Predicting species distributions for conservation decisions
Commonwealth Scientific and Industrial Research Organisation · The University of Queensland · +13 more institutions
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…
Citation impact
- FWCI
- 110.07
- Percentile
- 100%
- References
- 75
Authors
23- AGAntoine GuisanCorresponding
Commonwealth Scientific and Industrial Research Organisation, The University of Queensland, ARC Centre of Excellence for Environmental Decisions, Ecosystem Sciences, University of Lausanne
- RTReid Tingley
The University of Melbourne, ARC Centre of Excellence for Environmental Decisions
- JBJohn B. Baumgartner
The University of Melbourne, ARC Centre of Excellence for Environmental Decisions
- INIlona Naujokaitis‐Lewis
University of Toronto
- PSPatricia Sutcliffe
The University of Queensland, ARC Centre of Excellence for Environmental Decisions
Topics & keywords
- Process (computing)
- Identification (biology)
- Endangered species
- Computer science
- Decision support system
- Construct (python library)
- Distribution (mathematics)
- Management science
- Life in Land