Department Aquatic Ecology

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

In times of rapid environmental changes, baseline biodiversity data are crucial for management. In freshwaters, fish inventories are commonly based on the capture and morphological identification of specimens. The sampling of environmental DNA (eDNA) provides an alternative to assess diversity across large catchments. Here, we used extensive historic data of fish communities collected across 89 river sites in all major catchments of Switzerland and compared their diversity and community composition to a single campaign of eDNA and electrofishing, respectively. Locally, we found that eDNA provided diversity estimates similar to the integrated historic richness, while the electrofishing campaign captured a significantly lower local richness. Fish species locally recorded by electrofishing were nested (Jaccard's dissimilarity index) within the respective eDNA community for most sites. Finally, eDNA sequence reads positively correlated with the overall electrofishing biomass. Despite the congruences, the eDNA data did not correlate well with the electrofishing water quality index. Overall, eDNA was more accurately assessing overall diversity than a simultaneous electrofishing campaign, but yet cannot be directly used to calculate fish-based water quality indices.

The impacts of global change—from shifts in climate to overfishing to land use change—can depend heavily on local abiotic context. Building an understanding of how to downscale global change scenarios to local impacts is often difficult, however, and requires historical data across large gradients of variability. Such data are often not available—particularly in peer reviewed or gray literature. However, these data can sometimes be gleaned from casual records of natural history—field notebooks, data sheet marginalia, course notes, and more. Here, we provide an example of one such approach for the Gulf of Maine, as we seek to understand how environmental context can influence local outcomes of region-wide shifts in subtidal community structure. We explore a decade of hand-drawn algal cover maps around Appledore Island made by Dr. Art Borror while teaching at the Shoals Marine Lab. Appledore's steep wave exposure gradient—from exposed to the open ocean to fully protected—provides a living laboratory to test interactions between global change and local conditions. We then recreate Borror's methods two and a half decades later. We show that overfishing-driven urchin outbreaks in the 1980s were slowed or stopped by wave exposure and benthic topography. Similarly, local variation appears to have curtailed current invasions by filamentous red algae. Last, some formerly dominant kelps have disappeared over the past 40 years—an observation verified by subtidal surveys. Global change is altering life in the seas around us. While underutilized, solid natural history observations stand as a key resource for us to begin to understand how global change will translate to the heterogeneous mosaic of life in a future Gulf of Maine and other ecosystems around the world.

1. Ecological and ecosystem monitoring is rapidly shifting towards using environmental DNA (eDNA) data, particularly in aquatic systems. This approach enables a combined coverage of biodiversity across all major organismal groups and the assessment of ecological indices. Yet, most current approaches are not exploiting the full potential of eDNA data, largely interpreting results in a localized perspective. In riverine networks, by explicitly modelling hydrological transport and associated DNA decay, hydrology-based models enable upscaling eDNA-based diversity information, providing spatially integrated inference. To capitalize on these unprecedented biodiversity data and translate it into space-filling biodiversity projections, a streamlined implementation is needed.
2. Here, we introduce the eDITH R-package, implementing the eDITH model to project biodiversity across riverine networks with minimal prior information. eDITH couples a species distribution model relating a local taxon's eDNA shedding rate in streamwater to environmental covariates, a mass balance expressing the eDNA concentration at a river's cross-section as a weighted sum of upstream contributions, and an observational model accounting for uncertainties in eDNA measurements. By leveraging on spatially replicated eDNA measurements and minimal hydro-morphological data, eDITH enables disentangling the various upstream eDNA sources, and produces space-filling maps of a taxon's spatial distribution at any chosen resolution. eDITH is applicable to both eDNA concentration and metabarcoding data, and to any taxon whose DNA can be retrieved in streamwater.
3. The eDITH package provides user-friendly functions for single-run execution and fitting of eDITH to eDNA data with both Bayesian methods (via the BayesianTools package) and non-linear optimization. An interface to the DHARMa package allows model validation via posterior predictive checks. Necessary preliminary steps such as watershed delineation and hydrological characterization are implemented via the rivnet package. We illustrate eDITH's workflow and functionalities with two case studies from published fish eDNA data.
4. The eDITH package provides a user-friendly implementation of eDITH, specifically intended for ecologists and conservation biologists. It can be used without previous modelling knowledge but also allows customization for experienced users. Ultimately, eDITH allows upscaling eDNA biodiversity data for any river globally, transforming how state and change in biodiversity in riverine systems can be tracked at high resolution in a highly versatile manner.