Data and code from: Accounting for unobserved population dynamics and aging error in close-kin mark-recapture assessments

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 are 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 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.获取稳健的种群丰度估算值，是制约众多受威胁与开发利用物种保护与管理工作的核心挑战。近缘标记重捕法（Close-kin mark-recapture, CKMR）是一种基于遗传学的研究手段，其具备极大潜力可改善数据匮乏物种的监测工作：通过为难以开展评估的种群提供丰度、存活率及其他参数的估算途径。然而，现有CKMR模型在现实种群动态与采样场景下的敏感性测试仍较为匮乏，这阻碍了该方法在种群监测计划与资源评估中的应用。本研究采用基于个体的模拟方法，探究未纳入模型的种群动态与年龄鉴定不确定性，如何在不同采样策略下影响CKMR参数估算的准确性与精确性。随后，我们提出经修正的模型，可校正因模型设定偏差所引发的估算偏倚。研究结果显示，针对每年繁殖的稳定种群，基础版简单CKMR模型可得到稳健的种群丰度估算结果；但若种群存在动态趋势、非年度繁殖特征，或需要获取年度特异性的丰度估算值，则需构建更为复杂的CKMR模型。此外，本研究证实，CKMR可通过多种采样策略获取成体的可靠丰度估算值，其中即便从未直接观测到成体且年龄鉴定误差极低的幼体针对性采样方案也可行。最后，我们将适配种群增长与间歇性繁殖特征的CKMR模型，应用于巴哈马比米尼地区20年间采集的幼年柠檬鲨（Negaprion brevirostris）遗传数据，以此展示仅通过幼体采样开展CKMR分析，如何助力高度洄游种群的监测工作。综上，本研究加深了我们对导致CKMR模型产生偏倚的生物学因素与采样决策的认知，明确了未来研究的关键方向，并为生物学家规划与开展高效CKMR研究提供了参考建议，尤其针对长寿且数据匮乏的物种而言。