Evidence map›Paper›PMID 42680827›Full record

ArticleHeredity2026

Joint analysis of microsatellites and flanking sequences shows shared demographic response of coastal sand dune plant communities to past environmental changes.

Olivier Lepais, Maya Gonzalez, Marie-Lise Benot

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Article in Heredity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Olivier LepaisBIOGECO, Univ. Bordeaux, INRAE, Pessac, France. olivier.lepais@inrae.fr.
Maya GonzalezISPA, Bordeaux Sciences Agro, INRAE, Villenave-d'Ornon, France.ORCID http://orcid.org/0000-0002-5589-3227
Marie-Lise BenotBIOGECO, Univ. Bordeaux, INRAE, Pessac, France.

Funding

Agence Nationale de la Recherche (French National Research Agency) Cluster of Excellence COTE (ANR-10-LABX-45) DuneBioDiv project
6 · The paper itself

Abstract

Understanding recent change in effective population size is crucial to evaluate how specie respond to environmental modifications and their ability to adapt to global changes. However, the impact of past environmental change on the demography history of species communities has rarely been studied across multiple species, members of the same community sharing the same habitat. In this study, we compare historical change in effective population size across eight species of coastal sand dune plant communities along the coastal dune in Southwest France. We developed and sequenced species-specific microsatellite markers to genotype 3116 individuals. In an attempt to increase temporal resolution, we integrate both fast (microsatellite repeat number) and slow (substitution in flanking sequence) mutating polymorphisms to infer demographic parameters of a simple model of a single population size change in the past using coalescent simulations and approximate Bayesian computations. Recent and ancient effective population sizes were well inferred and informed by allelic richness at microsatellites and heterozygosity at flanking sequence respectively. The timing of event was more difficult to estimate, but benefit from summary statistics combining microsatellite variation and flanking substitutions. Most species showed a synchronous and strong decline dating back from 135 to 450 years ago, overlapping with the Little Ice Age during which high storminess caused sand drift that probably wiped out most of the open sand dune vegetation, which is now restricted along the shoreline. Historical habitat loss led to community level decline in effective population size that will constrain future sand dune plant responses.

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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.