Spatial frameworks for robust estimation of yield gaps

Autores
Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; Grassini, Patricio
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.
Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados Unidos
Fil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países Bajos
Fil: van Loon, Marloes P.. University of Agriculture Wageningen; Países Bajos
Fil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados Unidos
Materia
NO KEYWORDS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/168531

id CONICETDig_cce86f3f9d1590fd1a05e016c9d6ee3d
oai_identifier_str oai:ri.conicet.gov.ar:11336/168531
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Spatial frameworks for robust estimation of yield gapsRattalino Edreira, Juan IgnacioAndrade, José FranciscoCassman, Kenneth G.van Ittersum, Martin K.van Loon, Marloes P.Grassini, PatricioNO KEYWORDShttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados UnidosFil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países BajosFil: van Loon, Marloes P.. University of Agriculture Wageningen; Países BajosFil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados UnidosSpringer Nature2021-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/168531Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-7792662-1355CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s43016-021-00365-yinfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s43016-021-00365-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:34:00Zoai:ri.conicet.gov.ar:11336/168531instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:34:00.544CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Spatial frameworks for robust estimation of yield gaps
title Spatial frameworks for robust estimation of yield gaps
spellingShingle Spatial frameworks for robust estimation of yield gaps
Rattalino Edreira, Juan Ignacio
NO KEYWORDS
title_short Spatial frameworks for robust estimation of yield gaps
title_full Spatial frameworks for robust estimation of yield gaps
title_fullStr Spatial frameworks for robust estimation of yield gaps
title_full_unstemmed Spatial frameworks for robust estimation of yield gaps
title_sort Spatial frameworks for robust estimation of yield gaps
dc.creator.none.fl_str_mv Rattalino Edreira, Juan Ignacio
Andrade, José Francisco
Cassman, Kenneth G.
van Ittersum, Martin K.
van Loon, Marloes P.
Grassini, Patricio
author Rattalino Edreira, Juan Ignacio
author_facet Rattalino Edreira, Juan Ignacio
Andrade, José Francisco
Cassman, Kenneth G.
van Ittersum, Martin K.
van Loon, Marloes P.
Grassini, Patricio
author_role author
author2 Andrade, José Francisco
Cassman, Kenneth G.
van Ittersum, Martin K.
van Loon, Marloes P.
Grassini, Patricio
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv NO KEYWORDS
topic NO KEYWORDS
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.
Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados Unidos
Fil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países Bajos
Fil: van Loon, Marloes P.. University of Agriculture Wageningen; Países Bajos
Fil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados Unidos
description Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.
publishDate 2021
dc.date.none.fl_str_mv 2021-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/168531
Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-779
2662-1355
CONICET Digital
CONICET
url http://hdl.handle.net/11336/168531
identifier_str_mv Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-779
2662-1355
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1038/s43016-021-00365-y
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s43016-021-00365-y
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613049527304192
score 13.070432