Patterns of energy exchange for tropical ecosystems across a climate gradient in Mato Grosso, Brazil

Abstract The spatial and temporal variations in the partitioning of energy into latent (LE) and sensible (H) heat flux for tropical ecosystems are not yet fully understood. In the state of Mato Grosso State, Brazil, there are three different ecosystems (Cerrado, Pantanal and the Amazon Rainforest) with distributions that vary across rainfall and humidity gradients. Our goal was to analyze the seasonal variation in microclimate, spectral reflectance, LE and H for these ecosystems and quantify how energy partitioning varies across the regional climate gradient. We used the Bowen ratio energy balance method to estimate the LE and H of a dense, evergreen ombrophylous forest near Alta Floresta (AFL), a semi-deciduous forest in the Amazon-Cerrado transition zone near Sinop (SIN), a savanna grassland at Fazenda Miranda (FMI), a managed savanna pasture at Fazenda Experimental (FEX), a seasonally flooded woodland at Baia das Pedras in the Pantanal (BPE), and a riparian forest dominated by Vochysia divergens Pohl (CAM) in the Pantanal. Annual rainfall decreased from north to south, and 83% of the annual rainfall occurred during the wet season. However, the seasonal amplitude of volumetric soil water content (VSWC) increased from north to south, because of the increased potential for seasonal flooding. The vapor pressure deficit (VPD), air temperature, solar radiation ( R g ) and net radiation ( R n ) also increased from north to south, which directly affected the seasonal amplitude in the enhanced vegetation index (EVI). Our data suggest that energy partitioning in the wettest sites (AFL and CAM) were driven by solar radiation instead of soil water availability, while seasonal variation in rainfall was more important for the Amazon-Cerrado transitional forest (SIN), Cerrado (FMI and FEX) and Pantanal scrublands (BPE). These patterns are discernable using appropriate satellite vegetation indices, such as the EVI, allowing spatial and temporal variations in energy partitioning to be quantified across diverse landscapes like the Amazon Basin.

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