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Björn D. Lindahl

Researcher at Swedish University of Agricultural Sciences

Publications -  95
Citations -  13084

Björn D. Lindahl is an academic researcher from Swedish University of Agricultural Sciences. The author has contributed to research in topics: Organic matter & Decomposer. The author has an hindex of 40, co-authored 87 publications receiving 10154 citations.

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Towards a unified paradigm for sequence-based identification of fungi

TL;DR: All fungal species represented by at least two ITS sequences in the international nucleotide sequence databases are now given a unique, stable name of the accession number type, and the term ‘species hypothesis’ (SH) is introduced for the taxa discovered in clustering on different similarity thresholds.
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New primers to amplify the fungal ITS2 region – evaluation by 454‐sequencing of artificial and natural communities

TL;DR: Three new primers are described - fITS7, gITS7 and fITS9 - which may be used to amplify the fungal ITS2 region by targeting sites in the 5.8S encoding gene and yielded more diverse amplicon communities than the ITS1f primer.
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Roots and associated fungi drive long-term carbon sequestration in boreal forest.

TL;DR: It is shown that 50 to 70% of stored carbon in a chronosequence of boreal forested islands derives from roots and root-associated microorganisms, suggesting an alternative mechanism for the accumulation of organic matter in boreal forests during succession in the long-term absence of disturbance.
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Spatial separation of litter decomposition and mycorrhizal nitrogen uptake in a boreal forest

TL;DR: Observations show that the degrading and nutrient-mobilizing components of the fungal community are spatially separated, which has important implications for biogeochemical studies of boreal forest ecosystems.
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Fungal community analysis by high-throughput sequencing of amplified markers - a user's guide

TL;DR: Taking advantage of the collective experience of six research groups, the different stages involved in fungal community analysis are reviewed, from field sampling via laboratory procedures to bioinformatics and data interpretation, and potential pitfalls, alternatives, and solutions are discussed.