Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect
The occurrence of extreme climate phenomena has markedly increased due to the rising trend in global temperatures, leading to significant changes in plant distribution and behavior. This trend is particularly evident in Southwest China, a region highly sensitive to climate shifts and frequently expo...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
|
| Series: | Global Ecology and Conservation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2351989425000988 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850236335722332160 |
|---|---|
| author | Gang Qi Nan Cong Tangzhen Qiu Lei Rong Ping Ren Jiangtao Xiao |
| author_facet | Gang Qi Nan Cong Tangzhen Qiu Lei Rong Ping Ren Jiangtao Xiao |
| author_sort | Gang Qi |
| collection | DOAJ |
| description | The occurrence of extreme climate phenomena has markedly increased due to the rising trend in global temperatures, leading to significant changes in plant distribution and behavior. This trend is particularly evident in Southwest China, a region highly sensitive to climate shifts and frequently exposed to extreme climate events. However, the impact of the time-lag effect on vegetation is often overlooked. In this study, daily temperature (maximum and minimum) and precipitation data were used to calculate nine extreme climate indices. These indices were then employed to evaluate their impact on vegetation dynamics in the region. Subsequently, MODIS NDVI data were used to explore the correlations and time-lag effects between these extreme climate indices and vegetation changes. The analysis revealed significant annual and monthly growth rates in the regional average NDVI from 2000 to 2020, with R² determination coefficients of 0.06 and 0.94, respectively. Most extreme climate indices exhibited a strong positive correlation with NDVI on a monthly scale. A significant correlation was observed between extreme precipitation index and vegetation index in croplands and grasslands. There was a significant 0–2-month lag in the correlation between NDVI and extreme precipitation indices, whereas the correlation between NDVI and extreme temperature indices was more pronounced, with a lag of approximately 4–6 months. Ultimately, our study identified a stronger correlation between precipitation indices and NDVI, highlighting the necessity for increased attention to intense precipitation in the southwest to protect vegetation growth in the region. These findings provide a robust scientific basis for the proactive management of vegetation in Southwest China in response to future extreme climate events. |
| format | Article |
| id | doaj-art-72e84e849fbb445da0554a5a75f61107 |
| institution | OA Journals |
| issn | 2351-9894 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Global Ecology and Conservation |
| spelling | doaj-art-72e84e849fbb445da0554a5a75f611072025-08-20T02:01:58ZengElsevierGlobal Ecology and Conservation2351-98942025-04-0158e0349710.1016/j.gecco.2025.e03497Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effectGang Qi0Nan Cong1Tangzhen Qiu2Lei Rong3Ping Ren4Jiangtao Xiao5Key Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China; School of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610066, ChinaCAS Key Laboratory of Ecosystem Network Observation and Modeling, Lhasa Plateau Ecosystem Research Station, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Corresponding author.Key Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China; School of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610066, ChinaKey Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China; School of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610066, ChinaKey Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China; School of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610066, ChinaKey Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China; School of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610066, China; Corresponding author at: Key Lab of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China.The occurrence of extreme climate phenomena has markedly increased due to the rising trend in global temperatures, leading to significant changes in plant distribution and behavior. This trend is particularly evident in Southwest China, a region highly sensitive to climate shifts and frequently exposed to extreme climate events. However, the impact of the time-lag effect on vegetation is often overlooked. In this study, daily temperature (maximum and minimum) and precipitation data were used to calculate nine extreme climate indices. These indices were then employed to evaluate their impact on vegetation dynamics in the region. Subsequently, MODIS NDVI data were used to explore the correlations and time-lag effects between these extreme climate indices and vegetation changes. The analysis revealed significant annual and monthly growth rates in the regional average NDVI from 2000 to 2020, with R² determination coefficients of 0.06 and 0.94, respectively. Most extreme climate indices exhibited a strong positive correlation with NDVI on a monthly scale. A significant correlation was observed between extreme precipitation index and vegetation index in croplands and grasslands. There was a significant 0–2-month lag in the correlation between NDVI and extreme precipitation indices, whereas the correlation between NDVI and extreme temperature indices was more pronounced, with a lag of approximately 4–6 months. Ultimately, our study identified a stronger correlation between precipitation indices and NDVI, highlighting the necessity for increased attention to intense precipitation in the southwest to protect vegetation growth in the region. These findings provide a robust scientific basis for the proactive management of vegetation in Southwest China in response to future extreme climate events.http://www.sciencedirect.com/science/article/pii/S2351989425000988Climate extremesNDVITime lagVegetation changeSouthwest China |
| spellingShingle | Gang Qi Nan Cong Tangzhen Qiu Lei Rong Ping Ren Jiangtao Xiao Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect Global Ecology and Conservation Climate extremes NDVI Time lag Vegetation change Southwest China |
| title | Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect |
| title_full | Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect |
| title_fullStr | Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect |
| title_full_unstemmed | Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect |
| title_short | Evaluation of impact of climate extremes on vegetation change in Southwest China considering time-lag effect |
| title_sort | evaluation of impact of climate extremes on vegetation change in southwest china considering time lag effect |
| topic | Climate extremes NDVI Time lag Vegetation change Southwest China |
| url | http://www.sciencedirect.com/science/article/pii/S2351989425000988 |
| work_keys_str_mv | AT gangqi evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect AT nancong evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect AT tangzhenqiu evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect AT leirong evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect AT pingren evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect AT jiangtaoxiao evaluationofimpactofclimateextremesonvegetationchangeinsouthwestchinaconsideringtimelageffect |