Polypedilum Kieffer (Diptera: Chironomidae), with 520 currently known species worldwide, can be extremely difficult to identify species level based on the morphology. We used 3,670 cytochrome c oxidase subunit I (COI) barcodes to explore the efficiency of the COI barcodes to differentiate between species in a superdiverse aquatic insect genus. The Barcode of Life Data System (BOLD) presented 286 BIN clusters in Polypedilum, representing 163 morphospecies, of which 93 were contributed from our laboratory. Molecular operational taxonomic units (OTUs) ranged from 158 to 345, based on Automatic Barcode Gap Discovery (ABGD), the Barcode Index Number (BIN), Bayesian Poisson tree processes (bPTP), generalized mixed Yule coalescent (GMYC), jMOTU, multi‐rate Poisson tree processes (mPTP), neighbor‐joining (NJ) tree and prethreshold clustering. In comparison, GMYC, bPTP, mPTP and BIN suggested more species than warranted by morphology, while ABGD, jMOTU, NJ, prethreshold clustering and ABGD yielded a conservative number of species when setting higher thresholds. Nine species complexes with deep intraspecific divergences indicated 18 potentially cryptic species, which require further taxonomic research including complete life histories and nuclear genetic data to be resolved. The discrimination of Polypedilum species by DNA barcodes proved to be successful in 94.4% of all studied morphological species.

Communities of zooplankton can be adversely affected by contamination resulting from human activities. Yet understanding the influence of water quality on zooplankton under field-conditions is hindered by traditional labor-intensive approaches that are prone to incomplete or uncertain taxonomic determinations. Here, for the first time, an eco-genomic approach, based on genetic diversity in the mitochondrial cytochrome c oxidase I (COI) region of DNA of zooplankton was used to develop a site-specific, water quality criterion (WQC) for ammonia (NH). Ammonia has been recognized as a primary stressor in the catchment of the large, eutrophic Tai Lake, China. Nutrients, especially NH and nitrite (NO) had more significant effects on structure of the zooplankton community than did other environmental factors. Abundances of rotifers increased along a gradient of increasing concentrations of total ammonia nitrogen (TAN), while abundances of copepods and cladocera decreased. A novel, rapid, species sensitivity distribution (SSD) approach based on operational taxonomic units (OTUs) was established to develop a WQC for NH. The WQC based on OTUs was consistent with the WQC based on the traditional morphology taxonomy approach. This genetics-based SSD approach could be a useful tool for monitoring for status and trends in species composition and deriving ecological criteria and an efficient biomonitoring tool to protect local aquatic ecosystems in virtually any aquatic ecosystem.

Communities of zooplankton, a critical portion of aquatic ecosystems, can be adversely affected by contamination resulting from human activities. Understanding the influence of environmental change on zooplankton communities under field-conditions is hindered by traditional labor-intensive approaches that are prone to taxonomic and enumeration mistakes. Here, metabarcoding of cytochrome c oxidase I (COI) region of mitochondrial DNA was used to characterize the genetic diversity of zooplankton. The species composition of zooplankton communities determined by metabarcoding was consistent with the results based on the traditional morphological approach. The spatial distribution of common species (frequency of occurrence >10 samples) by metabarcoding exhibited good agreement with morphological data. Furthermore, metabarcoding can clearly distinguish the composition of the zooplankton community between lake and river ecosystems. In general, rotifers were more abundant in riverine environments than lakes and reservoirs. Finally, the sequence read number of different taxonomic groups using metabarcoding was positively correlated with the zooplankton biomass inferred by density and body length of zooplankton. Overall, the utility of metabarcoding for taxonomic profiling of zooplankton communities was validated by the morphology-based method on a large ecological scale. Metabarcoding of COI could be a powerful and efficient biomonitoring tool to protect local aquatic ecosystems.