Modeling the Brazilian Cerrado land use change highlights the need to account for private property sizes for biodiversity conservation

Simulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the...

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Published inScientific reports Vol. 14; no. 1; p. 4559
Main Authors Colman, Carina Barbosa, Guerra, Angélica, Almagro, André, de Oliveira Roque, Fabio, Rosa, Isabel M. D., Fernandes, Geraldo Wilson, Oliveira, Paulo Tarso S.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 24.02.2024
Nature Publishing Group
Nature Portfolio
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Summary:Simulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-55207-1