Environmental DNA offers great potential as a biodiversity monitoring tool. Previous work has demonstrated that eDNA metabarcoding provides reliable information for lake fish monitoring, but important questions remain about temporal and spatial repeatability, which is critical for understanding the ecology of eDNA and developing effective sampling strategies. Here, we carried out comprehensive spatial sampling of England's largest lake, Windermere, during summer and winter to (1) examine repeatability of the method, (2) compare eDNA results with contemporary gill‐net survey data, (3) test the hypothesis of greater spatial structure of eDNA in summer compared to winter due to differences in water mixing between seasons, and (4) compare the effectiveness of shore and offshore sampling for species detection. We find broad consistency between the results from three sampling events in terms of species detection and abundance, with eDNA detecting more species than established methods and being significantly correlated with rank abundance determined by long‐term data. As predicted, spatial structure was much greater in the summer, reflecting less mixing of eDNA than in the winter. For example Arctic charr, a deep‐water species, was only detected in deep, midlake samples in the summer, while littoral or benthic species such as minnow and stickleback were more frequently detected in shore samples. By contrast in winter, the eDNA of these species was more uniformly distributed. This has important implications for design of sampling campaigns, for example, deep‐water species could be missed and littoral/benthic species overrepresented by focusing exclusively on shoreline samples collected in the summer.

The sampling of environmental DNA (eDNA) coupled with cost-efficient and ever-advancing sequencing technology is propelling changes in biodiversity monitoring within aquatic ecosystems. Despite the increasing number of eDNA metabarcoding approaches, the ability to quantify species biomass and abundance in natural systems is still not fully understood. Previous studies have shown positive but sometimes weak correlations between abundance estimates from eDNA metabarcoding data and from conventional capture methods. As both methods have independent biases a lack of concordance is difficult to interpret. Here we tested whether read counts from eDNA metabarcoding provide accurate quantitative estimates of the absolute abundance of fish in holding ponds with known fish biomass and number of individuals. Environmental DNA samples were collected from two fishery ponds with high fish density and broad species diversity. In one pond, two different DNA capture strategies (on-site filtration with enclosed filters and three different preservation buffers versus lab filtration using open filters) were used to evaluate their performance in relation to fish community composition and biomass/abundance estimates. Fish species read counts were significantly correlated with both biomass and abundance, and this result, together with information on fish diversity, was repeatable when open or enclosed filters with different preservation buffers were used. This research demonstrates that eDNA metabarcoding provides accurate qualitative and quantitative information on fish communities in small ponds, and results are consistent between different methods of DNA capture. This method flexibility will be beneficial for future eDNA-based fish monitoring and their integration into fisheries management.

Accurate, cost‐effective monitoring of fish is required to assess the quality of lakes under the European Water Framework Directive. Recent studies have shown that environmental DNA (eDNA) metabarcoding is an effective and non‐invasive method, which can provide semi‐quantitative information about fish communities in large lakes. This study further investigated the potential of fish‐based eDNA metabarcoding as a tool for lake assessment by collecting and analysing water samples from eight Welsh lakes and six meres in Cheshire, England, with well‐described fish faunas. Water samples (N = 252) were assayed using two mitochondrial DNA regions (Cytb and 12S rRNA). eDNA sampling indicated the presence of very similar species in the lakes compared to those expected on the basis of existing and historical information. Firstly, 24 species were detected, with a total of 111 species occurrences in the lakes studied using eDNA. Secondly, there was a significant positive correlation between expected faunas and eDNA data in terms of confidence of species occurrence (Spearman's r = 0.74, df = 109, p < 0.001). Thirdly, eDNA data can estimate relative abundance with the standard five‐level classification scale (‘DAFOR’). Lastly, four ecological fish communities were characterized using eDNA data which agree with the predefined lake types according to environmental characteristics. Synthesis and applications. There are some limitations when using conventional captured‐based methods for surveying species richness and relative abundance, such as morphological identification bias, difficulties in recording small‐bodied, rare and/or elusive species and destructive impacts on the environment. This study provides further evidence that environmental DNA metabarcoding outperforms other captured‐based survey techniques in a wide range of lake types for community‐level analysis whether in species detection, relative abundance estimate using the standard five‐level classification scale or characterization ecological fish communities. Therefore, the fish‐based environmental DNA metabarcoding, a non‐invasive genetic method, has great potential as an assessment tool for lake quality under the European Water Framework Directive.

Background: Environmental DNA (eDNA) metabarcoding is a promising tool for rapid, non‐invasive biodiversity monitoring.Aims: In this study, eDNA metabarcoding is applied to explore the spatial and temporal distribution of fish communities in two aquaculture ponds and to evaluate the detection sensitivity of this tool for low‐density species alongside highly abundant species.Materials & Methods: This study was carried out at two artificially stocked ponds with a high fish density following the introduction and removal of two rare fish species.Results & Discussion: When two rare species were introduced and kept at a fixed location in the ponds, eDNA concentration (i.e., proportional read counts abundance) of the introduced species typically peaked after two days. The increase in eDNA concentration of the introduced fish after 43 hrs may have been caused by increased eDNA shedding rates as a result of fish being stressed by handling, as observed in other studies. Thereafter, it gradually declined and stabilised after six days. These findings are supported by the highest community dissimilarity of different sampling positions being observed on the second day after introduction, which then gradually decreased over time. On the sixth day, there was no longer a significant difference in community dissimilarity between sampling days. The introduced species were no longer detected at any sampling positions on 48 hrs after removal from the ponds. eDNA is found to decay faster in the field than in controlled conditions, which can be attributed to the complex effects of environmental conditions on eDNA persistence or resulting in the vertical transport of intracellular DNA and the extracellular DNA absorbed by particles in the sediment. The eDNA signal and detection probability of the introduced species were strongest near the keepnets, resulting in the highest community variance of different sampling events at this position. Thereafter, the eDNA signal significantly decreased with increasing distance, although the signal increased slightly again at 85 m position away from the keepnets.Conclusions: Collectively, these findings reveal that eDNA distribution in lentic ecosystems is highly localised in space and time, which adds to the growing weight of evidence that eDNA signal provides a good approximation of the presence and distribution of species in ponds. Moreover, eDNA metabarcoding is a powerful tool for detection of rare species alongside more abundant species due to the use of generic PCR primers, and can enable monitoring of spatial and temporal community variance.