Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China
In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the chara...
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Published in | Frontiers in plant science Vol. 14; p. 1143863 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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16.03.2023
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Abstract | In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future. |
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AbstractList | In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future. |
Author | Li, Congren Zheng, Jianghua Guan, Jingyun Ju, Xifeng Liu, Liang Liu, Yujia Li, Jianhao Mao, Xurui Han, Wanqiang |
AuthorAffiliation | 1 College of Geography and Remote Sensing Science, Xinjiang University , Urumqi , China 3 College of Tourism, Xinjiang University of Finance & Economics , Urumqi , China 2 Key Laboratory of Oasis Ecology, Xinjiang University , Urumqi , China |
AuthorAffiliation_xml | – name: 1 College of Geography and Remote Sensing Science, Xinjiang University , Urumqi , China – name: 3 College of Tourism, Xinjiang University of Finance & Economics , Urumqi , China – name: 2 Key Laboratory of Oasis Ecology, Xinjiang University , Urumqi , China |
Author_xml | – sequence: 1 givenname: Wanqiang surname: Han fullname: Han, Wanqiang organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 2 givenname: Jingyun surname: Guan fullname: Guan, Jingyun organization: College of Tourism, Xinjiang University of Finance & Economics, Urumqi, China – sequence: 3 givenname: Jianghua surname: Zheng fullname: Zheng, Jianghua organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 4 givenname: Yujia surname: Liu fullname: Liu, Yujia organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 5 givenname: Xifeng surname: Ju fullname: Ju, Xifeng organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 6 givenname: Liang surname: Liu fullname: Liu, Liang organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 7 givenname: Jianhao surname: Li fullname: Li, Jianhao organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 8 givenname: Xurui surname: Mao fullname: Mao, Xurui organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China – sequence: 9 givenname: Congren surname: Li fullname: Li, Congren organization: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China |
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Copyright | Copyright © 2023 Han, Guan, Zheng, Liu, Ju, Liu, Li, Mao and Li. Copyright © 2023 Han, Guan, Zheng, Liu, Ju, Liu, Li, Mao and Li 2023 Han, Guan, Zheng, Liu, Ju, Liu, Li, Mao and Li |
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Keywords | influencing factors grassland types climate regions vulnerability probability drought stress |
Language | English |
License | Copyright © 2023 Han, Guan, Zheng, Liu, Ju, Liu, Li, Mao and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Ankur Srivastava, University of Technology Sydney, Australia; Khurram Shahzad, CAS, China Edited by: Helena Freitas, University of Coimbra, Portugal This article was submitted to Plant Abiotic Stress, a section of the journal Frontiers in Plant Science |
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Title | Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China |
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