Kapota Dror, Dolev Amit, Saltz David
Mitrani Department of Desert Ecology Jacob Blaustein Institutes for Desert Research Ben-Gurion University of the Negev Midreshet Ben-Gurion Israel.
Science Division Nature and Parks Authority Jerusalem Israel.
Ecol Evol. 2017 Sep 12;7(20):8507-8514. doi: 10.1002/ece3.3321. eCollection 2017 Oct.
The residence time is the amount of time spent within a predefined circle surrounding each point along the movement path of an animal, reflecting its response to resource availability/quality. Two main residence time-based methods exist in the literature: (1) The variance of residence times along the path plotted against the radius of the circle was suggested to indicate the scale at which the animal perceives its resources; and (2) segments of the path with homogeneous residence times were suggested to indicate distinct behavioral modes, at a certain scale. Here, we modify and integrate these two methods to one framework with two steps of analysis: (1) identifying several distinct, nested scales of area-restricted search (ARS), providing an indication of how animals view complex resource landscapes, and also the resolutions at which the analysis should proceed; and (2) identifying places which the animal revisits multiple times and performs ARS; for these, we extract two scale-dependent statistical measures-the mean visit duration and the number of revisits in each place. The association between these measures is suggested as a signature of how animals utilize different habitats or resource types. The framework is validated through computer simulations combining different movement strategies and resource maps. We suggest that the framework provides information that is especially relevant when interpreting movement data in light of optimal behavior models, and which would have remained uncovered by either coarser or finer analyses.
停留时间是动物沿运动路径上每个点周围预定义圆圈内所花费的时间量,反映了其对资源可用性/质量的反应。文献中存在两种主要的基于停留时间的方法:(1)有人建议将沿路径的停留时间方差与圆圈半径作图,以表明动物感知其资源的尺度;(2)有人建议具有均匀停留时间的路径段在一定尺度上表明不同的行为模式。在此,我们将这两种方法修改并整合到一个具有两个分析步骤的框架中:(1)识别几个不同的、嵌套的区域限制搜索(ARS)尺度,这能表明动物如何看待复杂的资源景观,以及分析应进行的分辨率;(2)识别动物多次重访并进行ARS的地点;对于这些地点,我们提取两个依赖于尺度的统计量——平均访问持续时间和每个地点的重访次数。这些统计量之间的关联被认为是动物如何利用不同栖息地或资源类型的一个特征。该框架通过结合不同运动策略和资源地图的计算机模拟进行了验证。我们认为,该框架提供的信息在根据最优行为模型解释运动数据时特别相关,而这些信息无论是通过更粗略还是更精细的分析都无法发现。