A framework for modeling habitat quality in disturbance‐prone areas demonstrated with woodland caribou and wildfire

• Published in: Ecosphere
• Main Authors: Whitman, Ellen, Parisien, Marc‐André, Price, David T., St‐Laurent, Martin‐Hugues, Johnson, Chris J., DeLancey, Evan R., Arseneault, Dominique, Flannigan, Mike D.
• Other Authors: Natural Resources Canada
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2017
• Subjects: Ecology; Ecology, Evolution, Behavior and Systematics; Rangifer tarandus
• Online Access: http://dx.doi.org/10.1002/ecs2.1787; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.1787; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.1787; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.1787; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.1787

Abstract Natural resource management professionals require adaptable spatial tools for conserving and managing wildlife across landscapes. These tools should integrate multiple components of habitat quality and incorporate local disturbance regimes. We provide a spatial modeling framework that integrates three components of habitat (nutritional resources, connectivity, and predation risk) into indices of habitat quality under a simulated wildfire disturbance regime. Woodland caribou ( Rangifer tarandus caribou ), a species of conservation concern, is used to illustrate our framework. We simulated disturbance from wildfire on two boreal forest landscapes to produce stand ages, from which we computed and integrated the three habitat indicator components using different schemes. Spatial variation in the influence of wildfire and the distribution of the three components of habitat resulted in heterogeneous patterns of habitat quality. The inclusion of disturbance led to a different habitat quality landscape than that of a static model in which the influence of wildfire on vegetation communities was not considered, incorporating the likelihood of persistence into the overall representation of habitat quality. The integration of nutrition, connectivity, and predation risk into a single index of habitat quality produced spatial patterns distinct from maps of the individual components. Regardless of whether the components were combined through additive, multiplicative, or minimum habitat quality threshold methods, areas of very high‐ and poor‐quality habitat were found at consistent locations across the landscape, suggesting that these two types of regions provide opportunities for long‐term management interventions. The framework presented here is adaptable and modular; it could be modified and applied to other species, regions, and disturbance regimes. It provides a nuanced representation of persistent habitat and has the potential to be a useful tool for conservation planning.