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Abstract Most empirical research on biological shortfalls has focused on vertebrate taxa. This is important given many species in poorly studied groups such as invertebrates, plants, and fungi are predicted to possess high conservation risk. Here, we focus on Laboulbeniomycetes: a class of microfungi that are understudied. We examined four shortfalls: Linnean (knowledge gaps in species diversity), Wallacean (knowledge gaps in distributions), Latimerian (knowledge gaps in species persistence), and the newly introduced Scottian (knowledge gaps in species conservation assessments) shortfalls. The Linnean shortfall in Laboulbeniomycetes is hard to predict due to inconsistent species description rates. Analysis of distribution patterns indicates Laboulbeniomycetes are likely to experience an extremely high Wallacean shortfall, with many species having highly disjunct known distributions. Latimerian shortfall analysis shows over half (51%) of Laboulbeniomycetes have not been recorded in >50 years, while the group has a collective Scottian shortfall of 100%, given none of the 2454 described species have received an IUCN threat assessment. We suggest continued study of natural history collections, expanded citizen science programmes, and machine‐learning identification approaches as important tools for reducing knowledge shortfalls in both Laboulbeniomycetes and poorly studied taxa more generally. 

ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.