The study aims to evaluate the impact of climate change on pasture ecosystems in Central Kazakhstan, particularly within the Karaganda and Ulytau regions. The assessment combines remote sensing indicators (NDVI, LST) with long-term climatic datasets (CRU TS v4.09 and national meteorological records) for the period 2000–2024. Non-parametric statistical methods, including the Mann–Kendall trend test, Sen’s slope estimator, and Pettitt’s test, were applied to identify the direction, intensity, and structural shifts in temperature and precipitation trends. The results indicate significant regional warming, especially during summer and spring, alongside spatially inconsistent precipitation changes. The southern and southwestern areas (Zhezkazgan and Satpayev) show intensified aridization, manifested in rising land surface temperatures, decreasing rainfall, and declining vegetation productivity and exacerbated by anthropogenic pressures. Conversely, the eastern and northeastern regions exhibit stable or increasing NDVI values and moderate precipitation growth, suggesting potential for natural recovery. The study concludes that pasture degradation in Central Kazakhstan is driven by combined climatic and human factors, with pronounced spatial heterogeneity. The integrated approach enhances the reliability of climate impact assessments and provides a scientific basis for developing adaptive and region-specific strategies for sustainable pasture management under ongoing climate change.

River deltas provide the most productive pastures in Central Asia. Simultaneously they are highly vulnerable to water inflow changes. The aim of this study was to conduct an economic assessment of the short- and medium-term effect of reduced water inflow on farmers’ performance within the Ili Delta. Primary data were collected through 35 interviews with farmers and additional experts in 2015. Production parameters for three types of individual farms were estimated and entered into a full cost accounting. Contribution margins were calculated for three scenarios: (I) sufficient water inflow (normal situation), (II) decreasing water inflow, and (III) significantly reduced water inflow (worst case). Farmers purchase hay to adapt to pasture production loss due to decreasing water inflow. This more than doubled the variable costs of worst case in comparison to normal situation for small-, medium-, and large-scale type of individual farm. Monte Carlo simulation indicates a risk of 74% (small-scale farm) and 3% (medium-scale farm) that already variable costs will exceed revenues. Despite their high fixed costs, only large-scale individual farms generate positive net farm income from operations in the worst case due to government payments from participation in elite bull program that account for one-third of total revenue.

Kazakhstan’s Ili River delta nourishes a unique wetland ecosystem in arid Central Asia. The delta is dominated by common reed [Phragmites australis (Cav.) Trin. ex Steud.], an ecologically and economically significant species that is sensitive to water levels. We used machine learning methods, including the Random Forest algorithm, to classify common reed-containing wetland vegetation and water surfaces in the delta based on satellite data from 2000 to 2023. The remote sensing results were integrated with field-based geobotanical studies conducted between 2017 and 2019. These studies, which facilitated identification of three classes of vegetation: meadow, marsh and aquatic, also revealed a good correspondence between predicted and measured common reed biomass per unit area. The long-term dynamics of four wetland communities with a common reed content of ≥25% were analyzed with respect to significant interannual variability in the flow of the Ili River. The highest water inflows and water surface areas in the delta were recorded in 2002, 2010 and 2016, and in each case, a statistically significant expansion of common reed was observed one year later. Common reed areas subsequently declined—rapidly or after a lag of several years. Temporal expansion and contraction of these areas following pulses of water differed substantially from that of overall wetland vegetation as measured previously. The identified patterns have important scientific and practical significance for assessing the stability of the surrounding wetlands, preservation of the delta environment, and sustainable use of common reed.