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Objective 6

Objective 6: Development of a global framework and methodology for predicting spatiotemporal dynamics of vegetation-related ecosystem functioning that accounts for the constraints imposed by long-term biodiversity dynamics:

Models predicting the distribution of terrestrial vegetation-defined ecosystems and their functioning are a key component of climate simulation models due to climate-ecosystem feedbacks and thus of key importance for predicting future climate change. They are also needed for predicting changes in ecosystems, their functioning and associated services. State-of-the-art models of ecosystem responses and feedbacks (Dynamic Global Vegetation Models, DVGMs) to climate changes are based on generalized physical, physiological and ecological mechanisms and at best provides limited consideration of biodiversity effects (competitive interactions between a few generalized functional types). The ‘lacking’ representation of functional diversity has been highlighted as ‘troubling’ for climate modelling. Long-term historical constraints have not previously been considered for DGVMs at all. Our objective here is to develop a novel framework and methodology for predicting spatiotemporal dynamics of vegetation-related ecosystem functioning that accounts for the constraints imposed by long-term biodiversity dynamics. The framework will be based on the findings under the other objectives.

The HISTFUNC project will explore and develop a range of methodologies for predictive ecosystem modeling on a global scale, ranging from (i) advanced statistical modeling (building on our approaches in) over (ii) hybrid statistical-mechanistic models that combine statistical modeling of ecosystem-environment links, biodiversity-ecosystem relations, and large-scale historical effects with dynamic simulations of future dispersal dynamics as well as certain physiological effects (notably changing atmospheric CO2 levels) to (iii) DVGMs, modified to take biodiversity-ecosystem relations and large-scale historical effects into account. The modeling will primarily rely on data used under the previous objectives in combination with simulations of future climate.

Impact: The development of predictive ecosystem models that accounts for biodiversity effects and historical constraints will be a major step forward not just for ecology, but also for global change biology and climatology, improving the basis for predicting climate change and its feedbacks with ecosystems.