Exploring and clearly defining the level of taxonomic identification and quantification approaches for diversity and biomonitoring studies are essential, given its potential influence on the assessment and interpretation of ecological outcomes. In this study, we evaluated the response of benthic macroinvertebrate communities to the restoration or construction of gravel bars conducted in the dam-impacted Trinity River, with the non-dam influenced tributaries serving as the reference sites. We aim to evaluate the performance of different taxonomic and numerical (i.e., abundance vs. presence/absence data) resolutions of DNA metabarcoding with consequent comparison to morphology-based identification and how it affects assessment outcomes. DNA metabarcoding detected 93% of the morphologically identified individuals and provided finer taxonomic resolution. We also detected significant correlations between morphological sample abundance, biomass, and DNA metabarcoding read abundance. We observed a relatively high and significant congruence in macroinvertebrate community structure and composition between different taxonomic and numerical resolutions of both methods, indicating a satisfactory surrogacy between the two approaches and their varying identification levels and data transformation. Additionally, the community-environmental association were significant for all datasets but showed varying significant associations against the physicochemical parameters. Furthermore, both methods identified Simulium spp. as significant indicators of the dam-impacted gravel bars. Still, only DNA metabarcoding showed significant false discovery rate proving the method’s robustness compared to morphology-based identification. Our observations imply that coarser taxonomic resolution could be highly advantageous to DNA metabarcoding-based applications in situations where the lack of taxonomic information, e.g., poor reference database, might severely affect the quality of biological assessments.

The development and evaluation of DNA metabarcoding protocols for haplotype-level resolution require attention, specifically for population genetic analysis, i.e., parallel estimation of genetic diversity and dispersal patterns among multiple species present in a bulk sample. Further exploration and assessment of the laboratory and bioinformatics strategies are warranted to unlock the potential of metabarcoding-inferred population genetic analysis. Here, we assessed the inference of freshwater macroinvertebrate haplotypes from DNA metabarcoding data using mock samples with known Sanger-sequenced haplotypes. We also examined the influence of different DNA template concentrations and PCR cycles on detecting true haplotypes and the reduction of spurious haplotypes obtained from DNA metabarcoding. We tested our haplotyping strategy on a mock sample containing 20 specimens from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. The read processing and denoising step resulted in 14 zero-radius operational taxonomic units (ZOTUs) of 421-bp length, with 12 ZOTUs having 100% match with 12 of the Sanger haplotype sequences. Quality passing reads relatively increased with increasing PCR cycles, and the relative abundance of each ZOTUs was consistent for each cycle number. This suggests that increasing the cycle number from 24 to 64 did not affect the relative abundance of quality passing filter reads of each ZOTUs. Our study demonstrated the ability of DNA metabarcoding to infer intraspecific variability while highlighting the challenges that need to be addressed before its possible applications to population genetic studies.