Mangroves play an essential ecological role in the maintenance of the coastal zone and are extremely important for the socioeconomics of coastal communities. However, mangrove ecosystems are impacted by a range of anthropogenic pressures, and the loss of this habitat can be attributed primarily to the human occupation of the coastal zone. In the present study, we analyzed the spatial patterns of land use in the mangrove of the Brazilian Amazon coast, and evaluated the anthropogenic drivers of this impact, using a remote sensing approach. We mapped the road network using RapidEye images, and human settlements using global data. The results of these analyses indicate that the Brazilian Amazon coast has a low population density and low rates of anthropogenic impact in most of the coastal microregions investigated, factors that contribute to the maintenance and conservation of the region’s mangrove. The study also revealed that the paved road network is one of the principal drivers of land use in the mangrove, whereas other factors, such as population density, urban centers, and the number of settlements are much less important. While the region has 2024 km of paved highways, unpaved roads (17,496 km) facilitate access to the mangrove, with approximately 90% of anthropogenic impact being recorded within a 3 km radius of these roads. While the network of paved highways is relatively reduced in extension, preventive measures are urgently required to impede any major shift in the current scenario, caused by the expansion of major development programs. The results of the study indicate that biophysical, economic, and political factors may also contribute to the reduction, stability, and development of one of the world’s largest areas of mangrove forest.

Reliable estimates of biomass and carbon storage are essential for the understanding of the environmental drivers and processes that regulate the productivity of scrub forests. The present study estimated total (above-ground, AGB + below-ground, BGB) biomass and carbon storage of a scrub forest dominated by Avicennia germinans (L.) L. based on the existing allometric models for the AGB, while novel models were developed to estimate the BGB. Data collection followed a destructive approach by using the "sampling method", from 45 trees divided into three height classes. Tree height and diameter were used to estimate the BGB of these forests, providing more accurate estimates of their biomass. Our findings indicate the existence of a direct relationship with increasing topography and interstitial salinity, which result in an increase in the percentage contribution of the AGB. By contrast, increasing topography also led to reduction in tree height and contribution of the BGB, although this compartment represents approximately half of the total biomass of these forests. The contribution of BGB estimates increased from 43 to 49.5% from the lowest to the highest height class and the BGB and AGB values reached approximately 87 Mg ha^-1 (48.6%) and 91.7 Mg ha^-1 (51.4%), respectively. The estimates of the biomass and carbon stocks of scrub mangroves vary considerably worldwide, which reflects the uncertainties derived from the application of distinct sampling methods. Specific models developed for each height class should be considered instead generalist models to reduce the general uncertainties on the production and distribution of biomass and the storage of carbon. Overall, our results overcome a major lacuna in the development of allometric equations to estimate the production of BGB and the storage of carbon by scrub mangrove forests, contributing to the refinement of the total biomass estimates for this type of mangrove forest.

The aim of this study is to understand the relationship between radar backscattering (σ°, β° and γ) of a multi-polarized Radarsat-2 C-band image with the structural attributes of regenerating mangrove vegetation located at the mouth of the Amazon River. CBH (circumference at breast height), height and species data were collected to characterize vegetation structure and above-ground biomass (AGB) at 17 plots with a total of 3090 measured individuals. Significant relationships between the linear σ° in VH (vertical transmit, horizontal receive) cross-polarization produced r² values of 0.63 for the average height, 0.53 for the DBH, 0.46 for the basal area (BA) and 0.52 for the AGB. Using co-polarized HH (horizontal transmit, horizontal receive) and VV (vertical transmit, vertical receive), r² values increased to 0.81, 0.79, 0.67 and 0.79, respectively. Vegetation attribute maps of average canopy height, DBH and AGB were generated for the study area. We conclude that multi-polarized Radarsat-2 images were adequate for characterization of vegetation attributes in areas of mangrove regeneration.

The common hematophagous bat, Desmodus rotundus, is one of the main wild reservoirs of rabies virus in several regions in Latin America. New production practices and changed land use have provided environmental features that have been very favorable for D. rotundus bat populations, making this species the main transmitter of rabies in the cycle that involves humans and herbivores. In the Amazon region, these features include a mosaic of environmental, social, and economic components, which together creates areas with different levels of risk for human and bovine infections, as presented in this work in the eastern Brazilian Amazon. We geo-referenced a total of 175 cases of rabies, of which 88% occurred in bovines and 12% in humans, respectively, and related these cases to a number of different geographical and biological variables. The spatial distribution was analyzed using the Kernel function, while the association with independent variables was assessed using a multi-criterion Analytical Hierarchy Process (AHP) technique. The spatiotemporal analysis of the occurrence of rabies in bovines and humans found reduction in the number of cases in the eastern state of Pará, where no more cases were recorded in humans, whereas high infection rates were recorded in bovines in the northeastern part of the state, and low rates in the southeast. The areas of highest risk for bovine rabies are found in the proximity of rivers and highways. In the case of human rabies, the highest concentration of high-risk areas was found where the highway network coincides with high densities of rural and indigenous populations. The high-risk areas for human and bovine rabies are patchily distributed, and related to extensive deforested areas, large herds of cattle, and the presence of highways. These findings provide an important database for the generation of epidemiological models that could support the development of effective prevention measures and controls.