Early warning of drought-induced vegetation stress using multiple satellite-based ecological indicators
文献类型：期刊论文
| 作者 | Wang, Ying1,4; Chen, Yanan1; Wen, Jianguang2; Wu, Chaoyang3; Zhou, Wei1; Han, Lei1; Tang, Xuguang4 |
| 刊名 | ECOLOGICAL INDICATORS
 |
| 出版日期 | 2024-12-01 |
| 卷号 | 169页码:14 |
| 关键词 | Drought event Ecological indicator Vegetation stress Early warning Southwest China |
| ISSN号 | 1470-160X |
| DOI | 10.1016/j.ecolind.2024.112857 |
| 产权排序 | 4 |
| 英文摘要 | Droughts have posed, and continue to pose, severe risks to terrestrial ecosystems. Particularly against the backdrop of global climate change, the intensity and frequency of extreme droughts are expected to further aggravate. However, a significant gap persists in early drought warning for vegetation monitoring. Therefore, this study examined the spatial and temporal dynamics of two summer drought events happened in Southwest China in 2011 and 2022, and analyzed the early responses of four ecological indicators including global Orbiting Carbon Observatory-2 (OCO-2) SIF dataset (GOSIF), the leaf-scale fluorescence yield (Phi(f)), the near-infrared reflectance of vegetation (NIRv) and the normalized difference vegetation index (NDVI) to drought extremes. All these indicators successfully captured the drought-induced vegetation stress, but as a proxy for vegetation photosynthesis, GOSIF was the most sensitive. Specifically, during the 2022 drought, GOSIF fell below the baseline year as early as day of year (DOY) 193, whereas NIRv and NDVI began at DOY 201, and Phi(f) lagged severely. Similar behaviour was also found in the drought period of 2011. Overall, compared to the baseline year, GOSIF, Phi(f), NIRv and NDVI decreased by 96.93 %, 54.11 %, 43.92 % and 17.03 % in 2011, and reduced by 70.00 %, 42.01 %, 48.74 % and 19.53 % in 2022, respectively. During the past two decades, GOSIF exhibited the strongest correlation with drought intensity (r = 0.880, p < 0.05), followed by NIRv (r = 0.875, p < 0.05) and NDVI (r = 0.871, p < 0.05), and Phi(f) was the weakest (r = 0.432, p > 0.05). Spatially, the proportion of areas where the correlations exceeded 0.6 by GOSIF and NIRv were 42.39 % and 39.32 %, respectively. In summary, this study demonstrated that global re-constructed GOSIF possesses considerable potential as an early warning indicator for vegetation drought. |
| WOS关键词 | CHLOROPHYLL FLUORESCENCE ; PRIMARY PRODUCTIVITY ; IMPACT ; CHINA ; KARST ; NDVI ; ECOSYSTEM ; CANOPY ; GROWTH ; PLANT |
| 资助项目 | Special Project on National Science and Technology Basic Resources Investigation of China[2021FY100701] ; Opening Funds from Chongqing Jinfo Mountain Karst Ecosystem National Research and Observation Station[JFS2023B01] |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001361752900001 |
| 出版者 | ELSEVIER |
| 资助机构 | Special Project on National Science and Technology Basic Resources Investigation of China ; Opening Funds from Chongqing Jinfo Mountain Karst Ecosystem National Research and Observation Station |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/210536]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Chen, Yanan; Tang, Xuguang |
| 作者单位 | 1.Southwest Univ, Sch Geog Sci, Chongqing 400715, Peoples R China 2.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Hangzhou Normal Univ, Inst Remote Sensing & Geosci, Hangzhou 311121, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Ying,Chen, Yanan,Wen, Jianguang,et al. Early warning of drought-induced vegetation stress using multiple satellite-based ecological indicators[J]. ECOLOGICAL INDICATORS,2024,169:14. |
| APA | Wang, Ying.,Chen, Yanan.,Wen, Jianguang.,Wu, Chaoyang.,Zhou, Wei.,...&Tang, Xuguang.(2024).Early warning of drought-induced vegetation stress using multiple satellite-based ecological indicators.ECOLOGICAL INDICATORS,169,14. |
| MLA | Wang, Ying,et al."Early warning of drought-induced vegetation stress using multiple satellite-based ecological indicators".ECOLOGICAL INDICATORS 169(2024):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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