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Marine reserves have rapid and lasting effects. Ecology Letters, vol. Heckler, G. Population dynamics of the seabob shrimp Xiphopenaeus kroyeri Dendrobranchiata, Penaeidae in south-eastern Brazil. African Journal of Marine Science, vol. Shrimps and prawns of the world: An annotated catalogue of species of interest to fisheries. Fisheries Synopsis. Marine protected areas and ocean basin management. Aquatic Conservation: marine and freshwater ecosystems, vol. Lubchenco, J.
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Habitat preference of Burkenroad Crustacea: Decapoda in a tropical coastal lagoon, southwest Gulf of Mexico. How marine upwelling influences the distribution of Artemesia longinaris Decapoda: Penaeoidea? Sancinetti, G. Population biology of the commercially exploited shrimp Artemesia longinaris Decapoda: Penaeidae in an upwelling region in the Western Atlantic: comparisons at different latitudes.
Semensato, X. Artemesia longinarisBoletim do Instituto de Pesca, vol. Masters Dissertation in Biology. A Corrente do Brasil ao largo da costa leste brasileira. Boletim do Instituto Paulista de Oceanografia, vol. Marine Biology, vol. Valentini, H. COSTA, ed. Nas redes da pesca artesanal.
ZAR, J. Biostatistical analysis. Upper Saddle River: Prentice Hall. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Services on Demand Journal. Articles Abundance and spatial-temporal distribution of the shrimp Xiphopenaeus kroyeri Decapoda: Penaeidae : an exploited species in southeast Brazil. References Acha, E. Received: March 24, ; Accepted: June 10, How to cite this article. However, in western Atlantic green turtles, microsatellites discerned population structure that was congruent with but weaker than that identified by mtDNA control region sequences Naro-Maciel et al.
Thus, while it is clear that combining mtDNA and nuclear markers can provide insight into male-mediated gene flow and population boundaries, patterns may differ between regions and species, and additional studies are needed to clarify their generality and context dependencies. As technological advances continue to improve researchers' abilities to generate robust nuclear data that are comparable across laboratories, nuclear markers are poised to complement mtDNA in further advancing our understanding of female and male natal homing and fine-scale population structure.
Along with other approaches such as flipper tagging, satellite telemetry, and stable isotope analysis, genetics have been instrumental in quantifying connectivity between rookeries and foraging grounds. Early work in the Atlantic recognized the importance of both ocean current patterns and natal homing behavior in shaping the distribution of juvenile green turtles at foraging sites Luke et al. Recently, improved sampling efforts have coincided with advances in statistical analyses such as MSA to clarify how populations are linked to foraging habitats see Box 1.
This provides researchers and practitioners working in foraging grounds with knowledge about where the turtles are coming from, which is informative for public outreach engagement, identifying regional and international management partners, and integrating threats at nesting beaches and foraging grounds into risk assessments.
This information also enables estimation of proportional contributions of each source nesting stock to the foraging population. With the advancements defining rookery population structure across the Pacific, an increasing number of foraging grounds have now been analyzed using MSA across northern Australia Dethmers et al. These studies have shown considerable variation in results, with some foraging ground aggregations being composed mostly of turtles from the nearest stock see Glossary such as Hawaii, Aru, Gulf of Carpentaria, and the northern and southern Great Barrier Reef Dutton et al.
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While these studies have expanded our understanding of connectivity between rookeries and foraging areas, they do not provide information on migration routes or the factors that influence the dispersal of turtles. In recent years, multidisciplinary approaches have combined MSA and high-resolution ocean circulation modeling to further our understanding of marine turtle movement e. These studies have revealed that while ocean currents play a vital role in the spatial distribution of turtles they do not always correlate with MSA results, suggesting that other factors such as swimming behavior play important roles in the distribution of turtles Putman and He, ; Hays et al.
Finally, MSA can also help identify how threats and conservation efforts in foraging areas may affect nesting populations and vice versa, and could allow scientists and managers to study changes in population composition over time also see Human Impacts and Threat Assessment section. While considerable progress has been made, it is important to recognize that knowledge gaps still exist, and efforts to sample new rookeries and employ higher resolution markers need to continue to enable accurate MSA. This is highlighted by the fact that orphan haplotypes see Glossary are still common, and several recent cases illustrate how misinterpretation of MSA results may lead to incorrect conclusions under such scenarios.
In one instance, incomplete baseline sampling led to the potential misinterpretation of MSA results for foraging juveniles. CM-A13 is the dominant Mediterranean haplotype, and was detected among foraging juveniles in the Greater Caribbean region. This introduced the possibility of dispersal from the Mediterranean into the western Atlantic Bjorndal and Bolten, ; Anderson et al.
However, this haplotype was later found to occur at low frequency in the Florida nesting aggregation Shamblin et al. Analysis of the mtSTR for CM-A13 turtles nesting and foraging in Florida yielded a shared repeat haplotype that was not among the 33 described thus far from the Mediterranean Tikochinski et al. An MSA of juvenile green turtles in Texas foraging grounds suggested a large Florida rookery contribution based on the presence of these haplotypes at high frequencies Anderson et al.
Yet later analysis of the green turtle rookery at Rancho Nuevo, Tamaulipas, Mexico found CM-A1 and CM-A3 in the same frequencies as the central Florida MU, so the source of the majority of juveniles foraging in Texas remained unresolved using standard markers Shamblin et al. This marker demonstrated that turtles nesting in Florida and Tamaulipas represented distinct populations.
The case studies discussed above for green turtles highlight several important insights for using genetics to inform our understanding of population boundaries and connectivity. First, the presence of multiple MUs along the Florida and Mexican coasts demonstrate the importance of sampling the complete geographic extent of a nesting aggregation to test for structure, rather than assuming none is present. Second, the CM-A13 story from the western Atlantic reinforces the importance of adequate rookery sampling to capture rare haplotypes that are present at low frequencies.
Third, the Texas foraging aggregation example highlights that a low frequency of orphan haplotypes from a foraging aggregation does not necessarily imply that all potential source rookeries have been adequately sampled. As haplotypes are subdivided into ever-larger numbers of distinct genetic markers, there is also a greater need to increase sampling depth at rookeries and foraging aggregations to reduce sampling error.
This includes sampling of males at breeding grounds, which is a frequently overlooked component necessary to estimate male-mediated gene flow and define population boundaries. In addition to the examples discussed above, many new genetic studies of nesting and foraging grounds in green turtles and other species are already underway, guaranteeing improvement of our understanding of marine turtle population boundaries and connectivity in the future. However, despite these advances, challenges in the interpretation of genetic data also remain. Turtle mitochondrial DNA evolves slowly relative to that of many other vertebrate species Avise et al.
This may diminish the ability of these genetic markers to detect such demographic changes, and consequently, apparent lack of population structure may reflect a lack of power of the markers employed rather than true panmixia, particularly at demographic levels. Additionally, genetic differentiation in marine turtles is typically not well correlated with geographic distance, so there is no universal benchmark that can predict the scale of structure across populations.
In many cases, rookeries several hundreds of kilometers away are not genetically differentiated using traditional markers, but may not have significant contemporary demographic connectivity. Therefore, best practices entail understanding the strengths and limitations of each genetic dataset, and evaluating it along with data from complementary sources e. Integrating this information helps ensure that the best available science is used to inform management decisions.
While genetic data are key components of these evaluations, in some cases there may be valid reasons to consider treating rookeries as demographically distinct for management, even in the absence of genetic evidence that they are isolated. Age to maturity ATM is one of the key parameters required for estimating how long recovery could take for depleted populations because it is needed to calculate generation time.
Determining ATM is difficult in marine turtles due to challenges related to both longevity and life history, and both empirical and indirect approaches have been pursued. For example, coded wire tags were injected into juvenile Kemp's ridley turtles Lepidochelys kempii , and recovered via dead stranded animals years later to estimate a minimum ATM of 10—14 years Shaver and Caillouet, ; Caillouet et al. Skeletochronology has also shed light on ATM in green, loggerhead, and leatherback turtles Avens et al. The general consensus emerging from these studies, is that each species and perhaps each population may have different ATM ranges.
Techniques such as genetic CMR offer exciting new opportunities to directly measure ATM, however the process may require significant cost and long-term commitment of several decades, depending on the species. The project continues annually, with new nesting females being compared with hatchling turtles that left the beach years earlier.
To date, there have been no matches K. Stewart and P. Dutton, unpublished data , but continual investigation using microsatellites in combination with new SNP markers should yield results that are informative for leatherback ATM estimation in the near future albeit only for the female portion of the population.
This genetic fingerprinting technique also has potential for estimating other parameters essential to accurate population models for conservation management, such as survivorship from hatchling stage to adulthood. In addition, much else may be learned from knowing the genetic identities of thousands of individuals. For example, leatherback tissue samples from stranded animals, in-water captures and bycatch may all be genetically identified and compared to known individuals through comparison to data from the larger stocks or from hatchlings sampled at Sandy Point.
However, reliably detecting matches requires profiling a high proportion of the population, and for some species the turtles are too numerous or accessing all potential nesting habitat is not feasible. Given these constraints as well as the costs and required time investment, this approach is currently best applied under certain contexts, such as in smaller populations where turtles have high site fidelity, long-term project investment is feasible including the capacity to store and track DNA samples for years to decades , and where there are clear research questions Table 3.
However, rapidly evolving high-throughput technologies with the capacity to analyze thousands of samples concurrently will make it more feasible to conduct mass-tagging experiments in the future, provided that infrastructural support is available. Table 3. Genetic fingerprinting may also yield important information about a component of the adult marine turtle population that is rarely assessed, the males. Questions related to the sex ratios of breeding adults, mating patterns such as levels of multiple paternity, and male reproductive site fidelity may all be answered through intensive studies of nesting females and their hatchlings.
By comparing maternal and hatchling leatherback genetic identities at Sandy Point, Stewart and Dutton , were able to reconstruct the genetic identities of individual males contributing to each nest laid during several nesting seasons. Using this approach, males may be identified without being sampled directly Wright et al. Then by comparing all male genetic identities within a nesting season, the number of successful breeding males may be determined, providing an annual population census for all males and females.
However, it is important to note that these estimates represent the minimum number of breeding males, since all males may not successfully sire offspring due to mating and sperm competition. This work also requires consistent monitoring of females and nests directly because the maternal identity of each nest must be known to assess females and hatchlings and then by inference, the male identities.
In addition, the levels of multiple paternity at breeding sites are able to be determined with this approach targeting females and hatchlings. Multiple paternity has been detected in hawksbills Phillips et al. However, to be successful, this approach requires consistent and comprehensive monitoring over time, and male turtles without any or fewer reproductive successes due to competition and other factors can be missed.
Nonetheless, this application of genetic fingerprinting has the potential to advance our understanding of how males contribute to nesting populations. Genetic studies on males may be undertaken in conjunction with other methods, such as satellite tracking Hays et al. By identifying males that have made reproductive contributions to each clutch, we can also assign individual hatchlings to fathers and assess the relative contributions by different fathers for clutches with multiple paternity , and therefore gain insight on reproductive strategies and success for the males as well as the females Stewart and Dutton, However, complementary studies sampling in-water males at breeding grounds are needed to assess the number of males in the population with no reproductive success e.
Operational sex ratios OSRs or breeding sex ratios BSRs are important to understand and monitor over time, particularly given growing concern that climate change will affect sand temperatures where marine turtle nests incubate and alter hatchling sex ratios. As clutches of hatchlings are generally female-biased Wright et al.
To date, from the studies that looked at this ratio specifically, there does not appear to be a reduction in the proportion of males in breeding populations, despite there being female biases in the hatchling sex ratios. For example, Wright et al. In all of these studies, there were more males than females detected within the breeding population within a single year. Developing baselines for populations for OSRs or BSRs will be important for monitoring risk from climate change to populations over time.
Robust estimates of reproductive vital rates such as clutch frequency, the number of clutches a female lays in a given nesting season, and remigration interval the number of years a female skips between nesting seasons are important for monitoring and modeling population recovery. However, some females may disperse their nests beyond the limits of the areas of beach monitoring for tagging or observation, or there may be insufficient resources to conduct consistent monitoring, leading to missed turtles, sparse recapture data, and biased estimates of these key parameters.
Shamblin et al. This type of sampling allows genetic CMR on spatial scales that would be logistically impossible to replicate through traditional tagging approaches. A subpopulation-scale genetic CMR project has been underway since for loggerhead turtles nesting in the United States north of Florida to refine nesting female abundance estimates, assess reproductive parameters, determine the level of nest site fidelity, and calculate annual survival rates www. Nest sampling may also supplement traditional tagging approaches thus improving annual censuses of nesting populations where nesting females cannot be consistently observed.
For example, Frey et al. They were able to reconstruct genotypes for the mothers that were not observed and match unknown nests to mothers that had been sampled. They found that the number of nesting females in Texas was likely to have been underestimated based solely on nest counts or on the number of known mothers. Though it is well-established that many different human threats impact marine turtles, it is challenging to link human activities to population level effects, which is often key information for conservation and management action Wallace et al.
For example, to understand how human-caused mortality in foraging grounds may influence population abundance declines, we must distinguish the impacts among nesting stocks. Tackling these problems is unquestionably multi-faceted, and the role of genetics in unraveling these complexities has continued to expand in recent years.
Genetic tools have been used to quantify impacts over both short and long-term timescales, and are well-suited for many recently identified and emerging threats such as climate change. For threats occurring in foraging grounds or during migration transit, identification of natal origins is crucial to assess and compare impacts within and across populations. Advances in genetic marker resolution and analytical tools see Box 1 have allowed recent studies to make substantial headway in accomplishing this goal.
For example, LaCasella et al. Researchers have used comparable approaches to identify population sources of harvested green turtles in Malaysia Joseph et al. Employing finer resolution nuclear markers, Stewart et al. Similarly, Clusa et al. Although MSA alone will continue to contribute to threat assessments particularly when only mtDNA data are available , these examples highlight the increased power of combining MSA with assignment testing to understand the relative risks away from nesting beaches at finer scales.
However, there are some location and species-specific limitations in the applicability of these approaches because in some cases microsatellites have not provided any added resolution relative to mtDNA markers e. While bycatch is one of the principal threats to marine turtle populations globally Wallace et al. These applications will be most biologically informative when comprehensive genetic characterization of all potential natal origin stocks has been conducted see Social Dimensions Section below. Many marine turtle populations have suffered large declines due to anthropogenic activities, and there is evidence that human-caused reductions began several centuries ago Bjorndal and Jackson, ; McClenachan et al.
Some populations have shown encouraging signs of recovery due to conservation actions in recent years, while others continue to remain low or further decrease NRC, Marine turtles of today may be relics of historically larger and possibly biologically different populations, but it is unclear if or how such declines might impact population recovery and resiliency.
One way that species declines natural or human caused can impact population resiliency is through the loss of genetic diversity underlying phenotypic variation, which may reduce adaptive potential and increase inbreeding impacts Willi et al. For example, population bottlenecks have been shown to have strong negative impacts on hatching success in endangered birds Heber and Briskie, , and low major histocompatibility complex MHC genetic variation in Tasmanian devils Sarcophilus harrisii contributes to a high susceptibility to deadly transmissible cancers Jones et al.
Longevity and other life history traits of marine turtles provide buffers from diversity loss relative to other taxa e. Early research suggested that contemporary genetic bottlenecks in small nesting populations of Mediterranean loggerheads could be mitigated by male-mediated gene flow Carreras et al. Additionally, lower levels of genetic variation in younger vs. This work highlights that although marine turtles have buffers to maintain genetic diversity in the face of human-driven declines, they are not completely immune, and once it is lost it would likely take a long time to regenerate i.
These studies are an important first step in advancing our understanding of diversity loss and maintenance in marine turtles, but it is not yet known if or how such changes negatively impact marine turtle population resiliency, particularly in the face of other stressors such as disease and climate change. To our knowledge, only one study to date has investigated connections between genetic variation and phenotypic traits related to fitness in marine turtles, and there were no significant relationships between measures of reproductive success i.
However, examination of functional genomic regions MHC loci in loggerhead turtles suggested that locally adapted pools of MHC alleles at the margins of the population distribution combined with male-mediated gene flow may be key to sustaining adaptive potential across the entire rookery Stiebens et al. As diversity is increasingly characterized across more marine turtle species and geographical regions e. Habitat loss and degradation created by coastal development, pollution, climate change and other human activities increasingly threaten marine turtles at nesting and foraging grounds.
In addition to direct mortalities, these may impact populations indirectly in ways that are much more difficult to quantify such as altering population connectivity, demographic structure, or imparting sub-lethal impacts. Techniques such as MSA and assignment testing, passive maternal CMR via eggshell sampling, and gene expression assays have good potential to understand indirect consequences of human-caused habitat alteration. For instance, research is currently underway combining MSA and sex determination via hormone assays in foraging juvenile turtles to assess shifting sex ratios due to increasing sand temperatures at rookeries M.
Jensen and C. Allen, unpublished data. Tezak et al. If possible, this may support rapid, direct monitoring of sex ratios over larger spatial and temporal scales, facilitating robust estimates of climate change impacts on this important demographic parameter. Functional genomics may also be useful in understanding underlying genomic and physiological processes and investigating sub-lethal impacts. For example, gene expression assays have recently been used to begin studying the effects of exposure to endocrine-disrupting pollutants in hatchling development Gomez-Picos et al.
Recently identified genes underlying thermal stress responses in marine turtle embryos also may serve as candidates to examine the adaptive capacity of different populations and species to cope with increasing nest incubation temperatures Bentley et al. Finally, human activities such sea wall construction and beach nourishment projects that restrict or remove access to key marine turtle reproductive habitats continue to increase as humans react to these threats themselves.
These are occurring in concert with changes in habitat suitability due to warming and sea level rise Pike, , though it currently remains unclear how much plasticity or local adaptation exists in climatic niches across marine turtle populations Mazaris et al. Evolutionary history tells us that extant marine turtles have found ways to persist in the face of large-scale climatic and habitat changes across millennia, and these strategies will likely help buffer impacts of ongoing environmental changes on marine turtle population viability.
However, evidence of recent radiation and colonization events along with existence of many extinct marine turtle lineages also reminds us that evolutionary processes are dynamic, and that persistence is not guaranteed Pritchard, We must also recognize that such habitat alterations are co-occurring with other human-caused stresses on marine turtle populations.
Future research using approaches such as genetic CMR, assignment testing and functional genomics could be leveraged to track and understand changes due to these habitat changes over space and time at individual, rookery and population levels, possibly addressing questions such as: Under what contexts will turtles relocate to another rookery or lay eggs in sub-optimal or unviable conditions?
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How does this affect population connectivity and demographic structure? Do species exhibit local adaptation or broad plasticity in nesting climatic niches? It's common for researchers to conduct genetic studies of nesting populations with a local or regional focus. However, extensive dispersal and migrations of marine turtles across large geographical distances necessitates large-scale analyses and international collaboration to resolve connectivity and phylogeography questions.
Lack of this information can significantly limit MSA and assignment inferences, and in some cases can lead to inaccurate interpretation of results Shamblin et al. In the case of oceanic juvenile loggerheads foraging in the North Atlantic, baseline bp haplotype data were initially lacking for several potentially contributing rookeries, preventing robust MSA. While each group was working on regional studies of loggerhead turtle stock structure, they did not individually have access to complete datasets for the whole Atlantic that is required for meaningful MSA.
The LGWG provided a formal structure for individual sample and data holders to safely share data prior to publication of regional datasets to address data gaps and develop large-scale, synthetic stock structure analyses and facilitate robust MSA. The LGWG also recognized that the baseline would require continual updating as additional rookery data become available to maintain relevance for MSA in the future, and established a website to provide a forum to obtain updated results Shamblin et al.
These cooperative efforts represent significant advances in marine turtle biology and conservation, and directly enabled the assignments of animals bycaught in fisheries.
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Although such syntheses require substantial time commitments and large-scale international cooperation, continued efforts in other species and regions will be instrumental in facilitating comprehensive threat assessments and mitigation efforts. The reluctance or lack of capacity in many countries to deal with the bureaucratic burden of CITES has been an impediment to interchange of samples for larger-scale, comparable analyses, and is likely to continue without substantial investment in infrastructural support.
However, opportunities may exist for establishing or expanding collaborations like the LGWG and for building regional capacity or a network of in-country laboratories to generate and share genetic data within existing frameworks such as the IUCN Marine Turtle Specialist Group, The State of the World's Sea Turtles SWOT working group, or in some cases bilateral collaborations see Matsuzawa et al.
In addition to collaborative efforts within the scientific community, another advance has come from sharing results with stakeholders and the public in accessible platforms to promote citizen engagement to achieve goals in large-scale synthetic genetic projects. Representatives from these projects enter nesting data for each recorded clutch in an online nesting database maintained by seaturtle.
Following individual assignment of each genetic sample, a turtle ID unique to each nesting female is uploaded into the database. This provides volunteers collecting samples for the genetics project real time feedback on female identity as samples are processed. Participants from each beach project have access to the nesting history for any female that has ever laid a clutch on their beach. This feedback mechanism has strongly contributed to volunteer engagement and buy-in, particularly when the project was in its infancy. There is also a summary webpage on the project available to the general public that highlights some basic demographic data at various spatial scales and includes some example nesting histories.
A project of this scale simply would not be possible without the support and cooperation of the marine turtle management programs in the respective state agencies and the many organizations and volunteers that comprise the marine turtle nest monitoring networks in each state. Integrating collaborative initiatives with easy to use, standardized methods enables consistent data collection and maintenance across the subpopulation and facilitates large-scale analyses.
As these online resources and social media tools for citizen science become more accessible, we anticipate increasing opportunities to use this approach across a variety of marine turtle genetics research applications. Several key themes emerge from the diverse examples discussed that are useful in guiding future projects using genetic tools for marine turtle biology and conservation research.
First, there is not one best approach. Rather, it is most important to match the right tools to the research question and biological context, and for researchers employing genetics to understand the underlying theory to ensure appropriate inferences from their data Karl et al. Particularly in conservation contexts, budget constraints often need to be considered, making it even more important to prioritize research and management goals to make sure they are in line with research study designs. Some conservation questions may be adequately addressed using traditional markers or without sampling every individual or location.
However, it is also essential to recognize and pursue synergistic opportunities that can build capacity for future research and progress our state of knowledge. Additionally, it can be difficult to justify using limited funds to develop resources that do not immediately address management questions such as genome assemblies and annotation, new techniques or markers, pedigrees, and genetic linkage maps , but these resources open the door for a tremendous diversity of future studies highly relevant to conservation e.
By reaching out across disciplines, marine turtle biologists may likely find opportunities to partner with scientists in other academic fields as well as the biotechnology industry with expertise, interest and resources to develop these tools to build future capacity for marine turtle conservation genomics. Secondly, undertaking large-scale or long-term sampling and monitoring programs such as the genetic fingerprinting projects in St. Croix and the Southeast US require substantial forethought of logistical coordination, standardized sample collection and storage, and data management.
For programs embarking on incorporating genetic sampling into monitoring plans for the first time, learning from the challenges and best practices that have emerged from current genetic fingerprinting projects and long-term tagging databases, and investing time in developing infrastructure, training and data organization strategies can greatly facilitate project success Table 3. Many of the examples detailed in this review also demonstrate the importance of working groups and international collaborations in determining global marine turtle population boundaries, life history strategies, and threat assessments.
As we strive to put together the remaining pieces of these puzzles and address outstanding big questions in marine turtle biology and conservation, working together across boundaries will continue to be paramount to success. Finally, we recognize that for many conservation programs, despite continued cost reductions and increasing technological accessibility Box 1 , it may still not be feasible to independently integrate genetic sampling and analyses into biological monitoring due to financial, expertise and infrastructure barriers.
However, interested organizations may be able build partnerships and scale projects to capitalize on available resources Table 3. For example, some programs may have capacity to collect and store samples, but lack funding or infrastructure to conduct analyses. These groups can develop sampling schemes best suited for their resources and biological questions by conferring with experienced researchers and using validated methods for collection and storage e.
Organizations may also be able to build partnerships with other wildlife genetics researchers that have existing infrastructure and expertise to make costs feasible with existing resources or work collaboratively to seek funding together. While it certainly does not make sense for every program to conduct extensive genetic sampling, employing these and other creative strategies can help make these approaches and the knowledge they generate accessible to the broader marine turtle conservation research community.
As we look toward the future, what are the key remaining challenges, and how can we use genetics and genomics to address major unresolved questions in marine turtle biology, as well as emerging issues such as climate change?
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New studies creatively adapting traditional approaches will continue to play important roles, and there are also many exciting new techniques with great potential to expand our knowledge. Here, we highlight several promising avenues on the horizon, recognizing that there are many more possibilities that will likely emerge. First, integrating genetic tools with complementary data types such as stable isotopes, skeletochronology, hormones, telemetry, unmanned aerial vehicles, and oceanographic modeling has recently provided novel insight into marine turtle biology Stewart et al.
Many of these fields are undergoing revolutionary technological advances akin to those occurring in genomics, so the potential for combined novel applications will likely continue to grow into the future. However, high-resolution environmental data resources in the oceans have been more limited compared to terrestrial ecosystems, so analogous studies in the marine environment have lagged behind. But recent advances have facilitated the rapid expansion of seascape genomics studies that have diverse applications in conservation and resource management contexts Benestan et al.
These integrative approaches have good potential in marine turtle studies for tackling emerging threats such as monitoring foraging grounds to detect early signs of recruitment decline, or tracking possible phenological and range shifts due to habitat alteration and climate change. Minimally invasive techniques that have been validated and are currently being employed in other marine wildlife may also prove to be useful in marine turtles, such as environmental DNA eDNA sampling to estimate presence of a particular species Kelly et al.
High-throughput sequencing HTS; see Box 1 also holds promise for expanding our understanding of fundamental marine turtle ecology and evolution. The generation of genome-wide datasets open the door to phylogeographic and comparative genomic analyses that have yielded remarkable insight into evolutionary histories in other taxa Cammen et al. But beyond this, the versatility of HTS offers potential for a broad diversity of applications, such as genome-wide association studies GWAS to identify the genomic basis of key phenotypic traits Korte and Farlow, , rapid genotyping of individuals tracked over larger spatio-temporal scales e.
Over the past several decades, genetics have helped answer an increasing diversity of research questions in marine turtle biology and conservation. Rapidly expanding genetic and genomic toolboxes will undoubtedly continue to expand our knowledge in coming years. By collaborating and integrating these innovations with those in complementary disciplines, marine turtle conservation biologists can leverage these tools to tackle the remaining and emerging challenges in marine turtle ecology, evolution and conservation management.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors thank C. Turner Tomaszewicz and two reviewers for useful comments that improved the manuscript. Abreu-Grobois, F. Lepidochelys olivacea , Olive ridley. Available online at: www. Aggarwal, R. Development and characterization of novel microsatellite markers from the olive ridley sea turtle Lepidochelys olivacea.
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Bjorndal, K. Annual variation in source contributions to a mixed stock: implications for quantifying connectivity. Lutz, J. Musick, and J. Google Scholar. Population structure and genetic diversity in green turtles nesting at Tortuguero, Costa Rica, based on mitochondrial DNA control region sequences. Population structure and diversity of Brazilian green turtle rookeries based on mitochondrial DNA sequences. Chelonian Conserv. Variation in age and size at sexual maturity in Kemp's ridley sea turtles.
Bolker, B. Bowen, B. Conservation implications of complex population structure: lessons from the loggerhead turtle Caretta caretta. An odyssey of the green sea turtle: ascension Island revisited. Global population structure and natural history of the green turtle Chelonia mydas in terms of matriarchal phylogeny. Evolution 46, — A molecular phylogeny for marine turtles: trait mapping, rate assessment, and conservation relevance. Caillouet, C.
Kemp's Ridley sea turtle Lepidochelys kempii age at first nesting. Cammen, K. Genomic methods take the plunge: recent advances in high-throughput sequencing of marine mammals. Campbell, N. Genotyping-in-thousands by sequencing GT-seq : a cost effective SNP genotyping method based on custom amplicon sequencing.
Carreras, C. The genetic structure of the loggerhead sea turtle Caretta caretta in the Mediterranean as revealed by nuclear and mitochondrial DNA and its conservation implications. Casale, P. D Caretta caretta, Loggerhead Turtle. Age at size and growth rates of early juvenile loggerhead sea turtles Caretta caretta in the Mediterranean based on length frequency analysis. Chaves, J. Connectivity, population structure, and conservation of Ecuadorian green sea turtles. Cheng, I. Comparison of the genetics and nesting ecology of two green turtle rookeries.
Christiansen, F. Spatial variation in directional swimming enables juvenile sea turtles to reach and remain in productive waters. Clusa, M. Potential bycatch impact on distinct sea turtle populations is dependent on fishing ground rather than gear type in the Mediterranean Sea. Conant, T. Endangered Species Act. Washington, DC. Dethmers, K. The genetic structure of Australasian green turtles Chelonia mydas : exploring the geographical scale of genetic exchange. Migration of green turtles Chelonia mydas from Australasian feeding grounds inferred from genetic analyses.
Exogenous estradiol alters gonadal growth and timing of temperature sex determination in gonads of sea turtle. Marine turtle mitogenome phylogenetics and evolution. Dutton, D. Increase of a Caribbean leatherback turtle Dermochelys coriacea nesting population linked to long-term nest protection. Dutton, P. A method for sampling hatchling sea turtles for the development of a genetic tag. Composition of Hawaiian green turtle foraging aggregations: mtDNA evidence for a distinct regional population. Global phylogeography of the leatherback turtle Dermochelys coriacea.
Status and genetic structure of nesting populations of leatherback turtles Dermochelys coriacea in the western Pacific. Population structure and phylogeography reveal pathways of colonization by a migratory marine reptile Chelonia mydas in the central and eastern Pacific. Genetic stock structure of green turtle Chelonia mydas nesting populations across the Pacific islands. Pacific Sci. Population stock structure of leatherback turtles Dermochelys coriacea in the Atlantic revealed using mtDNA and microsatellite markers.
Encalada, S. Phylogeography and population structure of the Atlantic and Mediterranean green turtle Chelonia mydas : a mitochondrial DNA control region sequence assessment. Epstein, B. Rapid evolutionary response to a transmissible cancer in Tasmanian devils. FitzSimmons, N. Single paternity of clutches and sperm storage in the promiscous green turtle Chelonia mydas.
Geographic structure of the mitochondrial and nuclear gene polymorphisms in Australian green turtle populations and male-biased gene flow. Formia, A. Mitochondrial DNA diversity and phylogeography of endangered green turtle Chelonia mydas populations in Africa. Frey, A. Kemp's ridley Lepidochelys kempii nesting abundance in Texas, USA: a novel approach using genetics to improve population census. Gaos, A. Hawksbill turtle terra incognita: conservation genetics of eastern Pacific rookeries.
Gomez-Picos, P. Expression of aromatase in the embryonic brain of the olive ridley sea turtle Lepidochelys olivacea , and the effect of bisphenol-A in sexually differentiated embryos.
Gonzalez-Garza, B. Genetic variation, multiple paternity, and measures of reproductive success in the critically endangered hawksbill turtle Eretmochelys imbricata. Hahn, A. Jones and B. Hamabata, T. Genetic structure of green turtle Chelonia mydas peripheral populations nesting in the northwestern Pacific rookeries: evidence for northern refugia and postglacial colonization. Hamann, M. Global research priorities for sea turtles: informing management and conservation in the 21st century. Hancock-Hanser, B. Targeted multiplex next-generation sequencing: advances in techniques of mitochondrial and nuclear DNA sequencing for population genomics.
Hays, G. Route optimisation and solving Zermelo's navigation problem during long distance migration in cross flows.
Breeding periodicity for male sea turtles, operational sex ratios, and implications in the face of climate change. Different male vs. Heber, S. Population bottlenecks and increased hatching failure in endangered birds. Hoban, S. Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions. Hurtado, L. Thousands of SNPs in the critically endangered Kemp's Ridley sea turtle Lepidochelys kempii revealed by ddRAD-seq: opportunities for previously elusive conservation genetics research.
Gulf Mex. Jensen, M. Microsatellites provide insight into contrasting mating patterns in arribada vs. Spatial and temporal genetic variation among size classes of green turtles Chelonia mydas provides information on oceanic dispersal and population dynamics. Wyneken, K. Lohmann, and J. Defining olive ridley turtle Lepidochelys olivacea management units in Australia and assessing the potential impact of mortality in ghost nets. Genetic markers provide insight on origins of immature green turtles Chelonia mydas with biased sex ratios at two foraging grounds in Sabah, Malaysia.
Jones, M. Genetic diversity and population structure of Tasmanian devils, the largest marsupial carnivore. Joseph, J. Genetic structure and diversity of green turtles Chelonia mydas from two rookeries in the South China Sea. Genetic investigation of green turtles Chelonia mydas harvested from a foraging ground at Mantanani, Sabah, Malysia. Kalinowski, S. Karl, S. Common misconceptions in molecular ecology: echoes of the modern synthesis.
Kelly, R. Using environmental DNA to census marine fishes in a large mesocosm. Keske, C. Tag returns of adult green turtles from Florida's headstart program — Komoroske, L. Targeted next generation sequencing approaches for genotyping marine turtles.
Publications - Blakeslee lab
The 36th International Sea Turtle Symposium. Korte, A. The advantages and limitations of trait analysis with GWAS: a review. Plant Meth.