Ministry of Education Key Laboratory for Western Arid Region Grassland Resources and Ecology, College of Grassland and Environment Sciences, Xinjiang Agricultural University, Urumqi, 830052, China.
Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai, 200438, China.
Environ Sci Pollut Res Int. 2021 Aug;28(31):42516-42532. doi: 10.1007/s11356-021-13721-z. Epub 2021 Apr 4.
Global environment changes rapidly alter regional hydrothermal conditions, which undoubtedly affects the spatiotemporal dynamics of vegetation, especially in arid and semi-arid areas. However, identifying and quantifying the dynamic evolution and driving factors of vegetation greenness under the changing environment are still a challenge. In this study, gradual trend analysis was applied to calculate the overall spatiotemporal trend of the normalized difference vegetation index (NDVI) time series of Xinjiang province in China, the abrupt change analysis was used to detect the timing of breakpoint and trend shift, and two machine learning methods (boosted regression tree and random forest) were used to quantify the key factors of vegetation change and their relative contribution rate. The results have shown that vegetation has experienced overall recovery over the past 20 years in Xinjiang, and greenness increased at a rate of 17.83 10 year. Cropland, grassland, and sparse vegetation were the main biome types where vegetation restoration is happening. Nearly 10% of the pixels (about 166000 km) were detected to have breakpoints from 2004 to 2016 of the monthly NDVI, and most of the breakpoints were concentrated in the ecotone of various biomes. CO concentration was the most prevalent environmental factor to increase vegetation greenness, because continuous emission of CO greatly enhanced the fertilization effect, further promoted vegetation growth. Besides, cropland expansion and desertification control were the vital anthropogenic factors to vegetation turning "green" in Xinjiang, and most areas under anthropogenic were mainly in oasis areas. These findings provide new insights and measures for the regional response strategies and terrestrial ecosystem protection.
全球环境变化迅速改变了区域水热条件，这无疑会影响植被的时空动态，尤其是在干旱和半干旱地区。然而，识别和量化植被绿色度在变化环境下的动态演变和驱动因素仍然是一个挑战。本研究应用渐趋势分析来计算中国新疆地区归一化差异植被指数（NDVI）时间序列的整体时空趋势，利用突变分析检测突变点和趋势转折点的时间，以及应用两种机器学习方法（提升回归树和随机森林）来量化植被变化的关键因素及其相对贡献率。结果表明，过去 20 年新疆的植被经历了整体恢复，绿色度以每年 17.83 的速度增加。耕地、草地和稀疏植被是植被恢复的主要生物群落类型。约 10%的像元（约 166000 平方公里）在 2004 年至 2016 年的月度 NDVI 中检测到有突变点，且大部分突变点集中在各种生物群落的交错带。CO 浓度是增加植被绿色度的最普遍的环境因素，因为 CO 的持续排放极大地增强了施肥效应，进一步促进了植被的生长。此外，耕地扩张和荒漠化控制是新疆植被变“绿”的重要人为因素，而大多数人为因素主要集中在绿洲地区。这些发现为区域响应策略和陆地生态系统保护提供了新的见解和措施。
