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bioRxiv · 10.64898/2026.04.28.721440

WolfPackR: An R package for identifying wolf packs based on genetic and spatial data

Boncourt, E.
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Abstract

The global expansion of grey wolf (Canis lupus) populations, particularly in Europe, underscores the need for robust tools to study their social structure, territory use, and genetic relatedness. Wolf packs are dynamic, evolving through dispersal, mortality, and reproductive success, and their accurate identification is crucial for effective conservation and conflict mitigation. Traditional methods for estimating wolf populations and pack structures--such as snow tracking or howling surveys--are labor-intensive and often unreliable. Noninvasive genetic sampling and spatial capture-recapture models have improved monitoring, but integrating genetic and spatial data remains a challenge. We introduce WolfPackR, an R package designed to integrate genetic relatedness and spatial data for identifying wolf packs, lone individuals, and spatially isolated but genetically linked "ugly ducklings." WolfPackR uses pairwise relatedness estimators to define genetic groups and refines these groups through spatial overlap analysis based on Minimum Convex Polygons (MCPs). The package provides a comprehensive toolkit for analyzing population structure, territoriality, and social organization, including functions for genetic grouping, spatial clustering, summary statistics, and interactive visualization. We demonstrate the utility of WolfPackR using a case study of 505 genotyped and geospatialized wolf scat samples from Romania. By combining genetic and spatial data, WolfPackR accurately identifies pack structures that align with expert assessments and family tree reconstructions. The package modular design and reliance on widely used R libraries (dplyr, igraph, sf, leaflet) ensure flexibility and ease of integration into existing workflows. While sampling heterogeneity may limit territory delineation in some cases, WolfPackR offers a cost-effective and reproducible framework for studying wolf pack dynamics, with potential applications for other social species.

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Boncourt, E.. 2026-04-29. WolfPackR: An R package for identifying wolf packs based on genetic and spatial data. https://doi.org/10.64898/2026.04.28.721440

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