Modeling gross primary production of a tropical semi-deciduous forest in the southern Amazon Basin

Background/Question/Methods: Semi-deciduous forest in the Amazon Basin is sensitive to temporal variation in surface water availability that can limit seasonal rates of leaf and canopy gas exchange.  We estimated seasonal dynamics of gross primary production (GPP) over 3 years (2005-2008) using eddy covariance and assessed canopy spectral reflectance using satellite imagery for a mature tropical semi-deciduous forest located near Sinop, Mato Grosso, Brazil. A light use efficiency model, known as the vegetation photosynthesis model (VPM), was used to quantify how GPP varied over seasonal and interannual time-scales as a function of rainfall and micrometeorology.

Results/Conclusions: Our results indicate that the standard VPM model was incapable of reproducing the seasonal variation in GPP, primarily because the model overestimated dry-season GPP. In the standard model, the scalar function that alters light use efficiency (e_g) as a function of water availability (W_scalar) is calculated as a linear function of the Land Surface Water Index (LSWI) derived from MODIS; however, the LSWI is negatively correlated with several measures of water availability including precipitation, soil water content, and relative humidity (RH). Thus, during the dry season, when rainfall, soil water content, and RH are low, LSWI, and therefore, W_scalar, are at a seasonal maximum. Using previous research, we derived new functions for W_scalar based on time series of RH and photosynthetic photon flux density (PPFD) that significantly improved the performance of the VPM. Whether these new functions perform equally well in water stressed and unstressed tropical forests needs to be determined, but presumably unstressed ecosystems would have high cloud cover and humidity, which would minimize variations in W_scalar and GPP to spatial and/or temporal variation in water availability.