Signer Johannes, Fieberg John R
Wildlife Sciences, Faculty of Forestry and Forest Ecology, University of Goettingen, Göttingen, Germany.
Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, USA.
PeerJ. 2021 Mar 19;9:e11031. doi: 10.7717/peerj.11031. eCollection 2021.
A rich set of statistical techniques has been developed over the last several decades to estimate the spatial extent of animal home ranges from telemetry data, and new methods to estimate home ranges continue to be developed. Here we investigate home-range estimation from a computational point of view and aim to provide a general framework for computing home ranges, independent of specific estimators. We show how such a workflow can help to make home-range estimation easier and more intuitive, and we provide a series of examples illustrating how different estimators can be compared easily. This allows one to perform a sensitivity analysis to determine the degree to which the choice of estimator influences qualitative and quantitative conclusions. By providing a standardized implementation of home-range estimators, we hope to equip researchers with the tools needed to explore how estimator choice influences answers to biologically meaningful questions.
在过去几十年里,已经开发出了一套丰富的统计技术,用于从遥测数据估计动物家域的空间范围,并且仍在不断开发新的家域估计方法。在这里,我们从计算的角度研究家域估计,并旨在提供一个计算家域的通用框架,而不依赖于特定的估计器。我们展示了这样一个工作流程如何有助于使家域估计更容易、更直观,并且我们提供了一系列示例来说明如何轻松比较不同的估计器。这使得人们能够进行敏感性分析,以确定估计器的选择对定性和定量结论的影响程度。通过提供家域估计器的标准化实现,我们希望为研究人员提供所需的工具,以探索估计器选择如何影响对生物学上有意义问题的答案。