RESUMO
Obtaining robust estimates of population abundance is a central challenge hindering the conservation and management of many threatened and exploited species. Close-kin mark-recapture (CKMR) is a genetics-based approach that has strong potential to improve the monitoring of data-limited species by enabling estimates of abundance, survival, and other parameters for populations that are challenging to assess. However, CKMR models have received limited sensitivity testing under realistic population dynamics and sampling scenarios, impeding the application of the method in population monitoring programs and stock assessments. Here, we use individual-based simulation to examine how unmodeled population dynamics and aging uncertainty affect the accuracy and precision of CKMR parameter estimates under different sampling strategies. We then present adapted models that correct the biases that arise from model misspecification. Our results demonstrate that a simple base-case CKMR model produces robust estimates of population abundance with stable populations that breed annually; however, if a population trend or non-annual breeding dynamics are present, or if year-specific estimates of abundance are desired, a more complex CKMR model must be constructed. In addition, we show that CKMR can generate reliable abundance estimates for adults from a variety of sampling strategies, including juvenile-focused sampling where adults are never directly observed (and aging error is minimal). Finally, we apply a CKMR model that has been adapted for population growth and intermittent breeding to two decades of genetic data from juvenile lemon sharks (Negaprion brevirostris) in Bimini, Bahamas, to demonstrate how application of CKMR to samples drawn solely from juveniles can contribute to monitoring efforts for highly mobile populations. Overall, this study expands our understanding of the biological factors and sampling decisions that cause bias in CKMR models, identifies key areas for future inquiry, and provides recommendations that can aid biologists in planning and implementing an effective CKMR study, particularly for long-lived data-limited species.
RESUMO
Kinship-based methods of population assessment such as close-kin mark-recapture require accurate and efficient genotyping methods capable of resolving complex relationships among kin. Inference of such relationships can be difficult using biallelic loci due to the large number of markers required to obtain the necessary power. Sequencing-based microsatellite panels offer an efficient alternative, combining high polymorphism with efficient next-generation methods. Here we construct, optimize, and test one such panel for lake trout (Salvelinus namaycush) using a combination of previously-published loci adapted for sequencing and de novo loci mined from a genome assembly. We performed three rounds of primer optimization, yielding a final panel of 131 loci, followed by testing with two different levels of PCR multiplexing (all primers in one or two groups) and two different reaction volumes (5 and 10 µL). Our results showed that the use of the largest multiplex and smallest reaction volume did not substantially change results, allowing significant cost and time savings. To test panel accuracy, we used both a set of 153 known-origin samples from origins of management interest and a series of hatchery crosses representing nine families with parent-offspring, half-sibling, and largely-unrelated pairs. Our results indicate that sequencing-based microsatellite panels can efficiently and accurately provide the information required for a population genetics analyses including population assignment, calculation of between-population F ST, and kinship-based population estimation techniques. Such techniques are seeing increasing applications for a wide range of taxa; our findings should provide insight and guidance for the development of the necessary molecular resources.