Circuit theory predicts gene flow in plant and animal populations

Brad H. McRae*,^† and
Paul Beier^‡

*National Center for Ecological Analysis and Synthesis, 735 State Street, Suite 300, Santa Barbara, CA 93101; and
^‡School of Forestry and Merriam–Powell Center for Environmental Research, Northern Arizona University, Flagstaff, AZ 86011

Edited by John C. Avise, University of California, Irvine, CA, and approved September 18, 2007 (received for review July 12, 2007)

Abstract

Maintaining connectivity for broad-scale ecological processes like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes. However, determining which habitats should be set aside to promote connectivity has been difficult because existing models cannot incorporate effects of multiple pathways linking populations. Here, we test an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory. The model vastly improves gene flow predictions because it simultaneously integrates all possible pathways connecting populations. When applied to data from threatened mammal and tree species, the model consistently outperformed conventional gene flow models, revealing that barriers were less important in structuring populations than previously thought. Circuit theory now provides the best-justified method to bridge landscape and genetic data, and holds much promise in ecology, evolution, and conservation planning.

Footnotes

^†To whom correspondence should be addressed. E-mail: mcrae{at}nceas.ucsb.edu
Author contributions: B.H.M. and P.B. designed research; B.H.M. performed research; B.H.M. contributed new reagents/analytic tools; B.H.M. analyzed data; and B.H.M. and P.B. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.