Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple-stressor experiments.

Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple-stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co-occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open-source and interactive version of the dataset (https://jamesaorr.shinyapps.io/freshwater-multiple-stressors/). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple-stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors.

Land use changes biomass and temporal patterns of insect cross-ecosystem flows.

Emergent aquatic insects constitute an important food source for higher trophic levels, linking aquatic to terrestrial ecosystems. Little is known about how land use affects the biomass or composition of insect emergence. Previous studies are limited to individual time points or seasons, hampering understanding of annual biomass export patterns and detection of phenological changes. Over 1 year's primary emergence period, we continuously determined the biomass, abundance, and identity of >45,000 aquatic insects and recorded land-use-related environmental variables in 20 stream sites using a paired design with upstream forested sites and downstream agricultural sites. Total insect biomass and abundance were 2-7 mg day-1  m-2 and 7-36 ind day-1  m-2 higher in agricultural than forested sites. However, we found turnover of families between forested and agricultural sites, with more insects with shorter generation time in agriculture, indicating lower sensitivity to land-use-related stress because of higher recovery potential. Except for stoneflies, biomass and abundance of major orders were higher in agriculture, but their phenology differed. For different orders, emergence peaked 30 days earlier to 51 days later in agriculture than forest, whereas total abundance and biomass both peaked earlier in agriculture: 3-5 and 3-19 days, respectively. The most important land-use-related drivers were pesticide toxicity and electrical conductivity, which were differentially associated with different aquatic insect order abundances and biomass. Overall, we found that land use was related to changes in composition and phenology of aquatic insect emergence, which is likely to affect food-web dynamics in a cross-ecosystem context.

Three perspectives on the prediction of chemical effects in ecosystems.

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Metal Exposure and Sex Shape the Fatty Acid Profile of Midges and Reduce the Aquatic Subsidy to Terrestrial Food Webs.

Aquatic micropollutants can be transported to terrestrial systems and their consumers by emergent aquatic insects. However, micropollutants, such as metals, may also affect the flux of physiologically important polyunsaturated fatty acids (PUFAs). As certain PUFAs have been linked to physiological fitness and breeding success of terrestrial consumers, reduced fluxes from aquatic systems could affect terrestrial populations and food webs. We chronically exposed larvae of the aquatic insect Chironomus riparius to a range of environmentally relevant sediment contents of cadmium (Cd) or copper (Cu) in a 28-day microcosm study. Since elevated water temperatures can enhance metals' toxic effects, we used two temperature regimes, control and periodically elevated temperatures (heat waves) reflecting an aspect of climate change. Cd and Cu significantly reduced adult emergence by up to 95% and 45%, respectively, while elevated temperatures had negligible effects. Both metal contents were strongly reduced (∼90%) during metamorphosis. Furthermore, the chironomid FA profile was significantly altered during metamorphosis with the factors sex and metal exposure being relevant predictors. Consequently, fluxes of physiologically important PUFAs by emergent adults were reduced by up to ∼80%. Our results suggest that considering fluxes of physiologically important compounds, such as PUFAs, by emergent aquatic insects is important to understand the implications of aquatic micropollutants on aquatic-terrestrial meta-ecosystems.

Local stressors mask the effects of warming in freshwater ecosystems.

Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude.

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

Invasion impacts and dynamics of a European-wide introduced species.

Globalization has led to the introduction of thousands of alien species worldwide. With growing impacts by invasive species, understanding the invasion process remains critical for predicting adverse effects and informing efficient management. Theoretically, invasion dynamics have been assumed to follow an "invasion curve" (S-shaped curve of available area invaded over time), but this dynamic has lacked empirical testing using large-scale data and neglects to consider invader abundances. We propose an "impact curve" describing the impacts generated by invasive species over time based on cumulative abundances. To test this curve's large-scale applicability, we used the data-rich New Zealand mud snail Potamopyrgus antipodarum, one of the most damaging freshwater invaders that has invaded almost all of Europe. Using long-term (1979-2020) abundance and environmental data collected across 306 European sites, we observed that P. antipodarum abundance generally increased through time, with slower population growth at higher latitudes and with lower runoff depth. Fifty-nine percent of these populations followed the impact curve, characterized by first occurrence, exponential growth, then long-term saturation. This behaviour is consistent with boom-bust dynamics, as saturation occurs due to a rapid decline in abundance over time. Across sites, we estimated that impact peaked approximately two decades after first detection, but the rate of progression along the invasion process was influenced by local abiotic conditions. The S-shaped impact curve may be common among many invasive species that undergo complex invasion dynamics. This provides a potentially unifying approach to advance understanding of large-scale invasion dynamics and could inform timely management actions to mitigate impacts on ecosystems and economies.

Towards a unified study of multiple stressors: divisions and common goals across research disciplines.

Anthropogenic environmental changes, or 'stressors', increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

Limitations of trait-based approaches for stressor assessment: The case of freshwater invertebrates and climate drivers.

The appeal of trait-based approaches for assessing environmental vulnerabilities arises from the potential insight they provide into the mechanisms underlying the changes in populations and community structure. Traits can provide ecologically based explanations for observed responses to environmental changes, along with predictive power gained by developing relationships between traits and environmental variables. Despite these potential benefits, questions remain regarding the utility and limitations of these approaches, which we explore focusing on the following questions: (a) How reliable are predictions of biotic responses to changing conditions based on single trait-environment relationships? (b) What factors constrain detection of single trait-environment relationships, and how can they be addressed? (c) Can we use information on meta-community processes to reveal conditions when assumptions underlying trait-based studies are not met? We address these questions by reviewing published literature on aquatic invertebrate communities from stream ecosystems. Our findings help to define factors that influence the successful application of trait-based approaches in addressing the complex, multifaceted effects of changing climate conditions on hydrologic and thermal regimes in stream ecosystems. Key conclusions are that observed relationships between traits and environmental stressors are often inconsistent with predefined hypotheses derived from current trait-based thinking, particularly related to single trait-environment relationships. Factors that can influence findings of trait-based assessments include intercorrelations of among traits and among environmental variables, spatial scale, strength of biotic interactions, intensity of habitat disturbance, degree of abiotic stress, and methods of trait characterization. Several recommendations are made for practice and further study to address these concerns, including using phylogenetic relatedness to address intercorrelation. With proper consideration of these issues, trait-based assessment of organismal vulnerability to environmental changes can become a useful tool to conserve threatened populations into the future.

Assessing the Mixture Effects in In Vitro Bioassays of Chemicals Occurring in Small Agricultural Streams during Rain Events.

Rain events may impact the chemical pollution burden in rivers. Forty-four small streams in Germany were profiled during several rain events for the presence of 395 chemicals and five types of mixture effects in in vitro bioassays (cytotoxicity; activation of the estrogen, aryl hydrocarbon, and peroxisome proliferator-activated receptors; and oxidative stress response). While these streams were selected to cover a wide range of agricultural impacts, in addition to the expected pesticides, wastewater-derived chemicals and chemicals typical for street runoff were detected. The unexpectedly high estrogenic effects in many samples indicated the impact by wastewater or overflow of combined sewer systems. The 128 water samples exhibited a high diversity of chemical and effect patterns, even for different rain events at the same site. The detected 290 chemicals explained only a small fraction (<8%) of the measured effects. The experimental effects of the designed mixtures of detected chemicals that were expected to dominate the mixture effects of detected chemicals were consistent with predictions for concentration addition within a factor of two for 94% of the mixtures. Overall, the burden of chemicals and effects was much higher than that previously detected in surface water during dry weather, with the effects often exceeding proposed effect-based trigger values.

Fungicides: An Overlooked Pesticide Class?

Fungicides are indispensable to global food security and their use is forecasted to intensify. Fungicides can reach aquatic ecosystems and occur in surface water bodies in agricultural catchments throughout the entire growing season due to their frequent, prophylactic application. However, in comparison to herbicides and insecticides, the exposure to and effects of fungicides have received less attention. We provide an overview of the risk of fungicides to aquatic ecosystems covering fungicide exposure (i.e., environmental fate, exposure modeling, and mitigation measures) as well as direct and indirect effects of fungicides on microorganisms, macrophytes, invertebrates, and vertebrates. We show that fungicides occur widely in aquatic systems, that the accuracy of predicted environmental concentrations is debatable, and that fungicide exposure can be effectively mitigated. We additionally demonstrate that fungicides can be highly toxic to a broad range of organisms and can pose a risk to aquatic biota. Finally, we outline central research gaps that currently challenge our ability to predict fungicide exposure and effects, promising research avenues, and shortcomings of the current environmental risk assessment for fungicides.

Effects of a Systemic Pesticide Along an Aquatic Tri-Trophic Food Chain.

Systemic pesticides, such as the neonicotinoid imidacloprid, can be introduced into aquatic ecosystems through contaminated plant material, which is the basis for detrital (brown) aquatic food-webs. With the aim of exemplarily assessing for indirect effects on the level of predators, we first offered imidacloprid contaminated and uncontaminated alder leaves to the stonefly shredder Protonemura sp. for 72 h. Shredder survival, leaf decomposition, body length and biomass were all between 20% and 50% lower under imidacloprid exposure compared to uncontaminated conditions, indicating physiological implications. Subsequently, these shredders were provided as prey to stonefly predators (Isoperla sp.) kept in cages in a stream. Predator biomass and length decreased by up to 11% and 4.3%, respectively, when feeding on imidacloprid exposed prey. Our study hence suggests that plant material contaminated with systemic pesticides can exert adverse effects in aquatic predators when preying on shredders consuming such leaves, which warrants a further consideration of this pathway.

Advancing understanding and prediction in multiple stressor research through a mechanistic basis for null models.

Global environmental change is driven by multiple anthropogenic stressors. Conservation and restoration require understanding the individual and joint action of these stressors to evaluate and prioritize management measures. To date, most studies on multiple stressor effects have sought to identify potential stressor interactions, defined as deviations from null models, and related meta-analyses have focused on quantifying the relative proportion of stressor interactions across studies. These studies have provided valuable insights about the complexity of multiple stressor effects, but remain largely devoid of a theoretical framework for null model selection and prediction of effects. We suggest that multiple stressor research would benefit by (1) integrating and developing additional null models and (2) selecting null models based on their mechanistic assumptions of the stressor mode of action and organism sensitivities as well as stressor-effect relationships for individuals and populations. We present a range of null models and outline their underlying assumptions and application in multiple stressor research. Moving beyond mere description requires multiple stressor research to shift its focus from identifying statistically significant interactions to the use and development of mechanistic (null) models. Justified selection of the appropriate null model is a first step to achieve this.

Contrasting effects of aquatic subsidies on a terrestrial trophic cascade.

Subsidies from adjacent ecosystems can alter recipient food webs and ecosystem functions, such as herbivory. Emerging aquatic insects from streams can be an important prey in the riparian zone. Such aquatic subsidies can enhance predator abundances or cause predators to switch prey, depending on the herbivores. This can lead to an increase or decrease of in situ herbivores and herbivory. We examined the effects of aquatic subsidies on a simplified terrestrial food web consisting of two types of herbivores, plants and predators (spiders). In our six-week experiment, we focused on the prey choice of the spiders by excluding predator immigration and reproduction. In accordance with predator switching, survival of leafhoppers increased in the presence of aquatic subsidies. By contrast, the presence of aquatic subsidies indirectly reduced weevils and herbivory. Our study shows that effects of aquatic subsidies on terrestrial predators can propagate through the food web in contrasting ways. Thereby, the outcome of the trophic cascade is determined by the prey choice of predators.

Large Scale Risks from Agricultural Pesticides in Small Streams.

Small streams are important refuges for biodiversity. In agricultural areas, they may be at risk from pesticide pollution. However, most related studies have been limited to a few streams on the regional level, hampering extrapolation to larger scales. We quantified risks as exceedances of regulatory acceptable concentrations (RACs) and used German monitoring data to quantify the drivers thereof and to assess current risks in small streams on a large scale. The data set was comprised of 1 766 104 measurements of 478 pesticides (including metabolites) related to 24 743 samples from 2301 sampling sites. We investigated the influence of agricultural land use, catchment size, as well as precipitation and seasonal dynamics on pesticide risk taking also concentrations below the limit of quantification into account. The exceedances of risk thresholds dropped 3.7-fold at sites with no agriculture. Precipitation increased detection probability by 43%, and concentrations were the highest from April to June. Overall, this indicates that agricultural land use is a major contributor of pesticides in streams. RACs were exceeded in 26% of streams, with the highest exceedances found for neonicotinoid insecticides. We conclude that pesticides from agricultural land use are a major threat to small streams and their biodiversity. To reflect peak concentrations, current pesticide monitoring needs refinement.

Organic chemicals jeopardize the health of freshwater ecosystems on the continental scale.

Organic chemicals can contribute to local and regional losses of freshwater biodiversity and ecosystem services. However, their overall relevance regarding larger spatial scales remains unknown. Here, we present, to our knowledge, the first risk assessment of organic chemicals on the continental scale comprising 4,000 European monitoring sites. Organic chemicals were likely to exert acute lethal and chronic long-term effects on sensitive fish, invertebrate, or algae species in 14% and 42% of the sites, respectively. Of the 223 chemicals monitored, pesticides, tributyltin, polycyclic aromatic hydrocarbons, and brominated flame retardants were the major contributors to the chemical risk. Their presence was related to agricultural and urban areas in the upstream catchment. The risk of potential acute lethal and chronic long-term effects increased with the number of ecotoxicologically relevant chemicals analyzed at each site. As most monitoring programs considered in this study only included a subset of these chemicals, our assessment likely underestimates the actual risk. Increasing chemical risk was associated with deterioration in the quality status of fish and invertebrate communities. Our results clearly indicate that chemical pollution is a large-scale environmental problem and requires far-reaching, holistic mitigation measures to preserve and restore ecosystem health.

Contribution of waste water treatment plants to pesticide toxicity in agriculture catchments.

Pesticide residues are frequently found in water bodies and may threaten freshwater ecosystems and biodiversity. In addition to runoff or leaching from treated agricultural fields, pesticides may enter streams via effluents from wastewater treatment plants (WWTPs). We compared the pesticide toxicity in terms of log maximum Toxic Unit (log mTU) of sampling sites in small agricultural streams of Germany with and without WWTPs in the upstream catchments. We found an approximately half log unit higher pesticide toxicity for sampling sites with WWTPs (p < 0.001). Compared to fungicides and insecticides, herbicides contributed most to the total pesticide toxicity in streams with WWTPs. A few compounds (diuron, terbuthylazin, isoproturon, terbutryn and Metazachlor) dominated the herbicide toxicity. Pesticide toxicity was not correlated with upstream distance to WWTP (Spearman's rank correlation, rho = - 0.11, p > 0.05) suggesting that other context variables are more important to explain WWTP-driven pesticide toxicity. Our results suggest that WWTPs contribute to pesticide toxicity in German streams.

Evolutionary patterns and physicochemical properties explain macroinvertebrate sensitivity to heavy metals.

Ecological risk assessment depends strongly on species sensitivity data. Typically, sensitivity data are based on laboratory toxicity bioassays, which for practical constraints cannot be exhaustively performed for all species and chemicals available. Bilinear models integrating phylogenetic information of species and physicochemical properties of compounds allow to predict species sensitivity to chemicals. Combining the molecular information (DNA sequences) of 31 invertebrate species with the physicochemical properties of six bivalent metals, we built bilinear models that explained 70-80% of the variability in species sensitivity to heavy metals. Phylogeny was the most important component of the bilinear models, as it explained the major part of the explained variance (> 40%). Predicted values from bilinear modeling were in agreement with experimental values (> 50%); therefore, this approach is a good starting point to build statistical models which can potentially predict heavy metal toxicity for untested invertebrate species based on empirical values for similar species. Despite their good performance, development of the presented bilinear models would benefit from improved phylogenetic and toxicological datasets. Our analysis is an example for linking evolutionary biology with applied ecotoxicology. Its future applications may encompass other stress factors or traits influencing the survival of aquatic organisms in polluted environments.

Pesticides reduce regional biodiversity of stream invertebrates.

The biodiversity crisis is one of the greatest challenges facing humanity, but our understanding of the drivers remains limited. Thus, after decades of studies and regulation efforts, it remains unknown whether to what degree and at what concentrations modern agricultural pesticides cause regional-scale species losses. We analyzed the effects of pesticides on the regional taxa richness of stream invertebrates in Europe (Germany and France) and Australia (southern Victoria). Pesticides caused statistically significant effects on both the species and family richness in both regions, with losses in taxa up to 42% of the recorded taxonomic pools. Furthermore, the effects in Europe were detected at concentrations that current legislation considers environmentally protective. Thus, the current ecological risk assessment of pesticides falls short of protecting biodiversity, and new approaches linking ecology and ecotoxicology are needed.

Analysing chemical-induced changes in macroinvertebrate communities in aquatic mesocosm experiments: a comparison of methods.

Mesocosm experiments that study the ecological impact of chemicals are often analysed using the multivariate method 'Principal Response Curves' (PRCs). Recently, the extension of generalised linear models (GLMs) to multivariate data was introduced as a tool to analyse community data in ecology. Moreover, data aggregation techniques that can be analysed with univariate statistics have been proposed. The aim of this study was to compare their performance. We compiled macroinvertebrate abundance datasets of mesocosm experiments designed for studying the effect of various organic chemicals, mainly pesticides, and re-analysed them. GLMs for multivariate data and selected aggregated endpoints were compared to PRCs regarding their performance and potential to identify affected taxa. In addition, we analysed the inter-replicate variability encountered in the studies. Mesocosm experiments characterised by a higher taxa richness of the community and/or lower taxonomic resolution showed a greater inter-replicate variability, whereas variability decreased the more zero counts were encountered in the samples. GLMs for multivariate data performed equally well as PRCs regarding the community response. However, compared to first axis PRCs, GLMs provided a better indication of individual taxa responding to treatments, as separate models are fitted to each taxon. Data aggregation methods performed considerably poorer compared to PRCs. Multivariate community data, which are generated during mesocosm experiments, should be analysed using multivariate methods to reveal treatment-related community-level responses. GLMs for multivariate data are an alternative to the widely used PRCs.