Simulating Deforestation in Minas Gerais, Brazil, under Changing Government Policies and Socioeconomic Conditions

PLoS One. 2015 Sep 15;10(9):e0137911. doi: 10.1371/journal.pone.0137911. eCollection 2015.

Abstract

Agricultural expansion is causing deforestation in Minas Gerais, Brazil, converting savanna and tropical dry forest to farmland, and in 2012, Brazil's Forest Code was revised with the government reducing deforestation restrictions. Understanding the effects of policy change on rates and locations of natural ecosystem loss is imperative. In this paper, deforestation in Minas Gerais was simulated annually until 2020 using Dinamica Environment for Geoprocessing Objects (Dinamica EGO). This system is a state-of-the-art land use and cover change (LUCC) model which incorporates government policy, landscape maps, and other biophysical and anthropogenic datasets. Three studied scenarios: (i) business as usual, (ii) increased deforestation, and (iii) decreased deforestation showed more transition to agriculture from shrubland compared to forests, and consistent locations for most deforestation. The probability of conversion to agriculture is strongly tied to areas with the smallest patches of original biome remaining. Increases in agricultural revenue are projected to continue with a loss of 25% of the remaining Cerrado land in the next decade if profit is maximized. The addition of biodiversity value as a tax on land sale prices, estimated at over $750,000,000 USD using the cost of extracting and maintaining current species ex-situ, can save more than 1 million hectares of shrubland with minimal effects on the economy of the State of Minas Gerais. With environmental policy determining rates of deforestation and economics driving the location of land clearing, site-specific protection or market accounting of externalities is needed to balance economic development and conservation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • Brazil
  • Conservation of Natural Resources / economics*
  • Government*
  • Models, Theoretical*
  • Policy*
  • Socioeconomic Factors
  • Spatial Analysis

Grants and funding

Funding for this research was provided by an NSERC Undergraduate Student Research Award, Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG), and the Inter American Institute for Global Change Research (IAI) Collaborative Research Network Program CRN 3 – 025 which is supported by the US National Science Foundation (Grant GEO-1128040). The authors' acknowledge the support provided by the University of Alberta, and the National Science and Engineering Research Council of Canada (NSERC-Discovery). MES gratefully acknowledges a research scholarship from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.