Evidence map›Paper›PMID 33059667›Full record

ArticleBMC ecology2020

How do genes flow? Identifying potential dispersal mode for the semi-aquatic lichen Dermatocarpon luridum using spatial modelling and photobiont markers.

Jennifer A Doering, Tom Booth, Yolanda F Wiersma, Michele D Piercey-Normore

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In one paragraph

Article in BMC ecology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper 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

4 authors.

Jennifer A DoeringDepartment of Biological Sciences, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada. Jennifer.Doering@umanitoba.ca.ORCID 0000-0002-3181-6518
Tom BoothDepartment of Biological Sciences, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.
Yolanda F WiersmaDepartment of Biology, Memorial University of Newfoundland, St. John's, NL, A1B 3X9, Canada.
Michele D Piercey-NormoreDepartment of Biological Sciences, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada.

Funding

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada CGS-MCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada Discovery
6 · The paper itself

Abstract

backgroundLandscape genetics is an interdisciplinary field that combines tools and techniques from population genetics with the spatially explicit principles from landscape ecology. Spatial variation in genotypes is used to test hypotheses about how landscape pattern affects dispersal in a wide range of taxa. Lichens, symbiotic associations between mycobionts and photobionts, are an entity for which little is known about their dispersal mechanism. Our objective was to infer the dispersal mechanism in the semi-aquatic lichen Dermatocarpon luridum using spatial models and the spatial variation of the photobiont, Diplosphaera chodatii. We sequenced the ITS rDNA and the β-actin gene regions of the photobiont and mapped the haplotype spatial distribution in Payuk Lake. We subdivided Payuk Lake into subpopulations and applied four spatial models based on the topography and hydrology to infer the dispersal mechanism.

resultsGenetic variation corresponded with the topography of the lake and the net flow of water through the waterbody. A lack of isolation-by-distance suggests high gene flow or dispersal within the lake. We infer the dispersal mechanism in D. luridum could either be by wind and/or water based on the haplotype spatial distribution of its photobiont using the ITS rDNA and β-actin markers.

conclusionsWe inferred that the dispersal mechanism could be either wind and/or water dispersed due to the conflicting interpretations of our landscape hypotheses. This is the first study to use spatial modelling to infer dispersal in semi-aquatic lichens. The results of this study may help to understand lichen dispersal within aquatic landscapes, which can have implications in the conservation of rare or threatened lichens.

Indexed as

LichensGene FlowGenetics, PopulationGenotypeSymbiosisDermatocarpon luridumDiplosphaera chodatiiDispersalGenetic variationLichenized algaSemi-aquaticSpatial modelling

Identifiers

PMID33059667
PMCPMC7565318

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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.