From national monitoring to transnational indicators: reporting and processing of aquatic biology data under the European Environment Agency’s State of the Environment data flow

Biological monitoring data from aquatic ecosystems are collected from European countries on a yearly basis by the European Environment Agency (EEA) through the Water Information System for Europe (WISE). The WISE-SoE (State of Environment) data flows provide indicators of pressures, states and impacts of surface waters and groundwaters on a pan-European scale. The WISE-2 Biology was established to obtain a harmonised flow of biology data reported annually as Ecological Quality Ratios (EQRs) from European surface waters, as a supplement to the mandatory 6-yearly reporting of ecological status of water bodies for the Water Framework Directive. The purposes of this paper are 1) to describe the compilation of national aquatic biology monitoring data indicators and to inform about the public availability of these data, 2) to give an overview of the reported data and indicate the potential for assessments based on these data, and 3) to illustrate the potential for further use of the underlying species abundance data in biodiversity research and assessment. WISE-2 data are reported for the following biological quality elements: phytoplankton, phytobenthos, macrophytes, macroalgae, angiosperms, benthic invertebrates and fish in rivers, lakes, transitional and/or coastal waters. The EQR values represent the deviation from reference conditions. The final processed and quality-checked data are published in EEA’s database Waterbase - Biology, which currently holds data from more than 13,000 waterbodies in 26 countries from the reporting years 2011–2021. Examples of time series aggregated by geographic regions give an indication of the type of trends that can be obtained from the reported data at the nEQR scale. However, the current results are representative only for certain geographic regions with high coverage of water bodies. Within the European research project EuropaBON (Europa Biodiversity Observation Network), the use of WISE-2 data can be leveraged to support biodiversity policy and conservation planning. EuropaBON’s online database provides an overview of how biodiversity monitoring schemes across Europe flows through different integration nodes, to produce Essential Biodiversity Variables and other policy-relevant indicators. Here, we use the EuropaBON visualisation tool to illustrate the WISE-2 as a European integration node for 157 biology datasets via the national integration nodes.publishedVersio

Shifted dynamics of plankton communities in a restored lake: exploring the effects of climate change on phenology through four decades

Lake surface temperatures have increased globally in recent decades. Climate change can affect lake biota directly via enhanced water temperatures, shorter ice cover duration and prolonged stratification, and indirectly via changes in species interactions. Changes in the seasonal dynamics of phytoplankton and zooplankton can further affect whole lake ecosystems. However, separating the effects of climate change from the more direct and dominating effects of nutrients is a challenge. Our aim was to explore the ecological effects of climate change while accounting for the effects of re-oligotrophication in Lake Mjøsa, the largest lake in Norway. While restoration measures since the 1970s have resulted in strongly reduced nutrient levels, the surface water temperature has increased by almost 0.4°C decade-1 during the same period. We analysed long-term trends and abrupt changes in environmental and biological time series as well as changes in the seasonal dynamics of individual plankton taxa. The general long-term trends in phenology were diverging for phytoplankton (later peaks) vs. zooplankton (earlier peaks). However, individual taxa of both phytoplankton and zooplankton displayed earlier peaks. Earlier peaks of the phytoplankton group Cryptophyceae can be explained by increased spring temperature or other climate-related changes. Earlier onset of population growth of certain zooplankton species (Limnocalanus macrurus and Holopedium gibberum) can also be explained by climatic change, either directly (earlier temperature increase) or more indirectly (earlier availability of Cryptophyceae as a food source). In the long run, climate-related changes in both phytoplankton and zooplankton phenology may have implications for the fish communities of this lake.publishedVersio

Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach

Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change, which will result in an increase of temperatures and a decrease in annual precipitation. On the other hand, pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European ´Farm-to-Fork` strategy, which aims for a 50 % reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study investigates how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia, Spain), a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using three climatic scenarios (for the years 2008, 2050 and 2100), three pesticide dosage regimes (the recommended dose, and 50 % increase and 50 % decrease), and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of Bayesian networks. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides, yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures, and higher exposure peaks in scenarios where heavy precipitation events occur right after pesticide application. Our case study shows that pesticides such as azoxystrobin, difenoconazole and MCPA are posing unacceptable ecological risks for aquatic organisms, and that the implementation of the ´Farm-to-Fork` strategy is crucial to reduce them.publishedVersio

Simulating water quality and ecological status of Lake Vansjø, Norway, under land-use and climate change by linking process-oriented models with a Bayesian network

Excess nutrient inputs and climate change are two of multiple stressors affecting many lakes worldwide. Lake Vansjø in southern Norway is one such eutrophic lake impacted by blooms of toxic blue-green algae (cyanobacteria), and classified as moderate ecological status under the EU Water Framework Directive. Future climate change may exacerbate the situation. Here we use a set of chained models (global climate model, hydrological model, catchment phosphorus (P) model, lake model, Bayesian Network) to assess the possible future ecological status of the lake, given the set of climate scenarios and storylines common to the EU project MARS (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). The model simulations indicate that climate change alone will increase precipitation and runoff, and give higher P fluxes to the lake, but cause little increase in phytoplankton biomass or changes in ecological status. For the storylines of future management and land-use, however, the model results indicate that both the phytoplankton biomass and the lake ecological status can be positively or negatively affected. Our results also show the value in predicting a biological indicator of lake ecological status, in this case, cyanobacteria biomass with a BN model. For all scenarios, cyanobacteria contribute to worsening the status assessed by phytoplankton, compared to using chlorophyll-a alone.publishedVersio

A Decision Support System to Predict Acute Fish Toxicity

We present a decision support system using a Bayesian network to predict acute fish toxicity from multiple lines of evidence. Fish embryo toxicity testing has been proposed as an alternative to using juvenile or adult fish in acute toxicity testing for hazard assessments of chemicals. The European Chemicals Agency has recommended the development of a so-called weight-of-evidence approach for strengthening the evidence from fish embryo toxicity testing. While weight-of-evidence approaches in the ecotoxicology and ecological risk assessment community in the past have been largely qualitative, we have developed a Bayesian network for using fish embryo toxicity data in a quantitative approach. The system enables users to efficiently predict the potential toxicity of a chemical substance based on multiple types of evidence including physical and chemical properties, quantitative structure-activity relationships, toxicity to algae and daphnids, and fish gill cytotoxicity. The system is demonstrated on three chemical substances of different levels of toxicity. It is considered as a promising step towards a probabilistic weight-of-evidence approach to predict acute fish toxicity from fish embryo toxicity.publishedVersio

Size- and stage-dependence in cause-specific mortality of migratory brown trout

Evidence‐based management of natural populations under strong human influence frequently requires not only estimates of survival but also knowledge about how much mortality is due to anthropogenic vs. natural causes. This is the case particularly when individuals vary in their vulnerability to different causes of mortality due to traits, life history stages, or locations. Here, we estimated harvest and background (other cause) mortality of landlocked migratory salmonids over half a century. In doing so, we quantified among‐individual variation in vulnerability to cause‐specific mortality resulting from differences in body size and spawning location relative to a hydropower dam. We constructed a multistate mark–recapture model to estimate harvest and background mortality hazard rates as functions of a discrete state (spawning location) and an individual time‐varying covariate (body size). We further accounted for among‐year variation in mortality and migratory behaviour and fit the model to a unique 50‐year time series of mark–recapture–recovery data on brown trout (Salmo trutta ) in Norway. Harvest mortality was highest for intermediate‐sized trout, and outweighed background mortality for most of the observed size range. Background mortality decreased with body size for trout spawning above the dam and increased for those spawning below. All vital rates varied substantially over time, but a trend was evident only in estimates of fishers' reporting rate, which decreased from over 50% to less than 10% throughout the study period. We highlight the importance of body size for cause‐specific mortality and demonstrate how this can be estimated using a novel hazard rate parameterization for mark–recapture models. Our approach allows estimating effects of individual traits and environment on cause‐specific mortality without confounding, and provides an intuitive way to estimate temporal patterns within and correlation among different mortality sources

A new broad typology for rivers and lakes in Europe: Development and application for large-scale environmental assessments

European countries have defined >1000 national river types and >400 national lake types to implement the EU Water Framework Directive (WFD). In addition, common river and lake types have been defined within regions of Europe for intercalibrating the national classification systems for ecological status of water bodies. However, only a low proportion of national types correspond to these common intercalibration types. This causes uncertainty concerning whether the classification of ecological status is consistent across countries. Therefore, through an extensive dialogue with and data provision from all EU countries, we have developed a generic typology for European rivers and lakes. This new broad typology reflects the natural variability in the most commonly used environmental type descriptors: altitude, size and geology, as well as mean depth for lakes. These broad types capture 60–70% of all national WFD types including almost 80% of all European river and lake water bodies in almost all EU countries and can also be linked to all the common intercalibration types. The typology provides a new framework for large-scale assessments across country borders, as demonstrated with an assessment of ecological status and pressures based on European data from the 2nd set of river basin management plans. The typology can also be used for a variety of other large-scale assessments, such as reviewing and linking the water body types to habitat types under the Habitats Directive and the European Nature Information System (EUNIS), as well as comparing type-specific limit values for nutrients and other supporting quality elements across countries. Thus, the broad typology can build the basis for all scientific outputs of managerial relevance related to water body types

Big Question To Developing Solutions : A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022

In 2012, 20 key questions related to hazard and exposure assessment and environmental and health risks of pharmaceuticals and personal care products in the natural environment were identified. A decade later, this article examines the current level of knowledge around one of the lowest-ranking questions at that time, number 19: "Can nonanimal testing methods be developed that will provide equivalent or better hazard data compared with current in vivo methods?" The inclusion of alternative methods that replace, reduce, or refine animal testing within the regulatory context of risk and hazard assessment of chemicals generally faces many hurdles, although this varies both by organism (human-centric vs. other), sector, and geographical region or country. Focusing on the past 10 years, only works that might reasonably be considered to contribute to advancements in the field of aquatic environmental risk assessment are highlighted. Particular attention is paid to methods of contemporary interest and importance, representing progress in (1) the development of methods which provide equivalent or better data compared with current in vivo methods such as bioaccumulation, (2) weight of evidence, or (3) -omic-based applications. Evolution and convergence of these risk assessment areas offer the basis for fundamental frameshifts in how data are collated and used for the protection of taxa across the breadth of the aquatic environment. Looking to the future, we are at a tipping point, with a need for a global and inclusive approach to establish consensus. Bringing together these methods (both new and old) for regulatory assessment and decision-making will require a concerted effort and orchestration. Environ Toxicol Chem 2023;00:1-15. (c) 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.Peer reviewe

Evaluation of a Bayesian Network for Strengthening the Weight of Evidence to Predict Acute Fish Toxicity from Fish Embryo Toxicity Data

The use of fish embryo toxicity (FET) data for hazard assessments of chemicals, in place of acute fish toxicity (AFT) data, has long been the goal for many environmental scientists. The FET test was first proposed as a replacement to the standardized AFT test nearly 15 y ago, but as of now, it has still not been accepted as a standalone replacement by regulatory authorities such as the European Chemicals Agency (ECHA). However, the ECHA has indicated that FET data can be used in a weight of evidence (WoE) approach, if enough information is available to support the conclusions related to the hazard assessment. To determine how such a WoE approach could be applied in practice has been challenging. To provide a conclusive WoE for FET data, we have developed a Bayesian network (BN) to incorporate multiple lines of evidence to predict AFT. There are 4 different lines of evidence in this BN model: 1) physicochemical properties, 2) AFT data from chemicals in a similar class or category, 3) ecotoxicity data from other trophic levels of organisms (e.g., daphnids and algae), and 4) measured FET data. The BN model was constructed from data obtained from a curated database and conditional probabilities assigned for the outcomes of each line of evidence. To evaluate the model, 20 data‐rich chemicals, containing a minimum of 3 AFT and FET test data points, were selected to ensure a suitable comparison could be performed. The results of the AFT predictions indicated that the BN model could accurately predict the toxicity interval for 80% of the chemicals evaluated. For the remaining chemicals (20%), either daphnids or algae were the most sensitive test species, and for those chemicals, the daphnid or algal hazard data would have driven the environmental classification. Integr Environ Assess Manag 2020;00:1–9. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC