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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.

O presente trabalho propõe relacionar os temas de sociedade, tecnologias espaciais e meio ambiente através de estudo de caso de problemas ambientais brasileiros, orientado pelo uso de técnicas de imageamento feito por satélites. Este estudo, que teve início no Curso de Inverno de Introdução às Tecnologias Espaciais de 2019 ministrado pelo INPE (Instituto Nacional de Pesquisas Espaciais), e procurou integrar os temas acima com os 17 Objetivos de Desenvolvimento Sustentável (ODS) da ONU. A utilização de tecnologias espaciais, desta forma, foi proposta como método para o estudo de problemas ambientais nas cidades, de modo a explorar o planejamento urbano de maneira sustentável e inteligente. O estudo de caso foi realizado em cinco cidades brasileiras representando cada macrorregião do país e seus problemas característicos, tais como saneamento básico e de alagamentos. Através da utilização de ferramentas permitidas pelo sensoriamento realizado por satélites, bem como o Sistema de Informação Geográfica (GIS), foi possível caracterizar as cidades quanto aos seus problemas escolhidos e propor soluções práticas de planejamento urbano. Como um modo de organizar tais propostas, finalmente, foi criado o conceito de um Sistema Integrado de Meio Ambiente e Desenvolvimento Urbano (SIMADU), que agiria com o papel de unificar as técnicas de análise de planejamento urbano com tecnologia satelital.

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.

O conhecimento do balanço de radiação ondas longas (BOL) é importante para determinação das trocas energéticas que ocorrem no sistema superfície-atmosfera. Assim, neste trabalho avaliou-se a variabilidade estacional do BOL numa área de Mata Atlântica, através da análise da influência de diferentes variáveis meteorológicas, discutindo suas possíveis causas. A pesquisa foi realizada numa Reserva Particular do Patrimônio Natural (RPPN) no município de Coruripe-AL. As medições foram feitas por um saldo radiômetro (CNR1, Kipp e Zonen) instalado acima do dossel florestal numa torre micrometeorológica de 26 metros de altura durante os períodos de 03.11.2016 a 31.12.2016 (estação seca) e 01.05.2017 a 30.06.2017 (estação chuvosa). O BOL variou em 101,63% da estação chuvosa para a seca (-11,6 W m-2 a -23,39 W.m-2) em dias nublados e 30,33% (-49,19 W.m-2 a -64,11 W.m-2) em dias claros. A radiação de onda longa atmosférica (Ra) média no período chuvoso foi 430,96 W.m-2 e 418,90 W.m-2 no seco, enquanto a radiação terrestre (Rs) foi 456,46 W.m-2 (chuvoso) e 470,60 W.m-2 (seco). Rs foi sempre maior que Ra e, por consequência, o BOL foi sempre negativo em ambas estações, com uma diferença média de 103,19% de uma estação para outra.

Known as a degenerative and progressive dementia, Alzheimers disease (AD) affects about 25 million elderly people around the world. This illness results in a decrease in the productivity of people and places limits on their daily lives. Electroencephalography (EEG), in which the electrical brain activity is recorded in the form of time series and analyzed using signal processing techniques, is a well-known neurophysiological AD biomarker. EEG is noninvasive, low-cost, has a high temporal resolution, and provides valuable information about brain dynamics in AD. Here, we present an original approach based on the use of quantile graphs (QGs) for classifying EEG data. QGs map frequency, amplitude, and correlation characteristics of a time series (such as the EEG data of an AD patient) into the topological features of a network. The five topological network metrics used hereclustering coefficient, mean jump length, betweenness centrality, modularity, and Laplacian Estrada indexshowed that the QG model can distinguish healthy subjects from AD patients, with open or closed eyes. The QG method also indicates which channels (corresponding to 19 different locations on the patients scalp) provide the best discriminating power. Furthermore, the joint analysis of delta, theta, alpha, and beta wave results indicate that all AD patients under study display clear symptoms of the disease and may have it in its late stage, a diagnosis known a priori and supported by our study. Results presented here attest to the usefulness of the QG method in analyzing complex, nonlinear signals such as those generated from AD patients by EEGs.

The Amazon forest plays an important role in regulating the local, regional and global climate, due to the high potential for absorbing carbon in its biomass and transferring large amounts of water from the land surface to the atmosphere through evapotranspiration. Despite the several studies that have explored the mechanisms of seasonal vegetation control, a small number of them have focused on flooded forests. In the Amazon basin, it corresponds to c.a. 14% of the basin. This study was performed in a floodplain forest located at the transition area between the Amazon and Cerrado (Savana) biomes, near the Bananal (BAN) Island region seeking to understand the mechanisms of vegetation control during the dry and flooded periods. The seasonality of gross primary productivity (GPP) and evapotranspiration (ET) from eddy covariance measurements were assessed, along with environmental drivers and phenological patterns, obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)). ET measurements presented many gaps, and a statistical model (the Generalized Additive Model – GAM) was used to reconstruct the records from 2004 to 2017, using the ERA5 reanalysis climate data. Moreover, the remote sensing product (MOD16A2) was acquired to analyze the reliability of this product in describing seasonal ET. The long-term change on the hydrological pattern at the BAN region was analyzed through the Gravity Recovery and Climate Experiment (GRACE) satellite product. The results revealed that Gross primary production is limited by soil moisture during the flooded period due to the excess water, while GPP is positively associated with soil moisture during non-flooded months. Besides, GPP is maximized when the accumulated water deficit (CWD) increases, indicating that it depends on the amount of water input in the environment. EVI was positively associated with leaf litter mass and GPP, suggesting the synchrony between leaf production and the photosynthetic capacity of the canopy, decreasing at the peak of the flooded period and at the end of the dry season. The EVI was also able to describe the interannual variations of the canopy in relation to environmental factors, such as during the extreme drought of the El Niño year (2015/2016). The main ET drivers were identified during the model calibration process, which are: vapour pressure deficit, radiation and soil moisture. The seasonal ecosystem productivity and evapotranspiration are not synchronized in this Southern Amazon forest during the flooded period, because the free water evaporation mainly drives ET. However, during non-flooded months ET is governed by forest transpiration, as indicated by the association with the carbon, phenological and meteorological seasonal patterns. The flood pulse regulates the soil volume water content, and consequently, the water availability for plants during non-flooded months. These findings highlighted the vulnerability of this forest facing extreme dry years, given the decreased flood pulse trend reported here, which consequently diminished the total water storage in this region during 2016, assessed through GRACE product. The Amazon forest plays an important role in regulating the local, regional and global climate, due to the high potential for absorbing carbon in its biomass and transferring large amounts of water from the land surface to the atmosphere through evapotranspiration. Despite the several studies that have explored the mechanisms of seasonal vegetation control, a small number of them have focused on flooded forests. In the Amazon basin, it corresponds to c.a. 14% of the basin. This study was performed in a floodplain forest located at the transition area between the Amazon and Cerrado (Savana) biomes, near the Bananal (BAN) Island region seeking to understand the mechanisms of vegetation control during the dry and flooded periods. The seasonality of gross primary productivity (GPP) and evapotranspiration (ET) from eddy covariance measurements were assessed, along with environmental drivers and phenological patterns, obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)). ET measurements presented many gaps, and a statistical model (the Generalized Additive Model – GAM) was used to reconstruct the records from 2004 to 2017, using the ERA5 reanalysis climate data. Moreover, the remote sensing product (MOD16A2) was acquired to analyze the reliability of this product in describing seasonal ET. The long-term change on the hydrological pattern at the BAN region was analyzed through the Gravity Recovery and Climate Experiment (GRACE) satellite product. The results revealed that Gross primary production is limited by soil moisture during the flooded period due to the excess water, while GPP is positively associated with soil moisture during non-flooded months. Besides, GPP is maximized when the accumulated water deficit (CWD) increases, indicating that it depends on the amount of water input in the environment. EVI was positively associated with leaf litter mass and GPP, suggesting the synchrony between leaf production and the photosynthetic capacity of the canopy, decreasing at the peak of the flooded period and at the end of the dry season. The EVI was also able to describe the interannual variations of the canopy in relation to environmental factors, such as during the extreme drought of the El Niño year (2015/2016). The main ET drivers were identified during the model calibration process, which are: vapour pressure deficit, radiation and soil moisture. The seasonal ecosystem productivity and evapotranspiration are not synchronized in this Southern Amazon forest during the flooded period, because the free water evaporation mainly drives ET. However, during non-flooded months ET is governed by forest transpiration, as indicated by the association with the carbon, phenological and meteorological seasonal patterns. The flood pulse regulates the soil volume water content, and consequently, the water availability for plants during non-flooded months. These findings highlighted the vulnerability of this forest facing extreme dry years, given the decreased flood pulse trend reported here, which consequently diminished the total water storage in this region during 2016, assessed through GRACE product.