Evidence map›Paper›PMID 41779071›Full record

ArticleMicrobial ecology2026

Metabarcoding Reveals Rich and Diverse Aeromycobiota in Protected Oak Forests.

Vaidotas Lygis, Adas Marčiulynas, Teodora Plepytė, Sigitas Šulčius, Audrius Menkis

Abstract read
In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
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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

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

5 authors.

Vaidotas LygisState Scientific Research Institute Nature Research Centre, Akademijos str. 2, Vilnius, LT- 08412, Lithuania.
Adas MarčiulynasInstitute of Forestry, Lithuanian Research Centre for Agriculture and Forestry, Liepų str. 1, Girionys, Kaunas, LT-53101, Lithuania.
Teodora PlepytėState Scientific Research Institute Nature Research Centre, Akademijos str. 2, Vilnius, LT- 08412, Lithuania.
Sigitas ŠulčiusState Scientific Research Institute Nature Research Centre, Akademijos str. 2, Vilnius, LT- 08412, Lithuania.
Audrius MenkisDepartment of Forest Mycology and Plant Pathology, Uppsala BioCenter, Swedish University of Agricultural Sciences, P.O. Box 7026, Uppsala, SE-75007, Sweden. audrius.menkis@slu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Old-growth oak (Quercus robur) forests in Europe are biodiversity hotspots, yet their airborne fungal diversity remains poorly studied. We investigated aeromycobiota in three Lithuanian oak stands (Punia, Dūkštos and Šilinė) using passive spore traps combined with DNA metabarcoding. Weekly sampling between August and September 2022 yielded 75 spore samples, producing 262,755 high-quality fungal sequences clustered into 1,881 operational taxonomic units (OTUs) representing six phyla and 36 classes. Ascomycota (53.1% of OTUs) and Basidiomycota (44.3%) dominated in richness, while Basidiomycota prevailed in relative sequence abundance (62.8%). Major taxa included Exobasidiaceae sp., Cladosporium sp., Melampsora sp., and Thelephora terrestris. Airborne fungal communities exhibited a substantial core assemblage shared among stands, accompanied by stand-associated differences in species richness and relative sequence abundance. The Punia stand showed the highest richness and the greatest proportion of stand-specific OTUs. Temporal variation was detectable but moderate relative to spatial differences among stands. Functional guild analysis revealed dominance of saprotrophs (46.5% of assigned OTUs), followed by pathotrophs (14.5%) and symbiotrophs (13.2%). Overall, our results demonstrate that passive spore traps-based airborne metabarcoding captures high fungal diversity and resolves both widespread and stand-associated community patterns in old-growth oak forests. This study provides the first characterization of aeromycobiota in old-growth Q. robur forests of Northern Europe and highlights the value of airborne metabarcoding for fungal biodiversity assessment and long-term forest monitoring.

Indexed as

Air MicrobiologyBiodiversityFungiQuercusAscomycotaBasidiomycotaDNA Barcoding, TaxonomicDNA, FungalForestsLithuaniaPhylogenySpores, FungalDNA, FungalAirborne Fungal CommunitiesHigh-Throughput SequencingOld-Growth ForestPassive Spore TrapsSpecies RichnessSpore Deposition

Identifiers

PMID41779071
PMCPMC13065563

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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.