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Inferring the extinction of species known only from a single specimen

Roberts, David L., Jaric, Ivan (2020) Inferring the extinction of species known only from a single specimen. Oryx, 54 (1-2). pp. 161-166. ISSN 0030-6053. (doi:10.1017/S0030605319000590) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:79524)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
https://doi.org/10.1017/S0030605319000590

Abstract

Many species are poorly known, with the sum of our knowledge represented by specimens in museums. For assessment of conservation status the most enigmatic and challenging species are probably those known only from a single specimen. We examine the potential persistence of such species using the orchid flora of Madagascar as a case study. We apply a statistical method that tests the like- lihood of species presence in relation to the time when a species was collected and a measure of annual collection ef- fort, calculated in three ways based on specimen collection over time. The results suggest that as of  up to nine of the  orchid species known from a single specimen may be inferred to be extinct under at least one of the three methods of estimating collection effort and extinction. In addition, up to two additional species are likely to be extinct by  assuming no new collections were made by that time. Substantial collection effort and/or additional evi- dence will be needed to reach a decision on the persistence of more recently observed species known only from a single collection. This represents a challenge for conservation prac- titioners.

Item Type: Article
DOI/Identification number: 10.1017/S0030605319000590
Uncontrolled keywords: Collection effort, extinction, herbarium specimen, Madagascar, museum specimen, orchid, Orchidaceae
Subjects: Q Science > QH Natural history
Q Science > QH Natural history > QH324.2 Computational biology
Q Science > QH Natural history > QH75 Conservation (Biology)
Q Science > QK Botany
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation
Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
Depositing User: David Roberts
Date Deposited: 09 Jan 2020 13:46 UTC
Last Modified: 05 Nov 2024 12:44 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/79524 (The current URI for this page, for reference purposes)

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