Evidence map›Paper›PMID 34097819›Full record

ArticleMolecular ecology resources2021

Disentangling adaptation from drift in bottlenecked and reintroduced populations of Alpine ibex.

Deborah M Leigh, Heidi E L Lischer, Frédéric Guillaume, Christine Grossen, Torsten Günther

Abstract read
In one paragraph

Article in Molecular ecology resources, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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.

Deborah M LeighWSL Swiss Federal Research Institute, Birmensdorf, Switzerland.ORCID https://orcid.org/0000-0003-3902-2568
Heidi E L LischerInterfaculty Bioinformatics Unit, University of Bern, Bern, Switzerland.ORCID https://orcid.org/0000-0002-9616-2092
Frédéric GuillaumeDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-0874-0081
Christine GrossenDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-4157-1910
Torsten GüntherHuman Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.ORCID https://orcid.org/0000-0001-9460-390X

Funding

Universität Zürich
6 · The paper itself

Abstract

Identifying local adaptation in bottlenecked species is essential for conservation management. Selection detection methods have an important role in species management plans, assessments of adaptive capacity, and looking for responses to climate change. Yet, the allele frequency changes exploited in selection detection methods are similar to those caused by the strong neutral genetic drift expected during a bottleneck. Consequently, it is often unclear what accuracy selection detection methods have across bottlenecked populations. In this study, simulations were used to explore if signals of selection could be confidently distinguished from genetic drift across 23 bottlenecked and reintroduced populations of Alpine ibex (Capra ibex). The meticulously recorded demographic history of the Alpine ibex was used to generate comprehensive simulated SNP data. The simulated SNPs were then used to benchmark the confidence we could place in outliers identified in empirical Alpine ibex RADseq derived SNP data. Within the simulated data set, the false positive rates were high for all selection detection methods (F

Indexed as

Genetic DriftGenetics, PopulationAnimalsGene FrequencyGoatsbottleneckconservationevolutionary managementoutlierreintroduction

Identifiers

PMID34097819
PMCPMC8518545

What OpenQuestion holds

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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.