ArticleProceedings of the National Academy of Sciences of the United States of America2024
Microevolutionary change in wild stickleback: Using integrative time-series data to infer responses to selection.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Spatial variation and individual specialization of stickleback diet in relation to trophic morphology.Aquatic ecology · 2026Article
- Joining forces to push past paradoxes: Combining quantitative genetics and genomics shows evolution hiding in plain sight.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Microevolutionary change in wild stickleback: Using integrative time-series data to infer responses to selection.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
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7 authors.
Funding
Abstract
A central goal in evolutionary biology is to understand how different evolutionary processes cause trait change in wild populations. However, quantifying evolutionary change in the wild requires linking trait change to shifts in allele frequencies at causal loci. Nevertheless, datasets that allow for such tests are extremely rare and existing theoretical approaches poorly account for the evolutionary dynamics that likely occur in ecological settings. Using a decade-long integrative phenome-to-genome time-series dataset on wild threespine stickleback (
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Registered trials
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