Stomatal pores on leaf surfaces respond to environmental and physiological signals to regulate leaf gas exchange. Mathematical models can predict stomatal conductance (g s), with one parameter (m or g l) reflecting the sensitivity of g s to the photosynthetic rate (A), atmospheric carbon dioxide concentration and atmospheric humidity, and a second parameter (g 0) representing the minimum g s. Such models are solved iteratively with a photosynthesis model to form the core of many models of crop or ecosystem carbon and water fluxes. For three decades, g s models have frequently been used assuming fixed parameter values for m or g 1 and g 0 across species and major plant functional types. This study of temperate tree species reveals significant interspecific variation in stomatal function. Applying species-specific parameterizations substantially reduced error in model predictions of g s by 34 to 64% and A by 52 to 60% and resulted in significant correlation between modelled and measured values. This work challenges the long-held assumption of fixed parameter values and, in doing so, suggests an approach for reducing modelling error across a wide range of ecological and agricultural applications.