Abstract
Modelling results of stomatal conductance of trembling aspen (Populustremuloides Michx.) and white birch (Betulapapyrifera Marsh.) are reported. Stomatal conductance for the two species was related to global solar radiation, vapour pressure deficit, and air temperature using both linear and nonlinear least squares approaches. Both approaches provided an equally poor fit when relating the large scatter of stomatal conductance data to each of the environmental variables separately. However, an additive, multiple linear regression model and a multiplicative, nonlinear least squares model were able to explain between 50 and 62% of the variability in stomatal conductance when all three environmental variables were included in the models. The two models were able to track changes in stomatal conductance from one half-hour period to the next.
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