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Soil mineralogy and texture are directly related to soil carbon due to the physical properties of the clay surface. Traditional techniques for quantifying carbon in soil are time-consuming and expensive, making large-scale quantification for mapping unfeasible. The alternative is the use of soil sensors, such as diffuse reflectance spectroscopy (DRS), an economical, fast, and accurate technique for predicting carbon stocks. In this sense, this study aimed to (a) investigate the relationship of C with different soil mineralogical, chemical, and physical attributes for different geological and geomorphological compartments; (b) understand which spectral bands are most important for estimating C content; (c) estimate C content from diffuse reflectance spectroscopy using different mathematical techniques and indicate which one is the best for tropical soil conditions; and (d) map C contents in detail. The study area was the Western Plateau of São Paulo (WPSP), which covers approximately 13 million hectares (~ 48% of the State of São Paulo, Brazil). A total of 265 samples were collected in this area. The attributes clay, silt, sand, crystalline and non-crystalline iron, base saturation, soil density, total pore volume, total C, C stock, kaolinite/(kaolinite + gibbsite) and hematite/(hematite + goethite), hematite and goethite contents, and spectral curves were evaluated. The spectra were recorded at 0.5-nm intervals, with an integration time of 2.43 nm s-1 over the 350 to 2500-nm range (350-800 nm-visible-VIS and 801-2500 nm-near-infrared-NIR). The data were subjected to descriptive statistics, Spearman correlation, stepwise analysis, and cluster grouping for characterization purposes; partial least squares regression (PLSR) and random forest (RF) for estimation purposes; and geostatistics analysis for creation of spatial maps. Our results indicate that the highest C contents are associated with more clayey soils, oxidic mineralogy, higher total pore volume, and lower soil density in highly dissected basalt compartments. The random forest algorithm associated with the Vis-NIR spectral range is more efficient for estimating and mapping C contents. This suggests that integrating diffuse reflectance spectroscopy with machine learning techniques holds promise for shaping public policies related to land use, mitigating CO2 emissions, and facilitating the implementation of carbon credit policies in a rapid and economically efficient manner.

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The conversion of native vegetation to agricultural areas leads to a natural process of carbon loss but these systems can stabilize in terms of carbon dynamics depending on the management and conversion time, presenting potential to both store and stabilize this carbon in the soil, resulting in lower soil respiration rates. In this context, this study aimed to investigate the effect of converting native Cerrado forest areas to agricultural systems with a forest planted with Eucalyptus camaldulensis and silvopastoral systems on the dynamics of CO2 emission and carbon stock at different soil depths. The experimental sites are located in the Midwest of Brazil, in the coordinates 20°22'31″ S and 51°24'12″ W. Were evaluated soil CO2 emission (FCO2), soil organic carbon, the degree of humification of soil organic matter (HLIFS), soil temperature, soil moisture, and soil chemical and physical attributes. The soil of the area is classified as an Oxisol (Haplic Acrustox). Soil samples were collected at depths of 0.00-0.10, 0.10-0.20, 0.20-0.30, and 0.30-0.40 m. The lowest FCO2 values were found in the silvopastoral system (1.05 µmol m-2 s-1), followed by the native forest (1.65 µmol m-2 s-1) and the eucalyptus system (1.96 µmol m-2 s-1), indicating a 36% reduction in FCO2 compared to the conversion of the native forest to the silvopastoral system and an increase of 19% when converting the native forest to the eucalyptus system. The soil chemical attributes (N, K+, Ca2+, H++Al3+, CEC, and organic carbon) showed a decrease along the profile. The shallowest depths (0.00-0.10 and 0.10-0.20 m) presented no differences between systems but the subsequent depths (0.20-0.30 and 0.30-0.40 m) had a difference (95% confidence interval), relative to N, Ca2+, H++Al3, CEC, and organic carbon stock (OCS), and the soil under silvopastoral system showed a higher concentration of these attributes than the native forest. The multivariate analysis showed that the eucalyptus and silvopastoral systems did not differ from the forest in the shallowest soil layer but differed from each other. This behavior changed from the second assessed depth (0.10-0.20 m), in which the silvopastoral system stands out, differing both from the eucalyptus system and from the native forest, and this behavior is maintained at the following depths (0.20-0.30 and 0.30-0.40 m). OCS, H++Al3, CEC, and nitrogen are strongly related to land use change for silvopastoral system. Regarding the behavior/relationship of attributes as a function of depth, the silvopastoral system contributed to soil carbon accumulation and stability over consecutive years.

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Abstract Objective: to analyze the psychosocial impacts of the COVID-19 pandemic among Brazilian women from rural settlements. Method: this is a quantitative and longitudinal study conducted with 13 settled women. The data were collected between January 2020 and September 2021 using questionnaires on the perception of the social environment (quality of life, social support, self-efficacy), common mental disorder symptoms and sociodemographic aspects. The data were analyzed using descriptive statistics, cluster analysis and variance analysis. Results: intersecting vulnerability conditions were identified that possibly intensified the challenges arising from the pandemic. The Quality of Life physical domain fluctuated differently and inversely according to the mental disorder symptoms. As for the psychological domain, at the end of the segment, an increase over time was identified in the entire sample, as the women's perception was better than before the pandemic. Conclusion: worsening of the participants' physical health deserves to be highlighted and, probably, it can be related to the difficulty accessing health services in this period as well as to the fear of contamination. Despite this, the participants were emotionally resilient throughout the period, including signs of improvement in terms of psychological aspects, suggesting a possible effect of the community organization of the settlement.

Resumo Objetivo: analisar os impactos psicossociais da pandemia de COVID-19 entre mulheres brasileiras de assentamentos rurais. Método: trata-se de um estudo quantitativo longitudinal com 13 mulheres assentadas. Os dados foram coletados entre janeiro de 2020 e setembro de 2021 utilizando questionários sobre a percepção do ambiente social (qualidade de vida, apoio social, autoeficácia), sintomas de transtorno mental comum e aspectos sociodemográficos. Os dados foram analisados por meio de estatística descritiva, análise de agrupamento e de variância. Resultados: foram identificadas condições de vulnerabilidade interseccionadas que, possivelmente, exacerbaram os desafios decorrentes da pandemia. O domínio físico da qualidade de vida oscilou diferentemente e inversamente de acordo com os sintomas de transtorno mental. Quanto ao domínio psicológico, no final do segmento, identificou-se em toda a amostra um incremento ao longo do tempo, pois a percepção das mulheres estava melhor do que antes da pandemia. Conclusão: a piora na saúde física das participantes merece destaque e, provavelmente, pode estar relacionada à dificuldade de acesso aos serviços de saúde neste período bem como ao medo da contaminação. Apesar disso, as participantes apresentaram-se emocionalmente resilientes em todo o período, inclusive, com sinais de melhora em relação aos aspectos psicológicos, sugerindo um possível efeito da organização comunitária do assentamento.

Resumen Objetivo: analizar los impactos psicosociales de la pandemia de COVID-19 en mujeres brasileñas de asentamientos rurales. Método: se trata de un estudio longitudinal cuantitativo con 13 mujeres asentadas. Los datos se recolectaron entre enero de 2020 y septiembre de 2021 mediante cuestionarios sobre percepción del entorno social (calidad de vida, apoyo social, autoeficacia), síntomas de trastorno mental común y aspectos sociodemográficos. Los datos se analizaron mediante estadística descriptiva, análisis de conglomerados y análisis de varianza. Resultados: se identificaron condiciones de vulnerabilidad entrelazadas que posiblemente exacerbaron los desafíos impuestos por la pandemia. El dominio físico de la calidad de vida fluctuó de manera diferente e inversa de acuerdo a los síntomas del trastorno mental. En cuanto al dominio psicológico, al final del segmento, se identificó un aumento en el tiempo en toda la muestra, dado que la percepción de las mujeres era mejor que antes de la pandemia. Conclusión: hay que destacar el empeoramiento de la salud física de las participantes que, probablemente, puede estar relacionado con la dificultad para acceder a los servicios de salud durante ese período y el miedo al contagio. A pesar de eso, las participantes fueron resilientes emocionalmente durante todo el período e, inclusive, tuvieron signos de mejoría en los aspectos psicológicos, lo que sugiere un posible efecto de la organización comunitaria del asentamiento.

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The knowledge of the lithological context is necessary to interpret trace elements concentrations in the soil. Soil magnetic signature (χ) and soil X-ray fluorescence (XRF) are promising approaches in the study of the spatial variability of trace elements and the environmental monitoring of soil quality. This research aimed to assess the efficiency of measurements of χ and XRF sensors for spatial characterization of zinc (Zn), manganese (Mn), and copper (Cu) contents in soils of a sandstone-basalt transitional environment, using machine learning modeling. The studied area consisted of the Western Plateau of São Paulo (WPSP), with soils originating from sandstone and basalt. A total of 253 soil samples were collected at a depth of 0.0-0.2 m. The soils were characterized by particle size and chemical analysis: organic matter (OM), cation exchange capacity (CEC), ammonium oxalate-extracted iron (Feo), sodium dithionite-citrate-bicarbonate-extracted iron (Fed), and sulfuric acid-extracted iron (Fet). Hematite (Hm), goethite (Gt), kaolinite (Kt), and gibbsite (Gb) contents were obtained by X-ray diffraction (XRD). Magnetite (Mt) and maghemite (Mh) contents were obtained by soil χ, while trace elements contents were obtained by XRF and predicted by χ. Descriptive analysis, the test of means, and correlation were performed between attributes. Zn, Mn, and Cu contents were predicted using the machine learning algorithm random forest, and the spatial variability was obtained using the ordinary kriging interpolation technique. Landscape dissections influenced iron oxides, which had the highest contents in slightly dissected environments. Trace elements contents were not influenced by landscape dissections, demonstrating that lithological knowledge is necessary to characterize trace elements in soils. The prediction models developed through the machine learning algorithm random forest showed that χ can be used to characterize trace elements. The similar spatial pattern of trace elements obtained by XRF and χ measurements confirm the applicability of these sensors for mapping it under lithological and landscape transition, aiming for sustainable strategic planning of land use and occupation.

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OBJECTIVE: to analyze the psychosocial impacts of the COVID-19 pandemic among Brazilian women from rural settlements. METHOD: this is a quantitative and longitudinal study conducted with 13 settled women. The data were collected between January 2020 and September 2021 using questionnaires on the perception of the social environment (quality of life, social support, self-efficacy), common mental disorder symptoms and sociodemographic aspects. The data were analyzed using descriptive statistics, cluster analysis and variance analysis. RESULTS: intersecting vulnerability conditions were identified that possibly intensified the challenges arising from the pandemic. The Quality of Life physical domain fluctuated differently and inversely according to the mental disorder symptoms. As for the psychological domain, at the end of the segment, an increase over time was identified in the entire sample, as the women's perception was better than before the pandemic. CONCLUSION: worsening of the participants' physical health deserves to be highlighted and, probably, it can be related to the difficulty accessing health services in this period as well as to the fear of contamination. Despite this, the participants were emotionally resilient throughout the period, including signs of improvement in terms of psychological aspects, suggesting a possible effect of the community organization of the settlement.

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There is a growing need of sustainable solutions for balancing agricultural production with the reduction of its environmental impacts. The rapid increase in sugarcane cultivation and the progressive conversion of pre-harvest burning (BH) to green harvest (GH) have brought into debate the contribution of agricultural sector to the greenhouse gas (GHG) mitigation. This study focused on the estimated GHG emission from sugarcane cultivation during years in which sugarcane areas in southern Brazil expanded and passed throughout an important transition, from 2006 to 2012, when harvest adopted was changed from burned to not-burned based. Sugarcane management and harvest were mapped through visual interpretation of Landsat-type satellite images, and the areas under sugarcane cultivation were distinguished according to each agricultural phase and harvest regime (i.e., manual harvest with burning vs. green mechanized harvest). Based on a broad data review and applying the IPCC (2006) methodologies, the results were expressed in terms of kilograms of carbon dioxide equivalent (kg CO2eq ha-1). Avoiding burn prior to harvest, even during expansion of sugarcane areas, promoted a mean reduction of GHG emission from 901 to 686 kg CO2eq ha-1 relative to harvest phase (24% lower) and an increase from 1418.3 to 1507.9 kg CO2eq ha-1 related to the ratoon maintenance phase (6% higher). Analyzing the total GHG emission per unit of cultivated sugarcane area (hectare), it was observed a decrease from 2275 to 2034 kg CO2eq ha-1 (11% reduction). The gradual transition of pre-harvest burning on that period has contributed to the reduction of GHG emission associated with sugarcane production being an important step towards GHG mitigation while still providing more sustainable sugar and ethanol production in southern Brazil.

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The spatial structure of soil CO2 emission (FCO2) and soil attributes are affected by different factors in a highly complex way. In this context, this study aimed to characterize the spatial variability patterns of FCO2 and soil physical, chemical, and microbiological attributes in a sugarcane field area after reform activities. The study was conducted in an Oxisol with the measurement of FCO2, soil temperature (Ts), and soil moisture (Ms) in a regular 90 × 90-m grid with 100 sampling points. Soil samples were collected at each sampling point at a depth of 0-0.20 m to determine soil physical (density, macroporosity, and microporosity), particle size (sand, silt, and clay), and chemical attributes (soil organic matter, pH, P, K, Ca, Mg, Al, H + Al, cation exchange capacity, and base saturation). Geostatistical analyses were performed to assess the spatial variability and map soil attributes. Two regions (R1 and R2) with contrasting emission values were identified after mapping FCO2. The abundance of bacterial 16S rRNA, pmoA, and nifH genes, determined by real-time quantitative PCR (qPCR), enzymatic activity (dehydrogenase, urease, cellulase, and amylase), and microbial biomass carbon were determined in R1 and R2. The mean values of FCO2 (2.91 µmol m-2 s-1), Ts (22.6 °C), and Ms (16.9%) over the 28-day period were similar to those observed in studies also conducted under Oxisols in sugarcane areas and conventional soil tillage. The spatial pattern of FCO2 was similar to that of macropores, air-filled pore space, silt content, soil organic matter, and soil carbon decay constant. No significant difference was observed between R1 and R2 for the copy number of bacterial 16S rRNA and nifH genes, but the results of qPCR for the pmoA gene presented differences (p < 0.01) between regions. The region R1, with the highest FCO2 (2.9 to 4.2 µmol m-2 s-1), showed higher enzymatic activity of dehydrogenase (33.02 µg TPF g-1 dry soil 24 h-1), urease (41.15 µg NH4-N g-1 dry soil 3 h-1), amylase (73.84 µg glucose g-1 dry soil 24 h-1), and microbial biomass carbon (41.35 µg C g-1 soil) than R2, which had the lowest emission (1.9 to 2.7 µmol m-2 s-1). In addition, the soil C/N ratio was higher in R2 (15.43) than in R1 (12.18). The spatial pattern of FCO2 in R1 and R2 may not be directly related to the total amount of the microbial community (bacterial 16S rRNA) in the soil but to the specific function that these microorganisms play regarding soil carbon degradation (pmoA).