The ecosystem service value (ESV) is an important basis for measuring an ecological environment’s quality and the efficient management of ecosystems. It is particularly necessary to explore a proven methodology for assessing and predicting ESV dynamics coupled with policy-oriented scenarios that can provide a theoretical groundwork for macro decision, particularly in the context of implementing ecological protection and restoration projects. This study selected the land cover (LC) of Sichuan Province at five periods and the spatiotemporal dynamic equivalent factor method to assess the ESVs from 2000 to 2020. Additionally, the study coupled the Markov chain and GeoSOS-FLUS model, and predicted the future pattern of ESVs under four future development scenarios. The results show that (a) the areas of forests, shrubs, waters, wastelands, wetlands, and impervious areas showed a continuous increase from 2000 to 2020, with the most frequent interchanges occurring among croplands, forests, and grasslands. (b) The implementation of ecological protection and restoration projects led to a 13,083.32 × 10⁸ yuan increase in ESV, and barycenter of the ESVs is located in the northeastern part of Ya’an and exhibits a tendency to move towards the northeast. (c) The ESV aggregation pattern of each city has remained unchanged, with Ganzi being the only city with a high aggregation. Overall, there are more conflict cities than coordination cities between economic development and the ecological environment. (d) The total ESV in 2025 will continue to increase under all development scenarios, reaching a maximum of 50,903.37 × 10⁸ yuan under the EP scenario. This study can provide insights for ecological planning decisions and sustainable regional socio-economic development.

Regional ecosystem health is the basis for regular regional exploration, ecological protection, and sustainable development. This study explored ecosystem health at the southern end of the Hu Line (Sichuan and Yunnan provinces) using the pressure–state–response model and examined the spatial evolution of ecosystem health. The proportion of unhealthy and morbid cities decreased from 45.9% in 2000 to 35.1% in 2016. The imbalance of ecosystem health among cities has gradually increased since 2006, but more high-quality cities have emerged (Z of Moran’s Index < 1.96, p > 0.05). Overall, the regional ecosystem on the southeast side of the Hu Line was healthier than that on the northwest side. Differences in ecosystem health on both sides of the Hu Line showed decreasing trends over time except for the pressure score. The spatial pattern of ecosystem health moved along the Hu Line because the pressure and state scores of ecosystems were mainly determined by the natural environmental conditions. Based on the county-level assessment, the grade of imbalance within cities was divided, and those that were lagging were identified. To correct regional imbalances, a comprehensive and proactive policy framework for a smart development model was put forward in Sichuan and Yunnan.

Stress events induced by global warming pose severe threats to vegetation health. Assessing the impact of these stress events on the health and growth of vegetation ecosystems in China is crucial. This study constructed three vegetation health assessment systems and selected the one that most effectively reflects vegetation health. By identifying the characteristics of stress events, and employing trend analysis, sensitivity analysis, anomaly change analysis, and modified residual analysis, this study explores the dynamic changes in vegetation health and their responses to stress events across China from 2001 to 2020. The results indicate that the Pressure–State–Response (PSR) model has the best evaluation performance, achieving the highest fit to Solar-Induced Chlorophyll Fluorescence (SIF) with an goodness of fit (R²) of up to 0.74. Overall, vegetation health exhibits more negative anomalies than positive ones and shows the strongest positive sensitivity to Cumulative Precipitation Anomaly (CPA) and the strongest negative sensitivity to Cumulative Heat (CH). Among different vegetation types, alpine vegetation has the highest stability in health, while meadows and grasslands are the most sensitive to stress events. Additionally, stress events have a greater contribution rate to vegetation health than other events. Our findings will provide important data for climate change adaptation policies and extreme environmental early warning while also contributing to the formulation of policies aimed at improving vegetation health. These results are of significant importance for enhancing carbon sequestration capacity, refining carbon market policies, and promoting the sustainable development of ecosystems.

Monitoring cropland dynamics in arid regions is critical for balancing food security with water scarcity constraints. However, distinguishing fragmented agricultural oases from spectrally similar desert vegetation remains a persistent challenge due to spectral confusion and landscape heterogeneity. To address these challenges, this study developed the STGP-OCE feature cube on the Google Earth Engine platform (GEE) by integrating the Oasis Cooling Effect (OCE) into the commonly used STGP (Spectral, Textural, Geomorphic, and Phenological) feature space, coupled with the XGBoost ensemble model. Through ablation experiments and feature importance analysis, we quantified the feature construction mechanism for arid regions. Oasis Cooling Intensity emerged as the most influential variable (Gain score: 0.315), demonstrating that the thermal signature of continuous anthropogenic irrigation serves as a robust thermodynamic proxy to resolve the spectral ambiguity between crops and drought-tolerant desert vegetation. By hierarchically coupling this thermal indicator with textural features to suppress fragmentation noise, topographic constraints to filter non-arable terrain, and phenological trajectories, the STGP-OCE feature cube achieved an Overall Accuracy of 95.12% and a Precision of 94.95%, significantly outperforming models built on lower-dimensional cubes as well as existing global land cover products. We generated a 10 m annual cropland dataset for Xinjiang, China, revealing a substantial 32.9% expansion (19,360 km²) from 2015 to 2024, mainly occurring in vulnerable oasis–desert transition zones and coinciding with reported reclamation activities. These highlight the continuous agricultural encroachment into desert margins, while the proposed STGP-OCE cube provides a reliable methodology for high-precision cropland monitoring in arid regions.

Understanding the impact of drought on the water use efficiency (WUE) of grasslands is essential for comprehending the mechanisms of the carbon–water cycle in the context of global warming. Nevertheless, the cumulative and lagged effects of drought on WUE across different grassland types in China remain unclear. This study investigates the cumulative and lagged effects of drought on WUE across different grassland types in China from 1982 to 2018. We employed the Sen-MK trend test and correlation analysis to identify the primary factors influencing the temporal effects of drought on WUE. The results indicated that WUE in Chinese grasslands, across various grassland types, exhibited an upward trend over time, with the most rapid increase observed in meadow. Drought had both cumulative and lagged effects on WUE, with cumulative effects lasting an average of 5.2 months and lagged effects lasting 6.1 months. Specifically, the cumulative effects of drought on WUE lasted for 5.6 months for alpine and subalpine meadow, slope, and desert grassland, whereas the lagged effects lasted 9 months for alpine and subalpine plain grassland. Furthermore, the influence of drought on WUE in grasslands varied across different grassland types and intensified with increasing altitude. The trends observed in the cumulative and lagged impacts of drought on WUE across various aridity index (AI) zones were consistent with those for grasslands as a whole. Our findings underscore that the response of WUE to drought in grasslands and their distinct types is primarily characterized by lagged effects. This research provides an important reference value for enhancing the stability of grassland ecosystems.