Evidence map›Paper›PMID 37186829›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Restoring particulate and mineral-associated organic carbon through regenerative agriculture.

Aaron M Prairie, Alison E King, M Francesca Cotrufo

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  8. Can circularity support net-zero agriculture: an exploratory case.Animal frontiers : the review magazine of animal agriculture · 2025
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  16. Restoring particulate and mineral-associated organic carbon through regenerative agriculture.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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

3 authors.

Aaron M PrairieGraduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523.ORCID 0000-0001-8192-9329
Alison E KingDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523.ORCID 0000-0002-4155-577X
M Francesca CotrufoDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523.ORCID 0000-0002-6191-8953

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sustainability of agricultural production and mitigation of global warming rely on the regeneration of soil organic carbon (SOC), in particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) forms. We conducted a global systematic meta-analysis of the effects of regenerative management practices on SOC, POC, and MAOC in cropland, finding: 1) no-till (NT) and cropping system intensification increase SOC (11.3% and 12.4%, respectively), MAOC (8.5% and 7.1%, respectively), and POC (19.7% and 33.3%, respectively) in topsoil (0 to 20 cm), but not in subsoil (>20 cm); 2) experimental duration, tillage frequency, the intensification type, and rotation diversity moderate the effects of regenerative management; and 3) NT synergized with integrated crop-livestock (ICL) systems to greatly increase POC (38.1%) and cropping intensification synergized with ICL systems to greatly increase MAOC (33.1 to 53.6%). This analysis shows that regenerative agriculture is a key strategy to reduce the soil C deficit inherent to agriculture to promote both soil health and long-term C stabilization.

Indexed as

climate changeregenerative agriculturesoil healthsoil organic carbon

Identifiers

PMID37186829
PMCPMC10214150

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.