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Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change
Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance i...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4130446/ https://www.ncbi.nlm.nih.gov/pubmed/25165526 http://dx.doi.org/10.1002/ece3.1133 |
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author | Wan, Jizhong Wang, Chunjing Yu, Jinghua Nie, Siming Han, Shijie Zu, Yuangang Chen, Changmei Yuan, Shusheng Wang, Qinggui |
author_facet | Wan, Jizhong Wang, Chunjing Yu, Jinghua Nie, Siming Han, Shijie Zu, Yuangang Chen, Changmei Yuan, Shusheng Wang, Qinggui |
author_sort | Wan, Jizhong |
collection | PubMed |
description | Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change. |
format | Online Article Text |
id | pubmed-4130446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-41304462014-08-27 Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change Wan, Jizhong Wang, Chunjing Yu, Jinghua Nie, Siming Han, Shijie Zu, Yuangang Chen, Changmei Yuan, Shusheng Wang, Qinggui Ecol Evol Original Research Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change. Blackwell Publishing Ltd 2014-07 2014-06-14 /pmc/articles/PMC4130446/ /pubmed/25165526 http://dx.doi.org/10.1002/ece3.1133 Text en © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Wan, Jizhong Wang, Chunjing Yu, Jinghua Nie, Siming Han, Shijie Zu, Yuangang Chen, Changmei Yuan, Shusheng Wang, Qinggui Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title | Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title_full | Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title_fullStr | Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title_full_unstemmed | Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title_short | Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change |
title_sort | model-based conservation planning of the genetic diversity of phellodendron amurense rupr due to climate change |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4130446/ https://www.ncbi.nlm.nih.gov/pubmed/25165526 http://dx.doi.org/10.1002/ece3.1133 |
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