The use and misuse of herbarium specimens in evaluating plant extinction risks. (19th November 2018)
- Record Type:
- Journal Article
- Title:
- The use and misuse of herbarium specimens in evaluating plant extinction risks. (19th November 2018)
- Main Title:
- The use and misuse of herbarium specimens in evaluating plant extinction risks
- Authors:
- Nic Lughadha, Eimear
Walker, Barnaby E.
Canteiro, Cátia
Chadburn, Helen
Davis, Aaron P.
Hargreaves, Serene
Lucas, Eve J.
Schuiteman, André
Williams, Emma
Bachman, Steven P.
Baines, David
Barker, Amy
Budden, Andrew P.
Carretero, Julia
Clarkson, James J.
Roberts, Alexandra
Rivers, Malin C. - Abstract:
- Abstract : Herbarium specimens provide verifiable and citable evidence of the occurrence of particular plants at particular points in space and time, and are vital resources for assessing extinction risk in the tropics, where plant diversity and threats to plants are greatest. We reviewed approaches to assessing extinction risk in response to the Convention on Biological Diversity's Global Strategy for Plant Conservation Target 2: an assessment of the conservation status of all known plant species by 2020. We tested five alternative approaches, using herbarium-derived data for trees, shrubs and herbs in five different plant groups from temperate and tropical regions. All species were previously fully assessed for the IUCN Red List. We found significant variation in the accuracy with which different approaches classified species as threatened or not threatened. Accuracy was highest for the machine learning model (90%) but the least data-intensive approach also performed well (82%). Despite concerns about spatial, temporal and taxonomic biases and uncertainties in herbarium data, when specimens represent the best available evidence for particular species, their use as a basis for extinction risk assessment is appropriate, necessary and urgent. Resourcing herbaria to maintain, increase and disseminate their specimen data is essential to guide and focus conservation action. This article is part of the theme issue 'Biological collections for understanding biodiversity in theAbstract : Herbarium specimens provide verifiable and citable evidence of the occurrence of particular plants at particular points in space and time, and are vital resources for assessing extinction risk in the tropics, where plant diversity and threats to plants are greatest. We reviewed approaches to assessing extinction risk in response to the Convention on Biological Diversity's Global Strategy for Plant Conservation Target 2: an assessment of the conservation status of all known plant species by 2020. We tested five alternative approaches, using herbarium-derived data for trees, shrubs and herbs in five different plant groups from temperate and tropical regions. All species were previously fully assessed for the IUCN Red List. We found significant variation in the accuracy with which different approaches classified species as threatened or not threatened. Accuracy was highest for the machine learning model (90%) but the least data-intensive approach also performed well (82%). Despite concerns about spatial, temporal and taxonomic biases and uncertainties in herbarium data, when specimens represent the best available evidence for particular species, their use as a basis for extinction risk assessment is appropriate, necessary and urgent. Resourcing herbaria to maintain, increase and disseminate their specimen data is essential to guide and focus conservation action. This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'. … (more)
- Is Part Of:
- Philosophical transactions. Volume 374:Number 1763(2019)
- Journal:
- Philosophical transactions
- Issue:
- Volume 374:Number 1763(2019)
- Issue Display:
- Volume 374, Issue 1763 (2019)
- Year:
- 2019
- Volume:
- 374
- Issue:
- 1763
- Issue Sort Value:
- 2019-0374-1763-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-11-19
- Subjects:
- natural history collections -- IUCN Red List -- conservation assessment -- digitization -- machine learning -- extent of occurrence
Biology -- Periodicals
Science -- Periodicals
570 - Journal URLs:
- https://royalsocietypublishing.org/loi/rstb ↗
- DOI:
- 10.1098/rstb.2017.0402 ↗
- Languages:
- English
- ISSNs:
- 0962-8436
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 9067.xml