Comparing IUCN and Probabilistic Assessments of Threat: Do IUCN Red List Criteria Conflate Rarity and Threat?

Estimates of threat form an intrinsic element of World Conservation Union (IUCN) Red List criteria, and in the assignment of species to defined threat categories. However, assignment under the IUCN criteria is demanding in terms of the amount of information that is required. For many species adequat...

Full description

Saved in:
Bibliographic Details
Published inBiodiversity and conservation Vol. 15; no. 6; pp. 1903 - 1912
Main Authors Robbirt, Karen M, Roberts, David L, Hawkins, Julie A
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Nature B.V 01.06.2006
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Estimates of threat form an intrinsic element of World Conservation Union (IUCN) Red List criteria, and in the assignment of species to defined threat categories. However, assignment under the IUCN criteria is demanding in terms of the amount of information that is required. For many species adequate data are lacking. Further, many of the terms and parameters used under IUCN criteria are subjective and open to varying interpretations. During the last decade a number of probabilistic statistical models have been developed which use historical sighting data, such as herbarium and museum collections, to generate objective, quantitative inference of threat and extinction without the requirement for extensive formal survey procedures and where little or no other data exists. In this study these statistical models were applied to herbarium data for the genus Guzmania (Bromeliaceae) from Ecuador. The results suggest that, for species for which collection records are adequate, these methods can be of use in strengthening IUCN Red List assessment procedure. Further, these methods present a unique means of prioritising threat when few biological data are available.[PUBLICATION ABSTRACT]
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0960-3115
1572-9710
DOI:10.1007/s10531-005-4307-2