期刊
ECOLOGICAL MODELLING
卷 305, 期 -, 页码 10-21出版社
ELSEVIER
DOI: 10.1016/j.ecolmodel.2015.03.003
关键词
Grain; Habitat selection; Odocoileus virginianus; Perceptual range; Resource selection; Scale
类别
资金
- Parks Canada
- Manitoba Conservation
- Alberta Co-operative Conservation Research Unit (ACCRU)
- Louisiana-Pacific Inc.
- University of Alberta
- PrioNet Canada
- Natural Sciences and Engineering Research Council of Canada
- Saskatchewan Government
Like most aspects of ecology, the process of habitat or resource selection scales in space as well as time. However, scaling questions have generally focused on extent including size of study area and home ranges that dictate availability of resources. Grain of analysis (size of resource units used) is generally restricted to questions of methodology as opposed to functional ecology. Most often, grain is adopted as a point, unit, or patch that is common in size to all habitat resources used and available; however, in the process of habitat selection, it is feasible that individual animals may opt to select for different resources at different grains. For example, animals may use units of vegetation association at a finer grain when feeding or resting compared to when moving through habitat. Here we introduce and evaluate the 'multi-grain resource selection function', or MRSF. We generated MRSFs for a case study of GPS-collared white-tailed deer (Odocoileus virginianus; n=14) at Riding Mountain National Park, Manitoba, Canada. We created models across two seasons and extents and varied the radius around used and available points within which resource types were measured, and compared models to evaluate the relative importance of resource variables at different grains. We hypothesized that resource selection would vary with grain and that RSFs computed using multiple grains would be more predictive than models computed using a single grain as they better incorporate the space of influence on decision making in different habitat areas. We found that models of animals using grains of different sizes for different resource types were characterized by comparatively lower AIC scores. We conclude that scaling grain can and should be considered in models of resource selection, and that animals make decisions on resource selection at multiple grains. The MRSF, like analyses incorporating individual effects, density dependence, and functional responses, brings us closer to incorporating process, rather than only patterns, into the study of resource and habitat selection. (C) 2015 Elsevier B.V. All rights reserved.
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