Atmospheric processes and climate are closely linked to the carbon cycle in the Amazon region as a consequence of the strong biosphere-atmosphere coupling. The radiative effects of aerosols and clouds are still unknown for a wide variety of species and types of vegetation present in Amazonian biomes. This study examines the effects of atmospheric aerosols on solar radiation and their effects on Net Ecosystem Exchange (NEE) in an area of semideciduous tropical forest in the North of Mato Grosso State. Our results show a reduction of assimilation in the NEE with a considerable loss with the decrease of incident solar radiation of 40% and relative irradiance between 1.10-0.67. An average increase of 35-70% in net CO2 assimilation was observed for pollution levels (Aerosol Optical Depth) above 1.25. The increase of 35-70% in the NEE was attributed to the increase of up to 60% in the diffuse fraction of Photosynthetically Active Radiation, concerning its direct fraction. These results were mainly attributable to the Biomass Burning Organic Aerosols from fires over the area studied. Important influences on temperature and relative humidity of air, induced by the interaction between solar radiation and high aerosol load in the observation area, were also observed; an average cooling of 3.0 °C and 10%, respectively. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in CO2 flux can be occurring over large areas of the Amazon, with important effects on the potential for CO2 absorption on ecosystems of semideciduous forests distributed in the region.

Estimates of net primary (NPP) and ecosystem production (NEP) are needed for tropical savanna, which is structurally diverse but understudied compared to tropical rainforest. Estimates of NPP and NEP are available from eddy covariance and inventory methods, but both approaches have errors and uncertainties. We used both methods to estimate carbon (C) fluxes for an upland mixed grassland and a seasonally flooded forest to determine the correspondence in C cycling components derived from these methods and assess the contribution of the various C cycling components to the overall NEP. Both techniques provided similar estimates of NPP, NEP, and gross primary production (GPP). Belowground NPP accounted for 49-53% of the total NPP for both ecosystems, followed by aboveground litter (26-27%) and wood (16-17%) production. Increases in water availability increased the potential for C storage, but the mechanism was different in the savanna types with an increase in soil moisture causing higher NPP in the mixed grassland but lower ecosystem respiration (Reco) in the Cerrado forest. Compared to other savanna ecosystems, the mixed grassland had a similar rate of Reco but lower productivity and C use efficiency (CUE = NPP/GPP = 0.28). The Cerrado forest had a high CUE (0.58) and similar C flux rates to other tropical savanna forests and woodlands. While our measurements are spatially and temporally limited, the agreement in C fluxes estimated using inventory and eddy covariance methods suggest that the C cycle estimates for these savanna ecosystems are robust.

Since the Brazilian Cerrado has been heavily impacted by agricultural activities over the last four to five decades, reference evapotranspiration (ETo) plays a pivotal role in water resources management for irrigation agriculture. The Penman-Monteith (PM) is one of the most accepted models for ETo estimation, but it requires many inputs that are not commonly available. Therefore, assessing the FAO guidelines to compute ETo when meteorological data are missing could lead to a better understanding of how climatic variables are related to water requirements and atmospheric demands for a grass-mixed savanna region and which variable impacts the estimates the most. In this study, ETo was computed from April 2010 to August 2019. We tested twelve different scenarios considering radiation, relative humidity, and/or wind speed as missing climatic data using guidelines given by FAO. When wind speed and/or relative humidity data were the only missing data, the PM method showed the lowest errors in the ETo estimates and correlation coefficient (r) and Willmott’s index of agreement (d) values close to 1.0. When radiation data were missing, computed ETo was overestimated compared to the benchmark. FAO procedures to estimate the net radiation presented good results during the wet season; however, during the dry season, their results were overestimated, especially because the method could not estimate negative Rn. Therefore, we can infer that radiation data have the highest impact on ETo for our study area and also regions with similar conditions and FAO guidelines are not suitable when radiation data are missing.