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Bradley R. Moore - One of the best experts on this subject based on the ideXlab platform.
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Defining the Stock Structures of key commercial tunas in the Pacific Ocean II: Sampling considerations and future directions
Fisheries Research, 2020Co-Authors: Bradley R. Moore, Tim Adams, Valerie Allain, Johann D. Bell, Mark Bigler, Don Bromhead, Sangaa Clark, Campbell R. Davies, Karen Evans, Ueta FaasiliAbstract:Abstract Delineating the Stock Structure of highly-mobile, wide-ranging fishes subject to exploitation is a challenging task, yet one that is fundamental to optimal fisheries management. A case in point are Stocks of skipjack tuna (Katsuwonus pelamis), yellowfin tuna (Thunnus albacares), bigeye tuna (Thunnus obesus) and albacore tuna (Thunnus alalunga) in the Pacific Ocean, which support important commercial, artisanal, subsistence, and recreational fisheries, and contribute roughly 70 % of global commercial tuna catches. Although some spatial and temporal structuring is recognised within these Stocks, growing evidence from a range of approaches suggests that the Stock Structure of each tuna species is more complex than is currently assumed in both Stock assessment and climate change models, and in management regimes. In a move towards improving understanding of the Stock Structure of skipjack, yellowfin, bigeye and South Pacific albacore tunas in the Pacific Ocean, an international workshop was held in Noumea, New Caledonia, in October 2018 to review knowledge about their movement and Stock Structure in the region, define and discuss the main knowledge gaps and uncertainties concerning their Stock Structure, and develop biological sampling approaches to support the provision of this information. Here, we synthesise the discussions of this latter component. For each tuna species, we identify several general sampling considerations needed to reduce uncertainty, including i) the need for broadscale sampling in space, ideally covering each species’ distribution, targeting adults in spawning condition and adopting a phased approach; ii) the need for temporally-repeated sampling of the same geographical areas to assess stability in observed patterns over time; iii) the need to resolve patterns in spatial dynamics, such as those resulting from movements associated with the seasonal extensions of poleward flowing currents, from underlying Stock Structure, iv) the importance of adopting a multidisciplinary approach to Stock identification, and v) the need for careful planning of logistics and coordination of sampling efforts across agencies. Finally, we present potential sampling designs that could be adopted to help overcome uncertainties around the initial identification of Stocks and the provenance, mixing and proportional contributions of individuals in harvested assemblages, as well as how these uncertainties could be accounted for in fisheries management via the use of management strategy evaluation.
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defining the Stock Structures of key commercial tunas in the pacific ocean i current knowledge and main uncertainties
Fisheries Research, 2020Co-Authors: Bradley R. Moore, Jessica H. Farley, Johann D. Bell, Karen Evans, Peter M Grewe, John M Hampton, Amandine D Marie, Carolina V MinteveraAbstract:Abstract Tunas are the focus of significant fisheries in the Pacific Ocean, where landings of four species – skipjack tuna (Katsuwonus pelamis), yellowfin tuna (Thunnus albacares), bigeye tuna (Thunnus obesus) and albacore tuna (Thunnus alalunga) – constitute approximately 70 % of the global tuna catch. Stock assessments for skipjack, yellowfin and bigeye tunas in the Pacific Ocean currently assume eastern and western Stocks. For albacore tuna, separate North Pacific Ocean and South Pacific Ocean Stocks are currently assumed. In each case, these geographic definitions reflect the historical development of fisheries management across the Pacific rather than biological considerations. There is widespread agreement that uncertainties surrounding the Stock Structures of these four tuna species could have important impacts on the population dynamics models used to assess their status and inform management options. Knowledge of Stock Structure is also essential for improved modelling of the effects of climate change on tuna distribution and abundance and associated implications for fisheries. This paper reviews current knowledge and understanding of the Stock Structures of skipjack, yellowfin, bigeye and South Pacific albacore tunas in the Pacific Ocean, by exploring available literature relating to their biology, movement and spatial dynamics. As a guide for future research in this area, we identify the main uncertainties in defining the Stock Structure of these four tunas in the Pacific, including i) spawning dynamics; ii) the degree of spawning area fidelity and localised residency; iii) the provenance of individuals in, and proportional contributions of self-replenishing populations to, fishery catches within the Pacific Ocean; iv) linkages with adjacent ‘Stocks’; v) the effects of climate change on Stock Structure and proportional contributions of self-replenishing populations to fisheries; and vi) the implications of improved knowledge of tuna Stock Structure for Stock assessment and climate change model assumptions and fisheries management. We also briefly propose some approaches that future studies could use to address these uncertainties.
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Stock Structure of blue threadfin eleutheronema tetradactylum across northern australia as indicated by parasites
Journal of Fish Biology, 2011Co-Authors: David Welch, Aaron C. Ballagh, Stephen J. Newman, Bradley R. Moore, Quentin Allsop, Jason Stapley, R J G LesterAbstract:The parasite fauna of the blue threadfin Eleutheronema tetradactylum, collected from 14 sites across northern Australia, was examined to evaluate the degree of movement and subsequent Stock Structure of the fish. Univariate and multivariate analysis of nine ‘permanent’ parasite species [the nematodes Anisakis (type I) and Terranova (type II), the cestodes Otobothrium australe, Pterobothrium pearsoni, Pterobothrium sp. A, Callitetrarhynchus gracilis, Parotobothrium balli and Nybelinia sp., and the acanthocephalan Pomphorhynchus sp.] demonstrated little similarity between sites, indicating limited mixing and therefore long-term separation of post-juvenile fish. As such, the effects of fishing are likely to be localized within the current administrative boundaries, implying little need for interstate co-operative management. Within each jurisdiction, management of E. tetradactylum populations, including the establishment of harvest strategies and fishery regulations, should be conducted in a way that recognizes the resident nature of the fish.
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Defining the Stock Structure of Northern Australia's Threadfin Salmon Species
2010Co-Authors: David Welch, Aaron C. Ballagh, Stephen J. Newman, Robert J. G. Lester, Bradley R. Moore, L. Van Herwerden, John B. Horne, Quentin Allsop, Thor Saunders, Jason StapleyAbstract:The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources relies on robust information on the resource status. In northern Australia management of inshore fisheries that target blue threadfin (Eleutheronema tetradactylum) and king threadfin (Polydactylus macrochir) is independent for each of these jurisdictions. However, the lack of information on the Stock Structure and biology of threadfins means that the appropriate spatial scale of management is not known and assessment of the resource status is not possible. Establishing the Stock Structure of blue and king threadfin would also immensely improve the relevance of future resource assessments for fishery management of threadfins across northern Australia. This highlighted the urgent need for Stock Structure information for this species. The impetus for this project came from unsuccessful attempts in Queensland to conduct Stock assessments for the king and blue threadfin resource, research that indicated the potential for localised Stock Structure, and the assessment that blue and king threadfin in Western Australia were fully and over-exploited respectively. The project objectives were to determine the Stock Structure of blue and king threadfin across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the Stock Structure of each species, including: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) stable isotope ratios, parasite abundances, and life history parameters (growth and size at sex change). This holistic approach to Stock identification gave the advantage of using techniques that were informative about the fish's life history at different spatial and temporal scales, increasing the likelihood of detecting different Stocks where they existed and providing greater certainty in the signals given by the data. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Life history characteristics are influenced by both genetic and environmental factors. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year at locations along the east coast, within the Gulf of Carpentaria (GoC), and the Western Australian coastline. Using each of the techniques to compare fish samples collected from each of these locations we tested the null hypothesis for each species that they were comprised of a single homogeneous population across northern Australia. The null hypothesis was rejected after the first year leading us to re-sample the first year locations to test for temporal stability in Stock Structure, and to assess Stock Structure at finer spatial scales by sampling at other locations as well. Blue threadfin showed strong site fidelity with localised Stock structuring evident and adjacent Stocks separated by only tens of kilometres. This was found even where continuous habitat was present along coastlines with no obvious barriers to mixing. This was shown by clear and consistent signals of differences between fish from different locations including genetic differences. Blue threadfins also show what is called 'isolation by distance' whereby the farther apart Stocks are from one another the greater the genetic differences between them. There was also extreme variability found in the life history characteristics among the different Stocks. Similarly, king threadfin also showed fine scale Stock Structure with limited mixing between adjacent Stocks separated by tens to hundreds of kilometres. Where there was sufficient distances separating them, or bio-geographical barriers such as headlands separating adjacent Stocks, king threadfin were also genetically distinct. King threadfin also exhibited 'isolation by distance' though the pattern was notas strong as in blue threadfin. King threadfins also show a high degree of variation in their life history characteristics among the different Stocks identified. Further, in the eastern Gulf of Carpentaria evidence of overfishing of king threadfin was evident in the truncation of size and age Structures compared with samples taken over a decade ago, and the presence of females much smaller than found elsewhere or reported from the same region previously. The management implications of these results indicate the need for management of threadfin fisheries in Australia to be carried out on regional scales much finer than are currently in place. Given the fine spatial scale Stock Structure evident for both threadfin species management at local scales may not be pragmatic. At the very least management should consider these spatial dynamics by implementing monitoring and assessment of threadfin fisheries guided by the Stocks identified in this study, and by the likely spatial scale of Stocks indicated by these results. We also encourage the assessment of the threadfin resource status for the major fishery region in northern Australia. We recommend that the signals of overfishing detected for king threadfin in the Gulf of Carpentaria need to be investigated to assess the status of the Stocks present in that region.
Brian M Shamblin - One of the best experts on this subject based on the ideXlab platform.
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geographic patterns of genetic variation in a broadly distributed marine vertebrate new insights into loggerhead turtle Stock Structure from expanded mitochondrial dna sequences
PLOS ONE, 2014Co-Authors: Brian M Shamblin, Alan B Bolten, Karen A Bjorndal, Alberto F Abreugrobois, Luis Cardona, Carlos Carreras, Marcel Clusa, Catalina Monzonarguello, Campbell J Nairn, Janne T NielsenAbstract:Previous genetic studies have demonstrated that natal homing shapes the Stock Structure of marine turtle nesting populations. However, widespread sharing of common haplotypes based on short segments of the mitochondrial control region often limits resolution of the demographic connectivity of populations. Recent studies employing longer control region sequences to resolve haplotype sharing have focused on regional assessments of genetic Structure and phylogeography. Here we synthesize available control region sequences for loggerhead turtles from the Mediterranean Sea, Atlantic, and western Indian Ocean basins. These data represent six of the nine globally significant regional management units (RMUs) for the species and include novel sequence data from Brazil, Cape Verde, South Africa and Oman. Genetic tests of differentiation among 42 rookeries represented by short sequences (380 bp haplotypes from 3,486 samples) and 40 rookeries represented by long sequences (,800 bp haplotypes from 3,434 samples) supported the distinction of the six RMUs analyzed as well as recognition of at least 18 demographically independent management units (MUs) with respect to female natal homing. A total of 59 haplotypes were resolved. These haplotypes belonged to two highly divergent global lineages, with haplogroup I represented primarily by CC-A1, CC-A4, and CC-A11 variants and haplogroup II represented by CC-A2 and derived variants. Geographic distribution patterns of haplogroup II haplotypes and the nested position of CCA11.6 from Oman among the Atlantic haplotypes invoke recent colonization of the Indian Ocean from the Atlantic for both global lineages. The haplotypes we confirmed for western Indian Ocean RMUs allow reinterpretation of previous mixed Stock analysis and further suggest that contemporary migratory connectivity between the Indian and Atlantic Oceans occurs on a broader scale than previously hypothesized. This study represents a valuable model for conducting comprehensive international cooperative data management and research in marine ecology.
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expanded mitochondrial control region sequences increase resolution of Stock Structure among north atlantic loggerhead turtle rookeries
Marine Ecology Progress Series, 2012Co-Authors: Brian M Shamblin, Peter H. Dutton, Alan B Bolten, Karen A Bjorndal, Janne T Nielsen, Alberto F Abreugrobois, Kimberly J Reich, Blair E Witherington, Dean A Bagley, Llewellyn M EhrhartAbstract:The southeastern USA hosts the largest nesting concentration of loggerhead turtles Caretta caretta in the Atlantic. Regionally significant nesting also occurs along the Caribbean coast of Mexico, in Cuba, and in the Bahamas. Previous studies of North Atlantic loggerhead turtle rookeries based on a 380 bp fragment of the mitochondrial control region supported recognition of 8 demographically independent nesting populations (management units) in the Northwest Atlantic in addition to Cape Verde in the eastern Atlantic. Recent analysis of expanded mitochon- drial control region sequences revealed additional genetic diversity and increased population Structure between western and eastern Atlantic loggerhead turtle rookeries. We se quenced an 817 bp mitochondrial DNA fragment in 2427 samples from nesting beaches in the southeastern USA, Cay Sal Bank, Bahamas, and Quintana Roo, Mexico. Pairwise FST comparisons, pairwise exact tests of population differentiation, and analysis of molecular variance support previously proposed management unit designations and additionally indicate that southeastern and south- western Florida rookeries should be recognized as distinct management units. Therefore, North- west Atlantic loggerhead turtle rookeries can be subdivided into 10 management units, corre- sponding to the beaches from (1) Virginia through northeastern Florida, (2) central eastern Florida, (3) southeastern Florida, (4) Dry Tortugas, Florida, (5) Cay Sal, Bahamas, (6) southwestern Cuba, (7) Quintana Roo, Mexico, (8) southwestern Florida, (9) central western Florida, and (10) northwestern Florida. We confirmed increased resolution of Stock Structure between many North- west Atlantic management units and the Cape Verde rookery with the expanded control region haplotypes.
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mitogenomic sequences better resolve Stock Structure of southern greater caribbean green turtle rookeries
Molecular Ecology, 2012Co-Authors: Brian M Shamblin, Alan B Bolten, Karen A Bjorndal, Zandy Hillisstarr, Ian Lundgren, Eugenia Naromaciel, Campbell J NairnAbstract:Analyses of mitochondrial control region polymorphisms have supported the presence of several demographically independent green turtle (Chelonia mydas) rookeries in the Greater Caribbean region. However, extensive sharing of common haplotypes based on 490-bp control region sequences confounds assessment of the scale of natal homing and population Structure among regional rookeries. We screened the majority of the mitochondrial genomes of 20 green turtles carrying the common haplotype CM-A5 and representing the rookeries of Buck Island, St. Croix, United States Virgin Islands (USVI); Aves Island, Venezuela; Galibi, Suriname; and Tortuguero, Costa Rica. Five singlenucleotide polymorphisms (SNPs) were identified that subdivided CM-A5 among regions. Mitogenomic pairwise /ST values of eastern Caribbean rookery comparisons were markedly lower than the respective pairwise FST values. This discrepancy results from the presence of haplotypes representing two divergent lineages in each rookery, highlighting the importance of choosing the appropriate test statistic for addressing the study question. Haplotype frequency differentiation supports demographic independence of Aves Island and Suriname, emphasizing the need to recognize the smaller Aves rookery as a distinct management unit. Aves Island and Buck Island rookeries shared mitogenomic haplotypes; however, frequency divergence suggests that the Buck Island rookery is sufficiently demographically isolated to warrant management unit status for the USVI rookeries. Given that haplotype sharing among rookeries is common in marine turtles with cosmopolitan distributions, mitogenomic sequencing may enhance inferences of population Structure and phylogeography, as well as improve the resolution of mixed Stock analyses aimed at estimating natal origins of foraging turtles.
Hilario Murua - One of the best experts on this subject based on the ideXlab platform.
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otolith microchemistry a useful tool for investigating Stock Structure of yellowfin tuna thunnus albacares in the indian ocean
Marine and Freshwater Research, 2019Co-Authors: Iraide Artetxearrate, Iker Zudaire, Igaratza Fraile, David A Crook, Alan Greig, Haritz Arrizabalaga, Hilario MuruaAbstract:A better understanding of the Stock Structure of yellowfin tuna (Thunnus albacares) in the Indian Ocean is needed to ensure the sustainable management of the fishery. In this study, carbon and oxygen stable isotopes (δ13C and δ18O) and trace elements (138Ba, 55Mn, 25Mg and 88Sr) were measured in otoliths of young-of-the-year (YOY) and age-1 yellowfin tuna collected from the Mozambique Channel and north-west Indian Ocean regions. Elemental profiles showed variation in Ba, Mg and Mn in YOY otolith composition, but only Mn profiles differed between regions. Differences in YOY near-core chemistry were used for natal-origin investigation. Ba, Mg and Mn were sufficiently different to discriminate individuals from the two regions, in contrast with carbon and oxygen stable isotopes. A linear discriminant analysis resulted in 80% correct classification of yellowfin tuna to their natal origin. Classification success increased to 91% using a random forest algorithm. Finally, a unique larval source was detected among age-1 yellowfin tuna. The signal of these fish resembled that of YOY from a north-west Indian Ocean origin, highlighting the importance of local production. The present study supports the use of otolith chemistry as a promising approach to analyse yellowfin Stock Structure in the Indian Ocean.
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putting all the pieces together integrating current knowledge of the biology ecology fisheries status Stock Structure and management of yellowfin tuna thunnus albacares
Reviews in Fish Biology and Fisheries, 2017Co-Authors: Carlo Pecoraro, Iker Zudaire, Hilario Murua, Nathalie Bodin, Paul Taconet, Pindaro Diazjaimes, Alessia Cariani, Fausto Tinti, Emmanuel ChassotAbstract:Yellowfin tuna (Thunnus albacares; YFT) is an apex marine predator inhabiting tropical and sub-tropical pelagic waters. It supports the second largest tuna fishery in the world. Here, we review the available literature on YFT to provide a detailed overview of the current knowledge of its biology, ecology, fisheries status, Stock Structure and management, at global scale. YFT are characterized by several peculiar anatomical and physiological traits that allow them to survive in the oligotrophic waters of the pelagic realm. They are opportunistic feeders, which allows fast growth and high reproductive outputs. Globally, YFT fisheries have expanded over the last century, progressively moving from coastal areas into the majority of sub-tropical and tropical waters. This expansion has led to a rapid increase in global commercial landings, which are predominantly harvested by industrial longline and purse seine fleets. For management purposes, YFT is divided into four Stocks, each of which is currently managed by a separate tuna Regional Fisheries Management Organization. Our current understanding of YFT Stock Structure is, however, still uncertain, with conflicting evidence arising from genetic and tagging studies. There is, moreover, little information about their complex life-history traits or the interactions of YFT populations with spatio-temporally variable oceanographic conditions currently considered in Stock assessments. What information is available, is often conflicting at the global scale. Finally, we suggest future research directions to manage this valuable resource with more biological realism and more sustainable procedures.
Emmanuel Chassot - One of the best experts on this subject based on the ideXlab platform.
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putting all the pieces together integrating current knowledge of the biology ecology fisheries status Stock Structure and management of yellowfin tuna thunnus albacares
Reviews in Fish Biology and Fisheries, 2017Co-Authors: Carlo Pecoraro, Iker Zudaire, Hilario Murua, Nathalie Bodin, Paul Taconet, Pindaro Diazjaimes, Alessia Cariani, Fausto Tinti, Emmanuel ChassotAbstract:Yellowfin tuna (Thunnus albacares; YFT) is an apex marine predator inhabiting tropical and sub-tropical pelagic waters. It supports the second largest tuna fishery in the world. Here, we review the available literature on YFT to provide a detailed overview of the current knowledge of its biology, ecology, fisheries status, Stock Structure and management, at global scale. YFT are characterized by several peculiar anatomical and physiological traits that allow them to survive in the oligotrophic waters of the pelagic realm. They are opportunistic feeders, which allows fast growth and high reproductive outputs. Globally, YFT fisheries have expanded over the last century, progressively moving from coastal areas into the majority of sub-tropical and tropical waters. This expansion has led to a rapid increase in global commercial landings, which are predominantly harvested by industrial longline and purse seine fleets. For management purposes, YFT is divided into four Stocks, each of which is currently managed by a separate tuna Regional Fisheries Management Organization. Our current understanding of YFT Stock Structure is, however, still uncertain, with conflicting evidence arising from genetic and tagging studies. There is, moreover, little information about their complex life-history traits or the interactions of YFT populations with spatio-temporally variable oceanographic conditions currently considered in Stock assessments. What information is available, is often conflicting at the global scale. Finally, we suggest future research directions to manage this valuable resource with more biological realism and more sustainable procedures.
Alan B Bolten - One of the best experts on this subject based on the ideXlab platform.
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geographic patterns of genetic variation in a broadly distributed marine vertebrate new insights into loggerhead turtle Stock Structure from expanded mitochondrial dna sequences
PLOS ONE, 2014Co-Authors: Brian M Shamblin, Alan B Bolten, Karen A Bjorndal, Alberto F Abreugrobois, Luis Cardona, Carlos Carreras, Marcel Clusa, Catalina Monzonarguello, Campbell J Nairn, Janne T NielsenAbstract:Previous genetic studies have demonstrated that natal homing shapes the Stock Structure of marine turtle nesting populations. However, widespread sharing of common haplotypes based on short segments of the mitochondrial control region often limits resolution of the demographic connectivity of populations. Recent studies employing longer control region sequences to resolve haplotype sharing have focused on regional assessments of genetic Structure and phylogeography. Here we synthesize available control region sequences for loggerhead turtles from the Mediterranean Sea, Atlantic, and western Indian Ocean basins. These data represent six of the nine globally significant regional management units (RMUs) for the species and include novel sequence data from Brazil, Cape Verde, South Africa and Oman. Genetic tests of differentiation among 42 rookeries represented by short sequences (380 bp haplotypes from 3,486 samples) and 40 rookeries represented by long sequences (,800 bp haplotypes from 3,434 samples) supported the distinction of the six RMUs analyzed as well as recognition of at least 18 demographically independent management units (MUs) with respect to female natal homing. A total of 59 haplotypes were resolved. These haplotypes belonged to two highly divergent global lineages, with haplogroup I represented primarily by CC-A1, CC-A4, and CC-A11 variants and haplogroup II represented by CC-A2 and derived variants. Geographic distribution patterns of haplogroup II haplotypes and the nested position of CCA11.6 from Oman among the Atlantic haplotypes invoke recent colonization of the Indian Ocean from the Atlantic for both global lineages. The haplotypes we confirmed for western Indian Ocean RMUs allow reinterpretation of previous mixed Stock analysis and further suggest that contemporary migratory connectivity between the Indian and Atlantic Oceans occurs on a broader scale than previously hypothesized. This study represents a valuable model for conducting comprehensive international cooperative data management and research in marine ecology.
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expanded mitochondrial control region sequences increase resolution of Stock Structure among north atlantic loggerhead turtle rookeries
Marine Ecology Progress Series, 2012Co-Authors: Brian M Shamblin, Peter H. Dutton, Alan B Bolten, Karen A Bjorndal, Janne T Nielsen, Alberto F Abreugrobois, Kimberly J Reich, Blair E Witherington, Dean A Bagley, Llewellyn M EhrhartAbstract:The southeastern USA hosts the largest nesting concentration of loggerhead turtles Caretta caretta in the Atlantic. Regionally significant nesting also occurs along the Caribbean coast of Mexico, in Cuba, and in the Bahamas. Previous studies of North Atlantic loggerhead turtle rookeries based on a 380 bp fragment of the mitochondrial control region supported recognition of 8 demographically independent nesting populations (management units) in the Northwest Atlantic in addition to Cape Verde in the eastern Atlantic. Recent analysis of expanded mitochon- drial control region sequences revealed additional genetic diversity and increased population Structure between western and eastern Atlantic loggerhead turtle rookeries. We se quenced an 817 bp mitochondrial DNA fragment in 2427 samples from nesting beaches in the southeastern USA, Cay Sal Bank, Bahamas, and Quintana Roo, Mexico. Pairwise FST comparisons, pairwise exact tests of population differentiation, and analysis of molecular variance support previously proposed management unit designations and additionally indicate that southeastern and south- western Florida rookeries should be recognized as distinct management units. Therefore, North- west Atlantic loggerhead turtle rookeries can be subdivided into 10 management units, corre- sponding to the beaches from (1) Virginia through northeastern Florida, (2) central eastern Florida, (3) southeastern Florida, (4) Dry Tortugas, Florida, (5) Cay Sal, Bahamas, (6) southwestern Cuba, (7) Quintana Roo, Mexico, (8) southwestern Florida, (9) central western Florida, and (10) northwestern Florida. We confirmed increased resolution of Stock Structure between many North- west Atlantic management units and the Cape Verde rookery with the expanded control region haplotypes.
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mitogenomic sequences better resolve Stock Structure of southern greater caribbean green turtle rookeries
Molecular Ecology, 2012Co-Authors: Brian M Shamblin, Alan B Bolten, Karen A Bjorndal, Zandy Hillisstarr, Ian Lundgren, Eugenia Naromaciel, Campbell J NairnAbstract:Analyses of mitochondrial control region polymorphisms have supported the presence of several demographically independent green turtle (Chelonia mydas) rookeries in the Greater Caribbean region. However, extensive sharing of common haplotypes based on 490-bp control region sequences confounds assessment of the scale of natal homing and population Structure among regional rookeries. We screened the majority of the mitochondrial genomes of 20 green turtles carrying the common haplotype CM-A5 and representing the rookeries of Buck Island, St. Croix, United States Virgin Islands (USVI); Aves Island, Venezuela; Galibi, Suriname; and Tortuguero, Costa Rica. Five singlenucleotide polymorphisms (SNPs) were identified that subdivided CM-A5 among regions. Mitogenomic pairwise /ST values of eastern Caribbean rookery comparisons were markedly lower than the respective pairwise FST values. This discrepancy results from the presence of haplotypes representing two divergent lineages in each rookery, highlighting the importance of choosing the appropriate test statistic for addressing the study question. Haplotype frequency differentiation supports demographic independence of Aves Island and Suriname, emphasizing the need to recognize the smaller Aves rookery as a distinct management unit. Aves Island and Buck Island rookeries shared mitogenomic haplotypes; however, frequency divergence suggests that the Buck Island rookery is sufficiently demographically isolated to warrant management unit status for the USVI rookeries. Given that haplotype sharing among rookeries is common in marine turtles with cosmopolitan distributions, mitogenomic sequencing may enhance inferences of population Structure and phylogeography, as well as improve the resolution of mixed Stock analyses aimed at estimating natal origins of foraging turtles.
