Evidence map›Paper›PMID 37117718›Full record

ArticleNature food2021

Global option space for organic agriculture is delimited by nitrogen availability.

Pietro Barbieri, Sylvain Pellerin, Verena Seufert, Laurence Smith, Navin Ramankutty, Thomas Nesme

Abstract read
PubMed Publisher
In one paragraph

Article in Nature food, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Pietro BarbieriINRA, UMR 1391 ISPA, CS 20032, Villenave d'Ornon, France. pietro.barbieri@agro-bordeaux.fr.ORCID http://orcid.org/0000-0003-3248-4487
Sylvain PellerinINRA, UMR 1391 ISPA, CS 20032, Villenave d'Ornon, France.
Verena SeufertInstitute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0003-2975-5856
Laurence SmithThe Royal Agricultural University, Cirencester, UK.ORCID http://orcid.org/0000-0002-9898-9288
Navin RamankuttyThe School of Public Policy and Global Affairs and The Institute for Resources, Environment, and Sustainability, The University of British Columbia, Vancouver, British Columbia, Canada.ORCID http://orcid.org/0000-0002-3737-5717
Thomas NesmeINRA, UMR 1391 ISPA, CS 20032, Villenave d'Ornon, France.ORCID http://orcid.org/0000-0003-0695-9936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organic agriculture is widely accepted as a strategy to reduce the environmental impacts of food production and help achieve global climate and biodiversity targets. However, studies concluding that organic farming could satisfy global food demand have overlooked the key role that nitrogen plays in sustaining crop yields. Using a spatially explicit biophysical optimization model that accounts for crop growth nitrogen requirements, we show that, in the absence of synthetic nitrogen fertilizers, the production gap between organic and conventional agriculture increases as organic agriculture expands globally (with organic producing 36% less food for human consumption than conventional in a fully organic world). Yet, by targeting both food supply (via a redesign of the livestock sector) and demand (by reducing average per capita caloric intake), public policies could support a transition towards organic agriculture in 40-60% of the global agricultural area even under current nitrogen limitations thus helping to achieve important environmental and health benefits.

Identifiers

PMID37117718

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.