Numerous studies have confirmed that climate change leads to a decrease in the net ecosystem productivity (NEP) of terrestrial ecosystems and alters regional carbon source/sink patterns. However, the response mechanism of NEP to climate change in the arid regions of Central Asia remains unclear. Therefore, this study combined the Carnegie–Ames–Stanford approach (CASA) and empirical models to estimate the NEP in Central Asia and quantitatively evaluate the sensitivity of the NEP to climate factors. The results show that although the net primary productivity (NPP) in Central Asia exhibits an increasing trend, it is not significant. Soil heterotrophic respiration (RH) has increased significantly, while the NEP has decreased at a rate of 6.1 g C·m⁻²·10 a⁻¹. Spatially, the regional distribution of the significant increase in RH is consistent with that of the significant decrease in the NEP, which is concentrated in western and southern Central Asia. Specifically, the NPP is more sensitive to precipitation than temperature, whereas RH and NEP are more sensitive to temperature than precipitation. The annual contribution rates of temperature and precipitation to the NEP are 28.79% and 23.23%, respectively. Additionally, drought has an important impact on the carbon source/sink in Central Asia. Drought intensified from 2001 to 2008, leading to a significant expansion of the carbon source area in Central Asia. Therefore, since the start of the 21st century, climate change has damaged the NEP of the Central Asian ecosystem. Varying degrees of warming under different climate scenarios will further aggravate the expansion of carbon source areas in Central Asia. An improved understanding of climate change impacts in Central Asia is critically required for sustainable development of the regional economy and protection of its natural environment. Our results provide a scientific reference for the construction of the Silk Road Economic Belt and global emissions reduction.

The ecosystems in the arid inland areas of Central Asia are fragile and severely degraded. Understanding and assessing ecosystem resilience is a challenge facing ecosystems. Based on the net primary productivity (NPP) data estimated by the CASA model, this study conducted a quantitative analysis of the ecosystem’s resilience and comprehensively reflected its resilience from multiple dimensions. Furthermore, a comprehensive resilience index was constructed. The result showed that plain oasis’s ecosystem resilience is the highest, followed by deserts and mountainous areas. From the perspective of vegetation types, the highest resilience is artificial vegetation and the lowest is forest. In warm deserts, the resilience is higher in shrubs and meadows and lower in grassland vegetation. High coverage and biomass are not the same as the strong adaptability of the ecosystem. Moderate and slightly inelastic areas mainly dominate the ecosystem resilience of the study area. The new method is easy to use. The evaluation result is reliable. It can quantitatively analyze the resilience latitude and recovery rate, a beneficial improvement to the current ecosystem resilience evaluation.

Soil moisture (SM) significantly affects the exchange of land surface energy and the stability of terrestrial ecosystems. Although some conclusions have been drawn about the effects of SM on the ecosystem water use efficiency (WUE), the influence mechanism and the quantitative assessment framework of SM on WUE are still unclear. This study provides an analysis framework for the feedback relationship between SM and WUE based on the dependence of the evaporation fraction on SM and output datasets from remote sensing and the Global Land Data Assimilation System. The results show that the range of WUE of terrestrial ecosystems of China was 0.02–19.26 g C/kg H₂O in the growing season with an average value of 1.05 g C/kg H₂O. They also show a downward trend in 43.99% of the total area. In the evapotranspiration (ET) pathway, SM negatively affected WUE, and the sensitivity coefficient ranged from −18.49 to −0.04. In the net primary production (NPP) pathway, the sensitivity coefficient ranged from −68.66 to 43.19. Under the dual effects of the ET and NPP pathways, the influence of SM on WUE was negative in 84.62% of the area. Variation in SM led to significant WUE variability. Generally, the percentage change in WUE (ΔWUE) ranged from 0% to 190.86%, with an average value of 28.02%. The maximum ΔWUE ranged from 0% to 758.78%, with an average value of 109.29%. The WUE of forest ecosystems showed strong resistance to SM variation, whereas that of non-forest vegetation was more sensitive to SM variation. This analytical framework provides a new perspective on the feedback relationship between WUE and SM in terrestrial ecosystems.