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A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temp...

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Detalles Bibliográficos
Autores principales: Liu, Zhiyong, Li, Chao, Zhou, Ping, Chen, Xiuzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054395/
https://www.ncbi.nlm.nih.gov/pubmed/27713530
http://dx.doi.org/10.1038/srep35105
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author Liu, Zhiyong
Li, Chao
Zhou, Ping
Chen, Xiuzhi
author_facet Liu, Zhiyong
Li, Chao
Zhou, Ping
Chen, Xiuzhi
author_sort Liu, Zhiyong
collection PubMed
description Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.
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spelling pubmed-50543952016-10-19 A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China Liu, Zhiyong Li, Chao Zhou, Ping Chen, Xiuzhi Sci Rep Article Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. Nature Publishing Group 2016-10-07 /pmc/articles/PMC5054395/ /pubmed/27713530 http://dx.doi.org/10.1038/srep35105 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Liu, Zhiyong
Li, Chao
Zhou, Ping
Chen, Xiuzhi
A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title_full A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title_fullStr A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title_full_unstemmed A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title_short A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China
title_sort probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054395/
https://www.ncbi.nlm.nih.gov/pubmed/27713530
http://dx.doi.org/10.1038/srep35105
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