Protected areas (PAs) now shelter 54% of the remaining forests of the Brazilian Amazon and contain 56% of its forest carbon. However, the role of these PAs in reducing carbon fluxes to the atmosphere from deforestation and their associated costs are still uncertain. To fill this gap, we analyzed the effect of each of 595 Brazilian Amazon PAs on deforestation using a metric that accounts for differences in probability of deforestation in areas of pairwise comparison. We found that the three major categories of PA (indigenous land, strictly protected, and sustainable use) showed an inhibitory effect, on average, between 1997 and 2008. Of 206 PAs created after the year 1999, 115 showed increased effectiveness after their designation as protected. The recent expansion of PAs in the Brazilian Amazon was responsible for 37% of the region's total reduction in deforestation between 2004 and 2006 without provoking leakage. All PAs, if fully implemented, have the potential to avoid 8.0 ± 2.8 Pg of carbon emissions by 2050. Effectively implementing PAs in zones under high current or future anthropogenic threat offers high payoffs for reducing carbon emissions, and as a result should receive special attention in planning investments for regional conservation. Nevertheless, this strategy demands prompt and predictable resource streams. The Amazon PA network represents a cost of US$147 ± 53 billion (net present value) for Brazil in terms of forgone profits and investments needed for their consolidation. These costs could be partially compensated by an international climate accord that includes economic incentives for tropical countries that reduce their carbon emissions from deforestation and forest degradation.Amazon Region Protected Areas | effectiveness | reducing emissions from deforestation and forest degradation | simulation model | opportunity cost

[1] The evaluation of impacts of land use change is in general limited by the knowledge of past land use conditions. Most publications on the field present only a vague description of the earlier patterns of land use, which is usually insufficient for more comprehensive studies. Here we present the first spatially explicit reconstruction of historical land use patterns in Brazil, including both croplands and pasturelands, for the period between 1940 and 1995. This reconstruction was obtained by merging satellite imagery with census data, and provides a 5′ Â 5′ yearly data set of land use for three different categories (cropland, natural pastureland and planted pastureland) for Brazil. The results show that important land use changes occurred in Brazil. Natural pasture dominated in the 1950s and 1960s, but since the beginning of 1970s it has been gradually replaced by planted pasture, especially in southeast and center west of Brazil. The croplands began its expansion in the 1960s reaching extensive areas in almost all states in 1980. Carbon emissions from historical land use changes were calculated by superimposing a composite biomass map on grids of a weighted average of the fractions of the vegetation types and the replacement land uses. Net emissions from land use changes between 1940 and 1995 totaled 17.2 AE 9.0 Pg-C (90% confidence range), averaging 0.31 AE 0.16 Pg-C yr À1

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The loss of tropical forests threatens a broad range of ecosystem services. Particularly, tropical deforestation is a major driver of biodiversity decline and substantial carbon emissions. Regrowth of secondary vegetation may help to restore habitat for many threatened species and improve ecosystem services that deteriorated due to deforestation. However, spatial-temporal patterns of regrowing secondary vegetation in the tropics remain weakly understood. We therefore analyze regrowth dynamics across two different land use systems in southern Amazonia: the extensive pastoralism in Pará and the capital-intensive agriculture in Mato Grosso. Both systems are connected by the BR-163 highway, which represents a major axis of deforestation and agricultural development in the Brazilian Amazon since decades. We used a 29 year time series of Landsat images to extract regrowth extent, duration, lag time between deforestation and regrowth, and frequency of regrowth cycles. Our results reached an overall accuracy of 89% and showed regrowth on up to 50% of the deforested area in Pará and a maximum of 25% in Mato Grosso. In both states, annual regrowth rates drastically dropped after 1996, which coincided with socioeconomic transformations and drought events. The majority of regrowth was concentrated within 60m distance to forest edges and cleared again after an average of 5 years. Our approach bears great potential for mapping post deforestation regrowth dynamics within and beyond the Brazilian Amazon based on long-term and freely accessible remote sensing data collections, such as the Landsat and the forthcoming Sentinel-2 archives.

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In tropical areas, pioneer occupation fronts steer the rapid expansion of deforestation, contributing to carbon emissions. Up-to-date carbon emission estimates covering the long-term development of such frontiers depend on the availability of high spatial-temporal resolution data. In this paper, we provide a detailed assessment of carbon losses from deforestation and potential forest degradation from fragmentation for one expanding frontier in the Brazilian Amazon. We focused on one of the Amazonia's hot-spots of forest loss, the BR-163 highway that connects the high productivity agricultural landscapes in Mato Grosso with the exporting harbors of the Amazon. We used multidecadal (1984-2012) Landsat-based time series on forested and non-forested area in combination with a carbon bookkeeping model. We show a 36% reduction in 1984s biomass carbon stocks, which led to the emission of 611.5 TgCO 2 between 1985 and 1998 (43.6 TgCO 2 year-1) and 959.8 TgCO 2 over 1999-2012 (68.5 TgCO 2 year-1). Overall, fragmentation-related carbon losses represented 1.88% of total emissions by 2012, with an increasing relevance since 2004. We compared the Brazilian Space Agency deforestation assessment (PRODES) with our data and found that small deforestation polygons not captured by PRODES had increasing importance on estimated deforestation carbon losses since 2000. The comparative analysis improved the understanding of data-source-related uncertainties on carbon estimates and indicated disagreement areas between datasets that could be subject of future research. Furthermore, spatially explicit, annual deforestation and emission estimates like the ones derived from this study are important for setting regional baselines for REDD? or similar payment for ecosystem services frameworks.

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