ArticleThe New phytologist2026
Biogeography and host associations of Russula subsection Xerampelinae based on large-scale analysis of UNITE sequence data.
Article in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Global distribution and biogeography of ericoid mycorrhizal fungi.The New phytologist · 2026Article
- Limitations of Common Molecular Markers in Fungal Biodiversity Analysis and the Benefits of Their Synergistic Use.Molecular ecology resources · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Estimating fungal geographic ranges and niche potential is limited by the ephemeral nature of fruiting bodies. While environmental DNA offers broader insights, species-level identification remains difficult due to uncertain sequence clustering thresholds, low interspecific variation in barcoding regions, and limited taxonomic resolution. To address this, we analyzed large-scale environmental sequence data to investigate biogeographic patterns and ectomycorrhizal host associations in Russula subsection Xerampelinae, a group widely distributed across boreal and arctic ecosystems. We used maximum likelihood phylogenetic methods to identify internal transcribed spacer sequences from the UNITE database for 13 previously defined Russula species. Additionally, we retrieved sequence-associated metadata on locality and host association from PlutoF. In total, 1363 sequences were resolved in clades with our target species, expanding known distributions and plant host associations. Integrating environmental metadata with phylogenetic analyses revealed widespread distributions and host generalism across the Northern Hemisphere. However, UNITE's species hypotheses clustering thresholds often failed to reflect phylogenetically defined species boundaries, even at conservative levels. Our phylogeny-based assignment approach applied on metabarcoding data improves species resolution and biogeographic inference, providing a step-by-step workflow for sequence-based identification and for addressing ecologically and evolutionarily driven research questions.
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