Global fitness maximising approaches to evaluate the trade-offs involved in the evergreen and deciduous conundrum
Which traits and/or trade-offs determine benefits of being deciduous or evergreen?
With the changing climate comes an increase in demand for climate knowledge. This project takes on the challenge of building a prognostic trait-based model to understand and predict how evergreen-deciduous strategies affect plant fitness and global distribution.
Trait-based Dynamic Global Vegetation Modelling
As the effects of climate change on the earth are becoming more and more apparent, the demand for a better understanding of Earth system processes increases. This makes Earth System Modelling (ESM) an indispensable tool to simulate biogeochemical fluxes and predict future trends. ESM predictions vary widely in their carbon-balance. This project will fundamentally improve the representation of the terrestrial biosphere upon environmental change by modifying Dynamic Global Vegetation Models (DGVMs) with trait dynamics and constraints.
The evergreen-deciduous conundrum
Despite its global significance, the challenge of building a prognostic model to understand and predict how evergreen-deciduous strategies affect plant fitness and the global distribution of these leaf habits has, however, not been addressed. Here, we will apply eco-evolutionary principles to develop a mechanistic foundation with respect to this conundrum, evaluating trade-offs among key dynamic traits in relation to plant carbon and nutrient management and hydraulics in the absence and presence of competition.
The impacts of these trait constraints will be tested in the modular fully data-constrained DGVM of Microsoft Research to provide generic ecological insights on emergent trait values for different leaf habits, including their impacts on flux predictions, now and in a future climate.