Evidence map›Paper›PMID 40964865›Full record

ArticlePest management science2026

Predicting the seasonal distribution of fall armyworm in North America using species distribution models.

Fan-Qi Gao, Robert L Meagher, Rodney N Nagoshi, Jason W Chapman, Regan Early

Abstract read
In one paragraph

Article in Pest management science, 2026. 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

5 authors.

Fan-Qi GaoCentre for Ecology and Conservation, University of Exeter, Cornwall, UK.ORCID https://orcid.org/0009-0009-6749-4272
Robert L MeagherCenter for Medical, Agricultural and Veterinary Entomology, Agricultural Research Service, US Department of Agriculture, Gainesville, FL, USA.
Rodney N NagoshiCenter for Medical, Agricultural and Veterinary Entomology, Agricultural Research Service, US Department of Agriculture, Gainesville, FL, USA.
Jason W ChapmanCentre for Ecology and Conservation, University of Exeter, Cornwall, UK.
Regan EarlyCentre for Ecology and Conservation, University of Exeter, Cornwall, UK.ORCID https://orcid.org/0000-0003-4108-5904

Funding

China Scholarship CouncilUniversity of Exeter
6 · The paper itself

Abstract

backgroundSpecies distribution models (SDMs) are widely used in pest management to predict outbreak areas. Migratory pests cause seasonal crop damage through long-distance migration, making it crucial to understand their seasonal activity when estimating outbreak regions. Fall armyworm (FAW), a highly migratory pest, was studied using SDMs to predict its seasonal distribution in the central and eastern USA and explore the environmental factors influencing its distribution.

resultsWe used monthly environmental and species distribution data to model each month or season individually. Based on model results, the suitable habitat for FAW expands rapidly in summer, covering most of the central and eastern USA in July and August, and then begins to contract in September. Based on the environmental variables included in models for different seasons, FAW distribution in winter is mainly influenced by minimum temperature. In spring, rainfed corn cultivation area and Normalized Difference Vegetation Index (NDVI) also play important roles. In summer, minimum temperature is no longer important, and the main factors are precipitation, evapotranspiration, rainfed corn cultivation area, and NDVI. In autumn, minimum temperature becomes important again, while rainfed corn cultivation area is no longer a key factor.

conclusionThis study indicates that FAW may have outbreaks across the central and eastern USA in July and August, emphasizing the necessity of implementing early large-scale pest control. Using separate models for each season, rather than a single model to predict whether seasonal distribution could improve prediction accuracy by identifying key environmental variables in each season and refining niche characterization. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Indexed as

Animal DistributionSpodopteraAnimalsEcosystemModels, BiologicalNorth AmericaSeasonsenvironmental niche modelsinsect migrationrealized nicheseasonal habitatSpodoptera frugiperda

Identifiers

PMID40964865
PMCPMC12713716

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.