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Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a divers...

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Detalles Bibliográficos
Autores principales: Reilly, Michael, Willenbockel, Dirk
Formato: Texto
Lenguaje:English
Publicado: The Royal Society 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935120/
https://www.ncbi.nlm.nih.gov/pubmed/20713402
http://dx.doi.org/10.1098/rstb.2010.0141
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author Reilly, Michael
Willenbockel, Dirk
author_facet Reilly, Michael
Willenbockel, Dirk
author_sort Reilly, Michael
collection PubMed
description Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address.
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spelling pubmed-29351202010-09-27 Managing uncertainty: a review of food system scenario analysis and modelling Reilly, Michael Willenbockel, Dirk Philos Trans R Soc Lond B Biol Sci Articles Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address. The Royal Society 2010-09-27 /pmc/articles/PMC2935120/ /pubmed/20713402 http://dx.doi.org/10.1098/rstb.2010.0141 Text en © 2010 The Royal Society http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Reilly, Michael
Willenbockel, Dirk
Managing uncertainty: a review of food system scenario analysis and modelling
title Managing uncertainty: a review of food system scenario analysis and modelling
title_full Managing uncertainty: a review of food system scenario analysis and modelling
title_fullStr Managing uncertainty: a review of food system scenario analysis and modelling
title_full_unstemmed Managing uncertainty: a review of food system scenario analysis and modelling
title_short Managing uncertainty: a review of food system scenario analysis and modelling
title_sort managing uncertainty: a review of food system scenario analysis and modelling
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935120/
https://www.ncbi.nlm.nih.gov/pubmed/20713402
http://dx.doi.org/10.1098/rstb.2010.0141
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