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Historical carbon fluxes in the expanding deforestation frontier of Southern Brazilian Amazonia (1985–2012)
Authors:Hissa  Letícia de Barros Viana  Müller  Hannes  Aguiar  Ana Paula Dutra  Hostert  Patrick  Lakes  Tobia
Institution:1.Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany
;2.Earth System Science Center (CCST), National Institute for Space Research (INPE), Ministry of Science, Technology and Innovation (MCTI), Av. dos Astronautas 1758, São José dos Campos, SP, CEP 12227-010, Brazil
;3.Integrative Research Institute on Transformations of Human-Environment Systems, Humboldt Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany
;
Abstract:

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 multi-decadal (1984–2012) Landsat-based time series on forested and non-forested area in combination with a carbon book-keeping model. We show a 36% reduction in 1984s biomass carbon stocks, which led to the emission of 611.5 TgCO2 between 1985 and 1998 (43.6 TgCO2 year−1) and 959.8 TgCO2 over 1999–2012 (68.5 TgCO2 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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