Quantitative assessment of the dynamics of carbon and water use efficiency on the Loess Plateau in the context of complex climate change and its driving mechanisms is important for the improvement of the regional ecological environment and the enhancement of ecological service functions. In order to assess the impact of climate change and human activities on the carbon and water use efficiency of the Loess Plateau, this study investigates the spatial and temporal rates of change in CUE, WUE, and meteorological factors at the image metric scale using one-dimensional linear fit regression, investigates the spatial correlation between CUE and meteorological factors using partial correlation analysis, and quantifies the relative contributions of human activities to CUE and WUE using residual analysis. The following are the study’s conclusions: (1) The CUE and WUE of the Loess Plateau decreased geographically from 2000 to 2020, and both the CUE and WUE of the Loess Plateau exhibited a non-significant declining trend (p > 0.05), with the CUE falling at a rate of 0.001/10a (a: year) and the WUE decreasing at a rate of 0.047/10a (a: year). (2) From 2000 to 2020, the mean values of the CUE and WUE of the Loess Plateau were 0.60 and 1.75, respectively, with a clear spatial difference. (3) CUE was favorably linked with precipitation in 56.51% of the Loess Plateau, dispersed throughout the south-central portion of the Loess Plateau and Inner Mongolia, whereas the biased association with temperature was not statistically significant and often negative. (4) An examination of residuals revealed that human activities affected the trend of CUE and WUE to some degree. Only the WUE residuals of evergreen broadleaf forests exhibited a strong upward trend that was considerably influenced by people. In conclusion, this study used remote sensing image data and meteorological data to systematically analyze the spatial and temporal dynamic patterns of carbon use efficiency and water use efficiency on the Loess Plateau over the past 21 years, as well as the characteristics of their responses to climate change and human activities, thereby providing theoretical guidance for the study of carbon and water cycles in terrestrial ecosystems on the Loess Plateau.

Soil moisture is an important component of the soil–vegetation–atmosphere terrestrial hydrological cycle and is an important factor affecting terrestrial ecosystems. In the context of extensive vegetation greening on the Tibetan Plateau (TP), it is important to investigate the effect of vegetation greening on soil moisture to maintain ecosystem stability and protect the sustainability of ecological restoration projects. To evaluate the effect of vegetation greening on soil moisture on the TP, the spatial distribution and trends of soil moisture and vegetation on the TP were analyzed using GIMMS NDVI data and ERA5 soil moisture data from 1982 to 2015. The effects of grassland NDVI, precipitation, and temperature on SM were also explored using multiple regression apparent and SEM. The main results are as follows: from 1982 to 2015, both grassland NDVI and SM showed a stable increasing trend. Precipitation was the most important factor influencing SM changes on the TP. In the context that vegetation greening is mainly influenced by temperature increase, vegetation plays a dominant role in SM changes in soil drying and soil wetting zones. In this paper, the climate–vegetation–soil moisture coupling mechanism of grasslands on the TP is investigated, and the related results can provide some theoretical references and suggestions for global ecosystem conservation and the sustainable development of ecological restoration projects.

Plant functional traits (PFTs) can reflect the response of plants to environment, objectively expressing the adaptability of plants to the external environment. In previous studies, various relationships between various abiotic factors and PFTs have been reported. However, how these factors work together to influence PFTs is not clear. This study attempted to quantify the effects of topographic conditions, soil factors and vegetation structure on PFTs. Four categories of variables were represented using 29 variables collected from 171 herb plots of 57 sites (from different topographic and various herb types) in Xindian SWDP. The partial least squares structural equation modeling showed that the topographic conditions and soil properties also have a direct effect on plant functional traits. Among the topographic conditions, slope (SLO) has the biggest weight of 0.629, indicating that SLO contributed the most to plant functional traits and vegetation structure. Among soil properties, maximum water capacity (MWC) contributes the most and is followed by soil water content (SWC), weighted at 0.588 and 0.416, respectively. In a word, the research provides new points into the quantification of the correlation between different drivers that may be important for understanding the mechanisms of resource utilization, competition and adaptation to the environment during plant recovery.