Evidence map›Paper›PMID 37945784›Full record

ArticleNature food2023

Agricultural input shocks affect crop yields more in the high-yielding areas of the world.

Aino Ahvo, Matias Heino, Vilma Sandström, Daniel Chrisendo, Mika Jalava, Matti Kummu

Abstract read
In one paragraph

Article in Nature food, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Aino AhvoWater and Development Research Group, Aalto University, Espoo, Finland.
Matias HeinoWater and Development Research Group, Aalto University, Espoo, Finland.ORCID 0000-0003-4294-7756
Vilma SandströmWater and Development Research Group, Aalto University, Espoo, Finland.ORCID 0000-0002-0475-7487
Daniel ChrisendoWater and Development Research Group, Aalto University, Espoo, Finland.ORCID 0000-0002-4941-8606
Mika JalavaWater and Development Research Group, Aalto University, Espoo, Finland.ORCID 0000-0003-4133-7462
Matti KummuWater and Development Research Group, Aalto University, Espoo, Finland. matti.kummu@aalto.fi.ORCID 0000-0001-5096-0163

Funding

Academy of Finland (Suomen Akatemia) 339834EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 819202
6 · The paper itself

Abstract

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.

Indexed as

FertilizersPesticidesAgricultureCrop ProductionCrops, AgriculturalFertilizersPesticides

Identifiers

PMID37945784
PMCPMC10727984

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.