| Popis: |
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 monitoring of data-limited species by enabling estimates of abundance, survival, and other parameters for populations that have been challenging to assess. However, CKMR models have received limited sensitivity testing under realistic population dynamics and sampling scenarios, impeding application of the method in population monitoring programs and stock assessments. Here, we use individual-based simulation to examine how unmodeled population dynamics and sampling strategy affect the accuracy and precision of CKMR parameter estimates, and present adapted models that correct the biases that arise from model misspecification. Our results demonstrate that a relatively simple CKMR model produces robust estimates of population abundance when key assumptions including annual breeding and stable population size are met; however, if strong population declines or non-annual breeding dynamics are present, a more complex CKMR model must be constructed to avoid biased parameter estimates. 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. Finally, we apply our adapted CKMR model to two decades of genetic data from juvenile lemon sharks (Negaprion brevirostris) in Bimini, Bahamas to demonstrate how juvenile-focused CKMR can be used to expand 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, and provides recommendations for sampling design and model construction that can aid biologists in planning and implementing an effective CKMR experiment, particularly for long-lived data-limited species. |
