...
首页> 外文期刊>Ecology and Evolution >Known unknowns in an imperfect world: incorporating uncertainty in recruitment estimates using multi‐event capture–recapture models
【24h】

Known unknowns in an imperfect world: incorporating uncertainty in recruitment estimates using multi‐event capture–recapture models

机译:不完美世界中的已知未知数:使用多事件捕获-捕获模型将不确定性纳入招聘估计中

获取原文
   

获取外文期刊封面封底 >>

       

摘要

AbstractStudying the demography of wild animals remains challenging as several of the critical parts of their life history may be difficult to observe in the field. In particular, determining with certainty when an individual breeds for the first time is not always obvious. This can be problematic because uncertainty about the transition from a prebreeder to a breeder state – recruitment – leads to uncertainty in vital rate estimates and in turn in population projection models. To avoid this issue, the common practice is to discard imperfect data from the analyses. However, this practice can generate a bias in vital rate estimates if uncertainty is related to a specific component of the population and reduces the sample size of the dataset and consequently the statistical power to detect effects of biological interest. Here, we compared the demographic parameters assessed from a standard multistate capture–recapture approach to the estimates obtained from the newly developed multi-event framework that specifically accounts for uncertainty in state assessment. Using a comprehensive longitudinal dataset on southern elephant seals, we demonstrated that the multi-event model enabled us to use all the data collected (6639 capture–recapture histories vs. 4179 with the multistate model) by accounting for uncertainty in breeding states, thereby increasing the precision and accuracy of the demographic parameter estimates. The multi-event model allowed us to incorporate imperfect data into demographic analyses. The gain in precision obtained has important implications in the conservation and management of species because limiting uncertainty around vital rates will permit predicting population viability with greater accuracy.
机译:摘要研究野生动物的人口统计学仍然具有挑战性,因为在该领域中可能很难观察到其生活史的几个关键部分。特别是,确定某人首次繁殖的时间并不总是很明显。这可能是有问题的,因为从前育种者到育种者状态(招募)的不确定性导致生命率估计值以及人口预测模型的不确定性。为避免此问题,通常的做法是从分析中丢弃不完善的数据。但是,如果不确定性与人口的特定组成部分相关,则此做法可能会在生命率估算上产生偏差,并减少数据集的样本大小,从而减少检测生物学兴趣影响的统计能力。在这里,我们将通过标准多州捕获-再捕获方法评估的人口参数与从新开发的多事件框架获得的估计值进行了比较,该框架专门考虑了状态评估中的不确定性。通过使用关于南部象海豹的完整纵向数据集,我们证明了多事件模型使我们能够通过考虑繁殖状态的不确定性来使用收集到的所有数据(6639捕获-再捕获历史与多状态模型的4179),从而增加了人口统计参数估算值的准确性和准确性。多事件模型使我们能够将不完善的数据纳入人口统计分析。获得的精确度的提高对物种的保护和管理具有重要意义,因为限制生命率周围的不确定性将可以更准确地预测种群生存力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号