The nuclear ribosomal internal transcribed spacer (ITS) region is the formal fungal barcode and in most cases the marker of choice for the exploration of fungal diversity in environmental samples. ...Two problems are particularly acute in the pursuit of satisfactory taxonomic assignment of newly generated ITS sequences: (i) the lack of an inclusive, reliable public reference data set and (ii) the lack of means to refer to fungal species, for which no Latin name is available in a standardized stable way. Here, we report on progress in these regards through further development of the UNITE database (http://unite.ut.ee) for molecular identification of fungi. 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 (e.g. Hymenoscyphus pseudoalbidus|GU586904|SH133781.05FU), and their taxonomic and ecological annotations were corrected as far as possible through a distributed, third‐party annotation effort. We introduce the term ‘species hypothesis’ (SH) for the taxa discovered in clustering on different similarity thresholds (97–99%). An automatically or manually designated sequence is chosen to represent each such SH. These reference sequences are released (http://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and in the QIIME pipeline. The system and the data will be updated automatically as the number of public fungal ITS sequences grows. We invite everybody in the position to improve the annotation or metadata associated with their particular fungal lineages of expertise to do so through the new Web‐based sequence management system in UNITE.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The genus Hebeloma is renowned as difficult when it comes to species determination. Historically, many dichotomous keys have been published and used with varying success rate. Over the last 20 years ...the authors have built a database of Hebeloma collections containing not only metadata but also parametrized morphological descriptions, where for about a third of the cases micromorphological characters have been analysed and are included, as well as DNA sequences for almost every collection. The database now has about 9000 collections including nearly every type collection worldwide and represents over 120 different taxa. Almost every collection has been analysed and identified to species using a combination of the available molecular and morphological data in addition to locality and habitat information. Based on these data an Artificial Intelligence (AI) machine-learning species identifier has been developed that takes as input locality data and a small number of the morphological parameters. Using a random test set of more than 600 collections from the database, not utilized within the set of collections used to train the identifier, the species identifier was able to identify 77% correctly with its highest probabilistic match, 96% within its three most likely determinations and over 99% of collections within its five most likely determinations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Hebeloma section Denudata includes the majority of the taxa commonly referred to as the Hebeloma crustuliniforme complex. In a recent paper we described in detail H. subsection Denudata and fifteen ...European species recognised within this subsection, using morphological and molecular methods. In this paper we continue this work and describe in detail three additional subsections and several new species. Within H. subsection Hiemalia we recognise just one species, Hebeloma hiemale. Here we propose an epitype in order to unambiguously define this taxon. Nine species occurring in Europe are assigned to H. subsect. Clepsydroida, namely Hebeloma ammophilum, H. cavipes, H. fragilipes, H. ingratum, H. laetitiae, H. limbatum sp. nov., H. matritense sp. nov., H. pseudofragilipes sp. nov., and H. vaccinum. Finally, we introduce H. subsection Echinospora with three species: Hebeloma echinosporum sp. nov., H. populinum, and H. rostratum sp. nov. We provide descriptions of all three of these species in order to clarify the taxonomy of this section. We provide a key to H. sect. Denudata and the discussed subsections. For the majority of the taxa there is good overall consistency between morphological and phylogenetic delimitation and, where the information exists, thanks to Aanen and Kuyper's work, biological delimitation.
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•Cheilocystidia shapes are important for delimiting infrageneric taxa in Hebeloma.•Up to six loci were sequenced of 270 collections to test subsection and species limits.•Five new species and two new subsections are described.•Good overall consistency between morphological and phylogenetic taxon limits.•Also consistency with intercompatibility groups of Aanen & Kuyper where data exist.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Attempts to use machine learning (ML) for species identification of macrofungi have usually involved the use of image recognition to deduce the species from photographs, sometimes combining this with ...collection metadata. Our approach is different: we use a set of quantified morphological characters (for example, the average length of the spores) and locality (GPS coordinates). Using this data alone, the machine can learn to differentiate between species.
Our case study is the genus
Hebeloma
, fungi within the order Agaricales, where species determination is renowned as a difficult problem. Whether it is as a result of recent speciation, the plasticity of the species, hybridization or stasis is a difficult question to answer. What is sure is that this has led to difficulties with species delimitation and consequently a controversial taxonomy.
The Hebeloma Project—our attempt to solve this problem by rigorously understanding the genus—has been evolving for over 20 years. We began organizing collections in a database in 2003. The database now has over 10,000 collections, from around the world, with not only metadata but also morphological descriptions and photographs, both macroscopic and microscopic, as well as molecular data including at least an internal transcribed spacer (ITS) sequence (generally, but not universally, accepted as a DNA barcode marker for fungi (Schoch et al. 2012)), and in many cases sequences of several loci. Included within this set of collections are almost all type specimens worldwide. The collections on the database have been analysed and compared. The analysis uses both the morphological and molecular data as well as information about habitat and location. In this way, almost all collections are assigned to a species. This development has been enabled and assisted by citizen scientists from around the globe, collecting and recording information about their finds as well as preserving material.
From this database, we have built a website, which updates as the database updates. The website (hebeloma.org) is currently undergoing beta testing prior to a public launch. It includes up-to-date species descriptions, which are generated by amalgamating the data from the collections of each species in the database. Additional tools allow the user to explore those species with similar habitat preferences, or those from a particular biogeographic area. The user is also able to compare a range of characters of different species via an interactive plotter.
The ML-based species identifier is featured on the website. The standardised storage of the collection data on the database forms the backbone for the identifier. A portion of the collections on the database are (almost) randomly selected as a training set for the learning phase of the algorithm. The learning is “supervised” in the sense that collections in the training set have been pre-assigned to a species by expert analysis. With the learning phase complete, the remainder of the database collections may then be used for testing. To use the species identifier on the website, a user inputs the same small number of morphological characters used to train the tool and it promptly returns the most likely species represented, ranked in order of probability.
As well as describing the neural network behind the species identifier tool, we will demonstrate it in action on the website, present the successful results it has had in testing to date and discuss its current limitations and possible generalizations.
Between 1960 and 2009, regular visits to Svalbard were made and a number of Hebeloma spp. were collected by several mycologists. We have studied 249 such collections, many from the Herbarium in Oslo ...(O) and from the private herbarium of the first author. The collections represent 17 different species. Of the 17 species, five (H. louiseae, H. pallidolabiatum, H. perexiguum, H. pubescens and H. spetsbergense) are only known from Svalbard. In this paper we discuss the habitat and apparent associates of the 17 species recorded, as well as their frequency of occurrence within our sample, and compare this with our data from other regions of the northern hemisphere. A further analysis compares the records we have from the collection of basidiomes with data published from root analysis of mycorrhizal associates on Svalbard. Root associate data strongly suggest the occurrence of an unknown Hebeloma species, not close to any of the infrageneric groups known to occur in arctic habitats.
•Seventeen species of Hebeloma have been recorded in basidiome surveys.•Five species of Hebeloma have so far only been found on Svalbard.•Root-associate ITS diversity is compared to what is known from basidiome records.•Root-associate data strongly suggest at least one additional undescribed species.
• Soil abiotic factors are considered to be important in determining the distribution of ectomycorrhizal (ECM) fungal species; however, there are few field data to support this. Here, we relate ECM ...species distributions to changes in soil chemistry along a short (90-m), natural nutrient gradient. • The ECM community was characterized, using morphological and molecular techniques, in soil samples collected at 10-m intervals. • There were pronounced changes in ECM fungal community structure along the transect, with many taxa showing discrete distributions. Although there was a change of host from Pinus to Picea along the gradient, host-specific fungi did not account for the observed change in community structure. Ordination analyses showed that community structure was strongly correlated with soil characteristics, in particular extractable ammonium and base saturation. However, autocorrelation among soil parameters makes it difficult to isolate the effects of individual parameters. • The distinctive changes in soil and vegetation along the transect used in this study provided an exceptional opportunity to examine the local-scale impact of natural spatial heterogeneity on an ECM fungal community.
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Russula
is one of the most speciose genera of mushroom-forming fungi, but phylogenetic relationships among species and subgeneric groupings are poorly understood. Our multi-locus phylogenetic ...reconstruction places
R. firmula
,
R. rubra
,
R. rutila
and
R. veternosa
in a well-supported Rubrinae clade, belonging to the Integrae clade of the Crown clade of the genus
Russula
. Traditional morphology-based classifications placed these four species in two different subsections based on the presence or absence of incrustations on pileocystidia. The Integrae clade also contains
R. integra
and related species that are traditionally placed in other groups based on their mild taste. Ancestral state reconstruction suggests that the common ancestor of the Crown clade and the Integrae clade probably did not have any incrustations in the pileipellis, had a mild taste, yellow spore print and were associated with angiosperms. All four species of the Rubrinae clade are defined by a darker yellow or ochre spore print, acrid taste and incrustations on pileocystidia. This last character contradicts the former splitting of the group because incrustations were apparently overlooked in
R. firmula
and
R. veternosa
. Incrustation type is now highlighted as being important for the delimitation of species and groups within the Crown clade. Pink or red staining of the incrustations in sulphovanillin is present in all species of the Rubrinae clade and a majority of the analysed species of the Integrae clade. The delimitation of the Rubrinae clade and its species circumscriptions are summarised here in a new diagnostic key.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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