Evidence map›Paper›PMID 40963355›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2025

Measuring the socio-economic and environmental outcomes of regenerative agriculture across spatio-temporal scales.

Katherine Berthon, Ruth Wade, Pippa Chapman, Coline C Jaworski, Jonathan R Leake, Niamh McHugh, Lisa Collins, Tim Daniell, Yu Zhao, Penelope Watt and 3 more

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Key action areas for transforming the UK food system: insights from the Transforming UK Food Systems (TUKFS) Programme project portfolio.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
  3. Measuring the socio-economic and environmental outcomes of regenerative agriculture across spatio-temporal scales.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
  4. Food systems transformation: rationale and methodologies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    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

13 authors.

Katherine BerthonDepartment of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.ORCID 0000-0001-8224-2828
Ruth WadeFaculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK.
Pippa ChapmanSchool of Geography, University of Leeds, Leeds LS2 9JT, UK.
Coline C JaworskiUniversité Côte d'Azur, INRAE, Sophia-Antipolis 06560, France.
Jonathan R LeakeSchool of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK.
Niamh McHughGame and Wildlife Conservation Trust, Fordingbridge, Hampshire SP6 1EF, UK.
Lisa CollinsSchool of Bioscience, University of Surrey, Guildford, Surrey GU2 7XH, UK.
Tim DaniellSchool of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK.
Yu ZhaoSchool of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK.
Penelope WattAnimal and Plant Sciences, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0001-5356-6188
Bob DohertySchool for Business and Society, University of York, York YO10 5DD, UK.
Peter JacksonInstitute for Sustainable Food, The University of Sheffield, Sheffield S10 2TN, UK.
Lynn V DicksDepartment of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.ORCID 0000-0002-8304-4468

Funding

Biotechnology and Biological Sciences Research Council BB/V004581/1UKRI Transforming UK Food System Programme BB/V004719/1
6 · The paper itself

Abstract

Regenerative agriculture aims to produce food while simultaneously improving soil health, supporting biodiversity, reducing input costs and enhancing climate resilience. Evidence on its environmental and socio-economic impacts across different systems and climates remains limited, with few studies measuring multiple outcomes following whole farming system transition. To be impactful, regenerative agriculture research must address farmers' knowledge needs and provide practically feasible, economically viable solutions. This can be achieved through action-based research, co-designed with farmer stakeholders in real-world settings. Such research is time-consuming and involves potential risk for farmers adopting new practice combinations. Here, we describe two UK research projects gathering evidence on regenerative agriculture in partnership with farmers, at different scales. One is a replicated large-plot trial that stacks regenerative principles, the other a farmer-led quasi-experiment, following the transition in active farm businesses and using a flexible scoring system based on regenerative principles. We highlight benefits, challenges and future research directions emerging from these projects, including: challenges defining regenerative agriculture; co-design and maximizing knowledge exchange; generalizing results beyond study sites, when practices and outcomes are context-dependent; the need for interdisciplinarity; and generating evidence on long-term transitions with time lags between system change and outcomes, in an environment of short-term funding.This article is part of the theme issue 'Transforming terrestrial food systems for human and planetary health'.

Indexed as

AgricultureConservation of Natural ResourcesEnvironmentFarmersHumansSocioeconomic FactorsUnited Kingdomco-designregenerative agriculturesoil healthsystems approach

Identifiers

PMID40963355
PMCPMC12444378

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.