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Understanding the variability of soil CO 2 emission across several land use and cover (LULC) classes and biomes and its relationship with climate variables is important to drive strategies that contribute to meeting local and international demands for sustainable development and low carbon agriculture. The hypothesis of this research is that soil CO 2 emission in situ (FCO 2) is variable between LULCs across different biomes and that there may be an association between soil CO 2 flux and environmental variables such as temperature and soil moisture. This study evaluated FCO 2 , measured by a portable EGM-5 CO 2 gas analyzer, CO 2 Flux model (obtained by remote sensing approach), soil moisture (SM), soil temperature (ST) and relationship between these variables in different LULC classes. We identified LULCs can contribute to carbon neutralization actions over the Cerrado, Atlantic Forest and Pantanal biomes located in State of Mato Grosso do Sul (MS), Brazil. Four LULC classes were evaluated in each biome: agriculture (soybean cultivation), pasture, eucalyptus plantation, and native vegetation. A principal component analysis (PCA) was performed to verify the relationship between biomes and LULC classes with the variables evaluated, and a Pearson correlation plot was created to assess the relationship between the variables evaluated. The lowest FCO 2 values were found in eucalyptus and soybean crops, regardless of biome. Our findings reveal the existence of soil CO 2 flux variability between the different LULCs and biomes. Pasture in Pantanal and Atlantic Forest biomes exhibited the highest FCO 2 values. Eucalyptus cultivation and native forest showed negative CO 2 Flux values, regardless of biome. Lower FCO 2 values were also observed for soybean cultivation. Such findings reinforce that native vegetation function as carbon sinks and that, therefore, their conservation is vital for the mitigation of CO 2 emissions. However, soybean and eucalyptus farming can be strategic for low carbon agriculture in MS and carbon neutralization projects by simultaneously contribute to economic and sustainable development of the regions covered by the biomes evaluated here. [Display omitted] • Multivariate analysis in understanding CO 2 soil emission. • Higher FCO 2 values were observed in pastures in the Pantanal and Atlantic Forest. • CO 2 absorptions were observed in eucalyptus and native forest áreas. [ABSTRACT FROM AUTHOR]

• Remotely sensed data in establishment of new boundary between biomes. • Land Use and Land Cover Change and the advance of the Cerrado biome on the edge of the Brazilian Amazonia. • Biophysical-atmospheric aspects altered with the anthropic advance and its influence on public environmental policies. The Amazonia is the largest tropical forest in the world, with approximately 5 million km2 occupying about 49.3% of Brazil in the North and Central-West regions and bordering the Cerrado sensu lato (Brazilian savannah). The border area between these two biomes is called the Cerrado-Amazonia transition that extends approximately 6240 km. Currently, these limits, as well as other areas of ecotonal stress, are not clearly defined mainly due to intense Land Use and Land Cover Change (LULCC). Remote sensing is a tool that tries to define and update these limits. In this context, the objective of this study was to use remote sensing tools to determine the transition between the two large Brazilian biomes. The study area comprised the transition between the Cerrado-Amazonia biomes in Brazil and an area composed of a buffer of 300 km was created around the official line of the abovementioned biomes. We used data from some remote sensors to calculate the composition of the previous year's pixel means for the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) (-1˜1), CO 2 Flux (μmol m−2 s-1), evaporative efficiency (mm yr-1), and Gross Primary Production (GPP) (g C m−2 d−1) variables. The statistical analyses were performed by softening the pixels of all the variables by means of the Kernel density (KD). Later, the analysis of the main components and the cluster between the biomes and the remote sensing variables were applied. Therefore, we sought to standardize the results and to find an overall mean between the standards to delimit a new area of the Amazonia and Cerrado biomes, called the Transition Area between Biomes (TAB). The variables analyzed by remote sensing were effective for identifying the Amazonia and Cerrado biomes characteristics that highlighted the evaporative efficiency variable in relation to other variables in both biomes. Thus, from the results achieved, a new boundary was determined that delimits the transition of the biomes that is different than the official government boundary. The analyses used in this study constitute important tools to foment the creation of public policies able to curb the anthropic actions on these biomes. [ABSTRACT FROM AUTHOR]

Highlights • Genetic correlations of low to moderate magnitude were observed between harvests. • Multiple-trait BLUP / Additive Index procedure allowed for the genetic selection. • This procedure can be efficiently applied on Jatropha curcas breeding. Abstract Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas , mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas. [ABSTRACT FROM AUTHOR]

The failure of the Fundão Dam in Mariana, more precisely in the subdistrict of Bento Rodrigues, state of Minas Gerais (Brazil) on November 5th, 2015, is considered to be "the biggest environmental tragedy in the country's history." About thirty-four million cubic meters of tailings were dumped into the river where, another 16 million continued to reach the Atlantic ocean. This disaster seriously affected the flora, fauna, economic activities and people's lives, including the loss of human lives. Remote sensing allows mapping the variability of terrain properties, such as vegetation, water and geology, both in space and time, offering a synoptic view and useful environmental information in future decision making. In this way, this research aims to analyze the impacts of the failure of the Fundão Dam in the municipality of Mariana-MG on the vegetation cover, by means of remote sensing techniques and analysis of digital processing of orbital optical images. In order to analyze the soil cover, Unmixing Espectral Linear Model (UELM) was used in order to separate soil, shade and vegetation classes. Subsequently, Artificial Neural Network (ANN) classification method was applied, followed by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). The results showed a loss of 13.02% of the vegetation, about 1289 ha, and a reduction of 68.57% of shade (water), approximately 1347 ha. The UELM showed to be effective in the separation of each image-fraction, being an important stage for the success of the classification. The EVI was the index that best described the vegetation deficit in the affected areas spilling the sludge from waste. [ABSTRACT FROM AUTHOR]

• Classification of eucalyptus species based on their growth using the K-means method. • Obtaining eucalyptus vegetation indexes (VI) using Unmanned Aerial Vehicles. • Selection of the best VI features for classification of eucalyptus using ANOVA statistical test. • Recognition of eucalyptus in relation to its growth using machine learning methods and VI features. Growth and production models can help to simulate the growth of tree dimensions to predict forest productivity at different levels. In this context, the following questions arise: (i) is it possible to recognize the growth pattern of eucalyptus species based on spectral features using machine learning (ML) for data modeling? (ii) what spectral features provides better accuracy? and (iii) what ML algorithms are most accurate for performing this modeling? To answer these questions, the present study evaluated the use of ML techniques using breast height and total plant height to classify the growth of five species of eucalyptus and Corymbria citriodora in an unsupervised learning, and the obtained classes for induce ML algorithms to recognize the species with relation to their growth using vegetation indices (VIs) and spectral bands (SBs). It were evaluated five eucalyptus species (E. camaldulensis , E. uroplylla, E. saligna , E. grandis e E. urograndis) and C. citriodora in experimental design of randomized blocks with four replicates, with 20 plants inside each experimental plot. The diameter at breast height and total plant height at stand level were obtained by measuring five trees in each experimental unit in seven measurements. During this same period, a flight was carried out using a remotely piloted aircraft for the acquisition of spectral variables (SBs and VIs). For recognition of eucalyptus species in relation to their growth two machine learning approaches were employed: supervised and unsupervised. The average accuracy obtained from 10-fold cross-validation, employing Random Forest algorithm and 24 features, was 0.76. This result shows that the proposed approach is appropriate to recognize different eucalyptus species based on their growth. [ABSTRACT FROM AUTHOR]

The Brazilian Legal Amazon is an extensive territory (5,088,668.25 km2) in which different factors (environmental and social) influence the fire dynamics of the region. This study aims to explain the seasonal patterns of meteorological variables, fire, land use, and carbon emissions and their inter-relationships, focusing on years of El Niño–Southern Oscillation (ENSO) occurrence. For this purpose, we used data from fire foci and burned area obtained by the Moderate Resolution Imaging Spectroradiometer sensor and meteorological variables from Reanalysis 2. The kernel density was applied to the fire foci, and Spearman correlation coefficient between the foci and the other variables (fire foci, burned area, carbon emissions, evapotranspiration, wind speed, relative air humidity, rainfall, soil moisture, maximum temperature, minimum temperature, and mean air temperature) and Mann Kendall test for soybean, corn and sugarcane crops were performed. The years considered as La Niña were those with the highest fire foci, burned area, and carbon emissions. Our results show that even in periods considered as low fire risk, forests may be vulnerable to fires due to interaction with other variables. Furthermore, we found a tendency to increase the area planted with soybean, maize, and sugarcane, which may lead to more deforested areas in the region if there is no support from public policies. The uncertainty of the Legal Amazon's behavior towards climate change, combined with possible setbacks in Brazilian environmental policy due to the current government, highlights the importance of studies that encompass several factors such as this one. Flowchart of the stages developed, where: 1. ENSO phenomenon (Time series), 2. Remote Sensing and Weather data, 3. Land use and cover, 4. Carbon emission, 5. Fire foci and synoptic events, 6. Statistical analysis. [Display omitted] • The La Niña years were the ones that presented the greatest number of fire foci, burned area, and carbon emissions. • This understanding can make fire planning and control more effective by governmental and non-governmental agencies. • Even in periods considered to be of low fire risk, forests can be vulnerable to fires for other reasons. • Uncertainties regarding the behavior of the Amazon in the face of global warming increases the need for studies. • Public policies in the short term in the Amazon must be adopted to control deforestation and forest fires. [ABSTRACT FROM AUTHOR]

• Real-time monitoring of boron fertilization in eucalyptus is helpful for guiding precision diagnosis; • The 350–371 nm spectral range can be used for detecting boron-deficient plants; • Adequate boron levels can be identified by using the 426–444, 1811–1910, 1948–2115, and 2124–2208 nm; • The 425–475 nm spectral range can be used to find boron-toxicity plants. Boron (B) is an essential element whose deficiency results in rapid inhibition in the growth of plants, acting on their meristematic growth. Real-time monitoring of B fertilization in eucalyptus is helpful for guiding precision diagnosis and efficient management of plant boron nutrition. This research hypothesizes that different boron levels alter the reflectance of different wavelengths in eucalyptus. In this context, the objective of this study was to identify spectral ranges that can be used to monitor the boron status in eucalyptus plants. The experiment was carried out in a greenhouse, in which the treatments consisted of increasing boron levels in the form of boric acid (17% of B), whose levels varied from deficit to toxicity. Thus, five treatments were established: no boron, 1, 10, 20, and 40 mg/dm3 of boron. The remote sensing data used were bands, heights, and vegetation indices calculated after obtaining the spectral curves in each treatment. Our findings show that it is possible to accurately distinguish the boron levels in eucalyptus using hyper and multispectral bands. The 350–371 nm spectral range can be used for detecting boron-deficient plants. Plants with adequate boron levels can be identified by using the 426–444 nm, 1811–1910 nm, 1948–2115 nm, and 2124–2208 nm spectral ranges. Finally, the 425–475 nm spectral range can be used to find boron-toxicity plants. [ABSTRACT FROM AUTHOR]

• We found that the air temperature has a high influence on E. urophylla. • The water use and aridity index has influence on E. grandis × E. camaldulensis. • The vessel wall thickness is the connection between climate and wood. • The soil water deficit presented connection on rainfall exclusion for eucalyptus. The intensity of climate changes demands studies on the adaptability of the most planted eucalyptus genetic materials in the world, such as E. urophylla and E. grandis × E. camaldulensis which were evaluated in this study. The objective of this work was to evaluate wood traits and to relate it to the meteorological variables for each year of growth of the trees that grew in four sites with different climatic conditions and 33% rainfall exclusion. The wood traits evaluated were: wood density, vessel density, diameter and area, vessel wall thickness, total vessel wall thickness between adjacent cells, theoretical hydraulic conductivity, potential hydraulic conductivity, lumen conductivity area, vessel composition within space, vessel implosion resistance and vulnerability index to drought. Pearson's correlations between the evaluated variables were estimated and the results expressed graphically through the correlation network. Multiple regression analysis with adjustment by the Exhaustive Search method was used to estimate the vessel wall thickness in order to isolate this characteristic and identify the explanation intensity of the meteorological variables. Pearson's correlations between meteorological factors and wood traits show different interactions in the behavior of the clones and in the water availability conditions. Air temperature was present in all the vessel wall thickness estimation equations. The 33% rainfall exclusion provided the best equation adjustments with meteorological variables, explaining up to 84% of the variation in the vessel wall thickness. The rainfall exclusion intensified the effects of the interrelations between climate and hydraulic architecture in E. grandis × E. camaldulensis , with implosion resistance and vessel wall thickness having a strong relationship between climate and wood. The results of rain reduction in the dynamics between wood and climate have implications for indirect selection in breeding programs. [ABSTRACT FROM AUTHOR]

Cotton has high production costs compared to other annual crops because large numbers of plant protection product (PPP) applications can be needed to control insect pests, diseases, and growth. The hypothesis underlying this study was that vegetation indices (VIs) could be used to estimate application rates for cotton. Our objectives were to (i) evaluate the relationship between different VIs and the application rates for cotton; (ii) propose a modification to the canopy chlorophyll content index (CCCI); and (iii) to develop a VI based equation that will indicate the ideal application rate needed to maximize deposition in the middle layer of a cotton crop. The experiments were carried out during the crop seasons 2017/18, and 2018/19 in the State of Mato Grosso do Sul, Brazil. A multispectral sensor installed in an unmanned aerial vehicle (UAV) was used to obtain the VIs, and the application rates evaluated were 40, 70, 100, and 130 L ha−1. The spray deposits on cotton leaves were measured using the mass balance analysis method. Our findings revealed that an increase in the VIs led to a rise in the application rate needed to maintain spray deposition on the middle layer of cotton plants. The CCCI is related to the rate variation in the cotton crop. However, our results showed that the proposed modified equation (the simplified modified canopy chlorophyll content index), which is based on the relative deposition, improves the estimation of the application rate that will optimize spray deposition in the middle layer of cotton plants. [ABSTRACT FROM AUTHOR]

• Forest recomposition to carbon sequestration in degraded areas. • A major challenge of foresters is to restore forest cover in degraded areas. • The adoption of mixed plantations allows obtaining of services and products. • The species used in mixed planting present different growth patterns. A major challenge for the forestry sector is to restore forest cover in degraded areas. In this regard, the adoption of mixed plantations is an opportunity to combine the obtaining of services and products from the forest, providing ecological and socioeconomic advantages. Thus, our objective was to evaluate the growth of native forest species in mixed plantations in Brazilian Savanna. The study was carried out in an area of 4.8 ha with about thirty species planted in spacing 3 × 3 m, located in Chapadão do Sul/MS. At 6.4 years after planting, in 15 randomized plots of 300 m2, the diameter at 1.3 m above ground (DBH), equivalent diameter (DBHeq), total height (H), number of stems (NSI), wood volume (V), biomass (B), carbon (C), and carbon sequestration (CO 2) of the trees were measured. Descriptive statistics of the variables were carried out by using boxplot diagrams and principal component analysis (PCA) to group the species according to their growth. The stocks of V and B were 114.03 m3 ha−1 and 52.99 Mg ha−1, respectively. Thus, the mixed planting of native forest species is efficient for recomposing deforested areas, especially as regards biomass accumulation and carbon stock. The species used in mixed planting present different growth form, which were separated by PCA into four groups. DBHeq was the variable that most influenced the differentiation of species into groups. The species Heliocarpus popayanensis, Croton floribundus, Guazuma ulmifolia, Senegalia polyphylla, Enterolobium contortisiliquum, Anadenanthera colubrina, Ceiba speciosa, Anadenanthera peregrina, Gallesia integrifolia and Peltophorum dubium showed the highest growth in the study area. [ABSTRACT FROM AUTHOR]

Brazil has the largest commercial beef cattle stock on Earth, and most of the cattle produced in the country is bred and finished on pastures. The cattle ranching sector represents a significant source of the country's greenhouse gas (GHG) emissions. Agricultural intensification has been highlighted as one of the main strategies in reaching global food security and reducing deforestation. The Sudden Death Disease (SDD) of pastures, which affects the most planted cultivar of Urochloa brizantha , is degrading pastures in the Amazon, contributing to low production yields and high emission rates. This paper discusses the intensification of pasture production systems and SDD, to examine the potential for pasture renovation to address livestock productivity and GHG balance, emissions and potential sinks. Does SDD represent a blessing or a curse to climate change mitigation in the Brazilian Amazon? A collection of pasture samples were assessed to measure wet and dry weight in areas with and without SDD, which were related to remote sensing data to provide an overall estimate of the total area affected by the SDD in Alta Floresta, a municipal county of southern Brazilian Amazonia. We found that 77.1% of all pastures had been committed to the syndrome, which has forced farmers to renew their pastures. This also has great potential in increasing soil carbon stocks, effectively reducing the CO 2 footprint of meat production in those areas. Therefore, we firmly believe that SDD management has provided an opportunity to rebalance the emissions/sequestration equation associated with meat production by the cattle ranching sector in this Amazonin frontier. • Livestock is the main driver of deforestation in the Brazilian Amazon. • The Sudden Death Disease (SDD) affects Brazilian pastures. • SDD has promoted the overall reduction in the greenhouse gas emissions. • Digital images of orbital sensors are able to detect pasture problems. [ABSTRACT FROM AUTHOR]

• Indigenous lands account for 23% of Amazonian forests in Brazil. • Brazilian government policies threaten forests and resources for their protection. • Illegal activities such as mining, logging and soybeans are allowed by indigenous people. • The liberation of exploitation by the capital of wealth in these territories will compromise biodiversity and climate. The Indigenous Lands in Brazil today resemble a steam locomotive, where the government and the indigenous add wood to the boiler and the conservationists push the brakes. Arranged on the rails and along the way of this locomotive are more than 100 million hectares of the largest tropical forest on the planet. In this article we evaluate the advance of soybean cultivation and fire foci in indigenous lands using remote sensing and discuss the possible effects of a liberation of the economic exploitation in these territories intended by the Brazilian government and requested by the indigenous people themselves. We present that even with the prohibition of economic exploitation on indigenous lands, there are large concentrations of fires in those territories which undermine public policies in Brazil, both in maintaining biodiversity as the assumed climate agreements. [ABSTRACT FROM AUTHOR]

• Natural regeneration recovers biomass stocks. • Silvicultural systems influences aerial biomass. • Forest fires reduces biomas of fire-sensitive species. The Brazilian Cerrado is the second largest biome in Brazil, and its natural landscapes have undergone transformations, due in large part to anthropic activities. However, little is known about the effects of these activities on the natural regeneration of Cerrado vegetation. Thus, the objective of this study was to evaluate the accumulation of woody biomass in an area of a Cerrado sensu stricto that was monitored for 27 years after the implementation of six silvicultural systems. A period of 17 years was sufficient for the woody community of the Cerrado sensu stricto to naturally recover its original stock of aerial biomass after the application of silvicultural systems. A Few woody species contribute to the total aerial biomass accumulated over time, and such contribution is variable with time and with the type of silvicultural system. At 27 years after cutting, the largest fraction of biomass accumulated in the area were represented by the species Miconia leucocarpa , Blepharocalyx salicifolius , Schefflera macrocarpa , Qualea grandiflora , Dalbergia miscolobium , Eriotheca pubescens , Qualea parviflora and Caryocar Brasiliense , which also demonstrated higher fire resistance. A period of 17 years after the implementation of silvicultural systems is considered sufficient for an area to recover naturally to the original stock of woody biomass at the community level. This result causes a greater reduction in the biomass of fire-sensitive species and transforms a Cerrado from a carbon sink into a source of CO 2 emissions to the atmosphere. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate fire dynamics in 'extreme' climatic events of the El Niño Southern Oscillation in the western Amazon in Acre, Brazil. It employed remote sensing products of burned areas, the Enhanced Vegetation Index (EVI), rainfall products, and kernel density to spatialise fire foci. The largest burned area recorded during the study was during the La Niña period, with a total of 296 km2 burned. The highest concentration of fire foci was found in the lowland open ombrophilous forest in areas with palm trees, where 28% of the fires occurred. Rainfall was concentrated on the cover of the submontane dense ombrophilous forests with emergent canopies with a maximum value of 2515.9 mm in the La Niña event. The highest and lowest EVI values occurred in the neutral episode with values ranging from 0.57 to 0.36. The correlation between burned and fire foci areas was greatest during the El Nino period (0.92). On the other hand, the maximum negative value was found between the rainfall and fires in the neutral episode (−0.80). Fire outbreaks and EVI presented a significant positive growth trend in the neutral episode. The largest fires were recorded during the neutral period, and this study highlights the vulnerability of the western Amazon to fire. [ABSTRACT FROM AUTHOR]

Despite its numerous important traits for biodiesel production, little research exists on the Jatropha curcas crop, mainly with respect to repeated measures over time (crop years). The present study was thus developed to evaluate repeated measures over time in Jatropha curcas and examine the applicability and efficiency of the harmonic mean of the relative performance of genetic values (HMRPGV) method in the selection of families for yield, stability, and adaptability, simultaneously. The work involved data from the evaluation of 730 individuals of 73 half-sib families, in a complete randomized block design, during six crop years, for the trait grain yield. Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was performed to estimate the variance components and predict the genetic values. Ten crop years must be evaluated to obtain 80% of the maximum coefficient of determination and 90% accuracy in terms of genetic gain from selection. The efficiency of performing 10 measurements compared with the situation in which only one measurement is used was 67%. The HMRPGV method has great potential in the selection of Jatropha curcas families for yield, stability, and adaptability, simultaneously. [ABSTRACT FROM AUTHOR]

Due to shortages of fossil fuels, and the worldwide concern approximately climate change and global warming, biofuels have become an important source of sustainable energy. Several species can be used to produce biofuels such as soybeans ( Glycine max ), oil palm ( Elaeis guineensis ), and Jatropha ( Jatropha curcas L.). Therefore, the objective of this paper was to integrate the information available in the literature and report the most promising strategies for genetic and biotechnological progress in Jatropha. Jatropha has become a potential crop to produce biofuel due to the high oil content found in the seeds, which can be transformed into biofuel. Jatropha has an average seed oil content of 35%, and the oil extracted from the seeds has 24.6% crude protein and 47.2% crude fat. Moreover, Jatropha has several agronomic morphological traits that make it a useful crop for biofuel production and animal feed, such as drought tolerance, rapid growth, and ease of propagation. It can be grown at almost any altitude, and plants can produce for more than 50 years. Additionally, Jatropha oil has good stability to oxidation, low viscosity, a low pour-point, which makes Jatropha oil better than soybean or palm oil. This paper presented an innovative and comprehensive literature review on all agronomic aspects of Jatropha, and the strategies that have been used to select superior genotypes for Jatropha breeding. Several important traits of Jatropha are affected by the environment and new strategies to select superior genotypes are required by breeders. Therefore, genomic wide selection associated with recurrent selection can be an appropriate strategy for Jatropha breeding. [ABSTRACT FROM AUTHOR]

Wildfires in the Amazon biome of Mato Grosso cause extensive environmental, economic, and health damages, including biodiversity loss and high greenhouse gas emissions. This study used remote sensing to examine the relationship between fire severity and climatic factors, focusing on dNBR (Differenced Normalized Burn Ratio), precipitation, LST (Land Surface Temperature), SPI (Standardized Precipitation Index), NDVI (Normalized Difference Vegetation Index), and VCI (Vegetation Condition Index), analyzing data from 2001 to 2022. Statistical tests included Shapiro-Wilk, Tukey, regression kriging, Mann-Kendall for trend analysis, Pettitt for change points, and canonical variable tests. Regarding trends, only LST showed a significant trend starting in 2009, with the Northeast mesoregion showing the highest impact on temperature. dNBR correlated positively with NDVI and VCI, and negatively with precipitation and SPI. The northern mesoregion had a positive influence on dNBR and NDVI but negative for precipitation, SPI, and VCI. The southwestern mesoregion associated positively with dNBR and LST but negatively with the other variables. The Northeast and South-Central mesoregions showed positive correlations with most variables except dNBR and NDVI. These findings highlight the northern mesoregion's vulnerability due to its proximity to the central Amazon Forest and agri-cultural activity, indicating increased fire susceptibility with reduced humidity. • The northeast mesoregion of the Mato Grosso Amazon had the greatest impact on temperature. • There is vulnerability in the northern mesoregion due to its proximity to the central rainforest and agricultural activity. • The main positive correlations for dNBR were with the variables NDVI and VCI. [ABSTRACT FROM AUTHOR]

Ecological Niche models (ENMs) are tools that allow us to approximate the area of suitability for a species, thereby allowing elaboration of conservation strategies. The validation of these models in situ is not always possible due to costly access remote areas where conserved species are often found. The goal of our study was to provide a new validation concept for ENMs by applying remote sensing (SR) techniques, such as Geographic Object-Based Image Analysis (GEOBIA), which enables mapping of large areas and provides detailed information on land use. To assess the GEOBIA validation technique, we selected the species Bertholletia excelsa (Brazil nut), a tree that has great importance as a non-timber forest product and is considered vulnerable by the International Union for Conservation of Nature (IUCN). Models were built on the ‘biomod2’ package, and evaluation was conducted using the area under the receiver operating characteristic curve (AUC) and True Skill Statistics (TSS) metrics. Images were obtained from the orbital Operational Land Imager (OLI) on board the Landsat-8 satellite and the thematic maps were evaluated using Kappa and Overall Accuracy Statistics. We calculated vegetation indices (EVI, SAVI, LAI, and NDVI) and applied them to the GEOBIA technique. A total of 693 possible sites of B. excelsa were detected. Of these, 25 accessible sites were used for validation, and 45 new records of B. excelsa were added in the study area. GEOBIA was demonstrated to have high potential for validating ENMs, as well as in the extraction of arboreal species from medium-resolution spatial images. [ABSTRACT FROM AUTHOR]

The Guarani Aquifer System is one of the largest freshwater reservoirs in the world and has been widely exploited due to the quantity and quality of the stored water. The outcropping areas are considered highly vulnerable, and anthropic interference can influence the recharge potential and cause changes in water quality. The purpose of this research was to spectrally and temporally analyze the anthropic interference in water production in the Guarani Aquifer in four distinct areas located in the outcrop and recharge areas located in the State of São Paulo, Brazil, from 2012 to 2018. Rainfall data were obtained using the CHIRPS dataset, and the actual evapotranspiration rate was obtained using the MODIS product. The lithology and piezometric level data were obtained through RIMAS of the Geological Service of Brazil. The piezometric level monitoring wells were used as a reference to delimit the study areas and the distance to eliminate overlapping spatial resolutions of the remote sensing products. The area bounded by the buffer is equivalent to 31,412 ha. The recharge was estimated with the ESPERE using the water table fluctuation method. The end classifications of land use were obtained using the normalized difference vegetation index through remote sensing data. The study area located in the municipality of Boa Esperança do Sul - SP had the largest area of exposed soil with a median of 2936 (ha) and the lowest recharge potential with a median of 338 mm/year. The study area located in the municipality of Bofete - SP had the smallest area of exposed soil with a median of 516 (ha) and the highest recharge potential with a median of 502 mm/year. The study area located in the municipality of Brotas - SP showed the lowest evapotranspiration rate, with a median of 639 mm/year. The municipality of São Simão - SP had the largest forest area, with a median of 18,009 ha. Although water resource policies have significantly influenced the valuation of groundwater, studies that assess changes in land use variables using time series analysis and evaluate how these changes influence water dynamics in the hydrological cycle are still lacking. The study aims to contribute technical support to the decision-making process of the National System of Water Resources Management (SINGREH) and State Law 9866/1997 to contribute to the sustainability of the Guarani Aquifer System. • Estimated recharge of the Guarani Aquifer with ESPERE. • Land use in the influence of aquifer recharge. • Spectral models in the distribution of rainfall and evapotranspiration and their influence on the aquifer. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) sources and sinks are an important global concern. Monitoring the spatiotemporal variations of GHG concentrations, particularly carbon dioxide (CO 2), is crucial for identifying potential sources and sinks and moving toward a sustainable future. Therefore, via a time-series of remote data and multispectral images, this study evaluates the CO 2 spatiotemporal dynamics and related factors during 2015–2018 in one of the world's main agricultural frontier areas, the state of Mato Grosso (SMT), Brazil, which is both experiencing continued deforestation and attempting to achieve sustainable food production. In this study, data was obtained from the measurement of column-averaged carbon dioxide (CO 2) dry air mole fraction in the atmosphere, set as X CO2 from Orbiting Carbon Observatory-2 satellite from January 2015 to December 2018. The enhanced vegetation index data were obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor, and rainfall data were obtained from the Climate Hazards Group InfraRed Precipitation with Station dataset. From a series of Landsat-8 satellite images, it was possible to distinguish land use and land cover classes and estimate the CO 2 flux in the SMT. The results showed that the temporal variability of CO 2 flux is correlated positively with rainfall, while X CO2 is negatively correlated with rainfall. Regarding spatial variability, we observed that forest areas that were converted to other land uses resulted in higher values that characterize with sources, and that the highest and lowest average concentrations of CO 2 occurred in the dry and rainy months, respectively, for X CO2 , which might be the result of differences in the vertical resolution of the CO 2 column and scale. In contrast, areas with large continuous forest areas tended to have lower values and contribute positively to the carbon balance as sinks, thereby mitigating climate change impacts. Therefore, not only X CO2 but also CO 2 flux are directly related to changes in land use and land cover (LULC) in complex systems that are affected by climatic variables and processes, such as photosynthesis and soil respiration. • X CO2 is inversely related to rainfall, with highest concentration in drier periods. • Human actions in land use and land cover change increase atmospherical CO 2. • Remote sensing to locate and understand the sources and sinks of carbon dioxide. [ABSTRACT FROM AUTHOR]

Fire is used in the management of pastures, renewal and expansion of areas, and agricultural activities in South America (SA). The objectives of this study were: i) to identify the countries and regions with the highest number of fire foci in SA, and ii) to evaluate the spatial dynamics of fire foci based on the Meteorological Fire Danger Index (MFDI) and future scenarios through numerical simulations. Fire foci time series comprised 21 years (1998–2018) from the BDQueimadas database. Cluster Analysis (CA), descriptive and exploratory statistics were employed. Fire foci maps for SA were made in 10-km pixel dimensions. MFDI was used to assess fire danger via SPEEDY (Simplified Parametrizations, primitivE-Equation DYnamics) model simulations. Three simulations were performed: control scenario (1980–2015), RCP2.6 scenario (optimistic - 2016 and 2050), and RCP8.5 scenario (pessimistic - 2015 and 2050). Regionally, three homogeneous groups of fire foci (G1, G2 and G3) and one atypical (NA - Not Grouped) were identified for Brazil via CA. The highest fire foci occurred in Brazil (62.72%), followed by Bolivia (9.03%), Argentina (8.28%), Venezuela (6.11%), Paraguay (5.94%), and Colombia (3.87%), respectively. The highest density of fire foci occurred in the MATOPIBA region, the confluence of Maranhão, Tocantins, Piauí, and Bahia, - (agricultural frontier), and also in the Cerrado-Amazon transition and the states of Mato Grosso and Mato Grosso do Sul in Brazil, followed by Paraguay, Bolivia, Venezuela, and Argentina. The countries and regions of Brazil do not change, only intensify from year to year, and such fire foci variability may be associated with the El Niño-Southern Oscillation (ENSO) phases. The control scenario identified in east-central Brazil, western Bolivia, Paraguay, and northern Argentina. The optimistic scenario showed an improvement in some countries and a worsening in the territorial distribution in Brazil, Venezuela, and Colombia. The pessimistic scenario identified increased degradation compared to the previous scenarios in almost all SA countries. • Brazil, Bolivia, Argentina, Venezuela, and Paraguay largest records of fire foci in South America. • Projections of future fire risk scenarios indicate central-eastern Brazil, Bolivia, Paraguay, and Argentina. • The integrated analysis identified land use and climatic variability as the main factors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Production factors and processing are associated to nutritional rice composition. • Cultivars and processing altere the physicochemical quality of the grains. • Fertilization levels enhance the nutritional quality of rice grains. • NIR, X-ray diffraction and SEM associated with qualitative rice diagnosis. • Cultivars and fertilizations management can assist in the rice milling industry. Cultivars and fertilization levels influence rice productivity and can be associated with grain quality. Thus, it is possible to make decisions regarding the choice of cultivars and application of fertilizer levels based on the type of milling, a necessary post-harvest process that may minimize the nutrient load in the grains and result in loss in quality. This study relates the physicochemical composition and morphological quality of brown and polished milled rice grains, cultivar types, and different levels of soil fertilization using near-infrared spectroscopy analysis, X-ray diffraction and scanning electron microscopy. Statistical tools were used to test the various treatments and identify the relationship between factors and variables. A high fertilization level is related to increasing crude protein composition and starch for cultivar IRGA 431 CL associated with polished rice. However, the combination of cultivar IRGA 424 RI and brown rice demonstrated a higher grain resistance, and different percentages of whole, chalky, and damaged rice. The correlation between ash × crude protein and starch × crude fiber was found to be positive for brown rice and negative for the polished rice. Further, an increase in starch content was inversely proportional to the ash content, whereas an increase in crude protein was inversely proportional to the low-fat content in milled rice. The crystalline characteristics of rice starch were preserved at high fertilization levels associated with polished grains that demonstrated high starch content. Polished grains, however, showed more pores and cavities, and consequently greater permeabilities in the surface. It is recommended that batches of grains produced from cultivar IRGA 431 CL with high levels of fertilization be subjected to polished rice milling to achieve high protein and starch quality. However, grains from cultivar IRGA 424 RI with high levels of fertilization are recommended for brown rice milling owing to the high percentage of physical defects observed. [ABSTRACT FROM AUTHOR]

• Paricá is a native species of Amazon used in the laminated wood industry. • Brazilian half-sib progenies of paricá has high genetic variability. • Combined selection strategy provides the greatest genetic gains for paricá. Paricá (Schizolobium parahyba var. amazonicum) is a tropical species native to the Amazon region and is continually growing for wood exploitation potential, especially in the laminated wood industry. In Brazil, there are still no breeding programs for this species. Therefore, it is necessary to assess its genetic diversity and use appropriate selection strategies to develop genotypes that serve the consumer market. This research hypothesized that half-sib families of paricá have genetic variability for characteristics favorable to wood production. Thus, the aim was to evaluate different selection strategies in paricá genotypes for growth traits. Half-sib progenies from 58 paricá matrices were planted in the experimental area of Embrapa Agrossilvipastoril in the municipality of Sinop-MT. The seeds used for obtaining the seedlings were collected in the states of Mato Grosso, Rondônia, Acre, Tocantins, and Pará. The traits evaluated were: diameter at breast height and plant height. Variance components and heritability were estimated, and subsequently, the genetic gains with the selection were predicted by four selection strategies: combined selection, among and within-families selection, mass selection, and stratified mass selection. The results obtained by analysis of variance showed the existence of genetic variability among families for the traits evaluated, which revealed the possibility of obtaining genetic gains and thereby success with the selection. All selection strategies showed to be suitable for obtaining genetic gains with a selection of the best paricá progenies aimed at wood production. However, the combined selection provided the highest genetic gains. The results reported in this research made it possible to direct the strategies of the first genetic breeding program for paricá in Brazil. [ABSTRACT FROM AUTHOR]