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Sequence data assembly is a foundational step in high‐throughput sequencing, with untold consequences for downstream analyses. Despite this, few studies have interrogated the many methods for assembling phylogenomic UCE data for their comparative efficacy, or for how outputs may be impacted. We study this by comparing the most commonly used assembly methods for UCEs in the under‐studied bee lineage Nomiinae and a representative sampling of relatives. Data for 63 UCE‐only and 75 mixed taxa were assembled with five methods, including ABySS, HybPiper, SPAdes, Trinity and Velvet, and then benchmarked for their relative performance in terms of locus capture parameters and phylogenetic reconstruction. Unexpectedly, Trinity and Velvet trailed the other methods in terms of locus capture and DNA matrix density, whereas SPAdes performed favourably in most assessed metrics. In comparison with SPAdes, the guided‐assembly approach HybPiper generally recovered the highest quality loci but in lower numbers. Based on our results, we formally moveClavinomiato Dieunomiini and renderEpinomiaonce more a subgenus ofDieunomia. We strongly advise that future studies more closely examine the influence of assembly approach on their results, or, minimally, use better‐performing assembly methods such as SPAdes or HybPiper. In this way, we can move forward with phylogenomic studies in a more standardized, comparable manner.

 

Native bee species in the United States provide invaluable pollination services. Concerns about native bee declines are growing, and there are calls for a national monitoring program. Documenting species ranges at ecologically meaningful scales through coverage completeness analysis is a fundamental step to track bees from species to communities. It may take decades before all existing bee specimens are digitized, so projections are needed now to focus future research and management efforts. From 1.923 million records, we created range maps for nearly 88% (3158 species) of bee species in the contiguous United States, provided the first analysis of inventory completeness for digitized specimens of a major insect clade, and perhaps most important, estimated spatial completeness accounting for all known bee specimens in USA collections, including undigitized bee specimens. Completeness analyses were very low (3–37%) across four examined spatial resolutions when using the currently available bee specimen records. Adding a subset of observations from community science data sources did not significantly increase completeness, and adding a projected 4.7 million undigitized specimens increased completeness by only an additional 12–13%. Assessments of data, including projected specimen records, indicate persistent taxonomic and geographic deficiencies. In conjunction with expedited digitization, new inventories that integrate community science data with specimen‐based documentation will be required to close these gaps. A combined effort involving both strategic inventories and accelerated digitization campaigns is needed for a more complete understanding of USA bee distributions. 

Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, particularly for insects, which face mounting pressures. We presentBeeBDC, a newRpackage, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducibleBeeBDC R-workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and, we added record-level flags for a series of potential quality issues. These data are provided in two formats, “cleaned” and “flagged-but-uncleaned”. TheBeeBDCpackage with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducibleRworkflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation.

 

Despite recent advances in phylogenomics, the early evolution of the largest bee family, Apidae, remains uncertain, hindering efforts to understand the history of Apidae and establish a robust comparative framework. Confirming the position of Anthophorinae—a diverse, globally distributed lineage of apid bees—has been particularly problematic, with the subfamily recovered in various conflicting positions, including as sister to all other Apidae or to the cleptoparasitic Nomadinae. We aimed to resolve relationships in Apidae and Anthophorinae by combining dense taxon sampling, with rigorous phylogenomic analysis of a dataset consisting of ultraconserved elements (UCEs) acquired from multiple sources, including low-coverage genomes. Across a diverse set of analyses, including both concatenation and species tree approaches, and numerous permutations designed to account for systematic biases, Anthophorinae was consistently recovered as the sister group to all remaining Apidae, with Nomadinae sister to (Apinae, [Xylocopinae, Eucerinae]). However, several alternative support metrics (concordance factors, quartet sampling, and gene genealogy interrogation) indicate that this result should be treated with caution. Within Anthophorinae, all genera were recovered as monophyletic, following synonymization of Varthemapistra with Habrophorula. Our results demonstrate the value of dense taxon sampling in bee phylogenomics research and how implementing diverse analytical strategies is important for fully evaluating results at difficult nodes.