ArticleEcology letters2026
Detection of Eco-Evolutionary Dynamics in Communities Using Joint Species Distribution Models.
Article in Ecology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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
1 citing paper in PubMed.
- Detection of Eco-Evolutionary Dynamics in Communities Using Joint Species Distribution Models.Ecology letters · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biodiversity at the metacommunity scale is typically influenced by numerous environmental, spatial, biotic, and stochastic factors. These factors can simultaneously impact evolution in individual species, due to site-varying local selection pressures and the impact of connectivity for gene flow and genetic drift. Joint species distribution models (JSDMs) can estimate the relative impacts of environmental, spatial, biotic, and other drivers on community composition, but these models do not currently consider the impact of contemporary evolutionary change. We applied a JSDM to analyse simulated and experimental populations and communities that experience contemporary trait evolution. We found that it successfully partitioned variance contributed by environmental, spatial, and evolving phenotypic drivers, and also estimated site- and time-specific covariance. We further demonstrated how the model-estimated effect sizes of trait evolution for community composition can be used to test predictions about the underlying mechanistic drivers of eco-evolutionary dynamics in communities.
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Registered trials
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.