Canadian Forest Service Publications

Critical remote sensing contributions to spatial wildlife ecological knowledge and management. 2010. McDermid, G.J.; Coops, N.C.; Wulder, M.A.; Franklin, S.E.; Seitz, N.E. Pages 193-221 (Chapter 11) in S.A. Cushman and F. Huettmann, editors. Spatial Complexity, Informatics and Wildlife Conservation. Springer, Tokyo-Japan. 458 p.

Year: 2010

Issued by: Pacific Forestry Centre

Catalog ID: 32144

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1007/978-4-431-87771-4_11

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Abstract

A spatial information management approach to applied wildlife ecology will rely on our capacity to link animal-based data sets — observations related to a species' distribution, abundance, health, or genetics, for example — to a variety of spatially explicit environmental variables. This idea is based on the general concept that an organism's characteristics and behaviors at both the individual and population levels are inextricably linked to the physical habitat in which it occurs (Guisan and Zimmermann 2000; Braun 2005). While the investigation of these links must be well-grounded by solid field observations, the multiple scales and extent over which information must be compiled suggests a key role for remote sensing instruments and related technologies. For example, it is becoming increasingly evident that the health of wild species is adversely affected by human activities and landscape change (e.g. Daszak et al. 2001; Farnsworth et al. 2005). Ongoing research may reveal a direct link between human-induced habitat changes and long-term physiological stress, leading to damaging health consequences in individual animals (i.e. impaired reproduction, diminished growth, suppressed immune function) and subsequent negative effects at the population level (i.e. low natality and survival rates, diminished abundance). An approach to understanding these relationships, based on sensitive and reliable measures of health, stress, and landscape change, is both urgently needed and impossible to conceive without remote sensing.