Conservation Genetics

, Volume 14, Issue 2, pp 263–274 | Cite as

Landscape genetics and limiting factors

  • Samuel A. Cushman
  • Andrew J. Shirk
  • Erin L. Landguth
Research Article

Abstract

Population connectivity is mediated by the movement of organisms or propagules through landscapes. However, little is known about how variation in the pattern of landscape mosaics affects the detectability of landscape genetic relationships. The goal of this paper is to explore the impacts of limiting factors on landscape genetic processes using simulation modeling. We used spatially explicit, individual-based simulation modeling to quantify the effects of habitat area, fragmentation and the contrast in resistance between habitat and non-habitat on the apparent strength and statistical detectability of landscape genetic relationships. We found that landscape genetic effects are often not detectable when habitat is highly connected. In such situations landscape structure does not limit gene flow. We also found that contrast in resistance values between habitat and non-habitat interacts with habitat extensiveness and fragmentation to affect detectability of landscape genetic relationships. Thus, the influence of landscape features critical to providing connectivity may not be detectable if gene flow is not limited by spatial patterns or resistance contrast of these features. We developed regression equations that reliably predict whether or not isolation by resistance will be detected independently of isolation by distance as a function of habitat fragmentation and contrast in resistance between habitat and non-habitat.

Keywords

Landscape genetics Limiting factors CDPOP Fragmentation thresholds Simulation modeling 

Supplementary material

10592_2012_396_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 17 kb)

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Copyright information

© Springer Science+Business Media B.V. (outside the USA)  2012

Authors and Affiliations

  • Samuel A. Cushman
    • 1
  • Andrew J. Shirk
    • 2
  • Erin L. Landguth
    • 3
  1. 1.Rocky Mountain Research StationU.S. Forest ServiceFlagstaffUSA
  2. 2.JISAO Climate Impacts GroupUniversity of WashingtonSeattleUSA
  3. 3.Division of Biological SciencesUniversity of MontanaMissoulaUSA

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