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Detecting black bear source-sink dynamics using individual-based genetic graphs.

Hope M Draheim1, Jennifer A Moore2, Dwayne Etter3

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Summary
This summary is machine-generated.

This study introduces a novel genetic graph approach to identify source and sink populations in black bears (Ursus americanus). Findings reveal asymmetric gene flow, crucial for understanding population viability and harvest management.

Keywords:
black bearconnectivitygenetic relatednessgraph theorysource–sink dynamics

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Area of Science:

  • Ecology
  • Population Genetics
  • Conservation Biology

Background:

  • Source-sink dynamics are critical for population connectivity, genetic structure, and viability.
  • Understanding these dynamics in continuously distributed populations is challenging.

Purpose of the Study:

  • To introduce and validate a novel individual-based genetic graph approach for identifying source-sink areas in black bears (Ursus americanus).
  • To correlate genetic graph metrics with ecological factors to understand drivers of source-sink dynamics.
  • To assess the robustness of the genetic graph approach to sampling bias.

Main Methods:

  • Genotyping of 569 black bear samples from Michigan's Northern Lower Peninsula (NLP) across three years (2002, 2006, 2010) using 12 microsatellite loci.
  • Construction of individual-based genetic graphs to model gene flow and identify source/sink nodes.
  • Comparison of genetic graph metrics with 10 ecological models to identify associated environmental factors.

Main Results:

  • Identification of 62 source nodes (16 important sources) and 79 sink nodes within the NLP black bear population.
  • Significant correlation between source strength, local harvest density (proxy for bear density), and habitat suitability.
  • Demonstration of asymmetric gene flow, indicating directional movement patterns.

Conclusions:

  • Individual-based genetic graphs effectively characterize source-sink dynamics in continuously distributed species.
  • Source-sink dynamics in NLP black bears are influenced by bear density and habitat suitability.
  • Findings highlight the importance of considering these dynamics for effective game species harvest management.