Evidence map›Paper›PMID 39083607›Full record

ArticleScience advances2024

An unprecedented fall drought drives Dust Bowl-like losses associated with La Niña events in US wheat production.

Lina Zhang, Haidong Zhao, Nenghan Wan, Guihua Bai, M B Kirkham, John W Nielsen-Gammon, Thomas J Avenson, Romulo Lollato, Vaishali Sharda, Amanda Ashworth and 2 more

Abstract read
In one paragraph

Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

12 authors.

Lina ZhangDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-3413-9946
Haidong ZhaoDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0003-0354-4460
Nenghan WanDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.
Guihua BaiDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-1194-319X
M B KirkhamDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0001-9518-3548
John W Nielsen-GammonDepartment of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0001-5336-2409
Thomas J AvensonVindara Inc., Orlando, FL 32812, USA.ORCID 0000-0001-7948-8827
Romulo LollatoDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0001-8615-0074
Vaishali ShardaCarl and Melinda Helwig Department of Biological and Agricultural Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-4048-0884
Amanda AshworthUSDA, Agricultural Research Service, Poultry Production and Product Safety Research Unit, Fayetteville, AR 72701, USA.ORCID 0000-0002-3218-8939
Prasanna H GowdaUSDA, Agricultural Research Service, Southeast Area, Stoneville, MS 38776, USA.
Xiaomao LinDepartment of Agronomy, 2004 Throckmorton Plant Sciences Center, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-0804-7853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unprecedented precipitation deficits in the 2022-2023 growing season across the primary wheat-producing region in the United States caused delays in winter wheat emergence and poor crop growth. Using an integrated approach, we quantitatively unraveled a 37% reduction in wheat production as being attributable to both per-harvested acre yield loss and severe crop abandonment, reminiscent of the Dust Bowl years in the 1930s. We used random forest machine learning and game theory analytics to show that the main driver of yield loss was spring drought, whereas fall drought dominated abandonment rates. Furthermore, results revealed, across the US winter wheat belt, the La Niña phase of the El Niño Southern Oscillation (ENSO), increased abandonment rates compared to the El Niño phase. These findings underscore the necessity of simultaneously addressing crop abandonment and yield decline to stabilize wheat production amid extreme climatic conditions and provide a holistic understanding of global-scale ENSO dynamics on wheat production.

Indexed as

DroughtsEl Nino-Southern OscillationTriticumCrops, AgriculturalSeasonsUnited States

Identifiers

PMID39083607
PMCPMC11290491

What OpenQuestion holds

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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.