Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.

Hydroclimatic conditions and related water resources change in the Tibetan Plateau is one of the main concerns for future sustainable development in China. This study presents a 254-year precipitation reconstruction from August of the previous year to June of the current year for the northeastern Tibetan Plateau based on tree-ring width data of tree-ring cores of Picea crassifolia from three sampling sites. The precipitation reconstruction explained 51.4% of the variance in instrumental precipitation during the calibration period 1958–2013. Dry periods with precipitation below the 254-year average value occurred during 1848–1865, 1873–1887, 1898–1923, and 1989–2003, and wet periods (precipitation above the mean) occurred during 1769–1785, 1798–1833, 1924–1938, 1957–1968, and 2004–2013. Spatial correlation analyses with the precipitation gridded dataset showed that our reconstruction contains some strong regional-scale precipitation signals for the upper Yellow River Basin. Our precipitation reconstruction also agreed in general with other dendroclimatic precipitation reconstructions from surrounding regions. In addition, reconstructed precipitation changes were consistent with the streamflow variation of the Yellow River.

Eastern Xinjiang, as a typical extremely arid area, exhibits a high sensitivity to climate change. Gaining a comprehensive understanding of the climatic changes in this region, along with their driving mechanisms, and comparing these with the broader trend of “warming and humidifying” in the Northwest can provide a scientific foundation for adapting to and addressing climate change. Based on a study of precipitation and temperature data from seven meteorological stations in Eastern Xinjiang from 1960 to 2022, the following findings were observed: (1) The climate of eastern Xinjiang is generally characterized by a warming and humidifying trend, with the rates of mean annual temperature and total annual precipitation being 0.39 °C/10 a and 3.32 mm/10 a. The eastern part of Xinjiang has less precipitation, with a lower growth rate than that of the neighboring regions, and higher temperatures, with a higher growth rate than that of the neighboring regions. (2) The first principal component of precipitation explains 47.85% of the variation in total precipitation, with a significant upward trend (p < 0.05) and an abrupt change in the late 1970s. It contains strong signals of regional precipitation, temperature, and dry and wet changes. (3) The increase in the first principal component of annual precipitation in eastern Xinjiang is mainly related to the warming of SSTs in the Indian Ocean and the central-eastern part of the tropical southern Pacific Ocean as well as the weakening of the Asian monsoon.

Our understanding of Central Asian historical streamflow variability is still limited because of short instrumental hydrologcial records. Based on tree-ring cores collected from three sampling sites in Kaiken River basin near Tien Shan, a regional tree-ring width chronology were developed. The correlation analysis showed that the runoff of Kaiken River from previous August to current June was significantly correlated with the regional chronology, and the high correlation coefficient was 0.661 (P < 0.01). Based on the regional chronology, the August-June runoff of Kaiken River has been reconstructed over the past 422 year, and it accounted for 43.7% of actual runoff variance during the common period 1983–2013. The reconstruction model is reliable, and the trend of observed and reconstructed data is relatively consistent. The results of multi-taper spectral analysis for the runoff reconstruction indicated some remarkable cycles for the past 422 years; the 11.5-year cycles correspond to the solar cycle and is found widely in runoff reconstructions in Central Asia. This may imply a solar influence on the hydroclimate variations of Tien Shan. The runoff reconstruction of Kaiken River compares well with runoff reconstructions the Urumqi River and Manas River, and implies that there is a common driving factor for the runoff in central Tien Shan, China. The analysis of linkages between climate variation and the runoff reconstruction of Kaiken River shows that there is a relationship between extremes in runoff variation and abnormal atmospheric circulations. Our 422-year steamflow reconstruction provides long-term perspective on current and 20th century hydrological events in central Tien Shan, is useful for aids sustainable water management and addresses regional climate change challenges.

The maximum latewood density (MXD) of tree rings can reflect the temperature of the growing season, but the timing of the response differs among regions. We selected 152 maximum latewood density chronologies from the Northern Hemisphere that showed a significant response to temperature. Based on a cluster analysis and the sensitivity of MXD to the monthly mean temperature, the chronologies were classified into six clusters. The clusters showed distinct regional characteristics, and the period and peak month of significant response of the chronologies in each cluster to temperature were different. Spatial synchronization of the MXDs revealed that the two clusters distributed in Europe showed the most consistency and the strongest response to the April–September monthly mean temperature compared with the other clusters. Temperature accounted for more than 40% of the total MXD variance in all clusters, whereas the effect of precipitation was much smaller. In addition to climatic factors, the random effect of the latitude and longitude of sampling sites, elevation, and tree species was a major factor contributing to the variance in MXD in each cluster. Latitude and longitude had the strongest influence among the three random effects, and tree species had the weakest influence, except at high latitudes. The MXD of each cluster showed sensitivity to temperature within a certain interval, with a positive linear response, and the sensitivity interval was greatest at high latitudes. Certain clusters showed a negative linear sensitivity to precipitation. The results provide a reference for studying the climatic threshold of large-scale tree-ring density formation.

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment.