4.7 Article

Adapting the IUCN Red List criteria for invertebrates

Journal

BIOLOGICAL CONSERVATION
Volume 144, Issue 10, Pages 2432-2440

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.biocon.2011.06.020

Keywords

Arthropoda; Conservation priority; Extinction; Risk assessment; Threatened species; World Conservation Union

Funding

  1. Portuguese Foundation for Science and Technology [SFRH/BPD/40688/2007]
  2. Direccao Regional dos Recursos Florestais [17.01-080203]

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The IUCN Red List is the most useful list of species that are at risk for extinction worldwide, as it relies on a number of objective criteria. Nevertheless, there is a taxonomic bias that excludes species with small body sizes, narrow distribution ranges and low dispersal abilities, which constitute the vast Majority of the planet's biota, particularly local endemics. By evaluating each IUCN criterion separately, we (i) identify the shortcomings for invertebrate applications, (ii) explain how risk categories may be wrongly applied due to inapplicable and/or misleading thresholds, (iii) suggest alternative ways of applying the existing criteria in a more realistic way and (iv) suggest possible new criteria that were not considered in the current evaluation framework but that could allow a more comprehensive and effective assessment of invertebrates. By adapting the criteria to rely more explicitly on the Area of Occupancy and the Extent of Occurrence, their respective trends and by using ecological modelling methods, the criteria's applicability would be increased. The change in some thresholds or, eventually, the creation of sub-categories would further increase their adequacy. Additionally, co-extinction could be introduced as an explicit part of the classification process. As a case study, we evaluated 48 species of Azorean arthropods and Iberian spiders according to the current criteria. More than one-quarter (27%) of all evaluated species were classified as Critically Endangered, 19% as Endangered, 6% as Vulnerable and 8% as Least Concern. The remaining 40% did not have enough data to reach a classification. (C) 2011 Elsevier Ltd. All rights reserved.

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