Illegal logging as a disincentive to the establishment of a sustainable forest sector in the Amazon

PLoS One. 2018 Dec 5;13(12):e0207855. doi: 10.1371/journal.pone.0207855. eCollection 2018.

Abstract

Brazil recently began granting timber concessions in public forests to promote sustainable forest use. The effectiveness of this strategy hinges on the design and implementation of the concessions themselves as well as their competitive position within the logging sector as a whole. There is, however, a lack of information on the competitive interaction between legal and illegal logging and its effects on concessions profits. We address this knowledge gap by using a spatially explicit simulation model of the Amazon timber industry to examine the potential impact of illegal logging on timber concessions allocation and profits in a 30-year harvest cycle. In a scenario in which illegal logging takes place outside concessions, including private and public "undesignated" lands, concession harvested area would decrease by 59% due to competition with illegal logging. Moreover, 29 out of 39 National Forests (≈74%) would experience a decrease in harvested area. This "leakage" effect could reduce concession net rents by up to USD 1.3 Billion after 30 years. Federal and State "undesignated" lands, if not adequately protected, could have 40% of their total volume illegally harvested in 30 years. Our results reinforce the need to invest in tackling illegal logging, if the government wants the forest concessions program to be successful.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil
  • Computer Simulation
  • Conservation of Natural Resources / economics
  • Conservation of Natural Resources / legislation & jurisprudence*
  • Conservation of Natural Resources / methods
  • Criminal Behavior
  • Forestry / economics
  • Forestry / legislation & jurisprudence*
  • Forestry / methods
  • Forests*
  • Humans
  • Motivation
  • Spatio-Temporal Analysis
  • Trees*
  • Wood / economics

Grants and funding

Letícia Santos de Lima and Britaldo Soares-Filho receive support from Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq (grant numbers 202203/2014-0 and 471272/2012-4, respectively). The Alexander von Humboldt Foundation also supports Britaldo Soares-Filho (grant number 2332333). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.