Degradation by logging, fire, and fragmentation is increasing as a spatially distinct disturbance in the Amazon landscape.

The mechanical performance of soil stabilization using lime to improve forest roads was assessed. This study was conducted with lateritic soil (LVAd30) using lime content of 2% in the municipality of Niquelândia, Goiás state, Brazil. Geotechnical tests of soil characterization, compaction, and mechanical strength were performed applying different compaction efforts and curing periods. The results showed that lime content significantly changed the mechanical performance of natural soil, increasing its mechanical strength and load-carrying capacity. Compaction effort and curing time provided different responses in the unconfined compressive strength (UCS) and California Bearing Ratio (CBR) tests. The best UCS value (786.59 kPa) for the soil-lime mixture was achieved with modified compaction effort and curing time of 28 days. In the CBR test, soil-lime mixtures compacted at intermediate and modified efforts and cured for 28 days were considered for application as subbase material of flexible road pavements, being a promising alternative for use in layers of forest roads.

Background: Long-term studies of community and population dynamics indicate that abrupt disturbances often catalyse changes in vegetation and carbon stocks. These disturbances include the opening of clearings, rainfall seasonality, and drought, as well as fire and direct human disturbance. Such events may be super-imposed on longer-term trends in disturbance, such as those associated with climate change (heating, drying), as well as resources. Intact neotropical forests have recently experienced increased drought frequency and fire occurrence, on top of pervasive increases in atmospheric CO₂ concentrations, but we lack long-term records of responses to such changes especially in the critical transitional areas at the interface of forest and savanna biomes. Here, we present results from 20 years monitoring a valley forest (moist tropical forest outlier) in central Brazil. The forest has experienced multiple drought events and includes plots which have and which have not experienced fire. We focus on how forest structure (stem density and aboveground biomass carbon) and dynamics (stem and biomass mortality and recruitment) have responded to these disturbance regimes. Results: Overall, the biomass carbon stock increased due to the growth of the trees already present in the forest, without any increase in the overall number of tree stems. Over time, both recruitment and especially mortality of trees tended to increase, and periods of prolonged drought in particular resulted in increased mortality rates of larger trees. This increased mortality was in turn responsible for a decline in aboveground carbon toward the end of the monitoring period. Conclusion: Prolonged droughts influence the mortality of large trees, leading to a decline in aboveground carbon stocks. Here, and in other neotropical forests, recent droughts are capable of shutting down and reversing biomass carbon sinks. These new results add to evidence that anthropogenic climate changes are already adversely impacting tropical forests.

O objetivo deste trabalho foi avaliar a eficácia da aplicação de modelos de análise de regressão e redes neurais artificiais (RNAs) na predição do volume de madeira e da biomassa acima do solo, da vegetação arbórea em área de cerradão. Volume de madeira e biomassa foram estimados com equações alométricas desenvolvidas para a área de estudo. Os índices de vegetação, como variáveis preditoras, foram estimados a partir de imagens do sensor LISS-III, e a área basal foi determinada por medições na floresta. A precisão das equações foi verificada pela correlação entre os valores estimados e observados (r), erro-padrão da estimativa (Syx) e gráfico residual. As equações de regressão para o volume de madeira total e do fuste (0,96 e 0,97 para r, e 11,92 e 9,72% para Syx, respectivamente) e para a biomassa (0,91 e 0,92 para r, e 22,73 e 16,80% para Syx, respectivamente) apresentaram bons ajustes. As redes neurais também apresentaram bom ajuste com o volume de madeira (0,99 e 0,99 para r, e 4,93 e 4,83% para Syx) e a biomassa (0,97 e 0,98 r, e 8,92 e 7,96% para Syx, respectivamente). A área basal e os índices de vegetação foram eficazes na estimativa do volume de madeira e biomassa para o cerradão. Os valores reais de volume de madeira e biomassa não diferiram estatisticamente dos valores estimados pelos modelos de regressão e redes neurais (χ^2ns); contudo, as RNAs são mais acuradas.

This article proposes the creation of a participatory governance framework for traditional communities, focusing on financial benefits sharing, whether they come from compensation, indemnification, or socio-environmental projects. The proposed governance framework was developed based on a series of governance principles and the perceptions and needs of fourteen traditional communities in the Brazilian Amazon. The results demonstrated that applied experiences were successful. In this way, the proposed framework presents itself as a mechanism that can be adapted to the specifics of managing financial resources in community contexts.