Anne Uilhoorn received her BSc degree in Biology in 2010 and her MSc degree in Environmental Biology in 2011 at Utrecht University
Anne Uilhoorn received her BSc degree in Biology in 2010 and her MSc degree in Environmental Biology in 2011 at Utrecht University. During her MSc she specialized in Ecology & Natural Resource Management. Her major research project in her master focused on the effects of salinization through climate change on decomposition in drained peat meadows in the Netherlands. Her master thesis was a proposal for a model on the effects of agricultural pollution on piscivorous birds in the Danube Delta (Romania).
After obtaining her MSc degree Anne worked as a research assistant at Wageningen University. She worked in the dendrochronology lab on the TROFOCLIM project (Tropical Forests and Climate Change) to detect, explain and predict long-term climate change effects on tropical tree dynamics. Following this experience she has been a professional congress organizer for the International Society for Microbial Ecology and Rhizosphere 4.
She joined CML in September 2015 to obtain her PhD on the subject of global fitness maximizing approaches to evaluate the trade-offs involved in the evergreen and deciduous conundrum.
The PhD project of Anne will be in collaboration with Microsoft’s Computational Science Lab in Cambridge. This project aims to incorporate trait dynamics and constraints in Dynamic Global Vegetation Models (DGVMs) to fundamentally improve their representation of the terrestrial biosphere upon environmental change. This prognostic model will be used to understand and predict how evergreen-deciduous strategies affect plant fitness and the global distribution of these leaf strategies. We will apply eco-evolutionary principles to develop a mechanistic foundation with respect to this conundrum. We will evaluate trade-offs among key dynamic traits in relation to plant carbon and nutrient management and hydraulics in the absence and presence of competition. The impact 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 impact on flux predictions, now and in a future climate.