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Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change

Climate change influences species geographical distribution and diversity pattern. The Chinese fire‐bellied newt (Cynops orientalis) is an endemic species distributed in East‐central China, which has been classified as near‐threatened species recently due to habitat destruction and degradation and i...

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Autores principales: Guo, Kun, Yuan, Sijia, Wang, Hao, Zhong, Jun, Wu, Yanqing, Chen, Wan, Hu, Chaochao, Chang, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328465/
https://www.ncbi.nlm.nih.gov/pubmed/34367565
http://dx.doi.org/10.1002/ece3.7822
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author Guo, Kun
Yuan, Sijia
Wang, Hao
Zhong, Jun
Wu, Yanqing
Chen, Wan
Hu, Chaochao
Chang, Qing
author_facet Guo, Kun
Yuan, Sijia
Wang, Hao
Zhong, Jun
Wu, Yanqing
Chen, Wan
Hu, Chaochao
Chang, Qing
author_sort Guo, Kun
collection PubMed
description Climate change influences species geographical distribution and diversity pattern. The Chinese fire‐bellied newt (Cynops orientalis) is an endemic species distributed in East‐central China, which has been classified as near‐threatened species recently due to habitat destruction and degradation and illegal trade in the domestic and international pet markets. So far, little is known about the spatial distribution of the species. Based on bioclimatic data of the current and future climate projections, we modeled the change in suitable habitat for C. orientalis by ten algorithms, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. In this study, 46 records of C. orientalis from East China and 8 bioclimatic variables were used. Among the ten modeling algorithms, four (GAM, GBM, Maxent, and RF) were selected according to their predictive abilities. The current habitat suitability showed that C. orientalis had a relatively wide but fragmented distribution, and it encompassed 41,862 km(2). The models suggested that precipitation of warmest quarter (bio18) and mean temperature of wettest quarter (bio6) had the highest contribution to the model. This study revealed that C. orientalis is sensitive to climate change, which will lead to a large range shift. The projected spatial and temporal pattern of range shifts for C. orientalis should provide a useful reference for implementing long‐term conservation and management strategies for amphibians in East China.
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spelling pubmed-83284652021-08-06 Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change Guo, Kun Yuan, Sijia Wang, Hao Zhong, Jun Wu, Yanqing Chen, Wan Hu, Chaochao Chang, Qing Ecol Evol Original Research Climate change influences species geographical distribution and diversity pattern. The Chinese fire‐bellied newt (Cynops orientalis) is an endemic species distributed in East‐central China, which has been classified as near‐threatened species recently due to habitat destruction and degradation and illegal trade in the domestic and international pet markets. So far, little is known about the spatial distribution of the species. Based on bioclimatic data of the current and future climate projections, we modeled the change in suitable habitat for C. orientalis by ten algorithms, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. In this study, 46 records of C. orientalis from East China and 8 bioclimatic variables were used. Among the ten modeling algorithms, four (GAM, GBM, Maxent, and RF) were selected according to their predictive abilities. The current habitat suitability showed that C. orientalis had a relatively wide but fragmented distribution, and it encompassed 41,862 km(2). The models suggested that precipitation of warmest quarter (bio18) and mean temperature of wettest quarter (bio6) had the highest contribution to the model. This study revealed that C. orientalis is sensitive to climate change, which will lead to a large range shift. The projected spatial and temporal pattern of range shifts for C. orientalis should provide a useful reference for implementing long‐term conservation and management strategies for amphibians in East China. John Wiley and Sons Inc. 2021-06-27 /pmc/articles/PMC8328465/ /pubmed/34367565 http://dx.doi.org/10.1002/ece3.7822 Text en © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://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
Guo, Kun
Yuan, Sijia
Wang, Hao
Zhong, Jun
Wu, Yanqing
Chen, Wan
Hu, Chaochao
Chang, Qing
Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title_full Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title_fullStr Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title_full_unstemmed Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title_short Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change
title_sort species distribution models for predicting the habitat suitability of chinese fire‐bellied newt cynops orientalis under climate change
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328465/
https://www.ncbi.nlm.nih.gov/pubmed/34367565
http://dx.doi.org/10.1002/ece3.7822
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