Constraining 3‐PG with a new δ13C submodel: a test using the δ13C of tree rings

L Wei, JD Marshall, TE Link… - Plant, cell & …, 2014 - Wiley Online Library
Plant, cell & environment, 2014Wiley Online Library
A semi‐mechanistic forest growth model, 3‐PG (P hysiological P rinciples P redicting G
rowth), was extended to calculate δ13 C in tree rings. The δ13 C estimates were based on
the model's existing description of carbon assimilation and canopy conductance. The model
was tested in two∼ 80‐year‐old natural stands of A bies grandis (grand fir) in northern
Idaho. We used as many independent measurements as possible to parameterize the
model. Measured parameters included quantum yield, specific leaf area, soil water content …
Abstract
A semi‐mechanistic forest growth model, 3‐PG (Physiological Principles Predicting Growth), was extended to calculate δ13C in tree rings. The δ13C estimates were based on the model's existing description of carbon assimilation and canopy conductance. The model was tested in two ∼80‐year‐old natural stands of Abies grandis (grand fir) in northern Idaho. We used as many independent measurements as possible to parameterize the model. Measured parameters included quantum yield, specific leaf area, soil water content and litterfall rate. Predictions were compared with measurements of transpiration by sap flux, stem biomass, tree diameter growth, leaf area index and δ13C. Sensitivity analysis showed that the model's predictions of δ13C were sensitive to key parameters controlling carbon assimilation and canopy conductance, which would have allowed it to fail had the model been parameterized or programmed incorrectly. Instead, the simulated δ13C of tree rings was no different from measurements (P > 0.05). The δ13C submodel provides a convenient means of constraining parameter space and avoiding model artefacts. This δ13C test may be applied to any forest growth model that includes realistic simulations of carbon assimilation and transpiration.
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