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Data · dataset · 2025

Data from: A spatially explicit representation of conservation agriculture for application in global change studies.

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Data from Prestele R, Hirsch AL, Davin EL, Seneviratne SI, and Verburg PH (2018) A spatially explicit representation of conservation agriculture for application in global change studies.

Description

Global Change Biology 24(9. Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy and proposed to contribute to climate change mitigation and adaptation through reduced emission of greenhouse gases, increased solar radiation reflection, and the sustainable use of soil and water resources.

To improve understanding of how CA management influences the land and climate system, we have developed the first global and spatially explicit data set of present-day CA distribution. National-level estimates of CA have been downscaled to a 5 arcminute regular grid based on multi-criteria analysis. We provide a best estimate of CA distribution and an uncertainty range in the form of a low and high estimate of CA distribution, reflecting the inconsistency in CA definitions.

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The present-day estimates are complemented by two scenarios of the potential future development of CA, combining present-day data and an assessment of the potential for implementation using biophysical and socioeconomic factors. By our estimates, 122 to 215 Mha or 9 to 15% of global arable land is currently managed under CA systems. Our scenario analysis suggests a future potential of CA in the range of 533 to 1130 Mha (38 to 81% of global arable land).

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Geoinformatics 70%
Provenance · 1 source records, 9 field assertions
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IISH Dataversedoi:10.34894/M0UJZE12 d agoJSON v1
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