Fungal community composition predicts forest carbon storage at a continental scale

Mark A. Anthony,Leho Tedersoo, Bruno De Vos,Luc Croise, Henning Meesenburg,Markus Wagner, Henning Andreae, Frank Jacob,Pawel Lech, Anna Kowalska, Martin Greve, Genoveva Popova,Beat Frey, Arthur Gessler,Marcus Schaub, Marco Ferretti,Peter Waldner, Vicent Calatayud, Roberto Canullo, Giancarlo Papitto,Aleksander Marinsek, Morten Ingerslev,Lars Vesterdal,Pasi Rautio, Helge Meissner, Volkmar Timmermann, Mike Dettwiler, Nadine Eickenscheidt,Andreas Schmitz, Nina Van Tiel, Thomas W. Crowther,Colin Averill

NATURE COMMUNICATIONS(2024)

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摘要
Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack of paired data on microbiome diversity and in situ observations of forest carbon accumulation and storage. Here, we investigated the relationship between soil microbiomes and forest carbon across 238 forest inventory plots spanning 15 European countries. We show that the composition and diversity of fungal, but not bacterial, species is tightly coupled to both forest biotic conditions and a seven-fold variation in tree growth rates and biomass carbon stocks when controlling for the effects of dominant tree type, climate, and other environmental factors. This linkage is particularly strong for symbiotic endophytic and ectomycorrhizal fungi known to directly facilitate tree growth. Since tree growth rates in this system are closely and positively correlated with belowground soil carbon stocks, we conclude that fungal composition is a strong predictor of overall forest carbon storage across the European continent. Soil microbial diversity and composition is thought to play a major role in elemental cycling. Here, the authors analyse a large dataset of soil microbiome and carbon data from European forests and find that soil fungal community composition is a strong predictor of carbon storage.
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