Cattle ranching intensification in Brazil can reduce global greenhouse gas emissions by sparing land from deforestation.
This study examines whether policies to encourage cattle ranching intensification in Brazil can abate global greenhouse gas (GHG) emissions by sparing land from deforestation. We use an economic model of global land use to investigate, from 2010 to 2030, the global agricultural outcomes, land use changes, and GHG abatement resulting from two potential Brazilian policies: a tax on cattle from conventional pasture and a subsidy for cattle from semi-intensive pasture. We find that under either policy, Brazil could achieve considerable sparing of forests and abatement of GHGs, in line with its national policy targets. The land spared, particularly under the tax, is far less than proportional to the productivity increased. However, the tax, despite prompting less adoption of semi-intensive ranching, delivers slightly more forest sparing and GHG abatement than the subsidy. This difference is explained by increased deforestation associated with increased beef consumption under the subsidy and reduced deforestation associated with reduced beef consumption under the tax. Complementary policies to directly limit deforestation could help limit these effects. GHG abatement from either the tax or subsidy appears inexpensive but, over time, the tax would become cheaper than the subsidy. A revenue-neutral combination of the policies could be an element of a sustainable development strategy for Brazil and other emerging economies seeking to balance agricultural development and forest protection.
The Fletcher School, Tufts University, Medford, MA 02155;Energy Biosciences Institute, University of California, Berkeley, CA 94704; avery.cohn@tufts.edu.
Avery S
AS
Cohn
International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria;
Aline
A
Mosnier
International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria;
Petr
P
Havlík
International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria;
Hugo
H
Valin
Commonwealth Scientific and Industrial Research Organization, St. Lucia, QLD 4067, Australia;
Mario
M
Herrero
Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences Vienna, 1180 Vienna, Austria; and.
Erwin
E
Schmid
Goldman School of Public Policy, University of California, Berkeley, CA 94720.
Michael
M
O'Hare
International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria;
Michael
M
Obersteiner
D000383:Agriculture / Q000379:methods*; D000397:Air Pollution / Q000032:analysis / Q000706:statistics & numerical data*; D000822:Animal Husbandry / Q000191:economics / Q000706:statistics & numerical data*; D000818:Animals; D001938:Brazil; D002244:Carbon / Q000032:analysis; D058572:Carbon Footprint / Q000706:statistics & numerical data*; D002417:Cattle; D003198:Computer Simulation; D003247:Conservation of Natural Resources / Q000191:economics; D016468:Forestry; D017752:Greenhouse Effect; D013660:Taxes
D002244:Carbon
agricultural intensification; climate policy; land sparing