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Clarifying misconceptions of extinction risk assessment with the IUCN Red List

  • Ben Collen
  • , Nicholas K. Dulvy
  • , Kevin J. Gaston
  • , Ulf Gärdenfors
  • , David A. Keith
  • , André E. Punt
  • , Helen M. Regan
  • , Monika Böhm
  • , Simon Hedges
  • , Mary Seddon
  • , Stuart H.M. Butchart
  • , Craig Hilton-Taylor
  • , Michael Hoffmann
  • , Steven P. Bachman
  • , H. Reşit Akçakaya
  • University College London
  • Simon Fraser University
  • University of Exeter
  • Swedish Species Information Centre
  • University of New South Wales
  • NSW Department of Planning, Industry and Environment
  • University of Washington
  • University of California at Riverside
  • Zoological Society of London Institute of Zoology
  • Wildlife Conservation Society
  • IUCN Mollusc Specialist Group
  • BirdLife International
  • IUCN
  • UNEP-WCMC
  • Royal Botanic Gardens, Kew
  • University of Nottingham

Research output: Contribution to journalArticlepeer-review

154 Scopus citations

Abstract

The identification of species at risk of extinction is a central goal of conservation. As the use of data compiled for IUCN Red List assessments expands, a number of misconceptions regarding the purpose, application and use of the IUCN Red List categories and criteria have arisen. We outline five such classes of misconception; the most consequential drive proposals for adapted versions of the criteria, rendering assessments among species incomparable. A key challenge for the future will be to recognize the point where understanding has developed so markedly that it is time for the next generation of the Red List criteria. We do not believe we are there yet but, recognizing the need for scrutiny and continued development of Red Listing, conclude by suggesting areas where additional research could be valuable in improving the understanding of extinction risk among species.

Original languageEnglish
Article number20150843
JournalBiology Letters
Volume12
Issue number4
DOIs
StatePublished - Apr 1 2016

Keywords

  • Climate change
  • Geographical range
  • Population decline
  • Rarity
  • Spatial autocorrelation
  • Uncertainty

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