Biomass production (BIO) and its anomalies were modeled using MODIS satellite images and gridded weather data to test an environmental monitoring system in the biomes Atlantic Forest (AF) and Caatinga (CT) within SEALBA, an agricultural growing region bordered by the states of Sergipe (SE), Alagoas (AL), and Bahia (BA), Northeast Brazil. Spatial and temporal variations on BIO between these biomes were strongly identified, with the annual long-term averages (2007–2023) for AF and CT of 78 ± 22 and 58 ± 17 kg ha−1 d−1, respectively. BIO anomalies were detected through its standardized indexes—STD (BIOSTD), comparing the results for the years from 2020 to 2023 with the long-term rates from 2007 to each of these years. The highest negative BIOSTD values were in 2023, but concentrated in CT, indicating periods with the lowest vegetation growth, regarding the long-term conditions from 2007 to 2023. The largest positive BIOSTD values were for the AF biome in 2022, evidencing the highest vegetative vigor in comparison with the long-term period 2007–2022. The proposed BIO monitoring system is important for environmental policies as they picture suitable periods and places for agricultural and forestry explorations, allowing sustainable managements under climate and land-use changes conditions, with possibilities for replication of the methods in other environmental conditions.

The persistence of coastal ecosystems is jeopardized by deforestation, conversion, and climate change, despite their capacity to store more carbon than terrestrial vegetation. The study’s objectives were to investigate how spatiotemporal changes impacted blue carbon storage and sequestration in the Satkhira coastal region of Bangladesh over the past three decades and, additionally to assess the monetary consequences of changing blue carbon sequestration. For analyzing the landscape change (LSC) patterns of the last three decades, considering 1992, 2007, and 2022, the LSC transformations were evaluated in the research area. Landsat 5 of 1992 and 2007, and Landsat 8 OLI-TIRS multitemporal satellite images of 2022 were acquired and the Geographical Information System (GIS), Remote Sensing (RS) techniques were applied for spatiotemporal analysis, interpreting and mapping the output. The spatiotemporal dynamics of carbon storage and sequestration of 1992, 2007, and 2022 were evaluated by the InVEST carbon model based on the present research years. The significant finding demonstrated that anthropogenic activity diminished vegetation cover, vegetation land decreased by 7.73% over the last three decades, and agriculture land converted to mariculture. 21.74% of mariculture land increased over the last 30 years, and agriculture land decreased by 12.71%. From 1992 to 2022, this constant LSC transformation significantly changed carbon storage, which went from 11,706.12 Mega gram (Mg) to 9168.03 Mg. In the past 30 years, 2538.09 Mg of carbon has been emitted into the atmosphere, with a combined market worth of almost 0.86 million USD. The findings may guide policymakers in establishing a coastal management strategy that will be beneficial for carbon storage and sequestration to balance socioeconomic growth and preserve numerous environmental services.

Mangrove forests are vital to coastal protection, biodiversity support, and climate regulation. In the Niger Delta, these ecosystems are increasingly threatened by oil spill incidents linked to intensive petroleum activities. This study investigates the extent of mangrove degradation between 1986 and 2022 in the lower Niger Delta, specifically the region between the San Bartolomeo and Imo Rivers, using remote sensing and machine learning. Landsat 5 TM (1986) and Landsat 8 OLI (2022) imagery were classified using the Support Vector Machine (SVM) algorithm. Classification accuracy was high, with overall accuracies of 98% (1986) and 99% (2022) and Kappa coefficients of 0.97 and 0.98. Healthy mangrove cover declined from 2804.37 km2 (58%) to 2509.18 km2 (52%), while degraded mangroves increased from 72.03 km2 (1%) to 327.35 km2 (7%), reflecting a 354.46% rise. Water bodies expanded by 101.17 km2 (5.61%), potentially due to dredging, erosion, and sea-level rise. Built-up areas declined from 131.85 km2 to 61.14 km2, possibly reflecting socio-environmental displacement. Statistical analyses, including Chi-square (χ2 = 1091.33, p < 0.001) and Kendall's Tau (τ = 1, p < 0.001), showed strong correlations between oil spills and mangrove degradation. From 2012 to 2022, over 21,914 barrels of oil were spilled, with only 38% recovered. Although paired t-tests and ANOVA results indicated no statistically significant changes at broad scales, localized ecological shifts remain severe. These findings highlight the urgent need for integrated environmental policies and restoration efforts to mitigate mangrove loss and enhance sustainability in the Niger Delta.

The use of geotechnologies combined with remote sensing has become increasingly essential and important for efficiently and economically understanding land use and land cover in specific regions. The objective of this study was to observe changes in agricultural activities, particularly agriculture/livestock farming, in the North Forest Zone of Pernambuco (Mata Norte), a political-administrative region where sugarcane cultivation has historically been the backbone of the local economy. The region's sugarcane biomass also contributes to land use and land cover observations through remote sensing techniques applied to digital satellite images, such as those from Landsat-8, which was used in this study. This study was conducted through digital image processing, allowing the calculation of the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), and the Leaf Area Index (LAI) to assess vegetation cover dynamics. The results revealed that sugarcane cultivation is the predominant agricultural and vegetation activity in Mata Norte. Livestock farming areas experienced a significant reduction over the observed decade, which, in turn, led to an increase in agricultural and forested areas. The most dynamic spatiotemporal behavior was observed in the expansion and reduction of livestock areas, a more significant change compared to sugarcane areas. Therefore, land use and land cover in this region are more closely tied to sugarcane cultivation than any other agricultural activity.

Research indicates a strong correlation between sociodemographic factors and success in learning to read. This study examines the sociodemographic characteristics of 1131 preschool and 1st-grade children in Portuguese public schools and explores the relationship between these characteristics and key competencies for reading acquisition. The collection included a sociodemographic questionnaire and pre-reading skills, such as letter-sound knowledge. To assess the relationship between the sociodemographic variables and the letter-sound knowledge, inter-subjects (parametric and non-parametric) difference tests were conducted, as well as correlation analyses. To understand whether letter-sound knowledge is predicted by sociodemographic variables, a multiple linear regression analysis was performed using the Enter method. The results suggest that the mother’s education is the variable that most strongly contributes to success in reading acquisition. Socioeconomic status and the type of school also play a role in reading achievement. Identifying the sociodemographic factors that most strongly correlate with reading acquisition success is crucial for a more accurate identification of at-risk children and to provide targeted support/inclusion in reading skills promotion projects.

To address gaps in practical skills among Public Health and Preventive Medicine graduates, an ‘open collaborative practice teaching model’ integrating medicine, teaching, and research was introduced. A cross-sectional study surveyed 312 Preventive Medicine undergraduates at a Yunnan medical university from 2020 to 2023, utilizing satisfaction scores and analyses (cluster, factor, SWOT) to assess the impact of the reform. Satisfaction scores from baseline, mid-term, and end-term assessments showed minor variations (4.30, 4.29, 4.36), with dissatisfaction primarily related to teaching content and methods. Key influences on satisfaction included teaching content, methods, and effectiveness. The SWOT analysis highlighted the importance of continuously updating teaching strategies to meet changing student expectations. This study suggests that the model has the potential for wider use in enhancing public health education, particularly in regions facing similar challenges.