Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Abstract

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, multi-substrate periphyton collection, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional multi-substrate microhabitat periphyton collections and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton collection and kick-net methodologies or site status, but there was significant difference between diatom communities depending on site (P = 0.042). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms as well as macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes that currently only use the kick-net technique to sample macroinvertebrates.

Seasonal turnover in community composition of stream‐associated macroinvertebrates inferred from freshwater environmental DNA metabarcoding

“…This can be done in connection with conventional kick sampling, but perhaps also as a standalone index, as has been suggested for marine macroinvertebrate monitoring using bulk metabarcoding (Aylagas et al, 2014). There are still many avenues to be explored for macroinvertebrate eDNA detection, such as taxonomy-free approaches with machine learning as has been done with diatom eDNA metabarcoding (Apothéloz-Perret-Gentil et al, 2020), and eDNA sampling could even help alleviate the need for multiple different sampling events, as the same sample can be used to infer multiple stream indices across different taxa (Maitland et al, 2020).…”

What do diatom indices indicate? Modeling the specific pollution sensitivity index

“…Nevertheless, the complexity of diatom responses to environmental variables and the potential for regional variation remind us that diatom-based indices should be applied with careful consideration of local conditions and, when necessary, adapted to specific regions or river types to ensure accurate water quality assessment. In this regard, DNA metabarcoding and high-throughput sequencing are being applied to diatom biomonitoring, improving data quantity and resolution (Maitland et al 2020 ). Overall, diatom-based indices, either based on DNA metabarcoding techniques or traditional microscopy-based methods, have advanced the state-of-the-art in river biomonitoring using diatoms as indicators of water quality (Goldenberg-Vilar et al 2020 ).…”

Diversity of freshwater algal assemblages across the United States as revealed by DNA metabarcoding

“…Such a mixed assemblage offers opportunities and challenges for using eDNA for ecological monitoring when compared to biofilm DNA. Metabarcoding studies comparing the effect of sample substrate on measured algal assemblages are sparse, but Maitland et al (2020) compared stream diatom assemblages from rock scrapes, sediment, macrophytes, leaf litter, and kick‐net sampling (a method traditionally used to target benthic macroinvertebrates) and found no significant differences in assemblage composition – though a higher number of planktonic diatom species were detected using kick‐netting than rock scrapes. Meanwhile, Hajibabaei et al (2019) found that benthic macroinvertebrate assemblages strongly differed between filtered water and kick‐net benthos samples, demonstrating that sample substrate has the potential to influence DNA‐based biomonitoring results.…”