Dataset Information

Changing patterns in deforestation avoidance by different protection types in the Brazilian Amazon.

ABSTRACT: This study quantifies how much deforestation was avoided due to legal protection in Legal Amazon in strictly protected areas, sustainable use areas, and indigenous lands. Only regions that are protected de jure (i.e., where deforestation is avoided due to effective laws rather than remoteness) were considered, so that the potential of legal protection could be better assessed. This is a cross-sectional approach, which allows comparisons in terms of avoided deforestation among the different types of protection in the same period. This study covers three different periods. Regions protected de jure were sampled by estimating a threshold distance at which deforestation starts to diminish and retaining all pixels up to that distance, and deforestation that has been avoided due to legal protection was estimated by matching. Indigenous lands avoided the highest percentage of deforestation during the 2001-2004 and 2005-2008 periods, followed by those under strict protection and sustainable use areas, in respective order. Shifting patterns in deforestation avoidance are clearly noticeable for the 2009-2014 period when 1) strictly protected areas outperformed indigenous lands in terms of the percentage of saved forests, 2) some protected regions began to attract deforestation instead of avoiding it, and 3) sustainable use areas, on average, did not avoid deforestation.

SUBMITTER: Jusys T

PROVIDER: S-EPMC5918171 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Changing patterns in deforestation avoidance by different protection types in the Brazilian Amazon.

Jusys Tomas T

PloS one 20180424 4

This study quantifies how much deforestation was avoided due to legal protection in Legal Amazon in strictly protected areas, sustainable use areas, and indigenous lands. Only regions that are protected de jure (i.e., where deforestation is avoided due to effective laws rather than remoteness) were considered, so that the potential of legal protection could be better assessed. This is a cross-sectional approach, which allows comparisons in terms of avoided deforestation among the different types ...[more]

PMID: 29689071

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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

Changing patterns in deforestation avoidance by different protection types in the Brazilian Amazon.

Publications

Changing patterns in deforestation avoidance by different protection types in the Brazilian Amazon.

Similar Datasets

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