Dataset Information

Brazilian Amazon indigenous territories under deforestation pressure.

ABSTRACT: Studies showed that Brazilian Amazon indigenous territories (ITs) are efficient models for preserving forests by reducing deforestation, fires, and related carbon emissions. Considering the importance of ITs for conserving socio-environmental and cultural diversity and the recent climb in the Brazilian Amazon deforestation, we used official remote sensing datasets to analyze deforestation inside and outside indigenous territories within Brazil's Amazon biome during the 2013-2021 period. Deforestation has increased by 129% inside ITs since 2013, followed by an increase in illegal mining areas. In 2019-2021, deforestation was 195% higher and 30% farther from the borders towards the interior of indigenous territories than in previous years (2013-2018). Furthermore, about 59% of carbon dioxide (CO₂) emissions within ITs in 2013-2021 (96 million tons) occurred in the last three years of analyzed years, revealing the magnitude of increasing deforestation to climate impacts. Therefore, curbing deforestation in indigenous territories must be a priority for the Brazilian government to secure these peoples' land rights, ensure the forests' protection and regulate the global climate.

SUBMITTER: Silva-Junior CHL

PROVIDER: S-EPMC10085996 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Brazilian Amazon indigenous territories under deforestation pressure.

Silva-Junior Celso H L CHL Silva Fabrício B FB Arisi Barbara Maisonnave BM Mataveli Guilherme G Pessôa Ana C M ACM Carvalho Nathália S NS Reis João B C JBC Silva Júnior Admo R AR Motta Nathalia A C S NACS E Silva Paulo Vinícius Moreira PVM Ribeiro Francarlos Diniz FD Siqueira-Gay Juliana J Alencar Ane A Saatchi Sassan S Aragão Luiz E O C LEOC Anderson Liana O LO Melo Maycon M

Scientific reports 20230410 1

Studies showed that Brazilian Amazon indigenous territories (ITs) are efficient models for preserving forests by reducing deforestation, fires, and related carbon emissions. Considering the importance of ITs for conserving socio-environmental and cultural diversity and the recent climb in the Brazilian Amazon deforestation, we used official remote sensing datasets to analyze deforestation inside and outside indigenous territories within Brazil's Amazon biome during the 2013-2021 period. Deforest ...[more]

PMID: 37037850

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Project description:Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges "bottom up", as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated-pre- and post-PPCDAM ("Plano de Ação para Proteção e Controle do Desmatamento na Amazônia")-the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation.

Dataset Information

Brazilian Amazon indigenous territories under deforestation pressure.

Publications

Brazilian Amazon indigenous territories under deforestation pressure.

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