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WildAgg: an R package to estimate and visualize wildlife aggregation data

May 10, 2021

This package is designed to estimate, summarize, and visualize wildlife aggregation metrics using location information like GPS collar data. The motivation for the development of this package began with two research efforts studying the aggregation and density of elk on the National Elk Refuge, Wyoming (Janousek et al.2021; and Graves et al. 2021). The primary goal of the WildAgg package is to provide a more straightforward implementation of the analyses conducted in the aforementioned work.\nIn Janousek et al. 2021, researchers modeled contact rates between wintering elk on the National Elk Refuge in order to inform elk management in face of potential chronic wasting disease spread. To model contact rates, the authors calculated an index of interaction between pairs of elk known as proximity (Bertrand et al. 1996). In WildAgg, users can calculate contact rates / proximity using the prox.calc function.\nThe over-arching goal of Graves et al. 2021 is to evaluate methods used for estimating density and aggregation of animals on the landscape. The authors found kernel density estimates (KDEs), KDE polygon areas, and the first quantile of inter-animal distances detected differences in aggregation of elk on the National Elk Refuge with the highest sensitivity. With these findings in mind, functions are included in WildAgg to calculate KDEs with accompanying descriptive statistics (function kde) and to calculate inter-animal distances (function interdist).