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The implications of minimum stomatal conductance on modeling water flux in forest canopies
Author(s) -
Barnard D. M.,
Bauerle W. L.
Publication year - 2013
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/jgrg.20112
Subject(s) - transpiration , stomatal conductance , flux (metallurgy) , extrapolation , conductance , canopy , atmospheric sciences , atmosphere (unit) , linear regression , environmental science , diffusion , canopy conductance , mathematics , photosynthesis , chemistry , statistics , botany , physics , meteorology , thermodynamics , biology , vapour pressure deficit , organic chemistry , combinatorics
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 49.7 mmol m −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.