Grassland ecosystems provide a range of services in semi-arid and arid regions. However, they have significantly declined due to overgrazing and desertification. In the current study, we employed Landsat time series data (TM, OLI, OLI-2) spanning from 1990 to 2024, combined with vegetation indices such as NDVI and SAVI, along with NDWI and digital elevation models (DEMs), to analyze land cover dynamics in the Ugii Lake watershed area, Mongolia. By integrating multisource remote sensing data into the advanced XGBoost (extreme gradient boosting) machine learning algorithm, we achieved high classification accuracy, with overall accuracies exceeding 94% and Kappa coefficients greater than 0.92. The results revealed a decline in montane grasslands (−6.2%) and an increase in other grassland types, suggesting ecosystem redistribution influenced by climatic and anthropogenic factors. Cropland exhibited resilience, recovering from a significant decline in the 1990s to moderate growth by 2024. Our findings highlight the stability of barren land and underscore pressures from ecological degradation and human activities. This study provides up-to-date statistical data to support decision-making in the conservation and sustainable management of grassland ecosystems in Mongolia under changing climatic conditions.

Climate change and anthropogenic activity in the Republic of Buryatia aggravate the processes of desertification and land degradation. The territory of Buryatia was zoned according to the aridity index based on ENVIREM climate data with a high spatial resolution. Long-term changes in the vegetation cover in arid and humid zones are quantitatively assessed based on a combined study of the time series of the normalized-difference vegetation index (NDVI) with the Advanced Very High Radiation Radiometer (AVHRR), meteorological series of the NCEP/NCAR Reanalysis data set, and field studies. Maps of the spatial distribution of NDVI linear trends and precipitation for 1982–2015 (with the differentiation of the wet (1982–1999) and dry periods (2000–2015)) have been constructed. During the wet period, positive NDVI trends are observed for almost the entire republic, while the dry period is characterized by a significant increase in negative trends of the vegetation index. A positive correlation between the Selyaninov hydrothermal coefficient and NDVI is observed for intermountain steppe basins, while it is negative for forest landscapes. The dynamics of the NDVI for steppe vegetation is more dependent on precipitation, while the dynamics of the NDVI for forests is more significantly correlated with temperature. Reforestation, postpyrogenic succession, the bushing of fallow lands, and other factors determine the growth in the NDVI. Negative NDVI trends are characteristic of steppe ecosystems with low precipitation and forest ecosystems exposed to felling and fires.

This study investigates the hydrological, ecological, and socio-economic responses of Ugii Lake—a freshwater body in semi-arid Central Mongolia—to climate variability and anthropogenic pressures. Seasonal field surveys conducted during the spring, summer, and fall of 2023–2024 revealed notable spatial and temporal variation in water quality, with pH ranging from 7.54 to 8.87, EC from 316 to 645 µS/cm, and turbidity between 0.36 and 5.76 NTU. Total dissolved solids (TDS) values and ionic compositions indicated increased salinization in some zones, particularly those exposed to high evaporation and shoreline disturbance. Heavy metal analysis identified elevated levels of aluminum, manganese, and zinc at several sampling points; however, concentrations generally remained within national environmental standards. Vegetation surveys showed that disturbed areas—especially those affected by grazing and tourism—exhibited reduced native plant diversity and dominance of invasive species. Socio-economic interviews with local herders and stakeholders indicated that 67.3% of households experienced declining livestock productivity, and 37.1% reported increased allergies or respiratory symptoms linked to deteriorating environmental conditions. Despite some ongoing conservation efforts, respondents expressed dissatisfaction with enforcement and impact. These findings highlight the need for community-driven, integrated lake management strategies that address environmental degradation, climate adaptation, and rural livelihood security.

Climate-induced disasters, such as droughts and floods, have a significant impact on rural areas across Asia, where local livelihoods inherently depend on ecosystem services, necessitating effective and context-specific strategies for building resilience. Ecosystem restoration (ER), a process involving human-assisted recovery of degraded ecosystems, has been widely implemented but insufficiently evaluated, particularly regarding its socioeconomic impacts. In this study, a multidimensional evaluation framework was developed to assess the effectiveness of ER in enhancing rural resilience in Asia. Based on a collaborative data synthesis workshop with researchers from Bangladesh, China, Mongolia and Japan, ecological and livelihood indicators, including climate parameters and temporal assessments, were integrated into the framework. A structured literature review identified 65 case studies across 17 Asian countries that incorporate socioeconomic evaluations of ER. The findings revealed distinct regional characteristics: East Asia emphasises policy-driven land use restoration; Southeast Asia focuses on community-based coastal and forest recovery tied to disaster risk reduction; and South Asia links ER to climate adaptation and traditional knowledge. This study highlights the growing importance of incorporating socioeconomic perspectives into ER and the need for context-sensitive evaluation tools tailored to diverse socioecological systems in Asia.