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This report presents the outcome of the joint work of PhD students and senior researchers working with DNA-based biodiversity assessment approaches with the goal to facilitate others the access to definitions and explanations about novel DNA-based methods. The work was performed during a PhD course (SLU PNS0169) at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. The course was co-organized by the EU COST research network DNAqua-Net and the SLU Research Schools Focus on Soils and Water (FoSW) and Ecology - basics and applications. DNAqua-Net (COST Action CA15219, 2016-2020) is a network connecting researchers, water managers, politicians and other stakeholders with the aim to develop new genetic tools for bioassessment of aquatic ecosystems in Europe and beyond. The PhD course offered a comprehensive overview of the paradigm shift from traditional morphology-based species identification to novel identification approaches based on molecular markers. We covered the use of molecular tools in both basic research and applied use with a focus on aquatic ecosystem assessment, from species collection to the use of diversity in environmental legislation. The focus of the course was on DNA (meta)barcoding and aquatic organisms. The knowledge gained was shared with the general public by creating Wikipedia pages and through this collaborative Open Access publication, co-authored by all course participants.

Freshwater habitats often experience species loss, with the greatest pressures coming from land use alterations and the establishment of non-native species as they become invasive. One species of concern is the tropical invasive freshwater cyanobacterium Raphidiopsis raciborskii, currently expanding its geographic distribution towards northern regions of Europe. As a toxin-producing, bloom-forming species, population growths of R. raciborskii can negatively affect local biodiversity and ecosystem services. Hence, in this study, I wanted to evaluate and validate (i) the geographical extent of suitable habitats, (ii) its competitive capacities with a native phytoplankton assemblage and (iii) its adaptive capabilities when moved from ideal to colder temperatures. To identify suitable colonization areas, I used Species Distribution Models (SDMs), which revealed suitable habitats in areas where the invasive cyanobacterium has not been recorded, i.e. several parts of Europe including south-eastern Sweden. However, there were some inconsistencies between SDM results and the field studies used to validate the SDM prediction, where only a few of the European screened lakes matched with the SDM prediction. To better understand the competitive success of R. raciborskii we performed a laboratory study using different nutrient and temperature conditions and, as competitors, an assembly of phytoplankton species typically found in Scandinavian freshwaters. Results confirmed the importance of temperature on R. raciborskii growth and its ability to withstand suboptimal environments. The physiological changes and gene expressions of R. raciborskii, when transferred from optimal to suboptimal temperatures, were tested through a differential transcriptomic experiment. Results showed a difference in gene expression in different treatments, with a downregulation of genes in the suboptimal temperature. Although R. raciborskii has not been recorded in Sweden, it is a well-established invasive species in many European lakes. Combined results from this thesis show that R. raciborskii meets the climatic conditions matching with the south-eastern parts of Sweden. If able to surpass physical and ecological barriers, due to its ability to withstand a wide-range of environments, it might be able to survive in lakes with less favorable conditions and bloom when conditions become ideal. To be able to prevent and contain the expansion of this invasive species in northern European lakes, proactive monitoring programs with high temporal and spatial frequency are needed in combination with broad information campaigns to minimize further spread to other freshwater systems.

Species distribution modelling is a valuable tool for identifying areas most at risk of the spread of invasive species. Here we model the environmental factors governing the distributions of two invasive species of concern that are currently found in Sweden at only a limited number of locations: the aquatic macrophyte Elodea nuttallii (Nuttall’s waterweed / smal vattenpest) and the bivalve Dreissena polymorpha (Zebra mussel / vandrarmussla). For E.nuttallii, the greatest risk factors are connectivity with other water bodies (facilitating dispersion), human population density and length of growing season. This implies that it is principally well-connected lakes in populated areas of southern Sweden that are most at risk of further spread (although other areas of concern are identified). For D.polymorpha, water alkalinity and the proportion of agricultural land (a source of nutrient pollution) are the most important factors, and the models identify lakes Vänern and Vättern, waters in parts of Östergötland, Jämtland and Gotland as key areas of concern for further spread.

Species distribution models (SDMs) calibrated with bioclimatic variables revealed a high probability for range expansion of the invasive toxin producing cyanobacterium, Raphidiopsis raciborskii to Sweden, where no reports of its presence have hitherto been recorded. While predictions focused on the importance of climate variables for possible invasion, other barriers to dispersal and successful colonization need to be overcome by the species for successful invasion. In this study, we combine field-based surveys of R. raciborskii (microscopy and molecular analysis using species-specific primers) of 11 Swedish lakes and in-silico screening of environmental DNA using 153 metagenomic datasets from lakes across Europe to validate the SDMs prediction. Field-based studies in lakes with high/low predicted probability of occurrence did not detect the presence of R. raciborskii, and in-silico screening only detected hints of its presence in 5 metagenomes from lakes with probability ranging from 0.059 to 0.825. The inconsistencies between SDMs results and both field-based/in-silico monitoring could be due to either sensitivity of monitoring approaches in detecting early invasions or uncertainties in SDMs that focused solely on climate drivers. However, results highlight the necessity of proactive monitoring with high temporal and spatial frequency.