The implications of minimum stomatal conductance on modeling water flux in forest canopies

Stomatal conductance (g(s)) models are widely used at a variety of scales to predict fluxes of mass and energy between vegetation and the atmosphere. Several g(s) models contain a parameter that specifies the minimum g(s) estimate (g(0)). Sensitivity analyses with a canopy flux model (MAESTRA) identified g(0) to have the greatest influence on transpiration estimates (seasonal mean of 40%). A spatial analysis revealed the influence of g(0) to vary (30-80%) with the amount of light absorbed by the foliage and to increase in importance as absorbed light decreased. The parameter g(0) is typically estimated by extrapolating the linear regression fit between observed g(s) and net photosynthesis (A(n)). However, our measurements demonstrate that the g(s)-A(n) relationship may become nonlinear at low light levels and thus, extrapolating values from data collected over a range of light conditions resulted in an underestimation of g(0) in Malus domestica when compared to measured values (20.4 vs 49.7mmolm(-2)s(-1) respectively). In addition, extrapolation resulted in negative g(0) values for three other woody species. We assert that g(0) can be measured directly with diffusion porometers (as g(s) when A(n)0), reducing both the time required to characterize g(0) and the potential error from statistical approximation. Incorporating measured g(0) into MAESTRA significantly improved transpiration predictions versus extrapolated values (6% overestimation versus 45% underestimation respectively), demonstrating the benefit in g(s) models. Diffusion porometer measurements offer a viable means to quantify the g(0) parameter, circumventing errors associated with linear extrapolation of the g(s)-A(n) relationship.