Predicting species distributions for conservation decisions. (17th October 2013)

• Record Type: Journal Article
• Authors: 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.
• Editors: Arita, Hector
• Is Part Of: Ecology letters. Volume 16:Number 12(2013:Dec.)
• Page Start: 1424
• Page End: 1435
• Publication Date: 2013-10-17
• Subjects: Biological invasions -- conservation planning -- critical habitats -- environmental suitability -- reserve selection -- species distribution model -- structured decision making -- translocation; Ecology -- Periodicals; 577
• DOI: 10.1111/ele.12189
• Languages: English
• ISSNs: 1461-023X

Abstract

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.