Evidence map›Paper›PMID 40435169›Full record

ArticlePloS one2025

On the coincidence of weather extremes and geopolitical conflicts: Risk analysis in regional food markets.

Nkongho Ayuketang Arreyndip, Jeremy S Pal

Abstract read
In one paragraph

Article in PloS one, 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. Review
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

2 authors.

Nkongho Ayuketang ArreyndipDepartment of Environmental Sciences, Informatics, and Statistics, Ca' Foscari University of Venice, Venice, Italy.ORCID https://orcid.org/0000-0002-5316-4063
Jeremy S PalRAAS-CMCC Risk Assessment and Adaptation Strategies, Institute of Climate Resilience, Lecce, Italy.ORCID https://orcid.org/0000-0002-5937-0319

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the recent increase in geopolitical tensions between major agricultural producers and weather extremes, there is a likelihood that geopolitical conflict will occur simultaneously with weather extremes, leading to devastating production losses between the conflicting parties. These losses can affect the entire food supply chain, leading to food shortages and price increases in regional markets. This paper models the impact of these concurrent events on the global food market, using the Russian-Ukrainian war and the extreme heatwaves of summer 2022 as a case study. The model considers four war scenarios: the start of the invasion, the peak of the war, Ukraine's resistance, sanctions against Russia, and refugee crises in Europe. Using data from the US Department of Agriculture (USDA), Statista, WITS, and Acclimate production value losses, the results show that the agricultural sectors of southern European countries such as France, Italy, and Spain were the most affected by the extreme events, although the direct impact of refugees was smaller compared to their northern counterparts. Strict sanctions against Russia coupled with Ukraine's resistance will benefit EU food markets, but at the same time the agricultural sectors of smaller countries and weaker economies, particularly those of Russia's allies, will be highly vulnerable. This study suggests that when developing and adopting conflict resolution strategies, their impact on weak economies should not be overlooked. An example of this policy recommendation is the continuous renewal of the Black Sea Grain Initiative to stabilize global food prices.

Indexed as

Extreme WeatherFood SupplyWeatherAgricultureCommerceEuropeHumansRisk AssessmentRussiaUkraine

Identifiers

PMID40435169
PMCPMC12118916

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Registered trials

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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.