A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers

Abstract

Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared three different approaches in order to better understand assessments of aquatic macroinvertebrate diversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species richness model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species richness model, that is, a generalized linear model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the kicknet and eDNA approaches, particularly at a local scale. We found the EPT-specific primer set fwhF2/EPTDr2n, detected a greater number of targeted EPT species compared to the more general primer set mlCOIintF/HCO2198. Moreover, we found that the species richness measured by eDNA from either primer set was poorly correlated to the richness measured by kicknet sampling (Pearson correlation = 0.27) and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the species richness model (Pearson correlation = 0.30 and 0.44, respectively). The weak relationships between the traditional kicknet sampling and eDNA with this model indicates inherent limitations in upscaling species richness estimates, and possibly a limited ability of the model to meet real world expectations. It is also possible that the number of replicates was not sufficient to detect ambiguous correlations. Future challenges include improving the accuracy and sensitivity of each approach individually, yet also acknowledging their respective limitations, in order to best meet stakeholder demands and address the biodiversity crisis we are facing.

Comparisons of eDNA and traditional sampling methods for enhanced assessment of benthic macroinvertebrate diversity in lotic environments with spatially varying land use

“…The results proved the complementary nature of capture-based (i.e., qualitative) and eDNA-based sampling methods, with each method detecting a distinct set of taxa and providing unique information regarding the species richness and composition of the sampled communities (Coble et al, 2019;Gleason et al, 2021). Although qualitative sampling detected a higher species richness than eDNA sampling, eDNA-based metabarcoding analysis demonstrated the potential to reveal cryptic or rare taxa such as Choroterpes altioculus, Cincticostella levanidovae, and Ceratopogonidae sp., which were previously recorded (https://water.nier.go.kr/) but not collected in this eld study (Coble et al, 2019;Marshall and Stepien, 2020;Keck et al, 2022b). In addition, even for taxa that were di cult to classify due to their complex morphological characteristics (e.g., chironomids), the identi cation down to the species level is possible from the eDNA metabarcoding, allowing for a better understanding of the habitats for a more diverse range of organisms compared to the results obtained from the traditional capture-based sampling methods, which only classi ed down to the family level in the case (Deiner et al, 2016).…”

Habitat suitability models reveal the spatial signal of environmental DNA in riverine networks

“…Having the continuous and spatially explicit information provided by HSM from upstream areas gives the opportunity to infer potential unseen populations of a sampled species but also to validate eDNA-based detections if locally congruent. Such validation is highly relevant for eDNA-based monitoring of waterbodies and is so far often done by comparison with traditional methods at a local level (Brantschen et al 2021, Keck et al 2022b). Whereas HSMs are not aimed to provide biomonitoring data, they have the potential to complement and validate field-based methods (here eDNA), and further integrate the sampling point into a landscape perspective, leading to a broader understanding of biodiversity dynamics in the context of conservation and management (Riaz et al 2020).…”

“…Currently, describing aquatic indicator communities is often limited to localized sampling (Kuemmerlen et al 2016). For a comprehensive assessment, the inclusion of models based on spatially explicit measurements of environmental parameters can validate spatially constrained field-sampling (Kuemmerlen et al 2016, Keck et al 2022b. For the sampling of eDNA, species distribution models can strengthen the plausibility of eDNA-based species detection and validate the detection of a rare species (Riaz et al 2020).…”

Integrating citizen science and environmental DNA metabarcoding to study biodiversity of groundwater amphipods in Switzerland

“…This suggests that the amphipods collected by water providers are most likely representative of the populations living in groundwater. In fact, since both methods have possibly rather different biases, we would expect them to give different results if they were not exhaustive, as is often the case when comparing eDNA and traditional methods in other ecosystems (see e.g., [31][32][33] ). Instead, the detections from eDNA are included (i.e., nested) within the ones from citizen science, indicating that the latter is a good approach for studying groundwater organisms 30,34 .…”