O projeto Jurupari foi uma iniciativa de extensão desenvolvida por alunos e professores do curso de Engenharia Florestal da Universidade Federal do Amazonas em parceria com a Oficina Escola de Lutheria da Amazônia (OELA), localizada na Zona Leste de Manaus. O projeto teve como objetivo capacitar os aprendizes de luthier por meio da ampliação de seus conhecimentos sobre as propriedades físicas e mecânicas da madeira, matéria-prima essencial para a construção de instrumentos musicais. A metodologia adotada incluiu apresentações multimídia e atividades práticas, realizadas tanto in loco na comunidade quanto nos laboratórios da universidade. Essa abordagem permitiu aos participantes desenvolverem uma nova percepção sobre a madeira e sua utilização sustentável, favorecendo a otimização dos processos de confecção dos instrumentos de corda. Além de aprimorar o aproveitamento da matéria-prima, o projeto proporcionou um intercâmbio de saberes entre o conhecimento científico e a prática artesanal tradicional. Dessa forma, os aprendizes puderam aperfeiçoar suas técnicas, garantindo maior qualidade aos produtos finais e contribuindo para o fortalecimento da sustentabilidade e valorização da lutheria na Amazônia.

Este projeto de extensão foi desenvolvido por alunos e professores do curso de Engenharia Florestal da Universidade Federal do Amazonas e consistiu na produção de vídeos de baixo custo, a partir de celulares e câmeras digitais, entre os anos de 2015 e 2016, e a posterior veiculação em uma plataforma gratuita de vídeos. O projeto denominado Kaapeguara, que no idioma tupi significa “morador do mato”. Os vídeos produzidos englobaram temas como ciência, focados no bioma amazônico. Apesar dos recursos financeiros e técnicos escassos, os vídeos totalizam mais de 172 mil visualizações de 2015 a 2023, com impacto positivo nos discentes e nos internautas que acessaram o canal.

The global forest sink, particularly the tropical forest sink, plays a critical role in the global carbon cycle (Bueno et al., 2020; Pan et al., 2024). Carbon stored in forests is equivalent to almost half the carbon emitted from fossil fuels between 1990 and 2019; however, persistent patterns of deforestation and degradation threaten this carbon sink and its vital role in climate regulation (Pan et al., 2024). Abandoned or left to recover, post-disturbance landscapes can lead to naturally regenerating forests that contribute to significant carbon sequestration, biodiversity benefits, and ecosystem services (Chazdon et al., 2016). Therefore, it is crucial to understand when and where regenerating forests occur to highlight their environmental contributions and promote forest restoration (de Jong et al., 2025). Advancements in RS technologies have enabled a proliferation of RS-based land cover datasets with the potential to estimate secondary forest age and extent (Xu et al., 2024; Baker et al., 2025). However, many have not been explicitly validated for the age or extent of post-disturbance forest regrowth. First comparisons of datasets on secondary forest extent reveal substantial differences at the pixel scale, calling for the need for a reference dataset.Creating a high-quality reference dataset is essential to ensure the reliability of remote sensing-based maps (Baker et al., 2025) and deliver meaningful results to policymakers (Xu et al., 2024; Tyukavina et al., 2025). Here, we propose a robust methodology and reference dataset to validate different secondary forest estimates and support a broader analysis of tropical forest regrowth dynamics. Using a stratified sampling design based on Potapov et al. (2022) and Zhang et al. (2023)'s land cover products, samples were extracted from areas of agreement and disagreement on forest gain, forest loss, stable forest, and stable non-forest regions. Forest trajectories, drivers of disturbance and regrowth, and years of disturbance and regrowth were interpreted using Landsat, Planet, and Google Earth Pro imagery from 2000-2020. Focusing on tropical biomes outside the Amazon Basin which are often overlooked, weighted area estimates from a preliminary 500-sample reference dataset in South America reveal 87.97Mha (5.12% ± 1.00%) of deforestation, 21.70Mha (1.24% ± 0.25%) of secondary forests, and 82.34Mha (4.72% ± 0.92%) of degraded forests. Although the preliminary sample does not indicate systematic over- or under-estimation of secondary forest age, results reveal high commission errors in the extent of naturally regenerating secondary forests outside the Amazon Basin. Furthermore, high uncertainty in the interpretation of tropical dry forest samples highlights the challenges in identifying secondary forests outside the humid tropics and emphasizes the need for more research outside of the Amazon. This dataset has the potential to expand across the pan-tropics to harmonize essential information on regenerating forests and guide urgent action needed to protect the forest carbon sink. Learning from the preliminary study in South America, we emphasize the importance of data quality and draw attention to the uncertainty of large-scale secondary forest products.

Anomalies in sea surface temperature of the tropical Pacific Ocean, are associated with changes in precipitation and humidity patterns in the Amazon region. Temperature increases (El Niño) causes abnormal dry seasons, making the forest more susceptible to wildfires. The decrease (La Niña) in ocean temperatures implies abnormal increases in rainfall, especially in the northern region of Amazon. Between 2019 and 2024, the municipality of Santarém (Pará, Brazil), eastern Amazon, was affected by an increase in forest fires, leading the local government to declare an environmental emergency state in 2024. The objective of this study was to characterize burned areas and changes in land cover in Santarém during the recent ENSO period (2019 to 2024). Annual data on Land Use and Land Cover (LULC) from MapBiomas (Collection 10), and monthly data of burned area from MapBiomas Fogo (Collection 4) were used. National Oceanic and Atmospheric Administration's (NOAAs) Weather Prediction Center data was used to define El Niño (EN), La Niña (LN) and “no anomalies” months (Regular - Rg). LULC was analyzed in small properties (SMp > 300 hectares (ha)), medium-sized (MS, 300 to 1125 ha), large properties (LP >1125 ha), and smallholdings (SMs < 300 ha), as well as indigenous lands (ILs), quilombola areas (Qa), and conservation units (Cs). These data were extracted from SICAR (National Rural Environmental Registry System). For EN periods, 19 months between 2019 and 2024 were analyzed, with 62,962.56 ha of burned areas. For LN (28 months), 15,799.59 ha were burned. During Rg (25 months), 60,109.20 ha of burned area were detected. During EN and Rg periods, Forest Formation (FF) was the most affected coverage, with 36,016.92 ha (EN, 57%) and 39,183.03 (Rg, 65%). For LN, the highest burned coverage was Pasture (Pt), with 8,537.94 ha burned. Mostly small properties (SMp) were affected, with 1,249.29 ha (EN) and 1,124.82 ha (Rg) of FF scorched (1.87%). Pt areas were also affected in SMp (2.07%), accounting for 4.84% of the total. For the protected areas, Cs had 5.63% of the total burned area, with 3,913.47 ha (EN), 2,574.09 ha (Rg) and 1,330.56 ha (LN), mostly in FF. ILs had 1.04% of the total, mostly during EN, with 1,287.27 ha. Other classes (MS, LP, SMs and Qa) accounted for only 1.06% of the burned area. Areas without SICAR classification had the largest burned area (87.43% of the total). These patterns raise concern, given that burning persists in forest areas that remain unprotected and unmonitored. The occurrence of climatic phenomena that induce drier vegetation and less precipitation in the Amazon enable increases in burned area associated with anthropic activities. Implementing fire-prevention measures in vulnerable areas is crucial, and it is equally important to account for these climatic periods. Investment in public policies for environmental education and fire mitigation are essential for transforming these scenarios, in order to mitigate the effects of climate change.