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A spatially explicit representation of conservation agriculture for application in global change studies
Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6120452/ https://www.ncbi.nlm.nih.gov/pubmed/29749125 http://dx.doi.org/10.1111/gcb.14307 |
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author | Prestele, Reinhard Hirsch, Annette L. Davin, Edouard L. Seneviratne, Sonia I. Verburg, Peter H. |
author_facet | Prestele, Reinhard Hirsch, Annette L. Davin, Edouard L. Seneviratne, Sonia I. Verburg, Peter H. |
author_sort | Prestele, Reinhard |
collection | PubMed |
description | Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is 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. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present‐day national‐level estimates of CA to a 5 arcminute regular grid, based on multicriteria 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. We also design 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, 122–215 Mha or 9%–15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no‐tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no‐tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533–1130 Mha (38%–81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices. |
format | Online Article Text |
id | pubmed-6120452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61204522018-09-05 A spatially explicit representation of conservation agriculture for application in global change studies Prestele, Reinhard Hirsch, Annette L. Davin, Edouard L. Seneviratne, Sonia I. Verburg, Peter H. Glob Chang Biol Primary Research Articles Conservation agriculture (CA) is widely promoted as a sustainable agricultural management strategy with the potential to alleviate some of the adverse effects of modern, industrial agriculture such as large‐scale soil erosion, nutrient leaching and overexploitation of water resources. Moreover, agricultural land managed under CA is 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. Due to the lack of official reporting schemes, the amount of agricultural land managed under CA systems is uncertain and spatially explicit information about the distribution of CA required for various modeling studies is missing. Here, we present an approach to downscale present‐day national‐level estimates of CA to a 5 arcminute regular grid, based on multicriteria 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. We also design 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, 122–215 Mha or 9%–15% of global arable land is currently managed under CA systems. The lower end of the range represents CA as an integrated system of permanent no‐tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no‐tillage or reduced tillage operations. Our scenario analysis suggests a future potential of CA in the range of 533–1130 Mha (38%–81% of global arable land). Our estimates can be used in various ecosystem modeling applications and are expected to help identifying more realistic climate mitigation and adaptation potentials of agricultural practices. John Wiley and Sons Inc. 2018-06-03 2018-09 /pmc/articles/PMC6120452/ /pubmed/29749125 http://dx.doi.org/10.1111/gcb.14307 Text en © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Primary Research Articles Prestele, Reinhard Hirsch, Annette L. Davin, Edouard L. Seneviratne, Sonia I. Verburg, Peter H. A spatially explicit representation of conservation agriculture for application in global change studies |
title | A spatially explicit representation of conservation agriculture for application in global change studies |
title_full | A spatially explicit representation of conservation agriculture for application in global change studies |
title_fullStr | A spatially explicit representation of conservation agriculture for application in global change studies |
title_full_unstemmed | A spatially explicit representation of conservation agriculture for application in global change studies |
title_short | A spatially explicit representation of conservation agriculture for application in global change studies |
title_sort | spatially explicit representation of conservation agriculture for application in global change studies |
topic | Primary Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6120452/ https://www.ncbi.nlm.nih.gov/pubmed/29749125 http://dx.doi.org/10.1111/gcb.14307 |
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