Seasonal variation in net carbon exchange and evapotranspiration in a Brazilian rain forest: A modelling analysis

Abstract

Tropical rain forests account for a significant fraction of global net primary productivity, and are important latent energy (LE) sources, affecting extra-tropical atmospheric circulation. The influence of environmental factors on these fluxes has until recently been poorly understood, largely due to a paucity of data, but in recent years the amount of available data has been increased greatly by use of eddy covariance techniques. In this paper we examine the factors that control daily and seasonal carbon (C) and LE fluxes, by comparing a detailed model of the soil-plant-atmosphere continuum against a unique long-term data-set collected using eddy covariance at an undisturbed rain forest site north of Manaus, Brazil. Our initial application of the model was parametrized with simple measurements of canopy structure, and driven with local meteorological data. It made effective predictions of C and LE exchange during the wet season, but dry season predictions were overestimates in both cases. Sensitivity analyses indicated that the best explanation for this behaviour was a seasonal change in soil and root hydraulic resistances (R(b)). An optimization routine was then used to estimate the increase in R(b) during the dry season that would be required to explain the reduced dry season fluxes. The local soil, a clay latosol, is typical of much of Amazonia, having very low available water and low hydraulic conductivity. We conclude that an increase in soil-root hydraulic resistance in the dry season introduces a significant seasonal cycle to carbon and water fluxes from this tropical forest. Furthermore, our model structure appears to be an effective tool for regional and temporal scaling of C and LE fluxes, with primary data requirements being regional and temporal information on meteorology, leaf area index (LAB, foliar N, critical leaf water potentials, and plant and soil hydraulic characteristics.