The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.

Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.

Even models relying on physical laws have parameters that need to be measured or estimated. Thermodynamic optimality principles potentially offer a way to reduce the number of estimated parameters by stating that a system evolves to an optimum state. These principles have been applied successfully within the Earth system, but it is often unclear what to optimize and how. In this review paper we identify commonalities between different successful applications as well as some doubtful applications.

This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.

Leaf transpiration and energy exchange are coupled processes at the small scale that have strong effects on the water cycle and climate at the large scale. In this technical note, we present a novel experimental set-up that enables detailed study of these coupled processes in the laboratory under controlled conditions. Results document the abilities of the experimental set-up to confirm or challenge our understanding of these processes.

Most of the rain falling on land is returned to the atmosphere by plant leaves, which release water vapour (transpire) through tiny pores. To better understand this process, we used artificial leaves in a special wind tunnel and discovered major problems with an established approach (PM equation) widely used to quantify transpiration and its sensitivity to climate change. We present an improved set of equations, consistent with experiments and displaying more realistic climate sensitivity.

We estimated forest transpiration (European beech) along a steep valley cross section. Atmospheric demand, obtained by the thermodynamic limit of maximum power, is the dominant control of transpiration at all sites. To our surprise we find that transpiration is rather similar across sites with different aspect (north vs. south) and different stand structure due to systematically varying sap velocities. Such a compensation effect is highly relevant for modeling and upscaling of transpiration.