Deforestation and Carbon Stock Loss in Brazil's Amazonian Settlements

Environ Manage. 2017 Mar;59(3):393-409. doi: 10.1007/s00267-016-0783-2. Epub 2016 Oct 24.

Abstract

We estimate deforestation and the carbon stock in 2740 (82 %) of the 3325 settlements in Brazil's Legal Amazonia region. Estimates are made both using available satellite data and a carbon map for the "pre-modern" period (prior to 1970). We used data from Brazil's Project for Monitoring Deforestation in Amazonia updated through 2013 and from the Brazilian Biomes Deforestation Monitoring Project (PMDBBS) updated through 2010. To obtain the pre-modern and recent carbon stocks we performed an intersection between a carbon map and a map derived from settlement boundaries and deforestation data. Although the settlements analyzed occupied only 8 % of Legal Amazonia, our results indicate that these settlements contributed 17 % (160,410 km2) of total clearing (forest + non-forest) in Legal Amazonia (967,003 km2). This represents a clear-cutting of 41 % of the original vegetation in the settlements. Out of this total, 72 % (115,634 km2) was in the "Federal Settlement Project" (PA) category. Deforestation in settlements represents 20 % (2.6 Pg C) of the total carbon loss in Legal Amazonia (13.1 Pg C). The carbon stock in remaining vegetation represents 3.8 Pg C, or 6 % of the total remaining carbon stock in Legal Amazonia (58.6 Pg C) in the periods analyzed. The carbon reductions in settlements are caused both by the settlers and by external actors. Our findings suggest that agrarian reform policies contributed directly to carbon loss. Thus, the implementation of new settlements should consider potential carbon stock losses, especially if settlements are created in areas with high carbon stocks.

Keywords: Agrarian reform; Amazon forest; Carbon; Colonization; Global warming; Settlement project.

MeSH terms

  • Biomass
  • Brazil
  • Carbon / analysis*
  • Carbon Sequestration*
  • Conservation of Natural Resources / trends*
  • Ecosystem*
  • Forests*
  • Humans
  • Rural Population / trends*

Substances

  • Carbon