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Abstract High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples.

High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples. Curated DNA barcode data were used to delineate nematode‐specific inter‐specific operational taxonomic unit (OTUs) clustering thresholds, which were subsequently tested on a artificial nematode community and environmental samples. Open‐reference clustering (UClust_ref) at these empirically derived thresholds outperformed denovo (UParse) as well as cluster‐free approaches (DADA2), resulting in the most accurate description of the nematode community. [ABSTRACT FROM AUTHOR]