Landscape Ecology

, Volume 29, Issue 4, pp 605–619

Using network theory to prioritize management in a desert bighorn sheep metapopulation

Authors

    • Department of Fisheries and WildlifeOregon State University
  • Clinton W. Epps
    • Department of Fisheries and WildlifeOregon State University
  • Ryan J. Monello
    • National Park ServiceBiological Resource Management Division
  • John D. Wehausen
    • White Mountain Research StationUniversity of California
Research Article

DOI: 10.1007/s10980-014-0016-0

Cite this article as:
Creech, T.G., Epps, C.W., Monello, R.J. et al. Landscape Ecol (2014) 29: 605. doi:10.1007/s10980-014-0016-0

Abstract

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.

Keywords

ColonizationConnectivityDispersalExtinctionFragmented populationGene flowGraph theoryHabitat patchLandscape resistance

Supplementary material

10980_2014_16_MOESM1_ESM.docx (4.1 mb)
Supplementary material 1 (DOCX 4211 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2014