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Commentary: IUCN classifications under uncertainty

Akçakaya, HR; Ferson, S; Burgman, MA; Keith, DA; Mace, GM; Todd, CR; (2012) Commentary: IUCN classifications under uncertainty. Environmental Modelling and Software , 38 119 - 121. 10.1016/j.envsoft.2012.05.009.

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Abstract

We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15-23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data. © 2012 Elsevier Ltd.

Type:Article
Title:Commentary: IUCN classifications under uncertainty
DOI:10.1016/j.envsoft.2012.05.009
UCL classification:UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Biosciences (Division of) > Genetics, Evolution and Environment

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