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Forests 2018, 9(10), 600; https://doi.org/10.3390/f9100600

Simulated Impacts of Soy and Infrastructure Expansion in the Brazilian Amazon: A Maximum Entropy Approach

1
Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
2
Senckenberg Biodiversity and Climate Research Centre (BiK-F), 60325 Frankfurt am Main, Germany
3
Department of Physical Geography, Goethe University, 60438 Frankfurt am Main, Germany
4
Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI 53726, USA
5
Department of Geography, University of Wisconsin, Madison, WI 53706, USA
6
Institute for Food and Resource Economics (ILR), University of Bonn, 53115 Bonn, Germany
*
Author to whom correspondence should be addressed.
Received: 18 September 2018 / Revised: 24 September 2018 / Accepted: 25 September 2018 / Published: 27 September 2018
(This article belongs to the Special Issue Policies Affecting Development and Forest Conservation)
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Abstract

Historically, the expansion of soy plantations has been a major driver of land-use/cover change (LUCC) in Brazil. While a series of recent public actions and supply-chain commitments reportedly curbed the replacement of forests by soy, the expansion of the agricultural commodity still poses a considerable threat to the Amazonian and Cerrado biomes. Identification of areas under high risk of soy expansion is thus paramount to assist conservation efforts in the region. We mapped the areas suitable for undergoing transition to soy plantations in the Legal Amazon with a machine-learning approach adopted from the ecological modeling literature. Simulated soy expansion for the year 2014 exhibited favorable validation scores compared to other LUCC models. We then used our model to simulate how potential future infrastructure improvements would affect the 2014 probabilities of soy occurrence in the region. In addition to the 2.3 Mha of planted soy in the Legal Amazon in 2014, our model identified another 14.7 Mha with high probability of soy conversion in the region given the infrastructure conditions at that time. Out of those, pastures and forests represented 9.8 and 0.4 Mha, respectively. Under the new infrastructure scenarios simulated, the Legal Amazonian area under high risk of soy conversion increased by up to 2.1 Mha (14.6%). These changes led to up to 11.4 and 51.4% increases in the high-risk of conversion areas of pastures and forests, respectively. If conversion occurs in the identified high-risk areas, at least 4.8 Pg of CO2 could be released into the atmosphere, a value that represents 10 times the total CO2 emissions of Brazil in 2014. Our results highlight the importance of targeting conservation policies and enforcement actions, including the Soy Moratorium, to mitigate future forest cover loss associated with infrastructure improvements in the region. View Full-Text
Keywords: land-use/cover change modeling; deforestation; MaxEnt; infrastructure improvements; tropical conservation; agricultural commodity; Cerrado land-use/cover change modeling; deforestation; MaxEnt; infrastructure improvements; tropical conservation; agricultural commodity; Cerrado
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Frey, G.P.; West, T.A.P.; Hickler, T.; Rausch, L.; Gibbs, H.K.; Börner, J. Simulated Impacts of Soy and Infrastructure Expansion in the Brazilian Amazon: A Maximum Entropy Approach. Forests 2018, 9, 600.

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