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Making use of multiple surveys: Estimating breeding probability using a multievent‐robust design capture–recapture model

机译:利用多重调查:使用多事件鲁棒性设计捕获-捕获模型估算繁殖概率

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Increased environmental stochasticity due to climate change will intensify temporal variance in the life‐history traits, and especially breeding probabilities, of long‐lived iteroparous species. These changes may decrease individual fitness and population viability and is therefore important to monitor. In wild animal populations with imperfect individual detection, breeding probabilities are best estimated using capture–recapture methods. However, in many vertebrate species (e.g., amphibians, turtles, seabirds), nonbreeders are unobservable because they are not tied to a territory or breeding location. Although unobservable states can be used to model temporary emigration of nonbreeders, there are disadvantages to having unobservable states in capture–recapture models. The best solution to deal with unobservable life‐history states is therefore to eliminate them altogether. Here, we achieve this objective by fitting novel multievent‐robust design models which utilize information obtained from multiple surveys conducted throughout the year. We use this approach to estimate annual breeding probabilities of capital breeding female elephant seals ( Mirounga leonina ). Conceptually, our approach parallels a multistate version of the Barker/robust design in that it combines robust design capture data collected during discrete breeding seasons with observations made at other times of the year. A substantial advantage of our approach is that the nonbreeder state became “observable” when multiple data sources were analyzed together. This allowed us to test for the existence of state‐dependent survival (with some support found for lower survival in breeders compared to nonbreeders), and to estimate annual breeding transitions to and from the nonbreeder state with greater precision (where current breeders tended to have higher future breeding probabilities than nonbreeders). We used program E‐SURGE (2.1.2) to fit the multievent‐robust design models, with uncertainty in breeding state assignment (breeder, nonbreeder) being incorporated via a hidden Markov process. This flexible modeling approach can easily be adapted to suit sampling designs from numerous species which may be encountered during and outside of discrete breeding seasons.
机译:气候变化引起的环境随机性的增加将加剧长寿命同卵物种的生命历史特征,尤其是繁殖概率的时间变化。这些变化可能会降低个体适应性和人口生存能力,因此对监测非常重要。在个体检测不完善的野生动物种群中,最好使用捕获-捕获方法估算繁殖概率。但是,在许多脊椎动物物种(例如两栖动物,海龟,海鸟)中,非繁殖者是不可观察到的,因为它们与领土或繁殖地点无关。尽管可以使用不可观察的状态来模拟非繁殖者的临时移居,但是在捕获-捕获模型中具有不可观察的状态是不利的。因此,处理无法观察到的生命历史状态的最佳方法是完全消除它们。在这里,我们通过采用新颖的多事件稳健设计模型来实现此目标,该模型利用了从全年进行的多次调查中获得的信息。我们使用这种方法来估计资本繁殖雌性海豹(Mirounga leonina)的年度繁殖概率。从概念上讲,我们的方法与Barker / robust设计的多状态版本相类似,因为它将离散繁殖季节收集的可靠设计捕获数据与一年中其他时间的观察结果相结合。我们的方法的一个主要优点是,当一起分析多个数据源时,非育种状态变为“可观察”。这使我们能够测试状态依赖性生存的存在(发现了一些支持,与非育种者相比,育种者的存活率较低),并能够以更高的精度估算年度繁殖向非育种者状态的过渡和从非育种者状态的转变(当前育种者倾向于比非繁殖者更高的未来繁殖概率)。我们使用程序E-SURGE(2.1.2)来拟合多事件鲁棒设计模型,并且通过隐藏的马尔可夫过程将育种状态分配(育种者,非育种者)的不确定性纳入了模型。这种灵活的建模方法可以轻松地适用于不连续繁殖季节内外都可能遇到的众多物种的采样设计。

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