Dataset Information

Reserves protect against deforestation fires in the Amazon.

ABSTRACT:

Background

Reserves are the principal means to conserve forests and biodiversity, but the question of whether reserves work is still debated. In the Amazon, fires are closely linked to deforestation, and thus can be used as a proxy for reserve effectiveness in protecting forest cover. We ask whether reserves in the Brazilian Amazon provide effective protection against deforestation and consequently fires, whether that protection is because of their location or their legal status, and whether some reserve types are more effective than others.

Methodology/principal findings

Previous work has shown that most Amazonian fires occur close to roads and are more frequent in El Niño years. We quantified these relationships for reserves and unprotected areas by examining satellite-detected hot pixels regressed against road distance across the entire Brazilian Amazon and for a decade with 2 El Niño-related droughts. Deforestation fires, as measured by hot pixels, declined exponentially with increasing distance from roads in all areas. Fewer deforestation fires occurred within protected areas than outside and the difference between protected and unprotected areas was greatest near roads. Thus, reserves were especially effective at preventing these fires where they are known to be most likely to burn; but they did not provide absolute protection. Even within reserves, at a given distance from roads, there were more deforestation fires in regions with high human impact than in those with low impact. The effect of El Niño on deforestation fires was greatest outside of reserves and near roads. Indigenous reserves, limited-use reserves, and fully protected reserves all had fewer fires than outside areas and did not appear to differ in their effectiveness.

Conclusions/significance

Taking time, regional factors, and climate into account, our results show that reserves are an effective tool for curbing destructive burning in the Amazon.

SUBMITTER: Adeney JM

PROVIDER: S-EPMC2660414 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reserves protect against deforestation fires in the Amazon.

Adeney J Marion JM Christensen Norman L NL Pimm Stuart L SL

PloS one 20090408 4

<h4>Background</h4>Reserves are the principal means to conserve forests and biodiversity, but the question of whether reserves work is still debated. In the Amazon, fires are closely linked to deforestation, and thus can be used as a proxy for reserve effectiveness in protecting forest cover. We ask whether reserves in the Brazilian Amazon provide effective protection against deforestation and consequently fires, whether that protection is because of their location or their legal status, and whe ...[more]

PMID: 19352423

Similar Datasets

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

Reserves protect against deforestation fires in the Amazon.

Background

Methodology/principal findings

Conclusions/significance

Publications

Reserves protect against deforestation fires in the Amazon.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure