Regional Patterns of Vegetation Dynamics and Their Sensitivity to Climate Variability in the Yangtze River Basin

Abstract

To better understand the mechanisms of the hydro-ecological cycle in the changing environments of the Yangtze River Basin (YZRB), it is valuable to investigate vegetation dynamics and their response to climate change. This study explored the spatial patterns of vegetation dynamics and the essential triggers of regional differences by analyzing vegetation variations in the 1982–2015 period at different time scales and the interannual variability of vegetation sensitivity to climate variability. The results showed that the normalized difference vegetation index (NDVI) increased significantly in the last three decades, but vegetation displayed great spatiotemporal variations at different time scales. The vegetation in the central part of the YZRB dominated by forests and shrublands was more sensitive to climate variability than vegetation in the source region of the YZRB, which was dominated by alpine meadows and tundra (AMT). The contribution of climate variables to the vegetation sensitivity index (VSI) had large spatial differences, but solar radiation and temperature were the dominant factors. Furthermore, 57.9% of the YZRB had increasing VSIs, especially in the south-central part. Consistent with the distributions of elevation and vegetation types, vegetation dynamics in the YZRB were divided into five spatial patterns, with the largest increasing NDVI trend in Region III and the largest VSI in Region IV. Moreover, the VSI exhibited fairly consistent dynamics in all subregions, but the contributions of climate variables to the VSI varied greatly among the different regions.

Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data

“…Sen slope estimation and the Mann-Kendall (M-K) nonparametric test were applied to evaluate the trends and spatial heterogeneity of the SPEI over the time series [49]. The M-K test is a nonparametric test based on the Sen slope estimator, which has been widely employed for detecting trends in meteorological and hydrological time series [50].…”

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

“…However, when temperatures exceed a certain threshold, vegetation growth is inhibited, leading to reduced productivity (Xiao et al, 2023). Solar radiation also makes a certain contribution to vegetation variability (Wang et al, 2022). Moderate wind speeds accelerate leaf transpiration rates, enhance plant net photosynthetic rates, and consequently promote vegetation growth (Zhang, Xu, et al, 2022).…”

Increasing sensitivity of the terrestrial ecosystem to climate change in China

“…Terrestrial ecosystems in China have a strong potential for carbon sequestration and are critical for the world's carbon pool (Lu et al, 2022). However, the dynamics of ecosystems functioning as current carbon sinks under global warming in the future are uncertain, especially in relation to vegetation responses (Wang et al, 2022;Jiang et al, 2022). The objectives of our study are to provide evidence of changes and drivers of the overall ecosystem sensitivity to land-atmosphere coupling, hereafter referred to as ecosystem sensitivity, ES.…”