Article

Landscape Ecology

, Volume 19, Issue 8, pp 869-882

Quantifying patch distribution at multiple spatial scales: applications to wildlife-habitat models

  • Chris J. JohnsonAffiliated withDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9Ecosystem Science and Management Program, University of Northern British Columbia
  • , Mark S. BoyceAffiliated withDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9
  • , Robert MuldersAffiliated withDepartment of Resources, Wildlife and Economic Development, Government of Northwest Territories
  • , Anne GunnAffiliated withDepartment of Resources, Wildlife and Economic Development, Government of Northwest Territories
  • , Rob J. GauAffiliated withDepartment of Resources, Wildlife and Economic Development, Government of Northwest Territories
  • , H. Dean CluffAffiliated withDepartment of Resources, Wildlife and Economic Development, Government of Northwest Territories
  • , Ray L. CaseAffiliated withDepartment of Resources, Wildlife and Economic Development, Government of Northwest Territories

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Abstract

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.

Canadian Arctic Habitat Hierarchy Landscape pattern Local quadrat variance Resource selection Scale