Unexpectedly high beta-diversity of root-associated fungal communities in the Bolivian Andes

Bolivia is one of the most biologically diverse countries on the planet. Between the Andes and the Amazon drainage basin spans the Yungas, a vast forested region shown to be extremely species rich in macro-organisms. However, it remains unclear whether this high diversity is also reflected in microbial diversity. Here we assess the genetic, taxonomic and functional diversity of root-associated fungi surrounding Cinchona calisaya calisaya trees, a typical element of the intermediate altitudes of the Bolivian Yungas. We determine the relative effects of edaphic properties, climate, and geography in regulating fungal community assembly. We show that α-diversity for these fungal communities was similar to temperate and arid ecosystems, averaging 90.1 operational taxonomic units (OTUs) per sample, with reads predominantly assigned to the Ascomycota phylum and with a saprotrophic lifestyle. ß-diversity was calculated as the distance-decay rate, and in contrast to α-diversity, was exceptionally high with a rate of -0.407. Soil properties (pH and P) principally regulated fungal community assembly in an analogous manner to temperate environments, with pH and phosphorus explaining 7.8 % and 7.2 % of community variation respectively. Surprisingly, altitude does not influence community formation, and there is limited evidence that climate (precipitation and temperature) play a role. Our results suggest that sampling should be performed over a wide geographical and environmental range in order to capture the full root-associated fungal diversity in subtropical regions. This study sheds further light on the diversity and distribution of the world's hidden biodiversity

Prototype biodiversity digital twin: prioritisation of DNA metabarcoding sampling locations

Advancements in environmental DNA (eDNA) metabarcoding have revolutionised our capacity to assess biodiversity, especially for cryptic or less-studied organisms, such as fungi, bacteria and micro-invertebrates. Despite its cost-effectiveness, the spatial selection for sampling sites remains a critical challenge due to the considerable time and resources required for processing and analysing eDNA samples. This study introduces a Biodiversity Digital Twin Prototype, aimed at optimising the selection and prioritisation of eDNA sampling locations. Leveraging available eDNA data and integrating user-defined criteria, this digital twin facilitates informed decision-making in selecting future sampling sites. Through the development of an associated data formatting tool, we also facilitate the accessibility and utility of DNA metabarcoding data for broader conservation efforts. This prototype will serve multiple end-users, from researchers and monitoring initiatives to commercial enterprises, by providing an intuitive interface for interactive exploration and prioritisation, based on estimated complementarity of future samples. The prototype offers a scalable approach to biodiversity sampling. Ultimately, this tool aims to refine our understanding of global biodiversity patterns and support targeted conservation strategies through efficient eDNA sampling

Predicting provenance of forensic soil samples:linking soil to ecological habitats by metabarcoding and supervised classification

Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA metabarcoding in predicting provenance in terms of environmental conditions, habitat type and geographic regions. We used linear regression for predicting environmental gradients of light, soil moisture, pH and nutrient status (represented by Ellenberg Indicator Values, EIVs) and Quadratic Discriminant Analysis (QDA) to predict habitat type and geographic region. eDNA data performed relatively well as a predictor of environmental gradients (R2 > 0.81). Its ability to discriminate between habitat types was variable, with high accuracy for certain forest types and low accuracy for heathland, which was poorly predicted. Geographic region was also less accurately predicted by eDNA. We demonstrated the application of provenance prediction in forensic science by evaluating and discussing two mock crime scenes. Here, we listed the plant species from annotated sequences, which can further aid in identifying the likely habitat or, in case of rare species, a geographic region. Predictions of environmental gradients and habitat types together give an overall accurate description of a crime scene, but care should be taken when interpreting annotated sequences, e.g. due to erroneous assignments in GenBank. Our approach demonstrates that important habitat properties can be derived from soil eDNA, and exemplifies a range of potential applications of eDNA in forensic ecology

Taxonomy and phylogeny of the phlegmacioid clade Camptori (Cortinarius s.l., Basidiomycota) in Europe with description of four new species

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A systematic survey of regional multi-taxon biodiversity:evaluating strategies and coverage

Abstract Background In light of the biodiversity crisis and our limited ability to explain variation in biodiversity, tools to quantify spatial and temporal variation in biodiversity and its underlying drivers are critically needed. Inspired by the recently published ecospace framework, we developed and tested a sampling design for environmental and biotic mapping. We selected 130 study sites (40 × 40 m) across Denmark using stratified random sampling along the major environmental gradients underlying biotic variation. Using standardized methods, we collected site species data on vascular plants, bryophytes, macrofungi, lichens, gastropods and arthropods. To evaluate sampling efficiency, we calculated regional coverage (relative to the known species number per taxonomic group), and site scale coverage (i.e., sample completeness per taxonomic group at each site). To extend taxonomic coverage to organisms that are difficult to sample by classical inventories (e.g., nematodes and non-fruiting fungi), we collected soil for metabarcoding. Finally, to assess site conditions, we mapped abiotic conditions, biotic resources and habitat continuity. Results Despite the 130 study sites only covering a minute fraction (0.0005%) of the total Danish terrestrial area, we found 1774 species of macrofungi (54% of the Danish fungal species pool), 663 vascular plant species (42%), 254 bryophyte species (41%) and 200 lichen species (19%). For arthropods, we observed 330 spider species (58%), 123 carabid beetle species (37%) and 99 hoverfly species (33%). Overall, sample coverage was remarkably high across taxonomic groups and sufficient to capture substantial spatial variation in biodiversity across Denmark. This inventory is nationally unprecedented in detail and resulted in the discovery of 143 species with no previous record for Denmark. Comparison between plant OTUs detected in soil DNA and observed plant species confirmed the usefulness of carefully curated environmental DNA-data. Correlations among species richness for taxonomic groups were predominantly positive, but did not correlate well among all taxa suggesting differential and complex biotic responses to environmental variation. Conclusions We successfully and adequately sampled a wide range of diverse taxa along key environmental gradients across Denmark using an approach that includes multi-taxon biodiversity assessment and ecospace mapping. Our approach is applicable to assessments of biodiversity in other regions and biomes where species are structured along environmental gradient

The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes : sequences, taxa and classifications reconsidered

Acknowledgements We acknowledge Marie Zirk for her work in designing the UNITE logotype and creating the visual abstract for this article. Funding UNITE database development is financed by the Estonian Research Council [PRG1170]; European Union's Horizon 2020 project BGE [101059492]. The PlutoF digital infrastructure is supported by the European Union's Horizon 2020 project BiCIKL [101007492]; Estonian Research Infrastructure roadmap project DiSSCo Estonia. Funding for open access charge: UNITE Community. Conflict of interest statement. None declared.Peer reviewedPublisher PD