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Arid and semi-arid environments correspond to one-third of the Earths terrestrial surface. In these environments, precipitation is an essential and limiting element for vegetation growth and ecosystem biomass productivity. The semi-arid region of Brazil comprises around 11.5% of the national territory, where the Caatinga biome originally composed ~ 76% of this area, with water deficit as a prominent feature, annual rainfall lower than 800 mm, temperatures ranging between 25 and 30 °C, and potential evapotranspiration higher than 2000 mm/year. Research on the dynamics of mass and heat fluxes through techniques such as eddy covariance (EC) has contributed to estimate the magnitude and seasonal patterns of turbulent exchanges between ecosystems and the atmosphere. This study was conducted in an area of dense Caatinga (DC) and another of sparse Caatinga (SC) from 2013 to 2014. It was observed that albedo (α) and net radiation (Rn) were higher in the SC compared with DC since the magnitude of incoming shortwave radiation was higher in this area. It was found that most of the Rn is converted to sensible heat flux (H), mainly during the dry period in the SC, about 50% for H and 20% for λE. The energy balance closure showed that the turbulent fluxes (H + λE) were underestimated in comparison to the available energy at the surface (Rn − G). We also observed that this discrepancy was higher in the DC area, corresponding to ~ 30%.

Deforestation is a threat to biodiversity and the worlds climate. As agriculture and mining areas grow, forest loss becomes unbearable for the environment. Consequently, monitoring deforestation is crucial for decision makers to create polices. The most reliable deforestation data about the Amazon forest is generated by the Brazils National Institute for Space Research (INPE) through its PRODES project. This effort is labor and time intensive because it depends on visual interpretation from experts. Additionally, frequent Amazons atmospheric phenomena, such as clouds, difficult image analysis which induces alternative approaches such as time series analysis. One way to increase the number of images of an area consists of using images from different satellites. NASA provides the Harmonized Landsat and Sentinel-2 (HLS) dataset solving spectral dissimilarities of satellite sensors. In this paper, the possibilities of HLS for forest monitoring are explored by applying two deforestation detection methods, Break Detection for Additive Season and Trend (BFAST) monitor and Random Forest, over four different vegetation indices, NDVI, EVI, GEMI and SAVI. The SAVI index used as input for BFAST monitor performed the best in this data setup with 95.23% for deforested pixel, 53.69% for non-deforested pixels. Although the HLS data is described as analysis ready, further pre-processing can enhance the outcome of the analysis. Especially, since the cloud and cirrus cover in the Amazon causes gaps in the dataset, a best pixel method is recommended to create patched images and thus a continuous time series as input for any land cover and land use classification.

Atmospheric flask samples are either collected at atmospheric pressure by opening a valve of a pre-evacuated flask or pressurized with the help of a pump to a few bar above ambient pressure. Under humid conditions, there is a risk that water vapor in the sample leads to condensation on the walls of the flask, notably at higher than ambient sampling pressures. Liquid water in sample flasks is known to affect the C2 mixing ratios and also alters the isotopic composition of oxygen (O-17 and O-18) in CO2 via isotopic equilibration. Hence, for accurate determination of CO2 mole fractions and its stable isotopic composition, it is vital to dry the air samples to a sufficiently low dew point before they are pressurized in flasks to avoid condensation. Moreover, the drying system itself should not influence the mixing ratio and the isotopic composition of CO2 or that of the other constituents under study. For the Airborne Stable Isotopes of Carbon from the Amazon (ASICA) project focusing on accurate measurements of CO2 and its singly substituted stable isotopologues over the Amazon, an airdrying system capable of removing water vapor from air sampled at a dew point lower than -2 degrees C, flow rates up to 12 L min(-1) and without the need for electrical power was needed. Since to date no commercial air-drying device that meets these requirements has been available, we designed and built our own consumable-free, power-free and portable drying system based on multitube Nafion (TM) gas sample driers (Perma Pure, Lakewood, USA). The required dry purge air is provided by feeding the exhaust flow of the flask sampling system through a dry molecular sieve (type 3A) cartridge. In this study we describe the systematic evaluation of our NafionTm-based air sample dryer with emphasis on its performance concerning the measurements of atmospheric CO2 mole fractions and the three singly substituted isotopologues of CO2 ((OCO)-O-16-C-13-O-16, (OCO)-O-16-C-12-O-17 and (OCO)-O-16-C-12-O-18) as well as the trace gas species CH4, CO, N2O and SF6. Experimental results simulating extreme tropical conditions (saturated air at 33 degrees C) indicated that the response of the air dryer is almost instantaneous and that approximately 85L of air, containing up to 4 % water vapor, can be processed staying below a -2 degrees C dew point temperature (at 275 kPa). We estimated that at least eight flasks can be sampled (at an overpressure of 275 kPa) with a water vapor content below -2 degrees C dew point temperature during a typical flight sampling up to 5 km altitude over the Amazon, whereas the remaining samples would stay well below 5 degrees C dew point temperature (at 275 kPa). The performance of the air dryer on measurements of CO2, CH4, CO, N2O, and SF6 and the CO2 isotopologues (OOO)-O-16-O-13-O-16 and (OCO)-O-16-C-12-O-18 was tested in the laboratory sim- ulating real sampling conditions by compressing humidified air from a calibrated cylinder, after being dried by the air dryer, into sample flasks. We found that the mole fraction and the isotopic composition difference between the different test conditions (including the dryer) and the base condition (dry air, without dryer) remained well within or very close to, in the case of N2O, the World Meteorological Organization recommended compatibility goals for independent measurement programs, proving that the test condition induced no significant bias on the sample measurements.

The large amount of carbon stored in trees and soils of the Amazon rain forest is under pressure from land use as well as climate change. Therefore, various efforts to monitor greenhouse gas exchange between the Amazon forest and the atmosphere are now ongoing, including regular vertical profile (surface to 4.5 km) greenhouse gas measurements across the Amazon. These profile measurements can be used to calculate fluxes to and from the rain forest to the atmosphere at large spatial scales by considering the enhancement or depletion relative to the mole fraction of air entering the Amazon basin from the Atlantic, providing an important diagnostic of the state, changes and sensitivities of the forests. Previous studies have estimated greenhouse gas mole fractions of incoming air (‘background’) as a weighted mean of mole fractions measured at two background sites, Barbados (Northern Hemisphere) and Ascension (Southern hemisphere) in the Tropical Atlantic, where the weights were based on sulphur hexafluoride (SF6) measured locally (in the Amazon vertical profiles) and at the two background sites. However, this method requires the accuracy and precision of SF6 measurements to be significantly better than 0.1 parts per trillion (picomole mole-1), which is near the limit for the best SF6 measurements and assumes that there are no SF6 sources in the Amazon basin. We therefore present here an alternative method. Instead of using SF6, we use the geographical position of each air-mass back-trajectory when it intersects the limit connecting these two sites to estimate contributions from Barbados versus Ascension. We furthermore extend the approach to include an observation site further south, Cape Point, South Africa. We evaluate our method using CO2 vertical profile measurements at a coastal site in Brazil comparing with values obtained using this method where we find a high correlation (r2 = 0.77). Similarly, we obtain good agreement for CO2 background when comparing our results with those based on SF6, for the period 2010-2011 when the SF6 measurements had excellent precision and accuracy. We also found high correspondence between the methods for background values of CO, N2O and CH4. Finally, flux estimates based on our new method agree well with the CO2 flux estimates for 2010 and 2011 estimated using the SF6-based method. Together, our findings suggest that our trajectory-based method is a robust new way to derive background air concentrations for the purpose of greenhouse gas flux estimation using vertical profile data.

The use of matrix by species that naturally inhabit forest fragments can be an important instrument to restore connectivity in fragmented landscapes. The type and structure of the matrix are determinant for this connectivity, however, few studies have explored this theme. In this study, we evaluated the community of small mammals within forest remnants and within two types of matrices (coffee plantation and pasture). In all, 11 species of small mammals were captured, being Akodon montensis, Oligoryzomys nigripes and Calomys cerqueirai the most abundant in fragments, coffee plantation and pasture, respectively. The results show that the composition and structure of the community in the two matrix types are distinct from those found in fragments, and the coffee plantation matrix has greater abundance and greater richness of small mammals than the pasture matrix.

The main objective of this study is to assess the ability of several high-resolution satellite-based precipitation estimates to represent the Precipitation Diurnal Cycle (PDC) over Brazil during the 20142018 period, after the launch of the Global Precipitation Measurement satellite (GPM). The selected algorithms are the Global Satellite Mapping of Precipitation (GSMaP), The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Climate Prediction Center (CPC) MORPHing technique (CMORPH). Hourly rain gauge data from different national and regional networks were used as the reference dataset after going through rigid quality control tests. All datasets were interpolated to a common 0.1◦ × 0.1◦ grid every 3 h for comparison. After a hierarchical cluster analysis, seven regions with different PDC characteristics (amplitude and phase) were selected for this study. The main results of this research could be summarized as follow: (i) Those regions where thermal heating produce deep convective clouds, the PDC is better represented by all algorithms (in term of amplitude and phase) than those regions driven by shallow convection or low-level circulation; (ii) the GSMaP suite (GSMaP-Gauge (G) and GSMaP-Motion Vector Kalman (MVK)), in general terms, outperforms the rest of the algorithms with lower bias and less dispersion. In this case, the gauge-adjusted version improves the satellite-only retrievals of the same algorithm suggesting that daily gauge-analysis is useful to reduce the bias in a sub-daily scale; (iii) IMERG suite (IMERG-Late (L) and IMERG-Final (F)) overestimates rainfall for almost all times and all the regions, while the satellite-only version provide better results than the final version; (iv) CMORPH has the better performance for a transitional regime between a coastal land-sea breeze and a continental amazonian regime. Further research should be performed to understand how shallow clouds processes and convective/stratiform classification is performed in each algorithm to improve the representativity of diurnal cycle.

Brazilian agricultural production provides a significant fraction of the food consumed globally, with the country among the top exporters of soybeans, sugar, and beef. However, current advances in Brazilian agriculture can be directly impacted by climate change and resulting biophysical effects. Here, we quantify these impacts until 2050 using GLOBIOM-Brazil, a global partial equilibrium model of the competition for land use between agriculture, forestry, and bioenergy that includes various refinements reflecting Brazil’s specificities. For the first time, projections of future agricultural areas and production are based on future crop yields provided by two Global Gridded Crop Models (EPIC and LPJmL). The climate change forcing is included through changes in climatic variables projected by five Global Climate Models in two emission pathways (RCP2.6 and RCP8.5) participating in the ISIMIP initiative. This ensemble of twenty scenarios permits accessing the robustness of the results. When compared to the baseline scenario, GLOBIOM-Brazil scenarios suggest a decrease in soybeans and corn production, mainly in the Matopiba region in the Northern Cerrado, and southward displacement of agricultural production to near-subtropical and subtropical regions of the Cerrado and the Atlantic Forest biomes.

Desertification is a global problem that impacts a significative part of the Earth’s surface, which cause a large environmental and social losses in several regions of the world. The Brazilian semiarid region, located mainly in the northeast part of the country, includes areas of moderate to very high susceptibility to desertification. In order to contribute to a comprehension of the dimensions of desertification in the Brazilian semiarid region, this paper aimed to develop a potential indicator for the evaluation and monitoring of this area, considering an appropriate temporal and spatial scales. For this objective, satellite data were used for the identification and monitoring of sub-areas potentially undergoing degradation/desertification. Thus multitemporal series of Enhanced Vegetation Index 2 (EVI2) covering the period between 2000 and 2016 was used, which were calculated from data provided by the MODIS sensor carried aboard the Terra satellite. Besides, previous samples were selected for the calibration and validation of the methodology. The results show an increase of areas potentially undergoing degradation/desertification, covering an area equal to 167,814.24 km2 at the end of the period analyzed (around 16.7% of the study area). Approximately 23.63% of the total degraded area comprises both the Very High Degradation Trajectory and High Degradation Trajectory. The proposed methodology contributed to the determination of the degree of the degradation through the determination of Degradation Trajectories, which differentiates it from the ones proposed in other studies; however, it is emphasized that this approach must be analyzed in association with additional information, such as trends and climatic scenarios of land use and land cover, as well as retrospective analyses of the landscape, soil erosion, field recognition, socioeconomic conditions, among others.

O objetivo deste estudo foi avaliar a produção e decomposição de serapilheira em uma área de floresta primária de terra firme na Reserva Biológica do Jaru. Para tanto, foi implantada uma parcela permanente de 1 hectare, onde foram demarcadas 25 subparcelas com 20 x 20 m cada. Para a coleta de serapilheira, instalou-se 25 coletores de PVC (1 em cada centro da subparcela), medindo 0,25 m², a 1 metro do solo, com malha de nylon de 1 mm. Para estimar o estoque de serapilheira, utilizou-se 25 coletores de madeira, medindo 0,25 m², com malha de nylon de 1 mm, dispostos no solo de cada subparcela. As coletas da pesquisa foram realizadas quinzenalmente, entre os meses de outubro de 2016 a setembro de 2017, e a serapilheira triada nas frações: folha, galho, material reprodutivo e miscelânea. No laboratório, os materiais amostrados foram secos em estufa à 80 ºC e pesados em balança de precisão centesimal, sendo que a decomposição de serapilheira foi estimada através da relação entre produção e estoque. De acordo com os resultados obtidos, a produção de serapilheira total foi de 14,13 Mg ha-1 e as frações seguiram o padrão: folha>miscelânea>galho>material reprodutivo. As maiores produções aconteceram na estação seca e a taxa de decomposição foi 1,37, indicando que a atividade microbiana na área de estudo é acelerada.

Examples of how environmental susceptibility has a direct impact on the social vulnerability of a population, by affecting both the social and cultural life quality are discussed for the Northeast of Brazil, which is considered to be the poorest region of the country. Several direct and indirect mechanisms associated to soil degradation/ desertification are addressed, mainly in relation to the impact they cause to the livelihood such as income, immigration/emigration rate, and mortality. Our purpose is to provide, based on a social vulnerability index, a spatial-temporal analysis of the population dynamics in response to the effects of degradation/desertification and extended periods of drought. The results of this study demonstrated that social vulnerability is mostly dictated by social factors but marginally by environmental factors. This conclusion has an impact on federal public policies designed to reduce social inequality in the region.

The present work aimed to analyze the simulations of surface fluxes of sensible and latent heat, and global radiation using the mesoscale atmospheric model (WRF) for the Bananal Island (Tocantins state, Brazil) region during three distinct seasonal periods (flooded, dry, and wet) in 2004. The final analysis of the NCEP global model was used as initial and boundary conditions of the WRF, which horizontal resolution (5 km) and physical parameterizations follow the operational settings used at CPTEC/INPE. The global radiation, the simulated sensible and latent heat fluxes were consistent with the observed data for the daily cycle, where the R2 was higher than 0.8, showing a good correlation between the data. However, the WRF outputs overestimates/underestimates follow a distinct seasonal pattern between global radiation and heat fluxes. There are some hypotheses for this result, such as potential limitations of the model in describing the surface conditions, whether static or dynamic. Future studies may investigate how sensitive the WRF would be when updating surface conditions for scenarios closer to reality, especially the flooded surface situation.

Tropical secondary forests (SF) play an important role in the global carbon cycle as a major terrestrial carbon sink. Here, we use high‐resolution TerraClass data set for tracking land use activities in the Brazilian Amazon from 20042014 to detect spatial patterns and carbon sequestration dynamics of secondary forests (SF). By integrating satellite lidar and radar observations, we found the SF area in the Brazilian Amazon increased from approximately 22 Mha (106 ha) in 2004 to 28 Mha in 2014. However, the expansion in area was also accompanied by a dynamic land use activity that resulted in about 50% recycling of SF area annually from frequent clearing and abandonment. Consequently, the average age of SF remained less than 10 years (age ~8.2 with one standard deviation of 3.2 spatially) over the period of the study. Estimation of changes of carbon stocks shows that SF accumulates approximately 8.5 Mg ha−1 year−1 aboveground biomass during the first 10 years after clearing and abandonment, 4.5 Mg ha−1 year−1 for the next 10 years followed by a more gradual increase of 3 Mg ha−1 year−1 from 20 to 30 years with much slower rate thereafter. The effective carbon uptake of SF in Brazilian Amazon was negligible (0.06 ± 0.03 PgC year−1 ) during this period, but the interannual variability was significantly larger (±0.2 PgC year−1 ). If the SF areas were left to grow without further clearing for 100 years, it would absorb about 0.14 PgC year−1 from the atmosphere, partially compensating the emissions from current rate of deforestation in the Brazilian Amazon.