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Landscape Ecology

, Volume 27, Issue 2, pp 253–266 | Cite as

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

  • Tabitha A. Graves
  • Tzeidle N. Wasserman
  • Milton Cezar Ribeiro
  • Erin L. Landguth
  • Stephen F. Spear
  • Niko Balkenhol
  • Colleen B. Higgins
  • Marie-Josée Fortin
  • Samuel A. Cushman
  • Lisette P. Waits
Research Article

Abstract

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range or measurement error in plant or animal locations. In this study, we evaluate the ways that spatial uncertainty, landscape characteristics, and genetic stochasticity interact to influence the strength and variability of conclusions about landscape-genetics relationships. We used a neutral landscape model to generate 45 landscapes composed of habitat and non-habitat, varying in percent habitat, aggregation, and structural connectivity (patch cohesion). We created true and alternate locations for 500 individuals, calculated ecological distances (least-cost paths), and simulated genetic distances among individuals. We compared correlations between ecological distances for true and alternate locations. We then simulated genotypes at 15 neutral loci and investigated whether the same influences could be detected in simple Mantel tests and while controlling for the effects of isolation-by-distance using the partial Mantel test. Spatial uncertainty interacted with the percentage of habitat in the landscape, but led to only small reductions in correlations. Furthermore, the strongest correlations occurred with low percent habitat, high aggregation, and low to intermediate levels of cohesion. Overall genetic stochasticity was relatively low and was influenced by landscape characteristics.

Keywords

Least cost Habitat resistance Fragmentation Genetic structure Sampling error Aggregation Cohesiveness Connectivity Gene flow Isolation-by-resistance 

Notes

Acknowledgments

We thank Brent Burch, Kevin McGarigal, and John Citta for useful discussions on modeling random effects. This study resulted from a distributed graduate seminar (developing best practices for testing landscape effects on gene flow), conducted through the National Center for Ecological Analysis and Synthesis (NCEAS), a center funded by the National Science Foundation Grant #EF-0553768, the University of California, Santa Barbara, and the State of California. We thank Carisa Stansbury and Rodrigo Cisneros for assistance with preliminary simulations. This was a truly collaborative project. Contributions of each coauthor are listed in Supplement II. We appreciate our individual sources of support, including scholarship, fellowship and research assistantship providers. We also thank 2 anonymous reviewers.

Supplementary material

10980_2011_9701_MOESM1_ESM.docx (20 kb)
Supplementary material 1 (DOCX 20 kb)

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Copyright information

© Springer Science+Business Media B.V. (outside the USA) 2011

Authors and Affiliations

  • Tabitha A. Graves
    • 1
  • Tzeidle N. Wasserman
    • 1
  • Milton Cezar Ribeiro
    • 2
    • 7
  • Erin L. Landguth
    • 3
  • Stephen F. Spear
    • 4
    • 5
  • Niko Balkenhol
    • 6
  • Colleen B. Higgins
    • 7
  • Marie-Josée Fortin
    • 8
  • Samuel A. Cushman
    • 9
  • Lisette P. Waits
    • 5
  1. 1.School of Forestry, Northern Arizona UniversityFlagstaffUSA
  2. 2.Departamento de EcologiaUniversidade Estadual Paulista (UNESP)Rio ClaroBrazil
  3. 3.Division of Biological SciencesUniversity of MontanaMissoulaUSA
  4. 4.Orianne SocietyClaytonUSA
  5. 5.Department of Fish and Wildlife ResourcesUniversity of IdahoMoscowUSA
  6. 6.Department of Forest Zoology and Forest ConservationUniversity of GoettingenGoettingenGermany
  7. 7.Department of Integrative Life SciencesVirginia Commonwealth UniversityRichmondUSA
  8. 8.Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoCanada
  9. 9.Forest Service Research Station, US Forest ServiceFlagstaffUSA

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