We have estimated phylogenies of fungus-growing termites and their associated mutualistic fungi of the genus Termitomyces using Bayesian analyses of DNA sequences. Our study shows that the symbiosis has a single African origin and that secondary domestication of other fungi or reversal of mutualistic fungi to a freeliving state has not occurred. Host switching has been frequent, especially at the lower taxonomic levels, and nests of single termite , is derived with two independent origins. Despite repeated host switching, statistical tests taking phylogenetic uncertainty into account show a significant congruence between the termite and fungal phylogenies, because mutualistic interactions at higher taxonomic levels show considerable specificity. We identify common characteristics of fungus-farming evolution in termites and ants, which apply despite the major differences between these two insect agricultural systems. We hypothesize that biparental colony founding may have constrained the evolution of vertical symbiont transmission in termites but not in ants where males die after mating.

DNA metabarcoding is promising for cost-effective biodiversity monitoring, but reliable diversity estimates are difficult to achieve and validate. Here we present and validate a method, called LULU, for removing erroneous molecular operational taxonomic units (OTUs) from community data derived by high-throughput sequencing of amplified marker genes. LULU identifies errors by combining sequence similarity and co-occurrence patterns. To validate the LULU method, we use a unique data set of high quality survey data of vascular plants paired with plant ITS2 metabarcoding data of DNA extracted from soil from 130 sites in Denmark spanning major environmental gradients. OTU tables are produced with several different OTU definition algorithms and subsequently curated with LULU, and validated against field survey data. LULU curation consistently improves α-diversity estimates and other biodiversity metrics, and does not require a sequence reference database; thus, it represents a promising method for reliable biodiversity estimation.

The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies.Over the past decades, rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats. Yet, in spite of the progress of molecular methods, knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging. In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels. Combining the information from previous efforts such as FUNGuild and Fun Fun together with involvement of expert knowledge, we reannotated 10210 and 151 fungal and Stramenopila genera, respectively. This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera, designed for rapid functional assignments of environmental studies. In order to assign the trait states to fungal species hypotheses, the scientific community of experts manually categorised and assigned available trait information to 697413 fungal ITS sequences. On the basis of those sequences we were able to summarise trait and host information into 92623 fungal species hypotheses at 1% dissimilarity threshold.

Highlights d 49 vertebrate species detected through metabarcoding of airborne eDNA from the zoo d Detections included 30 mammal, 13 bird, 4 fish, 1 amphibian, and 1 reptile species d 6 to 21 vertebrate species were detected per air filtering sample d Shorter geographical distance and higher biomass increased probability of detection

Different distance-based threshold selection approaches were used to assess and compare use of the internal transcribed spacer (ITS) region to distinguish among 901 Cortinarius species represented by >3000 collections. Sources of error associated with genetic markers and selection approaches were explored and evaluated using MOTUs from genus and lineage based-alignments. Our study indicates that 1%-2% more species can be distinguished by using the full-length ITS barcode as compared to either the ITS1 or ITS2 regions alone. Optimal threshold values for different picking approaches and genetic marker lengths inferred from a subset of species containing major lineages ranged from 97.0% to 99.5% sequence similarity using clustering optimization and UNITE SH, and from 1% to 2% sequence dissimilarity with CROP. Errors for the optimal cutoff ranged from 0% to 70%, and these can be reduced to a maximum of 22% when excluding species lacking a barcode gap. A threshold value of 99% is suitable for distinguishing species in the majority of lineages in the genus using the entire ITS region but only 90% of the species could be identified using just the ITS1 or ITS2 region. Prior identification of species, lacking barcode gaps and their subsequent separate analyses, maximized the accuracy of threshold approaches.

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