The detection and attribution of vegetation dynamics in drylands is an important step for the development of effective adaptation and mitigation strategies to combat the challenges posed by human activities and climate change. However, due to the spatial heterogeneity and interactive influences of various factors, quantifying the contributions of driving forces on vegetation change remains challenging. In this study, using the normalized difference vegetation index (NDVI) as a proxy of vegetation growth status and coverage, we analyzed the temporal and spatial characteristics of the NDVI in China’s Inner Mongolian grasslands using Theil–Sen slope statistics and Mann–Kendall trend test methods. In addition, using the GeoDetector method, a spatially-based statistical technique, we assessed the individual and interactive influences of natural factors and human activities on vegetation-NDVI change. The results show that the growing season average NDVI exhibited a fluctuating upward trend of 0.003 per year from 2000 to 2018. The areas with significant increases in NDVI (p < 0.05) accounted for 45.63% of the entire region, and they were mainly distributed in the eastern part of the Mu Us sandy land and the eastern areas of the Greater Khingan Range. The regions with a decline in the NDVI were mainly distributed in the central and western regions of the study area. The GeoDetector results revealed that both natural and human factors had significant impacts on changes in the NDVI (p < 0.001). Precipitation, livestock density, wind speed, and population density were the dominant factors affecting NDVI changes in the Inner Mongolian grasslands, explaining more than 15% of the variability, while the contributions of the two topography factors (terrain slope and slope aspect) were relatively low (less than 2%). Furthermore, NDVI changes responded to the changes in the level of specific influencing factors in a nonlinear way, and the interaction of two factors enhanced the effect of each singular factor. The interaction between precipitation and temperature was the highest among all factors, accounting for 39.3% of NDVI variations. Findings from our study may aid policymakers in better understanding the relative importance of various factors and the impacts of the interactions between factors on vegetation change, which has important implications for preventing and mitigating land degradation and achieving sustainable pasture use in dryland ecosystems.

Spatial scale plays a crucial role in the assessment and management of ecosystem services (ES), yet explicit information for identifying and understanding the scale effect on ES supply remains limited. In an attempt to detect scale effect on ES supply from a comprehensive perspective, this study developed a framework for integrating scale effect in three aspects, including individual ES patterns, pairwise ES interactions, and ecosystem service bundles (ESB). The framework was tested in Xilinhot, a prairie landscape city of Inner Mongolia, at four different levels of spatial scale. The results indicated that, most ES showed a decreasing clustering at coarser scales in terms of spatial pattern. At the same time, coarser scales resulted in fewer trade-offs and stronger synergies between pairwise ES. The identification of ESB varied greatly with scale, and this change reflected in the composition of ES variables and spatial distribution of bundles. We attributed the scale effect of the above three aspects to differences in social-ecological factors and their driving mechanisms at different scales. This comprehensive framework could support local managers to coordinate the management of multiple ES at different scales.

Grassland restoration projects are currently being implemented to mitigate human disturbance to the natural environment and reduce grassland degradation. China’s Grain-for-Green Programme (GFGP), including one project implemented in Duolun County, China, in 2000, has significantly improved the overall ecological health of this region. Using a modeling approach, this study quantified changes in four ecosystem services (ESs), including Net Primary Production (NPP), soil conservation (SC), water yield (WY), and sandstorm prevention (SP), in Duolun County between 2000 and 2016. We found the total NPP, water yield, and soil conservation increased by 80.44%, 248.2%, and 12.2%, respectively, during this period, while the sandstorm prevention decreased by 55.9%. Unlike other areas of GFGP implementation, the improvement of the ecological environment in Duolun County is largely attributed to the increased of vegetation coverage (88%) instead of land use circulation (12%). We found the grassland is a factor that reduces the trade-off while this effect was related with the grassland coverage. Future policies should be based on the mechanisms of vegetation underlying the ESs change and the relationships of ESs in order to achieve sustainable provision of ESs.