No abstract

Most of the present EU Water Framework Directive (WFD) compliant fish‐based assessment methods of European rivers are multi‐metric indices computed from traditional electrofishing (TEF) samples, but this method has known shortcomings, especially in large rivers. The probability of detecting rare species remains limited, which can alter the sensitivity of the indices. In recent years, environmental (e)DNA metabarcoding techniques have progressed sufficiently to allow applications in various ecological domains as well as eDNA‐based ecological assessment methods. A review of the 25 current WFD‐compliant methods for river fish shows that 81% of the metrics used in these methods are expressed in richness or relative abundance and thus compatible with eDNA samples. However, more than half of the member states' methods include at least one metric related to age or size structure and would have to adapt their current fish index if reliant solely on eDNA‐derived information. Most trait‐based metrics expressed in richness are higher when computed from eDNA than when computed from TEF samples. Comparable values are obtained only when the TEF sampling effort increases. Depending on the species trait considered, most trait‐based metrics expressed in relative abundance are significantly higher for eDNA than for TEF samples or vice versa due to over‐estimation of sub‐surface species or under‐estimation of benthic and rare species by TEF sampling, respectively. An existing predictive fish index, adapted to make it compatible with eDNA data, delivers an ecological assessment comparable with the current approved method for 22 of the 25 sites tested. Its associated uncertainty is lower than that of current fish indices. Recommendations for the development of future fish eDNA‐based indices and the associated eDNA water sampling strategy are discussed.

Abstract. The open-source programming language R has gained a central place in the hydrological sciences over the last decade, driven by the availability of diverse hydro-meteorological data archives and the development of open-source computational tools. The growth of R's usage in hydrology is reflected in the number of newly published hydrological packages, the strengthening of online user communities, and the popularity of training courses and events. In this paper, we explore the benefits and advantages of R's usage in hydrology, such as the democratization of data science and numerical literacy, the enhancement of reproducible research and open science, the access to statistical tools, the ease of connecting R to and from other languages, and the support provided by a growing community. This paper provides an overview of a typical hydrological workflow based on reproducible principles and packages for retrieval of hydro-meteorological data, spatial analysis, hydrological modelling, statistics, and the design of static and dynamic visualizations and documents. We discuss some of the challenges that arise when using R in hydrology and useful tools to overcome them, including the use of hydrological libraries, documentation, and vignettes (long-form guides that illustrate how to use packages); the role of integrated development environments (IDEs); and the challenges of big data and parallel computing in hydrology. Lastly, this paper provides a roadmap for R's future within hydrology, with R packages as a driver of progress in the hydrological sciences, application programming interfaces (APIs) providing new avenues for data acquisition and provision, enhanced teaching of hydrology in R, and the continued growth of the community via short courses and events.

Abstract. The open-source programming language R has gained a central place in the hydrological sciences over the last decade, driven by the availability of diverse hydro-meteorological data archives and the development of open-source computational tools. The growth of R's usage in hydrology is reflected in the number of newly published hydrological packages, the strengthening of online user communities, and the popularity of training courses and events. In this paper, we explore the benefits and advantages of R's usage in hydrology, such as: the democratization of data science and numerical literacy, the enhancement of reproducible research and open science, the access to statistical tools, the ease of connecting R to and from other languages, and the support provided by a growing community. This paper provides an overview of important packages at every step of the hydrological workflow, from the retrieval of hydro-meteorological data, to spatial analysis and cartography, hydrological modelling, statistics, and the design of static and dynamic visualizations, presentations and documents. We discuss some of the challenges that arise when using R in hydrology and useful tools to overcome them, including the use of hydrological libraries, documentation and vignettes (long-form guides that illustrate how to use packages); the role of Integrated Development Environments (IDEs); and the challenges of Big Data and parallel computing in hydrology. Last, this paper provides a roadmap for R's future within hydrology, with R packages as a driver of progress in the hydrological sciences, Application Programming Interfaces (APIs) providing new avenues for data acquisition and provision, enhanced teaching of hydrology in R, and the continued growth of the community via short courses and events.

We used historical sources from the end of the nineteenth to the mid-twentieth century and current data to retrace fish assemblage trajectories for the past 150 years on 29 river stretches distributed throughout the Seine River basin. We based our analyses on species presence/absence, occurrence of amphidromous and non-native species, and species ecological traits related to habitat preference, oxygen and temperature requirements, and diet. In accordance with general trends observed for Western Europe, we detected a general decline of amphidromous species and an increase in non-native species, even if, at some sites, several non-native species were extirpated. These changes affecting amphidromous and non-native species led to a weak increase in beta-diversity in fish assemblages. Independently of amphidromous and non-native species, for a reduced set of sites, we noted that changes in the balance of ecological traits over time, trace, in a consistent way, the major steps that affected watercourses like waterway development, increasing pollution, dam construction, or, locally, the recent wastewater treatment improvement. Despite local variations, we found contrasted trends between, on one hand, large rivers and/or catchments which had experienced strong expansion in human population, where fish assemblages had deteriorated, and, on the other hand, upstream catchments, with a declining human population, where fish assemblages showed signs of improvement. Because our results suggested that long-term changes affecting fish assemblages cannot be summarized as an unequivocal gradual degradation, we questioned the use of historical data to define ecological reference conditions for river assessment and management purposes.