ArticleEcology and evolution2025
Predicting the Phenology of Herbivorous Insects.
Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Epitranscriptomics as a Candidate Universal Modulator of Dormancy Transitions.Ecology and evolution · 2026Review
- Predicting the Phenology of Herbivorous Insects.Ecology and evolution · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Models of herbivorous insect phenology can be used to make agriculture more sustainable and to better manage the effects of climate change on natural communities. The phenology of herbivorous insects depends on heat time, but exactly how it varies across populations and the causes of this variation are unclear. Here, with multilevel Bayesian models, we performed a comparative analysis of 601 published herbivorous insect phenology models. We found that variation in herbivorous insect phenology can be explained by variation in phylogenetic relatedness, adult body size, feeding site, host plant taxonomy, geographic location, and the approaches that researchers used for model parameterization. Contrary to previous analysis, we also found that the minimum temperature required for development varies across life stages in a way that could be adaptive. Our analysis demonstrates that by accounting for more information on the variation across insect populations and their environments, we can make better and more generalizable predictions of herbivorous insect phenology.
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Registered trials
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