Background/Question/Methods   Ecosystem process models are essential tools in assessments of the changing global climate. Estimates of canopy transpiration scaled from measurements of sap flux are an increasingly important data source for parameterization of process models linking water and carbon exchange in forests. Data sets of sap flux, however, necessarily incorporate variability between diameter classes, individual trees and even within the sapwood of individuals. Gaps and discontinuities in data associated with sensor failures and sampling design changes are also common in long-term sap flux data sets. Uncertainties in estimates of canopy conductance translate into uncertainties in carbon assimilation through models that combine physiological and environmental data to estimate photosynthetic rates, such as the Canopy Conductance Constrained Carbon Assimilation (4CA) model*. We developed a method to propagate the uncertainties in the scaling and imputation of sap flux data to estimates of canopy transpiration and conductance using a state-space Jarvis-type conductance model in a hierarchical Bayesian framework. This presentation will focus on the impact of these uncertainties on estimates of water and carbon fluxes using 4CA and data from the Duke Free Air Carbon Enrichment (FACE) project.

Results/Conclusions   In 2006, a year of average precipitation (1127 mm), errors related to scaling and imputation of sap flux had little effect of annual carbon assimilation estimates (1-2%), as conductance was generally above values that would limit assimilation. In contrast, these errors translated into large (~27%) uncertainty in annual carbon assimilation estimates in 2007, a year of pronounced drought (800 mm of precipitation). During periods of high soil moisture, elevated CO2 plots exhibited higher canopy conductance than ambient CO2 plots, proportional to differences in leaf area index. During the drought of late 2007, canopy conductance was similar in the two CO2 treatments, indicating a greater sensitivity to low soil moisture in elevated CO2 plots. This non-random variability related to environmental conditions in both canopy conductance values and their impact on carbon assimilation estimates reveals the need for multiyear sap flux data sets to calibrate models in a changing global climate. Our approach represents a valuable tool for dealing with the variability, gaps and discontinuities within such data sets. *Schäfer, K.V.R., R. Oren, D.S. Ellsworth, C.T. Lai, J.D. Herrick, A.C. Finzi, D.D. Richter and G.G. Katul. 2003. Exposure to an enriched CO2 atmosphere alters carbon assimilation and allocation in a pine forest ecosystem. Global Change Biology. 9:1378–1400.