A Graphical User Interface for Parameterizing Biochemical Models of Photosynthesis and Chlorophyll Fluorescence

Abstract:

Recent advances in optical remote sensing of photosynthesis offer great promise for estimating gross primary productivity (GPP) at leaf, canopy and even global scale. These methods –including solar-induced chlorophyll fluorescence (SIF) emission, fluorescence spectra, and hyperspectral features such as the red edge and the photochemical reflectance index (PRI) – can be used to greatly enhance the predictive power of global circulation models (GCMs) by providing better constraints on GPP. The way to use measured optical data to parameterize existing models such as SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) is not trivial, however. We have therefore extended a biochemical model to include fluorescence and other parameters in a coupled treatment. To help parameterize the model, we then use nonlinear curve-fitting routines to determine the parameter set that enables model results to best fit leaf-level gas exchange and optical data measurements. To make the tool more accessible to all practitioners, we have further designed a graphical user interface (GUI) based front-end to allow researchers to analyze data with a minimum of effort while, at the same time, allowing them to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. Here we discuss the tool and its effectiveness, using recently-gathered leaf-level data.