Geology topics

John D. Swenson

Publications and source records attributed to John D. Swenson.

3 recordsLinked to original sources

USGS2026

Population structure and genetic stock identification in southeastern United States loggerhead sea turtles (Caretta caretta) using genome-wide SNPs

Characterizing the genetic structure and connectivity between populations of endangered species can be used to inform management actions. In vagile species with high gene flow or recently established populations, such characterizations can be difficult to undertake using traditional genetic markers, and genetic stock identification (GSI) may be confounded by allele-sharing between populations. Loggerhead sea turtles ( Caretta caretta ) in the southeastern United States comprise seven management units (MUs) based on female philopatry inferred via mitochondrial DNA sequences, yet nuclear microsatellite data do not reflect divergence. Further, loci for accurate GSI are not currently known. To address this, we generated genome-wide single nucleotide polymorphism (SNP) data from 146 females nesting at individual sites representative of each southeastern United States MU. We found weak (F ST =0.001–0.003) but significant divergence among all MUs, with more notable divergence between the Gulf Coast and Atlantic Ocean MUs, and amongst the Atlantic Ocean MUs. We then used an iterative leave-one-out approach to identify candidate loci for GSI. This approach identified loci that could assign individuals to natal ocean basins (i.e., to the Gulf Coast or to the Atlantic Ocean), and to individual MUs within the Atlantic Ocean, with high (≥90%) success and accuracy. Analyses of genome-wide SNPs refined our understanding of the magnitude and scale of population connectivity in loggerhead turtles in the southeastern United States, and provided a foundation for the development of SNP panels for accurate, fine-scale GSI in sea turtles.

Alabama, Florida, Georgia↗

USGS2024

Smaller body size under warming is not due to gill-oxygen limitation in a coldwater salmonid

Declining body size in fishes and other aquatic ectotherms associated with anthropogenic climate warming has significant implications for future fisheries yields, stock assessments and aquatic ecosystem stability. One proposed mechanism seeking to explain such body-size reductions, known as the gill oxygen limitation (GOL) hypothesis, has recently been used to model future impacts of climate warming on fisheries but has not been robustly empirically tested. We used brook trout ( Salvelinus fontinalis ), a fast-growing, cold-water salmonid species of broad economic, conservation and ecological value, to examine the GOL hypothesis in a long-term experiment quantifying effects of temperature on growth, resting metabolic rate (RMR), maximum metabolic rate (MMR) and gill surface area (GSA). Despite significantly reduced growth and body size at an elevated temperature, allometric slopes of GSA were not significantly different than 1.0 and were above those for RMR and MMR at both temperature treatments (15°C and 20°C), contrary to GOL expectations. We also found that the effect of temperature on RMR was time-dependent, contradicting the prediction that heightened temperatures increase metabolic rates and reinforcing the importance of longer-term exposures (e.g. >6 months) to fully understand the influence of acclimation on temperature–metabolic rate relationships. Our results indicate that although oxygen limitation may be important in some aspects of temperature–body size relationships and constraints on metabolic supply may contribute to reduced growth in some cases, it is unlikely that GOL is a universal mechanism explaining temperature–body size relationships in aquatic ectotherms. We suggest future research focus on alternative mechanisms underlying temperature–body size relationships, and that projections of climate change impacts on fisheries yields using models based on GOL assumptions be interpreted with caution.

Journal of Experimental Biology↗

USGS2024

Sources of bias in applying close-kin mark–recapture to terrestrial game species with different life histories

Close-kin mark–recapture (CKMR) is a method analogous to traditional mark–recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species’ and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent–offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Ecology↗