Yu Kaining, Yang Caijia, Wu Tao, Zhai Yifeng, Tian Shixiong, Feng Yuqing
Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang, 050031, China.
School of Water Resources and Environment, Hebei GEO University, Shijiazhuang, 050031, China.
Sci Rep. 2025 Jul 2;15(1):22569. doi: 10.1038/s41598-025-06921-x.
As a significant ecological barrier, the source region of the Yellow River serves as a crucial water source in China, and its vegetation dynamics play a pivotal role in water conservation. Monitoring vegetation dynamics is essential for ecological protection and the achievement of sustainable development goals, as it facilitates systematic assessment of vegetation restoration, supports the advancement of ecological civilization, and promotes coordinated economic and environmental development. Based on the newly released AVHRR GIMMS NDVI3g data from 1982 to 2020 provided by the NASA Goddard Space Flight Center, this study aims to identify the driving mechanisms influencing vegetation dynamics in the source region of the Yellow River over the past 40 years (1982-2020) by utilizing ordered cluster analysis, Pearson correlation analysis, and the Geodetector method. The influence of each driving factor on NDVI was systematically examined, and the spatial and temporal characteristics of vegetation as well as the effects of key drivers were clarified to inform ecological protection and sustainable development strategies. The results indicate that: (1) the overall NDVI in the source region of the Yellow River exhibited a significant upward trend from 1982 to 2020, with a noticeable shift occurring in 2009. Prior to 2009, NDVI demonstrated a slight declining trend, whereas a significant increase was observed afterward; (2) NDVI distribution displayed a spatial gradient, increasing from northwest to southeast, with higher values in the southeast and lower values in the northwest; (3) the interaction between any two driving factors had a more substantial influence on NDVI than individual factors, demonstrating a two-factor enhancement effect. Notably, the interaction between precipitation and temperature with other variables exhibited the strongest explanatory power, with q-values exceeding 0.5. Overall, natural factors such as temperature and precipitation played a crucial role in NDVI variation, and the abrupt change in 2009 may be attributed to regional warming and the implementation of ecological protection measures.
作为重要的生态屏障，黄河源区是我国重要的水源地，其植被动态对水源涵养起着关键作用。监测植被动态对于生态保护和实现可持续发展目标至关重要，它有助于系统评估植被恢复情况，支持生态文明建设，促进经济与环境协调发展。基于美国国家航空航天局戈达德太空飞行中心提供的1982年至2020年最新发布的AVHRR GIMMS NDVI3g数据，本研究旨在通过有序聚类分析、皮尔逊相关分析和地理探测器方法，识别过去40年（1982 - 2020年）黄河源区植被动态的驱动机制。系统研究了各驱动因素对归一化植被指数（NDVI）的影响，阐明了植被的时空特征以及关键驱动因素的作用，为生态保护和可持续发展战略提供依据。结果表明：（1）1982年至2020年黄河源区NDVI总体呈显著上升趋势，2009年出现明显转折。2009年之前，NDVI呈轻微下降趋势，之后则显著增加；（2）NDVI分布呈现空间梯度，由西北向东南递增，东南部值较高，西北部值较低；（3）任意两个驱动因素之间的相互作用对NDVI的影响比单个因素更大，表现出双因素增强效应。值得注意的是，降水和温度与其他变量之间的相互作用具有最强的解释力，q值超过0.5。总体而言，温度和降水等自然因素在NDVI变化中起关键作用，2009年的突变可能归因于区域变暖以及生态保护措施的实施。
