CHEMICAL TRACERS ELUCIDATE TROPHIC AND MIGRATORY DYNAMICS

Transcription

1 CHEMICAL TRACERS ELUCIDATE TROPHIC AND MIGRATORY DYNAMICS OF PACIFIC PELAGIC PREDATORS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF BIOLOGY AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Daniel James Madigan April 2013

2 ABSTRACT Pelagic predators face many challenges and uncertain futures. Much work has revealed their decline due to overfishing, alteration of ecosystems, trophic cascades, and climate change. In the face of these challenges there has been a dearth of information regarding fundamental life history and ecology of these species due to the difficulty of studying them in their natural environment. Electronic tagging studies have greatly expanded our knowledge of pelagic organisms, but in many cases they raise as many questions as are answered. From the moment of animal capture, we can find out where a tagged animal migrates to, but from where did it emigrate before capture? What are the ecological roles of these predators on their various regions of high use? What is the timing and origin of migrations? These questions have implications for management, both using movement data (to understand where, and to what an extent, a species may need protection from exploitation) and ecological data (to understand how overexploitation of different species or trophic levels may affect other organisms in a pelagic ecosystem). Various chemical tracers have served as new tools to answer some of these questions. Environmental contaminants, radioactive isotopes, and stable isotopes all have been used to examine movement patterns and trophic interactions in marine animals. Complementary techniques and laboratory-based studies are sometimes necessary to interpret data and provide the necessary parameters to use chemical analyses to understand the timing and origin of migrations and the roles migratory predators play in their various oceanic environments. iv

3 In Chapter 1, I use archived, frozen Pacific bluefin tuna Thunnus orientalis (PBFT) tissues to study the turnover and trophic fractionation of two stable isotope ratios (δ 13 C and δ 15 N) in two PBFT tissues (white muscle and liver). Captive bluefin with demonstrably lower white muscle and liver δ 13 C and δ 15 N values than their captive diet were kept in captivity for days, allowing for a long-term experiment of stable isotope dynamics (specifically, δ 13 C and δ 15 N) in PBFT. This experiment tuna reveals isotopic turnover rates and trophic discrimination factors (TDFs) for PBFT in the size range commonly encountered in the California Current Large Marine Ecosystem (CCLME). TDFs can then be used to investigate tuna trophic ecology, and the long turnover times of tuna muscle (t 1/2 for PBFT WM = 167 days) demonstrate that tunas take more than a year to reflect local isotopic prey conditions, and turnover rates can be applied to multiple tissues using isotopic clock techniques. These parameters are necessary for the interpretation of trophic ecology of pelagic predators in Chapter 2 and the timing and origin of PBFT migrations in Chapter 4. In Chapter 2, I assess trophic dynamics in the CCLME using stable isotope analysis (SIA), utilizing isotope turnover parameters from Chapter 1. Using δ 13 C and δ 15 N values of primary consumers (plankton), secondary consumers (small squids and forage fish), and mid-upper trophic level predators (n = 17 predator and 13 prey species; 292 predator and 181 prey samples), I categorize organisms into trophic groups and estimate food inputs between trophic groups. I reveal higher connectivity in the pelagic food web of the CCLME than is predicted by the generally-accepted wasp-waist model of upwelling pelagic food webs, which assumes that most pelagic predators in upwelling, eastern boundary current systems feed primarily on one or few species of planktivorous v

4 secondary consumers, such as sardine or anchovy, which in turn feed on highly diverse and abundant zooplankton. Chapter 3 and Chapter 4 examine PBFT migration using different chemical tracer techniques. In 2011 the accident at the Fukushima Daiichi nuclear plant caused a massive spill of radionuclides into the Pacific Ocean in the waters off eastern Japan. This presented the possibility that migratory animals that forage in this region and subsequently migrate to distant ecoregions could be identified as emigrants from western Pacific waters. To test this new tracer we measured radioactive cesium ( 134 Cs and 137 Cs) in 15 PBFT that were caught in the CCLME and were between 1-2 years of age, making them definitive recent (previous year) migrants from waters around Japan. All 15 PBFT had elevated Cs compared to pre-fukushima bluefin and post-fukushima CCLME yellowfin tuna (CCLME migrants), proving that the PBFT had transported radiocesium across the Pacific Ocean and demonstrating the potential use of radiocesium as a tracer of migration. Chapter 4 validates the concept put forth in Chapter 3 to use Fukushima-derived radiocesium to track the movements of PBFT. In 2012, we sampled a larger dataset (n = 350) of PBFT in the CCLME to determine migration status using presence or absence of 134 Cs and levels of 137 Cs compared to background levels of this radioisotope present in yellowfin tuna Thunnus albacares, residents of the CCLME. Using a sample set of 50, we demonstrate that all small PBFT (n = 28), known from size to be recent migrants from Japan, show measurable levels of 134 Cs and elevated levels of 137 Cs. This shows that all known migrants carry the radiocesium signal from the Fukushima accident. In contrast, larger fish (n = 22) showed pre-fukushima levels of radiocesium in 17 fish, and vi

5 5 fish showed measurable levels of 134 Cs and elevated levels of 137 Cs, indicating recent migration from Japan. This study demonstrates that the radiocesium marker is detectable in all recent migrants, and that recent migrants or >1 year CCLME residents can be discerned using this tracer in larger PBFT, for which recent, retrospective migratory history is unknown. Chapter 5 combines three chemical techniques (SIA, Cs radiotracer, and amino acid compound-specific isotope analysis or AA-CSIA) to elucidate bluefin migration in the CCLME. I used Cs-marked PBFT (definitive Japan migrants) to inform a larger SIA dataset for PBFT sampled between We revealed that a larger proportion of older PBFT in the CCLME are recent Japan migrants than is generally believed. We also demonstrate that there is a seasonal trend to the arrival of Japan migrants to the CCLME. Finally, we suggest that this complementary chemical tracer toolbox can be applied to many highly migratory pelagic species in the Pacific to further elucidate their migration dynamics. Overall this work develops several tracers for application to PBFT (SIA and AA- CSIA) and presents the discovery and validation of a new tracer for migrations of Pacific pelagic predators (Fukushima-derived radionuclides). New information is supplied on the migratory dynamics of PBFT. These tracers, when used in the context of their model organism, can be applied to other pelagic predators to better understand their movement patterns. These approaches are especially pragmatic for species that are targeted by fisheries, as with the use of chemical tracers novel information can still be obtained from organisms that are no longer alive. vii

6 ACKNOWLEDGMENTS The Ph.D. is an interesting process. To outsiders I think it looks like a rather fun, not too difficult, and endlessly exciting, rewarding, and magical experience. Parts of that are true, but those who have done it (and those are probably the only people reading this document) understand there are subtle (and not so subtle) aspects that can make the experience difficult at times. As such, one finds support in distraction, in academic camaraderie, in friends who put up with complaints, in professionals who provide intellectual support, in professionals who provide moral support. At any given time, one of these can supersede the others. But humans were of course what really got me through, and made it matter. First I want to thank the Tuna Boys, who above all gave me the experiences I will look back on with the greatest nostalgia. We pursued a Steinbeckian existence at times, and there were days we really were Mack and the Boys. Eventually the work had to get done, and our lives got more boring, but the bonds remain. Meller, Koala, Great Dane, Bub, Mitch, Pedro, Nishad, James, Ty, Joe, Jon, The Kid, and Danny thanks for being the most interesting and adventurous fellows one could find in Monterey. Alex you taught me more about fishing I ever wanted to know. Without other friends this thing would have been impossible. The 141 Abalones, Ma, Teeny Tine, Ebeth, Bradleen man, you made Monterey more fun. Meller, Mitch, Marino, Sweeney, Martinez, Chrissy, Patrick, Benito, Scott, Reardon, Hannes thanks for the trips to Baja, my most valuable pastimes. viii

7 Special thanks to Patrick I wouldn t have gotten through without you. You are a true friend. I ve found incredible collaborators in the last 5 years. Danny Fuller thanks for your help, and teaching me what it takes to find and catch offshore fish. Kurt Schaefer, Brian Popp, Andy Seitz, Heidi Dewar, Owyn Snodgrass, Suzy Kohin, Kevin Weng, Hoyt Peckham; you all taught me more about pelagic fish, pelagic fishing, and pelagic fish science. Thank you to Barbara Block, who introduced me to the world of pelagic fish. Stanford@SEA from Tahiti to Hawaii will remain one of my most memorable experiences. My committee thanks to Rob for introducing me to stable isotopes, shared love for dogs, and laughs on the R.C. Seamans. Gilly provided consistent skepticism when it was definitely needed. Heidi provided great support and constant insight into aspects of pelagic ecology and migration, not to mention the framework and access to critical samples. Thank you Fio for all your support as my advisor. You have always been a sound resource for advice, insight, and scientific guidance, and I am amazed and appreciated at the amount of time you were willing to provide to this work. ix

8 I also am eternally grateful to the Shogun crew. You guys work hard, and to take the time to help me out was something I ll always appreciate. Randy good laughs when the going got rough. Chachee and Luis we never got Elvis, but we tried. Some day. A special thanks to Nick Fisher and Zosia Baumann. Nick thanks for taking a chance on a dubious project it s been an interesting ride. Thanks Zosia for your support, and how hard you work when we re in the crunch together. I can t wait to work with you more. My family was there at all times, and for necessary relief back at home for the holidays. Mom, Jim, Marissa, Kelly, Cathy, Janet thanks so much for your support through this whole project, and keeping things light when it was necessary. Finally, Maile. Words can t do justice to your contribution to the last 6 years of my life. In my mind this whole thesis began with Kitchen Science in San Francisco. I would never be here, still, without you. x

9 TABLE OF CONTENTS ABSTRACT...iv ACKNOWLEDGMENTS...viii TABLE OF CONTENTS......xi LIST OF TABLES...xiv LIST OF FIGURES.xvi INTRODUCTION... 1 CHAPTER Abstract Introduction Materials & Methods Captive Husbandry of Tunas Isotope analysis Arithmetic corrections of δ 13 C values Estimating turnover rate Calculating TDF Effects of growth Comparison of captive and wild δ 15 N values Results Time-based δ 13 C and δ 15 N turnover Tissue-specific TDF Growth Growth-based δ 13 C and δ 15 N turnover Contributions to turnover of growth and metabolic processes Comparison of captive and wild data Discussion Turnover in tissues Trophic discrimination factors (TDF) PBFT growth Applications to field data Conclusions.43 CHAPTER Abstract Introduction Materials & Methods Sampling Trophic groups Size effects Trophic dynamics Results Sampling Cluster analysis Size effects...58 xi

10 Mixing models Discussion General patterns Size effects Predator groupings Mixing models: individual species Mixing models: overall trophic dynamics CCLME: Wasp-waist control? Assumptions and caveats Conclusions.74 CHAPTER Abstract Introduction Materials & Methods Radioanalysis Statistical analysis Back-calculations for 2011 PBFT Estimates of radiocesium transport to CCLME Results Radiocesium in PBFT Naturally-occurring and trace radionuclides PBFT harvest and total radiocesium transport to the CCLME Estimates of Cs concentrations in PBFT in Japan Discussion Transport of radiocesium in PBFT PBFT harvest and consumer safety Back-calculations of radiocesium in PBFT while in Japan Migration estimates from Cs in PBFT Total transport of Cs by PBFT and potential transport by other species Conclusions.93 CHAPTER Abstract Introduction Materials & Methods Sampling and radioanalysis Age estimation Back-calculated departure date Statistical analysis Results Discussion Comparison with 2011 PBFT Inferred migration patterns Timing of migrations Caveats, assumptions, and application to other taxa Conclusions xii

11 CHAPTER Abstract Introduction Materials & Methods Sampling and isotopic analysis Migratory origin Migration timing Cs: 137 Cs clock approach SIA approach Results Regional differences Bulk and stable isotope analysis Estimates of residency time Discussion Regional differences Residents, recent migrants, timing, and fisheries Conclusions APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX REFERENCES xiii

12 LIST OF TABLES Table 1-1. Mean stable isotope values and time in captivity for all Pacific bluefin tuna (Thunnus orientalis) used in Chapter Table 1-2. Parameter estimates and 95% confidence intervals for time-based exponential fit models for each tissue and isotope in Pacific bluefin tuna Table 1-3. Table of mean isotope values and bulk C:N ratio values of Pacific bluefin tuna tissues, captive feed, and tissue-specific TDF values for white muscle and liver Table 1-4. Parameter estimates and 95% confidence intervals for relative growth-based (W R ) exponential fit models for each tissue and isotope in Pacific bluefin tuna Table 1-5. Parameter estimates and 95% confidence intervals for metabolic constant (m) from time-based exponential fits to δ 15 N and δ 13 C data for Pacific bluefin tuna white muscle and liver Table 2-1. Table of all predator and prey species sampled in this study, separated by trophic group (TG2-5)...52 Table 2-2. Estimated proportional prey inputs from Bayesian isotope mixing model (MixSir) of trophic groups (TG) to diets of nine predator species and to diets of trophic groups as a whole (TG3-5) Table 3-1. Measured concentrations of 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K for pre-fukushima bluefin (PBFT 2008) and post-fukushima yellowfin tunas (YFT 2011) caught in California waters.. 82 Table 3-2. Measured 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K for post-fukushima bluefin (PBFT 2011), pre-fukushima bluefin (PBFT 2008), and post-fukushima yellowfin tuna (YFT 2011) caught in California waters.. 83 Table 3-3. Measured concentrations of naturally occurring radionuclides 7 Be, 211 Bi, and 212 Pb and for n=15 post-fukushima Pacific bluefin tuna (PBFT 2011) caught in California waters Table 3-4. Measured concentrations of 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K and back-calculated concentrations of 134 Cs and 137 Cs for individual post-fukushima bluefin (PBFT 2011) caught in California waters.86 Table 3-5. Pacific bluefin tuna catch data and total harvested muscle biomass from in the Eastern Pacific Ocean...88 xiv

13 Table 4-1. Catch date, size, estimated age, and radionuclide concentrations in 50 Pacific bluefin tuna (PBFT) Thunnus orientalis, captured in the California Current Large Marine Ecosystem in Table 4-2. Catch date, size, and radionuclide concentrations in 5 yellowfin tuna (YFT) Thunnus albacares, captured in the California Current Large Marine Ecosystem in Table 4-3. Size, estimated age, date of catch, and estimated date of departure from Japan for 33 Pacific bluefin tuna (PBFT) Thunnus orientalis, identified as recent Japan migrants by presence of 134 Cs in muscle tissue Table 5-1. All prey δ 15 N values used to generate regional estimates of prey δ 15 N..130 Table 5-2. Bulk white muscle δ 15 N values for Pacific bluefin tuna used in discriminant analysis Table 5-3. Amino acid compound-specific results for migrant and resident Pacific bluefin tuna Thunnus orientalis and CCLME residents yellowfin tuna T. albacares, jack mackerel Trachurus symmetricus, and Pacific saury Cololabis saira.136 xv

14 LIST OF FIGURES Figure 1-1. Isotopic change over time in white muscle and liver tissues in captive Pacific bluefin tuna (Thunnus orientalis)..25 Figure 1-2. Relative growth (W R ) for individual Pacific bluefin tuna over time in captivity Figure 1-3. Specific growth rates (k') for Pacific bluefin tuna in captivity..29 Figure 1-4. Isotopic change with growth in two tissues in captive Pacific bluefin tuna Figure 1-5. Change in 15 N with time in captive and wild Pacific bluefin tuna...32 Figure 2-1. Map of the study area showing sampling effort off southern California, USA and northern Baja, Mexico...50 Figure 2-2. Biplot of δ 13 C and δ 15 N values for pelagic predators and prey of the CCLME...55 Figure 2-3. Biplot of δ 13 C and δ 15 N values for trophic groups 2-5 and TDF-corrected δ 13 C and δ 15 N values for nine predator species.56 Figure 2-4. Relationship between mean organism size and mean δ 15 N values for species sampled in this study Figure 2-5. Relationship of predator size and isotope values 58 Figure 2-6. Biplots showing relationship between body length and δ 13 C and δ 15 N values for eight southern California Current residents..60 Figure 2-7. Mixing model estimates of median proportion of diet input from four trophic groups for CCLME predators 62 Figure 2-8. Schematic showing isotope mixing model estimates of food flow through the southern CCLME pelagic ecosystem...63 Figure 3-1. (A) Map of the Northern Pacific Ocean showing simplified movement patterns and radiocesium concentrations, uptake, and efflux for juvenile and juvenile yellowfin tuna in the CCLME. (B) Simplified migration patterns of some highly migratory species in the Pacific that inhabit waters around Japan and make subsequent long distance migrations to distant ecoregions..84 xvi

15 Figure 3-2. Measured and back-calculated values of radiocesium concentrations in muscle of post-fukushima Pacific bluefin tuna Thunnus orientalis..87 Figure 3-3. Relationship of standard length and 134 Cs and 137 Cs concentrations in white muscle tissue in Pacific bluefin tuna sampled in August Figure 4-1. (A) Map of simplified movement patterns and (B) concentrations of 134 Cs and 137 Cs in Pacific bluefin tuna (migrants and residents) and yellowfin tuna (residents) in the CCLME Figure 4-2. Ratios of 134 Cs: 137 Cs in Pacific bluefin tuna caught in the CCLME from June through August Figure 4-3. (A) Relationship between PBFT age and estimated time since departure (days) from Japan for the 33 PBFT that contained 134 Cs and (B) histogram of estimated departure dates from Japan for recent migrant PBFT 107 Figure 4-4. Operculum length (OL) vs. curved fork length (CFL) for Pacific bluefin tuna, Thunnus orientalis (PBFT).108 Figure 5-1. (A) Map showing the differences in radiocesium concentrations of sea water and stable isotope compositions of prey near Japan and in the California Current System. (B) Resultant differences in radiocesium concentration and stable isotope values in a predator (Pacific bluefin tuna Thunnus orientalis) near Japan and in the CCLME Figure 5-2. Predicted temporal change of 134 Cs: 137 Cs ratio in Pacific bluefin tuna during their cross-pacific migration prior to their catch off California Figure 5-3. (A) Relationship of Pacific bluefin tuna (PBFT) white muscle δ 15 N values with PBFT size. (B) Results of discriminant analysis for three year classes of PBFT sampled in the California Current. (C) Amino acid compound-specific isotope analysis results for migrant PBFT, resident PBFT, resident prey (Cololabis saira and Trachurus symmetricus), and resident predator (yellowfin tuna Thunnus albacares) Figure 5-4. Bulk white muscle δ 15 N values for all tuna used in this study Figure 5-5. Estimates of time spent in CCLME for 130 Pacific bluefin tuna using isotopic clock technique with white muscle δ 15 N values Figure 5-6. (A) Relative proportions of recent Japan migrants and >1 year CCLME residents by month of capture in the California Current Large Marine Ecosystem. (B) Histogram showing estimated month of entry into CCLME based on white muscle δ 15 N isotopic clock estimates for year-class xvii

16 (YC) 1 and YC Figure 5-7. Results of calculations of migration timing for 14 Pacific bluefin tuna analyzed for 134 Cs in xviii

17 INTRODUCTION Large open ocean predators (sharks, tunas, billfishes, whales, dolphins, turtles, and others) are amongst the most recongnizable and iconic marine species. Yet these animals are difficult to study, and often the knowledge of their life history and basic biology is not to scale with the levels to which they are exploited by humans. Large predators can play an important role in oceanic ecosystems (Myers and Worm 2003, Scheffer et al. 2005, Block et al. 2011) and can shape community structure, alter prey behavior, and maintain biodiversity in pelagic communities (Worm et al. 2003, Heithaus et al. 2008, Baum and Worm 2009). Some are considered critically endangered or threatened (e.g. leatherback sea turtles, white sharks, Atlantic bluefin tuna, and albatross), due to over-exploitation, by-catch in fisheries, and prey depletion (Myers and Worm 2003, Scheffer et al. 2005, Peckham et al. 2007, Cury et al. 2011). Thus, to work towards conservation of threatened marine predator species, maintain oceanic biodiversity, and preserve pelagic ecosystem function, management practices based on sound understanding of the biology of these species is necessary (Worm et al. 2003). For species that migrate vast distances, understanding of migratory patterns (often across ontogeny) is essential in gauging the extent to which a species utilizes different ecosystems, and consequently the effects fishing may have in different oceanic regions. Electronic tagging programs (e.g., Block et. al 2011) have shed an enormous amount of light on the cryptic movement patterns of pelagic species in a relatively short amount of time. However, these studies have also raised many more questions about the ecology and movements of pelagic animals. Do animals feed in distant, seemingly unproductive offshore areas, such as white sharks Carcharodon carcharias in the white 1

18 shark café (Boustany et al. 2002, Carlisle et al. 2012)? If so, how successfully are they foraging, and upon what are they foraging? When animals enter a hotspot for electronic tagging, we learn later from the tags where those animals went. Where, though, did those animals migrate from? Researchers have begun to utilize many intrinsic tags, such as stable isotopes, environmental contaminants, fatty acid signatures, and other markers to answer some of these questions (Ramos and González-Solís 2012). This thesis improves interpretations of chemical tools already in use (stable isotope analysis) using laboratory studies, puts these findings to use to explore ecological interactions in a pelagic ecosystem, and uses established (stable and amino acid compound-specific isotope analysis) and new (Fukushima derived radionuclides) chemical tracers in convert to improve the tools available for researchers of pelagic animals, and elucidate the ecology and trophic dynamics of pelagic predators in the Pacific Ocean, particularly Pacific bluefin tuna Thunnus orientalis. In Chapter 1, I examine dynamics of stable isotope turnover rates and trophic discrimination factors in Pacific bluefin tuna (PBFT) held in captivity for days. Stable isotope analysis (SIA) is a popular ecological tool that is increasingly used to study trophic ecology and animal migration. SIA uses the ratio of a heavier, less common isotope to a lighter, more common isotope, most often the ratios of 15 N/ 14 N (δ 15 N) and 13 C/ 12 C (δ 13 C) in ecological studies using plant and animal tissues. Due to this minimal fractionation (i.e., increase of δ-values) in food webs, δ 13 C values are often used to estimate carbon source inputs to consumer diets when δ 13 C values are different at the producer level. In contrast, δ 15 N values tend to increase with each trophic step, and accordingly are often used to estimate the trophic level of organisms within food webs. 2

19 Researchers have used SIA to examine trophic dynamics and structural changes in ecosystems (Peterson and Fry 1987, Rundel et al. 1989, Gannes et al. 1998, Layman et al. 2007), and isotope studies have also elucidated the movements of migratory animals (Hobson and Wassenaar 2008, Graham et al. 2010, Carlisle et al. 2012). However, the dynamics of consumer-prey isotope discrimination and of tissue-specific turnover rates of carbon and nitrogen in various animal tissues are required by researchers to correctly interpret SIA data from wild organisms (Gannes et al. 1997). Pelagic animals, including seabirds (Hobson et al. 1994, Sydeman et al. 1997), pinnipeds (Kurle and Worthy 2001), sharks (Estrada et al. 2003, MacNeil et al. 2005, Carlisle et al. 2012), and teleosts (Graham et al. 2007), have been increasingly studied using SIA. Due to the oceanic lifestyle of these animals, studies of their ecology and migration patterns have historically been difficult. The long-term holding of captive Pacific bluefin tuna, Thunnus orientalis, (PBFT) at the Tuna Research and Conservation Center (TRCC) and Monterey Bay Aquarium (MBA) (Farwell 2001) provides a unique opportunity to study SIA dynamics in an open ocean predator. PBFT were kept in captivity for up to 2914 days, and we calculated turnover rates in PBFT white muscle and liver, two commonly used tissues in isotope studies. We also calculated TDFs of PBFT from animals in which tissue isotopic composition had reached steady-state with the controlled diet. Together TDF values and turnover rates can be applied to data from wild tunas to study aspects of their feeding ecology and migration with a precision that has thus far not been possible. Chapter 2 puts the parameters from Chapter 1 (and from other studies) to examine trophic dynamics in the southern California Current Large Marine Ecosystem (CCLME). 3

20 The CCLME is one of five Eastern boundary current systems (EBCs), which are often described as wasp-waist ecosystems in which one or few mid-level forage species support a high diversity of larger predators that are highly susceptible to fluctuations in prey biomass. The assumption of wasp-waist control has not been empirically tested in all EBC ecosystems. In Chapter 2, I use stable isotope analysis to test the hypothesis of wasp-waist control in the southern California Current large marine ecosystem (CCLME). I analyzed prey and predator tissue for stable isotope values of δ 13 C and δ 15 N and used Bayesian mixing models to provide estimates of CCLME trophic dynamics from Our results show high omnivory, planktivory by some predators, and a higher degree of trophic connectivity than that suggested by the wasp-waist model. Based on this study period, wasp-waist models oversimplify trophic dynamics within the CCLME and potentially other EBC ecosystems. Higher trophic connectivity in the CCLME likely increases ecosystem stability and resilience to perturbations. Chapters 3 and 4 demonstrate and validate a new tool for the migrations of Pacific predators in the form of Fukushima-derived radiocesium. On March 11, 2011 an earthquake and subsequent tsunami flooded the Fukushima Dai-ichi nuclear power plants in Japan and led to the release of radionuclides directly into the ocean exceeding that from any previous accident (Buesseler et al. 2011), with an estimated total release of up to 22 x Bq (Buesseler et al. 2012). The dominant long-lived gamma-emitting radionuclides 134 Cesium (t 1/2 = 2.1 yrs) and 137 Cs (t 1/2 = 30 yrs) were released at a ratio of about 1 (0.99 ± 0.03) (Buesseler et al. 2011). Prior to the Fukushima discharge, low concentrations (1.5 mbq L -1 ) of the long-lived 137 Cs (fallout from weapons testing) were detectable in Japanese waters (Buesseler et al. 2011), whereas the shorter-lived 134 Cs was 4

21 undetectable in Pacific surface waters and biota. Pacific bluefin tuna, spawn in the western Pacific, and some juveniles remain in Japanese waters while others migrate eastward to the CCLME, with most migrating late in their first year or early in their second (Bayliff 1994). All bluefin between years 1-2 (here, 2 yr old PBFT) caught during summer in the eastern Pacific must have migrated from the western Pacific within several months of capture, and juveniles make extensive use of this region before their eastward migration to the CCLME (Kitagawa et al. 2009). I test the possibility that juvenile PBFT served as biological vectors of radionuclides between two distant ecoregions: the waters off Japan and the CCLME. The findings in Chapter 3 reveal a new tool to trace migration origin (using the presence of 134 Cs) and migration timing (using 134 Cs: 137 Cs ratios) in highly migratory marine species in the Pacific Ocean. Chapter 4 tests the assumptions of the Cs tracer in 50 PBFT in 2012, and demonstrates that all recent migrants (PBFT 1.7 years old) carry the Cs tracer, and older PBFT are a mix of CCLME residents and recent migrants. Finally, Chapter 5 combines the parameters derived in Chapter 1 and the new tracer developed in Chapters 3 and 4 to examine Pacific bluefin migration patterns from Japan to the CCLME. Many pelagic predators possess life history traits and/or high market values that make them vulnerable to overfishing and population collapse (De Roos and Persson 2002, Collette et al. 2011d). In the case of highly migratory species, migration patterns sometimes require international management and cooperation (e.g. Atlantic bluefin tuna (Block et al. 2001, Rooker et al. 2008, Taylor et al. 2011)). Thus for species that migrate vast distances, understanding of migratory patterns (often across 5

22 ontogeny) is essential in gauging the extent to which a species utilizes different ecosystems, and consequently the effects fishing may have in different oceanic regions. Pacific bluefin tuna utilizes both sides of the North Pacific Ocean, giving it one of the largest distributions of any fish species. Extensive conventional (Bayliff 1994) and electronic (Block et al. 2011) tagging programs have shown that once in the CCLME, PBFT often remain for years before returning to the west Pacific, presumably to spawn (Boustany et al. 2010, Block et al. 2011). PBFT are exploited by both recreational and commercial fisheries, with the commercial fishery in the CCLME preferably targeting larger (> 1-2 years old) fish (Zertuche-González et al. 2008). Presently, the proportion of long-term (>1 year) residents of the CCLME to recent (past year) migrants from Japan across different size classes of PBFT in the CCLME is largely unknown. It is therefore unclear whether the CCLME fishery depends largely on recent migrants of mixed size/age from Japan or on small/young fish that migrated to the CCLME several years before and were given the chance to mature within the CCLME to reach larger, targeted size. Stable isotope δ 15 N values can be used to infer different food-web baseline sources (e.g. phytoplankton vs. macroalgae), as primary producers in discrete ecosystems (e.g. oligotrophic pelagic versus productive coastal upwelling systems) may have dissimilar δ 15 N values that will propagate up regional food webs (Fry 2006, Graham et al. 2010, Carlisle et al. 2012). Thus a predator moving into a new ocean region from an isotopically distinct one will not reflect local δ 15 N prey values (migration effects). However, δ 15 N values also reflect trophic level due to the systematic increase of δ 15 N values with each trophic step in food webs (Post 2002, Fry 2006). Amino acid 6

23 compound-specific isotope analysis (AA-CSIA) can be used to discern migration from trophic effects when interpreting bulk tissue SI values (Popp et al. 2007, Olson et al. 2010, Seminoff et al. 2012). AA-CSIA measures the δ 15 N values of individual amino acids from proteins in tissues. Certain source amino acids (glycine, serine, and phenylalanine) have been shown to fractionate minimally up food webs, while trophic amino acids (alanine, valine, leucine, isoleucine, proline, and glutamic acid) demonstrate relatively high trophic fractionation (Popp et al. 2007, Chikaraishi et al. 2010). Thus by comparing the source AA δ 15 N values of tissues from animals with different bulk δ 15 N values, one can differentiate whether the difference is likely migration-based (different source δ 15 N values) or trophic (similar source δ 15 N values) (Sherwood et al., Popp et al. 2007, Seminoff et al. 2012). PBFT are not currently considered overfished, but overfishing is occurring (Collette et al. 2011a). The next stock assessment is likely to change estimates of PBFT population status for the worse (PBFWG 2011). In order to not follow the trends of overexploitation in southern bluefin tuna Thunnus maccoyii (Collette et al. 2011c) and Atlantic bluefin tuna T. thynnus (Collette et al. 2011b), information that facilitates international management of this Pacific-wide species is required (Whitlock et al. 2012). In Chapter 4 I use SIA values from PBFT marked with Fukushima-derived 134 Cs (Chapter 3) to inform a larger dataset of PBFT SIA values to elucidate the migratory history of different year classes of PBFT in the CCLME, and distinguish migration effects from potential trophic effects on bulk SIA values using AA-CSIA. Analysis revealed the proportion of migrants to residents in the CCLME, information which is essential for the CCLME fishery. We suggest that this new chemical toolbox can be 7

24 applied to PBFT, and other migratory species in the North Pacific Ocean, to complement the prospective data provided by tagging and provide reliable, retrospective information on the recent migratory history of Pacific predators. 8

25 Chapter 1 Tissue Turnover Rates and Isotopic Trophic Discrimination Factors in the Endothermic Teleost, Pacific Bluefin Tuna (Thunnus orientalis) Publication: Madigan DJ, SY Litvin, BN Popp, AB Carlisle, CJ Farwell, and BA Block Tissue turnover rates and isotopic trophic discrimination factors in the endothermic teleost, Pacific bluefin tuna (Thunnus orientalis). PLoS ONE 7:e Abstract Stable isotope analysis (SIA) of highly migratory marine pelagic animals can improve understanding of their migratory patterns and trophic ecology. However, accurate interpretation of isotopic analyses relies on knowledge of isotope turnover rates and tissue-diet isotope discrimination factors. Laboratory-derived turnover rates and discrimination factors have been difficult to obtain due to the challenges of maintaining these species in captivity. We conducted a study to determine tissue- (white muscle and liver) and isotope- (nitrogen and carbon) specific turnover rates and trophic discrimination factors (TDFs) using archived tissues from captive Pacific bluefin tuna (PBFT), Thunnus orientalis, days after a diet shift in captivity. Half-life values for 15 N turnover in white muscle and liver were 167 and 86 days, and for 13 C were 255 and 162 days, respectively. TDFs for white muscle and liver were 1.9 and 1.1 for δ 15 N and 1.8 and 1.2 for δ 13 C, respectively. Our results demonstrate that turnover of 15 N and 13 C in bluefin tuna tissues is well described by a single compartment first-order kinetics model. We report variability in turnover rates between tissue types and their isotope dynamics, and hypothesize that metabolic processes play a large role in turnover of nitrogen and carbon in PBFT white muscle and liver tissues. 15 N in white muscle tissue showed the most predictable change with diet over time, suggesting that white muscle δ 15 N data may provide the most reliable inferences for diet and migration studies 9

26 using stable isotopes in wild fish. These results allow more accurate interpretation of field data and dramatically improve our ability to use stable isotope data from wild tunas to better understand their migration patterns and trophic ecology Introduction Stable isotope analysis (SIA) is a popular ecological tool that is increasingly used to address a variety of topics, including trophic ecology and animal migration. Researchers have used SIA to examine nutrient flow, trophic dynamics, and structural changes in ecosystems (Peterson and Fry 1987, Rundel et al. 1989, Gannes et al. 1998, Layman et al. 2007, Madigan et al. 2012b), and isotope studies have also elucidated the origins, variation, and timing of movements of migratory animals (Hobson and Wassenaar 2008, Graham et al. 2010, Carlisle et al. 2012). However, the number of stable isotope studies of natural systems far outnumbers laboratory-based studies which can be necessary to validate and interpret results (Gannes et al. 1997). Foreseeing the growth of SIA studies, Gannes et al. (1997) called for more laboratory experiments, and though the number of studies has increased, additional controlled laboratory studies are needed for the many ecosystems, food webs, species and tissues subjected to SIA (Martínez del Rio et al. 2009). Specifically, the dynamics of consumer-prey isotope discrimination and of tissue-specific turnover rates of carbon and nitrogen in various animal tissues are required by researchers to correctly interpret SIA data from wild organisms (Gannes et al. 1997). SIA uses the ratio of a heavier, less common isotope to a lighter, more common isotope, most often the ratios of 15 N/ 14 N (δ 15 N) and 13 C/ 12 C (δ 13 C) in ecological studies 10

27 using plant and animal tissues. Carbon and nitrogen isotopes are fractionated (i.e., δ- values increase) between trophic levels in food webs; however the trophic increase of 13 C has been shown to be lower than that of 15 N across various taxa (Post 2002). Due to this minimal fractionation in food webs, δ 13 C values are often used to estimate carbon source inputs to consumer diets (e.g., C3 or C4 plants, macroalgae or phytoplankton) when δ 13 C values are different at the producer level. In contrast, δ 15 N values tend to increase with each trophic step, and accordingly are often used to estimate the trophic level of organisms within food webs. More complex tools that use SIA (e.g., mixing models (Moore and Semmens 2008), isotopic clocks (Klaassen et al. 2010) require accurate trophic discrimination factors (TDFs; the difference between the δ-values of a consumer s tissues and its diet) and tissue turnover rates to make reliable estimates of consumer foraging and the origin and timing of migrations. Isotopic turnover is defined as the time it takes for certain consumer tissues to reflect the isotopic composition of its food resources, and is the result of both tissue growth and tissue replacement (Hesslein et al. 1993, MacAvoy et al. 2005, MacAvoy et al. 2006). Turnover rates can be measured by monitoring tissue isotope values over time until steady-state is established between tissue and diet. A function is then fitted to the change in isotope composition over time, and a half-life for that tissue and isotope can be calculated (Hesslein et al. 1993, MacAvoy et al. 2005, MacAvoy et al. 2006). Tissue turnover rates in blood, liver, skeletal muscle, and other tissues have been described for several species (Hesslein et al. 1993, Bosley et al. 2002, Podlesak et al. 2005, Logan et al. 2006, Buchheister and Latour 2010). Turnover rates depend on metabolic processes within animal tissues, mass, and growth, which vary with ontogeny, 11

28 across taxa, and across tissue types. Using inappropriate TDF and turnover values can lead to erroneous interpretation of stable isotope data (Phillips and Gregg 2003a, Moore and Semmens 2008). Accurate isotopic turnover and TDF values are highly useful for improving isotope models, such as mixing models (Phillips and Gregg 2003a, Moore and Semmens 2008) and isotopic clock approaches (Fry 2006, Klaassen et al. 2010). Thus lab-controlled studies of stable isotope dynamics in animal tissues greatly improve our capacity to use isotopic data to study the natural history (e.g., diet and migrations) of the organisms of interest. Pelagic animals, including seabirds (Hobson et al. 1994, Sydeman et al. 1997), pinnipeds (Kurle and Worthy 2001), sharks (Estrada et al. 2003, MacNeil et al. 2005, Carlisle et al. 2012), and teleosts (Graham et al. 2007), have been increasingly studied using SIA. Due to the oceanic lifestyle of these animals, studies of their ecology and migration patterns have historically been difficult. Feeding ecology studies have relied on traditional gut content analyses (GCA). While providing species-specific diet information that SIA cannot provide, GCA often provides only a snapshot of predator diet (Cailliet 1977). While long-term, comprehensive studies using GCA are possible, they are extremely time- and labor-intensive. The movements of pelagic organisms have historically been difficult to study, though electronic tagging has significantly increased our understanding of the movements of these highly migratory pelagic species (Block et al. 2011). However, electronic tags are expensive, deployments are challenging to execute, and only in rare instances can the electronic tag provide data regarding foraging or diet information, though feeding has been demonstrated using tags in wild tunas, pinnipeds, and sharks (Sepulveda et al. 2004, Bestley et al. 2008, Kuhn et al. 2009). 12

29 Furthermore, electronic tagging only provides movement data while the tag is functioning on the animal and provides no information on retrospective movements. SIA serves as a powerful complement to electronic tagging and GCA, allowing the capacity to track large scale oceanic movements and diet using carbon and nitrogen isotope values. Few validation studies on stable isotope dynamics exist in large, predatory pelagic teleosts due to the difficulty of holding large pelagics in captivity. Thus laboratory-based studies of stable isotope dynamics in pelagic fishes are conspicuously absent, yet necessary in order to effectively apply SIA to study the ecology of pelagic species and ecosystems. The long-term holding of captive Pacific bluefin tuna, Thunnus orientalis, (PBFT) at the Tuna Research and Conservation Center (TRCC) and Monterey Bay Aquarium (MBA) (Farwell 2001) provides a unique opportunity to track the changes in isotopic composition of multiple tissues over a long time period after collection from the wild and a change to a controlled diet with a different isotopic composition in a temperaturecontrolled tank setting. PBFT used in this study were kept in captivity for up to 2914 days, providing the longest dataset available for a large pelagic fish fed a controlled diet. We aimed to 1). calculate turnover rates in PBFT white muscle and liver, two commonly used tissues in isotope studies and 2). calculate the TDFs of PBFT from animals in which tissue isotopic composition had reached steady-state with the controlled diet. In addition we estimated the relative importance of growth vs. metabolism in tissue turnover rates. Together TDF values and turnover rates can be applied to data from wild tunas to study aspects of their feeding ecology and migration with a precision that has thus far not been possible. 13

30 1.3. Materials & Methods Captive Husbandry of Tunas Juvenile Pacific bluefin tuna, Thunnus orientalis, were collected by hook and line off the coast of San Diego, CA, during July-September from 2000 to 2010 according to methods in Farwell (2001). These fish are born in the western Pacific and forage for a year prior to migrating to the eastern Pacific (Bayliff 1994, Boustany et al. 2010, Madigan et al. 2012a). Bluefin are transported to the Tuna Research and Conservation Center (TRCC) for research purposes and/or display at the Monterey Bay Aquarium in Pacific Grove, CA. Size at collection was measured as curved fork length (CFL) and ranged from 62.5 to 92 cm. Tunas were held aboard the F/V Shogun in seawater-filled wells and subsequently transported in a 4000 L tank to TRCC. Fish were held in three tanks at approximately 20 C (SD ± 0.2 C) until they were sacrificed for research according to IACUC protocols or incurred natural mortality. Fish were fed a consistent ratio of sardines, squid, and enriched gelatin as previously described (Farwell 2001). Tunas were fed thawed frozen food in the TRCC (by mass: squid 60%; sardine 31%; gelatin 9%) that have higher weighted mean δ 13 C and δ 15 N values (δ 13 C: ± 0.3; δ 15 N: 13.9 ± 0.7) than white muscle (WM) and liver (LIV) tissues of juvenile year class one and two (YC1 and YC2) PBFT (δ 13 C: ± 0.2; δ 15 N: 11.8 ± 0.2) captured off southern California. These experimental conditions allowed calculation of tissue turnover rates and tissue-specific trophic discrimination factors (TDFs) of δ 13 C and δ 15 N values in WM and LIV of juvenile, growing PBFT as they approached and maintained isotopic steady-state conditions with the isotopic composition of the feed. Some fish were moved as they reached large size from the TRCC facility to the Monterey Bay 14

31 Aquarium (MBA) tanks, where food ratios (kg food:kg tunas) remained the same although the quantity of food increased. Transport usually occurred after ~700 days in the TRCC, so only the largest fish with the longest duration in captivity were subjected to conditions in MBA tanks. Tissue samples were routinely collected over the course of ten years and frozen at -20 C. Archived tissues were used opportunistically for this study. Samples of captive food (sardine and squid WM tissues) were sampled periodically through the years of to ensure seasonal and inter-annual consistency of feed values. Squid and sardine feed are of coastal CA origin, and though δ 13 C and δ 15 N values in zooplankton have been shown to change on short timescales, considerable long-term stability of isotope values has been demonstrated in the California Current Ecosystem (Rau et al. 2003, Ohman et al. 2012). Consequently the isotopic compositions of feed from previous years were assumed to be similar to those analyzed in this study. For this study, we used only tissues from Pacific bluefin that were of similar size at capture (62.5 to 75 cm) and were healthy and feeding at the time of mortality. A total of 69 PBFT were sampled for WM and 62 for LIV tissues. Liver tissue was not available for 7 of the 69 individuals analyzed, either due to sample unavailability or C/N ratios too high for appropriate application of lipid-correction algorithms (Logan et al. 2008). Time in captivity ranged from days (485 ± 607 days) Isotope analysis PBFT WM tissue was collected from the hypaxial musculature under the first dorsal fin of the animal and ~20 cm below the skin. Liver tissue was collected from the interior of the center lobe of the liver. From sardines, a section of dorsal WM was taken; 15

32 from squid, a section of mantle with the outer membrane removed. Tissues were frozen at -80 C and subsequently lyophilized and ground to a homogenous powder for isotope analysis. The δ 13 C and δ 15 N values of all samples were determined at the Stanford Stable Isotope Biogeochemistry Laboratory using a Thermo Finnigan Delta-Plus IRMS coupled to a Carlo Erba NA1500 Series 2 elemental analyzer via a Thermo Finnigan Conflo II interface. Replicate reference materials of either graphite NIST RM 8541 (USGS 24), acetanilide, ammonium sulfate NIST RM 8547 (IAEA N1) or glutamic acid (USGS 40) were analyzed between approximately 8 unknowns and each had a standard deviation <0.15. Isotope ratios are described by: δ q X A = (R A /R standard - 1) x where q is the isotope of interest, X is the element of interest, A is the tissue type (e.g. muscle or liver), R A is the ratio of the rare to the common isotope, and R standard is the isotope standard Air or V-PDB. Isotope values are reported as per mille ( ) Arithmetic corrections of δ 13 C values White muscle and liver δ 13 C values were lipid-normalized based on bulk C/N values (by mass) following calculations in Logan et al. (2008) due to the ability of lipid content to bias δ 13 C measurements (Post et al. 2007, Logan et al. 2008) (Appendix 1). We used species- and tissue-specific lipid correction factors for Atlantic bluefin tuna Thunnus thynnus (Logan et al. 2008): 16

33 δ 13 C' tissue = P (P*F/ C:N) + δ 13 C tissue 1-2 where δ 13 C' tissue is the arithmetically-corrected δ 13 C tissue value, C:N is the atomic C/N ratio of the specific sample, and P and F are parameter constants based on measurements by Logan et al. (2008). While both chemical and lipid extractions have been shown to be effective methods to correct bias in δ 13 C values based on lipid-content, arithmetic corrections preserve sample integrity and simplify sample preparation (Post et al. 2007). Arithmetic corrections are especially useful and more reliable when organism- and tissuespecific algorithms are available, as was the case here (Post et al. 2007, Logan et al. 2008). Arithmetic corrections to tissue δ 13 C values only eliminate variability of lipid content, and the subsequent variability in δ 13 C, across sample types Estimating turnover rate We used an exponential fit model for two tissues (WM and LIV) and two isotope values (δ 13 C and δ 15 N) as used previously (Fry and Arnold 1982, Tieszen et al. 1983, Hobson and Clark 1992, Podlesak et al. 2005): δ t = ae -λt + c 1-3 where δ t is the isotope value of interest changing with time t, a and c are parameters derived from the best fit, and λ is a data-derived first-order rate constant. Parameters a and c represent important resultant parameters: a = isotope difference between initial and 17

34 final steady-state values and c is the data-derived final isotope steady-state value (Tieszen et al. 1983). The tissue- and isotope-specific half-life (t 0.5 ) is then calculated: t 0.5 = ln(2)/- λ 1-4 for different λ values derived for δ 15 N WM, δ 15 N LIV, δ 13 C WM, and δ 13 C LIV. We used a modified equation from Buchheister and Latour (2010) to calculate the time needed to obtain a given percentage (α) of complete turnover: t α/100 = ln(1-α/100)/-λ 1-5 where t α/100 is the time needed to attain α% turnover and λ is the data-derived first-order rate constant. Multi-compartment models can sometimes provide better insight into turnover dynamics than first-order, one-compartment models (Cerling et al. 2007, Martínez del Rio and Anderson-Sprecher 2008). We used the reaction progress variable model of Cerling et al. (2007) to evaluate whether a single-compartment model with first-order kinetics adequately described the changes in carbon and nitrogen isotopic compositions of white muscle and liver tissues in PBFT: t ss ( 1 F) 1-6 i ss where δ t is the isotopic value at time t during the experiment, δ i is the data-derived initial isotopic value (c a in eqn. 3), and δ ss is the data-derived isotope final steady-state value (Table 1-3). A linear fit to ln(1 - F) as a function of time has been shown to be consistent 18

35 with a system that can be well-described by a single compartment model (Cerling et al. 2007, Martínez del Rio and Anderson-Sprecher 2008). Modeling the change in δ 15 N and δ 13 C values of white muscle and liver tissues using equation 6 indicates that a singlecompartment model adequately described the results (Appendix 2). We compared our carbon turnover rates to those predicted by allometric scaling in fish reported in Weidel et al. (2011). This study showed that fish mass (g) was a strong predictor of fish carbon turnover rates (r 2 = 0.71) with the equation: ln(λ) = ln(mass) 1-7 We used final mass (W f ) to generate a mean (± SD) value for carbon turnover in Pacific bluefin white muscle to assess the application of this equation to Pacific bluefin, and to assess whether allometric scaling of turnover rates adequately predicted the carbon turnover rates we observed in PBFT Calculating TDF We calculated trophic discrimination factor (TDF) using the difference between mean δ 15 N WM, δ 15 N LIV, δ 13 C WM, and δ 13 C LIV values from animals that had reached steadystate with diet and the weighted mean δ 15 N and δ 13 C values of food, which was consistent over time. TDF values (Δ TISSUE ) are calculated for white muscle and liver according to the equation: Δ TISSUE = mean (δ TISSUE δ FOOD )

36 where Δ TISSUE represents the tissue- and isotope-specific TDF, δ TISSUE is the nitrogen or carbon isotope value of a specific tissue for each animal that reached steady-state with diet, and δ FOOD is an average nitrogen or carbon isotope value of the food (here squid, sardine, and supplement) arithmetically lipid-corrected (Logan et al. 2008) and weighted by the proportional mass of each item in the control diet. TDF values were calculated from isotope values from tissues in animals that had been in captivity for enough time to reach 95% turnover (t 0.95, Table 1-2). We compared our experimentally-derived TDF values to the Diet-Dependent Discrimination Factor algorithms reported by Caut et al We used the fish white muscle equation from that study for 15 N: Δ WM = x δ 15 N and compared that theoretical TDF to our experimentally-derived value Effects of growth Fish length (CFL) was recorded at t 0 and t f, and standard length (SL) estimated from CFL. Only final mass (W f ) was measured directly at t f. Initial mass (W i ) was estimated from SL using the equation: W i = ( x 10-7 ) x SL ( )

37 from Deriso and Bayliff (1991). Relative gain in mass (W R, hereafter referred to as relative growth ) was then calculated: W R = W f /W i 1-11 where W f is the measured final mass and W i is the initial mass estimate from SL. Using the equation from Ricker (1979) for W f : W f = W i e k't 1-12 where k' is the group specific growth-rate constant, we derive k': k' = ln(w R )/t 1-13 and can obtain the growth rate constant k' for all fish using relative growth (W R ) and time in captivity t. Hesslein et al. (1993) describes the isotope value of a fish at time t (δ t ) as: δ t = δ f + (δ i δ f )e -(k' + m)t 1-14 where δ f is the final, or data-derived steady-state isotope value, δ i is the initial isotope value, m is the metabolic turnover constant, and k' and t are as previously described. This is a modification of eq. 3, where δ f = c, (δ i δ f ) = a, and (k' + m) = λ. Thus we calculate λ from eq. 3, k' from eq. 13, and use eq. 14 to calculate the metabolic constant m for the 21

38 tissue and isotope of interest. We can also calculate the amount of relative growth needed to achieve α percent turnover of δ 13 C and δ 15 N (Buchheister and Latour 2010): G α/100 = exp (ln(1 α/100)/c) 1-15 and growth-based turnover can be calculated: G 0.5 = exp (ln(0.5)/c) 1-16 where G 0.5 is the growth-based half-life and c is the data-derived rate constant for δ 13 C WM, δ 13 C LIV, δ 15 N WM, and δ 15 N LIV. Finally, we estimate the proportion of isotopic turnover due to growth (P g ) and the proportion of turnover due to metabolism (P m ) as the proportion of k' and m, respectively, of the overall isotopic turnover constant λ (Ricker 1979, Buchheister and Latour 2010): P g = k'/λ 1-17 P m = m/λ 1-18 We apply equations to δ 13 C and δ 15 N values in PBFT WM and LIV tissues and report growth turnover constants, metabolic turnover constants, and overall estimated contribution of growth and turnover to observed isotope turnover in captive PBFT for both tissues and isotopes. 22

39 Comparison of captive and wild δ 15 N values We plotted wild Pacific bluefin tuna data from a companion study (Chapter 4) to compare turnover of wild fish that, based on size, are known to have recently arrived to the California Current from the Western Pacific Ocean (Bayliff 1994, Boustany et al. 2010, Madigan et al. 2012a) to turnover of captive fish analyzed here. We used the smallest wild bluefin in the dataset (61.6 cm) as a starting size for recent migrants in the CCLME (t = 0) and estimated each wild bluefin s residency time in the CCLME according to the PBFT growth equation (Bayliff et al. 1991): SL t = SL capture (t x cm day -1 ) 1-19 and solved for t for each wild fish to gain an estimate of residency time in the CCS. δ 15 N values of wild fish were plotted against time with captive fish to visually compare turnover of captive and wild datasets Results Both white muscle (WM) and liver (LIV) tissues reached asymptotic values, representing steady-state with diet in time- and growth-based models. This allowed for reliable calculation of tissue turnover rates and trophic discrimination factors for fish held in captivity from days (Table 1-1). A single-compartment model with first-order kinetics adequately described changes in carbon and nitrogen isotopic compositions of liver and white muscle tissues during the early stages (0 725 days) of the study. Application of the reaction progress variable showed no evidence of multiple turnover 23

40 pools, and the reaction progress variable model is sensitive to the steady-state isotopic composition (Cerling et al. 2007, Martínez del Rio and Anderson-Sprecher 2008); thus Table 1-1. Mean stable isotope values and time in captivity for all Pacific bluefin tuna (Thunnus orientalis) used in this study. δ 13 C values are arithmetically-corrected for lipid content based on tissue- and species-specific (Thunnus thynnus) algorithms from Logan et al. (2008). n Time in captivity (d) ΔMass (SD) (kg) WM δ 15 N (SD) WM δ 13 C (SD) LIV δ 15 N (SD) LIV δ 13 C (SD) (0.2) (0.4) 11.6 (0.8) (1.3) (0.93) 12.9 (0.7) (0.6) 13.8 (0.7) (0.8) (1.27) 13.5 (0.8) (0.5) 14.0 (0.7) (0.5) (1.13) 14.3 (0.3) (0.3) 14.4 (0.7) (0.4) (2.38) 14.8 (0.9) (0.5) 14.6 (0.4) (0.5) (0.95) 15.2 (0.3) (0.4) 15.2 (0.7) (0.4) (1.56) 15.3 (0.2) (0.3) 15.0 (0.6) (0.5) (47.96) 15.4 (0.3) (0.3) 15.1 (0.3) (0.5) (42.75) 15.7 (0.3) (0.4) 15.2 (0.8) (1.5) (43.73) 16.1 (0.3) (0.4) 14.6 ( ) ( ) results from the latter portions of this study were difficult to evaluate using the RPV approach. Exponential functions thus provided the best fit for turnover rates of C and N in both white muscle and liver Time-based δ 13 C and δ 15 N turnover Turnover based on changes in δ 13 C and δ 15 N values was evident in the early stages (0-725 days) of the study in both WM and LIV tissues, after which steady-state was reached for both isotope values in each tissue (Figure 1-1). Liver tissue turnover was 24

41 faster for both δ 13 C and δ 15 N (t 0.5 = 162 and 86 days, respectively) than turnover in WM (t 0.5 = 255 and 167 days; Table 1-2). Estimated carbon turnover in WM based on allometric scaling of isotopic turnover rates in fish (Weidel et al. 2011) was 183 ± 42 days, and our calculated value (255 days) was within the 95% confidence interval of this estimate. Figure 1-1. Isotopic change over time in white muscle and liver tissues in captive Pacific bluefin tuna (Thunnus orientalis). δ 15 N and δ 13 C values in Pacific bluefin tuna white muscle (WM; filled circles) and liver (LIV; open circles) are shown as a function of time (days) after change to isotopically distinct captive diet. Lines represent time-based exponential model fits for WM (solid line) and LIV (thin dotted line). 25

42 In general, exponential model fits were better for WM tissue than for liver and for δ 15 N than for δ 13 C values, resulting in narrowest 95% CI estimates for t 0.5 in WM δ 15 N ( d) and broadest 95% CI estimates for LIV δ 13 C ( d; Table 1-2). Using 95% turnover as the cutoff for steady-state isotopic conditions with diet (i.e. the time needed for δ 13 C and δ 15 N values in WM and LIV to accurately represent recent dietary inputs), liver δ 15 N reached steady-state with diet first (t 0.95 = 372 days) and white muscle δ 13 C last (t 0.95 = 1103 days). Table 1-2. Parameter estimates and 95% confidence intervals for time-based exponential fit models for each tissue (WM or LIV) and isotope (δ 15 N or δ 13 C) in Pacific bluefin tuna (Thunnus orientalis). Estimated half-life (t 0.5 ) and time for 95% isotope turnover (t 0.95 ) is shown for each tissue and isotope. Parameter (95% CI) Tissue Isotope a b λ r 2 t 0.5 (d) (95% CI) WM δ 15 N (15.46, 15.99) (-4.15, -3.41) ( , ) (134, 222) WM δ 13 C (-16.52, ) (-2.41, -1.63) ( , ) (168, 532) LIV δ 15 N (14.68, 15.31) (-3.00, -1.82) ( , ) (56, 190) LIV δ 13 C (-16.56, ) (-2.35, -1.23) ( , ) (90, 850) t 0.95 (d) Tissue-specific TDF Fish at steady-state with diet δ 13 C and δ 15 N values allowed for calculation of TDF values for δ 13 C and δ 15 N in WM and LIV tissues of PBFT. Sample size for TDF calculations ranged from n=9 (LIV δ 13 C) to n=24 (LIV δ 15 N) (Table 1-3). Mass-weighted feed mean δ 13 C and δ 15 N values, hereafter reported as mean ± SD (δ 13 C: ± 0.3; δ 15 N: 13.9 ± 26

43 0.7) were higher than initial PBFT white muscle values (δ 13 C: ± 0.2; δ 15 N: 11.8 ± 0.2) and lower than mean steady-state values of δ 13 C and δ 15 N in WM and LIV (Table 1-3). TDF values for δ 13 C and δ 15 N in WM were 1.8 ± 0.3 and 1.9 ± 0.4, respectively; TDF values for δ 13 C and δ 15 N in LIV were 1.2 ± 0.3 and 1.1 ± 0.6, respectively (Table 1-3). TDF values for δ 13 C are for arithmetically lipid- extracted δ 13 C values for both consumer (PBFT) and food. Table 1-3. Table of mean δ 15 N, δ 13 C (bulk), δ 13 C (arithmetically lipid-extracted (Logan et al. 2008)), and bulk C:N ratio values of Pacific bluefin tuna (Thunnus orientalis) tissues (WM and LIV), captive feed, and calculated tissue-specific TDF values for white muscle and liver (± SD). Fish used for TDF calculations were in captivity for a time period that allowed for at least 95% isotopic turnover for each tissue and isotope (see Table 1-2). Group Isotope Tissue n Mean (SD) C:N (SD) (mass) Feed Sardine δ 13 C WM (0.5) 3.2 (0.1) δ 13 C WM (0.5) 3.2 (0.1) δ 15 N WM (0.8) 3.2 (0.1) Squid δ 13 C WM (0.2) 3.5 (0.1) δ 13 C WM (0.2) 3.5 (0.1) δ 15 N WM (0.7) 3.5 (0.1) Supplement δ 13 C Wh (0.1) 4.2 (0) δ 13 C Wh (0.0) 4.2 (0) δ 15 N Wh (0.1) 4.2 (0) Feed mean δ 13 C (0.3) δ 13 C (0.3) (weighted by mass) δ 15 N (0.7) TDF Consumer Mean SD Time in capt. PBFT δ 13 C WM (0.3) 4.9 (1.8) > 1103 d PBFT δ 13 C WM (1.8) 4.9 (1.8) > 1103 d PBFT δ 15 N WM (0.4) 4.9 (2.0) > 721 d PBFT δ 13 C LIV (0.5) 7.6 (3.4) > 701 d PBFT δ 13 C LIV (2.0) 7.6 (3.4) > 701 d PBFT δ 15 N LIV (0.6) 6.2 (2.6) > 372 d 27

44 Growth PBFT held in captivity on a controlled diet showed substantial growth in TRCC and MBA tanks, with one individual increasing in mass by a factor of ~30 (Figure 1-2). Growth of captive PBFT was linear from days, and then became exponential between days. An exponential equation best fit the overall growth data (dashed line, Figure 1-2; r 2 = 0.87). The switch from linear to exponential growth was most likely a result of moving tuna from TRCC to MBA tanks, where tank volume Figure 1-2. Relative growth (W R ) for individual Pacific bluefin tuna over time (days) in captivity. Dashed line represents exponential model fit to data (r 2 = 0.87). increased and feed ratios remained the same but quantity increased (C. Farwell, pers. comm.). Specific growth rates (k') were most variable for fish early in the experiment, ranging from to (Figure 1-3). Only three fish showed negative k' values, which may have been a result of inadequate feeding in captivity or error in initial size 28

45 measurement. Growth rates (k') were more variable in the early stages of the experiment (0 800 d), then variability decreased throughout the course of the experiment (Figure 1-3). Linear fit to k' data (dashed line, Figure 1-3) had a slope near zero (-3.0 x 10-8 ) indicating a negligible change in k' over time in captivity. Overall k' can be estimated by the y-intercept of the linear fit to k' data or mean k'; these values were the same (k' = ). Figure 1-3. Specific growth rates (k') for Pacific bluefin tuna in captivity. Growth rates were calculated from relative growth (W R ) and time in captivity (t). Dashed line represents linear fit to data. Estimates of group growth rates (y-intercept of linear fit and mean k') are the same (k' = ). Table 1-4. Parameter estimates and 95% confidence intervals for relative growth-based (W R ) exponential fit models for each tissue (WM or LIV) and isotope (δ 15 N or δ 13 C) in Pacific bluefin tuna (Thunnus orientalis). Estimated growth-based half-life (G 0.5 ) is shown for each tissue and isotope. Parameter (95% CI) Tissue Isotope a b c r 2 G 0.5 WM δ 15 N (15.33, 16.06) (-16.68, -5.84) (-1.756, ) WM δ 13 C (-15.94, (-4.623, ) ( , ) LIV δ 15 N (14.65, 15.6) LIV δ 13 C (-16.69, ) (-17.0, 1.132) (-16.1, 2.894) (-2.669, ) (-3.039, )

46 Growth-based δ 13 C and δ 15 N turnover Change in δ 13 C and δ 15 N values in white muscle and liver was well represented by growth-based models, although fits (r 2 values) were slightly lower than those from timebased models (Tables 1-2, 1-4). Relative growth-based turnover was faster in liver than in white muscle for both δ 13 C and δ 15 N values (Figure 1-4). The growth-based half-life Figure 1-4. Isotopic change with growth in two tissues in captive Pacific bluefin tuna (Thunnus orientalis). δ 15 N and δ 13 C values in Pacific bluefin tuna white muscle (WM; filled circles) and liver (LIV; open circles) are shown as a function of relative growth (W R ) after switch to captive diet. Lines represent time-based exponential model fits for WM (solid line) and LIV (thin dotted line). was shortest for liver δ 13 C (1.56) and highest for WM δ 13 C (3.09) (Table 1-4). Growth (increase in mass) necessary for 50% turnover of nitrogen in white muscle and liver was 30

47 72% and 59% respectively, and 56% and for carbon in liver. A higher gain in mass was necessary for 50% turnover of carbon in white muscle (209%) (Table 1-4). Table 1-5. Parameter estimates and 95% confidence intervals for metabolic constant (m) from time-based exponential fits to δ 15 N and δ 13 C data for Pacific bluefin tuna (Thunnus orientalis) white muscle and liver. Estimates and 95% confidence intervals of proportion of turnover due to growth (P g ) and metabolism (P m ) is shown for each tissue and isotope. Parameter Tissue Isotope k m (95% CI) P g (95% CI) P m (95% CI) WM δ 15 N (0.31, 0.51) 0.62 (0.49, 0.69) ( , ) WM δ 13 C (0.39, 0.84) 0.41 (0.16, 0.61) ( , ) LIV δ 15 N (0.11, 0.23) 0.85 (0.77, 0.89) ( , ) LIV δ 13 C (0.21, 0.67) 0.63 (0.33, 0.79) ( , ) Contributions to turnover of growth and metabolic processes Routine metabolism, as the sum of all anabolic and catabolic processes, contributes to both components of isotope turnover in tuna tissues: new tissue growth, and all other metabolic processes (MacAvoy et al. 2005, MacAvoy et al. 2006). Studies of isotopic turnover is fish often discern the effects of growth from metabolism (Buchheister and Latour 2010). Thus all metabolic processes, excluding growth, are hereafter referred to simply as metabolic processes or metabolism. Overall estimates of proportion of turnover due to growth or metabolism for all tunas varied by tissue and by isotope (Table 1-5). In liver, metabolic processes contributed more to isotope turnover than in muscle, and more to turnover of nitrogen (85%) than of carbon (63%) (Table 1-5). Metabolic processes also contributed significantly to isotope turnover in muscle, accounting for 62% of WM nitrogen turnover and 41% of WM carbon turnover. 31

48 Growth accounted for the majority of isotope turnover in only one isotope and tissue (WM carbon, 59%; Table 1-5) Comparison of captive and wild data Data from wild Pacific bluefin tuna showed similar turnover of 15 N to captive fish (Figure 1-5). Samples from large wild bluefin tuna were not available, so we were unable to assess whether wild fish of larger sizes had reached steady-state with local prey. However the largest wild fish (which had the longest estimated residency times in the CCLME) had reached δ 15 N values of in white muscle tissue, similar to captive fish that had reached steady-state in captivity (Figure 1-5). Figure 1-5. Change in 15 N with time in captive and wild Pacific bluefin tuna (Thunnus orientalis). δ 15 N values in captive (filled circles) and wild (red x s) Pacific bluefin tuna white muscle. Time (days) for wild fish represents estimated residency time in the California Current Large Marine Ecosystem, and was estimated from fish size (Bayliff et al. 1991), using the smallest sampled individual (61.6 cm) to approximate starting value for t (t = 0 days). Dashed lines show weighted mean δ 15 N values for captive food (grey) and wild prey (red). 32

49 1.5. Discussion Pacific bluefin tuna that are captured in the wild and then transported and held in captivity provide excellent subjects for validation experiments. We used archived tissue samples from Pacific bluefin tuna held in captivity for a wide range of time to design an experimental framework from which isotopic turnover rates and trophic discrimination factors can be accurately estimated. These data reveal several important aspects of isotope turnover and trophic discrimination in growing endothermic fish. White muscle and nitrogen showed more predictable turnover dynamics and better model fits than liver and carbon. The duration of time in captivity required for tissues to reach steady-state (95% turnover) with diet (fastest: LIV 15 N = 372 days; slowest: WM 13 C = 1103 days) demonstrates that isotope turnover experiments in fish may need to exceed several years to adequately represent full turnover of δ 13 C and δ 15 N values in certain tissues. Finally, these results suggest that metabolic processes may contribute more to isotopic turnover, particularly in muscle tissue, in Pacific bluefin tuna, an endothermic pelagic fish, than in other fish species Turnover in tissues Overall, our tissue-specific turnover rates were lower (i.e. tissue turnover took longer) than values reported for mammals and birds (Bearhop et al. 2002, MacAvoy et al. 2006) and some ectothermic fish (Logan and Lutcavage 2010). Body temperatures are significantly lower in bluefin tuna in comparison to birds and mammals (20-25 C for bluefin and C for mammals and birds). However, our turnover rates were similar to values reported in leopard sharks by Kim et al. (2012), in which muscle tissue δ 13 C and δ 15 N values took several hundred days to reach steady-state and study animals were large 33

50 (1-5 kg) compared to fish in most previous studies (Weidel et al. 2011). Weidel et al. (2011) found an allometric relationship between fish size and isotope turnover; thus tissues in larger fish would take longer to reflect a diet switch. We estimated a white muscle carbon turnover half-life of 184 ± 42 days in Pacific bluefin tuna based on the allometric relationship in Weidel et al. (2011). While application of large fish to this equation extrapolates far beyond the fish sizes used in the study (Weidel et al. 2011), it does indicate that fish size can greatly affect turnover rates, and may explain the relatively slow turnover times in the relatively large Pacific bluefin tuna. Allometric scaling of turnover rate with body size in white sharks, for example, led to extremely long estimates of carbon turnover time in white muscle (t 1/2 = 394 ± 42 days) (Carlisle et al. 2012). Isotopic turnover rates have also been shown to be positively correlated with metabolic rate, at least in mammals (MacAvoy et al. 2006). As regional endotherms, or heterotherms (Katz 2002), Pacific bluefin tuna have lower metabolic rates than birds and mammals (Carey et al. 1971). The larger size of the tuna in this study and the leopard sharks in Kim et al. (2012) compared to fish in other studies of isotopic turnover, along with lower metabolic rates in fish (including regionally endothermic fish (Katz 2002)) compared to birds and mammals, may provide the basis for the relatively long turnover times we observed. Further studies on tunas and other fish will help elucidate the relative importance of animal size and metabolic rate on isotopic turnover in various tissues. Turnover rates of carbon and nitrogen were higher in liver tissue than in white muscle, which is consistent with results found in most other fish (Logan et al. 2006) although some studies found no differences between these tissues (Hesslein et al. 1993). 34

51 This has generally been attributed to the higher metabolic activity of liver tissue, in which protein synthesis and degradation can be much faster than in skeletal muscle tissue (Smith 1981, Houlihan et al. 1988, de la Higuera et al. 1999, Buchheister and Latour 2010). Liver has also been shown in other studies to be much more variable in isotopic values than muscle (Pinnegar and Polunin 1999, Sweeting et al. 2005). Speculative causes of high variability in liver are differences in amino acid composition of liver versus white muscle (Pinnegar and Polunin 1999, Sweeting et al. 2005) and, as a more metabolically active tissue, liver could have more inherent variability in isotope values (Sweeting et al. 2005). Carbon turnover was slower than nitrogen turnover in both liver and white muscle tissues, though the opposite result has been found in some fish (MacAvoy et al. 2001, Buchheister and Latour 2010). Differences in proportional contribution of metabolism versus growth to turnover have been proposed as the driving force between turnover rate differences between tissues and isotopes (Buchheister and Latour 2010), with more metabolically active tissues showing higher turnover rates. Results here support this relationship, as the tissue (liver) and isotope ( 15 N) with higher proportion of turnover attributable to metabolism (P m ) (Table 1-5) both showed higher turnover rates (Table 1-2) than muscle and 13 C, respectively. Thus the different proportional impacts of metabolism or growth on tissue turnover may determine which tissues and isotopes turn over faster in a given fish species (Buchheister and Latour 2010). δ 13 C values were more variable in white muscle and liver tissues with correspondingly low correlation coefficients for exponential model fits of turnover. Since this study was not longitudinal, and rather sampled unique individuals for each data 35

52 point, individual variation could have led to the variability seen in δ 13 C values (and δ 15 N values as well). Individual variation has shown to be a potentially important factor in controlled studies of isotope discrimination and turnover (Lecomte et al. 2011). Carbon isotope values of tissues can also be confounded by variable lipid content, with higher lipid tissues resulting in lower δ 13 C values due to the low 13 C content of lipids relative to protein and carbohydrates (Post et al. 2007, Logan et al. 2008, Logan and Lutcavage 2008). Two methods that have emerged for estimating the effects of lipid content on δ 13 C values are chemical extraction and arithmetic correction based on C/N ratio, which can be used as a proxy for lipid content (Post et al. 2007, Logan et al. 2008, Logan and Lutcavage 2008). Our values were arithmetically corrected based on lipid-correction algorithms derived from Atlantic bluefin tuna, Thunnus thynnus (Logan et al. 2008). Arithmetic corrections have been well supported by several studies but lipids will likely continue to be a source of variation in δ 13 C values in any lipid-rich tissues, whether they are chemically lipid extracted or arithmetically corrected. Liver tissues had higher lipid concentrations and C:N ratios than white muscle tissue (Appendix 1) which may have contributed to the higher variability and poorer model fits for δ 13 C in liver (Figure 1-1; Table 1-2) Trophic discrimination factors (TDFs) Trophic discrimination factors (TDFs) reported here are the first for pelagic teleosts in which at least 95% turnover for both δ 13 C and δ 15 N in liver and white muscle is demonstrated, and have been fed a mixed diet (resembling natural food habits). Varela et al. (2011) report TDF values for Atlantic bluefin tuna (Thunnus thynnus) reared on a 36

53 captive diet for five months. Their Δ 15 N estimate (1.6 ) was similar to ours here (1.9 ), though the Δ 13 C value (-0.2 ) was lower (Varela et al. 2011) and suggests that PBFT will have lower δ 13 C values than their diet. However, isotopic steady-state between tunas and diet was not demonstrated in this study, and reliability of turnover rate estimates is highly dependent on tissues reaching steady-state with diet, or an asymptotic isotopic value (Martínez del Rio et al. 2009). The short rearing time (~5 months, or 150 days) in the study by Varela et al. (2011) was likely insufficient for captive tunas to reach steady-state, based on turnover times reported here. In this study, 15 N TDF for white muscle (Δ 15 N WM : 1.9 ± 0.4) fell within the lower but wide range of Δ 15 N values reported for a variety of taxa (~-1 6 ) (McCutchan et al. 2003) and the range reported in a review for WM Δ 15 N of 22 fish species ( ) (Caut et al. 2009). However Caut et al. (2009) reported an inverse relationship between Δ 15 N and δ 15 N food value and proposed empirical algorithms to calculate Diet-Dependent Discrimination Factors (DDDFs). We calculated a TDF estimate of 1.9 using the DDDF algorithm for fish WM (Caut et al. 2009), the same estimate as our experimental value of 1.9. This suggests that the high δ 15 N value of tuna feed may impact our calculated TDFs, and that our experimentally-derived Δ 15 N values correlate with the TDFs for many fish species in Caut et al. (2009). The isotopic values of prey here are consistent with the diet of wild tuna in the California Current Large Marine Ecosystem (CCLME), which feed on higher trophic levels than fish in most other turnover studies using isotopes as tracers and thus feed on organisms with generally high δ 15 N values (Pinkas et al. 1971, Madigan et al. 2012b). 37

54 Our TDF values for carbon in both white muscle and liver fit within ranges found in previous studies; Δ 13 C values (WM 1.8; LIV 1.2 ) were high relative to the most commonly referenced Δ 13 C ranges of 0 1 (Post 2002). However it has been demonstrated that these values are highly taxa-, tissue-, and diet-dependent, and our values fall well within the range reported for 41 fish studies ( ) (Caut et al. 2009). Our results show that TDF for 15 N is lower and TDF for 13 C is higher than in other taxa (Post 2002), which suggests that traditional utilizations of δ 15 N values for trophic estimations and δ 13 C values for food web sourcing may not be appropriate for PBFT. Liver TDF values were lower and TDF for liver nitrogen more highly variable, suggesting that while liver can be useful for making inferences about diet on shorter timeframes due to faster turnover, liver isotope values and TDFs should be used with caution due to their high variability. Some mixing models (e.g. MixSir (Moore and Semmens 2008)) take TDF error into account, but TDF is one of the most influential factors on mixing model results (Moore and Semmens 2008). The most useful application of the TDFs reported here will be for trophic assessments of tuna that are complementary to traditional dietary analyses, which can under-represent prey, particularly prey that are quickly digested or do not contain hard parts (Cailliet 1977). Such approaches have been put to use in the California Current Large Marine Ecosystem (CCLME) (Madigan et al. 2012b) and the Mediterranean (Cardona et al. 2012) in which analyses revealed high consumption of krill and gelatinous salps, respectively. TDFs reported here will support similar studies of tuna feeding habits, particularly using white muscle (which was least variable). Liver tissue, which turns over more rapidly, will provide more recent insight into diet. 38

55 However, based on the variability of liver isotope values reported here, we recommend the use of liver TDF values in conjunction with other tissues, particularly WM, when calculating dietary reconstructions of wild tuna. In addition, due to the long turnover times reported here, trophic studies using SIA will benefit from complementary movement data (e.g. from electronic tags) to assess whether study animals have likely been feeding on local prey baselines for sufficiently long periods to have reached isotopic steady-state with local prey resources. In species where migration patterns occur on shorter timescales than tissue turnover rates, more advanced analytical approaches may be necessary for SIA-based trophic inferences (e.g. Carlisle et al. (2012)). Finally, it is important to note that our reported Δ 13 C values are for arithmetically lipid-corrected values of δ 13 C for both PBFT and food tissues. Bulk δ 13 C values are available in Table 1-3 allowing for calculation of Δ 13 C for any combination of predator/prey δ 13 C values (i.e. Δ 13 C for bulk tissues can be calculated from Table 1-3). When applying the Δ 13 C values found here to field data, it is important that researchers use a Δ 13 C value that is based on the approach (bulk or lipid-extracted) they take to their own consumer and prey δ 13 C data PBFT growth Pacific bluefin tuna growth in captivity was generally linear from days (0.050 ± cm/day, Figure 1-2). Variation of growth rate k' was highest in shortduration fish (Figure 1-3). Sources of this variation may be related to fish density in the tanks (which varied over time) or differences in the acclimation time and feeding in the first days in the TRCC across individual fish, as time to first feeding can vary in captive 39

56 tuna (Farwell 2001). Increased growth after days (Figure 1-2) is likely due to both natural growth dynamics of PBFT (Hsu et al. 2000) and increased food rations and space availability in MBA tanks. However k' remained generally constant throughout the experiment (k' = , Figure 1-3) and most fish were near, or had reached, steady-state conditions with diet before the move to MBA tanks (~725 days, Figure 1-1). Growth-based models fit isotope turnover well (Figure 1-4), though correlation coefficients were slightly lower than for time-based models (Table 1-4). The proportion of 13 C and 15 N turnover attributed to growth (i.e. dilution) versus metabolism was estimated for both tissues. As expected, metabolism accounted for the majority of turnover in liver for both isotopes (85% for 15 N, 63% for 13 C; Table 1-5), due to the high metabolic activity of liver. Interestingly, and in contrast to other studies (Logan et al. 2006, Buchheister and Latour 2010), metabolic processes accounted for a significant proportion of isotopic turnover in white muscle for both 15 N (62%) and 13 C (41%) (Table 1-5). Growth or dilution effects dominated isotope turnover in other species, accounting for up to 100% of turnover in some fish species (Bosley et al. 2002, Buchheister and Latour 2010). High metabolic influence on isotopic turnover in PBFT here is likely due to fish size and physiology. Most laboratory studies done previously have used larval or small, rapidly growing, juvenile fish (<0.5 kg) while our fish ranged from kg (Table 1-1). Pacific bluefin tuna are endothermic fish and have higher metabolic rates than ectothermic fishes (Carey et al. 1971, Carey et al. 1984, Korsmeyer and Dewar 2001, Blank et al. 2007a, Blank et al. 2007b); thus PBFT use more energy per unit mass to maintain an elevated metabolic rate and less energy is available for growth relative to other species. High metabolic contributions to tissue turnover have been demonstrated in 40

57 other endothermic species; for example, Carleton and Martínez del Rio (2005) found high metabolic rate influenced turnover rates in endothermic birds. Endothermic physiology (Fry and Arnold 1982, Tieszen et al. 1983, Hobson and Clark 1992, Logan et al. 2006, MacNeil et al. 2006) and larger size (and subsequently lower relative growth rates) of captive PBFT than fish in other studies (Weidel et al. 2011) likely account for the larger role of metabolism in isotope turnover in captive PBFT Applications to field data The power and breadth of isotopic techniques has been demonstrated in the development and application of novel predictive and statistical tools using SIA data. Dietary mixing models (e.g. MixSir (Moore and Semmens 2008), IsoSource (Phillips and Gregg 2003) and SIAR (Parnell et al. 2010)) generate estimates of relative proportion of dietary inputs. Isoscapes (Graham et al. 2010), when used with accurate parameters, can estimate the origin and timing of migration in animals that move between isotopically discrete regions. The results here provide the necessary parameters to perform speciesspecific isotopic studies on Pacific bluefin tuna. Dietary mixing models assume that consumers are at steady-state with diet and use consumer TDF (± SD) as a model input, and some mixing models have been shown to be highly sensitive to TDF values (Phillips and Gregg 2003, Moore and Semmens 2008). To date many studies have used the across-taxa mean of 3.4 for Δ 15 N in white muscle from Post et al. (2002), which may in many cases be inappropriate (D. Post, pers. comm.). In this study both δ 13 C and δ 15 N values clearly reached steady-state conditions in both liver and white muscle (Figure 1-1) so we are able to provide with confidence 41

58 accurate values for TDF that can be used in genus- or species-specific isotope mixing models (Madigan et al. 2012b). As highly migratory species, PBFT and other tunas can benefit from SIA studies using isoscapes (Graham et al. 2010) which allow inferences of both the origin and timing of migration. Electronic tagging has greatly increased our knowledge of movements of highly migratory species (HMS), particularly in the Pacific as a result of the Tagging of Pacific Predators (TOPP) program (Block et al. 2011). Electronic tags have revealed seasonally consistent migration patterns in certain species that utilize the CCLME, such as Pacific bluefin tuna that remain in the CCLME or make trans-pacific migrations, or albacore (Thunnus alalunga) that either overwinter in the CCLME or in the sub-tropical gyre (Boustany et al. 2010, Block et al. 2011, Childers et al. 2011). White (Carcharodon carcharias) and mako (Isurus oxyrinchus) sharks make inshoreoffshore migrations, moving between highly productive ecoregions and oligotrophic areas (Boustany et al. 2002, Weng et al. 2007, Block et al. 2011, Carlisle et al. 2012). The obvious benefit to SIA versus electronic tagging is that isotopic values allow for retrospective inferences of movement and trophic ecology while electronic tagging data is prospective from the time of animal tagging to time of recapture. Thus electronic tags provide high resolution data on the movements of animals within the tagging ecoregion and often the ecoregions they migrate to, but cannot provide data to infer migratory origin or relative trophic ecology between ecoregions (Carlisle et al. 2012). Studies that utilize the retrospective data from SIA with the prospective data from electronic tags, such as Seminoff et al. (2012) in endangered leatherback sea turtles and Carlisle et al. in 42

59 white sharks (Carlisle et al. 2012), demonstrate the power of combining these approaches. Tunas such as bluefins that have complex migration patterns that may be population-specific require well-conceived experiments. PBFT may exhibit residential behavior or trans-pacific-scale movements that occur with ontogeny and may be on time scales less than the time necessary for tissue-diet steady-state conditions. Therefore tuna tissues will have tissue isotopic values that represent a mixture of their recent foraging regions. The TDF and turnover values determined here could be applied to wild bluefin to estimate their migratory history. Change in δ 15 N values of wild Pacific bluefin tuna that recently migrated from Japan to the California Current was similar to observations in captive fish here (Figure 1-5). While this approach needs further, rigorous analysis, it suggests that isotopic turnover in this study was similar to that in the wild. Thus in Pacific bluefin tuna in particular, stable isotope analysis may reveal recent migratory origin and timing (Chapter 4). Similar approaches have been applied to isotopic compositions of otoliths in Atlantic bluefin tuna (Thunnus thynnus) to discern Mediterranean from Gulf of Mexico-spawned bluefin off the eastern US coastline (Rooker et al. 2008). Such studies will prove extremely valuable as we move towards better international management of bluefin species Conclusions Our results also allow for general reliability estimates of data from certain isotopes and tissues. Our model fits demonstrate that 15 N content in white muscle, for example, turns over at a much more predictable rate that does 13 C content in liver. While 43

60 several tools that use SIA data benefit from using multiple tissues, we suggest here that at least in PBFT, white muscle may provide more reliable estimates of migratory and trophic history, and while liver tissues supply useful additional information, the high variability of liver isotope values means that interpretation should be treated with care. Overall, this long-term experiment provides new parameters for isotopic studies of bluefin tunas. It demonstrates that long term laboratory studies of other pelagic animals are necessary as we move forward using stable isotope analysis to describe the movements and ecology of these important pelagic apex predators. 44

61 Chapter 2 Stable Isotope Analysis Challenges Wasp-Waist Food Web Assumptions in an Upwelling Pelagic Ecosystem Publication: Madigan DJ, AB Carlisle, H Dewar, OE Snodgrass, SY Litvin, F Micheli, and BA Block Stable isotope analysis challenges wasp-waist food web assumptions in an upwelling pelagic food web. Scientific Reports 2:e Abstract Eastern boundary currents (EBCs) are often described as wasp-waist ecosystems in which one or few mid-level forage species support a high diversity of larger predators that are highly susceptible to fluctuations in prey biomass. The assumption of wasp-waist control has not been empirically tested in all EBC ecosystems. This study used stable isotope analysis to test the hypothesis of wasp-waist control in the southern California Current large marine ecosystem (CCLME). We analyzed prey and predator tissue for δ 13 C and δ 15 N and used Bayesian mixing models to provide estimates of CCLME trophic dynamics from Our results show high omnivory, planktivory by some predators, and a higher degree of trophic connectivity than that suggested by the waspwaist model. Based on this study period, wasp-waist models oversimplify trophic dynamics within the CCLME and potentially other EBC ecosystems. Higher trophic connectivity in the CCLME likely increases ecosystem stability and resilience to perturbations Introduction The California Current large marine ecosystem (CCLME) is one of the world s eastern boundary currents (EBCs) that undergo seasonal upwelling leading to high productivity (Sherman and Alexander 1986). The CCLME supports a large biomass of 45

62 planktivorous lower trophic level (LTL) species such as sardine, anchovy, and small squids (Cury et al. 2011), which support diverse predators such as tunas, billfish, seabirds, pinnipeds, sharks, and cetaceans (Chavez et al. 2003, PICES 2004). Large-scale electronic tagging efforts (e.g., TOPP: Tagging of Pacific Predators) have revealed the importance of the CCLME to these highly migratory predators and demonstrated a high level of residency for many highly migratory species (HMS) (Schaefer et al. 2007, Boustany et al. 2010, Block et al. 2011). In the eastern Pacific Ocean, as in most other marine systems, HMS (e.g., tunas) and LTLs (e.g., sardine) have been heavily fished and some have shown periodic population declines (Pauly et al. 1998, Bakun and Broad 2003, Chavez et al. 2003). Although the populations of many of these species declined during periods of overfishing, many have subsequently rebounded in the CCLME. Trophic dynamics may affect population fluctuations, and assessing the strength of trophic linkages is important in forecasting the potential impacts of natural and human-induced declines in prey or predator populations. In characterizing ecosystem trophic structure, it is important to understand whether dominant forcing mechanisms are bottom-up or top-down (Cury et al. 2003). The effect of predator removal from pelagic ecosystems is contentious, but recent work suggests the possibility of top-down effects of predators even in open-ocean systems (Baum and Worm 2009). Conversely, bottom-up controls also likely affect HMS feeding success and consequently, the extent of their residency in the CCLME (Brodeur and Pearcy 1992) and other upwelling ecosystems (Cury et al. 2000). The interaction between top-down and bottom up controls remains relatively poorly understood and difficult to test in productive upwelling ecosystems. Other models of ecological control 46

63 in EBCs have been proposed, including wasp-waist control as an alternative to classical bottom-up or top-down models (Rice 1995, Bakun 1996, Cury et al. 2000). In wasp-waist (WW) systems, population dynamics are suggested to be largely controlled by LTLs rather than the bottom or the top. WW ecosystems are highly productive systems that support low diversity (one or few species) but high abundance of LTLs such as sardine and anchovy (Rice 1995, Bakun 1996, Cury et al. 2000). This large prey biomass supports a high diversity of marine mammals, teleosts, elasmobranchs, and seabirds. LTLs at the wasp-waist level exert top-down control on zooplankton and bottom-up control on top predators, with environmental factors largely affecting their abundance (Cury et al. 2000, Cury et al. 2003). Ecosystem models have shown that WW upwelling systems are more vulnerable to collapse when forage fish decline due to the critical energetic links that LTLs provide between highly available zooplankton and larger predators (Shannon et al. 2000). However, recent studies have shown that in some EBCs (e.g., the northern California Current), trophic dynamics may be more complex, with predators feeding on multiple trophic levels including planktonic organisms (e.g., euphausiids) (Miller et al. 2010), increasing ecosystem stability (Gross et al. 2009). Characterizing a system as WW (or under different controls) thus requires the acquisition of diet information for predators within a system. The primary tool to identify trophic linkages has traditionally been directly through gut content analysis (GCA) of predators (Hyslop 1980). GCA is an important tool to identify dominant prey species in predator diets. However, GCA is limited to feeding data during the timeframe(s) of predator sample availability, and may overemphasize the importance of large prey or prey with hard parts, which tend to 47

64 accumulate in the stomachs of predators (Hyslop 1980). Stable isotope analysis (SIA) is a newer ecological tool to study predator diets that provides longer-term estimates of the primary prey that are incorporated into predator tissue. SIA is time-integrated, nonlethal, and significantly faster than GCA (Fry 2006), and it is particularly powerful when combined with the specific prey data GCA can provide. SIA of carbon and nitrogen isotopes, the elements most commonly used in ecological studies, measures the ratio of a heavier, rare isotope to a lighter, more common isotope ( 13 C: 12 C or δ 13 C; 15 N: 14 N or δ 15 N) expressed as parts per mille ( ) relative to a standard. Stable isotope values increase stepwise up food webs due to preferential retention of the heavier isotope in consumer tissues during metabolic processes; the subsequent difference between the isotope values of consumer and prey is the trophic discrimination factor (TDF). δ 13 C values are often used to infer different baseline sources (e.g. phytoplankton vs. macroalgae), as primary producers in discrete ecosystems may have dissimilar δ 13 C values that will change minimally through food webs (Fry 2006). In contrast, δ 15 N values have generally been used to estimate trophic level due to the higher increase of δ 15 N values with each trophic step in food webs (Post 2002, Fry 2006). The stable isotope ratios of predator tissues reflect an integrated value of prey consumed over time. If prey isotope values are sufficiently different, relative proportions of dietary inputs can be estimated from predator isotope values using Bayesian mixing models (Phillips and Gregg 2003, Moore and Semmens 2008, Parnell et al. 2010) that take uncertainty in prey values and trophic discrimination factors into account when estimating predator diets. With adequate sampling of predators, potential prey, and TDF 48

65 values of predators, SIA becomes a powerful tool to study trophic interactions to an extent that is unfeasible using GCA alone. We used SIA to test whether the trophic dynamics of the CCLME were consistent with those hypothesized by the wasp-waist model. Specifically we asked the question: do predators in the southern CCLME rely predominantly on LTLs at the WW level? Alternatively, are there inter-specific differences in predator foraging and diversity of diet? Results show the degree to which predators rely on, and exploit, certain prey groups. Thus these results have implications for management of both predator and prey species in the CCLME (Field and Francis 2006). They also suggest the underlying mechanisms that dictate trophic dynamics in the CCLME, which is crucial for understanding and predicting changes in this pelagic ecosystem over time Materials & Methods Sampling Sampling took place between 2007 and 2010 in the summer and fall months (June-October) from the long-range San Diego fishing vessel R/V Shogun in the southern region of the CCLME (28 00 N N; W W, Figure 2-1). Samples were collected from multiple species and trophic levels. Skeletal white muscle tissue was collected for fish, mantle muscle tissue for cephalopods, and crustaceans were collected whole. Predators were captured using rod and reel and muscle biopsies were taken from the dorsal musculature. Stomachs were removed from some tuna that were sampled for muscle tissue for diet studies using GCA. Intact prey items (recently consumed and not highly digested) found during GCA of tuna stomachs were used for 49

66 SIA of prey. For these specimens only internal muscle tissue, which was unexposed to digestive enzymes, was collected. Prey samples were also collected using a dip net. All samples were stored immediately at -5 C. Prior to analysis, samples were kept at -80 C for 24h and then freeze-dried for 72h. Samples were homogenized using a Wig-L-Bug (Sigma Aldrich) and analyses of δ 13 C and δ 15 N were conducted at the Stanford Stable Isotope Biogeochemistry Laboratory using a Thermo Finnigan Delta-Plus IRMS coupled Figure 2-1. Map of the study area showing sampling effort off southern California, USA and northern Baja, Mexico. Sampling occurred from April - October between 2007 and Markers at each sampling location ( ) are scaled according to number of samples taken at that location. 50

67 to a Carlo Erba NA1500 Series 2 elemental analyzer via a Thermo Finnigan Conflo II interface. Replicate reference materials of graphite NIST RM 8541 (USGS 24), acetanilide, and ammonium sulfate NIST RM 8547 (IAEA N1) were analyzed between approximately 10 samples. Shark tissues were thoroughly rinsed in DI water to extract urea. All δ 13 C values were arithmetically lipid-normalized based on mass C:N ratios using taxon- or species-specific lipid normalization algorithms reported in (Logan et al. 2008). Stable isotope ratios are reported as mean ± SD Trophic groups Organisms were placed into four trophic groups (TG2-5; TG1 represents phytoplankton, not sampled in this study) using cluster analysis (Ward s minimum variance method) of mean δ 13 C and δ 15 N values for each species. To view overlap of predators and prey in isospace (plots of δ 13 C versus δ 15 N) we plotted δ 13 C and δ 15 N values of TDF-adjusted predators and trophic groups obtained from cluster analysis. Mean δ 13 C and δ 15 N values of predators were adjusted to visualize overlap with potential prey by subtracting laboratory-derived TDF values from mean (± SD) values of δ 13 C and δ 15 N for each predator. Teleosts were corrected using TDFs of captive Pacific bluefin tuna Thunnus orientalis (Δδ 15 N = 1.85 ± 0.38, Δδ 13 C=1.83 ± 0.33; (Madigan et al. 2012c)) and sharks were corrected using TDF values for large (>100 cm) sharks Carcharias taurus and Negaprion brevirostris (Δδ 15 N =2.29±0.22, Δδ 13 C =0.90±0.33) (Hussey et al. 2010). This allowed visualization of overlap of predator species and trophic groups with their potential prey in isospace. 51

68 Table 2-1. Table of all predator and prey species sampled in this study, separated by trophic group (TG2 5). Mean (± SD) δ 13 C and δ 15 N values are for white muscle for all species except crustaceans (analyzed whole). δ 13 C values are arithmetically lipidcorrected according to Logan et al Species Common name Code Mean δ 13 C (SD) Mean δ 15 N (SD) Mean length (SD) (cm) Trophic Group 5 Isurus oxyrinchus mako shark MAKO (0.24) (0.80) (17.9) 10 Sarda chiliensis bonito BON (0.32) (0.18) 47.8 (0.6) 12 Seriola lalandi yellowtail jack YT (0.57) (0.62) 73.7 (13.0) 34 Tetrapturus audax striped marlin STM Xiphias gladius swordfish SWD (1.17) (0.80) (29.4) 21 Thunnus orientalis Pacific bluefin tuna PBFT (0.26) (0.34) 84.8 (3.1) 42 Thunnus albacares yellowfin tuna YFT (0.31) (0.77) 77.6 (9.7) 64 Dosidicus gigas jumbo squid DG (0.23) (0.52) 22.4 (4.3) 17 Loligo opalescens market squid LOL (0.65) (0.50) 4.2 (1.5) 21 Trophic Group 4 Lampris guttatus opah OPA (0.55) (0.69) 97.2 (3.7) 4 Prionace glauca blue shark BLSK (0.57) (0.64) (31.8) 9 Thunnus alalunga albacore tuna ALB (0.26) (0.79) 86.0 (8.2) 61 Auxis thazard frigate mackerel FM nd 1 Scomber japonicus Pacific mackerel PM (0.64) (0.98) 18.6 (1.9) 16 Abraliopsis spp. squid ABRL (0.49) (0.36) 1.9 (0.3) 4 Lestidiops ringens slender barracudina SL BARR (0.16) (0.34) nd 5 Onychoteuthis spp. clubhook squid ONYC (0.15) (0.34) 10.3 (1.4) 6 Trophic Group 3 Sardinops sagax sardine SARD (0.21) (0.57) 8.2 (1.5) 18 Cololabis saira saury SAUR (0.26) (0.76) 9.2 (3.1) 20 Trachurus jack mackerel symmetricus JM (0.65) (0.58) 7.9 (2.8) 27 Gonatopsis spp. gonatid squid GON (0.29) (1.25) 7.9 (1.8) 7 Sebastes juv. rockfish juveniles SEB (0.78) (0.44) 6.2 (4.0) 7 Oxyjulis señorita californica SEN (0.01) (0.04) 17.8 (0.4) 2 Melanostigma midwater pammelas eelpout EELPT (0.31) (0.32) 7.2 (1.0) 8 Magnisudis duckbill atlantica barracudina DB BARR (0.31) (0.22) 28.1 (5.7) 5 Argonauta spp. argonauta ARGO (0.37) (0.03) 1.8 (0.4) 2 Pleuroncodes pelagic red crab planipes RC (0.21) (0.69) 2.0 (0.1) 5 Myctophidae spp. myctophid MYCT (0.25) (0.17) 5.6 (1.3) 5 Trophic Group 2 Euphausidae spp. krill KRILL (0.49) (0.77) 2.2 (0.3) 14 Copepoda calanoid copepod COPE (0.15) (0.87) 0.1 (0) 25 n 52

69 Size effects We performed correlation analysis (Pearson s correlation; α = 0.05) to investigate the relationship between organism size and δ 13 C and δ 15 N values. Correlation analysis of mean size vs. mean δ 13 C and δ 15 N values were performed across predators and for individual size vs. individual δ 13 C and δ 15 N values within particular prey and predator species. All statistical analyses of isotope data were carried out using MatLab (v. 2009a) Trophic dynamics We used a Bayesian mixing model (MixSir v ) (Moore and Semmens 2008) that takes into account isotopic error by using as inputs all predator δ 13 C and δ 15 N values and mean (± SD) δ 13 C and δ 15 N values of predator TDFs and prey. We first assessed proportional prey inputs from each trophic group (TG) into individual predator diets (e.g., to what extent do yellowfin tuna feed on organisms in TG2, TG3, TG4, and TG5?). Mixing models sometimes provide multiple solutions for diet input estimates (i.e., bimodal probability distributions). Using priors based on known predator diet can help constrain mixing model estimates (Moore and Semmens 2008). We generated mixing models using uninformed priors, as well as WW priors that gave more weight to TG3 species. Uninformed priors and doubling probability of TG3 (priors = [ ]) led to bimodal solutions for a few species and TG5. Thus we assigned priors of [ ] to TG2, TG3, TG4, and TG5, respectively. This assigned equal probability of dietary contributions of TG2, TG4, and TG5, and assumes a three-fold higher likelihood of TG3 (wasp-waist species) in predator diets. This prevented bimodal solutions and made estimates of high non-tg3 diet inputs more compelling due to the weight given TG3 53

70 inputs via prior assignments. We also tested the possibility of inter-annual variation in trophic dynamics using SIA values from 2008, 2009, and 2010 for yellowfin, albacore, and bluefin tunas, three species with adequate sample size for inter-annual analyses. To estimate overall trophic flow between entire trophic groups of the southern CCLME we estimated the relative prey inputs of each TG into the TGs themselves (e.g., to what extent does TG5 feed on organisms in TG2, TG3, TG4, and within TG5?). For TG mixing model runs we used a weighted-mean (weighted by sample size) TDF based on the species composition of each TG. We used Pacific bluefin tuna TDF for teleost predators (Madigan et al. 2012c), shark TDF for sharks (Hussey et al. 2010), squid TDF (Δδ 15 N = 3.3, Δδ 13 C = 0.0) (Hobson and Cherel 2006) for cephalopods, and a TDF for small pelagic fish (Δδ 15 N = 1.88, Δδ 13 C = 1.52) (Pepin and Dower 2007) for TG3 fish. We used mean δ 13 C and δ 15 N ± SD value for each TG as prey inputs for these mixing model runs. We used priors reflecting general wasp-waist assumptions [ ] as above and performed 10 7 iterations for all mixing model runs. Proportional diet inputs are reported to the nearest percent (Table 2-2). All statistical analyses of isotope data were carried out using MatLab (v. 2009a) Results Sampling We obtained tissue samples from 30 species from the southern CCLME from (17 predator and 13 prey; Figure 2-2 and Table 2-1) and analyzed 292 individual predators and 181 individual prey for δ 13 C and δ 15 N (Table 2-1). Prey species sampled from predator stomachs indicated that predators fed on a wide range of prey, 54

71 including forage fishes (saury, sardine, jack mackerel, juvenile rockfish) mesopelagic species (myctophids, eelpouts, barracudinas), rocky-reef associated wrasses (señoritas), epipelagic crustaceans (pelagic red crabs), and cephalopods (argonauta, gonatid, onychoteuthid, market, and jumbo squids) (Table 2-1) Cluster analysis Cluster analysis resulted in separation of species into four trophic groups based on mean species δ 13 C and δ 15 N values (Figure 2-2). These four groups were labeled, based on known life history, as: zooplankton (TG2), planktivorous prey or LTLs (TG3), mesopredators (TG4), and upper trophic level predators (in this study, apex predators) (TG5). Figure 2-2. Biplot of δ 13 C and δ 15 N values (mean ± SD) for predators (caps labels, ) and prey (lowercase labels, ). Large ovals show trophic groups (TG2-5) from cluster analysis by color. Species are abbreviated as in Table 2-1. Inset shows dendrogram of cluster analysis; each node represents an individual species. 55

72 Linkage distances were relatively high between the four groups (Figure 2-2 inset), suggesting that these trophic groups had distinct isotopic values. Hereafter these species groups will be referred to as TG2, TG3, TG4, and TG5 (see Table 2-1 for species included in each trophic group). TG3 represents LTLs at the wasp-waist trophic level of WW ecosystem models (Cury et al. 2000). The predominant planktivorous prey species (TG3) showed stepwise increases in δ 13 C and δ 15 N values relative to zooplankton (TG2), followed by meso-predators (TG4; onychoteuthid squids, Pacific mackerel, albacore, frigate mackerel, opah) (Figure 2-2). Figure 2-3. Biplot of δ 13 C and δ 15 N values (mean ± SD) for TGs 2-5 ( ) and TDFcorrected δ 13 C and δ 15 N values (mean ± SD) for nine predator species ( ), numerically labeled as shown. Sample size for each species shown in parentheses. Predators are adjusted for TDFs for δ 15 N and δ 13 C according to PB TDFs from Madigan et al (PM, BON, ALB, YT, PB, YFT: Δ 15 N=1.85, Δ 13 C=1.83 ) or Hussey et al (MAKO, BLSK: Δ 15 N=4.0, Δ 13 C=0.9 ). Grey outline encloses predator and prey isospace in the southern CCLME. Inset shows relative sizes (CFL ± SD) for nine species shown. 56

73 The highest mean δ 15 N values were observed in mako sharks, yellowtail, bonito, jumbo squid, blue sharks, striped marlin, yellowfin, and bluefin tunas (TG5), though these species showed considerable range in mean δ 13 C values ( ; Table 2-1 and Figure 2-2). After TDF correction, two predator clusters were clearly discernible based on their position in isospace relative to prey inputs (Figure 2-3). Of the nine predator species of adequate sample size to be included in this analysis, the three TG4 species (meso-predators) overlapped more closely with TG2 than TG3, though the TDFcorrected mean TG4 isotope values fell between the two groups (Figure 2-3). The remaining six species, all apex predators (TG5), overlapped closely with TG3 (Figure 2-3). Both clusters contained a range of predator sizes (Figure 2-3 inset). Figure 2-4. Relationship between mean organism size and mean δ 15 N values for species sampled in this study. Line represents logarithmic fit to data (δ 15 N = *ln(size); r 2 = 0.56). Inset shows relationship between length of individual meso- and higher level predators (>25 cm) and δ 13 C ( ) and δ 15 N ( ) values. Relationship between size and δ 13 C (δ 13 C = (size) ; r 2 = ) and δ 15 N (δ 15 N = (size) 17.9; r 2 =0.0026) are not significantly different from zero (P = 0.41 and 0.31, respectively). 57

74 Size effects δ 15 N values increased rapidly with size in organisms <25 cm but there was strikingly little change with size between 25 and 250 cm (Figure 2-4). Differences in mean δ 13 C and δ 15 N values of predators did not correspond with body size (Figure 2-5). Linear fits showed a slightly negative trend of mean predator δ 13 C values (r 2 = ) and a slightly positive trend of mean predator δ 15 N values (r 2 = ) with mean predator size, though neither were statistically significant (P = 0.98, P = 0.30, respectively) (Figure 2-5). Most individual species did not show significant change in Figure 2-5. Relationship of predator size and isotope values. For nine predator species δ 13 C ( ) and δ 15 N values ( ) are shown against predator size (CFL in cm). All values are mean ± SD. Lines represent linear fits for size versus δ 13 C (----) and size versus δ 15 N ( ). Correlations were not significant at the α = 0.05 level (inset). 58

75 δ 13 C and δ 15 N with size (Figure 2-6 and Appendix 3). Exceptions were JM and YT in which δ 13 C and δ 15 N values increased with size, and PB in which δ 13 C values increased and δ 15 N values decreased with size (Figure 2-6 and Appendix 3) Mixing models Bayesian mixing models required prior assignments that gave TG3 (WW prey) threefold higher likelihood of importance [ ] in predator diets to avoid bimodal solutions. This assumed WW feeding by all TG4 and TG5 predators, based on feeding studies in the CCLME(Pinkas et al. 1971, Preti et al. 2012) and general WW ecosystem model assumptions (Cury et al. 2000). Though this assumption places high emphasis on TG3, it makes results of non-tg3 feeding (i.e., non-ww) more compelling. However, median prey input estimates were similar for most species and TGs using uninformed priors or priors giving TG3 prey twice the importance of other prey ([ ]) (Table 2-2 and Appendix 4 and 5). Furthermore, priors of [ ] were only necessary to avoid bimodal results in BON, YT, and TG5 diet assessments (Appendix 4 and 5). Mixing model results revealed three general feeding patterns for nine predator species within the two upper trophic groups (TG4 and TG5). TG4 predators exhibited a high utilization of TG2 (krill) (Pacific mackerel: 89%, albacore: 75%, and blue shark: 69%), whereas for TG5 predators there were two different patterns. There was high omnivory by Pacific bluefin and yellowfin (high inputs of TG2, TG3, and/or TG4 with no dominance of any individual TG), and high utilization of TG3 by yellowtail: 76%, 59

76 swordfish: 96%, bonito: 68%, and mako sharks: 85% (Figure 2-7A and Table 2-2). Some of these predators showed increased feeding on TG4 (YFT: 41%; PB: 17%; BON: 15%) Figure 2-6. Biplots showing relationship between body length and δ 13 C ( ) and δ 15 N ( ) values for eight southern California Current residents (SARD (S. sagax), JM (T. symmetricus), ALB (T. alalunga), PB (T. orientalis),yft (T. albacares),yt (S. lalandi), BLSK (P. glauca), SWD (X. oxyrinchus)). Scale for y-axes (δ 13 C and δ 15 N) is the same for all species. Linear fits shown for body length v. δ 15 N ( ) and δ 13 C (---) values. 60

77 Table 2-2. Estimated proportional prey inputs from Bayesian isotope mixing model (MixSir) of trophic groups (TG) to diets of nine predator species and to diets of trophic groups as a whole (TG3-5). Values reported are for 1x10 7 iterations and priors based on wasp-waist assumptions [ ], as discussed in methods. Estimated proportional prey inputs Trophic Group 2 Trophic Group 3 Trophic Group 4 Trophic Group 5 Species Code Med 95% CI Med 95% CI Med 95% CI Med 95% CI S. japonicus PM P. glauca BLSK T. alalunga ALB T. orientalis PB T. albacares YFT S. chiliensis BON S. lalandi YT X. gladius SWD I. oxyrinchus MAKO Trophic Group (TG) MAKO, YT, 5 SWD, BON, YFT, PB, STM, LOL, DG BLSK, ABRL, 4 SLB, ALB, FM, 79 OPA, PM, ONYC SARD, EELPT, JM, SEB, 3 ARGO, DBB, SAUR, SEN, MYCT, GON, RC and some showed an increased level of feeding within TG5 (PB: 9% and YT: 7%) (Figure 2-7A and Table 2-2). Inter-annual variability in diet composition was revealed by mixing model results for individual tuna species (YFT, PB, and ALB) in 2008, 2009, and 2010 (Figure 2-7B). While albacore and bluefin diets were relatively consistent across years, yellowfin showed high use of TG3 in 2008 (63%) and 2010 (85%). In 2009 yellowfin used TG3 to 61

78 a much lower degree (11%) with higher feeding on TG2 (55%) and TG4 (29%) (Figure 2-7B). Figure 2-7. Mixing model estimates of median proportion of diet input from four trophic groups for CCLME predators. (A) Estimates of proportion of TG2, 3, 4, and 5 in nine predator species. Mean predator δ 15 N values increase from left to right. Sample size is shown above each column. 95% confidence intervals for input estimates shown in Table 2-2. (B) Mixing model estimates of prey inputs from TG2, 3, 4, and 5 into tuna diets (albacore ALB, Pacific bluefin PB, and yellowfin tuna YFT) for 2008, 2009, and nd indicates insufficient data for analysis. Sample size is shown above each column. 62

79 Figure 2-8. Schematic showing isotope mixing model estimates of food flow through the southern CCLME pelagic ecosystem, indicating high omnivory and high use of TG2 and TG3 by meso- and higher level predators, respectively. Arrows indicate inputs of a trophic group to another; arrow size is proportional to median mixing model estimates of prey inputs of trophic group to others. 95% confidence intervals for input estimates shown in Table 2-3. Far right schematic shows proportional prey inputs expected under wasp-waist ecosystem dynamics. Mixing model results for entire TGs suggest exclusive zooplanktivory by prey species (TG3), zooplanktivory by some predators and high omnivory by other predators, and trophic links across multiple TGs in the southern CCLME (Figure 2-8, Table 2-2). Results also indicate that TG3 organisms fed entirely on TG2 (99%; Figure 2-8, Table 2-2). Meso- and higher trophic level predators (TG4 and TG5) fed on all trophic groups, including their own (Figure 2-8). Though TG3 prey were the most significant input to TG5 predators (57 69%), they were of less importance to TG4 predators (8 24%) which fed predominately at the zooplankton level (74 84%) (Table 2-2). 63

80 2.5. Discussion SIA data provided insight into the ecosystem dynamics, structure, and effects of predator size on foraging ecology in the southern CCLME, and Bayesian mixing model results allowed the wasp-waist model to be tested in a highly productive eastern boundary current. Our study spanned multiple years and a broad range of species. The use of SIA allowed for a more comprehensive study of trophic structure in a pelagic ecosystem than previous studies, and we provide here long-term, overall trophic dynamic in the southern CCLME over several years General patterns The relationship between δ 13 C and δ 15 N values of southern CCLME organisms was highly linear (Figure 2-2), suggesting that these species likely feed within an oceanographic ecosystem with a similar isotopic baseline (i.e. the pelagic food web of the CCLME). This supports life history and electronic tagging data showing high residency within the CCLME (Collins 1973, Collins and MacCall 1977, Bedford 1992, Holts 1992, Schaefer et al. 2007, Cartamil et al. 2010, Block et al. 2011), as high use of other marine regions with different isotopic baselines would likely lead to predator δ 13 C and δ 15 N values that deviate from the observed linear pattern. Though some of these species do make seasonal offshore migrations (Squire 1987, Hinton et al. 2005, Schaefer et al. 2007, Boustany et al. 2010, Childers et al. 2011, Schaefer et al. in press), consistency of δ 13 C and δ 15 N values with the linear system pattern in isospace indicates high residency within the southern CCLME and the overall importance of the CCLME as a foraging area for these species. 64

81 Size effects The rapid increase in δ 15 N with size between 0 25 cm (Figure 2-4) suggests this may be a critical size phase in the CCLME, during which trophic level is rapidly increasing. All species in TG3 and TG4 fell within this size range, and in the CCLME organisms less than 25 cm seem most susceptible to predation. There was no trend of δ 13 C and δ 15 N values with size but high variability in isotope values in organisms between 25 and 250 cm (Figure 2-4), the difference between a mackerel- and mako shark-sized predator. Unlike other pelagic ecosystems where organism trophic level (inferred using δ 15 N values) increased with size (Revill et al. 2009), in the southern CCLME all species greater than ~25 cm appear able to use a diverse prey base leading to variation in predator δ 15 N values. Comparison of δ 13 C and δ 15 N with mean size for multiple predators (Figure 2-5) showed no correlation with size for either isotope. Different species of similar size had different mean δ 13 C and δ 15 N values (e.g. mako and blue sharks, yellowtail and albacore had considerably different δ 15 N and δ 13 C values) (Figure 2-5). Interestingly, there was intra-specific δ 13 C and δ 15 N correlation with size for some species (Figure 2-6). The increase of δ 13 C and δ 15 N values in JM and YT suggests the possibility for ontogenetic increases in trophic level with size for these species, which has been shown in other systems (Revill et al. 2009). PB δ 15 N values decreased with size; this could be a result of prey switching or habitat use differences across the sampled size range of PB. Overall, these differences are likely linked to species-specific feeding strategies and resultant differences in prey selection; size-based 65

82 differences in feeding strategies have been observed in other marine systems (Scharf et al. 2000) Predator groupings The two distinct predator groups in isospace (Figure 2-3) suggest two feeding strategies: foraging on planktonic organisms by some TG4 species (PM, ALB, and BLSK) or feeding on TG3 and higher trophic level fish and squids such as pacific and frigate mackerels, barracudinas, and market and jumbo squids by some TG5 predators (PB, MAKO, YFT, SWD, BON, and YT). These patterns are supported by mixing model results, which show high zooplanktivory by PM, ALB, and BLSK, omnivory in PB and YFT, and high inputs of TG3 to diets of SWD, YT, BON, and MAKO (Figure 2-7A). Because all species were sampled in the southern CCLME over the same timeframe, it is unlikely that these differences are a result of differences in prey availability, but rather due to differences in foraging strategies and physiological capabilities. These predators are known to have different thermal physiologies and diving behavior which likely influences their foraging capacity. PB, ALB, YFT, SWD, and MAKO all have varying degrees of regional endothermy (Carey et al. 1971, Block et al. 2001, Marcinek et al. 2001, Schaefer et al. 2007, Boustany et al. 2010), while the other predator species in this study are ectothermic. Our results support studies that indicate that predator physiology and behavior lead to specialization on particular prey in particular pelagic habitats, such as epipelagic TG3 prey for TG5 predators yellowfin, bonito, and yellowtail (Baxter 1960, Pinkas et al. 1971, Potier et al. 2004) and deep scattering layer (DSL) organisms by TG4 predators blue shark and albacore (Carey et al. 1990, Bertrand et al. 2002). 66

83 Mixing models: individual species Mixing model results provide new insight on the relative importance of particular prey species. For example, Pacific mackerel, albacore, and juvenile blue sharks are known to feed on plankton (particularly euphausiids) but also on squid and forage fishes (Fitch 1956, Pinkas et al. 1971, Glaser 2010, Preti et al. 2012). SIA integrates diet over longer time frames than GCA can often represent, and our results suggest that TG2 species account for more of the diet of TG4 organisms than GCA studies have indicated. These may be important prey in winter months in the CCLME, when TG3 organisms are less available and GCA data is scarce (Pinkas et al. 1971, Glaser 2010). TG2 prey may also be digested quickly and thus under-represented in GCA analyses; a recent study showed extensive consumption of salps, another zooplankton resource, by large predators in the Mediterranean pelagic ecosystem using SIA (Cardona et al. 2012). SIA has the advantage of integrating long-term feeding habits into a single isotopic value for each predator sampled. Many GCA studies rely on opportunistically sampled, line-caught fish, which limits their results to periods when fish are available and actively feeding. These studies are also inherently restricted temporally and spatially. SIA results here likely capture a more comprehensive estimate of predator diets. Inter-annual comparisons of mixing model results for yellowfin, albacore, and bluefin tunas suggest that trophic dynamics in the CCLME may shift annually, at least for tuna species during the period of this study (Figure 2-7B). SIA values reflect previous foraging, and tunas of this size range take over a year to reach steady-state with diet (Madigan et al. 2012c). Therefore, mixing model results for tuna δ 13 C and δ 15 N values 67

84 for a certain year should roughly reflect feeding habits of the previous year. Mixing model results for YFT in 2009 (Figure 2-7B) suggest potentially higher TG4 inputs (e.g., squid), and indeed squid dominated the diets of CCLME tuna in 2008 (Snodgrass et al. in prep). YFT 2010 diet estimates (Figure 2-7B) reflect higher TG3 inputs, and forage fishes were more prevalent in tuna diets in the CCLME in 2009 (Snodgrass et al. in prep). Thus our results for tuna mirror feeding patterns observed using GCA, and these interannual differences highlight the ability of these predators to change their feeding dynamics in response to changing prey conditions. The magnitude of inter-annual differences between the tuna species may also indicate differences in plasticity of the foraging strategies of these predators in the face of varying prey availability. PB and ALB, both highly endothermic, showed the least inter-annual variation while the less endothermic YFT varied greatly between 2008, 2009, and It is possible that YFT, being more restricted both latitudinally and vertically within the CCLME due to their narrower thermal niche (Block et al. 2011), are forced to alter their foraging in response to changes in epipelagic prey availability. PB and ALB would be more capable of pursuing specific prey (e.g., sardine or DSL organisms) into colder or deeper waters due to their endothermic specialization Mixing models: overall trophic dynamics Isotope mixing models also provided estimates of trophic flow between entire trophic groups for the southern CCLME. Our results showed that omnivory increased with trophic level, with the highest trophic group (TG5) feeding on all other TGs including species within TG5. TG3 organisms dominated the diet input estimates of TG5 68

85 predators (63%), and predominant feeding on schooling fishes is supported by dietary studies in the CCLME (Pinkas et al. 1971). The relatively high inputs of TG5 in bluefin, yellowtail, and mako sharks diets (9%, 7%, and 4%) are most likely a result of feeding on TG5 squid (market and jumbo squids) with high δ 15 N values; feeding studies have shown high consumption of market squid by bluefin and yellowtail on certain occasions and all species have been reported to feed on jumbo squid to various extents (Baxter 1960, Pinkas et al. 1971, Preti et al. 2012). Meso-predators in the TG4 group, some of which are often considered large, apex predators (e.g., opah, blue sharks, and albacore) fed largely on TG2 (79%). This suggests a surprising level of zooplanktivory by TG4 as a whole. It suggests that rather than relying on TG3 organisms to transfer energy from the zooplankton level, these large predators are able to directly utilize this often abundant resource. TG3 were of less importance to TG4 (16%) and TG4 and TG5 even less so (< 3%, Table 2-2) CCLME: Wasp-waist control? SIA results of a pelagic ecosystem under wasp-waist control would meet three basic criteria, based on general characteristics of WW systems (Rice 1995, Cury et al. 2000). First, the prey base would be dominated by one or a few planktivorous organisms or LTLs (here, TG3). Second, most or all predators would be expected to group together isotopically, as they would all feed extensively on this homogeneous prey base. Finally, isotopic mixing models would show that individual predators and higher trophic groups as a whole feed mainly on the TG3 level. Our study allowed for evaluation each of these three criteria. 69

86 The prey base in the southern CCLME from was not dominated by one or a few species; rather, field sampling and sampling of predator stomachs revealed a high diversity of TG3 prey (Table 2-1). This result differs from previous studies in the CCLME, when certain TG3 prey such as anchovy dominated the diets of teleost predators, including albacore, Pacific bluefin tuna, and bonito (Pinkas et al. 1971). Thus our results did not meet criterion 1 for WW control over the course of this study. Results also reveal that diverse prey are available if WW species are at lower abundances, leading to higher resilience of the CCLME food web. Predators did not group together isotopically as they would if all fed predominantly on WW prey; cluster analysis revealed two distinct predator groups (Figure 2-2). Furthermore, once, corrected for TDF, it became clear that different foraging strategies existed for different predators, even predators within the same TG, which clustered together in isospace (Figure 2-3). The high variability in predator δ 13 C and δ 15 N values (Figure 2-4 inset) suggests feeding on a wide range of prey, in contrast with criterion 2 for WW control. Finally, the quantitative SIA results of Bayesian mixing models did not reflect expected feeding patterns by individual predators or by trophic groups as a whole. Some predators fed extensively on TG3 (Figure 2-7A), but for others, TG3 accounted for a minority of prey inputs. Additionally, while TG3 was important (63%) to the highest trophic group (TG5), it did not comprise the majority of prey inputs for meso- and apex predators as a whole (Figure 2-8 and Table 2-2). The reliance of TG4 on zooplankton prey (79%) and feeding of TG5 on groups other than TG3 (37%) results in a much more complex, inter-connected food web than that expected under WW conditions (Figure 2-70

87 8). Thus our results contrast with all three expected criteria for SIA results in a WW ecosystem. Non-WW conditions in the CCLME contrast with other studies of EBC systems, which suggested WW control in the Benguela, Guinea, and Humboldt currents (Cury et al. 2000). This observed difference has several implications. One is that the southern CCLME, and potentially EBC systems in general, cannot be considered WW systems a priori, but rather must be examined over multiple years and different oceanographic conditions to ascertain trophic relationships. The highest trophic levels may heavily exploit WW prey when they are available, but results here suggest the capacity to forage on other organisms depending on readily available prey species. Non-WW ecosystem structure would increase system stability, as there is a positive relationship between ecosystem complexity and ecosystem stability (Gross et al. 2009). Adaptive food choice, leading to apex predators feeding on a diverse prey base and species at intermediate trophic levels being fed upon by multiple predator species, also increases food web stability (Gross et al. 2009) and has been shown to maintain ecosystem biodiversity (Bakun and Broad 2003, Kondoh 2003). This suggests that the southern CCLME pelagic ecosystem may maintain stability and biodiversity via the omnivory and diversity of foraging strategies of predators demonstrated here. Taken together these features of the CCLME ecosystem potentially explain the high resilience of its pelagic fish populations in the face of large scale oceanographic shifts such as Pacific Decadal Oscillations (PDOs) or El Niño Southern Oscillations (ENSO). We demonstrate that predators possess flexibility in prey selectivity which may facilitate switching between prey resources or enable exploitation of loopholes in prey 71

88 availability(bakun and Broad 2003). However, less energetic resources, or junk food in marine ecosystems, may only provide adequate sustenance and subsequent population stability for limited timeframes (Österblom et al. 2008). In the southern CCLME, this timeframe may be long enough for energetically rich prey to rebound and sustain teleost predators, as most studies demonstrating population declines in predators due to lack in prey quantity or quality have been on marine mammals or seabirds (Österblom et al. 2008, Bakun et al. 2009, Cury et al. 2011, Smith et al. 2011). Numerous compensatory mechanisms (e.g., deep-diving) may dampen or eliminate expected direct consequences of prey depletion for teleosts compared to seabirds, leading to their continual success and presence in the southern CCLME. The interaction of predator foraging plasticity and the availability of abundant and diverse prey at different trophic levels in the CCLME may underlie the high residency and consistent predator presence in this pelagic ecosystem Assumptions and caveats There are several assumptions implicit to our approach and to SIA in general. Organism isotope values vary over space and time, and we attempted to sample predator species throughout their residency period in the study area. However, as in all SIA studies, we were unlikely to capture all sources of isotopic variability. Electronic tagging has shown that many of these animals move not only north and south within the CCLME, but also offshore in seasonal patterns (Block et al. 2011). Brief migrations by some species to isotopically different areas may have slightly affected isotopic values, though not enough for values to clearly discern migrants from the system. The possibility that brief migrations may slightly alter the isotope composition of migratory species, and thus affect trophic inferences, must be taken into account when interpreting SIA results. 72

89 Mixing models are sensitive to TDF and prey values; thus accurate values of these parameters are important (Moore and Semmens 2008). We used experimentally derived TDF values from controlled studies on captive Pacific bluefin tuna (Madigan et al. 2012c) and two large shark species (Hussey et al. 2010). We assumed that Pacific bluefin TDF values were appropriate for teleosts and the TDFs from large sharks (Hussey et al. 2010) were appropriate for the shark species sampled here. Our TDF values are the most appropriate available values based on the taxonomy and size of the experimental animals and the predators to which they were applied, and are more appropriate than the mean TDF derived from several taxa in Post 2002 (Δδ 15 N = 3.4 ± 1, Δδ 13 C = 0.4 ± 1.4 ) that has been used in numerous studies. However, ecosystem-wide SIA studies will no doubt benefit from more lab-based studies on species-specific dynamics of isotopic fractionation relative to diet. Finally, it should be noted that the CCLME supports predator species and size ranges not included in this study. Seabirds and marine mammals make extensive use of the CCLME (Block et al. 2011), and seabirds in particular have been shown to be dependent upon epipelagic, TG3 forage fish due to diving limitations (Cury et al. 2011). Additionally, larger individuals of certain species, such as mako and blue sharks, are known to feed on higher trophic level prey in the CCLME, including large teleosts and marine mammals (Preti et al. 2012). Inclusion of the full size range of all species may alter TG composition and change proportional inputs to different TGs based on the foraging strategies of these animals. Thus our results can be generalized only to the teleosts and elasmobranch predators of the size ranges included in our analyses. 73

90 2.6. Conclusions Overall this study suggests that prey from several trophic groups are important to multiple predators and trophic groups in the southern CCLME. Forage base in the CCLME is constantly shifting due to changes in oceanographic conditions and fishing pressures (Shannon et al. 2000, Chavez et al. 2003, Cury et al. 2011, Smith et al. 2011). While the CCLME is utilized by predators for its richness of prey (Block et al. 2011), several oceanographic parameters likely have impacts on prey availability, predator foraging, and thus predator fitness. Oxygen minimum layer depth affects DSL composition and the ability of predators to forage on DSL organisms (Prince and Goodyear 2006), upwelling and productivity provide bottom-up controls on TG3 prey (Ware and Thomson 2005), and variations in ocean temperature alter the availability of many of the prey sampled here (Francis et al. 1998, Chavez et al. 2003). In a changing ocean, over short (ENSO events) and long (climate change) timescales, long-term studies using SIA could reveal shifts in predator diets and indicate how and to what extent large, pelagic predators in the CCLME alter their foraging strategies in different ocean conditions. Our results here suggest that predator feeding varies in the southern CCLME, lending stability to this important upwelling pelagic ecosystem. 74

91 Chapter 3 Fukushima-Derived Radiocesium: a New Tracer for the Movements of Pacific Bluefin Tuna Publication: Madigan DJ, Z Baumann, and NS Fisher Pacific bluefin tuna transport Fukushima-derived radionuclides from Japan to California. PNAS 109: Abstract The Fukushima Dai-ichi release of radionuclides into ocean waters caused significant local and global concern regarding the spread of radioactive material. We report unequivocal evidence that Pacific bluefin tuna, Thunnus orientalis, transported Fukushima-derived radionuclides across the entire North Pacific Ocean. We measured gamma-emitting radionuclides in California-caught tunas and found 134 Cs (3.8 ± 1.4 Bq kg -1 ) and elevated 137 Cs (5.9 ± 1.4 Bq kg -1 ) in fifteen Pacific bluefin tuna sampled in August We found no 134 Cs and background concentrations (~1 Bq kg -1 ) of 137 Cs in pre-fukushima bluefin and post-fukushima yellowfin tunas, ruling out elevated radiocesium uptake prior to 2011 or in California waters post-fukushima. These findings indicate that Pacific bluefin tuna can rapidly transport radionuclides from a point source in Japan to distant ecoregions, and demonstrate the importance of migratory animals as transport vectors of radionuclides. Other large, highly migratory marine animals make extensive use of waters around Japan, and these animals may also be transport vectors of Fukushima-derived radionuclides to distant regions of the North and South Pacific Oceans. These results reveal a new tool to trace migration origin (using the presence of 134 Cs) and migration timing (using 134 Cs: 137 Cs ratios) in highly migratory marine species in the Pacific Ocean. 75

92 3.2. Introduction The infrequency of nuclear accidents coupled with potentially wide-ranging effects on ecosystems and human health make the dynamics and risks of radionuclide discharge into the environment a relatively poorly understood but highly important area of research (Buesseler et al. 2011, Garnier-Laplace et al. 2011, Masson et al. 2011, Buesseler et al. 2012). On March 11, 2011 an earthquake and subsequent tsunami flooded the Fukushima Dai-ichi nuclear power plants in Japan and led to the release of radionuclides directly into the ocean exceeding that from any previous accident (Buesseler et al. 2011), with peak ocean concentrations on April 6, 2011 of 68 MBq m -3 (Buesseler et al. 2011) and an estimated total release of up to 22 x Bq (Buesseler et al. 2012) (1 Bq = 1 disintegration sec -1 ). The dominant long-lived gamma-emitting radionuclides 134 Cesium (t 1/2 = 2.1 yrs) and 137 Cs (t 1/2 = 30 yrs) were released at a ratio of about 1 (0.99 ± 0.03) (Buesseler et al. 2011). After considerable dilution 2-3 months after maximum discharge, surface concentrations still exceeded prior concentrations by up to 10,000-fold in coastal waters (Buesseler et al. 2011) and up to 1,000-fold over a 150,000 km 2 area of the Pacific up to 600 km east of Japan (Buesseler et al. 2012). Prior to the Fukushima discharge, low concentrations (1.5 mbq L -1 ) of the long-lived 137 Cs (fallout from weapons testing) were detectable in Japanese waters (Buesseler et al. 2011), whereas the shorter-lived 134 Cs was undetectable in Pacific surface waters and biota. The Pacific bluefin tuna, Thunnus orientalis, (PBFT) is a highly migratory fish that inhabits the western and eastern North Pacific Ocean at various life stages (Bayliff 1994) (Figure 1A). Mature PBFT spawn in the western Pacific, and some juveniles remain in Japanese waters while others migrate eastward to the California Current Large 76

93 Marine Ecosystem (CCLME) (Figure 1A), with most migrating late in their first year or early in their second (Bayliff 1994). Thus all bluefin between years 1-2 (here, 2 yr old PBFT) caught during summer in the eastern Pacific must have migrated from the western Pacific within several months of capture. Waters north of the Kuroshio Current (Figure 1A) showed high radionuclide concentrations in spring 2011 (Buesseler et al. 2011), and juveniles make extensive use of this region before their eastward migration to the CCLME (Kitagawa et al. 2009). We tested the possibility that juvenile PBFT served as biological vectors of radionuclides between two distant ecoregions: the waters off Japan and the CCLME. We analyzed 2 yr old PBFT caught off San Diego, CA in August 2011, known from size to be recent Japan migrants, for the presence of Fukushima-derived radionuclides. Since Cs accumulates in the muscle tissue of fish (Young et al. 1975) we analyzed the white muscle tissue of PBFT in 2011 for concentrations of 134 Cs, 137 Cs, and various naturally occurring gamma-emitting radionuclides. To rule out non-fukushima sources of radiocesium in fish muscle, we also measured radionuclide concentrations in PBFT collected in California waters before the Fukushima discharge (2008) and in yellowfin tuna, T. albacares (YFT; August 2011), in the CCLME where they are highly residential (Schaefer et al. 2007, Block et al. 2011) Materials & Methods Radioanalysis Tuna tissue samples were collected from recreational anglers in San Diego, California, USA. Angler-approximated capture date and fish size (CFL in cm) was 77

94 recorded. Approximately 30 g dry weight (29.4 ± 7.8 g) of white muscle tissue was collected from the hypaxial musculature below the first dorsal fin of each fish. All sampled fish were caught in US waters in the tuna fishing grounds off San Diego, CA. Samples were kept on dry ice (-55 C) and shipped to Stony Brook for radioanalysis. Muscle samples were freeze-dried and then ground with mortar and pestle. Pulverized tissue was placed into 4 oz Nalgene straight-side clear jars. Prior to radioanalysis all samples were stored at 60 C to avoid rehydration. We used a low energy germanium detector (LEGe; Canberra, Model GLP 3830 with a 3800 mm 2 active area). Sample counting times were adjusted to allow propagated counting errors of <10% for 137 Cs (662 kev), 134 Cs (605 kev) and 40 K (1460 kev), when possible. Genie 2000 software was used to analyze the peaks in the energy spectrum. Most post-fukushima PBFT samples were counted for 2 days but 2008 PBFT samples and 2011 YFT samples were counted for up to 5 days due to lower radioactivity. The lower detection limits were 0.5, 0.2 and 4 Bq kg -1 for 134 Cs, 137 Cs and 40 K, respectively. Naturally occurring 212 Pb (239 kev), 7 Be (478 kev), and 211 Bi (350 kev) were also detected at trace levels in tuna samples. Counting geometry was taken into consideration, and samples were calibrated using known quantities of 75 Se, 137 Cs and 152 Eu emitting over a broad energy spectrum (265 kev, 662 kev and 1408 kev, respectively). We also compared our counts of 137 Cs and 40 K with those in a certified IAEA fish standard (standard 414), consisting of freeze-dried fish muscle from the Irish and North Seas (Pham et al. 2006). The detection limits for each individual radioisotope were calculated for each individual sample of fish muscle using the well-known blank method (Currie 1968). 78

95 134 Cs and 137 Cs concentrations of post-fukushima PBFT and YFT samples were decay-corrected to August 25 th, 2011, which was the angler-estimated catch date for all fish. 134 Cs and 137 Cs concentrations in PBFT collected in 2008 were decay-corrected to the capture date of August 25 th, Statistical analysis Spearman s rho (two-tailed) at confidence interval of 95% (α = 0.05) was used to assess correlation between 2011 PBFT length and cesium concentrations. Spearman s rank correlation is non-parametric (does not assume data normality), not highly influenced by outliers, and gives an estimate of monotonic correlation between two variables even if the relationship is not linear. Spearman s correlation coefficient r s falls between -1 and 1, and gives direction and strength of correlation. P-values are reported with α = Analysis was performed using MatLab (Version 7.1) Back-calculations for 2011 PBFT We calculated 134 Cs and 137 Cs concentrations in 2011 PBFT for various times prior to capture in California (0, 30, 60, 90, 120 days), accounting for background levels of 137 Cs, decreases in tissue concentrations due to growth dilution, and efflux rates of radiocesium out of the fish during their migration across the Pacific. We first accounted for the background 137 Cs in tuna muscle (1.0 Bq kg -1 ) by subtracting 1.0 from total 137 Cs values. We then accounted for the radioactive decay of Cs isotopes, important only for the shorter-lived 134 Cs (t 1/2 = 2.1 years). Fish growth between departure from Japan and capture in August would dilute the original 79

96 radiocesium concentrations and add new muscle mass with assimilated background 137 Cs. We assumed a growth rate of mm day -1 for fish >56 cm SL (Bayliff et al. 1991). From standard length (SL) we estimated wet body mass (m wet ) in wet kg: m wet = SL x 1.41 x 10-5 (Itoh 2001) 3-1 and wet mass converted to dry mass: m dry = m wet x (Young et al. 1996) 3-2 The dry weights are shown in Tables 3-1 to 3-4. We assumed a constant pool of 137 Cs in fish muscle tissue due to observed levels in pre-fukushima fish (1.0 Bq kg Cs). We calculated the pool of background (not Fukushima-derived) 137 Cs in the muscle of each fish ( 137 Cs bgd,capture ) at the time of capture: 137 Cs bgd,capture = m capture x 1.0 Bq kg and subtracted this value from total measured 137 Cs values at the time of capture. To address growth dilution of the Cs concentrations in muscle, we calculated fish body mass, m t (0 120 days prior to catch) from standard lengths and converted to dry mass. For Pacific bluefin: SL t = SL capture - (t x cm day -1 ) (Bayliff et al. 1991)

97 where SL capture is length at time of capture, estimated from measured CFL (cm), for t = [0, 30, 60, 90, or 120] days. We then calculated m t from SL t : m t = 1.41 x 10-5 x SL t (Itoh 2001) 3-5 We assumed no uptake of Fukushima-derived Cs into fish muscle between departure from Japanese waters and capture off San Diego. We assumed total load of Fukushima-derived Cs in PBFT (Cs F ): Cs F = total measured 134 Cs + total measured 137 Cs Cs bgd,capture 3-6 and divided Cs F by the calculated body mass at days prior to capture. Estimated 134 Cs and 137 Cs concentrations in fish muscle (i.e., [ 134 Cs] and [ 137 Cs]) increased with each regressive time step due to this growth dilution (Table 3-4). To account for the metabolic efflux of assimilated cesium out of fish we used an experimentally-derived marine fish efflux rate constant (k) of d -1 (Mathews and Fisher 2009). Using this value we used an exponential decay model to determine Cs Ft prior to capture because assimilated metals are lost from marine animals following an exponential function (Wang and Fisher 1999): [ 134 Cs] t = [ 134 Cs] capture x e kt 3-7a 81

98 [ 137 Cs] t = ([ 137 Cs] capture -[ 137 Cs] bgd,capture ) x e kt 3-7b where t = time before capture in CA (0, 30, 60, 90, or 120 days), [Cs] capture is the measured Cs concentration at day of capture, and [Cs] t is the concentration of 134 Cs or 137 Cs back-calculated for time prior to capture t. Table 3-1. Measured concentrations of 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K for pre-fukushima bluefin (PBFT 2008) and post-fukushima yellowfin tunas (YFT 2011) caught in California waters. Estimated concentrations of 134 Cs and 137 Cs are for 5 individual fish for each species. Reported concentrations of both Cs radioisotopes are decay-corrected to date of capture. PBFT 2008 YFT 2011 Body Individual SL* Age Cs Cs K mass fish cm kg dry years Bq kg -1 dry < Median Mean SD Median Mean SD * Estimated from CFL: PBFT (Farwell 2011) YFT (Scida et al. 2001); Estimated from SL (Wild 1986, Itoh 2001) Estimated from SL (Bayliff et al. 1991, Wild 1994) 82

99 Table 3-2. Measured 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K for post- Fukushima bluefin (PBFT 2011), pre-fukushima bluefin (PBFT 2008), and post- Fukushima yellowfin tuna (YFT 2011) caught in California waters. SL* Body mass Age 134 Cs Radionuclide concentrations 137 Cs 40 K 134 Cs: 137 Cs Cs cm kg dry years Bq kg -1 Bq kg -1 PBFT 2011 n=15 PBFT 2008 n=5 Median Mean SD Median Mean SD YFT 2011 n=5 Median Mean SD *Estimated from CFL (PBFT (Farwell 2011) and YFT (Scida et al. 2001)) Estimated from SL (Wild 1986, Itoh 2001) Estimated from SL (Bayliff et al. 1991, Wild 1994). All radionuclide concentrations are in Bq kg -1 dry mass Estimates of radiocesium transport to CCLME We estimated radiocesium transport to the CCLME by PBFT using catch data as a proxy for PBFT biomass in the CCLME. Catch data from (IATTC 2010) was converted to muscle biomass. We then calculated values of transported radiocesium: muscle biomass x dry wt conv. factor (0.244 (Young et al. 1996)) x mean [ Cs kg -1 ]

100 to generate a range of values for transported radiocesium, assuming catch in 2011 fell within the range of catch from Estimated transport = 3 to Bq. Figure 3-1. (A) Map of the northern Pacific ocean showing simplified movement patterns for juvenile Pacific bluefin tuna (PBFT; blue arrows) from Japan to the California Current Large Marine Ecosystem (CCLME) and juvenile yellowfin tuna (YFT, yellow arrows) in the CCLME. Kuroshio Current (grey arrow east of Japan) and CCLME (grey region west of N. America) are shown. Pie charts show mean concentrations of 134 Cs (red) and 137 Cs (dark grey) in seawater (Bq m 3 ) (Buesseler et al. 2011) and muscle tissue (Bq kg -1 ) in PBFT after Fukushima, PBFT before Fukushima, and YFT after Fukushima. Pie charts for fish sized to scale of total radiocesium concentrations. Black arrows show uptake (solid arrows) and efflux (dotted arrows) of radiocesium in different ocean regions (arrow thickness scaled for relative efflux and uptake rates). * 134 Cs efflux applies only to 2011 PBFT. (B) Simplified migration patterns of some highly migratory species in the Pacific that inhabit waters around Japan and make subsequent long distance migrations to distant ecoregions including Kamchatka, the Aleutian Islands, North America, South America and New Zealand. Migration patterns are shown for salmon sharks (Nagasawa 1998) (short dashed line), sooty shearwaters (Shaffer et al. 2006) (long dashed line), Pacific bluefin tuna (Kitagawa et al. 2009) (solid lines), and loggerhead turtles (Bowen et al. 1995) (dotted line). 84

101 3.4. Results Radiocesium in PBFT All fifteen PBFT collected in 2011 contained 134 Cs (3.8 ± 1.4 Bq kg -1 dry wt) and 137 Cs (5.9 ±1.4 Bq kg -1 ) in white muscle tissue (Tables 3-1 and 3-2 and Figure 3-1A). At the time of capture, total Cs concentrations were about 10 times higher in 2011 PBFT than in PBFT from previous years (Table 3-2). Table 3-3. Measured concentrations of naturally occurring radionuclides 7 Be, 211 Bi, and 212 Pb and for n=15 post-fukushima Pacific bluefin tuna (PBFT 2011) caught in California waters. Note that units (mbq kg -1 ) are 3 orders of magnitude less than those for 134 Cs, 137 Cs, and 40 K. nd = not determined. PBFT 2011 SL (cm)* Body mass (kg dry) Age (years) SD *Estimated from CFL (Farwell 2011) Estimated from SL (Itoh 2001) Estimated from SL (Bayliff et al. 1991, Itoh 2001) 7 Be 211 Bi 212 Pb Total mbq kg -1 mbq kg nd 2.5 nd < < < < < < < < Median Mean

102 In contrast, 2008 PBFT and 2011 YFT had no measurable 134 Cs and consistent, much lower 137 Cs concentrations (consistent with background concentrations from fallout) than the 2011 PBFT (Table 3-1 and Figure 3-1A). Table 3-4. Measured concentrations of 134 Cs, 137 Cs, and the naturally occurring radionuclide 40 K and back-calculated concentrations of 134 Cs and 137 Cs for individual post-fukushima bluefin (PBFT 2011) caught in California waters. Estimated concentrations of 134 Cs and 137 Cs for individual fish (n=15) are shown for a range of days (0, 30, 60, 90, and 120) before capture for post-fukushima bluefin, taking into account background levels of 137 Cs, radiocesium efflux during transit, growth dilution, and radioactive decay. PBFT 2011 SL Body mass Age 134 C s 137 Cs Measured* Cs Calculated 0 d 30 d 60 d 90 d 120 d 40 K 134 Cs: 137 Cs 134 Cs 137 Cs 134 Cs 137 Cs C Cs 134 Cs 137 Cs 134 Cs 137 Cs s cm kg dry years Bq kg -1 dry Bq kg -1 dry Med Mean SD *Decay-corrected to August 25 th, 2011 (catch date) Estimated from CFL (Farwell 2011) Estimated from SL (Bayliff et al. 1991, Itoh 2001) 86

103 Naturally-occurring and trace radionuclides Mean concentrations of the naturally occurring gamma-emitting 40 K in the 2011 PBFT were 329 ± 46 Bq kg -1 (Table 3-1). Other naturally occurring gamma-emitting radionuclides ( 7 Be, 211 Bi, and 212 Pb) were detectable at extremely low concentrations (Table 3-3), approximately three orders of magnitude below measured radiocesium concentrations PBFT harvest and total radiocesium transport to the CCLME Pacific bluefin tuna are harvested annually in the EPO at mt (IATTC 2010) (Table 3-5) for human consumption ( ). If the mean value of Figure 3-2. Measured and back-calculated values of radiocesium concentrations in muscle of post-fukushima Pacific bluefin tuna Thunnus orientalis (n=15). Mean concentrations of 134 Cs (red triangles) or 137 Cs (gray squares) shown on left y-axis. Error bars represent 1 standard deviation. Ratios of 134 Cs: 137 Cs for each individual fish (empty circles) shown with scale on right y-axis. Dotted line represents 1:1 ratio of 134 Cs: 137 Cs, the ratio expected in tuna muscle while in waters off Japan contaminated with 134 Cs: 137 Cs ratio of 1.0. *Corrected for background levels of 137 Cs. 87

104 Table 3-5. Pacific bluefin tuna, Thunnus orientalis, catch data from in the Eastern Pacific Ocean (EPO)(IATTC 2010) and total harvested muscle biomass in the EPO. Year Catch ( 10 3 mt) Muscle biomass ( 10 6 kg)* Median Mean SD *Catch x 0.71 (ratio of muscle tissue to total body Mass (Deguara et al. 2010)) radiocesium observed in this dataset is applied to catch in the EPO, total estimated transport of Cs by Pacific bluefin tuna in 2011 is 3 to Bq Estimates of Cs concentrations in PBFT in Japan 2011 PBFT 134 Cs and 137 Cs concentrations were less than they would have been in Japanese waters due to growth, radioactive decay and efflux of cesium. We estimated that PBFT in Japan had 2 to 13 times higher radiocesium concentrations (30 to 120 days before capture, respectively) than concentrations measured at time of capture in California (Figure 3-2 and Table 3-4). There was a negative trend between animal size 88

105 and 137 Cs and 134 Cs concentrations, though the correlation was not significant (Spearman s rho; Figure 3-3). Figure 3-3. Relationship of standard length (cm) and 134 Cs and 137 Cs concentrations in white muscle tissue in Pacific bluefin tuna, Thunnus orientalis, sampled in August Spearman s rank correlation was performed and there was no significant relationship between Cs concentrations and size ( 134 Cs: n=15, df = 13, r s = , P=0.17; 137 Cs: n=15, df=13, r s = , P=0.07) Discussion Transport of radiocesium in PBFT All Pacific bluefin tuna sampled in 2011 contained measurable amounts of 134 Cs and elevated 137 Cs compared to PBFT that pre-dated the Fukushima disaster and YFT in the EPO that were sampled in August, This is unequivocal evidence that 89

106 Fukushima-derived radionuclides were transported to the CCLME by Pacific bluefin tuna, as no other sources of 134 Cs were present in the North Pacific preceding the Fukushima disaster (Buesseler et al. 2011, Buesseler et al. 2012) PBFT harvest and consumer safety Because bluefin tuna are harvested annually in the EPO at mt (IATTC 2010) (Table 3-5) for human consumption ( ), the possibility of radioactive contamination raises public health concerns. Radiocesium concentrations of post- Fukushima PBFT reported here were two orders of magnitude below the Japanese safety limit of 500 Bq kg -1 wet wt (about 2000 Bq kg -1 dry wt) (2011). Inferences about the safety of consuming radioactivity-contaminated seafood can be complicated due to complexities in translating food concentration to actual dose to humans (Aarkrog et al. 1997), but it is important to put the anthropogenic radioactivity levels in the context of naturally occurring radioactivity. Total radiocesium concentrations of post-fukushima PBFT were approximately thirty times less than concentrations of naturally-occurring 40 K in post-fukushima PBFT and YFT and pre-fukushima PBFT (Tables 3-1 and 3-2). Furthermore, prior to the Fukushima release the dose to human consumers of fish from 137 Cs was estimated to be 0.5% of that from the alpha-emitting 210 Po (derived from the decay of 238 U, naturally-occurring, ubiquitous and relatively non-varying in the oceans and its biota (Stewart et al. 2008); not measured here) in those same fish (Aarkrog et al. 1997). Thus even though 2011 PBFT showed a ten-fold increase in radiocesium concentrations, 134 Cs and 137 Cs would still likely provide low doses of radioactivity relative to naturally-occurring radionuclides, particularly 210 Po and 40 K. 90

107 Back-calculations of radiocesium in PBFT while in Japan To estimate the concentrations of 134 Cs and 137 Cs in 2011 PBFT at the time they left Japanese waters, we back-calculated radiocesium concentrations in muscle over a range of potential trans-pacific migration times ( days) using a loss rate of assimilated Cs from fish tissue of 1.9% day -1 (Mathews and Fisher 2009), growth dilution due to an increase in body mass during the trans-pacific migration, and radioactive decay We estimated that PBFT in Japan had 2 to 13 times higher radiocesium concentrations (30 to 120 days before capture, respectively) than concentrations measured at time of capture in California (Figure 3-2 and Table 3-4). The Japanese Ministry of Agriculture, Forestry, and Fisheries report post-fukushima concentrations of Cs in PBFT around Japan at Bq kg -1 dry weight (2011). Our estimates of total radiocesium (i.e., 134 Cs Cs) concentrations in PBFT for 90 and 120 days before capture are Bq kg -1, respectively (Table 3-4). The similarity between back-calculated values and those measured in Japan PBFT suggests that our model performs reasonably well in predicting previous concentrations of Cs in tuna captured months after exposure Migration estimates from Cs in PBFT Decay-corrected 134 Cs: 137 Cs ratios measured in post-fukushima bluefin caught off California averaged 0.6 ± 0.1 and ranged from (Tables 3-1 to 3-3). Assuming that fish tissue would reflect the 134 Cs: 137 Cs ratio of 1.0 to which they were exposed near Japan, radiocesium ratios can be used to make inferences about migration and the timing of exposure to contaminated waters. Back-calculated 134 Cs: 137 Cs ratios in most fish 91

108 approach 1:1 at 4 months (Figure 3-2), suggesting that most PBFT left Japan approximately 120 days before capture. Observed radiocesium levels were thus the result of potentially <1 month in contaminated waters, suggesting that relatively little time was needed for PBFT to assimilate radiocesium into muscle tissue Total transport of Cs by PBFT and potential transport by other species The total load of radiocesium transported to the CCLME by PBFT can be estimated from catches in the EPO. Catch data varies yearly (IATTC 2010), but assuming PBFT commercial catches in 2011 were within the range of catch from , transported and harvested radiocesium in tuna muscle tissue in 2011 could range from approximately Bq (Table 3-5) or <<1% of total radiocesium released into Japanese waters (Buesseler et al. 2012). Catch data represents a portion of the PBFT in the EPO, so total transport of radiocesium by PBFT would likely be higher. Still, this is a small quantity of radiocesium to be introduced to a large pelagic ecosystem, but it is also a conservative estimate based on one species. Other highly migratory species (HMS; e.g., turtles, sharks, and seabirds) that forage off Japan may assimilate radiocesium and transport it to distant regions of the north and south Pacific (Figure 3-1B). Tissue concentrations of radiocesium in these species would depend on time spent off Japan, foraging strategies, and timing of migration. The potential for species in Figure 3-1B and other HMS (e.g., pinnipeds, whales, and billfish) that forage in Japan to transport Fukushima-derived radiocesium is speculative. Recent findings of trace radiation in North Pacific albacore, reported in the popular press but not yet in the scientific literature (Welch 2012), reinforce the probability that highly migratory pelagic species can 92

109 transport Fukushima-derived radionuclides to distant ecoregions. These recent reports combined with the presence of Fukushima-derived radiocesium in all 2011 PBFT individuals reported here suggests that study of other HMS is warranted Conclusions Our results demonstrate that Fukushima-derived radionuclides in animal tissues can serve as tracers of both migration origin (presence or absence of 134 Cs) and timing (using 134 Cs: 137 Cs ratios) in mobile marine animals, providing valuable complementary movement data to extensive tagging programs in the Pacific (Block et al. 2011). Extensive data regarding spatio-temporal variations in Cs concentrations in the west Pacific, and consequent uptake by biota, are forthcoming, which will sharpen the precision of these new tracers. The Fukushima disaster thus provides an opportunity to examine both the extent of transport of anthropogenic radionuclides by highly migratory species and a new tool for examining migratory origins of apex predators in the Pacific Ocean. 93

110 Chapter 4 Validation of Fukushima-derived Radiocesium as a Tracer of Migration in Pacific Bluefin Tuna, Thunnus orientalis, in 2012 Publication: Madigan DJ, Z Baumann, OE Snodgrass, HA Ergül, H Dewar, and NS Fisher Radiocesium in Pacific bluefin tuna Thunnus orientalis in 2012 validates new tracer technique. Environmental Science & Technology: Abstract The detection of Fukushima-derived radionuclides in Pacific bluefin tuna (PBFT) that crossed the Pacific Ocean to the California Current Large Marine Ecosystem (CCLME) in 2011 presented the potential to use radiocesium as a tracer in highly migratory species. This tracer requires that all western Pacific Ocean emigrants acquire the 134 Cs signal, a radioisotope undetectable in Pacific biota prior to the Fukushima accident in We tested the efficacy of the radiocesium tracer by measuring 134 Cs and 137 Cs in PBFT (n = 50) caught in the CCLME in 2012, more than a year after the Fukushima accident. All small PBFT (n = 28; recent migrants from Japan) had 134 Cs (0.7 ± 0.2 Bq kg -1 ) and elevated 137 Cs (2.0 ± 0.5 Bq kg -1 ) in their white muscle tissue. Most larger, older fish (n = 22) had no 134 Cs and only background levels of 137 Cs, showing that one year in the CCLME is sufficient for 134 Cs and 137 Cs values in PBFT to reach pre- Fukushima levels. Radiocesium concentrations in 2012 PBFT were less than half those from 2011 and well below safety guidelines for public health. Detection of 134 Cs in all recent migrant PBFT supports the radiocesium tracer in migratory animals in Introduction The discharge of radionuclides into the western Pacific Ocean in 2011 from the failed Fukushima nuclear power plant has led to studies of radionuclide concentrations in 94

111 seawater and marine biota, both near Japan (Buesseler et al. 2011, Buesseler 2012, Buesseler et al. 2012) and in migratory marine species (Madigan et al. 2012a). In 2011, radiocesium from Fukushima was detected in Pacific bluefin tuna, Thunnus orientalis, that had recently traversed the North Pacific Ocean, suggesting the potential for Fukushima-derived radionuclides to serve as tracers of long-distance migrations by highly migratory species in the Pacific Ocean (Madigan et al. 2012a). While tools such as electronic tags have provided extensive animal movement data prospective from the date of tagging (Block et al. 2011), chemical tracers (such as radiocesium) can provide retrospective migration information that is often uniquely informative (Suzuki et al. 1978, Rooker et al. 2008, Madigan et al. 2012a, Ramos and González-Solís 2012). Certain conditions are necessary for the reliable use of Fukushima-derived radiocesium to trace migrations. While 137 Cs (t 1/2 = 30.1 yrs) still exists throughout the Pacific in low, background levels as a result of nuclear weapons testing that peaked in the 1960s, the shorter lived 134 Cs (t 1/2 = 2.1 yrs) from nuclear weapons testing has long since decayed (Buesseler et al. 2011). A point source of anthropogenic radionuclides such as Fukushima is therefore the only substantial source of 134 Cs in the Pacific Ocean, and consequently the presence of 134 Cs indicates recent migration from the contaminated region. For reliable application of this tracer, all animals migrating from contaminated waters must accumulate and retain measurable levels of 134 Cs to accurately identify their status as recent migrants from the western Pacific (to avoid interpretation of recent migrants as residents). Conversely, animals must excrete 134 Cs in their new environment at some determinable rate so that absence of 134 Cs can be interpreted as residency in the non-contaminated region for an interpretable period of time (to avoid erroneous 95

112 identification of recent migrants, and to constrain the time range of a recent migration). Given that potential transport of Fukushima-derived radiocesium is currently being examined in a variety of migratory animals including whales, turtles, tunas, sharks, and seabirds to infer migratory patterns, it is critical to test these assumptions. Pacific bluefin tuna (PBFT) are an ideal species for the validation and application of the radiocesium tracer. All PBFT spawn in the western Pacific Ocean, and juveniles forage in the waters around Japan (Bayliff 1994, Inagake et al. 2001, Shimose et al. 2012). Juveniles then either remain in the western Pacific or migrate eastward to the California Current Large Marine Ecosystem (CCLME). Most PBFT are thought to migrate late in their first year or early in their second (Bayliff 1994). Thus, the youngest PBFT in the CCLME (approximately years old) must have migrated from Japan within the preceding year. Previous studies suggest that larger, older PBFT in the CCLME are primarily residents for >1 year (Bayliff 1994). However, some fish migrate from Japan at older ages, and in a given year the proportion of Japan migrants to CCLME residents is largely unknown. This information could improve fisheries modeling and management of PBFT, in which severe population declines have recently been reported (ISC 2012, Whitlock et al. 2012). For radiocesium to function as a reliable tracer in PBFT, all PBFT in the CCLME below some threshold age (which must be recent migrants from Japan) must assimilate adequate concentrations of 134 Cs before their eastward migration and retain measurable concentrations after their trans-pacific migration to the CCLME. Marine fish have been shown to acquire Cs from both the aqueous phase and from diet (Mathews and Fisher 2009). Older fish in the CCLME that are residential (>1 year in the CCLME) must lose 96

113 134 Cs due to excretion (Mathews et al. 2008, Mathews and Fisher 2009, Madigan et al. 2012a), so that only recently migrated fish would carry measurable levels of 134 Cs, allowing the 134 Cs to distinguish recent migrants from >1 yr CCLME residents. We collected 50 samples of PBFT in 2012 and measured muscle tissue for 134 Cs and 137 Cs to determine if the acquisition of radiocesium by migrating PBFT persisted into the summer of 2012, more than a year after the Fukushima disaster. Radiocesium levels were compared to concentrations of another γ-emitting radionuclide, the naturallyoccurring 40 K, to provide context for observed radiocesium concentrations. For comparison, we also collected 5 samples of yellowfin tuna (Thunnus albacares) in 2012, which are known from electronic tagging studies to be residents of the CCLME and do not make migrations from the western Pacific Ocean (Schaefer et al. 2007, Block et al. 2011). We used small PBFT, known to be migrants from Japan, to test whether all migrants would demonstrate a measurable radiocesium signal from Fukushima. We examined the radiocesium levels in older fish to determine if residents and migrants could be discerned via the absence of 134 Cs (due to excretion during a year or more in CCLME waters) or presence of 134 Cs (due to recent migration from Japan). Finally, we use ratios of 134 Cs: 137 Cs to estimate time of departure from Japan in recently migrated PBFT Materials and Methods Sampling and radioanalysis Tuna tissue samples were collected from PBFT and yellowfin tuna (YFT; Thunnus albacares; CCLME residents) (Schaefer et al. 2007, Block et al. 2011) captured 97

114 by recreational sport fishermen. Fish were caught within 300 km of San Diego, CA, USA and landed in San Diego where they were filleted and frozen for human consumption. We sampled g of white muscle tissue from the dorsal musculature behind the head. Muscle tissue was kept on dry ice (-55 C) and shipped to Stony Brook University for radioanalysis. Muscle samples were freeze-dried and 65 ± 23 g dry wt of white muscle tissue was blended and combusted at 450 C for 4h. Combustion resulted in further compactness of the sample, which assured better counting efficiency during γ- radioanalysis (details below). Loss of Cs during combustion was assumed to be negligible, as shown previously (Buesseler et al. 1990). Ash was further ground with a mortar and pestle to achieve a uniform matrix, placed inside plastic jars, and stored at 60 C prior to radioanalysis. For γ-radioanalysis of 134 Cs, 137 Cs and 40 K we used high purity germanium detectors (HPGe; Canberra Industries). Sample counting times were adjusted to allow propagated counting errors of <10% for 137 Cs (662 kev), <15% for 134 Cs (605 kev) and <3% for 40 K (1461 kev). Most samples were counted for up to 3 d. Genie 2000 software (Canberra) was used to analyze the peaks in the energy spectrum. The lowest detection limits were 0.1 Bq kg -1 for both 134 Cs and 137 Cs and 0.9 Bq kg -1 for 40 K. These detection limits were calculated for each individual fish muscle sample using the well-known blank method (Currie 1968). Counting geometry was taken into consideration by varying the fullness of the jar when testing standards made of known quantities of 75 Se, 134 Cs, 137 Cs and 40 K emitting over a broad energy spectrum (265 kev, 605 kev, 662 kev and 1461 kev, respectively). 134 Cs and 137 Cs concentrations in tuna muscle samples were 98

115 decay-corrected to catch dates in the CCLME (Table 4-1). No decay correction was required for 40 K due to its long half-life (t 1/2 = yrs) Age estimation Age (age est ) was estimated from standard length (SL; cm) for PBFT and YFT according to Bayliff et al and Wild SL was calculated from curved fork length (CFL; cm) for PBFT according to Farwell 2000 and for YFT according to Scida et al When possible we measured the length from rostrum to operculum (operculum length, or OL, cm) and curved fork length (CFL, cm) of whole fish and calculated a regression for PBFT: CFL = OL to estimate CFL from OL (Figure S1). The linear equation had an r 2 value of 0.98 (Figure 4-3) Back-calculated departure date The ratio of radioactive Cs isotopes ( 134 Cs: 137 Cs = R) was used to back-calculate the time at which individual PBFT left the Fukushima-contaminated waters around Japan. This ratio would decrease in PBFT after their departure due to continued exposure to 137 Cs at background levels (1 mbq L -1 ) but no 134 Cs in central and eastern Pacific waters, and the faster decay rate of 134 Cs. A model based on that from Madigan et al. 2012a was used to estimate how 134 Cs: 137 Cs ratios in PBFT would change over time after leaving 99

116 waters around Japan. Briefly, Equation 4-2 describes the processes that impact the change of 134 Cs: 137 Cs ratio over time t. These processes are: radioactive decay (λ 1 and λ 2 for 137 Cs and 134 Cs; t 1/2 = 30.2 and 2.1 years, respectively) and efflux (k e : 0.02 d -1 ) (Mathews et al. 2008) of previously accumulated Cs (Mathews and Fisher 2009). Background 137 Cs in PBFT muscle (measured in pre-fukushima PBFT) is represented by A (here, A = 1 Bq kg -1 dry wt), which is the same for YFT never exposed to Fukushima radionuclides, PBFT residents of the CCLME >1 yr, and PBFT before Fukushima (2008) (Madigan et al. 2012a). Background 137 Cs (from nuclear weapons testing fallout) in PBFT is a result of uptake of 137 Cs from seawater and food (collectively, k a ) and loss of previously accumulated 137 Cs (k e ) (Madigan et al. 2012a). Since PBFT concentrations of 134 Cs and 137 Cs change differently over time due to different decay rates and acquisition of weapons fallout 137 Cs but not 134 Cs after leaving contaminated waters, estimated time since departure (t) will depend not only on the initial R calculation (R 0 ) but also on absolute concentrations of 134 Cs and 137 Cs in PBFT. The contribution of 137 Cs from weapons fallout (1.0 Bq kg -1 dry wt) will contribute relatively more 137 Cs to the total pool of 137 Cs in PBFT muscle in PBFT that acquire low amounts of Cs in contaminated waters. Consequently, fish that acquire relatively low amounts of 134 Cs and 137 Cs in contaminated waters will have R values that decrease more rapidly, with 134 Cs decreasing more rapidly than 137 Cs. In contrast, PBFT that acquire more 134 Cs and 137 Cs in contaminated waters will have slower rates of decrease of R, as both 134 Cs and 137 Cs concentrations will decrease at fairly similar rates until the 137 Cs concentration decreases to levels where background 137 Cs (A) contributes an appreciable proportion of 137 Cs to the total pool of 137 Cs in PBFT muscle: 100

117 4-2 Background 137 Cs concentration in PBFT (A) is a product of 137 Cs concentration in seawater (1 mbq L -1 ) and the Cs uptake rate constant (k a ) divided by the sum of efflux (k e ), radioactive decay (λ 1 ) and accumulation (k a ) rate constants: 4-3 It is assumed that 134 Cs and 137 Cs have identical rate constants of uptake and loss in fish. In 2012, accumulation rate constants (k a ) and efflux rate constants (k e ) yield A values = 1 Bq kg -1 of 137 Cs. PBFT that migrate away from Fukushima-contaminated waters will lose previously accumulated Cs from muscle tissue, and the concentration of 137 Cs and 134 Cs in PBFT muscle will asymptotically approach A (1 Bq kg -1 dry wt) and 0, respectively. Dividing A by the concentration of 137 Cs in surface seawater in the Pacific yields a dry wt concentration factor in PBFT muscle of 1000, and a wet wt concentration factor of 244, somewhat higher than the value of 100 calculated for generic marine fish (IAEA 2004). Back-calculations of departure date from Japan require an assumed initial value for 134 Cs: 137 Cs ratio (R) to solve for time t. R at the date of maximum discharge was approximately 1 (Buesseler et al. 2011). For PBFT in 2012, we calculated an assumed value of R for April 6, 2012, one year after peak discharge of radionuclides (Buesseler et 101

118 al. 2011) that would result from the different decay rates of 134 Cs and 137 Cs. This value (0.73) was used in estimates of departure date from Japan for individual PBFT (Table 4-3) Statistical analysis Mann-Whitney U-tests were used to compare the 134 Cs and 137 Cs concentrations of small ( cm SL) PBFT, larger PBFT migrants ( 134 Cs present), larger PBFT residents ( 134 Cs absent), PBFT migrants from 2011 (Madigan et al. 2012a), and YFT residents in the CCLME. Mann-Whitney U-test p-values were considered significant at p = Pearson s linear correlation was used to assess the potential linear correlation between PBFT age and estimated time since migration from waters around Japan (calculated from 134 Cs: 137 Cs ratios, Equation 2), with p-values significant at p = 0.05 and H 0 = no correlation between variables Results We collected 50 Pacific bluefin tuna in 2012 in May, June and August (Table 4-1). PBFT ranged from cm SL (79.4 ± 18.6 cm), corresponding to estimated ages of yrs (1.9 ± 0.7 yrs) (Table 4-1). 134 Cs was detected in 33 fish and concentrations of 137 Cs and 40 K are reported for all PBFT. All of the small PBFT ( cm SL; age est = yrs; n = 28; hereafter small PBFT ) had measurable concentrations of 134 Cs (0.7 ± 0.2 Bq kg -1 ), while only 5 of the 22 larger PBFT ( cm SL; age est = yrs) had detectable concentrations of 134 Cs (1.02 ± 0.27 Bq kg -1 ) (Table 4-1). When detected, 134 Cs concentrations ranged from Bq kg -1 dry 102

119 wt (0.7 ± 0.3 Bq kg -1 ), approximately 18% of the mean concentration reported in 2011 PBFT (4.0 ± 1.4 Bq kg -1 ) (Madigan et al. 2012a). For PBFT containing 134 Cs Table 4-1. Catch date, size, estimated age, and radionuclide concentrations in 50 Pacific bluefin tuna (PBFT) Thunnus orientalis, captured in the California Current Large Marine Ecosystem in Small PBFT: #1-28; larger PBFT: #29-50, as defined in the text. PBFT SL a Age b 134 Cs Cs K Catch date # cm years Bq kg -1 dry wt 134 Cs: 137 Cs 1 8/4/ /4/ /4/ /4/ /4/ /4/ /4/ /4/ /4/ /4/ /18/ /4/ /4/ /4/ /4/ /4/ /4/ /4/ /4/ /18/ /4/ /4/ /4/ /18/ /4/ /4/ /4/ /22/ /9/ nd /10/ /9/ nd /10/ nd /18/ nd /18/ nd /18/ nd /18/ /9/ nd /18/

120 39 8/4/ nd /18/ /18/ /10/ nd /10/ nd /10/ nd /10/ nd /10/ nd /26/ nd /10/ nd /10/ nd /26/ nd a Estimated from CFL (Farwell 2000). b Estimated from SL (Bayliff et al. 1991). nd : not detected. Dash ( ) indicates 134 Cs: 137 Cs ratios that could not be determined due to nondetection of 134 Cs. above the detection limit, the mean 134 Cs: 137 Cs ratio was 0.33 ± 0.06 (Table 4-1). YFT had no 134 Cs and only background levels (0.84 ± 0.12) of 137 Cs (Table 4-2). Concentrations of naturally-occurring 40 K ranged from Bq kg -1, and ratios of radioactivity from 40 K to Cs in PBFT ranged from 99 (PBFT #5) to 719 (PBFT #34) (Tables 4-1). PBFT sampled in the CCLME are either recent Japan migrants or CCLME residents (Figure 4-1A), and radiocesium concentrations enabled us to classify PBFT as migrants or residents (Table 4-1, Figure 4-1B). All fish 1.6 yrs old were migrants, while only 5 of 22 PBFT age yrs were migrants. Small migrant 2012 PBFT had lower concentrations than larger migrant PBFT of both 134 Cs (p < 0.05) and of 137 Cs (p < 0.01) (Figure 4-1B). Both 2012 migrant groups had lower concentrations than recent migrants sampled in Larger resident PBFT and YFT had no detectable 134 Cs and only background levels of 137 Cs (Tables 4-1 and 4-2, Figure 4-1B), and radiocesium levels between these groups was not significantly different (Figure 4-1B). The smallest fish categorized as a CCLME resident of >1 year was 73.7 cm SL (age est = 1.7 years) 104

121 A B Figure 4-1. Map of simplified movement patterns (A) and concentrations of 134 Cs and 137 Cs (B) in Pacific bluefin tuna (migrants and residents) and yellowfin tuna (residents) in the CCLME. Radiocesium concentrations in (B) are mean values (Bq kg -1 dry wt) + SD. P-values shown are for Mann-Whitney U-tests. 105

122 Figure 4-2. Ratios of 134 Cs: 137 Cs in Pacific bluefin tuna caught in the CCLME from June through August Open triangles indicate recent Japan migrants, and filled triangles indicate fish that are resident (>1 year) to CCLME. Cs ratios equal to 0 are due to absence of 134 Cs in these fish and are only observed in older fish (x-axis: 1.7 years old). 134 Cs: 137 Cs ratios greater than zero in PBFT >1.7 yrs represent PBFT that migrated from Japan at older ages. (Table 4-1), establishing this size and age as the threshold in this study between the 100% migrant group (small PBFT) and the mixed group of residents and migrants (larger PBFT) (Figure 4-2). There was a positive correlation between fish age and time since departure from Japan (estimated from 134 Cs: 137 Cs ratios) (p < 0.01, r 2 = 0.36; Figure 4-3A) indicating that larger PBFT left Japan earlier. Estimated departure times from Japan suggest that most 106

123 A B Figure 4-3. (A) Relationship between PBFT age and estimated time since departure (days) from Japan for the 33 PBFT that contained 134 Cs and (B) histogram of estimated departure dates from Japan for recent migrant PBFT. P-value and r 2 reported in (A) are for Pearson s linear correlation test. Solid line represents linear fit to data, dashed lines show 95% CI. Departure dates in (B), estimated from 134 Cs: 137 Cs ratios, were centered on early June. 107

124 Table 4-2. Catch date, size, and radionuclide concentrations in 5 yellowfin tuna (YFT) Thunnus albacares, captured in the California Current Large Marine Ecosystem in Cs was undetectable in all YFT. YFT Catch SL a Age b 137 Cs # date cm yrs Bq kg -1 dry wt a Estimated from CFL (Scida et al. 2001). b Estimated from SL (Wild 1994). 40 K 1 9/22/ /22/ /22/ /22/ /22/ Average SD CFL = (OL) n = 18 r 2 = 0.98 Figure 4-4. Operculum length (OL) vs. curved fork length (CFL) for Pacific bluefin tuna, Thunnus orientalis (PBFT). Line represents linear fit to data, with equation of line, samples size (n), and r 2 values shown. 108

125 migrants left Japan in early-mid June, with a few departing in April and July (Figure 4-3B) Discussion Our results demonstrate that PBFT continue to transport Fukushima-derived radiocesium across the Pacific Ocean to the CCLME. These findings support the use of Fukushima-derived radiocesium in Pacific bluefin tuna to determine whether PBFT in the eastern Pacific Ocean have recently migrated from Japan or have been residential in the CCLME for at least one annual cycle, at which point 134 Cs is undetectable and 137 Cs decreases to background levels Comparison with 2011 PBFT Prior to this study it was unknown whether concentrations of radiocesium in PBFT in 2012 would be higher or lower than those measured in Concentrations of Cs in PBFT could decrease over time due to dilution of radiocesium in waters around Japan, the decay of 134 Cs, and the potential for decreasing radiocesium concentrations in PBFT prey due to Cs dilution in seawater. However, PBFT captured in the CCLME in 2012 spent more time in contaminated waters than those sampled in PBFT in 2011 likely spent only 1 3 months in contaminated waters prior to eastward migration, and estimations of departure dates suggest that some may have spent less than one month in 109

126 Table 4-3. Size, estimated age, date of catch, and estimated date of departure from Japan for 33 Pacific bluefin tuna (PBFT) Thunnus orientalis, identified as recent Japan migrants by presence of 134 Cs in muscle tissue. PBFT # SL a cm Age b years Catch date Date at which fish had 134 Cs: 137 Cs of 0.73 Days since fish left Japan c /4/2012 6/18/ /4/2012 6/8/ /4/2012 6/16/ /4/2012 6/15/ /4/2012 6/3/ /4/2012 6/24/ /4/2012 6/8/ /4/2012 6/17/ /4/2012 5/30/ /4/2012 6/26/ /18/2012 6/6/ /4/2012 6/14/ /4/2012 5/24/ /4/2012 6/1/ /4/2012 6/11/ /4/2012 6/20/ /4/2012 6/14/ /4/2012 6/23/ /4/2012 6/3/ /18/2012 7/13/ /4/2012 7/5/ /4/2012 6/12/ /4/2012 6/21/ /18/2012 6/1/ /4/2012 6/7/ /4/2012 7/4/ /4/2012 6/12/ /22/2012 6/9/ /10/2012 4/10/ /18/2012 6/2/ /18/2012 5/21/ /18/2012 6/8/ /18/2012 5/15/ a SL = standard length. b Estimated from SL (Bayliff et al. 1991). c Estimated from the 134 Cs: 137 Cs ratio of each fish (Equation 4-2). 110

127 contaminated waters before their trans-pacific migration (Madigan et al. 2012a). Small PBFT in 2012 potentially spent their entire first year in coastal waters around Japan before migrating eastward. There is also the potential for trophic biomagnification of Cs in juvenile PBFT (Wang et al. 2000, Mathews and Fisher 2009), which are mid- to hightrophic level predators that feed on crustaceans, forage fish, and squid (Shimose et al. 2012). The potential biomagnification of Cs in PBFT presents the possibility of a time lag between maximum radiocesium concentrations in seawater and maximum concentrations in tuna (and other high trophic level predator) muscle tissue. Longer exposure times and potential trophic biomagnification presented the potential for higher concentrations of Cs in 2012 PBFT. Our results show that migrant PBFT concentrations of 134 Cs in 2012 dropped to approximately 18% of those in Total radiocesium ( Cs) also dropped, from 10.3 ±2.9 in 2011 (Madigan et al. 2012a) to 2.9 ± 1.0 Bq kg -1 in 2012 (Table 4-1), suggesting that radiocesium levels declined significantly in PBFT from 2011 to 2012 in the CCLME. This suggests that any enhanced bioaccumulation of Cs in PBFT over the longer exposure period was outweighed by the year-long dilution of radiocesium in contaminated waters in This is in contrast to the report that Cs concentrations remained steady (though highly variable) in demersal, coastal fish off Fukushima in 2012 (Buesseler 2012). It is likely that differences in radiocesium concentrations in both seawater and prey lead to differences in Cs concentrations between demersal coastal fish and pelagic fish such as PBFT. The radionuclides in PBFT from the Fukushima nuclear power plant accounted for an even smaller fraction of the total radioactivity in 2012 PBFT than in 2011 PBFT 111

128 (Madigan et al. 2012a) and remained well below safety limits set by the most stringent government regulations (100 Bq kg -1 wet wt, or about 400 Bq kg -1 dry wt). The radioactivity from the naturally occurring 40 K exceeded that of radiocesium by two to three orders of magnitude. Another naturally-occurring radionuclide, 210 Po, is present in tuna muscle provides a radioactive dose to seafood consumers that is orders of magnitude above the dose resulting from the Fukushima radionuclides (Fisher et al., Yamamoto et al. 1994) Inferred migration patterns The differences between migrant and resident PBFT (Figure 4-1B) demonstrate that recent migrants to the CCLME can easily be discerned from CCLME residents of at least one year using radiocesium concentrations; this is particularly apparent in concentrations of 134 Cs. 134 Cs was detected in only 23% (5 of 22 individuals) of older PBFT (Table 4-1, Figures 4-1, 4-2). This is an expected result, as many older PBFT in the CCLME are assumed to have migrated during their first year, although some variable proportion migrates in subsequent years (Bayliff et al. 1991). The 5 older fish with detectable 134 Cs demonstrate the utility of the radiocesium tracer to discern recent migrants from residents in older fish, for which migration status is unknown (Bayliff et al. 1991, Bayliff 1994). The higher concentrations of 134 Cs and 137 Cs in larger vs. smaller migrants may be the result of trophic biomagnification, as young PBFT off Japan show a diet shift to higher trophic level prey during their first year, and larger fish would thus be feeding on higher trophic levels in waters around Japan for a longer time period (Shimose 112

129 et al. 2012). Efflux rate constants for Cs may also be greater in smaller versus larger fish, though this has not been measured. Radiocesium levels in older resident PBFT were not significantly different from those in YFT, which do not migrate from the western Pacific and are residential to the CCLME (Schaefer et al. 2007, Block et al. 2011) and show no detectable 134 Cs and only background levels of 137 Cs (Table 4-2) over two years of data analysis (Madigan et al. 2012a). This suggests that older PBFT which carried radiocesium in 2011 eliminated 134 Cs to non-detectable and 137 Cs to background (~1 Bq kg -1 ) levels within one year of residency in the CCLME. Therefore, all PBFT in the CCLME for one year or more can be expected to carry radiocesium levels comparable to pre-fukushima conditions. This makes identification of CCLME residents particularly straightforward, as presence or absence of 134 Cs discerns migrants from residents. All PBFT that are 3-4 years old carried no 134 Cs, distinguishing all of these PBFT (n = 9) as >1 yr CCLME residents (Figure 4-2) Timing of migrations The significant linear relationship between PBFT age and time since departure from Japan (Figure 4-3A) suggests that older fish may have migrated from the western Pacific Ocean before younger fish. Older fish had similar 134 Cs: 137 Cs ratios to smaller fish, and greater estimated time since departure in older fish is a consequence of the greater concentrations (Figure 4-1B) of 134 Cs and 137 Cs in older fish than those in younger fish (see description of Equation 4-2 in Materials and Methods). Estimated time since Japan departure, based on 134 Cs: 137 Cs ratios, ranged from days (Table 4-3) with an 113

130 average time since departure of approximately two months (57 ± 16 d). This average matches the crossing time (65 d) of an electronically-tagged juvenile PBFT making its first trans-pacific migration, and the shortest time since departure in our study (30 d) is possible given the daily swimming speed (172.3 ± 41.7 km d -1 ) in that study (Kitagawa et al. 2009). If our lowest estimate of 30 d is accurate, it is the fastest reported trans-pacific migration by a PBFT. Time since departure for larger PBFT (>1.7 yrs) was nearly a month longer (79 ± 14 d) (Table 4-3). Variability in the timing of offshore migration has been demonstrated in conventional tagging studies (Bayliff et al. 1991), and it is possible that older, larger fish follow different cues for the initiation of offshore migration. Larger fish would have a higher tolerance for colder waters and would potentially be less affected by oceanographic conditions that may limit migration ability during periods of cooler water before spring and early summer. Departure from Japan began in late spring, centered on early June (Figure 4-3B), corresponding with conventional tagging studies that show many PBFT initiate their eastward migration during spring-summer (Bayliff et al. 1991). This early summer departure from Japan may explain why most recent Japan migrants to the CCLME were captured in August and not in earlier summer months in the CCLME (Table 4-1). Departure-date estimates rely on a predictable and consistent 134 Cs: 137 Cs ratio in PBFT muscle before leaving Japan. Our estimate of an initial 134 Cs: 137 Cs ratio in tuna muscle of 0.73 (Table 4-3) was based on the initial release ratio of 1 (Buesseler et al. 2011) and the different decay rates of 134 Cs and 137 Cs; more consistent and publicly accessible measurements of PBFT off Japan would provide the actual data to validate or modify this 114

131 estimate. However, the average 134 Cs: 137 Cs ratio for coastal and pelagic predatory fish species caught on April 9 th 2012, approximately one year after maximum discharge of radiocesium, was approximately equal (0.74 ±0.18, n=10 fish species). These data support our use of this initial 134 Cs: 137 Cs ratio value (0.73) in PBFT off Japan. The approach used here, especially applied to large datasets or used to interpret data from other chemical tracers, can improve our understanding of movement patterns of PBFT in the North Pacific Ocean. Understanding the relative proportions of migrants to CCLME residents in relation to oceanographic (e.g., ENSO events) or biological (e.g., sardine or anchovy abundance) conditions can help identify the drivers of the eastward migration of PBFT from Japan to the CCLME. Such studies could be applied to fisheries models which can benefit from migratory information (Whitlock et al. 2012) Caveats, assumptions, and application to other taxa One source of error in this study is the use of length as a proxy for age, as there is significant variability in this relationship (Bayliff et al. 1991). Ageing using otoliths is a more precise (albeit time-intensive) method (Shimose et al. 2009), although otoliths were not available for every individual sampled for white muscle tissue. Data for fisheries models in particular may require ageing using otoliths. It is also possible that time of departure from Japan is more representative of the time of departure from a broader area now contaminated by Fukushima radiocesium due to dispersal. It has recently been shown that Fukushima-derived radioactive Cs is dispersing further away from the Japanese shoreline and could be reaching waters as far as ~170 E in 2012 (Nakano and Povinec 2012). 115

132 The applicability of our results and approach to other Pacific species that migrate from Japan to distant ecoregions is important. Albacore tuna Thunnus alalunga (Childers et al. 2011), blue sharks Prionace glauca (Nakano 1994), Pacific loggerhead sea turtles Caretta caretta (Peckham et al. 2007), sooty shearwaters Puffinus griseus (Shaffer et al. 2006), salmon sharks Lamna ditropis (Nagasawa 1998), common minke whales Balaenoptera acutorostrata (Commission 1983) and other highly migratory species are all known to forage in the Kuroshio Current off eastern Japan and subsequently migrate to regions such as the Okhotsk Sea, the Aleutian Islands, the CCLME, and regions of the South Pacific Ocean. Detection of 134 Cs and elevated 137 Cs in 100% of small, recently migrated PBFT in 2012 suggests that other species that forage near Japan have a high probability of acquiring 134 Cs and 137 Cs, and the model in Equation 4-2 could be applied to radiocesium data in other migratory species. However, the movement patterns and feeding habits of each study species while near Japan should be taken into account when utilizing this tracer, as PBFT are known to feed specifically in waters near Japan during their juvenile stage, making use of the Kuroshio Current before migrating eastward (Inagake et al. 2001, Kitagawa et al. 2009, Shimose et al. 2012). Complementary data (e.g., known life history patterns, electronic tagging, or other chemical tracers) may help interpret radiocesium tracer data in other highly migratory taxa. Previous studies that measured radionuclides from the Bikini atoll weapons tests in the 1940s-60s attempted to infer migration patterns of pelagic animals, including yellowfin tuna T. albacares (Suzuki et al. 1978) and albacore tuna Thunnus alalunga (Suda 1956, Hodge et al. 1972, Young et al. 1975). However, nuclear detonations led to extensive, widespread fallout from the atmosphere (Volchok et al. 1971), and results of 116

133 those pioneering studies could only provide general, highly inferential results. In contrast, the Fukushima plant failure represents a more discrete point source of radionuclides. This unique attribute of Fukushima together with the unique migratory biology of PBFT (i.e., that all small PBFT in the CCLME must be migrants from Japan) provides an unprecedented opportunity to test and apply concentrations of anthropogenic radionuclides to trace animal movement Conclusions Despite the assumptions and gaps in knowledge that result from the Fukushima accident and observations of radioisotopes in marine biota, these radiocesium data present a clear and coherent picture of PBFT migrations that can be interpreted unequivocally. The data shown here are the strongest results possible for the evaluation of radiocesium as a tracer in PBFT and validate its use for the study of large-scale Pacific migrations, as was suggested in 2011 (Madigan et al. 2012a). We expect this new tool to produce novel data on the recent migration patterns of keystone pelagic predators, which have been historically difficult to obtain. 117

134 Chapter 5 Combining Radioactive and Stable Isotopes to Examine Migration Patterns of Pacific Bluefin Tuna Thunnus Orientalis 5.1. Abstract Understanding movement patterns of migratory marine animals is challenging but critical for effective management. Pacific bluefin tuna (PBFT) inhabit the western and eastern Pacific Ocean (WPO and EPO), are fished by several nations in both regions, and are in steep decline due to overfishing. Understanding the proportion of trans-pacific migrants to long-term (>1 year) residents of the California Current Large Marine Ecosystem (CCLME) is essential for improving fisheries management, as the agespecific contributions of WPO PBFT to and from the CCLME fisheries remain largely unquantified. Here, we use a Fukushima-derived radiotracer ( 134 Cs) in CCLME PBFT combined with bulk and amino acid stable isotope (δ 15 N) analyses to distinguish recent WPO migrants from CCLME residents. The proportion of recent WPO migrants decreased in older year classes (YCs): 75% migrants for YC1-2, 33% for YC2-3, and 0% for YC3-4. Proportions of migrants in YC2-3 PBFT in the CCLME were higher than is generally assumed. This toolbox of novel chemical tracers provides quantitative information on the migratory dynamics of PBFT and can be applied to other species that cross the North Pacific Ocean Introduction Large pelagic predators such as tunas and sharks play important roles in oceanic ecosystems (Myers and Worm 2003, Scheffer et al. 2005, Block et al. 2011) and can 118

135 shape community structure, alter prey behaviors, and maintain biodiversity in pelagic communities (Worm et al. 2003, Heithaus et al. 2008, Baum and Worm 2009). Many pelagic predators possess complex ontogenies, occupying different oceanic regions at different life stages. In bluefin tunas, these size-dependent life history traits result in longer periods of residency in specific oceanic regions. All bluefin species (Atlantic, southern, and Pacific) have high market values that make them vulnerable to overfishing and population collapse (De Roos and Persson 2002, Collette et al. 2011d). Other Pacific populations of pelagic predators are considered critically endangered or threatened (e.g., leatherback sea turtles, white sharks, and albatross), due to over-exploitation, by-catch in fisheries, and prey depletion (Myers and Worm 2003, Scheffer et al. 2005, Peckham et al. 2007, Cury et al. 2011) in the Pacific Ocean. To improve the status of threatened marine pelagic species, maintain oceanic biodiversity, and preserve ecosystem function, management practices based on sound understanding of the biology of these species are necessary (Worm et al. 2003). In the case of highly migratory species, migration patterns sometimes require international management and cooperation (e.g. Atlantic bluefin tuna (Block et al. 2001, Rooker et al. 2008, Taylor et al. 2011)). For species that migrate vast distances, understanding of migratory patterns (often across ontogeny) is essential to discern the extent to which a species utilizes different oceanic ecosystems. This in turn improves understanding of the effective mortality of regional fisheries on a particular species. The Pacific bluefin tuna, Thunnus orientalis (PBFT), utilizes both sides of the North Pacific Ocean (juveniles and adults) as well as the south Pacific (adults), giving PBFT one of the largest distributions of any fish species. All PBFT are spawned in the 119

136 western Pacific Ocean (WPO), and in their first several years of life an unknown proportion of the population migrates across the Pacific Ocean and feeds on abundant prey resources of the California Current Large Marine Ecosystem (CCLME) (Bayliff et al. 1991, Bayliff 1994) in the eastern Pacific Ocean (EPO). Extensive conventional (Bayliff 1994) and electronic (Block et al. 2011) tagging programs have shown that once in the CCLME, PBFT can remain residential for one to five years before returning to the west Pacific, presumably to spawn (Boustany et al. 2010, Block et al. 2011). PBFT are exploited by recreational and commercial fisheries (PBFWG 2011). Presently, the proportion of long-term residents of the CCLME (>1 year) to recent (within the preceding year) migrants from the WPO across different size classes of PBFT in the CCLME is largely unknown and challenging to discern. It is currently unclear whether PBFT fisheries in the CCLME depend predominately on recent WPO migrants (mixed size/age) or on long-term residents (young PBFT foraging in the CCLME), though movements of highly pelagic species are important to fisheries models (Whitlock et al. 2012). Fisheries models can improve the capacity to capture spatially explicit movements to understand the fishing mortality of multiple fleets on a year class throughout the Pacific using chemical tracers such as otolith microchemistry and isotopic analyses (Rooker et al. 2008, Secor 2010, Secor et al. 2012). Better and new chemical tracers can provide retrospective analyses of PBFT life history and help resolve the migratory dynamics of PBFT in the EPO (Ramos and González-Solís 2012). One such tool that can be used to elucidate migratory history is stable isotope analysis (SIA). Nitrogen isotopic composition, one of the most commonly used in ecological studies using SIA, determines the ratio of a heavier, rare isotope to a 120

137 lighter, more common isotope ( 15 N: 14 N, or δ 15 N) expressed as parts per thousand ( ) relative to an international standard. δ 15 N values of food-web baseline sources can differ greatly (e.g., phytoplankton vs. macroalgae), and these dissimilar δ 15 N values of primary producers in discrete ecosystems (e.g. oligotrophic pelagic versus productive coastal upwelling systems) may have dissimilar δ 15 N values that will propagate up regional food webs (Fry 2006, Graham et al. 2010, Carlisle et al. 2012). Thus a predator moving into a new ocean region that is isotopically distinct will not reflect local δ 15 N prey values (migration effects). However, δ 15 N values also reflect trophic level due to the systematic increase of δ 15 N values with each trophic step in food webs (Post 2002, Fry 2006). Newer techniques such as amino acid compound-specific isotope analysis (AA-CSIA) can be used to discern migration from trophic effects when interpreting bulk tissue SI values (Popp et al. 2007, Olson et al. 2010, Seminoff et al. 2012). AA-CSIA measures the δ 15 N values of individual amino acids from proteins in tissues. Certain source amino acids (glycine, serine, and phenylalanine) have been shown to fractionate minimally up food webs, while trophic amino acids (alanine, valine, leucine, isoleucine, proline, and glutamic acid) demonstrate relatively high trophic fractionation (Popp et al. 2007, Chikaraishi et al. 2010). Thus by comparing the source AA δ 15 N values of muscle tissue from animals with different bulk δ 15 N values, one can differentiate whether the difference is likely migration-based (different source δ 15 N values) or forage-based due to feeding differences (similar source δ 15 N values) (Popp et al. 2007, Sherwood et al. 2011, Seminoff et al. 2012). PBFT have recently been shown to be seriously overfished, with population declines of over 96% from pre-fished levels (ISC 2012). In order to improve fisheries 121

138 models for assessing biomass and prevent further overexploitation, information that facilitates a better understanding of trans-pacific migrations is necessary. Better quantification of the mixing dynamics over consecutive PBFT year classes will allow understanding of how much PBFT biomass is exchanged between the WPO and the EPO. This in turn will improve estimates of mortality on specific year classes by multiple fleets across the Pacific (Whitlock et al. 2012). Here we use SIA values from PBFT contaminated with Fukushima-derived 134 Cs that can unequivocally identify PBFT that migrated from waters off Japan (Buesseler et al. 2011, Buesseler et al. 2012, Madigan et al. 2012a, Madigan et al. 2013) in combination with a larger dataset of PBFT SIA values to elucidate the migratory history of different year classes of PBFT in the CCLME. In addition, AA-CSIA is used to separate migration effects from potential trophic effects on bulk SIA values. Analysis revealed, for the PBFT in this study, the proportion of WPO migrants to CCLME residents, information which is essential for CCLME fisheries. This novel chemical toolbox can be applied to PBFT, and other migratory species in the North Pacific Ocean, to potentially complement otolith microconstituent analysis and prospective data provided by tagging and provide reliable, retrospective information on the recent migratory history of Pacific predators. Given the differences in Cs and stable isotope signatures in the WPO and EPO, we explored the questions: can long-term residents of the CCLME (> 1 year) be discerned from recent migrants from the WPO? And, can the timing of migrations be established? Answering these questions would aid in the understanding and future study of PBFT in the NPO. 122

139 5.3. Materials & Methods Sampling and isotopic analysis Tunas were caught by hook and line in the CCLME and sampled aboard the sport fishing vessel F/V Shogun. Skeletal muscle samples (~ 50 g per fish) were taken from decked fish in the months of June-October on research cruises in 2008, 2009, and Research cruises took place in the CCLME (28 00 N N; W W). Fish samples were also obtained from recreational anglers fishing within 300 km of San Diego, CA in waters off southern California and northern Baja, Mexico. All fish were landed in ports throughout southern California and subsequently sampled for muscle tissue. For all samples, curved fork length (CFL; cm) was measured and date of capture was recorded. CFL was converted to standard length (SL; cm) according to a regression from Farwell (Farwell 2000): SL = CFL Fast-twitch (white) muscle (WM) biopsies were taken from the dorsal musculature with a stainless steel scalpel, frozen at -5 C, and freeze-dried at -80 C for 72h. Samples were homogenized using a grinding mill (Wig-L-Bug, Sigma Aldrich) and analyses of WM δ 15 N were conducted at the Stanford Stable Isotope Biogeochemistry Laboratory using a Thermo Finnigan Delta-Plus IRMS coupled to a Carlo Erba NA1500 Series 2 elemental analyzer via a Thermo Finnigan Conflo II interface. Replicate reference materials of graphite NIST RM 8541 (USGS 24), acetanilide, and ammonium 123

140 sulfate NIST RM 8547 (IAEA N1) were analyzed between every 10 samples. Stable isotope ratios are reported as mean ± SD. For AA-CSIA, 5-7 mg of homogenized white muscle tissue was derivatized to produce trifluoroacetic amino acid esters (Popp et al. 2007, Hannides et al. 2009). δ 15 N values of individual amino acids in each sample were determined using a Delta V mass spectrometer interfaced to a Trace GC gas chromatograph through a GC-C III combustion furnace (980 C), reduction furnace (650 C), and liquid nitrogen cold trap via a GC-C III interface. All samples were analyzed at least in triplicate and measured δ 15 N values were normalized to the known nitrogen isotopic composition of internal references norleucine and aminoadipic acid co-injected with each sample (Dale et al. 2011). We used source amino acids Gly, Ser, and Phe to calculate a weighted average, based on measurement error for each AA, of δ 15 N values for each sample group following Sherwood et al. (Sherwood et al. 2011) to determine if source AA δ 15 N values of WPO migrant PBFT (inferred from low bulk δ 15 N values) were different from CCLME residents (PBFT inferred as residents from high bulk δ 15 N values, yellowfin Thunnus albacares (YFT), Pacific saury Cololabis saira, and jack mackerel Trachurus symmetricus). The standard deviation of δ 15 N values derived from multiple analyses averaged 1.32 and ranged from 0.44 to 2.16 (Table 5-3). See Popp et al. (Popp et al. 2007), Sherwood et al. (Sherwood et al. 2011) and Hannides et al. (Hannides et al. 2009) for full description of methods. For Cs, tuna muscle samples were collected from recreational anglers as reported in Chapter Cs and 137 Cs concentrations (Bq kg -1 dry wt) were analyzed using a low- 124

141 energy germanium detector. 134 Cs and 137 Cs concentrations were decay-corrected to angler-estimated catch date for each fish. See Chapter 3 for a full description of methods Migratory Origin We characterized compositional differences in radioisotope and stable isotope concentrations between WPO and CCLME waters by grouping published δ 15 N values of local tuna prey species (WPO off Japan and the CCLME) and calculating a mean ± SD for all tabulated prey values. We also compared measured PBFT 134 Cs: 137 Cs concentration ratios with those measured in seawater off Japan ( 134 Cs: 137 Cs 1.0) as reported by Buesseler et al. (Buesseler et al. 2012). δ 15 N values of predators at isotopic steady-state with local prey were estimated by adding the trophic discrimination factor (TDF) of PBFT (1.9 ± 0.4 ) (Madigan et al. 2012c) to local prey averages. Regional estimates were used to establish that sufficient differences in isotopic compositions exist to discern individuals from the WPO (Japanese waters) and the CCLME and to use the isotopic compositions as endpoints in migration timing estimates. Discriminant analysis uses data of known classification ( training data ) to classify unknown data into specified categories (migrants and residents) (Klecka 1980). Muscle δ 15 N values of 14 of the 134 Cs-containing PBFT in Madigan et al. (Madigan et al. 2012a) (known recent migrants to CCLME) and juvenile yellowfin tuna (YFT; known residents of CCLME based on lack of 134 Cs (Madigan et al. 2012a) and electronic tagging data (Block et al. 2011)) from Madigan et al. (Madigan et al. 2012b) were used as training data in discriminant analysis to classify individual PBFT from a larger, multiyear dataset ( ; n = 130) as migrants or residents based on δ 15 N values. Discriminant analysis reported an error value for the classification of unknown data, 125

142 which estimates the percentage of individuals that were likely classified incorrectly (Klecka 1980). PBFT were classified into discrete year classes following age and growth algorithm in Shimose et al. (Shimose et al. 2009) where fish age 0-1 ( cm) are YC0-1, 1-2 ( cm) are YC1-2, 2-3 ( cm) are YC2-3, and 3-4 ( cm) are YC3-4. Youngest year-class 1-2 individuals (YC1-2) are known to be recent migrants (Bayliff et al. 1991, Bayliff 1994) and results would reflect the robustness of discriminant analysis (discriminant analysis should report smallest YC1-2 PBFT as migrants). YC2-3 and YC3-4 were separated into migrants and residents, and relative proportions reported for each year-class. Discriminant analysis was performed using a linear discriminant function, which fits a multivariate normal density to each group, with a pooled estimate of covariance. Analysis was carried out using MatLab (v. 2009a) Migration timing Cs: 137 Cs clock approach Radiocesium isotope ratios ( 134 Cs: 137 Cs = R; Figure 5-2) would decrease in PBFT upon leaving waters contaminated by Fukushima radionuclides. Thus 134 Cs: 137 Cs ratios were used to estimate the time since an individual PBFT left waters around Japan by using the mathematical model from Chapter 4:

143 where t represents time since leaving WPO waters off Japan, and R, [ 134 Cs] t, and [ 134 Cs] t represent the PBFT WM ratios of 134 Cs: 137 Cs, 134 Cs concentration, and 137 Cs concentrations at time t, respectively. A represents background levels of 137 Cs in PBFT WM (1.0 Bq kg -1 ) (Madigan et al. 2012a). Different radioactive decay constants for 137 Cs ( ) and 134 Cs ( ) are represented by λ 1 and λ 2, respectively. The background 137 Cs in bluefin is assumed to be constant at 1.0 Bq kg -1 dry wt, as a result of a balance between the uptake (k a ) of 137 Cs from water and food, and loss of previously assimilated 137 Cs (k e : 0.02% d -1 ; (Mathews and Fisher 2009)). This equation assumes that PBFT will acquire the same 134 Cs: 137 Cs ratio in their muscle tissue in contaminated waters. Though movement and feeding patterns, and thus absolute 134 Cs and 137 Cs concentrations, in PBFT muscle may vary, the ratio of discharged 134 Cs: 137 Cs was constant at R = 1.0 (Buesseler et al. 2011), and all juvenile PBFT that swam and foraged in contaminated waters are assumed to have acquired this ratio SIA approach Stable isotope (SI) values of PBFT tissues would not begin to change to reflect CCLME prey until PBFT entered and began feeding in the CCLME. Thus R was used to generate estimates of time since leaving the WPO, and δ 15 N values of the same fish (n = 14) were used to estimate time since PBFT entered CCLME waters (Phillips and Eldridge 2006, Klaassen et al. 2010). Thus, the difference between the 134 Cs: 137 Cs (time since leaving WPO waters around Japan) and WM (time since entering CCLME) isotopic clocks thus provides estimates of trans-pacific migration duration times. For WM stable isotope values, we used a modification of the isotopic clock approach (Phillips and 127

144 Eldridge 2006, Klaassen et al. 2010) that incorporated the uncertainty around regional (Japan and CCLME) prey values, stable isotope turnover rates in PBFT (Madigan et al. 2012c), and trophic discrimination factors in PBFT (Madigan et al. 2012c) using a resampling approach. We used statistical software (MatLab 2009a) to generate i random numbers from the mean and standard deviation (SD) from a normal distribution and ran 1000 iterations (i = 1:1000) for prey values in Japan (9.1 ± 1.0 ), prey values in the CCLME (14.0 ± 0.8 ), TDF for 15 N in PBFT WM (1.9 ± 0.4; (Madigan et al. 2012c)) and PBFT WM λ for 15 N ( ± ; (Madigan et al. 2012c)). Estimates of time (days) since entering the CCLME were then calculated for each of these 1000 iterations using the equation from Klaassen et al. (Klaassen et al. 2010): 5-3 where (i = 1:1000); t = time (days) since entering CCLME, λ is the first-order rate constant for turnover of 15 N in PBFT WM (Madigan et al. 2012c), and δ 0, δ f, and δ t represent PBFT δ 15 N values: the assumed initial δ 15 N value (Japan prey + PBFT TDF), final (steady-state) δ 15 N value (CCLME prey + PBFT TDF), and δ 15 N value at time t, respectively. From the 1000 values generated for each individual PBFT we calculated a mean t (± SD) value for each PBFT. The isotopic clock approach was applied to all PBFT (n = 130) and provided estimates of time in the CCLME for multiple year classes of PBFT. Histograms with a spline smoothing function were generated from mean estimates for YC1-2 and pooled YC2-3 and YC3-4 PBFT. 128

145 We estimated the month of entry to the CCLME by subtracting the WM isotopic clock-estimated duration in the CCLME (t) from the date of capture for each PBFT. Estimated age and size at entry into the CCLME was calculated for all PBFT based on WM isotopic clock estimates and the growth estimates of Shimose et. al (Shimose et al. 2009). (A) (B) Figure 5-1. (A) Map showing the differences in radiocesium concentrations of sea water and stable isotope compositions of prey near Japan and in the California Current System. (B) Resultant differences in radiocesium concentration and stable isotope values in a predator (Pacific bluefin tuna Thunnus orientalis) near Japan and in the CCLME Results Regional differences Isotopic compositions of similar prey items in the WPO and the CCLME are clearly distinct. δ 15 N values of tuna prey items in the WPO (Shimose et al. 2012) such as euphausiids and common forage fish (saury and anchovy) in Japan were lower (range: ; mean: 9.1 ± 1.0 ) (Minami et al. 1995, Mitani et al. 2006, Takai et al. 2007) than tuna prey in the CCLME (Pinkas 1971) such as euphausiids, forage fish, and squids 129

146 ( ; 14.0 ± 0.8 ) (Miller et al. 2010, Madigan et al. 2012b) (Table 5-1). The 134 Cs: 137 Cs ratio of seawater surrounding Japan was approximately 1.0 after the Fukushima disaster (Buesseler et al. 2012), while no 134 Cs was detected and only background concentrations of 137 Cs were present in seawater of the CCLME, resulting in a 134 Cs: 137 Cs ratio of 0 in CCLME seawater (Figure Table 5-1. All prey δ 15 N values used to generate regional estimates of prey δ 15 N. species n location δ 15 N (SD) reference euphausiid 1 Japan 7.4 ( ) (Minami et al. 1995) anchovy 1 Japan 8.9 ( ) (Minami et al. 1995) saury 15 Japan 9.2 (0.6) (Minami et al. 1995) anchovy 4 Japan 8.6 (0.8) (Mitani et al. 2006) krill 2 Japan 8.6 (0.1) (Mitani et al. 2006) krill 2 Japan 8.7 (0) (Mitani et al. 2006) krill 14 CCLME 12.4 (0.8) (Madigan et al. 2012b) sardine 18 CCLME 13.6 (0.6) (Madigan et al. 2012b) saury 20 CCLME 13.2 (0.8) (Madigan et al. 2012b) jack mackerel 27 CCLME 13.9 (0.6) (Madigan et al. 2012b) gonatid squid 7 CCLME 13.6 (1.3) (Madigan et al. 2012b) sebastes juv 7 CCLME 13.8 (0.4) (Madigan et al. 2012b) lanternfish 5 CCLME 14.0 (0.2) (Madigan et al. 2012b) pelagic red crab 5 CCLME 14.0 (0.7) (Madigan et al. 2012b) market squid 21 CCLME 15.3 (0.5) (Madigan et al. 2012b) onychoteuthid squid 6 CCLME 14.4 (0.3) (Madigan et al. 2012b) abraliopsis squid 4 CCLME 15.2 (0.4) (Madigan et al. 2012b) eelpout 8 CCLME 13.9 (0.3) (Madigan et al. 2012b) barracudina 5 CCLME 13.6 (0.2) (Madigan et al. 2012b) 130

147 Figure 5-2. Predicted temporal change of 134 Cs: 137 Cs ratio in PBFT during their cross- Pacific migration prior to their catch off California. Individual lines represent individual PBFT (n=15); the dashed line shows R=1.0 and the box marks migration duration range of d as predicted by using equation (4-1). 5-1A). Using prey δ 15 N values of each region and adjusting for PBFT trophic discrimination factor (TDF) (Chapter 1) led to PBFT white muscle δ 15 N value estimates of 11 ± 1.1 and 15.9 ± 0.9 at steady-state with WPO (δ 0 ) and with CCLME (δ f ) diet, respectively (Figure 5-1B). The 134 Cs: 137 Cs ratio in PBFT WM would hypothetically match the local seawater ratio while in Japan (1.0), while ratios in PBFT after their migration to the CCLME (0.62±0.14 Bq/kg) decreased primarily as a result of exposure to only 137 Cs (from atomic weapon testing fallout) in open Pacific waters during migration (see Figure 1B). 131

148 Bulk and stable isotope analysis We sampled WM tissue from 130 PBFT between cm (79 ± 10.4 cm) standard length (SL) for δ 15 N values in PBFT and 109 YFT δ 15 N values were used as training data in discriminant analyses to categorize these 130 additional PBFT as residents or migrants (Appendix 6). WM δ 15 N values in YFT that were also tested for radiocesium in 2011 (n = 5) ranged from (15.0 ± 0.5 ) (Table 5-2), and were not statistically different from YFT sampled from the CCLME from (n = 109), which ranged from (15.4 ± 0.8 ) (Mann Whitney U-test; Table 5-2). WM δ 15 N values of PBFT that contained radiocesium in 2011 (n = 14) ranged from (12.8 ±0.3 ), lower than average CCLME prey (Table 5-1, Figures 5-1A and 5-4). Discriminant analysis using residential YFT δ 15 N values and migrant PBFT δ 15 N values allowed for identification of recent WPO migrants and CCLME PBFT residents (Figure 5-3A and Appendix 6). PBFT classified as residents and YFT δ 15 N values showed high overlap, and migrant PBFT (containing 134 Cs) fell within the range of migrant PBFT δ 15 N values (Figure 5-4). The threshold bulk WM δ 15 N value between migrants and residents, as defined by discriminant analysis, was 14.2 (Appendix 6). Migrant to resident ratios were year-class dependent, as 75% (46 of 61) YC1-2 PBFT were categorized as recent migrants (Figure 5-3B). 33% of YC2-3 PBFT (22 of 67) were classified as migrants (Figure 5-3B) and YC3-4 (n=2) were both residents (Figure 5-3B). Classification error of discriminant analysis was 1.4%. AA-CSIA indicated that these differences were due to different δ 15 N values of source amino acids (migration effects): PBFT with high δ 15 N values (putative CCLME 132

149 residents), YFT (known CCLME residents) and CCLME prey (saury Cololabis saira and jack mackerel Trachurus symmetricus) all showed comparable source AA-CSIA δ 15 N values ( ) that were higher than putative migrant PBFT source AA-CSIA δ 15 N values (-0.5 ±0.7 ) (Figure 5-3C and Table 5-3) Estimates of residency time PBFT WM δ 15 N values generated isotopic clock CCLME residency time estimates for 130 PBFT (Figure 5-5). Residency time estimates showed that most YC1-2 PBFT were residential to the CCLME for 60 to 80 days, though a few YC1-2 PBFT were residential for longer periods (~250d; Figure 5-5). YC2-4 estimates of residency time were longer, peaking at ~500d, or months, though some residency times for YC2-3 were 0-300d (Figure 5-5). There was a seasonal trend in the migrant timing of entry into the CCLME. Immigration into the CCLME by YC1-2 PBFT was centered around May, while YC2-3 PBFT seem to have entered in the late winter and spring, with most fish arriving in February, March, and May (Figure 5-6A). Relatively few fish entered in the summer, fall or early winter (Figure 5-6A). Estimates of age and size upon CCLME entry showed three peaks (Figures 5-6B and 5-6C), with most PBFT entering late in their first year or early in their second, in accordance with previous observations (Bayliff 1994). However, an appreciable number of fish entered the CCLME late in their second year or early in their third (figure 5-6B), between sizes of cm (figure 5-6C). The smallest PBFT identified as a resident was 70.4 cm (Figure 5-3A and Appendix 6), corresponding to an age of approximately 1.65 years (Shimose et al. 2009). 133

150 PBFT were analyzed both for radiocesium and white muscle δ 15 N to generate two complementary tools to estimate migration timing. Range of WM δ 15 N values of these 14 fish was reasonably narrow ( ) compared to the larger PBFT dataset ( ), resulting in a narrower range of migration estimates than for the larger dataset. Mean estimated time since migration from Japan using radiocesium isotope values was 132±13 days, and estimated CCLME residency time using WM δ 15 N values was 110±22 days (Figure 5-7). Results of each method were significantly different at the p = 0.05 level (Mann-Whitney U-test, p = ). Trans-Pacific migration duration times, estimated from the differences between the 134 Cs: 137 Cs and WM clock estimates, ranged from -30 to 55 days (21 ± 24 days). Negative values for trans-pacific migration durtations are of course not possible, and where present indicate that WM δ 15 N isotopic clock estimates exceeded those that used 134 Cs: 137 Cs ratios. Table 5-2. Bulk white muscle δ 15 N values for Pacific bluefin tuna used in discriminant analysis. Training data (PBFT marked with 134 Cs (Madigan et al. 2012a) and YFT (Madigan et al. 2012b)) and PBFT δ 15 N values (n = 130) are shown. n/a indicates fish that were not measured for radiocesium ( 134 Cs). training data 134 Cs resident or migrant δ 15 N range δ 15 N mean (SD) species n year(s) YFT resident (0.5) YFT n/a resident (0.8) PBFT (0.14) migrant (0.3) PBFT data PBFT n/a migrant (0.9) PBFT n/a resident (0.5) 134

151 (A) δ 15 N Standard length (cm) (B) (C) Figure 5-3. (A) Relationship of PBFT white muscle δ 15 N values with PBFT size. Residents (filled circles) and migrants (empty circles) were identified by discriminant analysis. Bars below x-axis show how PBFT year class corresponds with size. (B) Results of discriminant analysis for three year classes of Pacific bluefin tuna sampled in the California Current. Year-class 1 (YC1) PBFT were all classified as migrants. Proportion of residents increased with YC2 (61%) and YC3 (67%). Estimated classification error was 1.4%. (C) Amino acid compound-specific isotope analysis results for migrant (M) PBFT, resident (R) PBFT, resident prey (Cololabis saira and Trachurus symmetricus), and resident predator (yellowfin tuna Thunnus albacares (YFT)). Number above icon shows sample size for each group. δ 15 N values shown are for non-trophic, source AAs, showing that differences in PBFT migrant bulk δ 15 N values are the result of feeding in a different food web with a lower δ 15 N baseline, and not due to trophic effects. 135

152 17 16 Bulk δ 15 N ( ) PBFT Migrants PBFT Residents Hot PBFT YFT Standard length (cm) Figure 5-4. Bulk white muscle δ 15 N values for all tuna used in this study. Wild PBFT are shown as migrants or residents, based on results of discriminant analysis. Training data for discriminant analysis (radioactive or hot PBFT (migrants) and YFT (residents)) are shown. Table 5-3. Amino acid compound-specific results for migrant and resident Pacific bluefin tuna Thunnus orientalis (PBFT) and CCLME residents yellowfin tuna T. albacares (YFT), jack mackerel Trachurus symmetricus, and Pacific saury Cololabis saira. sample group source amino acids mean δ 15 N (SD) weighted mean (SD) Pacific bluefin glycine (migrant) (1.06) (n = 3) serine 1.31 (1.46) (0.72) phenylalanine 9.60 (2.16) Pacific bluefin glycine 5.31 (1.5) (resident) (n = 3) serine 6.70 (1.5) 7.16 (0.81) phenylalanine (1.63) Pacific saury glycine 9.16 (1.5) (resident) (n = 3) serine 8.08 (1.5) 7.36 (0.50) phenylalanine 7.24 (0.58) jack mackerel glycine 9.78 (1.5) (resident) (n = 3) serine 9.61 (1.5) 8.19 (0.84) phenylalanine 9.35 (1.79) yellowfin tuna glycine 7.0 (0.44) (resident) (n = 5) serine 5.94 (0.81) 7.19 (0.36) phenylalanine 9.65 (0.92) 136

153 Number of individual PBFT PBFT YC1-2 PBFT YC2-4 migrants 1 year residents Time in CCLME (days) Figure 5-5. Estimates of time spent in CCLME for 130 PBFT using isotopic clock technique with white muscle δ 15 N values. Dashed line indicates year class 1 (grey dashed lines: mean ± SD), solid line indicates year-classes 2 and 3 (grey solid lines: mean ± SD). Note that all YC1 PBFT migrated from Japan less than 1 year before sampling. Older year classes migrated mostly more than a year before capture (CCLME residents), though some migrated less than 300 days before capture (Japan migrants). 137

154 25 Number of individual PBFT (A) PBFT (n = 130) PBFT YC1-2 (n = 61) PBFT YC2-4 (n = 69) 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Estimated month of arrival in CCLME (WM isotopic clock) Number of individual PBFT (B) (C) Estimated age (years) upon arrival in CCLME Estimated size (cm) upon arrival in CCLME Figure 5-6. (A) Histogram showing estimated month of entry into CCLME based on white muscle δ 15 N isotopic clock estimates for year-class (YC) 1-2 (white bars) and YC2-4 (grey bars). Few individuals entered the CCLME in late summer, fall, or early winter. (B) Estimated ages and (C) estimated sizes of 130 PBFT when they entered the CCLME, based on white muscle δ 15 N isotopic clock estimates. 138

155 5.5. Discussion Biogeochemical tools provide new means for elucidating life history, population structure and migration timelines in many fish (Ménard et al. 2007, Rooker et al. 2008, Graham et al. 2010, Secor 2010, Wells et al. 2010, Carlisle et al. 2012, Ramos and González-Solís 2012, Secor et al. 2012). In highly migratory species such as tunas, they are revolutionizing our capacity to conduct spatial and temporal movement patterns (Rooker et al. 2008, Graham et al. 2010, Secor 2010, Secor et al. 2012). In this study, we used three different biogeochemical analyses to examine the trans-oceanic migration patterns of Pacific bluefin tuna. Our analyses indicate that these tracers record the timing of migration from the WPO to the EPO and allow estimation of the residency time of PBFT in the CCLME. Furthermore, these techniques provide the capacity to detect whether an individual PBFT migrated to the CCLME in the past year or has been a multiyear resident in the region. Discriminant analysis indicates that our results are reliable (classification error = 1.4%) and that these techniques provide robust estimates. Our techniques revealed that some PBFT migrate later in life than 1-2 years, that timing differs between size classes, and PBFT arrive into the CCLME at different times. Thus, regional (WPO vs EPO) differences suggest that these are viable tools for analyzing the migration of Pacific migratory species that traverse the Pacific Ocean Regional differences Significant differences in δ 15 N values were observed between prey in the WPO and the EPO. This is likely due to oceanographic differences; as an eastern boundary current system, the CCLME is an upwelling system that brings 15 N-enriched nitrate to the surface waters which can be used by phytoplankton (Altabet and McCarthy 1985, Liu and 139

156 Kaplan 1989), while the WPO is more oligotrophic. These differences in the δ 15 N values of WPO and EPO phytoplankton propagate up local food webs, as the δ 15 N values of planktivorous fish species and krill in waters off Japan (Minami et al. 1995, Mitani et al. 2006, Takai et al. 2007) were depleted in 15 N relative to identical or trophically similar species in the CCLME (Miller et al. 2010, Madigan et al. 2012b) (Table 5-1). These regional δ 15 N value differences translate to top predators in each region. In waters off Japan, mako sharks and blue sharks have bulk WM δ 15 N values (13.7 and 12.0, respectively) (Takai et al. 2007), more than 3 lower than makos and blue sharks of similar size in the CCLME (16.4 and 15.2 ) (Madigan et al. 2012b). This indicates that the differences in oceanography between these two regions result in differences in baseline δ 15 N values that propagate up regional food webs, making δ 15 N values of predators distinct enough to discern residents of the WPO or EPO and track migrations between these regions. Radiocesium data provided a definitive marker of migration by PBFT from waters off Japan to the CCLME. Since presence of 134 Cs classifies these 14 fish as uneqivocal WPO migrants, their bulk WM δ 15 N values represent those of a PBFT that has recently migrated from the WPO to the EPO. Thus this relatively small (n=14) dataset enabled the interpretation of a larger dataset (n=130) of PBFT SIA data (bulk WM δ 15 N values) to infer migratory status with enhanced confidence and precision. We also demonstrate that δ 15 N values of individual amino acids provide complementary data that inform inferences of migratory and residency status. Data from AA-CSIA showed that the low bulk δ 15 N values observed in recently-migrated PBFT in the CCLME were a result of low source- 140

157 AA (such as glycine, serine, and phenylaline) δ 15 N values, confirming that migration (and not trophic differences) was the driver behind the bulk δ 15 N value differences. Figure 5-7. Results of calculations of migration timing for 14 Pacific bluefin tuna analyzed for 134 Cs in Estimates of time since departure from Japan are calculated from the 134 Cs: 137 Cs ratios in PBFT from Madigan et al. (Madigan et al. 2012a). Estimates of time since entering the CCLME are calculated using white muscle δ 15 N values from the same PBFT using the isotope turnover parameters reported in Madigan et al. (Madigan et al. 2012c). Grey bars and error bars represent means ± SD. Results of each method were significantly different at the p = 0.05 level (Mann-Whitney U-test). 141