Key Laboratory of Ecology and Environment in Minority Areas (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China.
College of Life & Environmental Sciences, Minzu University of China, Beijing, 100081, China.
Environ Sci Pollut Res Int. 2022 Feb;29(10):13782-13796. doi: 10.1007/s11356-021-16774-2. Epub 2021 Oct 1.
Changes in land management and climate alter vegetation dynamics; however, the factors driving vegetation changes remain elusive at multiple spatiotemporal levels. Here, we assess the drivers of changes in greenness from 2000 to 2015 in Northwest China (NW China). We used multiple stepwise linear regression (MSLR), redundancy analysis (RDA), and 12 other models to quantify the impacts of precipitation and temperature metrics, gross domestic product (GDP), population, and grazing intensity on the normalized difference vegetation index (NDVI) at three administrative levels (county, town, and village), four temporal levels (yearly, May, July, and September), two vegetation types (woodland and grassland), and at annual precipitation gradients of <200, 200-400, and >400 mm. The results suggest that NW China underwent vegetation greening from 2000 to 2015. Precipitation and temperature were the most influential factors contributing to the NDVI change. Population was the main determinant of NDVI under the precipitation gradient of <200 mm, and the effect of GDP on NDVI was moderate. On the temporal scale, annual precipitation, precipitation before the previous year, and precipitation in the current year determined the NDVI in May, July, and September, respectively, for both woodland and grassland. At multiple scales, climate change was the primary driver of vegetation change in NW China, rather than human disturbance. These findings expand our understanding on drivers of NDVI at multiple levels over a long period. Measures to manage decreasing vegetation coverage may be more effective and could be implemented sooner based on predicted climate change in drylands worldwide.
土地管理和气候变化的变化改变了植被动态；然而，在多个时空水平上，驱动植被变化的因素仍然难以捉摸。在这里，我们评估了 2000 年至 2015 年中国西北地区（NW 中国）绿色度变化的驱动因素。我们使用多元逐步线性回归（MSLR）、冗余分析（RDA）和其他 12 个模型来量化降水和温度指标、国内生产总值（GDP）、人口和放牧强度对归一化差异植被指数（NDVI）的影响在三个行政级别（县、镇和村）、四个时间级别（年、5 月、7 月和 9 月）、两种植被类型（林地和草地）以及年降水量梯度<200、200-400 和>400mm 下的影响。结果表明，2000 年至 2015 年，中国西北地区经历了植被绿化。降水和温度是影响 NDVI 变化的最主要因素。人口是<200mm 降水梯度下 NDVI 的主要决定因素，而 GDP 对 NDVI 的影响适中。在时间尺度上，年降水量、前一年降水量和当年降水量分别决定了 5 月、7 月和 9 月林地和草地的 NDVI。在多个尺度上，气候变化是中国西北地区植被变化的主要驱动因素，而不是人为干扰。这些发现扩展了我们对长时间多尺度 NDVI 驱动因素的理解。根据全球旱地预测的气候变化，采取管理植被覆盖度下降的措施可能会更加有效，并可以更早实施。
