Riverscape community genomics: A comparative analytical approach to identify common drivers of spatial structure

Area of Science:

• Ecology
• Genetics
• Conservation Biology

Background:

• Genetic diversity is crucial for population persistence, influenced by connectivity and isolation.
• Most studies examine single species, missing ecosystem-wide conservation opportunities.
• Riverscape community genomics offers a multispecies approach to understand genetic structure.

Purpose of the Study:

• To develop and apply a riverscape community genomics approach to evaluate genetic beta-diversity across multiple species.
• To identify common drivers of genetic structure in a fish community.
• To inform multispecies conservation strategies in riverine ecosystems.

Main Methods:

• Evaluated genetic beta-diversity in 31 native stream fish species across 75 sites using SNP genotyping (ddRAD).
• Analyzed genetic structure using partial redundancy analysis against four models: isolation by distance, barrier, stream hierarchy, and environment.
• Assessed spatial patterns of genetic differentiation and gene flow.

Main Results:

• General spatial patterns of genetic structure were consistent across most species, aligning with river network architecture.
• Stream hierarchy (IBH) was the most significant predictor of genetic variation (explaining 62% on average), outperforming other models.
• Twenty-four out of 31 species showed distinct subpopulations, indicating spatial modularity in gene flow.

Conclusions:

• The stream hierarchy model effectively explains genetic structure in riverine fish communities.
• Gene flow is predominantly higher within hierarchical units (catchments, watersheds) than between them.
• The 8-digit hydrologic unit (HUC) is identified as a relevant scale for managing genetic diversity in river networks.