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Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent. ISSN:1932-6203

California’s vernal pools are declining ecosystems that support valuable native plant and animal diversity. Vernal pool branchiopods are particularly at risk from vernal pool habitat loss and conservation efforts have targeted their long-term protection through the establishment of preserves and conservation banks. These conservation strategies require repeated, perpetual monitoring of preserved habitat, which is currently carried out through dip-net surveys and visual identification of specimens. Dip-netting may be destructive and frequently requires some sacrifice of protected species. Environmental DNA offers a new, modern method to monitor many protected freshwater organisms. We designed qPCR-based species-specific assays for four of California’s vernal pool branchiopods: The Vernal Pool Fairy Shrimp Branchinecta lynchi (BRLY), the Midvalley Fairy Shrimp Branchinecta mesovallensis (BRME), and the Conservancy Fairy Shrimp Branchinecta conservatio (BRCO), and the Vernal Pool Tadpole Shrimp Lepidurus packardi (LEPA). We tested these assays using eDNA sampling protocols alongside traditional dip-net surveys to assess their viability as an alternative method to monitor vernal pool branchiopods. Based on occupancy modeling, each of our assays achieved a 95% or higher detection rate when using optimized sampling protocols.