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ABSTRACT In metabarcoding studies, Linnaean taxonomy assignments of Operational Taxonomic Units (OTUs) or Amplicon Sequence Variants (ASVs) underpin many downstream bioinformatics analyses and ecological interpretations of environmental DNA (eDNA) datasets. However, public molecular databases (i.e., SILVA, EUKARYOME, BOLD) for most microbial metazoan phyla (nematodes, tardigrades, kinorhynchs, etc.) are sparsely populated, negatively impacting our ability to assign ecologically meaningful taxonomy to these understudied groups. Additionally, the choice of bioinformatics parameters and computational algorithms can further affect the accuracy of eDNA taxonomy assignments. Here, we use twoin silicodatasets to show that taxonomy assignments using the 18S rRNA gene can be dramatically improved by curating Linnaean taxonomy strings associated with each reference sequence and closing phylogenetic gaps by improving taxon sampling. Using free‐living nematodes as a case study, we applied two commonly used taxonomy assignment algorithms (BLAST+ and the QIIME2 Naïve Bayes classifier) across six iterations of the SILVA 138 reference database to evaluate the precision and accuracy of taxonomy assignments. The BLAST+ top hit with a 90% sequence similarity cutoff often returned the highest percentage of correctly assigned taxonomy at the genus level, and the QIIME2 Naïve Bayes classifier performed similarly well when paired with a reference database containing corrected taxonomy strings. Our results highlight the urgent need for phylogenetically informed expansions of public reference databases (encompassing both genomes and common gene markers), focused on poorly sampled lineages that are now robustly recovered via eDNA metabarcoding approaches. Additional taxonomy curation efforts should be applied to popular reference databases such as SILVA, and taxon sampling could be rapidly improved by more frequent incorporation of newly published GenBank sequences linked to genus‐ and/or species‐level identifications. 

Abstract The study of microbiomes across organisms and environments has become a prominent focus in molecular ecology. This perspective article explores common challenges, methodological advancements, and future directions in the field. Key research areas include understanding the drivers of microbiome community assembly, linking microbiome composition to host genetics, exploring microbial functions, transience and spatial partitioning, and disentangling non‐bacterial components of the microbiome. Methodological advancements, such as quantifying absolute abundances, sequencing complete genomes, and utilizing novel statistical approaches, are also useful tools for understanding complex microbial diversity patterns. Our aims are to encourage robust practices in microbiome studies and inspire researchers to explore the next frontier of this rapidly changing field. 

Abstract Environmental DNA (eDNA) data make it possible to measure and monitor biodiversity at unprecedented resolution and scale. As use‐cases multiply and scientific consensus grows regarding the value of eDNA analysis, public agencies have an opportunity to decide how and where eDNA data fit into their mandates. Within the United States, many federal and state agencies are individually using eDNA data in various applications and developing relevant scientific expertise. A national strategy for eDNA implementation would capitalize on recent scientific developments, providing a common set of next‐generation tools for natural resource management and public health protection. Such a strategy would avoid patchwork and possibly inconsistent guidelines in different agencies, smoothing the way for efficient uptake of eDNA data in management. Because eDNA analysis is already in widespread use in both ocean and freshwater settings, we focus here on applications in these environments. However, we foresee the broad adoption of eDNA analysis to meet many resource management issues across the nation because the same tools have immediate terrestrial and aerial applications.