Gurarie Eliezer, Cagnacci Francesca, Peters Wibke, Fleming Christen H, Calabrese Justin M, Mueller Thomas, Fagan William F
Department of Biology, University of Maryland, College Park, MD, 20742, USA.
Biodiversity and Molecular Ecology Department, IASMA Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Italy.
J Anim Ecol. 2017 Jul;86(4):943-959. doi: 10.1111/1365-2656.12674. Epub 2017 May 25.
Many animals undertake movements that are longer scaled and more directed than their typical home ranging behaviour. These movements include seasonal migrations (e.g. between breeding and feeding grounds), natal dispersal, nomadic range shifts and responses to local environmental disruptions. While various heuristic tools exist for identifying range shifts and migrations, none explicitly model the movement of the animals within a statistical framework that facilitates quantitative comparisons. We present the mechanistic range shift analysis (MRSA), a method to estimate a suite of range shift parameters: times of initiation, duration of transitions, centroids and areas of respective ranges. The method can take the autocorrelation and irregular sampling that is characteristic of much movement data into account. The mechanistic parameters suggest an intuitive measure, the range shift index, for the extent of a range shift. The likelihood based estimation further allows for statistical tests of several relevant hypotheses, including a range shift test, a stopover test and a site fidelity test. The analysis tools are provided in an R package (marcher). We applied the MRSA to a population of GPS tracked roe deer (Capreolus capreolus) in the Italian Alps between 2005 and 2008. With respect to seasonal migration, this population is extremely variable and difficult to classify. Using the MRSA, we were able to quantify the behaviours across the population and among individuals across years, identifying extents, durations and locations of seasonal range shifts, including cases that would have been ambiguous to detect using existing tools. The strongest patterns were differences across years: many animals simply did not perform a seasonal migration to wintering grounds during the mild winter of 2006-2007, even though some of these same animals did move extensively in other, harsher winters. For seasonal migrants, however, site fidelity across years was extremely high, even after skipping an entire seasonal migration. These results suggest that for roe deer behavioural plasticity and tactical responses to immediate environmental cues are reflected in the decision of whether rather than where to migrate. The MRSA also revealed a trade-off between the probability of migrating and the size of a home range.
许多动物进行的移动，其规模比典型的活动范围行为更大，且更具方向性。这些移动包括季节性迁徙（例如在繁殖地和觅食地之间）、出生扩散、游牧范围转移以及对当地环境干扰的反应。虽然存在各种用于识别范围转移和迁徙的启发式工具，但没有一种在便于进行定量比较的统计框架内明确对动物的移动进行建模。我们提出了机制性范围转移分析（MRSA），这是一种估计一系列范围转移参数的方法：起始时间、过渡持续时间、质心以及各个范围的面积。该方法可以考虑到许多移动数据所具有的自相关性和不规则采样。这些机制性参数提出了一种直观的度量，即范围转移指数，用于衡量范围转移的程度。基于似然性的估计还允许对几个相关假设进行统计检验，包括范围转移检验、中途停留检验和地点保真度检验。分析工具以R包（marcher）的形式提供。我们将MRSA应用于2005年至2008年期间意大利阿尔卑斯山一群安装了GPS追踪器的狍（Capreolus capreolus）。关于季节性迁徙，这群狍的行为变化极大且难以分类。使用MRSA，我们能够量化整个种群以及多年间个体之间的行为，确定季节性范围转移的范围、持续时间和地点，包括使用现有工具难以检测到的模糊情况。最明显的模式是年份之间的差异：在2006 - 2007年温和的冬季，许多动物根本没有进行季节性迁徙到越冬地，尽管其中一些动物在其他更严酷的冬季确实进行了广泛的移动。然而，对于季节性迁徙者来说，即使跳过了整个季节性迁徙，多年间的地点保真度仍然极高。这些结果表明，对于狍来说，行为可塑性和对即时环境线索的战术反应体现在是否迁徙而非迁往何处的决策中。MRSA还揭示了迁徙概率和活动范围大小之间的权衡。
