An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness‐of‐fit across diverse data sets

International audienceStomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO2 between the leaf and the atmosphere. Representation of stomatal conductance (g(sw)) is therefore an essential component of models that seek to simulate water and CO2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g(sw) and photosynthetic CO2 assimilation (A). However, measurement of leaf-level g(sw) response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of g(sw) and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between g(sw) and A was not linear, challenging the key assumption upon which optimality theory is based-that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in g(sw) at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g(0) and g(1). Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g(1) and other leaf traits. We also observed nonlinear behavior between A and g(sw) in independent data sets that included data collected from attached and detached leaves, and from plants grown at elevated CO2 concentration. We propose that this empirical modification of the USO model can improve the measurement of g(sw) parameters and the estimation of plant and ecosystem-scale water and CO2 fluxes