Environmental and anthropogenic drivers of connectivity patterns: A basis for prioritizing conservation efforts for threatened populations

Chrysoula Gubili, Stefano Mariani, Byron V. Weckworth, Paul Galpern, Allan D. McDevitt, Mark Hebblewhite, Barry Nickel, Marco Musiani

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Ecosystem fragmentation and habitat loss have been the focus of landscape management due to restrictions on contemporary connectivity and dispersal of populations. Here, we used an individual approach to determine the drivers of genetic differentiation in caribou of the Canadian Rockies. We modelled the effects of isolation by distance, landscape resistance and predation risk and evaluated the consequences of individual migratory behaviour (seasonally migratory vs. sedentary) on gene flow in this threatened species. We applied distance-based and reciprocal causal modelling approaches, testing alternative hypotheses on the effects of geographic, topographic, environmental and local population-specific variables on genetic differentiation and relatedness among individuals. Overall, gene flow was restricted to neighbouring local populations, with spatial coordinates, local population size, groups and elevation explaining connectivity among individuals. Landscape resistance, geographic distances and predation risk were correlated with genetic distances, with correlations threefold higher for sedentary than for migratory caribou. As local caribou populations are increasingly isolated, our results indicate the need to address genetic connectivity, especially for populations with individuals displaying different migratory behaviours, whilst maintaining quality habitat both within and across the ranges of threatened populations.

Original languageEnglish
Pages (from-to)199-211
Number of pages13
JournalEvolutionary Applications
Volume10
Issue number2
DOIs
StatePublished - Feb 1 2017

Keywords

  • Rangifer tarandus
  • connectivity
  • gene flow
  • isolation
  • landscape genetics
  • nuclear loci
  • reciprocal causal modelling

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