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Individual-level patterns of resource selection do not predict hotspots of contact
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  • Anni Yang,
  • Raoul Boughton,
  • Ryan Miller,
  • Nathan P. Snow,
  • Kurt Vercauteren,
  • Kim Pepin,
  • George Wittemyer
Anni Yang
University of Oklahoma

Corresponding Author:[email protected]

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Raoul Boughton
The Mosaic Company
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Ryan Miller
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Nathan P. Snow
USDA-APHIS-WS National Wildlife Research Center
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Kurt Vercauteren
USDA-APHIS-WS National Wildlife Research Center
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Kim Pepin
USDA-APHIS-WS National Wildlife Research Center
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George Wittemyer
Colorado State University
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Contact among animals is crucial for various ecological processes, including social behaviors, disease transmission, and predator-prey interactions. However, the distribution of contact events across time and space is heterogeneous, influenced by environmental factors and biological purposes. Previous studies have assumed that areas with abundant resources and preferred habitats attract more individuals and, therefore, lead to more contact. To examine the accuracy of this assumption, we used a use-available framework to identify landscape factors influencing contact locations. Our study focused on two wild pig populations in Florida and Texas, USA. We employed a contact-resource selection function (RSF) model, where contact locations were defined as used points and locations without contact as available points. By comparing the contact RSF with a population-level RSF, we assessed the factors driving both habitat selection and contact. We found that the landscape predictors (e.g., wetland, linear features, and food resources) played different roles in habitat selection and contact processes for wild pigs in both study areas. This indicates that pigs interacted with their landscapes differently when choosing habitats compared to when they encountered other individuals. Consequently, relying solely on the spatial overlap of individual or population-level RSF models may lead to a misleading understanding of contact-related ecology. Our findings challenge prevailing assumptions about contact and introduce innovative approaches to better understand the ecological drivers of spatially explicit contact. By accurately predicting the spatial distribution of contact events, we can enhance our understanding of ecological processes and their spatial dynamics.