Towards Improvement of Physiologically Based Estimates of Seasonal Transpiration.

A sound understanding of the feedbacks between climate, plant transpiration, and hydrology is crucial for accurate predictions of future global and regional water resources, as well as for predicting crop water use and crop responses under future climate conditions. One of the most commonly used semi-empirical models of stomatal conductance (g_s) was proposed by Ball et al., (1987), hereafter abbreviated the BWB model. The BWB model links g_s to net photosynthesis (A_n), relative humidity at the leaf surface (h_s ), and CO₂ concentration at the leaf surface (C_s ). The slope term (m) is the slope of the relationship between g_s and A_nh_s/C_s and represents the composite sensitivity of g_s to environmental factors. Other models that couple g_s to A_n utilize different forms of the original BWB model but similarly link the demand for CO₂ with g_s and utilize a variation of the slope term. While good estimates of m are necessary for accurately estimating transpiration, the parameter requires a substantial time investment to collect. Hence, some models use a set value of the parameter across functional types, and values are also frequently assumed from previous literature values. Although the parameter is sometimes derived via fitting to large data sets, a traditional and robust method of collection is via time-intensive gas exchange measurements. Here we report values of m measured via gas exchange for Zea mays and Helianthus annuus L. across two growing seasons and demonstrate the influence of the parameter on the accuracy of transpiration estimates.