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.

Stomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO ₂ 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 CO ₂ exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO ₂ concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g _sw and photosynthetic CO ₂ 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 CO ₂ 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 CO ₂  fluxes.
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