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Updated: May 16, 2025
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A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
Published on: November 21, 2019
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Contrasting Patterns of Raccoon (Procyon lotor) Spatial Population Genomics Throughout a Rabies Management Area in
Matthew W Hopken1,2, Clara P Mankowski1, Christine Thurber3
1US Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center Fort Collins Colorado USA.
Evolutionary Applications
|May 14, 2025
Summary
Spatial genetic analysis reveals distinct northern raccoon (Procyon lotor) populations across North America. Findings inform management of zoonotic diseases like rabies by detailing landscape influences on raccoon movement and connectivity.
Area of Science:
- Population genetics
- Wildlife ecology
- Conservation biology
Background:
- Generalist species like northern raccoons (Procyon lotor) present challenges for population structure analysis due to wide distributions.
- Understanding raccoon population genetics is crucial for wildlife management, particularly concerning human-wildlife conflicts and zoonotic diseases.
Purpose of the Study:
- To investigate genetic diversity and population structure in eastern North American raccoons using spatial genetic analyses.
- To identify geographic clusters and understand landscape influences on raccoon gene flow to inform rabies management strategies.
Main Methods:
- Utilized a RADcapture panel of 1000 microhaplotype loci on an extensive raccoon tissue repository.
- Employed Bayesian clustering and spatially explicit population genetic analyses across 22 US states and 2 Canadian provinces.
Main Results:
- Delineated multiple raccoon ancestry clusters across a broad geographic range.
- Identified a potential phylogeographic split correlating with post-Pleistocene recolonization.
- Revealed landscape impacts on gene flow, with the Appalachian Mountains restricting connectivity and other regions showing high connectivity.
Conclusions:
- Raccoon genetic structure is influenced by historical biogeography and current landscape features.
- Spatial genetic data provides high-resolution insights into population connectivity, crucial for regional zoonotic disease risk management.
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