[Analysis of Vegetation Dynamics Associated with Driving Factors in Major Basins of Yellow River].

Authors

Hao-Cheng Ke, Fei Wang, Mao-Lin Wang, Chen Yang, Meng-Han Tian

Published in

Huan jing ke xue= Huanjing kexue. Volume 47. Issue 9. Pages 6162-6176. Sep 08, 2026.

Abstract

Vegetation dynamics serve as a dual indicator of climate and ecological changes. Quantifying the characteristics and drivers of vegetation dynamics at the regional scale is a key scientific issue for understanding how terrestrial ecosystems respond to climate change and human activities. Based on normalized difference vegetation index （NDVI） data from 2000 to 2022 across eight major basins of the Yellow River （YRB）， this study quantified the spatiotemporal dynamics of vegetation and， by integrating wavelet coherence analysis with Geodetector， provided a mechanistic disentanglement of how individual environmental drivers govern NDVI variability. The results show that： ① Over time， there was a stalky upward tendency in its change across all regions from 2000 to 2022 （P<0.05）， and the spatial change rate was between 0.001 7-0.01 a^-1. It tended to increase from northwest to southeast at the spatial scale， with 71.08% of the total area showing significant improvement， mainly shifting to higher coverage levels. ② Integrating multiple change-point detection algorithms， we identified 2011 and 2017 as the two dominant breakpoints in the NDVI series. Ordinal clustering and the moving T-test proved the most robust for identifying abrupt shifts in both NDVI and meteorological variables in YRB. NDVI exhibited heterogeneous and lagged responses to precipitation and temperature， with precipitation exerting a markedly stronger control than temperature. ③ Climate factors （annual precipitation and sunshine duration） were primary drivers， while land-use types and elevation exerted localized synergistic effects. NDVI correlated negatively with sunshine duration （P<0.05） but positively with precipitation and land-use intensity. These findings provide mechanistic insights for optimizing ecological conservation strategies in YRB.

PMID:
42765235
Bibliographic data and abstract were imported from PubMed on 21 Sep 2026.

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