Will the Congo basin forest hit a tipping point? Estimating the risk of large-scale changes of the Congo Basin forests based on data assimilation in a Land Surface Model

The Congo Basin hosts the second largest expanse of tropical rainforests in the world. As such, it
plays a critical role in our changing Earth System. Yet, there is a striking discrepancy between the
paramount importance of Congo Basin forests on the one hand and their scientific coverage on the
other. This explains why the scientific community has not developed, as of today, reliable modelling
tools capable of projecting the impact of future changes on the forest state and functioning. In this
project, I propose to fill this gap by combining a state-of-the-art Land Surface Model with the most
up-to-date observations of the carbon cycle and functional diversity in the Congo Basin. More
specifically, I will develop a vegetation model (ED2) using multiple data sources from intact and
disturbed forests, upscale the model simulations, and validate model outputs using recent remote
sensing products. Data for model calibration and validation include (1) dynamics of carbon and
functional diversity observed in multiple chronosequences, (2) repeated inventories of dozens of
intact forests, (3) eddy covariance data from the first fluxtower in the Congo Basin and (4) remote
sensing observations of human-induced disturbance, forest structure, productivity and biomass. I will
then use the model to examine forest resilience under current and future climate and land-use
change scenarios and to detect any potential large-scale tree cover loss in the Cong Basin by the end
of this century.