Oosthuizen W Chris, Pradel Roger, Bester Marthán N, de Bruyn P J Nico
Department of Zoology and Entomology Mammal Research Institute University of Pretoria Hatfield South Africa.
Biostatistics and Population Biology Group CEFE, CNRS, Univ Montpellier, Univ Paul Valéry Montpellier 3, EPHE, IRD Montpellier France.
Ecol Evol. 2019 Feb 5;9(2):836-848. doi: 10.1002/ece3.4828. eCollection 2019 Jan.
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 (). 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.
气候变化导致环境随机性增加，将加剧长寿反复生殖物种生活史特征的时间变异性，尤其是繁殖概率。这些变化可能会降低个体适合度和种群生存力，因此进行监测很重要。在个体检测不完美的野生动物种群中，最好使用捕获再捕获方法来估计繁殖概率。然而，在许多脊椎动物物种（如两栖动物、海龟、海鸟）中，非繁殖个体是不可观测的，因为它们不固定在某个领地或繁殖地点。尽管不可观测状态可用于模拟非繁殖个体的暂时迁出，但捕获再捕获模型中存在不可观测状态也有缺点。因此，处理不可观测生活史状态的最佳解决方案是完全消除它们。在这里，我们通过拟合新颖的多事件稳健设计模型来实现这一目标，该模型利用全年多次调查获得的信息。我们用这种方法来估计资本繁殖型雌性海象的年度繁殖概率。从概念上讲，我们的方法类似于Barker/稳健设计的多状态版本，因为它将离散繁殖季节收集的稳健设计捕获数据与一年中其他时间的观测结果结合起来。我们方法的一个显著优点是，当一起分析多个数据源时，非繁殖个体状态变得“可观测”。这使我们能够检验状态依赖生存的存在（有一些证据表明繁殖个体的生存率低于非繁殖个体），并更精确地估计进出非繁殖个体状态的年度繁殖转变（当前繁殖个体的未来繁殖概率往往高于非繁殖个体）。我们使用程序E-SURGE（2.1.2）来拟合多事件稳健设计模型，通过隐马尔可夫过程纳入繁殖状态分配（繁殖个体、非繁殖个体）的不确定性。这种灵活的建模方法可以很容易地适应离散繁殖季节期间和之外可能遇到的众多物种的抽样设计。
