Movement patterns and study area boundaries: influences on survival estimation in capture-mark-recapture studies
Movement patterns and study area boundaries: influences on survival estimation in capture-mark-recapture studies
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DOI：
10.1111/j.0030-1299.2008.16686.x
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发表时间：
2008-08-01
期刊：
影响因子：
3.4
通讯作者：
Letcher, Benjamin H.
中科院分区：
文献类型：
--
作者：
Horton, Gregg E.;Letcher, Benjamin H.
在捕获-标记-再捕获（CMR）研究期间，无法解释研究区域中个体的可用性以及由此产生的参数估计值的混淆，可能会使CMR模型参数估计值的正确解释变得困难。虽然基于Cormack-Jolly-Seber（CJS）模型的重要进展导致了真实生存率的估计，该估计通过在研究区域捕获的可用性中消除死亡或重新捕获概率的混淆来工作，但这些方法依赖于研究人员选择与人口中的移民模式正确匹配的方法的能力。如果对研究中心保真度（非移动）做出了不正确的假设，则一旦发现不正确的假设，改变研究设计可能会很困难或不可能，而且成本高昂。移动特征的微妙之处（例如，依赖生活史的移民，游牧民族与领土拥有者）可能导致同一种群成员中可供捕获的概率的混合。这些混合物的结果可能只是从其他CMR模型参数迁移的部分非混杂。个体运动中基于生物学的差异可能与研究设计的限制因素联合收割机结合，使问题进一步复杂化。由于CMR模型中的运动及其与其他参数的相互作用的复杂性，需要量化和解决这些问题。基于我们的工作与流居住人口的大西洋鲑鱼萨尔莫salar，我们使用了模拟方法来评估现有的CMR模型下的各种混合运动概率。Barker联合数据模型提供了所有测试条件下真实生存率的无偏估计值。CJS和稳健设计模型提供了类似的真实生存无偏估计，但只有当移民信息可以直接纳入个人的遭遇史。对于稳健设计模型，马尔可夫迁移（未来捕获的可用性取决于个人的当前位置）是一种难以检测的迁移模式，除非生存率，特别是重新捕获概率很高。此外，当局部移动相对于研究区域边界较高且移动变得更加分散（例如随机游走）时，难以区分局部移动和永久性迁移，并对正确解释估计的生存参数（表观生存与真实生存）产生影响。
The inability to account for the availability of individuals in the study area during capture-mark-recapture (CMR) studies and the resultant confounding of parameter estimates can make correct interpretation of CMR model parameter estimates difficult. Although important advances based on the Cormack-Jolly-Seber (CJS) model have resulted in estimators of true survival that work by unconfounding either death or recapture probability from availability for capture in the study area, these methods rely on the researcher's ability to select a method that is correctly matched to emigration patterns in the population. If incorrect assumptions regarding site fidelity (non-movement) are made, it may be difficult or impossible as well as costly to change the study design once the incorrect assumption is discovered. Subtleties in characteristics of movement (e.g. life history-dependent emigration, nomads vs territory holders) can lead to mixtures in the probability of being available for capture among members of the same population. The result of these mixtures may be only a partial unconfounding of emigration from other CMR model parameters. Biologically-based differences in individual movement can combine with constraints on study design to further complicate the problem. Because of the intricacies of movement and its interaction with other parameters in CMR models, quantification of and solutions to these problems are needed. Based on our work with stream-dwelling populations of Atlantic salmon Salmo salar, we used a simulation approach to evaluate existing CMR models under various mixtures of movement probabilities. The Barker joint data model provided unbiased estimates of true survival under all conditions tested. The CJS and robust design models provided similarly unbiased estimates of true survival but only when emigration information could be incorporated directly into individual encounter histories. For the robust design model, Markovian emigration (future availability for capture depends on an individual's current location) was a difficult emigration pattern to detect unless survival and especially recapture probability were high. Additionally, when local movement was high relative to study area boundaries and movement became more diffuse (e.g. a random walk), local movement and permanent emigration were difficult to distinguish and had consequences for correctly interpreting the survival parameter being estimated (apparent survival vs true survival).