Evidence map›Paper›PMID 41408038›Full record

ArticleNature communications2025

Climate-crop models to support opportunity crop adaptation in Africa.

Meijian Yang, Jose Rafael Guarin, Bright S Freduah, Gershom O Wesley, Dilys S MacCarthy, Stephen Narh, Andres Castellano, Jonas Jägermeyr, Kevin Karl, Elena Mendez Leal and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Meijian Yang *Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA. my2824@columbia.edu.ORCID http://orcid.org/0000-0002-0704-7835
Jose Rafael Guarin *Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA. jose.r.guarin@nasa.gov.ORCID http://orcid.org/0000-0002-3167-4329
Bright S FreduahSoil and Irrigation Research Centre, School of Agriculture, College of Basic and Applied Sciences, University of Ghana, Kpong, Ghana.ORCID http://orcid.org/0000-0002-4147-0485
Gershom O WesleySoil and Irrigation Research Centre, School of Agriculture, College of Basic and Applied Sciences, University of Ghana, Kpong, Ghana.ORCID http://orcid.org/0009-0008-8316-2588
Dilys S MacCarthySoil and Irrigation Research Centre, School of Agriculture, College of Basic and Applied Sciences, University of Ghana, Kpong, Ghana.ORCID http://orcid.org/0000-0002-8062-3499
Stephen NarhSoil and Irrigation Research Centre, School of Agriculture, College of Basic and Applied Sciences, University of Ghana, Kpong, Ghana.
Andres CastellanoAutonomic Integra, Bethesda, MD, USA.
Jonas JägermeyrCenter for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA.
Kevin KarlCenter for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA.
Elena Mendez LealCenter for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA.
Senthold AssengSchool of Life Sciences, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany.ORCID http://orcid.org/0000-0002-7583-3811
Chuang ZhaoCollege of Resources and Environmental Sciences, China Agricultural University, Beijing, China.ORCID http://orcid.org/0000-0002-9535-8181
Alex C RuaneNASA Goddard Institute for Space Studies, New York, NY, USA.ORCID http://orcid.org/0000-0002-5582-9217
Cynthia E RosenzweigCenter for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY, USA.ORCID http://orcid.org/0000-0002-8541-2201

Funding

Rockefeller Foundation 2023 FCW 004
6 · The paper itself

Abstract

In an era marked by climatic uncertainties and burgeoning food security challenges, climate-crop models emerge as important tools for guiding investments in climate-resilient agriculture. Here, we construct climate-crop model applications for 24 crops spanning the African food basket, including cereals, legumes, oilseeds, roots/tubers, and vegetables, in support of the Vision for Adapted Crops & Soils (VACS) program. Notably, we expand the modeling framework for 19 "opportunity" crops that have hitherto been underrepresented or overlooked but hold potential to bolster agricultural resilience across the continent. We calibrate and parameterize our process-based models using field observations and comprehensive literature reviews. We evaluate the model outputs spatially and temporally against national crop statistics across Africa, showing acceptable reproduction of yields and response to reported extreme droughts and heat waves. This work offers a scalable framework for climate-crop modeling and impact assessments related to food security in Africa and beyond.

Indexed as

Climate ModelsCrops, AgriculturalAfricaAgricultureClimateClimate ChangeDroughtsFood SecurityFood Supply

Identifiers

PMID41408038
PMCPMC12711928

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.