Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

Abstract

Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm) and quantum yield (a) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapour pressure deficit are the key constraints for 18% and 27% of the simulations respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0:89).
\nWe investigated further the seasonal variation of ecosystem-scale parameters derived with LAIF . Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen.