The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.

Aim: Species inhabiting fresh waters are severely affected by climate change and other anthropogenic stressors. Effective management and conservation plans require advances in the accuracy and reliability of species distribution forecasts. Here, we forecast distribution shifts of Salmo trutta based on environmental predictors and examine the effect of using different statistical techniques and varying geographical extents on the performance and extrapolation of the models obtained.Location: Watercourses of Ebro, Elbe and Danube river basins (c. 1,041,000 km²; Mediterranean and temperate climates, Europe).Methods: The occurrence of S. trutta and variables of climate, land cover and stream topography were assigned to stream reaches. Data obtained were used to build correlative species distribution models (SDMs) and forecasts for future decades (2020s, 2050s and 2080s) under the A1b emissions scenario, using four statistical techniques (generalised linear models, generalised additive models, random forest, and multivariate adaptive regression).Results: The SDMs showed an excellent performance. Climate was a better predictor than stream topography, while land cover characteristics were not necessary to improve performance. Forecasts predict the distribution of S. trutta to become increasingly restricted over time. The geographical extent of data had a weak impact on model performance and gain/loss values, but better species response curves were generated using data from all three basins collectively. By 2080, 64% of the stream reaches sampled will be unsuitable habitats for S. trutta, with Elbe basin being the most affected, and virtually no new habitats will be gained in any basin.Main conclusions: More reliable predictions are obtained when the geographical data used for modelling approximate the environmental range where the species is present. Future research incorporating both correlative and mechanistic approaches may increase robustness and accuracy of predictions.

Over the last decade, steady advancements have been made in the use of DNA-based methods for detection of species in a wide range of ecosystems. This progress has culminated in molecular monitoring methods being employed for the detection of several species for enforceable management purposes of endangered, invasive, and illegally harvested species worldwide. However, the routine application of DNA-based methods to monitor whole communities (typically a metabarcoding approach) in order to assess the status of ecosystems continues to be limited. In aquatic ecosystems, the limited use is particularly true for macroinvertebrate communities. As part of the DNAqua-Net consortium, a structured discussion was initiated with the aim to identify potential molecular methods for freshwater macroinvertebrate community assessment and identify important knowledge gaps for their routine application. We focus on three complementary DNA sources that can be metabarcoded: 1) DNA from homogenised samples (bulk DNA), 2) DNA extracted from sample preservative (fixative DNA), and 3) environmental DNA (eDNA) from water or sediment. We provide a brief overview of metabarcoding macroinvertebrate communities from each DNA source and identify challenges for their application to routine monitoring. To advance the utilisation of DNA-based monitoring for macroinvertebrates, we propose an experimental design template for a series of methodological calibration tests. The template compares sources of DNA with the goal of identifying the effects of molecular processing steps on precision and accuracy. Furthermore, the same samples will be morphologically analysed, which will enable the benchmarking of molecular to traditional processing approaches. In doing so we hope to highlight pathways for the development of DNA-based methods for the monitoring of freshwater macroinvertebrates.