Towards reassessing data-deficient species

Bland, Lucie M., Bielby, Jon, Kearney, Stephen, Orme, C. David L., Watson, James E. M. and Collen, Ben (2017) Towards reassessing data-deficient species. Conservation Biology, 31 3: 531-539. doi:10.1111/cobi.12850

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Author Bland, Lucie M.
Bielby, Jon
Kearney, Stephen
Orme, C. David L.
Watson, James E. M.
Collen, Ben
Title Towards reassessing data-deficient species
Journal name Conservation Biology   Check publisher's open access policy
ISSN 0888-8892
1523-1739
Publication date 2017-06-01
Year available 2017
Sub-type Article (original research)
DOI 10.1111/cobi.12850
Open Access Status File (Author Post-print)
Volume 31
Issue 3
Start page 531
End page 539
Total pages 9
Place of publication Malden, United States
Publisher Wiley-Blackwell Publishing
Language eng
Abstract One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data-deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data-deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data-deficient assessments. To develop this, we reviewed 2879 data-deficient assessments in 6 animal groups and identified 8 main justifications for assigning data-deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data-deficient species slipping unnoticed toward extinction.
Formatted abstract
One in six species (13,465 spp.) on the IUCN Red List are currently classified as Data Deficient due to lack of information on their taxonomy, population status or impact of threats. Despite the chance that many are at high risk of extinction, Data Deficient species are typically excluded from global and local conservation priorities as well as funding schemes. The number of Data Deficient species will greatly increase as the Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of Data Deficient assessments. To develop this, we reviewed 2,879 Data Deficient assessments in six animal groups and identified eight main justifications for assigning Data Deficient status (type series, few records, old records, uncertain provenance, uncertain population status and/or distribution, uncertain threats, taxonomic uncertainty, new species). Assigning a consistent set of justification tags to species classified as Data Deficient is a simple way to achieve more strategic assessments. Such tags will: clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for re-assessment. With renewed efforts, it could be straightforward to prevent thousands of Data Deficient species slipping unnoticed towards extinction.
Keyword Biodiversity Conservation
Ecology
Environmental Sciences
Biodiversity & Conservation
Environmental Sciences & Ecology
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID LP 130100435
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
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Created: Mon, 10 Oct 2016, 22:47:41 EST by James Watson on behalf of School of Geography, Planning & Env Management