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Predicting species distributions for conservation decisions

Ecology letters, 2013-12, Vol.16 (12), p.1424-1435 [Peer Reviewed Journal]

2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS ;2015 INIST-CNRS ;2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS. ;2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS 2013 ;ISSN: 1461-023X ;EISSN: 1461-0248 ;DOI: 10.1111/ele.12189 ;PMID: 24134332

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Title:
Predicting species distributions for conservation decisions
Author: Guisan, Antoine ; Tingley, Reid ; Baumgartner, John B. ; Naujokaitis-Lewis, Ilona ; Sutcliffe, Patricia R. ; Tulloch, Ayesha I. T. ; Regan, Tracey J. ; Brotons, Lluis ; McDonald-Madden, Eve ; Mantyka-Pringle, Chrystal ; Martin, Tara G. ; Rhodes, Jonathan R. ; Maggini, Ramona ; Setterfield, Samantha A. ; Elith, Jane ; Schwartz, Mark W. ; Wintle, Brendan A. ; Broennimann, Olivier ; Austin, Mike ; Ferrier, Simon ; Kearney, Michael R. ; Possingham, Hugh P. ; Buckley, Yvonne M.
Arita, Hector ; Arita, Hector
Subjects: Animal and plant ecology ; Animal, plant and microbial ecology ; Applied ecology ; Biological and medical sciences ; Biological invasions ; Conservation biology ; Conservation of Natural Resources ; conservation planning ; Conservation, protection and management of environment and wildlife ; critical habitats ; Decision Making ; Decision Support Techniques ; Dispersal ; Ecology - methods ; Endangered & extinct species ; Endangered Species ; environmental suitability ; Fundamental and applied biological sciences. Psychology ; General aspects ; Idea and ; Models, Theoretical ; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking ; Research Design ; reserve selection ; species distribution model ; structured decision making ; translocation
Is Part Of: Ecology letters, 2013-12, Vol.16 (12), p.1424-1435
Description: Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on‐ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision‐making contexts when used within a structured and transparent decision‐making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision‐making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
Publisher: Oxford: Blackwell Publishing Ltd
Language: English
Identifier: ISSN: 1461-023X
EISSN: 1461-0248
DOI: 10.1111/ele.12189
PMID: 24134332
Source: MEDLINE
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Predicting species distributions for conservation decisions

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