4.7 Article

Statistical confirmation of indirect land use change in the Brazilian Amazon

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 6, Issue 2, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1748-9326/6/2/024010

Keywords

soy; cattle; deforestation; Amazonia; biofuel

Funding

  1. National Science Foundation
  2. NASA [NNX07AF16G]
  3. Amazon Forest
  4. Division Of Behavioral and Cognitive Sci
  5. Direct For Social, Behav & Economic Scie [0822799] Funding Source: National Science Foundation
  6. Division Of Behavioral and Cognitive Sci
  7. Direct For Social, Behav & Economic Scie [0822597, 1157952] Funding Source: National Science Foundation

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Expansion of global demand for soy products and biofuel poses threats to food security and the environment. One environmental impact that has raised serious concerns is loss of Amazonian forest through indirect land use change (ILUC), whereby mechanized agriculture encroaches on existing pastures, displacing them to the frontier. This phenomenon has been hypothesized by many researchers and projected on the basis of simulation for the Amazonian forests of Brazil. It has not yet been measured statistically, owing to conceptual difficulties in linking distal land cover drivers to the point of impact. The present article overcomes this impasse with a spatial regression model capable of linking the expansion of mechanized agriculture in settled agricultural areas to pasture conversions on distant, forest frontiers. In an application for a recent period (2003-2008), the model demonstrates that ILUC is significant and of considerable magnitude. Specifically, a 10% reduction of soy in old pasture areas would have decreased deforestation by as much as 40% in heavily forested counties of the Brazilian Amazon. Evidently, the voluntary moratorium on primary forest conversions by Brazilian soy farmers has failed to stop the deforestation effects of expanding soy production. Thus, environmental policy in Brazil must pay attention to ILUC, which can complicate efforts to achieve its REDD targets.

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