Predicting species distributions for conservation decisions

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. and Buckley, Yvonne M. (2013) Predicting species distributions for conservation decisions. Ecology Letters, 16 12: 1424-1435. doi:10.1111/ele.12189

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads

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.
Title Predicting species distributions for conservation decisions
Journal name Ecology Letters   Check publisher's open access policy
ISSN 1461-023X
1461-0248
Publication date 2013-12-01
Year available 2013
Sub-type Article (original research)
DOI 10.1111/ele.12189
Open Access Status DOI
Volume 16
Issue 12
Start page 1424
End page 1435
Total pages 12
Place of publication Chichester, West Sussex, United Kingdom
Publisher Wiley-Blackwell Publishing
Language eng
Abstract 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.
Formatted abstract
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.
Keyword Biological invasions
Conservation planning
Critical habitats
Environmental suitability
Reserve selection
Species distribution model
Structured decision making
Translocation
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID 226852
Institutional Status UQ

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 256 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 277 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 05 Nov 2013, 01:24:05 EST by Ms Ayesha Tulloch on behalf of School of Biological Sciences