| Autor: |
Xihong, Lian, Limin, Jiao, Yuanchao, Hu, Zejin, Liu |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Science of The Total Environment. 858:159995 |
| ISSN: |
0048-9697 |
| DOI: |
10.1016/j.scitotenv.2022.159995 |
| Popis: |
Ecological regions of medium fragility account for 55 % of China's land. Large-scale afforestation and land reclamation have been carried out in these areas over the past few decades. However, how future climate change poses risks and challenges to them remains unclear. By establishing a multi-algorithm framework combining machine learning algorithms with multi-source dataset, our work predicts Normalized Difference Vegetation Index (NDVI, a proxy for vegetation greenness) and its variations in the 21st century under different climate scenarios. We find that vegetation greening (i.e., NDVI increase) in northern and southwestern China is unstable over four 20-year periods from 2020 to 2100. However, a strikingly prominent greening is expected to occur on the Qinghai-Tibet Plateau until the end of this century. Future warming can not only exacerbate the difficulties of vegetation conservation and restoration in vulnerable ecological regions, also threaten these new croplands, stymieing ambitions to increase crop production in China. Our results underscore the crucible that a warming climate presents to current restoration projects. We highlight the urgency of adapting to climate change to achieve ambitious goals of carbon sequestration and food security in China. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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Full Text from ScienceDirect