One stomatal model to rule them all? Evaluating competing hypotheses to regulate the exchange of carbon and water against experimental data

Nearly 2/3 of the annual global evapotranspiration (ET) over land arises from the vegetation. Yet, coupled-climate models only attribute between 22% – 58% of the annual terrestrial ET to plants. In coupled-climate models, the exchange of carbon and water between the terrestrial biosphere and the atmosphere is simulated by land-surface models (LSMs). Within those LSMs, stomatal conductance (g_s) models allow plants to regulate their transpiration and carbon uptake, but most are empirically linked to climate, soil moisture availabilty, and CO₂. Therefore, how and which g_s schemes are implemented within LSMs is a key source of model uncertainty. This uncertainty has led to considerable investment in theory development in the recent years; multiple alternative hypotheses of optimal leaf-level regulation of gas exchange have been proposed as solutions to reduce existing model biases. However, a systematic inter-model evaluation is lacking (i.e. inter-model comparison within a single framework is needed to understand how different mechanistic assumptions across these new g_s models affect plant behaviour). Here, we asked how, and under what conditions, nine novel optimal g_s models differ from one another. The models were trained to match under average conditions before being subjected to: (i) a dry-down, (ii) high vapour pressure deficit, and (iii) elevated CO₂. These experiments allowed us to identify the models’ specific responses and sensitivities. To further assess whether the models’ responses were realistic, we tested them against photosynthetic and hydraulic field data measured along mesic-xeric gradients in Europe and Australia. Finally, we evaluated model performance versus model complexity and the amount of information taken in by each model, which enables us to make recommendations regarding the use of stomatal conductance schemes in global climate models.