We also fitted several reduced models and compared these with AIC, always retaining the lake identity as a random effect term due to the nature of the experimental design. We thank Jean Carreau and Patrick LaFrance of WSP Montréal for useful discussions on the topics of eDNA and biomonitoring. Yet, there are many interacting facets that control the rates of production, transport and decay of eDNA within ecosystems that cannot be observed within small artificial systems, as has been argued in other areas of ecology which make use of mesocosm studies (Carpenter, 1996). Thermal stratification and fish thermal preference explain vertical eDNA distributions in lakes, Freshwater Institute, Fisheries & Oceans Canada, 501 University Crescent, Department of Biology, Queen’s University, Department of Biology, Lakehead University. Benches were cleaned thoroughly with 20% bleach before use. Once we had selected our best‐fitting model with AIC, we confirmed the significance of the highest‐level interaction term with a likelihood‐ratio test. All samples were immediately transported to the laboratory in a cooler with ice packs and stored at 4 ⁰C until filtration. Measurements of oxygen, pH, phosphate, nitrate, nitrite, hydroxylamine. Thermal Stratification The density of water is a function of its temperature – see figure 1. This work was funded by a Mitacs Accelerate Industrial Fellowship (JEL), an NSERC Collaborative Research and Development award (MEC), Canada Research Chair and NSERC Discovery awards to MEC and MDR, Québec Centre for Biodiversity Science Excellence award (JEL), the WSP Montréal Environment Department and in‐kind support from the IISD Experimental Lakes Area and Fisheries & Oceans Canada. NMDS plots for each lake showed that communities were clearly grouped by lake state (Figure 3), with distinct communities detected during stratification and turnover in most lakes. Temperature profiles in each lake confirmed that eDNA sampling occurred during stratification and turnover (isothermal or near‐isothermal conditions) within the study lakes (Table S3). The full text of this article hosted at iucr.org is unavailable due to technical difficulties. Dark lakes tend to have a shallower thermocline depth than clear lakes because the light is absorbed and not allowed to penetrate deeper. Despite these widespread seasonal changes common to lakes across the world, there has been little investigation into how the water movements will impact the distribution of eDNA signal and therefore detection probability. Habitat use by lake trout was validated by acoustic telemetry and was significantly related to eDNA distribution during stratification. Many cold‐water stenotherms, such as Salvelinus namaycush (lake trout), Coregonids and Cottus spp. Abundance, life history, physiology and behaviour of organisms are implicated as biotic factors which shape the release of eDNA at varying scales. In this study, we explored the impact of lake stratification and turnover on the distribution of eDNA in dimictic lakes and make specific predictions for warm‐ and cold‐water fishes. In aquatic ecosystems, speed and volume of lotic flow has received prominent attention in both experimental and field settings, with estimates of eDNA transport ranging from metres to kilometres (Deiner, Fronhofer, Mächler, & Altermatt, 2016; Jane et al., 2015). Instead, information about sequences found in blank samples is displayed in Table S6. Lake stratification is the tendency of lakes to form separate and distinct thermal layers during warm weather. 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