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Age-related effects on whole-tree hydraulics are one of the key challenges to better predicting the production and growth of old-growth forests. Previous models have described the optimal state of stomatal behaviour, and field studies have implied on age/size-induced trends in tree ecophysiology related to hydraulics. On these bases, we built a Bayesian hierarchical model to link sap flow density and drivers of transpiration directly. The model included parameters with physiological meanings and accounted for variations in leaf-sapwood area ratio and the time lag between sap flow and transpiration. The model well-simulated the daily pattern of sap flow density and the variation between tree age groups. The results of parameterization show that (1) the usually higher stomatal conductance in young than old trees during mid-summer was mainly because the sap flow of young trees were more activated at low to medium light intensity, and (2) leaf-sapwood area ratio linearly decreased while time lag linearly increased with increasing tree height. Uncertainty partitioning and cross-validation, respectively, indicated a reliable and fairly robust parameter estimation. The model performance may be further improved by higher data quality and more process-based expressions of the internal dynamics of trees.

Weaker Light Response, Lower Stomatal Conductance and Structural Changes in Old Boreal Conifers Implied by a Bayesian Hierarchical Model