How Well Can We Predict Wildlife Corridors? Tests of Alternative Modeling Approaches in Migratory Elk and Dispersing Wolverines

Scientific Disciplines
Biological Sciences - Terrestrial
Montana State University
landscape connectivity
modeling approaches
circuit theory models
landscape modeling approaches
Volume 18, No. 1-4

How well can we predict wildlife corridors?  
Tests of alternative modeling approaches in 
Migratory elk and dispersing wolverines
Meredith M. Rainey*, Ecology Department, Montana State University, Bozeman, Montana 59717
Andrew J. Hansen, Ecology Department, Montana State University, Bozeman, Montana 59717
Landscape connectivity has become a key focus of conservation biology as natural habitat 
is increasingly fragmented by human land use.  Several landscape modeling approaches are 
now relied upon to identify likely dispersal and migration corridors and guide conservation 
planning. However, the predictive accuracy of these methods has seen limited testing against 
empirical movement data, which limits confidence in their utility and confuses selection of 
appropriate methods for a given application.  To address these issues, we used GPS collar data 
from migrating elk and dispersing wolverines to evaluate the ability of common modeling 
approaches (cost-distance/least-cost path models and circuit theory models) to predict 
observed movement routes.  While both methods made generally similar predictions, cost-
distance models consistently outperformed circuit theory models, and predictive success was 
much higher for elk than for wolverine movements.  Furthermore, the form and complexity of 
underlying landscape resistance maps influenced model performance and revealed unforeseen 
differences between models.  These findings illustrate that corridor model performance 
depends greatly on focal species and landscape characteristics as well as selection of 
appropriate methods for the application at hand.