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Using expert knowledge effectively: Lessons from species distribution models for wildlife conservation and management

Citation

Johnson, CJ and Hurley, M and Rapaport, E and Pullinger, MG, Using expert knowledge effectively: Lessons from species distribution models for wildlife conservation and management, Expert Knowledge and Its Application in Landscape Ecology, Springer, AH Perera, CA Drew, CJ Johnson (ed), New York, United States, pp. 153-172. ISBN 978-1-4614-1033-1 (2012) [Research Book Chapter]

Copyright Statement

Copyright 2012 Springer Science+Business Media, LLC

DOI: doi:10.1007/978-1-4614-1034-8_8

Abstract

The spatial and temporal relationships between organisms and their environments are fundamental to both theoretical and applied ecology. The heterogeneous distribution of organisms in space and time will influence most ecological relationships, including predation, competition, and resource use, and. ultimately, population dynamics and evolution (Turchin 1996). Recognizing that the science and practice of ecology involves a consideration of spatial processes, much recent research has focused on formally representing and quantifying the spatial and temporal relationships between organisms and their environments (Morales et al. 2010). One prominent area of investigation for landscape ecologists has been the development of statistical models and associated analyses that empirically represent those relationships (Elith and Leathwick 2009). This set of methods has become known as "species distribution models" (SDMs). Guisan and Thuiller (2005) define SDMs as" ... empirical models relating field observations to environmental predictor variables, based on statistically or theoretically derived response surfaces."

Item Details

Item Type:Research Book Chapter
Keywords:species distribution models, wildlife conservation, wildlife management, expert knowledge
Research Division:Environmental Sciences
Research Group:Environmental Science and Management
Research Field:Environmental Management
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management not elsewhere classified
Author:Pullinger, MG (Mr Michael Pullinger)
ID Code:116538
Year Published:2012
Web of Science® Times Cited:6
Deposited By:Geography and Spatial Science
Deposited On:2017-05-12
Last Modified:2017-10-16
Downloads:0

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