A graph-theory framework for evaluating landscape connectivity and conservation planning.

Published

Journal Article

Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.

Full Text

Duke Authors

Cited Authors

  • Minor, ES; Urban, DL

Published Date

  • April 2008

Published In

Volume / Issue

  • 22 / 2

Start / End Page

  • 297 - 307

PubMed ID

  • 18241238

Pubmed Central ID

  • 18241238

Electronic International Standard Serial Number (EISSN)

  • 1523-1739

International Standard Serial Number (ISSN)

  • 0888-8892

Digital Object Identifier (DOI)

  • 10.1111/j.1523-1739.2007.00871.x

Language

  • eng