Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation

Concerted political attention has focused on reducing deforestation1,2,3, and this remains the cornerstone of most biodiversity conservation strategies4,5,6. However, maintaining forest cover may not reduce anthropogenic forest disturbances, which are rarely considered in conservation programmes6. These disturbances occur both within forests, including selective logging and wildfires7,8, and at the landscape level, through edge, area and isolation effects9. Until now, the combined effect of anthropogenic disturbance on the conservation value of remnant primary forests has remained unknown, making it impossible to assess the relative importance of forest disturbance and forest loss. Here we address these knowledge gaps using a large data set of plants, birds and dung beetles (1,538, 460 and 156 species, respectively) sampled in 36 catchments in the Brazilian state of Pará. Catchments retaining more than 69–80% forest cover lost more conservation value from disturbance than from forest loss. For example, a 20% loss of primary forest, the maximum level of deforestation allowed on Amazonian properties under Brazil’s Forest Code5, resulted in a 39–54% loss of conservation value: 96–171% more than expected without considering disturbance effects. We extrapolated the disturbance-mediated loss of conservation value throughout Pará, which covers 25% of the Brazilian Amazon. Although disturbed forests retained considerable conservation value compared with deforested areas, the toll of disturbance outside Pará’s strictly protected areas is equivalent to the loss of 92,000–139,000 km2 of primary forest. Even this lowest estimate is greater than the area deforested across the entire Brazilian Amazon between 2006 and 2015 (ref. 10). Species distribution models showed that both landscape and within-forest disturbances contributed to biodiversity loss, with the greatest negative effects on species of high conservation and functional value. These results demonstrate an urgent need for policy interventions that go beyond the maintenance of forest cover to safeguard the hyper-diversity of tropical forest ecosystems

Análise espaço-temporal da doença de Chagas e seus fatores de risco ambientais e demográficos no município de Barcarena, Pará, Brasil

To the Federal University of Pará (UFPA), to the Laboratory of Epidemiology and Geoprocessing (EpiGeo) of the University of the State of Pará (UEPA), to the Laboratory of Geoprocessing of the Evandro Chagas Institute (LabGeo/IEC), to the Health Department of the Municipality of Barcarena (SESMUB), to the Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Council for Scientific and Technological Development (CNPq).Universidade do Estado do Pará. Belém, PA, Brazil.Universidade do Estado do Pará. Belém, PA, Brazil.Universidade do Estado do Pará. Belém, PA, Brazil.Universidade do Estado do Pará. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Secretaria Municipal de Saúde de Barcarena. Barcarena, PA, Brazil.Universidade do Estado do Pará. Belém, PA, Brazil.Universidade do Estado do Pará. Belém, PA, Brazil.Introduction: Chagas disease is a parasitosis considered a serious problem of public health. In the municipality of Barcarena, Pará, from 2007 to 2014, occurred the highest prevalence of this disease in Brazil. Objective: To analyze the disease distribution related to epidemiological, environmental and demographic variables, in the area and period of the study. Methods: Epidemiological and demographic data of Barcarena Health Department and satellite images from the National Institute For Space Research (INPE) were used. The deforestation data were obtained through satellite image classification, using artificial neural network. The statistical significance was done with the χ2 test, and the spatial dependence tests among the variables were done using Kernel and Moran techniques. Results: The epidemiological curve indicated a disease seasonal pattern. The major percentage of the cases were in male, brown skin color, adult, illiterate, urban areas and with probable oral contamination. It was confirmed the spatial dependence of the disease cases with the different types of deforestation identified in the municipality, as well as agglomerations of cases in urban and rural areas. Discussion: The disease distribution did not occur homogeneously, possibly due to the municipality demographic dynamics, with intense migratory flows that generates the deforestation. Conclusion: Different relationships among the variables studied and the occurrence of the disease in the municipality were observed. The technologies used were satisfactory to construct the disease epidemiological scenarios