Modelling basin-wide variations in Amazon forest productivity – Part 1: Model calibration, evaluation and upscaling functions for canopy photosynthesis

摘要

Given the importance of Amazon rainforest in the global carbon andhydrological cycles, there is a need to parameterize and validateecosystem gas exchange and vegetation models for this region in orderto adequately simulate present and future carbon and waterbalances. In this study, a sun and shade canopy gas exchange model iscalibrated and evaluated at five rainforest sites using eddycorrelation measurements of carbon and energy fluxes.Results from the model-data evaluation suggest that with adequateparameterisation, photosynthesis models taking into account theseparation of diffuse and direct irradiance and the dynamics of sunlitand shaded leaves can accurately represent photosynthesis in theseforests. Also, stomatal conductance formulations that only take intoaccount atmospheric demand fail to correctly simulate moisture andCO₂ fluxes in forests with a pronounced dry season, particularlyduring afternoon conditions. Nevertheless, it is also the case thatlarge uncertainties are associated not only with the eddy correlationdata, but also with the estimates of ecosystem respiration requiredfor model validation. To accurately simulate Gross PrimaryProductivity (GPP) and energy partitioning the most criticalparameters and model processes are the quantum yield of photosyntheticuptake, the maximum carboxylation capacity of Rubisco, and simulationof stomatal conductance.Using this model-data synergy, we developed scaling functions toprovide estimates of canopy photosynthetic parameters for a range ofdiverse forests across the Amazon region, utilising the best fittedparameter for maximum carboxylation capacity of Rubisco, and foliarnutrients (N and P) for all sites.