8 research outputs found

    Spatial variables driving the model that have strong correlation to deforestation and low spatial autocorrelation.

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    <p>Spatial variables driving the model that have strong correlation to deforestation and low spatial autocorrelation.</p

    Annual rates of deforestation in primary forest and primary savanna reported by Potapov et al. [10].

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    <p>Annual rates of deforestation in primary forest and primary savanna reported by Potapov et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0128473#pone.0128473.ref010" target="_blank">10</a>].</p

    Modeled scenarios of future land cover change with average rates of forest and savanna clearing, including secondary forest conversions.

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    <p>Modeled scenarios of future land cover change with average rates of forest and savanna clearing, including secondary forest conversions.</p

    Favorability for protected areas estimated by rural population density and carbon biomass.

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    <p>Favorability for protected areas estimated by rural population density and carbon biomass.</p

    Average carbon loss over time shows trends towards increasing or decreasing carbon stocks depending on the location and scenario assumptions.

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    <p>Average carbon loss over time shows trends towards increasing or decreasing carbon stocks depending on the location and scenario assumptions.</p

    Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).

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    <p>Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).</p
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