Work

Threshold Extraction and Early Warning of Key Ecological Factors for Grassland Degradation Risk

Year: 2025

Type: article

Abstract: Grassland degradation poses a serious threat to ecosystem stability and the sustainable development of human societies. In this study, we propose a framework for grassland degradation risk assessments and early warning based on key ecological factors (KEFs) in Xilingol. The NDVI, NPP, and grass yield were selected as KEFs to represent vegetation coverage, ecosystem productivity, and actual biomass, respectively. By constructing a grassland degradation index (GDI) and integrating K-means clustering, the average curvature, and a gravity center shift analysis, we quantified the degradation risk levels and identified the threshold values for different grassland types. The results showed the following: (1) the grass yield was the most sensitive indicator of grassland degradation in Xilingol, with high-risk thresholds decreasing from 115.67 g·m−2 in the temperate meadow steppes (TMSs) to 73.27 g·m−2 in the temperate typical steppes (TTSs), and further to 32.30 g·m−2 in the temperate desert steppes (TDSs); (2) the TDSs exhibited the highest curvature value (2.81 × 10−4) in the initial stage, indicating a higher likelihood of rapid early-stage degradation, whereas the TMSs and TTSs reached peak curvature in the latest stages; and (3) the TTSs had the largest proportion of high-risk areas (33.02%), with a northeast–southwest distribution and a probable westward expansion trend. This study provides a practical framework for grassland degradation risk assessments and early warning, offering valuable guidance for ecosystem management and sustainable land use.

Source: Remote Sensing

DOI: 10.3390/rs17173098