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Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus)
The purpose of this study was to determine whether limited occurrence data for highly threatened species can provide useful spatial information to inform conservation. The study was conducted across central and southern China. We developed a habitat suitability model for the Critically Endangered Ch...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869214/ https://www.ncbi.nlm.nih.gov/pubmed/29607009 http://dx.doi.org/10.1002/ece3.3862 |
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author | Chen, Shu Cunningham, Andrew A. Wei, Gang Yang, Jian Liang, Zhiqiang Wang, Jie Wu, Minyao Yan, Fang Xiao, Hanbin Harrison, Xavier A. Pettorelli, Nathalie Turvey, Samuel T. |
author_facet | Chen, Shu Cunningham, Andrew A. Wei, Gang Yang, Jian Liang, Zhiqiang Wang, Jie Wu, Minyao Yan, Fang Xiao, Hanbin Harrison, Xavier A. Pettorelli, Nathalie Turvey, Samuel T. |
author_sort | Chen, Shu |
collection | PubMed |
description | The purpose of this study was to determine whether limited occurrence data for highly threatened species can provide useful spatial information to inform conservation. The study was conducted across central and southern China. We developed a habitat suitability model for the Critically Endangered Chinese giant salamander (Andrias davidianus) based on one biotic and three abiotic parameters from single‐site locality records, which represent the only relevant environmental data available for this species. We then validated model quality by testing whether increased percentage of predicted suitable habitat at the county level correlated with independent data on giant salamander presence. We randomly selected 48 counties containing historical records which were distinct from, and independent of, the single‐site records used to develop the model, and 47 additional counties containing >50% predicted suitable habitat. We interviewed 2,812 respondents near potential giant salamander habitat across these counties and tested for differences in respondent giant salamander reports between counties selected using each method. Our model predicts that suitable giant salamander habitat is found widely across central and southern China, with counties containing ≥50% predicted suitable habitat distributed in 13 provinces. Counties with historical records contain significantly more predicted suitable habitat than counties without historical records. There are no statistical differences in any patterns of respondent giant salamander reports in surveyed counties selected from our model compared with the areas of known historical giant salamander distribution. A Chinese giant salamander habitat suitability model with strong predictive power can be derived from the restricted range of environmental variables associated with limited available presence‐only occurrence records, constituting a cost‐effective strategy to guide spatial allocation of conservation planning. Few reported sightings were recent, however, with most being over 20 years old, so that identification of areas of suitable habitat does not necessarily indicate continued survival of the species at these locations. |
format | Online Article Text |
id | pubmed-5869214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58692142018-03-30 Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) Chen, Shu Cunningham, Andrew A. Wei, Gang Yang, Jian Liang, Zhiqiang Wang, Jie Wu, Minyao Yan, Fang Xiao, Hanbin Harrison, Xavier A. Pettorelli, Nathalie Turvey, Samuel T. Ecol Evol Original Research The purpose of this study was to determine whether limited occurrence data for highly threatened species can provide useful spatial information to inform conservation. The study was conducted across central and southern China. We developed a habitat suitability model for the Critically Endangered Chinese giant salamander (Andrias davidianus) based on one biotic and three abiotic parameters from single‐site locality records, which represent the only relevant environmental data available for this species. We then validated model quality by testing whether increased percentage of predicted suitable habitat at the county level correlated with independent data on giant salamander presence. We randomly selected 48 counties containing historical records which were distinct from, and independent of, the single‐site records used to develop the model, and 47 additional counties containing >50% predicted suitable habitat. We interviewed 2,812 respondents near potential giant salamander habitat across these counties and tested for differences in respondent giant salamander reports between counties selected using each method. Our model predicts that suitable giant salamander habitat is found widely across central and southern China, with counties containing ≥50% predicted suitable habitat distributed in 13 provinces. Counties with historical records contain significantly more predicted suitable habitat than counties without historical records. There are no statistical differences in any patterns of respondent giant salamander reports in surveyed counties selected from our model compared with the areas of known historical giant salamander distribution. A Chinese giant salamander habitat suitability model with strong predictive power can be derived from the restricted range of environmental variables associated with limited available presence‐only occurrence records, constituting a cost‐effective strategy to guide spatial allocation of conservation planning. Few reported sightings were recent, however, with most being over 20 years old, so that identification of areas of suitable habitat does not necessarily indicate continued survival of the species at these locations. John Wiley and Sons Inc. 2018-02-16 /pmc/articles/PMC5869214/ /pubmed/29607009 http://dx.doi.org/10.1002/ece3.3862 Text en © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Chen, Shu Cunningham, Andrew A. Wei, Gang Yang, Jian Liang, Zhiqiang Wang, Jie Wu, Minyao Yan, Fang Xiao, Hanbin Harrison, Xavier A. Pettorelli, Nathalie Turvey, Samuel T. Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title | Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title_full | Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title_fullStr | Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title_full_unstemmed | Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title_short | Determining threatened species distributions in the face of limited data: Spatial conservation prioritization for the Chinese giant salamander (Andrias davidianus) |
title_sort | determining threatened species distributions in the face of limited data: spatial conservation prioritization for the chinese giant salamander (andrias davidianus) |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869214/ https://www.ncbi.nlm.nih.gov/pubmed/29607009 http://dx.doi.org/10.1002/ece3.3862 |
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