Identification of landscape features influencing gene flow: How useful are habitat selection models?

Gretchen H. Roffler, Michael K. Schwartz, Kristy L. Pilgrim, Sandra L. Talbot, George K. Sage, Layne G. Adams, Gordon Luikart

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid-range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long-term genetic connectivity.

Original languageEnglish
Pages (from-to)805-817
Number of pages13
JournalEvolutionary Applications
Issue number6
StatePublished - Jul 1 2016


  • Ovis dalli dalli
  • dispersal
  • landscape genetics
  • multiple regression on distance matrices
  • population connectivity
  • resistance surfaces
  • resource selection function


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