31 3 1 IA 14 2.1 Moniak MLEb-31 3 2 IA 532 93.3 Moniak MLEb-31 3 3 IB 193 32.1 Moniak MLEb-31 3 4 IIA 87 9.6 Moniak MLEb-31 3 5 IIB 520 43.9 Moniak MLEb-31 3 6 IIB 14 1.9 Moniak MLEb-31 3 7 III 1 0.1 Moniak MLEb-31 4 2 IB 24 5.7 Moniak MLEb-31 4 3 III 1 0.2 Moniak MLEb-31 6 1 IA 3 1.3 117 4.71 Moniak MLEb-31 6 2 IB 24 7.1 419 12.17 Moniak MLEb-31 6 3 IB 8 2.1 362 7.24 Moniak MLEb-31 6 4 SD 14 1.5 127 2.66 Moniak MLEb-31 6 5 SD 41 7.0 613 13.97 Moniak MLEb-31 6 6 IIA 41 7.4 544 13.19 Moniak MLEb-31 6 7 IIA 34 14.1 323 10.13 Moniak MLEb-31 6 8 III 20 8.7 362 12 Moniak MLEb-31 6 9 III 5 1.2 120 2.97 Enekoion MLEB-33 2 1 IA 8 1.7 Enekoion MLEB-33 2 2 IA 12 3.4 Enekoion MLEB-33 2 3 IA 74 17.7 Enekoion MLEB-33 2 4 IB 89 17.1 Enekoion MLEB-33 2 5 II 7 1.1 Enekoion MLEB-33 8 1 I 20 3.6 26 1.02 Enekoion MLEB-33 8 2 I 21 4.4 48 2.7 Enekoion MLEB-33 8 3 I 7 0.9 273 3.75 Enekoion MLEB-33 8 4 I 91 0.96 Enekoion MLEB-33 8 5 I 2 0.01 Totals 15,421 2721.6 32,727 799.1

232

APPENDIX B

Taxonomic assignments and relative abundance by test pit and site for Moniak Islet and Enekoion Islet

233

6.4 mm samples 6.4 mm and 3.2 mm samples MLEb-1 MLEb-31 MLEB-33 MLEb-1 MLEb-31 MLEB-33 Taxon MNI NISP MNI NISP MNI NISP MNI NISP MNI NISP MNI NISP Selachii 2 8 3 3 1 7 1 2 2 2 1 1 Carcharhinidae Carcharhinus spp. 2 2 2 2 Acanthuridae 26 103 14 36 2 2 16 78 9 24 1 3 Acanthurus spp. 7 43 5 12 8 25 3 5 Ctenochaetus spp. 4 11 3 3 1 1 3 5 1 1 Naso spp. 3 9 5 7 1 1 2 4 1 1 1 1 Balistidae 23 587 15 54 7 14 11 255 8 58 1 13 Belonidae 6 13 7 20 1 3 5 50 8 50 1 3 Bothidae 5 18 5 16 0 0 5 31 5 31 2 3 Caesionidae 1 1 Carangidae 15 83 9 22 2 2 8 84 5 31 1 2 Carangoides spp. 3 8 3 5 2 9 4 5 Caranx spp. 8 45 9 28 1 4 7 11 4 7 Decapterus spp. 6 32 11 49 Elagatis bipinnulatus 3 27 3 10 Selar spp. 7 87 4 5 1 1 8 27 1 1 1 1 Chaetodontidae 1 9 1 1 2 8 Cirrhitidae 8 43 10 36 9 67 6 23 Diodontidae Diodon spp. 6 192 5 17 1 1 3 78 3 10 1 1 Exocoetidae 6 54 1 3 12 267 6 11 2 4 Fistulariidae Fistularia commersonii 5 24 8 27 1 2 3 11 6 26 Gerreidae Gerres spp. 4 6 Holocentridae 26 88 13 31 2 3 19 76 7 13 Myripristis spp. 3 22 2 7 8 47 2 5 1 1 Neoniphon spp. 3 11 4 5 2 6 1 1 Sargocentron spp. 12 78 8 26 1 2 12 103 6 12 1 2 Kuhliidae Kuhlia spp. 3 8 2 2 5 18 2 2 Kyphosidae Kyphosus spp. 5 72 4 10 1 1 7 36 3 8 Labridae 13 75 13 52 2 5 8 31 5 14 Lethrinidae 6 37 6 19 1 1 8 60 4 4 Gnathodentex aureolineatus 2 2 1 1 Lethrinus spp. 15 110 6 20 1 2 12 84 4 7 1 4 Monotaxis grandoculis 9 35 7 24 2 2 7 43 4 11 Lutjanidae 14 145 8 29 5 14 12 106 7 20 2 6 Aprion virescens 1 1 1 1 Lutjanus spp. 29 179 27 95 7 16 15 75 12 39 2 4 Mugilidae 5 16 4 9 2 8 1 1 Mullidae 4 25 4 6 2 4 5 17 4 13 1 1 Mulloidichthys spp. 7 55 7 11 1 2 7 35 7 25 1 1 Parupeneus spp. 5 24 6 19 5 18 3 8 Muraenidae 7 16 8 16 3 7 11 54 7 33 2 7 Ostraciidae 1 58 4 50 Pomacentridae 1 11 3 5 5 24 3 4 1 1 Scaridae 37 233 16 134 7 17 11 99 8 40 2 9 Calotomus spp. 4 9 2 2 Chlorurus spp. 12 47 5 16 4 9 4 5 Hipposcarus longiceps 14 103 14 67 1 1 9 25 5 10 Scarus spp. 10 104 4 10 6 16 1 1 Scombridae 15 75 1 1 2 2 11 56 1 1 1 1 Katsuwonus pelamis 27 387 3 7 2 4 10 64 3 7 Thunnus spp. 5 13 3 6 234

Serranidae 33 550 17 125 5 20 22 336 9 69 4 26 Anyperodon leucogrammicus 2 10 2 5 2 2 Cephalopholis spp. 4 9 1 1 1 1 2 6 Epinephelus spp. 7 19 8 13 5 13 2 2 Plectropomus spp. 2 7 1 2 Variola louti 5 18 7 14 1 1 2 2 2 2 Siganidae Siganus spp. 11 118 4 4 1 1 5 20 4 6 Sphyraenidae Sphyraena spp. 5 21 5 29 1 1 Totals 509 4188 325 1083 67 144 378 2655 192 648 34 98

235

APPENDIX C

Taxonomic assignments and relative abundance by site and cultural layer for Ebon Islet

236

Screen Size Site TPs Layer Family Genus Species NISP MNI 6.4 mm MLEb-1 17-20 HISTORIC Acanthuridae 9 2 6.4 mm MLEb-1 17-20 HISTORIC Acanthuridae Acanthurus spp. 17 3 6.4 mm MLEb-1 17-20 HISTORIC Acanthuridae Ctenochaetus sp. 4 1 6.4 mm MLEb-1 17-20 HISTORIC Balistidae 2 1 6.4 mm MLEb-1 17-20 HISTORIC Carangidae 2 2 6.4 mm MLEb-1 17-20 HISTORIC Carangidae Caranx sp. 2 1 6.4 mm MLEb-1 17-20 HISTORIC Cirrhitidae 1 1 6.4 mm MLEb-1 17-20 HISTORIC Holocentridae 10 4 6.4 mm MLEb-1 17-20 HISTORIC Holocentridae Sargocentron sp. 2 1 6.4 mm MLEb-1 17-20 HISTORIC Kyphosidae Kyphosus spp. 15 2 6.4 mm MLEb-1 17-20 HISTORIC Labridae 4 1 6.4 mm MLEb-1 17-20 HISTORIC Lethrinidae 4 1 6.4 mm MLEb-1 17-20 HISTORIC Lethrinidae Lethrinus sp. 5 1 6.4 mm MLEb-1 17-20 HISTORIC Lethrinidae Monotaxis grandoculis 1 1 6.4 mm MLEb-1 17-20 HISTORIC Lutjanidae 7 1 6.4 mm MLEb-1 17-20 HISTORIC Lutjanidae Lutjanus spp. 9 2 6.4 mm MLEb-1 17-20 HISTORIC Lutjanidae Lutjanus cf. kasmira 2 1 6.4 mm MLEb-1 17-20 HISTORIC Mugilidae 3 1 6.4 mm MLEb-1 17-20 HISTORIC Mullidae Mulloidichthys sp. 2 1 6.4 mm MLEb-1 17-20 HISTORIC Scaridae 3 2 6.4 mm MLEb-1 17-20 HISTORIC Scaridae Calotomus sp. 1 1 6.4 mm MLEb-1 17-20 HISTORIC Scaridae Chlorurus sp. 2 1 6.4 mm MLEb-1 17-20 HISTORIC Scaridae Scarus sp. 4 1 6.4 mm MLEb-1 17-20 HISTORIC Serranidae 8 2 6.4 mm MLEb-1 17-20 IA Acanthuridae 87 19 6.4 mm MLEb-1 17-20 IA Acanthuridae Acanthurus spp. 25 3 6.4 mm MLEb-1 17-20 IA Acanthuridae Ctenochaetus spp. 6 2 6.4 mm MLEb-1 17-20 IA Acanthuridae Naso sp. 7 1 6.4 mm MLEb-1 17-20 IA Balistidae 562 17 6.4 mm MLEb-1 17-20 IA Belonidae 9 3 6.4 mm MLEb-1 17-20 IA Bothidae 13 2 6.4 mm MLEb-1 17-20 IA Carangidae 62 10 6.4 mm MLEb-1 17-20 IA Carangidae Carangoides spp. 7 2 6.4 mm MLEb-1 17-20 IA Carangidae Caranx spp. 38 4 6.4 mm MLEb-1 17-20 IA Carangidae Decapterus spp. 22 3 6.4 mm MLEb-1 17-20 IA Carangidae Elagatis bipinnulatus 25 2 6.4 mm MLEb-1 17-20 IA Carangidae Selar spp. 66 4 6.4 mm MLEb-1 17-20 IA Chaetodontidae 9 1 6.4 mm MLEb-1 17-20 IA Cirrhitidae 34 4 6.4 mm MLEb-1 17-20 IA Diodontidae Diodon spp. 187 3 237

6.4 mm MLEb-1 17-20 IA Exocoetidae 29 1 6.4 mm MLEb-1 17-20 IA Fistulariidae Fistularia commersonii 21 2 6.4 mm MLEb-1 17-20 IA Selachii 7 1 6.4 mm MLEb-1 17-20 IA Holocentridae 60 14 6.4 mm MLEb-1 17-20 IA Holocentridae Myripristis spp. 18 2 6.4 mm MLEb-1 17-20 IA Holocentridae Sargocentron spp. 59 8 6.4 mm MLEb-1 17-20 IA Holocentridae Neoniphon spp. 10 2 6.4 mm MLEb-1 17-20 IA Kuhliidae Kuhlia sp. 4 1 6.4 mm MLEb-1 17-20 IA Kyphosidae Kyphosus spp. 54 2 6.4 mm MLEb-1 17-20 IA Labridae 56 6 6.4 mm MLEb-1 17-20 IA Lethrinidae 24 2 6.4 mm MLEb-1 17-20 IA Lethrinidae Gnathodentex aureolineatus 1 1 6.4 mm MLEb-1 17-20 IA Lethrinidae Lethrinus spp. 72 8 6.4 mm MLEb-1 17-20 IA Lethrinidae Monotaxis grandoculis 20 3 6.4 mm MLEb-1 17-20 IA Lutjanidae 108 6 6.4 mm MLEb-1 17-20 IA Lutjanidae Lutjanus spp. 96 7 6.4 mm MLEb-1 17-20 IA Lutjanidae Lutjanus cf. kasmira 34 10 6.4 mm MLEb-1 17-20 IA Mugilidae 9 1 6.4 mm MLEb-1 17-20 IA Mullidae 24 3 6.4 mm MLEb-1 17-20 IA Mullidae Mulloidichthys spp. 48 3 6.4 mm MLEb-1 17-20 IA Mullidae Parupeneus spp. 20 3 6.4 mm MLEb-1 17-20 IA Muraenidae 10 3 6.4 mm MLEb-1 17-20 IA Ostraciidae 58 1 6.4 mm MLEb-1 17-20 IA Pomacentridae 11 1 6.4 mm MLEb-1 17-20 IA Scaridae 205 28 6.4 mm MLEb-1 17-20 IA Scaridae Calotomus sp. 6 1 6.4 mm MLEb-1 17-20 IA Scaridae Chlorurus spp. 40 8 6.4 mm MLEb-1 17-20 IA Scaridae Hipposcarus longiceps 85 9 6.4 mm MLEb-1 17-20 IA Scaridae Scarus spp. 89 5 6.4 mm MLEb-1 17-20 IA Scombridae 36 4 6.4 mm MLEb-1 17-20 IA Scombridae Katsuwonus pelamis 207 9 6.4 mm MLEb-1 17-20 IA Scombridae Thunnus sp. 5 1 6.4 mm MLEb-1 17-20 IA Serranidae 447 22 6.4 mm MLEb-1 17-20 IA Serranidae Anyperodon leucogrammicus 10 2 6.4 mm MLEb-1 17-20 IA Serranidae Cephalopholis spp. 9 4 6.4 mm MLEb-1 17-20 IA Serranidae Epinephelus spp. 15 4 6.4 mm MLEb-1 17-20 IA Serranidae Plectropomus sp. 6 1 6.4 mm MLEb-1 17-20 IA Serranidae Variola louti 14 3 6.4 mm MLEb-1 17-20 IA Siganidae Siganus spp. 103 7 6.4 mm MLEb-1 17-20 IA Sphyraenidae Sphyraena spp. 16 3 6.4 mm MLEb-1 17-20 IB Acanthuridae 3 1 238

6.4 mm MLEb-1 17-20 IB Acanthuridae Naso sp. 1 1 6.4 mm MLEb-1 17-20 IB Acanthuridae Ctenochaetus sp. 1 1 6.4 mm MLEb-1 17-20 IB Balistidae 15 2 6.4 mm MLEb-1 17-20 IB Belonidae 1 1 6.4 mm MLEb-1 17-20 IB Bothidae 3 1 6.4 mm MLEb-1 17-20 IB Carangidae 9 1 6.4 mm MLEb-1 17-20 IB Carangidae Carangoides sp. 1 1 6.4 mm MLEb-1 17-20 IB Carangidae Caranx sp. 3 1 6.4 mm MLEb-1 17-20 IB Carangidae Decapterus sp. 5 1 6.4 mm MLEb-1 17-20 IB Carangidae Elagatis bipinnulatus 2 1 6.4 mm MLEb-1 17-20 IB Carangidae Selar sp. 11 1 6.4 mm MLEb-1 17-20 IB Cirrhitidae 5 2 6.4 mm MLEb-1 17-20 IB Diodontidae Diodon sp. 3 1 6.4 mm MLEb-1 17-20 IB Exocoetidae 19 2 6.4 mm MLEb-1 17-20 IB Fistulariidae Fistularia commersonii 1 1 6.4 mm MLEb-1 17-20 IB Holocentridae 10 5 6.4 mm MLEb-1 17-20 IB Holocentridae Myripristis sp. 4 1 6.4 mm MLEb-1 17-20 IB Holocentridae Neoniphon sp. 1 1 6.4 mm MLEb-1 17-20 IB Holocentridae Sargocentron spp. 15 2 6.4 mm MLEb-1 17-20 IB Kuhliidae Kuhlia sp. 2 1 6.4 mm MLEb-1 17-20 IB Kyphosidae Kyphosus sp. 3 1 6.4 mm MLEb-1 17-20 IB Labridae 8 3 6.4 mm MLEb-1 17-20 IB Lethrinidae 7 2 6.4 mm MLEb-1 17-20 IB Lethrinidae Gnathodentex aureolineatus 1 1 6.4 mm MLEb-1 17-20 IB Lethrinidae Lethrinus spp. 22 3 6.4 mm MLEb-1 17-20 IB Lethrinidae Monotaxis grandoculis 10 2 6.4 mm MLEb-1 17-20 IB Lutjanidae 15 3 6.4 mm MLEb-1 17-20 IB Lutjanidae Lutjanus spp. 19 3 6.4 mm MLEb-1 17-20 IB Lutjanidae Lutjanus cf. kasmira 5 1 6.4 mm MLEb-1 17-20 IB Mugilidae 1 1 6.4 mm MLEb-1 17-20 IB Mullidae 1 1 6.4 mm MLEb-1 17-20 IB Mullidae Mulloidichthys sp. 2 1 6.4 mm MLEb-1 17-20 IB Mullidae Parupeneus spp. 4 2 6.4 mm MLEb-1 17-20 IB Muraenidae 4 2 6.4 mm MLEb-1 17-20 IB Scaridae 12 2 6.4 mm MLEb-1 17-20 IB Scaridae Chlorurus spp. 4 2 6.4 mm MLEb-1 17-20 IB Scaridae Hipposcarus longiceps 8 1 6.4 mm MLEb-1 17-20 IB Scaridae Scarus spp. 7 2 6.4 mm MLEb-1 17-20 IB Scombridae 9 3 6.4 mm MLEb-1 17-20 IB Scombridae Katsuwonus pelamis 46 6 6.4 mm MLEb-1 17-20 IB Scombridae Thunnus spp. 5 2 239

6.4 mm MLEb-1 17-20 IB Serranidae 60 4 6.4 mm MLEb-1 17-20 IB Serranidae Epinephelus sp. 2 1 6.4 mm MLEb-1 17-20 IB Serranidae Variola louti 3 1 6.4 mm MLEb-1 17-20 IB Siganidae Siganus sp. 10 1 6.4 mm MLEb-1 17-20 IB Sphyraenidae Sphyraena sp. 3 1 6.4 mm MLEb-1 17-20 IIA Acanthuridae 3 3 6.4 mm MLEb-1 17-20 IIA Acanthuridae Acanthurus sp. 1 1 6.4 mm MLEb-1 17-20 IIA Balistidae 5 1 6.4 mm MLEb-1 17-20 IIA Belonidae 2 1 6.4 mm MLEb-1 17-20 IIA Carangidae 4 1 6.4 mm MLEb-1 17-20 IIA Carangidae Caranx sp. 1 1 6.4 mm MLEb-1 17-20 IIA Carangidae Decapterus sp. 2 1 6.4 mm MLEb-1 17-20 IIA Carangidae Selar sp. 2 1 6.4 mm MLEb-1 17-20 IIA Carcharhinidae Carcharhinus cf. longimanus 1 1 6.4 mm MLEb-1 17-20 IIA Cirrhitidae 3 1 6.4 mm MLEb-1 17-20 IIA Diodontidae Diodon sp. 1 1 6.4 mm MLEb-1 17-20 IIA Exocoetidae 4 1 6.4 mm MLEb-1 17-20 IIA Fistulariidae Fistularia commersonii 1 1 6.4 mm MLEb-1 17-20 IIA Holocentridae 3 1 6.4 mm MLEb-1 17-20 IIA Holocentridae Sargocentron sp. 2 1 6.4 mm MLEb-1 17-20 IIA Labridae 4 2 6.4 mm MLEb-1 17-20 IIA Lethrinidae Lethrinus sp. 4 1 6.4 mm MLEb-1 17-20 IIA Lethrinidae Monotaxis grandoculis 3 2 6.4 mm MLEb-1 17-20 IIA Lutjanidae 2 1 6.4 mm MLEb-1 17-20 IIA Lutjanidae Lutjanus sp. 2 1 6.4 mm MLEb-1 17-20 IIA Mullidae Mulloidichthys sp. 2 1 6.4 mm MLEb-1 17-20 IIA Muraenidae 1 1 6.4 mm MLEb-1 17-20 IIA Scaridae 3 1 6.4 mm MLEb-1 17-20 IIA Scaridae Hipposcarus longiceps 3 2 6.4 mm MLEb-1 17-20 IIA Scaridae Scarus sp. 3 1 6.4 mm MLEb-1 17-20 IIA Scombridae 5 1 6.4 mm MLEb-1 17-20 IIA Scombridae Katsuwonus pelamis 35 4 6.4 mm MLEb-1 17-20 IIA Scombridae Thunnus sp. 1 1 6.4 mm MLEb-1 17-20 IIA Serranidae 14 2 6.4 mm MLEb-1 17-20 IIA Serranidae Epinephelus sp. 1 1 6.4 mm MLEb-1 17-20 IIA Serranidae Variola louti 1 1 6.4 mm MLEb-1 17-20 IIA Siganidae Siganus sp. 2 1 6.4 mm MLEb-1 17-20 IIB Acanthuridae Naso sp. 1 1 6.4 mm MLEb-1 17-20 IIB Balistidae 3 2 6.4 mm MLEb-1 17-20 IIB Belonidae 1 1 6.4 mm MLEb-1 17-20 IIB Bothidae 1 1 240

6.4 mm MLEb-1 17-20 IIB Carangidae 6 1 6.4 mm MLEb-1 17-20 IIB Carangidae Caranx sp. 1 1 6.4 mm MLEb-1 17-20 IIB Carangidae Decapterus sp. 3 1 6.4 mm MLEb-1 17-20 IIB Carangidae Selar sp. 8 1 6.4 mm MLEb-1 17-20 IIB Selachii 1 1 6.4 mm MLEb-1 17-20 IIB Carcharhinidae Carcharhinus cf. melanopterus 1 1 6.4 mm MLEb-1 17-20 IIB Diodontidae Diodon sp. 1 1 6.4 mm MLEb-1 17-20 IIB Exocoetidae 1 1 6.4 mm MLEb-1 17-20 IIB Fistulariidae Fistularia commersonii 1 1 6.4 mm MLEb-1 17-20 IIB Holocentridae 4 1 6.4 mm MLEb-1 17-20 IIB Kuhliidae Kuhlia sp. 2 1 6.4 mm MLEb-1 17-20 IIB Labridae 3 1 6.4 mm MLEb-1 17-20 IIB Lethrinidae 2 1 6.4 mm MLEb-1 17-20 IIB Lethrinidae Lethrinus sp. 6 1 6.4 mm MLEb-1 17-20 IIB Lethrinidae Monotaxis grandoculis 1 1 6.4 mm MLEb-1 17-20 IIB Lutjanidae 13 3 6.4 mm MLEb-1 17-20 IIB Lutjanidae Lutjanus spp. 8 2 6.4 mm MLEb-1 17-20 IIB Lutjanidae Lutjanus cf. kasmira 1 1 6.4 mm MLEb-1 17-20 IIB Mugilidae 3 2 6.4 mm MLEb-1 17-20 IIB Mullidae Mulloidichthys sp. 1 1 6.4 mm MLEb-1 17-20 IIB Muraenidae 1 1 6.4 mm MLEb-1 17-20 IIB Scaridae 10 4 6.4 mm MLEb-1 17-20 IIB Scaridae Calotomus sp. 1 1 6.4 mm MLEb-1 17-20 IIB Scaridae Chlorurus sp. 1 1 6.4 mm MLEb-1 17-20 IIB Scaridae Hipposcarus longiceps 7 2 6.4 mm MLEb-1 17-20 IIB Scaridae Scarus sp. 1 1 6.4 mm MLEb-1 17-20 IIB Scombridae 25 7 6.4 mm MLEb-1 17-20 IIB Scombridae Katsuwonus pelamis 95 7 6.4 mm MLEb-1 17-20 IIB Scombridae Thunnus sp. 2 1 6.4 mm MLEb-1 17-20 IIB Serranidae 21 3 6.4 mm MLEb-1 17-20 IIB Serranidae Epinephelus sp. 1 1 6.4 mm MLEb-1 17-20 IIB Serranidae Plectropomus sp. 1 1 6.4 mm MLEb-1 17-20 IIB Siganidae Siganus sp. 2 1 6.4 mm MLEb-1 17-20 IIB Sphyraenidae Sphyraena sp. 2 1 6.4 mm MLEb-1 17-20 IIIA Acanthuridae 1 1 6.4 mm MLEb-1 17-20 IIIA Bothidae 1 1 6.4 mm MLEb-1 17-20 IIIA Exocoetidae 1 1 6.4 mm MLEb-1 17-20 IIIA Holocentridae 1 1 6.4 mm MLEb-1 17-20 IIIA Lethrinidae Lethrinus sp. 1 1 6.4 mm MLEb-1 17-20 IIIA Lutjanidae Lutjanus sp. 3 1 6.4 mm MLEb-1 17-20 IIIA Scaridae Calotomus sp. 1 1 241

6.4 mm MLEb-1 17-20 IIIA Scombridae Katsuwonus pelamis 4 1 6.4 mm MLEb-1 17-20 IIIA Siganidae Siganus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Acanthuridae 14 2 6.4 and 3.2 mm MLEb-1 17 Historic Acanthuridae Acanthurus spp. 9 3 6.4 and 3.2 mm MLEb-1 17 Historic Acanthuridae Ctenochaetus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 Historic Acanthuridae Naso sp. 3 1 6.4 and 3.2 mm MLEb-1 17 Historic Balistidae 2 1 6.4 and 3.2 mm MLEb-1 17 Historic Belonidae 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Carangidae 4 1 6.4 and 3.2 mm MLEb-1 17 Historic Carangidae Caranx spp. 2 2 6.4 and 3.2 mm MLEb-1 17 Historic Cirrhitidae 2 1 6.4 and 3.2 mm MLEb-1 17 Historic Holocentridae 3 2 6.4 and 3.2 mm MLEb-1 17 Historic Holocentridae Myripristis sp. 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Holocentridae Sargocentron sp. 4 1 6.4 and 3.2 mm MLEb-1 17 Historic Kyphosidae Kyphosus spp. 7 2 6.4 and 3.2 mm MLEb-1 17 Historic Lethrinidae 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Lethrinidae Lethrinus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Lethrinidae Monotaxis grandoculis 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Lutjanidae 6 1 6.4 and 3.2 mm MLEb-1 17 Historic Lutjanidae Lutjanus spp. 5 2 6.4 and 3.2 mm MLEb-1 17 Historic Ostraciidae 1 1 6.4 and 3.2 mm MLEb-1 17 Historic Pomacentridae 2 1 6.4 and 3.2 mm MLEb-1 17 Historic Scaridae 3 1 6.4 and 3.2 mm MLEb-1 17 Historic Scaridae Scarus sp. 3 1 6.4 and 3.2 mm MLEb-1 17 Historic Serranidae 5 1 6.4 and 3.2 mm MLEb-1 17 IA Acanthuridae 38 7 6.4 and 3.2 mm MLEb-1 17 IA Acanthuridae Acanthurus spp. 12 3 6.4 and 3.2 mm MLEb-1 17 IA Acanthuridae Ctenochaetus spp. 3 2 6.4 and 3.2 mm MLEb-1 17 IA Acanthuridae Naso sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IA Balistidae 198 4 6.4 and 3.2 mm MLEb-1 17 IA Belonidae 11 1 6.4 and 3.2 mm MLEb-1 17 IA Bothidae 19 1 6.4 and 3.2 mm MLEb-1 17 IA Caesionidae 1 1 6.4 and 3.2 mm MLEb-1 17 IA Carangidae 28 1 6.4 and 3.2 mm MLEb-1 17 IA Carangidae Carangoides spp. 9 2 6.4 and 3.2 mm MLEb-1 17 IA Carangidae Caranx spp. 5 2 6.4 and 3.2 mm MLEb-1 17 IA Carangidae Decapterus spp. 7 3 6.4 and 3.2 mm MLEb-1 17 IA Carangidae Elagatis bipinnulatus 9 2 6.4 and 3.2 mm MLEb-1 17 IA Carangidae Selar spp. 13 3 6.4 and 3.2 mm MLEb-1 17 IA Chaetodontidae 6 1 6.4 and 3.2 mm MLEb-1 17 IA Cirrhitidae 31 5 242

6.4 and 3.2 mm MLEb-1 17 IA Diodontidae Diodon sp. 75 1 6.4 and 3.2 mm MLEb-1 17 IA Exocoetidae 173 6 6.4 and 3.2 mm MLEb-1 17 IA Fistulariidae Fistularia commersonii 2 1 6.4 and 3.2 mm MLEb-1 17 IA Selachii 2 1 6.4 and 3.2 mm MLEb-1 17 IA Gerreidae Gerres spp. 4 2 6.4 and 3.2 mm MLEb-1 17 IA Holocentridae 31 11 6.4 and 3.2 mm MLEb-1 17 IA Holocentridae Myripristis spp. 30 3 6.4 and 3.2 mm MLEb-1 17 IA Holocentridae Neoniphon sp. 4 1 6.4 and 3.2 mm MLEb-1 17 IA Holocentridae Sargocentron spp. 53 5 6.4 and 3.2 mm MLEb-1 17 IA Kuhliidae Kuhlia sp. 6 1 6.4 and 3.2 mm MLEb-1 17 IA Kyphosidae Kyphosus spp. 18 3 6.4 and 3.2 mm MLEb-1 17 IA Labridae 19 3 6.4 and 3.2 mm MLEb-1 17 IA Lethrinidae 19 2 6.4 and 3.2 mm MLEb-1 17 IA Lethrinidae Lethrinus spp. 23 4 6.4 and 3.2 mm MLEb-1 17 IA Lethrinidae Monotaxis grandoculis 18 2 6.4 and 3.2 mm MLEb-1 17 IA Lutjanidae 46 4 6.4 and 3.2 mm MLEb-1 17 IA Lutjanidae Lutjanus spp. 37 5 6.4 and 3.2 mm MLEb-1 17 IA Lutjanidae Lutjanus cf. kasmira 6 2 6.4 and 3.2 mm MLEb-1 17 IA Mugilidae 7 1 6.4 and 3.2 mm MLEb-1 17 IA Mullidae 12 2 6.4 and 3.2 mm MLEb-1 17 IA Mullidae Mulloidichthys spp. 19 2 6.4 and 3.2 mm MLEb-1 17 IA Mullidae Parupeneus sp. 6 1 6.4 and 3.2 mm MLEb-1 17 IA Muraenidae 31 4 6.4 and 3.2 mm MLEb-1 17 IA Ostraciidae 43 1 6.4 and 3.2 mm MLEb-1 17 IA Pomacentridae 18 2 6.4 and 3.2 mm MLEb-1 17 IA Scaridae 71 6 6.4 and 3.2 mm MLEb-1 17 IA Scaridae Chlorurus spp. 6 2 6.4 and 3.2 mm MLEb-1 17 IA Scaridae Hipposcarus longiceps 16 5 6.4 and 3.2 mm MLEb-1 17 IA Scaridae Scarus spp. 6 2 6.4 and 3.2 mm MLEb-1 17 IA Scombridae 32 4 6.4 and 3.2 mm MLEb-1 17 IA Scombridae Katsuwonus pelamis 33 3 6.4 and 3.2 mm MLEb-1 17 IA Scombridae Thunnus sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IA Serranidae 189 10 6.4 and 3.2 mm MLEb-1 17 IA Serranidae Anyperodon leucogrammicus 2 2 6.4 and 3.2 mm MLEb-1 17 IA Serranidae Cephalopholis sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IA Serranidae Epinephelus spp. 12 4 6.4 and 3.2 mm MLEb-1 17 IA Serranidae Variola louti 1 1 6.4 and 3.2 mm MLEb-1 17 IA Siganidae Siganus sp. 7 1 6.4 and 3.2 mm MLEb-1 17 IA Sphyraenidae Sphyraena spp. 19 3 6.4 and 3.2 mm MLEb-1 17 IB Acanthuridae 21 4 6.4 and 3.2 mm MLEb-1 17 IB Acanthuridae Acanthurus sp. 3 1 243

6.4 and 3.2 mm MLEb-1 17 IB Balistidae 48 3 6.4 and 3.2 mm MLEb-1 17 IB Belonidae 28 1 6.4 and 3.2 mm MLEb-1 17 IB Bothidae 8 1 6.4 and 3.2 mm MLEb-1 17 IB Carangidae 32 3 6.4 and 3.2 mm MLEb-1 17 IB Carangidae Caranx spp. 3 2 6.4 and 3.2 mm MLEb-1 17 IB Carangidae Decapterus spp. 15 2 6.4 and 3.2 mm MLEb-1 17 IB Carangidae Elagatis bipinnulatus 1 1 6.4 and 3.2 mm MLEb-1 17 IB Carangidae Selar spp. 6 2 6.4 and 3.2 mm MLEb-1 17 IB Carcharhinidae Carcharhinus cf. amblyrhynchos 1 1 6.4 and 3.2 mm MLEb-1 17 IB Chaetodontidae 2 1 6.4 and 3.2 mm MLEb-1 17 IB Cirrhitidae 33 2 6.4 and 3.2 mm MLEb-1 17 IB Diodontidae Diodon sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IB Exocoetidae 69 3 6.4 and 3.2 mm MLEb-1 17 IB Fistulariidae Fistularia commersonii 7 1 6.4 and 3.2 mm MLEb-1 17 IB Gerreidae Gerres sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IB Holocentridae 31 4 6.4 and 3.2 mm MLEb-1 17 IB Holocentridae Myripristis spp. 14 3 6.4 and 3.2 mm MLEb-1 17 IB Holocentridae Neoniphon sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IB Holocentridae Sargocentron spp. 41 4 6.4 and 3.2 mm MLEb-1 17 IB Kuhliidae Kuhlia spp. 11 3 6.4 and 3.2 mm MLEb-1 17 IB Kyphosidae Kyphosus sp. 10 1 6.4 and 3.2 mm MLEb-1 17 IB Labridae 9 3 6.4 and 3.2 mm MLEb-1 17 IB Lethrinidae 33 3 6.4 and 3.2 mm MLEb-1 17 IB Lethrinidae Lethrinus spp. 49 5 6.4 and 3.2 mm MLEb-1 17 IB Lethrinidae Monotaxis grandoculis 20 2 6.4 and 3.2 mm MLEb-1 17 IB Lutjanidae 39 4 6.4 and 3.2 mm MLEb-1 17 IB Lutjanidae Aprion sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IB Lutjanidae Lutjanus spp. 18 2 6.4 and 3.2 mm MLEb-1 17 IB Lutjanidae Lutjanus cf. kasmira 3 2 6.4 and 3.2 mm MLEb-1 17 IB Mugilidae 1 1 6.4 and 3.2 mm MLEb-1 17 IB Mullidae 2 1 6.4 and 3.2 mm MLEb-1 17 IB Mullidae Mulloidichthys spp. 14 3 6.4 and 3.2 mm MLEb-1 17 IB Mullidae Parupeneus spp. 9 2 6.4 and 3.2 mm MLEb-1 17 IB Muraenidae 19 5 6.4 and 3.2 mm MLEb-1 17 IB Ostraciidae 5 1 6.4 and 3.2 mm MLEb-1 17 IB Pomacentridae 3 1 6.4 and 3.2 mm MLEb-1 17 IB Scaridae 15 2 6.4 and 3.2 mm MLEb-1 17 IB Scaridae Chlorurus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IB Scaridae Hipposcarus longiceps 3 1 6.4 and 3.2 mm MLEb-1 17 IB Scaridae Scarus spp. 6 2 6.4 and 3.2 mm MLEb-1 17 IB Scombridae 17 3 244

6.4 and 3.2 mm MLEb-1 17 IB Scombridae Katsuwonus pelamis 6 2 6.4 and 3.2 mm MLEb-1 17 IB Scombridae Thunnus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IB Serranidae 121 6 6.4 and 3.2 mm MLEb-1 17 IB Serranidae Cephalopholis sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IB Serranidae Epinephelus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IB Serranidae Variola louti 1 1 6.4 and 3.2 mm MLEb-1 17 IB Siganidae Siganus spp. 10 2 6.4 and 3.2 mm MLEb-1 17 IB Sphyraenidae Sphyraena sp. 8 1 6.4 and 3.2 mm MLEb-1 17 IIA Acanthuridae 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Acanthuridae Acanthurus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Balistidae 3 1 6.4 and 3.2 mm MLEb-1 17 IIA Belonidae 3 1 6.4 and 3.2 mm MLEb-1 17 IIA Bothidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Carangidae 9 1 6.4 and 3.2 mm MLEb-1 17 IIA Carangidae Decapterus spp. 5 2 6.4 and 3.2 mm MLEb-1 17 IIA Carangidae Selar sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Exocoetidae 11 1 6.4 and 3.2 mm MLEb-1 17 IIA Holocentridae 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Holocentridae Sargocentron sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Kyphosidae Kyphosus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Labridae 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Lethrinidae 4 1 6.4 and 3.2 mm MLEb-1 17 IIA Lethrinidae Lethrinus sp. 6 1 6.4 and 3.2 mm MLEb-1 17 IIA Lethrinidae Monotaxis grandoculis 4 2 6.4 and 3.2 mm MLEb-1 17 IIA Lutjanidae 4 1 6.4 and 3.2 mm MLEb-1 17 IIA Mullidae 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Mullidae Mulloidichthys sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Mullidae Parupeneus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIA Muraenidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Ostraciidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Pomacentridae 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Scaridae 4 1 6.4 and 3.2 mm MLEb-1 17 IIA Scaridae Chlorurus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Scaridae Hipposcarus longiceps 5 2 6.4 and 3.2 mm MLEb-1 17 IIA Scombridae 3 1 6.4 and 3.2 mm MLEb-1 17 IIA Scombridae Katsuwonus pelamis 8 2 6.4 and 3.2 mm MLEb-1 17 IIA Serranidae 10 2 6.4 and 3.2 mm MLEb-1 17 IIA Siganidae Siganus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIA Sphyraenidae Sphyraena sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIB Acanthuridae 2 1 6.4 and 3.2 mm MLEb-1 17 IIB Balistidae 3 1 245

6.4 and 3.2 mm MLEb-1 17 IIB Belonidae 7 1 6.4 and 3.2 mm MLEb-1 17 IIB Bothidae 2 1 6.4 and 3.2 mm MLEb-1 17 IIB Carangidae 10 1 6.4 and 3.2 mm MLEb-1 17 IIB Carangidae Caranx sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Carangidae Decapterus spp. 20 3 6.4 and 3.2 mm MLEb-1 17 IIB Carangidae Selar sp. 5 1 6.4 and 3.2 mm MLEb-1 17 IIB Carcharhinidae Carcharhinus cf. melanopterus 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Diodontidae Diodon sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Exocoetidae 13 1 6.4 and 3.2 mm MLEb-1 17 IIB Fistulariidae Fistularia commersonii 2 1 6.4 and 3.2 mm MLEb-1 17 IIB Gerreidae Gerres sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Holocentridae 9 1 6.4 and 3.2 mm MLEb-1 17 IIB Holocentridae Myripristis sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIB Holocentridae Sargocentron sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IIB Kuhliidae Kuhlia sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Lethrinidae 3 1 6.4 and 3.2 mm MLEb-1 17 IIB Lethrinidae Lethrinus sp. 5 1 6.4 and 3.2 mm MLEb-1 17 IIB Lutjanidae 8 1 6.4 and 3.2 mm MLEb-1 17 IIB Lutjanidae Lutjanus sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IIB Mullidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Mullidae Mulloidichthys sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Mullidae Parupeneus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Muraenidae 3 1 6.4 and 3.2 mm MLEb-1 17 IIB Scaridae 6 1 6.4 and 3.2 mm MLEb-1 17 IIB Scaridae Hipposcarus longiceps 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Scaridae Scarus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Scombridae 4 3 6.4 and 3.2 mm MLEb-1 17 IIB Scombridae Katsuwonus pelamis 16 2 6.4 and 3.2 mm MLEb-1 17 IIB Scombridae Thunnus sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIB Serranidae 9 2 6.4 and 3.2 mm MLEb-1 17 IIB Siganidae Siganus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIIA Acanthuridae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Balistidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Bothidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Carangidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Carangidae Decapterus sp. 2 1 6.4 and 3.2 mm MLEb-1 17 IIIA Carangidae Selar sp. 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Cirrhitidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Exocoetidae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Labridae 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Lutjanidae 3 1 246

6.4 and 3.2 mm MLEb-1 17 IIIA Lutjanidae Lutjanus sp. 3 1 6.4 and 3.2 mm MLEb-1 17 IIIA Scombridae Katsuwonus pelamis 1 1 6.4 and 3.2 mm MLEb-1 17 IIIA Serranidae 2 1 6.4 mm MLEb-1 6 IA Balistidae 1 1 6.4 mm MLEb-1 6 IA Bothidae 1 1 6.4 mm MLEb-1 6 IA Carangidae Caranx sp. 1 1 6.4 mm MLEb-1 6 IA Carangidae Decapterus sp. 1 1 6.4 mm MLEb-1 6 IA Carcharhinidae Carcharhinus cf. melanopterus 1 1 6.4 mm MLEb-1 6 IA Holocentridae 1 1 6.4 mm MLEb-1 6 IA Holocentridae Sargocentron sp. 1 1 6.4 mm MLEb-1 6 IA Lethrinidae 2 1 6.4 mm MLEb-1 6 IA Lutjanidae 1 1 6.4 mm MLEb-1 6 IA Lutjanidae Lutjanus cf. kasmira 2 2 6.4 mm MLEb-1 6 IA Scaridae 5 2 6.4 mm MLEb-1 6 IA Scombridae 9 2 6.4 mm MLEb-1 6 IA Scombridae Katsuwonus pelamis 6 2 6.4 mm MLEb-1 6 IA Selachii 12 1 6.4 mm MLEb-1 6 IA Serranidae 1 1 6.4 mm MLEb-1 6 IA Serranidae Variola louti 1 1 6.4 mm MLEb-1 6 IB Scaridae 3 1 6.4 mm MLEb-1 6 IB Scaridae Hipposcarus longiceps 3 1 6.4 mm MLEb-1 6 IB Scombridae 8 2 6.4 mm MLEb-1 6 IB Scombridae Katsuwonus pelamis 3 1 6.4 mm MLEb-1 6 IB Selachii 5 1 6.4 mm MLEb-1 6 IB Serranidae 2 1 6.4 mm MLEb-1 6 IIA Carangidae 1 1 6.4 mm MLEb-1 6 IIA Scaridae 3 1 6.4 mm MLEb-1 6 IIA Scombridae 2 1 6.4 mm MLEb-1 6 IIA Scombridae Katsuwonus pelamis 2 2 6.4 mm MLEb-1 6 IIA Serranidae 1 1 6.4 mm MLEb-1 6 IIIA Lethrinidae 1 1 6.4 mm MLEb-1 6 IIIA Scaridae 1 1 6.4 mm MLEb-1 6 IIIA Scaridae Hipposcarus longiceps 1 1 6.4 mm MLEb-1 6 IIIA Serranidae 2 1 6.4 mm MLEb-1 6 IIIA Siganidae Siganus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IA Acanthuridae 12 2 6.4 and 3.2 mm MLEb-1 6 IA Acanthuridae Naso sp. 3 1 6.4 and 3.2 mm MLEb-1 6 IA Balistidae 48 4 6.4 and 3.2 mm MLEb-1 6 IA Belonidae 40 1 6.4 and 3.2 mm MLEb-1 6 IA Bothidae 10 1 6.4 and 3.2 mm MLEb-1 6 IA Carangidae 25 2 247

6.4 and 3.2 mm MLEb-1 6 IA Carangidae Caranx sp. 3 1 6.4 and 3.2 mm MLEb-1 6 IA Carangidae Decapterus spp. 19 6 6.4 and 3.2 mm MLEb-1 6 IA Carangidae Selar sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IA Carangidae Seriola sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IA Carcharhinidae Carcharhinus cf. melanopterus 25 1 6.4 and 3.2 mm MLEb-1 6 IA Chaetodontidae 2 1 6.4 and 3.2 mm MLEb-1 6 IA Cirrhitidae 19 6 6.4 and 3.2 mm MLEb-1 6 IA Diodontidae Diodon sp. 11 1 6.4 and 3.2 mm MLEb-1 6 IA Exocoetidae 57 4 6.4 and 3.2 mm MLEb-1 6 IA Fistulariidae Fistularia commersonii 1 1 6.4 and 3.2 mm MLEb-1 6 IA Ginglymostomatidae Nebrius ferrugineus 1 1 6.4 and 3.2 mm MLEb-1 6 IA Holocentridae 30 5 6.4 and 3.2 mm MLEb-1 6 IA Holocentridae Myripristis spp. 12 3 6.4 and 3.2 mm MLEb-1 6 IA Holocentridae Neoniphon sp. 2 1 6.4 and 3.2 mm MLEb-1 6 IA Holocentridae Sargocentron spp. 26 6 6.4 and 3.2 mm MLEb-1 6 IA Kuhliidae Kuhlia spp. 7 2 6.4 and 3.2 mm MLEb-1 6 IA Labridae 15 3 6.4 and 3.2 mm MLEb-1 6 IA Lethrinidae 29 1 6.4 and 3.2 mm MLEb-1 6 IA Lethrinidae Lethrinus spp. 11 3 6.4 and 3.2 mm MLEb-1 6 IA Lethrinidae Monotaxis grandoculis 20 1 6.4 and 3.2 mm MLEb-1 6 IA Lutjanidae 23 3 6.4 and 3.2 mm MLEb-1 6 IA Lutjanidae Lutjanus sp. 2 1 6.4 and 3.2 mm MLEb-1 6 IA Lutjanidae Lutjanus cf. kasmira 2 2 6.4 and 3.2 mm MLEb-1 6 IA Mugilidae 3 1 6.4 and 3.2 mm MLEb-1 6 IA Mullidae 8 2 6.4 and 3.2 mm MLEb-1 6 IA Mullidae Mulloidichthys spp. 12 2 6.4 and 3.2 mm MLEb-1 6 IA Mullidae Parupeneus sp. 2 1 6.4 and 3.2 mm MLEb-1 6 IA Muraenidae 28 5 6.4 and 3.2 mm MLEb-1 6 IA Ostraciidae 10 1 6.4 and 3.2 mm MLEb-1 6 IA Pomacentridae 2 1 6.4 and 3.2 mm MLEb-1 6 IA Scaridae 65 5 6.4 and 3.2 mm MLEb-1 6 IA Scaridae Chlorurus spp. 9 2 6.4 and 3.2 mm MLEb-1 6 IA Scaridae Hipposcarus longiceps 1 1 6.4 and 3.2 mm MLEb-1 6 IA Scaridae Scarus spp. 4 3 6.4 and 3.2 mm MLEb-1 6 IA Scombridae 29 5 6.4 and 3.2 mm MLEb-1 6 IA Scombridae Katsuwonus pelamis 8 2 6.4 and 3.2 mm MLEb-1 6 IA Scombridae Thunnus spp. 3 3 6.4 and 3.2 mm MLEb-1 6 IA Selachii 22 1 6.4 and 3.2 mm MLEb-1 6 IA Serranidae 59 6 6.4 and 3.2 mm MLEb-1 6 IA Serranidae Cephalopholis sp. 3 1 6.4 and 3.2 mm MLEb-1 6 IA Serranidae Epinephelus spp. 3 2 248

6.4 and 3.2 mm MLEb-1 6 IA Serranidae Variola louti 3 2 6.4 and 3.2 mm MLEb-1 6 IA Siganidae Siganus sp. 8 1 6.4 and 3.2 mm MLEb-1 6 IA Sphyraenidae Sphyraena sp. 4 1 6.4 and 3.2 mm MLEb-1 6 IB Acanthuridae 5 2 6.4 and 3.2 mm MLEb-1 6 IB Acanthuridae Acanthurus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IB Acanthuridae Naso sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IB Balistidae 19 4 6.4 and 3.2 mm MLEb-1 6 IB Belonidae 15 4 6.4 and 3.2 mm MLEb-1 6 IB Bothidae 3 1 6.4 and 3.2 mm MLEb-1 6 IB Carangidae 17 2 6.4 and 3.2 mm MLEb-1 6 IB Carangidae Caranx sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IB Carangidae Decapterus spp. 4 2 6.4 and 3.2 mm MLEb-1 6 IB Carangidae Scomberoides iysan 1 1 6.4 and 3.2 mm MLEb-1 6 IB Carcharhinidae Triaenodon obesus 1 1 6.4 and 3.2 mm MLEb-1 6 IB Carcharhinidae Carcharhinus cf. melanopterus 9 1 6.4 and 3.2 mm MLEb-1 6 IB Cirrhitidae 1 1 6.4 and 3.2 mm MLEb-1 6 IB Exocoetidae 11 1 6.4 and 3.2 mm MLEb-1 6 IB Holocentridae 4 1 6.4 and 3.2 mm MLEb-1 6 IB Holocentridae Myripristis sp. 5 1 6.4 and 3.2 mm MLEb-1 6 IB Holocentridae Sargocentron spp. 8 2 6.4 and 3.2 mm MLEb-1 6 IB Kyphosidae Kyphosus sp. 4 1 6.4 and 3.2 mm MLEb-1 6 IB Labridae 5 2 6.4 and 3.2 mm MLEb-1 6 IB Lethrinidae 12 2 6.4 and 3.2 mm MLEb-1 6 IB Lethrinidae Lethrinus spp. 5 2 6.4 and 3.2 mm MLEb-1 6 IB Lethrinidae Monotaxis grandoculis 2 1 6.4 and 3.2 mm MLEb-1 6 IB Lutjanidae 6 1 6.4 and 3.2 mm MLEb-1 6 IB Lutjanidae Lutjanus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IB Mugilidae 2 1 6.4 and 3.2 mm MLEb-1 6 IB Mullidae 8 1 6.4 and 3.2 mm MLEb-1 6 IB Mullidae Mulloidichthys sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IB Muraenidae 8 1 6.4 and 3.2 mm MLEb-1 6 IB Ostraciidae 2 1 6.4 and 3.2 mm MLEb-1 6 IB Scaridae 15 2 6.4 and 3.2 mm MLEb-1 6 IB Scaridae Chlorurus sp. 4 1 6.4 and 3.2 mm MLEb-1 6 IB Scaridae Hipposcarus longiceps 9 2 6.4 and 3.2 mm MLEb-1 6 IB Scaridae Scarus sp. 3 1 6.4 and 3.2 mm MLEb-1 6 IB Scombridae 11 2 6.4 and 3.2 mm MLEb-1 6 IB Scombridae Katsuwonus pelamis 3 1 6.4 and 3.2 mm MLEb-1 6 IB Selachii 6 1 6.4 and 3.2 mm MLEb-1 6 IB Serranidae 16 2 6.4 and 3.2 mm MLEb-1 6 IB Serranidae Epinephelus sp. 1 1 249

6.4 and 3.2 mm MLEb-1 6 IB Serranidae Variola louti 1 1 6.4 and 3.2 mm MLEb-1 6 IB Sphyraenidae Sphyraena sp. 3 1 6.4 and 3.2 mm MLEb-1 6 IIA Acanthuridae Acanthurus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Acanthuridae Ctenochaetus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Belonidae 3 1 6.4 and 3.2 mm MLEb-1 6 IIA Carangidae 3 1 6.4 and 3.2 mm MLEb-1 6 IIA Carangidae Selar sp. 2 1 6.4 and 3.2 mm MLEb-1 6 IIA Carcharhinidae Carcharhinus cf. melanopterus 4 1 6.4 and 3.2 mm MLEb-1 6 IIA Cirrhitidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Exocoetidae 6 1 6.4 and 3.2 mm MLEb-1 6 IIA Holocentridae 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Holocentridae Myripristis sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Kyphosidae Kyphosus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Lethrinidae 2 1 6.4 and 3.2 mm MLEb-1 6 IIA Lethrinidae Lethrinus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Lutjanidae 2 1 6.4 and 3.2 mm MLEb-1 6 IIA Mullidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Mullidae Mulloidichthys sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Muraenidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Scaridae 5 1 6.4 and 3.2 mm MLEb-1 6 IIA Scaridae Hipposcarus longiceps 1 1 6.4 and 3.2 mm MLEb-1 6 IIA Scombridae 3 1 6.4 and 3.2 mm MLEb-1 6 IIA Scombridae Katsuwonus pelamis 3 2 6.4 and 3.2 mm MLEb-1 6 IIA Serranidae 3 2 6.4 and 3.2 mm MLEb-1 6 IIB Acanthuridae 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Belonidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Carangidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Carcharhinidae Carcharhinus cf. melanopterus 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Exocoetidae 4 1 6.4 and 3.2 mm MLEb-1 6 IIB Holocentridae Sargocentron sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Lethrinidae Lethrinus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Mullidae Parupeneus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Serranidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIB Serranidae Cephalopholis sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIIA Balistidae 2 1 6.4 and 3.2 mm MLEb-1 6 IIIA Belonidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIIA Lethrinidae 2 1 6.4 and 3.2 mm MLEb-1 6 IIIA Lethrinidae Lethrinus sp. 1 1 6.4 and 3.2 mm MLEb-1 6 IIIA Mullidae 1 1 6.4 and 3.2 mm MLEb-1 6 IIIA Scaridae 2 1 6.4 and 3.2 mm MLEb-1 6 IIIA Scaridae Hipposcarus longiceps 1 1 250

6.4 and 3.2 mm MLEb-1 6 IIIA Serranidae 2 1 6.4 and 3.2 mm MLEb-1 6 IIIA Siganidae Siganus sp. 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Acanthuridae 9 5 6.4 mm MLEb-5 1, 13 and 15-27 I Acanthuridae Acanthurus sp. 5 1 6.4 mm MLEb-5 1, 13 and 15-27 I Acanthuridae Ctenochaetus sp. 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Acanthuridae Naso spp. 5 4 6.4 mm MLEb-5 1, 13 and 15-27 I Balistidae 29 9 6.4 mm MLEb-5 1, 13 and 15-27 I Belonidae 4 2 6.4 mm MLEb-5 1, 13 and 15-27 I Bothidae 3 1 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae 9 1 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Carangoides sp. 2 1 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Caranx spp. 18 3 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Decapterus spp. 8 4 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Elagatis bipinnulatus 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Selar sp. 2 1 6.4 mm MLEb-5 1, 13 and 15-27 I Carangidae Seriola sp. 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Cirrhitidae 7 3 6.4 mm MLEb-5 1, 13 and 15-27 I Diodontidae Diodon sp. 5 1 6.4 mm MLEb-5 1, 13 and 15-27 I Exocoetidae 2 2 6.4 mm MLEb-5 1, 13 and 15-27 I Fistulariidae Fistularia commersonii 11 2 6.4 mm MLEb-5 1, 13 and 15-27 I Holocentridae 8 5 6.4 mm MLEb-5 1, 13 and 15-27 I Holocentridae Myripristis spp. 6 2 6.4 mm MLEb-5 1, 13 and 15-27 I Holocentridae Sargocentron spp. 13 2 6.4 mm MLEb-5 1, 13 and 15-27 I Kuhliidae Kuhlia sp. 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Kyphosidae Kyphosus sp. 5 1 6.4 mm MLEb-5 1, 13 and 15-27 I Labridae 16 6 6.4 mm MLEb-5 1, 13 and 15-27 I Lethrinidae 9 1 6.4 mm MLEb-5 1, 13 and 15-27 I Lethrinidae Gnathodentex aureolineatus 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Lethrinidae Lethrinus spp. 41 4 6.4 mm MLEb-5 1, 13 and 15-27 I Lethrinidae Monotaxis grandoculis 23 7 6.4 mm MLEb-5 1, 13 and 15-27 I Lutjanidae 9 2 6.4 mm MLEb-5 1, 13 and 15-27 I Lutjanidae Lutjanus spp. 46 4 6.4 mm MLEb-5 1, 13 and 15-27 I Lutjanidae Lutjanus cf. kasmira 13 4 6.4 mm MLEb-5 1, 13 and 15-27 I Mugilidae 2 1 6.4 mm MLEb-5 1, 13 and 15-27 I Mullidae Mulloidichthys sp. 4 1 6.4 mm MLEb-5 1, 13 and 15-27 I Mullidae Parupeneus sp. 8 1 6.4 mm MLEb-5 1, 13 and 15-27 I Pomacentridae 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Scaridae 216 16 6.4 mm MLEb-5 1, 13 and 15-27 I Scaridae Chlorurus spp. 39 7 6.4 mm MLEb-5 1, 13 and 15-27 I Scaridae Hipposcarus longiceps 103 9 6.4 mm MLEb-5 1, 13 and 15-27 I Scaridae Scarus spp. 35 5 251

6.4 mm MLEb-5 1, 13 and 15-27 I Scombridae 161 42 6.4 mm MLEb-5 1, 13 and 15-27 I Scombridae Katsuwonus pelamis 567 83 6.4 mm MLEb-5 1, 13 and 15-27 I Scombridae Thunnus sp. 3 1 6.4 mm MLEb-5 1, 13 and 15-27 I Selachii 9 1 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae 100 7 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae Anyperodon leucogrammicus 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae Cephalopholis sp. 1 1 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae Epinephelus spp. 10 3 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae Plectropomus spp. 2 2 6.4 mm MLEb-5 1, 13 and 15-27 I Serranidae Variola louti 7 3 6.4 mm MLEb-5 1, 13 and 15-27 I Siganidae Siganus sp. 2 1 6.4 mm MLEb-5 1, 13 and 15-27 I Sphyraenidae Sphyraena sp. 2 1 6.4 and 3.2 mm MLEb-5 13 I Acanthuridae Acanthurus sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Acanthuridae Naso sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Balistidae 10 1 6.4 and 3.2 mm MLEb-5 13 I Belonidae 21 1 6.4 and 3.2 mm MLEb-5 13 I Bothidae 5 1 6.4 and 3.2 mm MLEb-5 13 I Carangidae 12 2 6.4 and 3.2 mm MLEb-5 13 I Carangidae Carangoides sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Carangidae Caranx sp. 2 1 6.4 and 3.2 mm MLEb-5 13 I Carangidae Decapterus spp. 7 2 6.4 and 3.2 mm MLEb-5 13 I Carcharhinidae Carcharhinus cf. melanopterus 6 1 6.4 and 3.2 mm MLEb-5 13 I Chaetodontidae 1 1 6.4 and 3.2 mm MLEb-5 13 I Cirrhitidae 10 3 6.4 and 3.2 mm MLEb-5 13 I Diodontidae Diodon sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Exocoetidae 20 1 6.4 and 3.2 mm MLEb-5 13 I Fistulariidae Fistularia commersonii 2 1 6.4 and 3.2 mm MLEb-5 13 I Holocentridae 8 3 6.4 and 3.2 mm MLEb-5 13 I Holocentridae Myripristis sp. 3 1 6.4 and 3.2 mm MLEb-5 13 I Holocentridae Sargocentron spp. 16 2 6.4 and 3.2 mm MLEb-5 13 I Kyphosidae Kyphosus sp. 2 1 6.4 and 3.2 mm MLEb-5 13 I Labridae 4 2 6.4 and 3.2 mm MLEb-5 13 I Lethrinidae 8 1 6.4 and 3.2 mm MLEb-5 13 I Lethrinidae Lethrinus sp. 3 1 6.4 and 3.2 mm MLEb-5 13 I Lethrinidae Monotaxis grandoculis 17 4 6.4 and 3.2 mm MLEb-5 13 I Lutjanidae 11 2 6.4 and 3.2 mm MLEb-5 13 I Lutjanidae Aprion sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Lutjanidae Lutjanus spp. 10 2 6.4 and 3.2 mm MLEb-5 13 I Lutjanidae Lutjanus cf. kasmira 3 2 6.4 and 3.2 mm MLEb-5 13 I Mugilidae 4 1 6.4 and 3.2 mm MLEb-5 13 I Mullidae 10 1 252

6.4 and 3.2 mm MLEb-5 13 I Mullidae Mulloidichthys sp. 7 1 6.4 and 3.2 mm MLEb-5 13 I Mullidae Parupeneus sp. 4 1 6.4 and 3.2 mm MLEb-5 13 I Muraenidae 1 1 6.4 and 3.2 mm MLEb-5 13 I Pomacentridae 4 1 6.4 and 3.2 mm MLEb-5 13 I Scaridae 10 2 6.4 and 3.2 mm MLEb-5 13 I Scaridae Chlorurus sp. 3 1 6.4 and 3.2 mm MLEb-5 13 I Scaridae Hipposcarus longiceps 1 1 6.4 and 3.2 mm MLEb-5 13 I Scombridae 9 5 6.4 and 3.2 mm MLEb-5 13 I Scombridae Katsuwonus pelamis 9 2 6.4 and 3.2 mm MLEb-5 13 I Serranidae 34 3 6.4 and 3.2 mm MLEb-5 13 I Serranidae Anyperodon leucogrammicus 1 1 6.4 and 3.2 mm MLEb-5 13 I Serranidae Epinephelus sp. 2 1 6.4 and 3.2 mm MLEb-5 13 I Siganidae Siganus sp. 1 1 6.4 and 3.2 mm MLEb-5 13 I Sphyraenidae Sphyraena sp. 4 1

253

APPENDIX D

Correspondence analysis data (column and row scores)

254

Column Scores (6.4 mm only samples) Taxon Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7 Axis 8 Axis 9 Axis 10 Acanthuridae 1.05051 0.721093 0.414389 -0.10659 -1.05552 -0.91613 -1.42817 -0.1086 -0.09716 0.745563 Acanthurus spp. 1.57391 1.83196 -0.97221 -4.39656 2.20692 -2.55271 0.109168 -0.40709 -0.13142 1.27471 Anyperodon leucogrammicus 0.341601 0.333719 1.86609 -0.26567 -1.6475 0.529852 -1.08196 0.140777 0.684976 1.60037 Balistidae 0.359169 -0.12514 0.829452 -0.09511 -0.27065 0.438983 -0.74596 0.029593 0.676967 0.995101 Belonidae 0.197401 0.406117 0.094068 1.53677 0.704587 -0.46772 -0.32426 0.740982 0.794928 0.532535 Bothidae 0.471065 -2.49079 -3.55536 0.72907 -2.2273 1.36155 -2.26555 -1.24288 -0.52297 -1.12294 Calotomus spp. 1.59927 -0.41382 -7.24893 -2.36088 -4.30812 -1.07332 -1.14332 2.5533 0.995461 0.501009 Carangidae 1.20427 0.428963 0.811502 -1.15187 0.026354 -0.62771 -0.21078 1.35136 1.29551 -4.77855 Carangoides spp. 0.505269 0.603416 0.845341 0.92832 -0.28732 2.24123 0.508899 -0.35533 -1.46594 -0.21614 Caranx spp. 0.289666 -0.60564 -0.21823 -0.44581 1.30652 -0.26574 -0.96286 -1.00112 0.394365 0.350977 Carcharhinus cf. longimanus 0.8189 3.79879 -1.50258 7.06193 6.3639 -13.7979 -5.69908 -3.37204 -1.17726 -2.27328 Carcharhinus cf. melanopterus -0.44642 -9.56857 -2.75169 -0.26178 5.0698 1.33693 -4.19308 -2.81407 5.23311 -0.71961 Cephalopholis spp. 0.908376 0.136906 2.18816 -0.126 -1.81097 0.570101 -1.28591 0.484633 0.781214 1.53795 Chaetodontidae 1.75854 -0.15831 2.67126 0.083516 -2.05617 0.630475 -1.59184 1.00042 0.925571 1.44432 Chlorurus spp. 0.057065 0.526212 0.517108 -0.44739 -0.27731 1.01468 0.2063 0.217368 0.227014 1.03827 Cirrhitidae 0.487738 1.20745 0.060699 -0.02871 0.848352 0.137514 0.192119 -0.74809 -1.24114 -0.00134 Ctenochaetus spp. 1.00348 1.15034 -0.29337 -2.0254 0.989483 1.2034 1.1678 -0.37143 -1.36306 0.242127 Decapterus spp. -0.34283 -0.82997 -0.01692 0.676638 0.982506 -0.04934 -1.2571 -1.28696 0.451103 0.23679 Diodon spp. 0.581641 0.275879 0.070972 1.89403 0.923837 -0.58148 -0.36169 1.07234 0.879377 0.335401 Elagatis bipinnulatus 0.505269 0.603416 0.845341 0.92832 -0.28732 2.24123 0.508899 -0.35533 -1.46594 -0.21614 Epinephelus spp. 0.084547 0.440841 0.367955 1.14136 0.275037 -0.27827 -0.42481 0.534977 0.748878 0.761707 Exocoetidae 0.153454 0.533256 -3.69655 2.3189 -1.37989 0.033095 -0.45465 0.05408 -1.45921 -1.23135 Fistularia commersonii -0.02562 0.48675 -0.2741 1.74438 1.09898 -0.62461 -0.14317 0.703919 0.776265 0.40228 Gnathodentex aureolineatus 0.087513 0.857326 0.236701 1.20992 0.302295 2.77815 1.20915 -0.80725 -2.26311 -0.76962 Hipposcarus longiceps -0.24002 -0.46841 0.802512 0.641713 -0.67152 -1.85744 1.41109 0.337576 -0.61654 1.50535 Holocentridae 0.97563 0.273025 -0.67414 -0.87527 0.073057 0.697589 -0.14279 -0.48435 -0.8874 0.015187 Katsuwonus pelamis -1.659 0.517583 -0.13192 -0.22704 -0.31001 0.01156 -0.11123 -0.48567 0.172288 -0.44482 Kuhlia spp. -0.06612 -0.38775 -0.83578 1.50731 1.05382 2.11664 1.58773 2.21939 1.37044 0.433113 Kyphosus spp. 1.33562 1.51495 -1.05251 -3.99455 1.84069 0.511507 1.60706 -0.38216 -1.29447 0.547638

255

Labridae 0.141764 0.947735 -0.05238 0.575302 0.852346 -0.13321 0.055206 -0.25685 -0.42184 0.24809 Lethrinidae 0.788436 -2.53309 -0.71744 -0.23055 0.665527 -0.52236 5.34101 -4.23861 0.63385 -0.05076 Lethrinus spp. 0.660288 0.554945 -0.91722 0.414616 -0.90541 0.513828 -0.3063 0.105215 -0.71881 0.025994 Lutjanidae 0.613167 -0.84254 -0.59249 0.564759 1.56467 0.750496 0.078477 0.616302 0.887327 0.114071 Lutjanus cf. kasmira 0.544749 -1.3533 0.721945 -0.83145 0.156757 0.908538 -1.39885 -1.11289 0.519052 0.609623 Lutjanus spp. 0.662811 0.495866 -1.45 -0.18233 -0.28707 0.315821 0.114955 0.593108 -0.16317 0.258304 Monotaxis grandoculis -0.37942 1.1492 -0.40853 0.325366 1.10873 -0.71682 0.030048 -0.47601 -0.16682 0.497431 Mugilidae 0.367468 -0.38933 -2.04076 -0.90193 2.27007 0.941785 2.1463 3.29017 2.80022 1.30816 Mullidae 1.56797 0.234392 1.44922 1.19021 -0.59382 2.3167 0.126488 0.289399 -1.28549 -0.33318 Mulloidichthys spp. 0.883477 0.658648 -0.54393 -0.07276 1.57044 -0.87729 0.158943 0.883818 0.650513 0.552874 Muraenidae 1.08001 0.289411 -0.28226 2.67608 1.58432 0.4252 0.401691 1.03446 -0.28097 -0.74719 Myripristis spp. -0.09424 0.746289 0.727422 0.549847 -0.39589 1.85871 0.39468 -0.59997 -1.13199 0.209584 Naso spp. -1.1059 0.343192 -0.36799 0.448158 0.2464 1.35034 0.880619 0.591722 0.870446 1.06712 Neoniphon spp. 1.50445 0.365293 1.04187 1.55911 -0.10637 2.87877 0.699265 0.052393 -2.02251 -0.92568 Ostraciidae 1.75854 -0.15831 2.67126 0.083516 -2.05617 0.630475 -1.59184 1.00042 0.925571 1.44432 Parupeneus spp. 0.795982 0.611309 0.639287 1.38451 0.097961 2.82846 0.954206 -0.37743 -2.14281 -0.84765 Plectropomus spp. -0.93826 -0.41143 -0.21762 0.138726 -0.10202 0.354947 0.251811 2.28568 3.40106 2.32765 Pomacentridae -0.36687 0.579735 1.4635 -0.44026 -1.44316 0.479541 -0.82702 -0.28904 0.564678 1.67839 Sargocentron spp. 0.968382 -0.24555 0.643123 -0.12939 0.584571 0.416513 -1.0201 -1.30509 -0.79726 -0.1087 Scaridae 0.214635 -0.68422 0.956652 -0.45072 -0.61351 -0.28706 0.153389 0.260927 0.468604 -0.37071 Scarus spp. 0.107471 0.775746 -0.01352 0.015937 0.594919 0.195496 0.208037 0.060914 -0.00322 0.619724 Scombridae -1.71064 -0.3309 -0.08173 -0.34546 0.089312 -0.05075 0.185364 0.649628 -0.3021 -0.08799 Selachii -0.9157 -6.0125 0.348351 -0.98699 1.23897 -2.14221 -0.90834 4.44871 -7.64469 1.20645 Selar spp. 0.728753 0.221605 0.396008 1.66771 0.551336 -0.42999 -0.51546 1.06335 0.885152 0.474015 Seriola spp. -2.49228 1.31778 0.255745 -0.96405 -0.83016 0.328607 -0.0622 -1.5785 0.203785 1.91247 Serranidae 0.637099 -0.56441 0.834625 -0.03092 -0.27192 -0.57071 0.733123 0.497877 -0.17476 -1.35329 Siganus spp. 1.17307 -0.78762 -0.68104 1.50549 -3.01767 -1.87876 2.07132 -1.45855 0.889772 0.615823 Sphyraena spp. 0.542098 -0.31127 0.333231 1.03271 0.017159 1.62125 0.527872 1.81307 1.22215 0.770181 Thunnus spp. 0.258447 0.610048 -1.1771 2.93358 2.3954 0.340676 0.988889 0.610311 -0.60236 -1.03441 Variola louti -0.08354 -0.70272 0.401266 0.66751 0.925481 -0.1115 -1.83215 -2.65304 -0.83475 -0.37212

256

Row Scores (6.4 mm only samples) Site and Cultural Layer Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7 Axis 8 Axis 9 Axis 10 MLEb-1 TP17-20 HISTORIC 0.780751 0.310695 -0.42452 -0.97709 0.369769 -0.14525 0.162924 -0.01392 -0.02292 0.026442 MLEb-1 TP17-20 IA 0.458221 -0.01474 0.233904 0.005896 -0.12471 0.031065 -0.06819 0.031943 0.022293 0.018403 MLEb-1 TP17-20 IB 0.259598 0.131472 -0.19412 0.318415 0.230061 0.363403 0.226241 -0.05887 -0.19072 -0.07219 MLEb-1 TP17-20 IIA 0.21338 0.353581 -0.13157 0.498554 0.385976 -0.67986 -0.24413 -0.10767 -0.02835 -0.02897 MLEb-1 TP17-20 IIB -0.13733 -0.38376 -0.35491 0.169397 0.200657 0.006509 0.116665 0.360779 0.295551 0.051493 MLEb-1 TP17-20 IIIA 0.565233 -0.06627 -1.99342 0.135108 -1.49088 -0.10386 -0.4073 -0.05271 -0.19902 -0.0708 MLEb-1 TP6 IA -0.09532 -1.39748 -0.12698 -0.20636 0.414317 0.125239 -0.4759 -0.54048 -0.04347 -0.06983 MLEb-1 TP6 IB -0.76918 -1.12482 0.378108 -0.24927 -0.06419 -0.70677 0.235536 0.908383 -1.1999 0.052428 MLEb-1 TP6 IIA -0.49544 -0.01923 0.3762 -0.40551 -0.23163 -0.25219 0.10644 0.298077 0.271974 -1.2467 MLEb-1 TP6 IIIA 0.514645 -1.00755 0.239062 0.287 -0.78182 -1.02326 1.94199 -0.92016 0.240186 0.069282 MLEb-5 I -0.64941 0.122656 0.022394 -0.06806 -0.05035 0.016191 -0.00266 -0.0504 0.004908 0.024368

257

Column Scores (6.4 mm and 3.2 mm samples) Taxon Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7 Axis 8 Axis 9 Axis 10 Axis 11 Acanthuridae -0.59469 0.086364 -1.19364 0.998479 -0.43306 -0.79894 0.593311 1.52917 -0.311 0.878794 -0.02715 Acanthurus spp. -3.32641 0.860002 -0.77318 0.210097 0.131746 -0.43386 -1.48026 -0.70568 0.64415 0.206424 -0.69111 Anyperodon leucogrammicus -0.56781 2.57138 0.199642 -1.07572 1.75408 2.57669 3.46183 -0.1127 -1.88064 0.681877 0.74823 Aprion spp. 0.968157 1.23646 0.156437 -1.67947 4.37821 2.55047 -2.87855 2.32312 -0.74157 -3.75027 2.87522 Balistidae -0.26076 -0.86233 1.23857 0.45207 -0.65917 -0.49094 0.169476 0.93228 0.050231 0.678699 1.38504 Belonidae -1.33286 -3.05062 0.05942 0.231652 0.119021 0.885222 0.021752 -0.229 -0.48671 0.212625 0.503836 Bothidae 0.551336 -0.59453 0.767231 -1.07602 1.4366 -3.02802 0.656573 1.35313 0.046762 1.33661 0.508503 Caesionidae -0.94466 2.93554 -0.74317 0.022142 -2.43482 1.55302 5.60461 0.872412 -2.23629 1.21792 -1.34834 Carangidae -0.1192 -1.12931 -1.01485 0.216263 1.51477 -1.14301 -0.38156 0.203122 0.360942 -0.58863 0.857619 Carangoides spp. -0.56781 2.57138 0.199642 -1.07572 1.75408 2.57669 3.46183 -0.1127 -1.88064 0.681877 0.74823 Caranx spp. -1.34936 0.69425 -0.23592 0.950702 0.100021 -0.24301 -2.36828 0.259742 -1.82505 1.09964 0.293986 Carcharhinus cf. amblyrhynchos 1.75043 0.629856 -1.7724 -0.08751 -1.37545 0.47692 -4.93336 6.72917 -0.31379 -7.11034 0.809068 Carcharhinus cf. melanopterus 0.445943 -3.28841 -2.87451 0.493773 2.38984 0.521995 0.733796 -3.72675 -1.74778 -0.73258 -0.14377 Cephalopholis spp. 1.56913 -1.86984 -5.45973 3.14042 0.80198 2.41728 1.66855 0.877769 1.44214 0.981332 0.347263 Chaetodontidae 1.09962 1.43526 0.395254 0.119564 1.19799 1.59132 -0.34934 0.153725 0.334211 -1.04604 1.26053 Chlorurus spp. 0.321986 0.144848 1.22368 0.321083 0.511748 0.586349 0.682193 0.368955 1.55916 0.017636 -1.91163 Cirrhitidae 0.276424 0.888162 0.424609 0.663658 0.465747 -0.47825 0.51049 -1.26883 0.981193 -0.38281 1.94801 Ctenochaetus spp. -3.61185 1.55592 -2.25932 -0.43508 -1.99075 -0.79313 0.545114 -3.8297 -0.13383 -2.11435 0.256775 Decapterus spp. 1.11171 -0.34464 0.911942 -0.19147 0.405292 -1.40071 -0.0973 -0.3771 -0.09478 1.72004 -0.97649 Diodon spp. 1.49357 0.684442 0.035161 -0.84701 0.709721 0.3715 -1.18135 -0.57548 -2.73328 1.0623 -0.11171 Elagatis bipinnulatus -0.0463 2.16698 -1.08625 -0.01441 -2.0817 1.19432 2.09196 2.82466 -1.59545 -1.55816 -0.62921 Epinephelus spp. 0.228232 1.01743 0.813454 1.00357 -0.28938 1.08147 1.83669 0.059113 -0.59708 -0.31739 -0.10229 Exocoetidae 0.616979 -0.08425 -1.04928 0.261629 -0.12394 -0.60322 1.41482 -0.00755 0.471076 -0.11588 0.128945 Fistularia commersonii 1.49357 0.684442 0.035161 -0.84701 0.709721 0.3715 -1.18135 -0.57548 -2.73328 1.0623 -0.11171 Gerres spp. 0.732623 1.04553 -1.16599 -1.18913 -1.87211 -0.23121 0.441626 1.24543 -4.9474 1.2053 -1.87207 Hipposcarus longiceps -0.70738 -0.87391 0.749876 -1.72079 -1.17198 0.893552 1.41982 0.092857 0.197132 0.427383 -0.99195 Holocentridae -0.31021 1.20776 -0.13644 0.188873 -0.36881 0.518511 0.406058 -0.36577 -0.1834 0.065163 -0.40611 Katsuwonus pelamis 0.194131 -0.32345 -0.15128 -1.87909 0.495555 -1.76424 0.46091 -0.98896 0.158609 -0.89015 -0.82681 Kuhlia spp. 2.0271 0.453064 -0.49185 0.382352 -1.55197 -0.3002 -2.31352 1.10859 -1.15263 -0.91721 -0.46311

258

Kyphosus spp. -2.71655 0.662089 -0.55162 -0.22564 0.153714 -0.21149 -0.58798 -0.55973 0.557367 -0.57303 -1.08999 Labridae 0.46901 0.098548 0.971873 0.333697 0.908397 -0.84082 0.676641 1.32224 0.944159 -0.74703 0.816922 Lethrinidae -0.88095 -1.12067 0.425859 -1.07618 -1.06734 0.641209 -1.13734 0.421737 -0.20173 -0.63544 0.796475 Lethrinus spp. -0.08782 -0.91765 -0.78006 0.059278 -0.81308 0.970824 -0.46772 0.57682 0.259551 -0.41737 0.601926 Lutjanidae 0.066815 0.463198 -0.1501 -0.32791 0.212696 -1.07191 -0.26716 0.246092 0.294962 -0.74057 0.652389 Lutjanus cf. kasmira 1.09962 1.43526 0.395254 0.119564 1.19799 1.59132 -0.34934 0.153725 0.334211 -1.04604 1.26053 Lutjanus spp. -0.99427 1.15094 -0.23211 0.245042 0.567022 -1.08599 0.06476 0.697737 -1.36031 1.24217 1.87264 Monotaxis grandoculis -0.71657 0.592106 0.788819 -1 2.79881 1.13342 -0.84374 0.795 1.42166 0.245843 -1.0824 Mugilidae 0.296246 0.003532 1.50786 1.03013 1.24594 1.07257 0.19226 0.563706 -0.74423 -1.72174 0.496878 Mullidae -0.00773 -1.24839 0.777156 -1.84694 -1.37012 1.03585 0.067579 -1.13602 0.582334 0.34969 0.857506 Mulloidichthys spp. 0.501088 -0.19891 0.023111 -0.72265 -0.24214 -0.20702 -0.62869 -0.16506 -0.06103 -1.95651 -1.57079 Muraenidae 0.939216 0.302193 0.067375 0.13909 -0.79553 0.03735 -0.52297 -0.07836 0.491385 -1.5246 -0.94779 Myripristis spp. 0.02984 0.41767 -0.17324 0.439441 -0.62763 -0.13864 -0.98029 -0.88155 -0.6982 -1.25673 0.057786 Naso spp. -1.93884 0.445388 1.26457 1.96113 1.50345 0.445681 -0.90167 -1.21517 -0.37907 1.30051 0.994605 Nebrius ferrugineus 3.40683 0.332584 2.01131 3.81506 -1.52963 -0.28868 -1.2449 -4.90375 5.05626 2.09847 0.640023 Neoniphon spp. 1.4042 1.29933 -0.16809 1.2499 -1.77997 0.580418 -0.19121 0.899278 0.835395 -1.26465 0.033583 Ostraciidae -1.58286 -0.18555 0.574524 1.09507 -0.36023 -0.64252 -1.41358 1.15012 2.05577 0.869305 -2.70473 Parupeneus spp. 1.23933 -1.18153 -2.74366 -0.24122 1.56871 1.04073 -0.43197 1.10368 0.332077 1.41923 -1.94128 Pomacentridae -1.04838 1.34125 -0.167 -0.19304 0.58542 0.474906 -0.86561 0.498079 1.99814 1.49544 -1.43966 Sargocentron spp. 0.504237 -0.06748 -0.32162 1.20435 0.231774 0.609131 -0.15817 0.061645 0.37356 0.489515 -0.56443 Scaridae -0.18405 -0.0638 0.676921 -0.13189 -0.87696 0.826426 0.255714 -0.86514 0.345463 0.504068 0.565895 Scarus spp. 0.255918 0.292547 0.256701 1.58411 -1.2103 -0.49739 -1.49459 -0.29619 -0.84806 0.758263 -0.40192 Scomberoides iysan -2.91726 -5.72339 5.95827 4.67241 1.43774 -1.00241 2.35868 2.20363 -5.05799 -4.42454 -2.55773 Scombridae 0.762887 0.062214 0.679745 -0.62593 1.12976 0.34308 -0.4177 -1.16916 -1.24075 -0.07254 -0.56749 Selachii -0.15169 -0.81842 2.40881 2.83654 -0.84224 0.087308 2.23946 -0.60924 -0.746 -0.36938 -1.08868 Selar spp. 0.387009 0.313846 -0.97265 -1.64045 -0.93274 -2.78839 1.13678 0.427993 0.424032 -0.8061 0.022284 Seriola spp. 3.40683 0.332584 2.01131 3.81506 -1.52963 -0.28868 -1.2449 -4.90375 5.05626 2.09847 0.640023 Serranidae 0.125053 -0.09741 -0.49653 -0.37618 -0.40883 0.144763 0.517716 -0.04573 0.29918 -0.07149 0.518162 Siganus spp. 0.656692 -1.02007 0.513997 -2.82018 -1.36432 1.9038 -1.53533 1.36989 0.738079 2.09232 1.6352 Sphyraena spp. -0.22195 0.470218 0.879366 -0.15303 0.398599 0.816562 1.53838 1.09097 0.647589 -0.09243 -2.16017 Thunnus spp. 2.34928 0.374053 0.352194 1.11109 -1.60709 -0.55732 -1.26213 -1.76699 -0.39742 1.64978 -0.70331

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Triaenodon obesus -2.91726 -5.72339 5.95827 4.67241 1.43774 -1.00241 2.35868 2.20363 -5.05799 -4.42454 -2.55773 Variola louti 0.940437 -0.29856 1.49307 2.44743 -1.08636 0.090032 0.108028 -0.00046 0.500892 -1.224 -0.36339

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Row Scores (6.4 mm and 3.2 mm samples) Site and Cultural Layer Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7 Axis 8 Axis 9 Axis 10 Axis 11 MLEb-1 TP17 Historic -1.08051 0.289474 -0.22239 0.310398 -0.00499 -0.13559 -0.50387 -0.09137 0.046023 0.213054 0.07196 MLEb-1 TP17 IA -0.1083 0.299303 -0.0553 0.001505 -0.13807 0.079235 0.271462 0.036816 -0.06807 0.032432 -0.02942 MLEb-1 TP17 IB 0.200674 0.064219 -0.13188 -0.00595 -0.078 0.024332 -0.23895 0.28397 -0.00955 -0.18934 0.017655 MLEb-1 TP17 IIA -0.15678 -0.21687 0.073066 -0.43624 0.103701 -0.0988 0.006613 0.175739 0.407105 0.144685 -0.37247 MLEb-1 TP17 IIB 0.351883 -0.23643 -0.10456 -0.32031 -0.07051 -0.22999 -0.21841 -0.14737 -0.45669 0.252858 -0.12221 MLEb-1 TP17 IIIA 0.140734 -0.03345 -0.07279 -0.17848 0.265257 -1.18074 0.41965 0.309508 0.174235 0.116435 0.529235 MLEb-1 TP6 IA 0.390569 0.03391 0.149656 0.259264 -0.08674 -0.01473 -0.0603 -0.20694 0.153908 0.05588 0.013966 MLEb-1 TP6 IB -0.33444 -0.58355 0.443337 0.317527 0.08153 -0.05114 0.114243 0.092993 -0.15396 -0.11782 -0.05581 MLEb-1 TP6 IIA -0.35919 -0.25353 -0.33945 -0.43168 -0.17043 -0.18474 0.066562 -0.62871 0.073823 -0.50313 0.009298 MLEb-1 TP6 IIB 0.236611 -1.16002 -1.58745 0.598845 0.484719 0.404478 0.351053 0.034319 0.099304 0.205554 0.028112 MLEb-1 TP6 IIIA -0.29776 -1.02832 0.351691 -0.80324 -0.84586 0.756745 -0.07648 0.124188 0.19817 0.348942 0.652454 MLEb-5 TP13 I 0.02131 0.187916 0.155159 -0.22232 0.574545 0.235917 -0.0399 -0.0879 -0.03559 -0.01039 0.107826

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APPENDIX E

Fish bone size data: Kruskal-Wallis one way analysis of variance and effect size and bootstrapping around the median

262

Scaridae

Scaridae C1 and C2 vertebral measurement (mm) (M1, M2, and M3) descriptive statistics for the late (MLEb-1; TP 17- 20) and early (MLEb-5; all TPs) prehistoric assemblages.

Late (MLEb-1; TP 17-20) Early (MLEb-5; all TPs) C1 C2 C1 C2 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 n 20 20 20 24 24 24 33 28 33 17 17 17 Mean 7.35 8.08 9.39 6.84 7.66 8.95 7.46 8.27 9.76 7.46 8.19 9.88 Median 7.64 8.17 10.01 7.16 8.05 9.14 7.79 8.57 9.85 7.76 8.63 10.07 Variance 3.67 4.21 3.83 2.81 3.74 3.43 1.58 2.55 1.65 2.62 3.19 2.20 Std. deviation 1.91 2.05 1.96 1.68 1.93 1.85 1.26 1.60 1.29 1.62 1.79 1.48 Minimum 3.27 3.65 5.07 2.77 3.05 4.21 3.81 4.34 5.70 4.92 5.49 7.73 Maximum 10.72 10.89 11.63 9.75 11.04 12.06 9.14 10.90 11.55 9.93 11.08 12.93 Range 7.45 7.24 6.56 6.98 7.99 7.85 5.33 6.56 5.85 5.01 5.59 5.20 Skewness -0.51 -0.68 -1.07 -0.64 -0.46 -0.71 -0.97 -0.41 -1.00 -0.09 -0.16 0.22 Kurtosis -0.29 -0.23 0.30 0.25 0.12 0.76 1.02 0.09 1.66 -1.14 -1.26 -0.69

Scaridae C1 and C2 vertebral measurement (mm) (M1, M2, and M3) bootstrap results based on 10,000 replicates for the late (MLEb-1; TP 17-20) and early (MLEb-5; all TPs) prehistoric assemblages.

Late (MLEb-1; TP 17-20) Early (MLEb-5; all TPs) C1 C2 C1 C2 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 Median 7.64 8.17 10.01 7.16 8.05 9.14 7.79 8.57 9.85 7.76 8.63 10.07 95% CI of Lower 6.26 7.22 8.95 6.09 6.68 8.50 7.51 7.53 9.51 6.41 6.85 8.69 median Upper 8.84 9.57 10.64 7.64 8.50 9.50 7.82 8.93 10.41 8.12 9.12 10.86 99% CI of Lower 5.74 6.53 8.44 6.04 6.65 8.38 7.24 7.42 9.39 5.99 6.50 8.48 median Upper 8.91 9.77 10.72 7.71 8.76 9.53 7.93 9.00 10.49 9.74 9.73 10.91

Kruskal-Wallis one way analysis of variance and effect size (η2) test results based on a comparison of the late (MLEb-1; TP 17-20) and early (MLEb-5; all TPs) prehistoric assemblages for Scaridae C1 and C2 vertebral measurements (mm) (M1, M2, and M3).

Late (MLEb-1; TP 17-20) and early (MLEb-5; all TPs) comparison Kruskal-Wallis test results Effect size C1 M1 χ2(1, N = 53) = 0.002, p = 0.96 η2 = 0.00004 M2 χ2(1, N = 48) = 0.002, p = 0.98 η2 = 0.00004 M3 χ2(1, N = 53) = 0.03, p = 0.86 η2 = 0.0006 C2 M1 χ2(1, N = 41) = 1.12, p = 0.29 η2 = 0.03 M2 χ2(1, N = 41) = 0.71, p = 0.40 η2 = 0.02 M3 χ2(1, N = 41) = 1.04, p = 0.15 η2 = 0.05

263

Katsuwonus pelamis

K. pelamis C21 to C25 vertebral measurement (mm) (M1, M2, and M3) descriptive statistics for: (a) late (MLEb-1; TP 17-20), and (b) early (MLEb-5; all TPs) prehistoric assemblages.

(a)

Late (MLEb-1; TP 17-20) C21 C22 C23 C24 C25 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 n 21 21 21 28 29 29 20 20 20 11 11 11 22 22 22 Mean 8.62 9.89 9.66 8.24 9.51 9.26 8.12 9.73 9.85 7.00 8.38 8.82 6.53 8.26 8.27 Median 8.54 9.81 9.45 8.01 9.25 8.96 7.97 9.65 9.64 6.39 8.02 8.14 6.37 8.25 8.26 Variance 2.21 2.33 1.29 1.88 2.63 1.39 2.23 3.15 3.60 1.88 2.55 1.95 1.18 2.11 2.18 Std. deviation 1.49 1.53 1.13 1.37 1.62 1.18 1.49 1.77 1.90 1.37 1.60 1.40 1.09 1.45 1.48 Minimum 6.34 7.56 7.95 5.92 7.04 7.31 5.96 7.14 7.41 5.29 6.52 7.24 4.52 5.53 5.75 Maximum 11.78 12.96 12.60 11.01 13.00 11.43 11.28 13.17 15.99 9.51 11.18 11.49 9.22 11.12 12.43 Range 5.44 5.40 4.65 5.09 5.96 4.12 5.32 6.03 8.58 4.22 4.66 4.25 4.70 5.59 6.68 Skewness 0.64 0.37 0.83 0.35 0.44 0.44 0.60 0.43 1.80 0.85 0.71 0.94 0.60 0.13 0.67 Kurtosis 0.19 -0.49 0.76 -0.54 -0.71 -0.92 -0.13 -0.80 4.97 -0.59 -0.79 -0.43 0.75 -0.60 1.88 (b)

Early (MLEb-5; all TPs) C21 C22 C23 C24 C25 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 n 30 35 42 78 82 80 97 103 106 46 46 47 61 70 71 Mean 9.88 11.09 10.47 9.08 10.27 9.59 8.38 9.91 9.59 7.09 8.49 8.80 7.08 8.53 8.29 Median 9.76 11.21 10.66 9.12 10.37 9.63 8.20 9.74 9.57 7.09 8.18 8.56 7.16 8.48 8.19 Variance 2.12 3.18 2.27 1.37 1.81 1.43 1.57 1.94 1.08 0.91 1.61 1.31 0.86 1.14 0.99 Std. deviation 1.45 1.78 1.51 1.17 1.34 1.20 1.25 1.39 1.04 0.95 1.27 1.15 0.93 1.07 1.00 Minimum 7.01 7.33 7.79 6.53 7.35 6.67 6.06 6.81 7.53 5.32 6.49 7.12 5.22 6.64 6.56 Maximum 12.63 14.46 13.83 12.02 13.44 11.92 12.10 13.58 12.21 9.52 11.42 12.11 9.30 11.00 10.64 Range 5.62 7.13 6.04 5.49 6.09 5.25 6.04 6.77 4.68 4.20 4.93 4.99 4.08 4.36 4.08 Skewness -0.07 -0.18 0.17 -0.02 -0.08 -0.15 0.53 0.37 0.27 0.30 0.51 1.01 0.31 0.35 0.29 Kurtosis -0.17 -0.42 -0.28 -0.35 -0.69 -0.32 -0.02 -0.04 -0.29 -0.15 -0.37 1.09 -0.07 -0.47 -0.30

264

K. pelamis C21 to C25 vertebral measurement (mm) (M1, M2, and M3) bootstrap results based on 10,000 replicates for: (a) late (MLEb-1; TP 17-20), and (b) early (MLEb-5; all TPs) prehistoric assemblages.

(a)

Late (MLEb-1; TP 17-20) C21 C22 C23 C24 C25 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 Median 8.54 9.81 9.45 8.01 9.25 8.96 7.97 9.65 9.64 6.39 8.02 8.14 6.37 8.25 8.26 95% CI of Lower 8.03 9.25 9.19 7.60 8.56 8.60 7.31 8.87 8.84 6.12 7.22 7.83 5.96 7.17 7.55 median Upper 8.85 10.35 10.09 8.67 10.13 9.71 8.70 9.84 10.01 7.72 9.41 10.11 7.06 9.11 8.91 99% CI of Lower 7.40 8.75 8.77 7.26 8.39 8.48 6.87 8.64 8.34 6.06 7.00 7.78 5.81 7.07 7.44 median Upper 8.97 10.74 10.39 9.23 10.47 10.04 8.92 10.96 10.28 8.47 9.88 10.44 7.17 9.18 9.00

(b)

Early (MLEb-5; all TPs) C21 C22 C23 C24 C25 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 M1 M2 M3 Median 9.76 11.21 10.66 9.12 10.37 9.63 8.20 9.74 9.57 7.09 8.18 8.56 7.16 8.48 8.19 95% CI of Lower 9.43 10.45 9.92 8.84 10.06 9.38 7.88 9.49 9.16 6.69 7.90 8.37 6.76 8.05 7.96 median Upper 10.60 12.05 10.94 9.40 10.75 9.99 8.59 10.10 9.84 7.45 8.88 8.77 7.48 8.88 8.56 99% CI of Lower 9.21 10.33 9.65 8.69 9.66 9.34 7.81 9.45 9.12 6.59 7.85 8.22 6.70 7.99 7.89 median Upper 10.65 12.08 11.10 9.58 10.83 10.03 8.73 10.20 10.01 7.55 9.16 9.01 7.52 9.07 8.65

265

Kruskal-Wallis one way analysis of variance and effect size (η2) test results based on a comparison of the late (MLEb-1; TP 17-20) and early (MLEb-5; all TPs) prehistoric assemblages for K. pelamis C21 to C25 vertebral measurements (mm) (M1, M2, and M3).

Late (MLEb-1; TP 17-20) and early (MLEb-5; all TPs) comparison Kruskal-Wallis test results Effect size C21 M1 χ2(1, N = 51) = 8.63, p = 0.0038* η2 = 0.17 M2 χ2(1, N = 56) = 6.27, p = 0.01* η2 = 0.11 M3 χ2(1, N = 63) = 5.21, p = 0.003* η2 = 0.08 C22 M1 χ2(1, N = 106) = 7.73, p = 0.005* η2 = 0.007 M2 χ2(1, N = 111) = 5.33, p = 0.02* η2 = 0.05 M3 χ2(1, N = 109) = 1.91, p = 0.17 η2 = 0.02 C23 M1 χ2(1, N = 115) = 0.96, p = 0.33 η2 = 0.008 M2 χ2(1, N = 121) = 0.48, p = 0.48 η2 = 0.004 M3 χ2(1, N = 124) = 0.0004, p = 0.98 η2 = 0.000003 C24 M1 χ2(1, N = 57) = 0.49, p = 0.48 η2 = 0.008 M2 χ2(1, N = 57) = 0.18, p = 0.67 η2 = 0.003 M3 χ2(1, N = 58) = 0.12, p = 0.73 η2 = 0.002 C25 M1 χ2(1, N = 83) = 5.29, p = 0.02* η2 = 0.06 M2 χ2(1, N = 92) = 0.92, p = 0.34 η2 = 0.01 M3 χ2(1, N = 93) = 0.02, p = 0.89 η2 = 0.0002 * Significant at ɑ = 0.05

266