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Abstract Taxonomic discussions often permeate the broader scientific community slowly, yet they may hold more relevance than typically assumed. In many zooplankton groups, identification issues arise from cryptic species complexes, increasingly revealed by molecular approaches, and from groups with high morphological similarity. These challenges can lead to substantial uncertainties in species-level identification, questioning whether the expected species are truly covered and whether those sharing names across ecosystems are indeed distinct entities. This review provides a condensed overview on identification challenges of key species in the ICES zooplankton time series from the North Atlantic and adjacent seas. Examples are given across all relevant groups, including copepods, gelatinous plankton, and meroplanktonic larvae. The high prevalence of challenging species complexes underscores the need to further explore the implications of an accurate species assignment for understanding what defines a species’ role in an ecosystem. This review highlights the dynamic nature of taxonomy, with species being split and cryptic species eventually becoming morphologically distinguishable. It provides examples showing that relying solely on molecular methods without deep taxonomic expertise poses significant risks. It also aims to serve as a starting point for delving deeper into the taxonomy of the ICES zooplankton time series. 

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.