Developing a foundation for eco-epidemiological assessment of aquatic ecological status over large geographic regions utilizing existing data resources and models

Water quality deterioration remains a major stressor for macroinvertebrate, diatom and fish communities in German rivers

About 60 % of Europe's rivers fail to meet ecological quality standards derived from biological criteria. The causes are manifold, but recent reports suggest a dominant role of hydro-morphological and water quality-related stressors. Yet, in particular micropollutants and hydrological stressors often tend to be underrepresented in multiple-stressor studies. Using monitoring data from four Federal States in Germany, this study investigated the effects of 19 stressor variables from six stressor groups (nutrients, salt ions, dissolved oxygen/water temperature, mixture toxicity of 51 micropollutants, hydrological alteration and morphological habitat quality) on three biological assemblages (fishes, macroinvertebrates, benthic diatoms). Biological effects were analyzed for 35 community metrics and quantified using Random Forest (RF) analyses to put the stressor groups into a hierarchical context. To compare metric responses, metrics were grouped into categories reflecting important characteristics of biological communities, such as sensitivity, functional traits, diversity and community composition as well as composite indices that integrate several metrics into one single index (e.g., ecological quality class). Water quality-related stressors - but not micropollutants - turned out to dominate the responses of all assemblages. In contrast, the effects of hydro-morphological stressors were less pronounced and stronger for hydrological stressors than for morphological stressors. Explained variances of RF models ranged 23-64 % for macroinvertebrates, 16-40 % for benthic diatoms and 18-48 % for fishes. Despite a high variability of responses across assemblages and stressor groups, sensitivity metrics tended to reveal stronger responses to individual stressors and a higher explained variance in RF models than composite indices. The results of this study suggest that (physico-chemical) water quality deterioration continues to impact biological assemblages in many German rivers, despite the extensive progress in wastewater treatment during the past decades. To detect water quality deterioration, monitoring schemes need to target relevant physico-chemical stressors and micropollutants. Furthermore, monitoring needs to integrate measures of hydrological alteration (e.g., flow magnitude and dynamics). At present, hydro-morphological surveys rarely address the degree of hydrological alteration. In order to achieve a good ecological status, river restoration and management needs to address both water quality-related and hydro-morphological stressors. Restricting analyses to just one single organism group (e.g., macroinvertebrates) or only selected metrics (e.g., ecological quality class) may hamper stressor identification and its hierarchical classification and, thus may mislead river management.

Assessment of the contribution of surfactants to mixture toxicity in French surface waters

Surfactants are widely used 'down-the-drain' chemicals with the potential to occur at high concentrations in local water bodies and to be part of unintentional environmental mixtures. Recently, increased regulatory focus has been placed on the impacts of complex mixtures in aquatic environments and the substances that are likely to drive mixture risk. This study assessed the contribution of surfactants to the total mixture pressure in freshwater ecosystems. Environmental concentrations, collated from existing French monitoring data, were combined with estimated ecotoxicological thresholds to calculate hazard quotients (HQ) for each substance, and hazard indices (HI) for each mixture. Two scenarios were investigated to correct for concentrations below the limit of quantification (LOQ) in the dataset. The first (best-case) scenario assumed all values Collapse

Key Words

• Aquatic
• Complex mixtures
• Concentration addition
• Environmental monitoring
• Risk assessment
• Surfactants

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Affiliation(s)

Nathalie Briels ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Charlotte Nys ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Karel P J Viaene ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Frederik Verdonck ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Erin M Maloney Shell Global Solutions International B.V., Carel van Bylandtlaan 16, 2596 HR Den Haag, the Netherlands
James Dawick Innospec Limited, Innospec Manufacturing Park, Oil G Sites Road Ellesmere Port, Cheshire CH65 4EY, UK
Chiara Maria Vitale Procter & Gamble, Brussels Innovation Centre, Temselaan 100, B-1853 Strombeek-Bever, Belgium
Diederik Schowanek Procter & Gamble, Brussels Innovation Centre, Temselaan 100, B-1853 Strombeek-Bever, Belgium.

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Optimal zinc level and uncertainty quantification in agricultural soils via visible near-infrared reflectance and soil chemical properties

Zinc (Zn) is a vital element required by all living creatures for optimal health and ecosystem functioning. Therefore, several researchers have modeled and mapped its occurrence and distribution in soils. Nonetheless, leveraging model predictive performances while coupling information derived from visible near-infrared (Vis-NIR) and soils (i.e. chemical properties) to estimate potential toxic elements (PTEs) like Zn in agricultural soils is largely untapped. This study applies two methods to rapidly monitor Zn concentration in agricultural soil. Firstly, employing Vis-NIR and machine learning algorithms (MLAs) (Context 1) and secondly, applying Vis-NIR, soil chemical properties (SCP), and MLAs (Context 2). For the Vis-NIR information, single and combined pretreatment methods were applied. The following MLAs were used: conditional inference forest (CIF), partial least squares regression (PLSR), M5 tree model (M5), extreme gradient boosting (EGB), and support vector machine regression (SVMR) respectively. For context 1, the results indicated that M5-MSC (M5 tree model-multiplicative scatter correction) with coefficient of determination (R²) = 0.72, root mean square error (RMSE) = 21.08 (mg/kg), median absolute error (MdAE) = 13.69 and ratio of performance to interquartile range (RPIQ) = 1.63 was promising. Regarding context 2, CIF with spectral pretreatment and soil properties [CIF-DWTLOGMSC + SCP (conditional inference forest-discrete wavelet transformation-logarithmic transformation-multiplicative scatter correction-soil chemical properties)] yielded the best performance of R² = 0.86, RMSE = 14.52 (mg/kg), MdAE = 6.25 and RPIQ = 1.78. Altogether, for contexts 1 and 2, the CIF-DWTLOGMSC + SCP approach (context 2) was the best Zn model outcome for the agricultural soil. The uncertainty map revealed a low to high error distribution in context 1, and a low to moderate distribution in context 2 for all models except CIF, which had some patches with high uncertainty. We conclude that a multiple optimization approach for modeling Zn levels in agricultural soils is invaluable and may provide fast and reliable information needed for area-specific decision-making.

Heterogeneity in biological assemblages and exposure in chemical risk assessment: Exploring capabilities and challenges in methodology with two landscape-scale case studies

Chemical exposure concentrations and the composition of ecological receptors (e.g., species) vary in space and time, resulting in landscape-scale (e.g. catchment) heterogeneity. Current regulatory, prospective chemical risk assessment frameworks do not directly address this heterogeneity because they assume that reasonably worst-case chemical exposure concentrations co-occur (spatially and temporally) with biological species that are the most sensitive to the chemical's toxicity. Whilst current approaches may parameterise fate models with site-specific data and aim to be protective, a more precise understanding of when and where chemical exposure and species sensitivity co-occur enables risk assessments to be better tailored and applied mitigation more efficient. We use two aquatic case studies covering different spatial and temporal resolution to explore how geo-referenced data and spatial tools might be used to account for landscape heterogeneity of chemical exposure and ecological assemblages in prospective risk assessment. Each case study followed a stepwise approach: i) estimate and establish spatial chemical exposure distributions using local environmental information and environmental fate models; ii) derive toxicity thresholds for different taxonomic groups and determine geo-referenced distributions of exposure-toxicity ratios (i.e., potential risk); iii) overlay risk data with the ecological status of biomonitoring sites to determine if relationships exist. We focus on demonstrating whether the integration of relevant data and potential approaches is feasible rather than making comprehensive and refined risk assessments of specific chemicals. The case studies indicate that geo-referenced predicted environmental concentration estimations can be achieved with available data, models and tools but establishing the distribution of species assemblages is reliant on the availability of a few sources of biomonitoring data and tools. Linking large sets of geo-referenced exposure and biomonitoring data is feasible but assessment of risk will often be limited by the availability of ecotoxicity data. The studies highlight the important influence that choices for aggregating data and for the selection of statistical metrics have on assessing and interpreting risk at different spatial scales and patterns of distribution within the landscape. Finally, we discuss approaches and development needs that could help to address environmental heterogeneity in chemical risk assessment.

Natural and anthropogenic factors and their interactions drive stream community integrity in a North American river basin at a large spatial scale

Urbanization, agriculture, and other human activities can exert considerable influence on the health and integrity of stream ecosystems. These influences vary greatly over space, time, and scale. We investigated trends in stream biotic integrity over 19 years (1997-2016) in relation to natural and anthropogenic factors in their spatial context using data from a stream biomonitoring program in a region dominated by agricultural land use. Macroinvertebrate and fish diversity and abundance data were used to calculate four multimetric indices (MMIs) that described biotic integrity of streams from 1997 to 2016. Boosted regression trees (BRT), a machine learning technique, were used to model how stream integrity responded to catchment-level natural and anthropogenic drivers including land use, human population density, road density, runoff potential, and natural factors such as latitude and elevation. Neither natural nor anthropogenic factors were consistently more influential on the MMIs. Macroinvertebrate indices were most responsive to time, latitude, elevation, and road density. Fish indices were driven mostly by latitude and longitude, with agricultural land cover among the most influential anthropogenic factors. We concluded that 1) stream biotic integrity was mostly stable in the study region from 1997 to 2016, although macroinvertebrate MMIs had decreased approximately 10% since 2010; 2) stream biotic integrity was driven by a mix of factors including geography, human activity, and variability over yearly time intervals; 3) MMI responses to environmental drivers were nonlinear and often nonmonotonic; 4) MMI composition could influence causal inferences; and 5) although our findings were mostly consistent with the literature on drivers of stream integrity, some commonly seen patterns were not evident. Our findings highlight the utility of large-scale, publicly available spatial data for understanding drivers of stream biodiversity and illustrate some potential pitfalls of large scale, integrative analyses.

Discovering Ecological Relationships in Flowing Freshwater Ecosystems

Knowledge of ecological responses to changes in the environment is vital to design appropriate measures for conserving biodiversity. Experimental studies are the standard to identify ecological cause-effect relationships, but their results do not necessarily translate to field situations. Deriving ecological cause-effect relationships from observational field data is, however, challenging due to potential confounding influences of unmeasured variables. Here, we present a causal discovery algorithm designed to reveal ecological relationships in rivers and streams from observational data. Our algorithm (a) takes into account the spatial structure of the river network, (b) reveals the complete network of ecological relationships, and (c) shows the directions of these relationships. We apply our algorithm to data collected in the US state of Ohio to better understand causes of reductions in fish and invertebrate community integrity. We found that nitrogen is a key variable underlying fish and invertebrate community integrity in Ohio, likely negatively impacting both. We also found that fish and community integrity are each linked to one physical habitat quality variable. Our algorithm further revealed a split between physical habitat quality and water quality variables, indicating that causal relations between these groups of variables are likely absent. Our approach is able to reveal networks of ecological relationships in rivers and streams based on observational data, without the need to formulate a priori hypotheses. This is an asset particularly for diagnostic assessments of the ecological state and potential causes of biodiversity impairment in rivers and streams.

A Critical Review of Organic Ultraviolet Filter Exposure, Hazard, and Risk to Corals

There has been a rapid increase in public, political, and scientific interest regarding the impact of organic ultraviolet (UV) filters to coral reefs. Such filters are found in sunscreens and other consumer products and enter the aquatic environment via direct (i.e., recreational activities, effluents) or indirect (i.e., land runoff) pathways. This review summarizes the current state of the science regarding the concentration of organic UV filters in seawater and sediment near coral reef ecosystems and in coral tissues, toxicological data from early and adult life stages of coral species, and preliminary environmental risk characterizations. Up to 14 different organic UV filters in seawater near coral reefs have been reported across 12 studies, with the majority of concentrations in the nanograms per liter range. Nine papers report toxicological findings from no response to a variety of biological effects occurring in the micrograms per liter to milligrams per liter range, in part given the wide variations in experimental design and coral species and/or life stage used. This review presents key findings; scientific data gaps; flaws in assumptions, practice, and inference; and a number of recommendations for future studies to assess the environmental risk of organic UV filters to coral reef ecosystems. Environ Toxicol Chem 2021;40:967-988. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

SSDs revisited: part II-practical considerations in the development and use of application factors applied to species sensitivity distributions

Application factors are routinely applied in the extrapolation of laboratory aquatic toxicity data to ensure protection from exposure to chemicals in the natural environment. The magnitude of the application factor is both a scientific and a policy decision, but in any case, it should be rooted in scientific knowledge so as to not be arbitrary. Information-rich chemicals are often subjected to species sensitivity distribution (SSD) analysis to transparently describe certain aspects of assessment uncertainty and are normally subjected to much smaller application factors than screening information data sets. We describe a new set of tools useful to assess the quality of SSDs. Twenty-two data sets and 19 chemicals representing agrochemicals, biocides, surfactants, metals, and common wastewater contaminants were compiled to demonstrate how the tools can be used. "Add-one-in" and "leave-one-out" simulations were used to investigate SSD robustness and develop quantitative evidence for the use of application factors. Theoretical new toxicity data were identified for add-one-in simulations based on the expected probabilities necessary to lower the hazardous concentration to 5% of a species (HC5) by a factor of 2, 3, 5, or 10. Simulations demonstrate the basis for application factors in the range of 1 to 5 for well-studied chemicals with high-quality SSDs. Leave-one-out simulations identify the fact that the most influential values in the SSD come from the extremes of the sensitive and tolerant toxicity values. Mesocosm and field data consistently demonstrate that HC5s are conservative, further justifying the use of small application factors for high-quality SSDs. Environ Toxicol Chem 2019;38:1526-1541. © 2019 SETAC.

Toward sustainable environmental quality: Priority research questions for Europe

The United Nations' Sustainable Development Goals have been established to end poverty, protect the planet, and ensure prosperity for all. Delivery of the Sustainable Development Goals will require a healthy and productive environment. An understanding of the impacts of chemicals which can negatively impact environmental health is therefore essential to the delivery of the Sustainable Development Goals. However, current research on and regulation of chemicals in the environment tend to take a simplistic view and do not account for the complexity of the real world, which inhibits the way we manage chemicals. There is therefore an urgent need for a step change in the way we study and communicate the impacts and control of chemicals in the natural environment. To do this requires the major research questions to be identified so that resources are focused on questions that really matter. We present the findings of a horizon-scanning exercise to identify research priorities of the European environmental science community around chemicals in the environment. Using the key questions approach, we identified 22 questions of priority. These questions covered overarching questions about which chemicals we should be most concerned about and where, impacts of global megatrends, protection goals, and sustainability of chemicals; the development and parameterization of assessment and management frameworks; and mechanisms to maximize the impact of the research. The research questions identified provide a first-step in the path forward for the research, regulatory, and business communities to better assess and manage chemicals in the natural environment. Environ Toxicol Chem 2018;37:2281-2295. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Aquatic exposures of chemical mixtures in urban environments: Approaches to impact assessment

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes, from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the event mean concentration concept, with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modeling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed of the role of nonchemical stressors in such highly modified urban water bodies. Environ Toxicol Chem 2018;37:703-714. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Prospective aquatic risk assessment for chemical mixtures in agricultural landscapes

Environmental risk assessment of chemical mixtures is challenging because of the multitude of possible combinations that may occur. Aquatic risk from chemical mixtures in an agricultural landscape was evaluated prospectively in 2 exposure scenario case studies: at field scale for a program of 13 plant-protection products applied annually for 20 yr and at a watershed scale for a mixed land-use scenario over 30 yr with 12 plant-protection products and 2 veterinary pharmaceuticals used for beef cattle. Risk quotients were calculated from regulatory exposure models with typical real-world use patterns and regulatory acceptable concentrations for individual chemicals. The results could differentiate situations when there was concern associated with single chemicals from those when concern was associated with a mixture (based on concentration addition) with no single chemical triggering concern. Potential mixture risk was identified on 0.02 to 7.07% of the total days modeled, depending on the scenario, the taxa, and whether considering acute or chronic risk. Taxa at risk were influenced by receiving water body characteristics along with chemical use profiles and associated properties. The present study demonstrates that a scenario-based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. Environ Toxicol Chem 2018;37:674-689. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Identification and ranking of environmental threats with ecosystem vulnerability distributions

Responses of ecosystems to human-induced stress vary in space and time, because both stressors and ecosystem vulnerabilities vary in space and time. Presently, ecosystem impact assessments mainly take into account variation in stressors, without considering variation in ecosystem vulnerability. We developed a method to address ecosystem vulnerability variation by quantifying ecosystem vulnerability distributions (EVDs) based on monitoring data of local species compositions and environmental conditions. The method incorporates spatial variation of both abiotic and biotic variables to quantify variation in responses among species and ecosystems. We show that EVDs can be derived based on a selection of locations, existing monitoring data and a selected impact boundary, and can be used in stressor identification and ranking for a region. A case study on Ohio’s freshwater ecosystems, with freshwater fish as target species group, showed that physical habitat impairment and nutrient loads ranked highest as current stressors, with species losses higher than 5% for at least 6% of the locations. EVDs complement existing approaches of stressor assessment and management, which typically account only for variability in stressors, by accounting for variation in the vulnerability of the responding ecosystems.

Future needs and recommendations in the development of species sensitivity distributions: Estimating toxicity thresholds for aquatic ecological communities and assessing impacts of chemical exposures

A species sensitivity distribution (SSD) is a probability model of the variation of species sensitivities to a stressor, in particular chemical exposure. The SSD approach has been used as a decision support tool in environmental protection and management since the 1980s, and the ecotoxicological, statistical, and regulatory basis and applications continue to evolve. This article summarizes the findings of a 2014 workshop held by the European Centre for Toxicology and Ecotoxicology of Chemicals and the UK Environment Agency in Amsterdam, The Netherlands, on the ecological relevance, statistical basis, and regulatory applications of SSDs. An array of research recommendations categorized under the topical areas of use of SSDs, ecological considerations, guideline considerations, method development and validation, toxicity data, mechanistic understanding, and uncertainty were identified and prioritized. A rationale for the most critical research needs identified in the workshop is provided. The workshop reviewed the technical basis and historical development and application of SSDs, described approaches to estimating generic and scenario-specific SSD-based thresholds, evaluated utility and application of SSDs as diagnostic tools, and presented new statistical approaches to formulate SSDs. Collectively, these address many of the research needs to expand and improve their application. The highest priority work, from a pragmatic regulatory point of view, is to develop a guidance of best practices that could act as a basis for global harmonization and discussions regarding the SSD methodology and tools. Integr Environ Assess Manag 2017;13:664-674. © 2016 SETAC.

Towards the review of the European Union Water Framework Directive: Recommendations for more efficient assessment and management of chemical contamination in European surface water resources

Water is a vital resource for natural ecosystems and human life, and assuring a high quality of water and protecting it from chemical contamination is a major societal goal in the European Union. The Water Framework Directive (WFD) and its daughter directives are the major body of legislation for the protection and sustainable use of European freshwater resources. The practical implementation of the WFD with regard to chemical pollution has faced some challenges. In support of the upcoming WFD review in 2019 the research project SOLUTIONS and the European monitoring network NORMAN has analyzed these challenges, evaluated the state-of-the-art of the science and suggested possible solutions. We give 10 recommendations to improve monitoring and to strengthen comprehensive prioritization, to foster consistent assessment and to support solution-oriented management of surface waters. The integration of effect-based tools, the application of passive sampling for bioaccumulative chemicals and an integrated strategy for prioritization of contaminants, accounting for knowledge gaps, are seen as important approaches to advance monitoring. Including all relevant chemical contaminants in more holistic "chemical status" assessment, using effect-based trigger values to address priority mixtures of chemicals, to better consider historical burdens accumulated in sediments and to use models to fill data gaps are recommended for a consistent assessment of contamination. Solution-oriented management should apply a tiered approach in investigative monitoring to identify toxicity drivers, strengthen consistent legislative frameworks and apply solutions-oriented approaches that explore risk reduction scenarios before and along with risk assessment.

Eco-epidemiology of aquatic ecosystems: Separating chemicals from multiple stressors

A non-toxic environment and a good ecological status are policy goals guiding research and management of chemicals and surface water systems in Europe and elsewhere. Research and policies on chemicals and water are however still disparate and unable to evaluate the relative ecological impacts of chemical mixtures and other stressors. This paper defines and explores the use of eco-epidemiological analysis of surveillance monitoring data sets via a proxy to quantify mixture impacts on ecosystems. Case studies show examples of different, progressive steps that are possible. Case study data were obtained for various regions in Europe and the United States. Data types relate to potential stressors at various scales, concerning landscape, land-use, in-stream physico-chemical and pollutant data, and data on fish and invertebrates. The proxy-values for mixture impacts were quantified as predicted (multi-substance) Potentially Affected Fractions of species (msPAF), using Species Sensitivity Distribution (SSD) models in conjunction with bioavailability and mixture models. The case studies summarize the monitoring data sets and the subsequent diagnostic bioassessments. Variation in mixture toxic pressures amongst sites appeared to covary with abundance changes in large (50-86%) percentages of taxa for the various study regions. This shows that an increased mixture toxic pressure (msPAF) relates to increased ecological impacts. Subsequent multi-stressor evaluations resulted in statistically significant, site-specific diagnosis of the magnitudes of ecological impacts and the relative contributions of different stress factors to those impacts. This included both mixtures and individual chemicals. These results allow for ranking stressors, sites and impacted species groups. That is relevant information for water management. The case studies are discussed in relation to policy and management strategies that support reaching a non-toxic environment and good ecological status. Reaching these goals requires not only focused sectoral policies, such as on chemical- or water management, but also an overarching and solution-focused view.

A framework for screening sites at risk from contaminants of emerging concern

Trace levels of a variety of currently unregulated organic chemicals have been detected in treated wastewater effluents and surface waters that receive treated effluents. Many of these chemicals of emerging concern (CECs) originate from pharmaceuticals and personal care products that are used widely and that frequently are transported "down the drain" to a wastewater treatment plant (WWTP). Actual effects of CECs on aquatic life have been difficult to document, although biological effects consistent with effects of some CECs have been noted. There is a critical need to find appropriate ways to screen wastewater sites that have the greatest potential of CEC risk to biota. Building on the work of several researchers, the authors present a screening framework, as well as examples based on the framework, designed to identify high-risk versus lower-risk sites that are influenced by WWTP effluent. It is hoped that this framework can help researchers, utilities, and the larger water resource community focus efforts toward improving CEC risk determinations and management of these risks.