Agricultural input shocks affect crop yields more in the high-yielding areas of the world.
Journal
Nature food
ISSN: 2662-1355
Titre abrégé: Nat Food
Pays: England
ID NLM: 101761102
Informations de publication
Date de publication:
09 Nov 2023
09 Nov 2023
Historique:
received:
26
10
2022
accepted:
05
10
2023
medline:
10
11
2023
pubmed:
10
11
2023
entrez:
9
11
2023
Statut:
aheadofprint
Résumé
The industrialization of agriculture has led to an increasing dependence on non-locally sourced agricultural inputs. Hence, shocks in the availability of agricultural inputs can be devastating to food crop production. There is also a pressure to decrease the use of synthetic fertilizers and pesticides in many areas. However, the combined impact of the agricultural input shocks on crop yields has not yet been systematically assessed globally. Here we modelled the effects of agricultural input shocks using a random forest machine learning algorithm. We show that shocks in fertilizers cause the most drastic yield losses. Under the scenario of 50% shock in all studied agricultural inputs, global maize production could decrease up to 26%, and global wheat production up to 21%, impacting particularly the high-yielding 'breadbasket' areas of the world. Our study provides insights into global food system resilience and can be useful for preparing for potential future shocks or agricultural input availability decreases at local and global scales.
Identifiants
pubmed: 37945784
doi: 10.1038/s43016-023-00873-z
pii: 10.1038/s43016-023-00873-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 819202
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 819202
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 819202
Organisme : Academy of Finland (Suomen Akatemia)
ID : 339834
Organisme : Academy of Finland (Suomen Akatemia)
ID : 339834
Informations de copyright
© 2023. The Author(s).
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