期刊
CANADIAN JOURNAL OF ZOOLOGY
卷 93, 期 11, 页码 813-821出版社
CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjz-2015-0005
关键词
Alces alces; disturbance; habitat selection; logistic regression; management; moose; remote sensing; receiver operating characteristic; resource selection function
类别
资金
- Forest Ecosystem Science Cooperative, Inc.
- National Research Council of Canada
- Ontario Ministry of Natural Resources
- Discovery, Strategic, and Collaborative Research grants from the Natural Sciences and Engineering Research Council of Canada
Site-specific variation in relative habitat abundance and disturbance regimes may produce differences in habitat preferences of associated populations. An evaluation of the predictive power of habitat selection models across space would benefit our understanding of the reliability of models of selection and space use in predicting animal occurrence. We used presence-absence data from winter surveys of moose (Alces alces (L., 1758)) to estimate resource selection functions (RSFs) across two study sites using Far North Land Cover updated with recent disturbance from fire and timber harvest. Moose selected foraging habitat (e.g., deciduous land cover) and for increasing deciduous foliage cover (Delta NDVI, i.e., the difference in the normalized difference vegetation index). Snow depth negatively influenced habitat selection, likely due to increased predation risk and reduced movement and foraging efficiency. Models lost little predictive power when applied to another site based on comparison of receiver operating characteristic (ROC) curves. Our results corroborated the current body of knowledge concerning moose habitat selection, i.e., moose preferentially use forest stands dominated by deciduous species, but suggested that moose strongly avoided very recently disturbed areas. Minimal site-specific variation and ROC comparison suggests that RSFs may be extended into novel systems, given adequate consideration for habitat quality and abundance, thereby simplifying management needs of this important species.
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