Determining the drivers of population structure in a highly urbanized landscape to inform conservation planning

Conserv Biol. 2018 Feb;32(1):148-158. doi: 10.1111/cobi.12969. Epub 2017 Oct 30.

Abstract

Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human-dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home-range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11-81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions.

Keywords: Montañas de Santa Mónica; Santa Monica Mountains; adaptive variation; cambio climático; climate change; conservation planning; genética de paisajes; genética poblacional; landscape genetics; population genetics; variación adaptativa; vertebrados; vertebrates.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • California
  • Conservation of Natural Resources*
  • Ecosystem
  • Gene Flow
  • Genetic Variation
  • Genetics, Population*
  • Humans