Washington Cooperative Fish and Wildlife Research Unit, School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA.
Applied Physics Laboratory, Polar Science Center, University of Washington, Seattle, Washington, USA.
Ecology. 2022 Oct;103(10):e3772. doi: 10.1002/ecy.3772. Epub 2022 Jul 15.
Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture-recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears (Ursus maritimus) in a 28,125 km survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture-recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km grid cell/day in nearshore cells to 1.6-2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124-250). Abundance estimates were similar to a previous multiyear integrated population model using capture-recapture and telemetry data (2008-2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR-movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR-movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.
动物运动是影响个体生存和繁殖、种群结构和群落动态的基本生态过程。然而，用于量化动物运动和时空丰度的方法通常是分开的，因此忽略了个体水平和种群水平过程之间的联系。我们描述了一个综合的空间捕获-再捕获（SCR）运动模型，该模型用于联合估计（1）在定义的空间区域内个体的数量和分布，以及（2）这些个体随时间的运动。我们将该模型应用于 2015 年在美国楚科奇海东部 28125 平方公里的调查区域内对北极熊（Ursus maritimus）的研究，该研究结合了捕获-再捕获和遥测数据。在模拟研究中，该模型使用双变量正态随机游走和相关随机游走运动过程为运动、丰度和检测参数提供了无偏估计。我们的案例研究为雄性和雌性熊的定向运动持久性提供了详细证据，在 36 天的研究期间，个体经常穿越大于调查区域的区域。从个体到种群水平推断的扩展，我们发现密度从近岸单元的<0.75 头/625km 网格单元/天到周围有海冰的单元的 1.6-2.5 头/网格单元/天不等。每日丰度估计值范围为 53 至 69 头，无逐日趋势。由于进入和离开该区域的运动，使用调查区域的独特熊的数量随着时间的推移而增加，导致在研究期间估计有 171 头熊使用该调查区域（95%可信区间为 124-250）。丰度估计与使用捕获-再捕获和遥测数据的先前多年综合种群模型相似（2008-2016；Regehr 等人，Scientific Reports 8:16780，2018）。总体而言，SCR 运动模型成功地量化了个体和种群水平的空间利用，包括景观特征对运动、丰度和检测的影响，同时将运动和丰度过程联系起来，直接在规定的空间区域和时间内估计密度。综合 SCR 运动模型为将更大的运动现实性纳入种群动态并将运动与时空密度和丰度等新兴特性联系起来提供了一种可推广的方法。
