Grazing is very common in the grassland ecosystem, and it has a significant impact on the C stocks and cycle. One of the most important drivers of soil C stocks is functional diversity. However, limited studies have attempted to explore the effects of functional diversity on soil C stocks associated with grazing disturbance. This study was carried out in Hulunbeier grassland, Inner Mongolia, and four grazing intensities (no grazing (NG), light grazing (LG), moderate grazing (MG), and heavy grazing (HG)) were identified. The plant functional traits and important soil properties under different grazing intensities were measured. Functional identity and diversity were calculated based on the measured functional traits. The impacts of functional identity and diversity on soil organic carbon stocks (SOC_stocks) were analyzed using a multi-model inference (MMI) approach. Our study showed that the functional diversity effect on soil C stocks varies depending on grazing intensity. We identified that functional richness has a significant impact on SOC_stocks in NG. The community weighted mean of leaf area became the best predictor of SOC_stocks in LG. As grazing intensified, functional divergence best explained SOC_stocks in moderate and heavy grazing sites, and their relationship was positive. The major outcomes of this research could shed light on the mechanics of soil carbon storage.

Stability is a key characteristic for understanding ecosystem processes and evolution. However, research on the stability of complex ecosystems often faces limitations, such as reliance on single parameters and insufficient representation of continuous changes. This study developed a multidimensional stability assessment system for regional ecosystems based on disturbances. Focusing on the lower reaches of the Yellow River Basin (LR-YRB), we integrated the remote sensing ecological index (RSEI) with texture structural parameters, and applied the Landsat-based detection of trends in disturbance and recovery (LandTrendr) algorithm to analyze the continuous changes in disturbances and recovery from 1986 to 2021, facilitating the quantification and evaluation of resistance, resilience, and temporal stability. The results showed that 72.27% of the pixels experienced 1–9 disturbances, indicating the region’s sensitivity to external factors. The maximum disturbances primarily lasted 2–3 years, with resistance and resilience displaying inverse spatial patterns. Over the 35-year period, 61.01% of the pixels exhibited moderate temporal stability. Approximately 59.83% of the pixels recovered or improved upon returning to pre-disturbance conditions after maximum disturbances, suggesting a strong recovery capability. The correlation among stability dimensions was low and influenced by disturbance intensity, underscoring the necessity for a multidimensional assessment of regional ecosystem stability based on satellite remote sensing.