Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives
The frequent occurrence of drought events in recent years has caused significant changes in plant biodiversity. Understanding vegetation dynamics and their responses to climate change is of great significance to reveal the behaviour mechanism of terrestrial ecosystems. In this study, NDVI and SIF we...
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2022.953805/full |
| _version_ | 1811309930143023104 |
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| author | Zhaoqiang Zhou Zhaoqiang Zhou Yibo Ding Qiang Fu Can Wang Can Wang Yao Wang Yao Wang Hejiang Cai Hejiang Cai Hejiang Cai Suning Liu Haiyun Shi Haiyun Shi |
| author_facet | Zhaoqiang Zhou Zhaoqiang Zhou Yibo Ding Qiang Fu Can Wang Can Wang Yao Wang Yao Wang Hejiang Cai Hejiang Cai Hejiang Cai Suning Liu Haiyun Shi Haiyun Shi |
| author_sort | Zhaoqiang Zhou |
| collection | DOAJ |
| description | The frequent occurrence of drought events in recent years has caused significant changes in plant biodiversity. Understanding vegetation dynamics and their responses to climate change is of great significance to reveal the behaviour mechanism of terrestrial ecosystems. In this study, NDVI and SIF were used to evaluate the dynamic changes of vegetation in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought in the PRB was evaluated from both linear and nonlinear perspectives, and the difference of vegetation response to meteorological drought in different land types was revealed. Cross wavelet analysis was used to explore the teleconnection factors (e.g., large-scale climate patterns and solar activity) that may affect the relationship between meteorological drought and vegetation dynamics. The results show that 1) from 2001 to 2019, the vegetation cover and photosynthetic capacity of the PRB both showed increasing trends, with changing rates of 0.055/10a and 0.036/10a, respectively; 2) compared with NDVI, the relationship between SIF and meteorological drought was closer; 3) the vegetation response time (VRT) obtained based on NDVI was mainly 4–5 months, which was slightly longer than that based on SIF (mainly 3–4 months); 4) the VRT of woody vegetation (mainly 3–4 months) was longer than that of herbaceous vegetation (mainly 4–5 months); and 5) vegetation had significant positive correlations with the El Niño Southern Oscillation (ENSO) and sunspots but a significant negative correlation with the Pacific Decadal Oscillation (PDO). Compared with sunspots, the ENSO and the PDO were more closely related to the response relationship between meteorological drought and vegetation. The outcomes of this study can help reveal the relationship between vegetation dynamics and climate change under the background of global warming and provide a new perspective for studying the relationship between drought and vegetation. |
| first_indexed | 2024-04-13T09:51:01Z |
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| id | doaj.art-68a0d9b98ef94351b8cfc5180457995a |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-13T09:51:01Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Earth Science |
| spelling | doaj.art-68a0d9b98ef94351b8cfc5180457995a2022-12-22T02:51:36ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632022-08-011010.3389/feart.2022.953805953805Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectivesZhaoqiang Zhou0Zhaoqiang Zhou1Yibo Ding2Qiang Fu3Can Wang4Can Wang5Yao Wang6Yao Wang7Hejiang Cai8Hejiang Cai9Hejiang Cai10Suning Liu11Haiyun Shi12Haiyun Shi13State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaGuangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaYellow River Engineering Consulting Co., Ltd., Zhengzhou, ChinaSchool of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, ChinaState Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaGuangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaState Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaGuangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaState Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaGuangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaDepartment of Civil and Environmental Engineering, National University of Singapore, Singapore, SingaporeCenter for Climate Physics, Institute for Basic Science, Daejeon, South KoreaState Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaGuangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, ChinaThe frequent occurrence of drought events in recent years has caused significant changes in plant biodiversity. Understanding vegetation dynamics and their responses to climate change is of great significance to reveal the behaviour mechanism of terrestrial ecosystems. In this study, NDVI and SIF were used to evaluate the dynamic changes of vegetation in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought in the PRB was evaluated from both linear and nonlinear perspectives, and the difference of vegetation response to meteorological drought in different land types was revealed. Cross wavelet analysis was used to explore the teleconnection factors (e.g., large-scale climate patterns and solar activity) that may affect the relationship between meteorological drought and vegetation dynamics. The results show that 1) from 2001 to 2019, the vegetation cover and photosynthetic capacity of the PRB both showed increasing trends, with changing rates of 0.055/10a and 0.036/10a, respectively; 2) compared with NDVI, the relationship between SIF and meteorological drought was closer; 3) the vegetation response time (VRT) obtained based on NDVI was mainly 4–5 months, which was slightly longer than that based on SIF (mainly 3–4 months); 4) the VRT of woody vegetation (mainly 3–4 months) was longer than that of herbaceous vegetation (mainly 4–5 months); and 5) vegetation had significant positive correlations with the El Niño Southern Oscillation (ENSO) and sunspots but a significant negative correlation with the Pacific Decadal Oscillation (PDO). Compared with sunspots, the ENSO and the PDO were more closely related to the response relationship between meteorological drought and vegetation. The outcomes of this study can help reveal the relationship between vegetation dynamics and climate change under the background of global warming and provide a new perspective for studying the relationship between drought and vegetation.https://www.frontiersin.org/articles/10.3389/feart.2022.953805/fullmeteorological droughtnormalized difference vegetation indexsolar-induced chlorophyll fluorescencevegetation response timelinearnonlinear |
| spellingShingle | Zhaoqiang Zhou Zhaoqiang Zhou Yibo Ding Qiang Fu Can Wang Can Wang Yao Wang Yao Wang Hejiang Cai Hejiang Cai Hejiang Cai Suning Liu Haiyun Shi Haiyun Shi Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives Frontiers in Earth Science meteorological drought normalized difference vegetation index solar-induced chlorophyll fluorescence vegetation response time linear nonlinear |
| title | Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| title_full | Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| title_fullStr | Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| title_full_unstemmed | Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| title_short | Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| title_sort | comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives |
| topic | meteorological drought normalized difference vegetation index solar-induced chlorophyll fluorescence vegetation response time linear nonlinear |
| url | https://www.frontiersin.org/articles/10.3389/feart.2022.953805/full |
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