Towards a general framework for the assessment of interactive effects of multiple stressors on aquatic ecosystems: Results from the Making Aquatic Ecosystems Great Again (MAEGA) workshop

A model for screening the fate and behaviour of the engineered nanoparticles in aquatic systems using semi-quantitative analysis and rule-based system

Concerns over the possible adverse effects of engineered nanoparticles (ENPs) on aquatic organisms have grown due to their continuous emission into aquatic systems. Consequently, to safeguard these aquatic life forms and support the sustainable use of ENPs, the characterisation of their exposure is necessary. Currently, despite the great amount of work reported to elucidate the exposure and risks of ENPs, cost-effective and easy-to-use exposure characterisation models are lacking and scarce. This study describes the use of semi-quantitative analysis (SQA) integrated with a rule-based system to evaluate ENP exposure in aquatic systems. The performance of the model was illustrated using case studies of nZnO, nTiO2, and nAg and theoretical examples that simulate natural systems. The results demonstrate that our proposed model can be highly valuable as an alternative approach for the preliminary screening of the exposure and possible environmental impact of ENPs in aquatic systems. The SQA application is relatively cost-effective and easy to use, since no software or mathematical computations are required. In addition, non-experts can easily understand the hierarchical nature, Boolean logic, and visual representations of simple rules using decision trees; which is highly valuable given that testing each variation of ENPs is tedious and associated with high cost.

Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach

The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20:367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Effects of heat and pesticide stress on life history, physiology and the gut microbiome of two congeneric damselflies that differ in stressor tolerance

The combined impact of toxicants and warming on organisms is getting increased attention in ecotoxicology, but is still hard to predict, especially with regard to heat waves. Recent studies suggested that the gut microbiome may provide mechanistic insights into the single and combined stressor effects on their host. We therefore investigated effects of sequential exposure to a heat spike and a pesticide on both the phenotype (life history and physiology) and the gut microbiome composition of damselfly larvae. We compared the fast-paced Ischnura pumilio, which is more tolerant to both stressors, with the slow-paced I. elegans, to obtain mechanistic insights into species-specific stressor effects. The two species differed in gut microbiome composition, potentially contributing to their pace-of-life differences. Intriguingly, there was a general resemblance between the stressor response patterns in the phenotype and in the gut microbiome, whereby both species responded broadly similar to the single and combined stressors. The heat spike negatively affected the life history of both species (increased mortality, reduced growth rate), which could be explained not only by shared negative effects on physiology (inhibition of acetylcholinesterase, increase of malondialdehyde), but also by shared effects on gut bacterial species' abundances. The pesticide only had negative effects (reduced growth rate, reduced net energy budget) in I. elegans. The pesticide generated shifts in the bacterial community composition (e.g. increased abundance of Sphaerotilus and Enterobacteriaceae in the gut microbiome of I. pumilio), which potentially contributed to the relatively higher pesticide tolerance of I. pumilio. Moreover, in line with the response patterns in the host phenotype, the effects of the heat spike and the pesticide on the gut microbiome were mainly additive. By contrasting two species differing in stress tolerance, our results suggest that response patterns in the gut microbiome may improve our mechanistic understanding of single and combined stressor effects.

Establishing ecologically-relevant nutrient thresholds: A tool-kit with guidance on its use

One key component of any eutrophication management strategy is establishment of realistic thresholds above which negative impacts become significant and provision of ecosystem services is threatened. This paper introduces a toolkit of statistical approaches with which such thresholds can be set, explaining their rationale and situations under which each is effective. All methods assume a causal relationship between nutrients and biota, but we also recognise that nutrients rarely act in isolation. Many of the simpler methods have limited applicability when other stressors are present. Where relationships between nutrients and biota are strong, regression is recommended. Regression relationships can be extended to include additional stressors or variables responsible for variation between water bodies. However, when the relationship between nutrients and biota is weaker, categorical approaches are recommended. Of these, binomial regression and an approach based on classification mismatch are most effective although both will underestimate threshold concentrations if a second stressor is present. Whilst approaches such as changepoint analysis are not particularly useful for meeting the specific needs of EU legislation, other multivariate approaches (e.g. decision trees) may have a role to play. When other stressors are present quantile regression allows thresholds to be established which set limits above which nutrients are likely to influence the biota, irrespective of other pressures. The statistical methods in the toolkit may be useful as part of a management strategy, but more sophisticated approaches, often generating thresholds appropriate to individual water bodies rather than to broadly defined "types", are likely to be necessary too. The importance of understanding underlying ecological processes as well as correct selection and application of methods is emphasised, along with the need to consider local regulatory and decision-making systems, and the ease with which outcomes can be communicated to non-technical audiences.

Combined effects of heatwaves and micropollutants on freshwater ecosystems: Towards an integrated assessment of extreme events in multiple stressors research

Freshwater ecosystems are strongly influenced by weather extremes such as heatwaves (HWs), which are predicted to increase in frequency and magnitude in the future. In addition to these climate extremes, the freshwater realm is impacted by the exposure to various classes of chemicals emitted by anthropogenic activities. Currently, there is limited knowledge on how the combined exposure to HWs and chemicals affects the structure and functioning of freshwater ecosystems. Here, we review the available literature describing the single and combined effects of HWs and chemicals on different levels of biological organization, to obtain a holistic view of their potential interactive effects. We only found a few studies (13 out of the 61 studies included in this review) that investigated the biological effects of HWs in combination with chemical pollution. The reported interactive effects of HWs and chemicals varied largely not only within the different trophic levels but also depending on the studied endpoints for populations or individuals. Hence, owing also to the little number of studies available, no consistent interactive effects could be highlighted at any level of biological organization. Moreover, we found an imbalance towards single species and population experiments, with only five studies using a multitrophic approach. This results in a knowledge gap for relevant community and ecosystem level endpoints, which prevents the exploration of important indirect effects that can compromise food web stability. Moreover, this knowledge gap impairs the validity of chemical risk assessments and our ability to protect ecosystems. Finally, we highlight the urgency of integrating extreme events into multiple stressors studies and provide specific recommendations to guide further experimental research in this regard.

Reviewing the effects of contamination on the biota of Brazilian coastal ecosystems: Scientific challenges for a developing country in a changing world

Pollution is a major worldwide problem that is increasing with urban growth, mainly along coastal areas. Pollution is often worse, governance is poorer and managerial strategies to improve environmental quality are less advanced in developing than developed countries. Here, we present an overview of the current scientific knowledge of the impacts of contamination on the biota of coastal ecosystems of Brazil and evaluate the scientific challenges to provide baseline information for local managerial purposes. We compiled data from 323 peer-reviewed published papers from the extensive Brazilian coast. We critically evaluated the produced knowledge (target contaminants, sources, ecosystems, taxa, response variables) and the science behind it (rigour and setting) within its socioenvironmental context (land occupation, use of the coast, sanitation status, contamination history). Research was driven largely by environmental outcomes of industrial development with a focus on the single effects of metals on the biota. The current knowledge derives mainly from laboratory manipulative experiments or from correlative field studies of changes in the biota with varying levels of contamination. Of these, 70% had problems in their experimental design. Environmental impacts have mainly been assessed using standard indicators of populations, mostly in ecotoxicological studies. Benthic assemblages have mostly been studied using structural indicators in field studies. Future assessments of impacts should expand research to more taxonomic groups and ecosystem compartments, adding combined functional and structural responses. Furthermore, further investigations need to consider the interactive effects of contaminants and other environmental stressors. By doing so, researchers would deliver more robust and effective results to solve problems of pollution.

Refocusing multiple stressor research around the targets and scales of ecological impacts

Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.

A guideline to frame stressor effects in freshwater ecosystems

Environmental policies fall short in protecting freshwater ecosystems, which are heavily threatened by human pressures and their associated stressors. One reason is that stressor effects depend on the context in which they occur and it is difficult to extrapolate patterns to predict the effect of stressors without these being contextualized in a general frame. This study aims at improving existing decision-making frameworks such as the DPSIR approach (Driver-Pressure-State-Impact-Response) or ERA (Environmental Risk Assessment) in the context of stressors. Here, we delve into stressor-impact relationships in freshwater ecosystems and develop a guideline which includes key characteristics such as stressor type, stressor duration, location, the natural levels of environmental variables to which each ecosystem is used to, among others. This guideline is intended to be useful in a wide range of ecosystem conditions and stressors. Incorporating these guidelines may favor the comparability of scientific results and may lead to a substantial advancement in the efficacy of diagnosis and predictive approaches of impacts.

How Do Indirect Effects of Contaminants Inform Ecotoxicology? A Review

Indirect effects in ecotoxicology are defined as chemical- or pollutant-induced alterations in the density or behavior of sensitive species that have cascading effects on tolerant species in natural systems. As a result, species interaction networks (e.g., interactions associated with predation or competition) may be altered in such a way as to bring about large changes in populations and/or communities that may further cascade to disrupt ecosystem function and services. Field studies and experimental outcomes as well as models indicate that indirect effects are most likely to occur in communities in which the strength of interactions and the sensitivity to contaminants differ markedly among species, and that indirect effects will vary over space and time as species composition, trophic structure, and environmental factors vary. However, knowledge of indirect effects is essential to improve understanding of the potential for chemical harm in natural systems. For example, indirect effects may confound laboratory-based ecological risk assessment by enhancing, masking, or spuriously indicating the direct effect of chemical contaminants. Progress to better anticipate and interpret the significance of indirect effects will be made as monitoring programs and long-term ecological research are conducted that facilitate critical experimental field and mesocosm investigations, and as chemical transport and fate models, individual-based direct effects models, and ecosystem/food web models continue to be improved and become better integrated.

Mosquito larvae that survive a heat spike are less sensitive to subsequent exposure to the pesticide chlorpyrifos

While extreme high temperatures are an important aspect of global warming, their effects on organisms are relatively understudied, especially in ecotoxicology. Sequential exposure to heat spikes and pesticides is a realistic scenario as both are typically transient stressors and are expected to further increase in frequency under global warming. We tested the effects of exposure to a lethal heat spike and subsequently to an ecologically relevant lethal pulse exposure of the pesticide chlorpyrifos in the larvae of mosquito Culex pipiens. The heat spike caused direct and delayed mortality, and resulted in a higher heat tolerance and activity of acetylcholinesterase, and a lower fat content in the survivors. The chlorpyrifos exposure caused mortality, accelerated growth rate, and decreased the heat tolerance and the activity of acetylcholinesterase. The preceding heat spike did not change how chlorpyrifos reduced the heat tolerance. Notably, the preceding heat spike did lower the lethal effect of the pesticide, which makes an important novel finding at the interface of ecotoxicology and global change biology, and adds a new dimension to the "climate-induced toxicant sensitivity" (CITS) concept. This may be due to both survival selection and cross-tolerance, and therefore likely a widespread phenomenon. Our results emphasize the importance of including extreme high temperatures as an important transient global change stressor in ecotoxicology.

Metabolite Changes in an Estuarine Annelid Following Sublethal Exposure to a Mixture of Zinc and Boscalid

Environmental pollutants such as heavy metals and fungicides pose a serious threat to waterways worldwide. Toxicological assessment of such contaminants is usually conducted using single compound exposures, as it is challenging to understand the effect of mixtures on biota using standard ecotoxicological methods; whereas complex chemical mixtures are more probable in ecosystems. This study exposed Simplisetia aequisetis (an estuarine annelid) to sublethal concentrations of a metal (zinc) and a fungicide (boscalid), both singly and as a mixture, for two weeks. Metabolomic analysis via gas and liquid chromatography-mass spectrometry was used to measure the stress response(s) of the organism following exposure. A total of 75 metabolites, including compounds contributing to the tricarboxylic acid cycle, the urea cycle, and a number of other pathways, were identified and quantified. The multiplatform approach identified distinct metabolomic responses to each compound that differed depending on whether the substance was presented singly or as a mixture, indicating a possible antagonistic effect. The study demonstrates that metabolomics is able to elucidate the effects and mode of action of contaminants and can identify possible outcomes faster than standard ecotoxicological endpoints, such as growth and reproduction. Metabolomics therefore has a possible future role in biomonitoring and ecosystem health assessments.

Urbanisation of floodplain ecosystems: Weight-of-evidence and network meta-analysis elucidate multiple stressor pathways

Freshwater floodplains are dynamic, diverse ecosystems that represent important transition zones between terrestrial, riparian, subsurface and aquatic habitats. Given their historic importance in human development, floodplains have been exposed to a variety of pressures, which in combination have been instrumental in driving changes within these ecosystems. Here, we present an evidence-based framework to explore direct and indirect effects of pressures and stressors on floodplain ecosystems and test this structure within the urban landscape. Evidence was obtained from peer-reviewed scientific literature, focusing on effects of key pressures and stressors on receptors, including species composition (e.g., species presence-absence, diversity) and ecosystem function (e.g., biomass, decomposition). The strength of direct and indirect effects of individual and multiple stressors on biological receptors was quantified using two separate analyses: an evidence-weighted analysis and a quantitative network meta-analysis using data extracted from 131 studies. Results demonstrate the power of adopting a systematic framework to advance quantitative assessment of floodplain ecosystems affected by multiple stressors. While direct pathways were generally stronger and provided the core network skeleton, there were many more significant indirect pathways indicating evidence gaps in our mechanistic understanding of these processes. Indeed, the importance of indirect pathways (e.g. increase in impervious surface → increase in the accumulation rate of sediment nutrients) suggests that embracing complexity in network meta-analysis is a necessary step in revealing a more complete snapshot of the network. Results from the weight-of-evidence approach generally mirrored the direct pathway structure and demonstrated the strength of incorporating study quality alongside data sufficiency. Networks illustrated novel disturbance pathways (e.g., decrease in habitat structure → decrease in structure and function of aquatic and riparian assemblages) that can be used for hypothesis generation for future scientific enquiries. Our results highlight the broader applicability of adopting the proposed framework for assessing complex environments, such as floodplains.

Qualifying the effects of single and multiple stressors on the food web structure of Dutch drainage ditches using a literature review and conceptual models

In September 2017, a workshop was held at Wageningen University and Research to determine the current state of knowledge of multiple stressor effects on aquatic ecosystems and to assess how to improve prediction of these effects. We developed a theoretical framework that integrates species-level responses to stressors to predict how these effects propagate through higher levels of biological organisation. Here, we present the application of the framework for drainage ditch ecosystems in the Netherlands. We used food webs to assess single and multiple stressor effects of common stressors on ditch communities. We reviewed the literature for the effects of targeted stressors (nutrients, pesticides, dredging and mowing, salinization, and siltation) on each functional group present in the food web and qualitatively assessed the relative sensitivity of groups. Using this information, we created a stressor-response matrix of positive and negative direct effects of each stressor-functional group combination. Fungicides, salinization, and sedimentation were identified as particularly detrimental to most groups, although destructive management practices, such as dredging with almost complete community removal, would take precedence depending on frequency. Using the stressor-response matrix we built, first, a series of conceptual null models of single stressor effects on food web structure and, second, a series of additive null models to illustrate potential paired-stressor effects. We compared these additive null models with published studies of the same pairs of combined single stressors to explore more complex interactions. Our approach serves as a first-step to considering multiple stressor scenarios in systems that are understudied or data-poor and as a baseline from which more complex models that include indirect effects and quantitative data may be developed. We make specific suggestions for appropriate management strategies that could be taken to support the biodiversity of these systems for individual stressors and their combined impacts.