结合捕获时间的空间野生动物调查捕获历史分析
Capture history analysis for spatial wildlife surveys with detection times
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中文总结 AI 辅助
本研究针对带个体可识别特征的野生动物调查，结合捕获时间与位置，依托计数过程理论开发极大似然估计量，构建统一框架并解决相关开放问题，经模拟与新西兰负鼠实例验证方法有效性。
中文摘要 AI 辅助
针对具有个体可识别特征的物种开展的野生动物调查，大多基于个体动物的捕获历史分析，但其中很少有研究同时考虑动物的捕获时间与捕获位置。本研究中，当捕获时间已知时，我们针对采用近距探测器、多捕获陷阱、单捕获陷阱及移除动物陷阱的个体可识别动物调查，开发了极大似然估计量。我们依托事件历史（或生存）分析基础的计数过程理论完成这一工作。该研究为此类调查提供了统一框架，解决了单捕获陷阱和移除调查的开放问题，并为多捕获陷阱引入了新的统计方法。我们通过模拟测试新方法，还对新西兰采用单捕获陷阱捕获的负鼠开展了分析。
英文摘要
Many wildlife surveys of species with individually identifiable animals are based on the analysis of the capture histories of individual animals. However, not many of these take account of both the animals' capture times and their capture locations. In this work, we develop a maximum likelihood estimator for surveys of individually identifiable animals using proximity detectors, multi-catch traps, single-catch traps, and traps that remove animals from the population, when capture times are known. We do this using the counting process theory at the foundation of event history (or survival) analysis. The work provides a unifying framework for such surveys, resolves open problems for single-catch traps and removal surveys, and introduces a new statistical method for multi-catch traps. We test the new methods by simulation and we present an analysis of possums in New Zealand caught with single-catch traps.
