Lyons James E, Kendall William L, Royle J Andrew, Converse Sarah J, Andres Brad A, Buchanan Joseph B
U.S. Fish and Wildlife Service, Division of Migratory Bird Management, Patuxent Wildlife Research Center, Laurel, Maryland, U.S.A.
U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, Colorado 80523, U.S.A.
Biometrics. 2016 Mar;72(1):262-71. doi: 10.1111/biom.12393. Epub 2015 Sep 8.
We present a novel formulation of a mark-recapture-resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state-space formulation of the Jolly-Seber mark-recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state-space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.
我们提出了一种新的标记重捕-再观察模型公式，该公式可用于估计种群数量、中途停留持续时间以及在迁徙区域的到达和离开时间表。估计基于唯一标记个体的遭遇历史以及标记和未标记动物的相对数量。我们对Jolly-Seber标记重捕模型的状态空间公式进行贝叶斯分析，并结合用于未标记动物数量计数的二项式模型，以得出种群数量以及到达和离开概率的估计值。我们还提供了一种用于中途停留持续时间的新估计器，该估计器源自状态空间模型中表示到达和离开之间过渡阶段的潜在状态变量。我们对野外采样方案进行了模拟研究，以了解超种群大小、标记比例和采样动物数量对估计偏差和精度的影响。模拟结果表明，在所有采样场景中，有标记种群比例估计值的相对偏差都很低，从未超过2%。我们的方法不需要枚举研究时检测到的所有未标记动物，也不需要直接了解种群中标记动物的数量。这为各种采样情况（例如候鸟、繁殖海鸟、海龟、鱼类、鳍足类动物等）提供了灵活性和潜在应用。通过对迁徙鹬类的一项研究数据展示了这些方法的应用。
