Monitoring ecosystem dynamics is fundamental to understanding and eventually forecasting ecosystem states. To achieve this, it is crucial to identify and understand potential negative/ positive effects from a changing world on the system. As one key aspect of every ecosystem are the living organisms it involves, our research focuses on vegetation, since it has major implications for both the climate, because plants absorb carbon dioxide, and human well-being, because people depend on the products of plants. Specifically addressing global drylands, where vegetation productivity is tightly linked to the availability of water (mainly through rainfall), we quantify changes in vegetation functioning by analyzing the slopes of a sequential linear regression (SeRGS) over a time series of remote sensing data (NDVI and rainfall), as introduced in Abel et al., 2019. Further, we apply a data-driven, empirical approach to estimate the relative importance of potential drivers of identified changes, as in Abel et al., 2020 (in revision). We show that there are substantial regional and continental differences in vegetation functioning and that these trends can be linked to global trends of population expansion, large-scale agriculture intensification/ expansion and changing climatic conditions. Results from these studies, follow-up research and perspectives will be presented and discussed at EGU.References:Abel, C., Horion, S., Tagesson, T., Brandt, M., Fensholt, R. (2019). Towards improved remote sensing based monitoring of dryland ecosystem functioning using sequential linear regression slopes (SeRGS). Remote Sens. Environ. 224, 317-332.Abel, C., Horion, S., Tagesson, T., De Keersmaecker, W., Seddon, A. W. R., Abdi A. M., Fensholt, R. (2020). How the human-environment nexus changes global dryland vegetation functioning, in revision.