Policy change, land use, and agriculture: The case of soy production and cattle ranching in Brazil, 2001-2012
Mathematisch-Naturwissenschaftliche Fakultät
The Brazilian Amazon has experienced one of the world's highest deforestation rates in the last decades.
Cattle ranching and soy expansion constitute the major drivers of deforestation, both through direct
conversion and indirectly by land use displacement. However, deforestation rates decreased significantly
after the implementation of the action plan to prevent and control deforestation in 2004. The aim of this
study is to quantify the contribution of cattle and soy production with deforestation before and after the
implementation of the action plan in the two states Mato Grosso and Par a along the BR-163. Specifically,
we aim to empirically test for land use displacement processes from soy expansion in Mato Grosso to the
deforestation frontier between 2001 and 2012. First, we calculated the relationships between deforestation
rate and the change in cattle head and planted soy area respectively for the BR-163 region. Second,
we estimated different panel regression models to test the association between processes of land use
displacement. Our results indicate a close linkage between cattle ranching and deforestation along the
BR-163 between 2001 and 2004. Soy expansion in Mato Grosso was significantly associated with
deforestation during this period. However, these relations have diminished after the implementation of
the action plan to control and prevent deforestation. With the decrease in deforestation rates in 2005,
cattle ranching and deforestation were not directly linked, nor was soy expansion in Mato Grosso and
deforestation at the forest frontier. Our analysis hence suggests that there was a close coupling of processes
and spatial displacement until 2004 and a decoupling has taken place following the political
interventions. These findings improve the understanding of land use displacement processes in Brazil
and the methods offer potential for exploring similar processes in different regions of the world.
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