Perceived multiple stressor effects depend on sample size and stressor gradient length

Unveiling growth and carbon composition of macroalgae with different strategies under global change

Marine macroalgae ecosystems are increasingly recognized as potential contributors to carbon sequestration within blue carbon strategies. This study investigates how the carbon storage capacity of two macroalgal species with different living strategies, Fucus vesiculosus (k-strategy, slow-growing) and Ulva lactuca (r-strategy, fast-growing), respond to the individual or combined impacts of two drivers of global change, eutrophication and marine heatwaves. Differences in growth, biomass and carbon accumulation were assessed after 7 and 14 days in two experiments (field and laboratory) that tested different combinations of nutrient enrichment (increase nutrient/surface area of 1 g/cm2 in the field experiment and a concentration of 10 ml/l of Provasoli solution in the laboratory) and warming (5 °C increase) treatments. Results revealed that nutrient addition treatments had significant effects, reducing carbon incorporation by up to 22.5 % in F. vesiculosus compared to control. This reduction was particularly evident in the field experiment, suggesting that eutrophication negatively impacts the carbon storage potential of this slow-growing species. However, F. vesiculosus demonstrated greater resilience in maintaining biomass stability, whereas U. lactuca exhibited reduced growth and carbon accumulation under natural conditions. These findings highlight species-specific differences in carbon assimilation and biomass composition among macroalgae, which can influence their potential contribution to carbon cycling and storage in marine ecosystems, shaped by their ecological and physiological traits, and emphasize the importance of nutrient management for optimizing blue carbon storage. This research contributes to our understanding of macroalgae's role in climate mitigation and underscores the need for targeted conservation strategies to enhance their ecosystem services.

Incorporating stressor interactions into spatially explicit cumulative impact assessments

Human-induced stressors are impacting the oceans and reducing the biodiversity of marine ecosystems. The many stressors affecting marine environments do not act in isolation. However, their cumulative impact is difficult to predict. Most of the available methods for quantifying cumulative impacts on marine ecosystems sum the impact of individual stressors to estimate cumulative impact. We demonstrate how experimental evidence from interacting stressors can be accounted for in cumulative impact assessments. We adapted a widely used additive model to incorporate nonadditive stressor interactions into a marine spatially explicit cumulative impact assessment for seagrasses. We combined experimental data on the impact of multiple stressors with spatial data on stressor intensity to test whether stressor interactions impact seagrasses in a case study region in South Australia. We also assessed how uncertainty about cumulative impacts changes when uncertainty in stressor interactions is included in the impact mapping. The results from an additive spatial cumulative impact assessment model were compared with results from the model incorporating interactions. Cumulative effects from the interaction model were more variable than those produced by the additive model. Five of the 15 stressor interactions that we tested produced impacts that significantly deviated from those predicted by an additive model. Areas of our study region that showed the largest discrepancies between the additive and interactive outputs were also associated with higher uncertainty. Our study demonstrates that the inclusion of stressor interactions changes the pattern and intensity of modeled spatial cumulative impact. Additive models have the potential to misrepresent cumulative impact intensity and do not provide the opportunity for targeted mitigation measures when managing the interactive effects of stressors. Appropriate inclusion of interacting stressor data may have implications for the identification of key stressors and the subsequent spatial planning and management of marine ecosystems and biodiversity.

Reconciling Variability in Multiple Stressor Effects Using Environmental Performance Curves

Understanding the effects of multiple stressors has become a major focus in ecology and evolution. While many studies have investigated the combined effects of stressors, revealing massive variability, a mechanistic understanding that reconciles the diversity of multiple stressor outcomes is lacking. Here, we show how performance curves can fill this gap by revealing mechanisms that shape multiple stressor outcomes. Our experiments with 12 bacterial taxa, demonstrate that additional stressors alter the shape of temperature, pH and salinity performance curves. This leads to changes in stressor interaction outcomes-for example, shifts between additive, antagonistic or synergistic interactions-along gradients, revealing that small changes in a stressor along nonlinear performance curves can dramatically impact the stressor interaction. These findings help to explain the lack of generality found across multiple stressor studies and highlight how a performance curve approach can provide a more holistic view of multiple stressor interactions.

Influence of salinity on the thermal tolerance of aquatic organisms

Aquatic organisms are challenged by changes in their external environment, such as temperature and salinity fluctuations. If these variables interacted with each other, the response of organisms to temperature changes would be modified by salinity and vice versa. We tested for potential interaction between temperature and salinity effects on freshwater, brackish, and marine organisms, including algae, macrophytes, heterotrophic protists, parasites, invertebrates, and fish. We performed a meta-analysis that compared the thermal tolerance (characterised by the temperature optimum, lower and upper temperature limits, and thermal breadth) at various salinities. The meta-analysis was based on 90 articles (algae: 15; heterotrophic protists: 1; invertebrates: 43; and fish: 31). Studies on macrophytes and parasites were lacking. We found that decreasing salinity significantly increased and decreased the lower and upper temperature limits, respectively, in all groups. Thus, a lowered salinity increased the thermal sensitivity of organisms. These findings mainly reflect the response of brackish and marine organisms to salinity changes, which dominated our database. The few studies on freshwater species showed that their lower thermal limits increased and the upper thermal limits decreased with increasing salinity, albeit statistically nonsignificant. Although non-significant, the response of thermal tolerance to salinity changes differed between various organism groups. It generally decreased in the order of: algae > invertebrates > fish. Overall, our findings indicate adverse effects of salinity changes on the temperature tolerance of aquatic organisms. For freshwater species, studies are comparatively scarce and further studies on their thermal performance at various salinity gradients are required to obtain more robust evidence for interactions between salinity and temperature tolerance. Considering test conditions such as acclimation temperature and potential infection with parasites in future studies may decrease the variability in the relationship between salinity and thermal tolerance.

Improving multiple stressor-response models through the inclusion of nonlinearity and interactions among stressor gradients

Stressor-response models are used to detect and predict changes within ecosystems in response to anthropogenic and naturally occurring stressors. While nonlinear stressor-response relationships and interactions between stressors are common in nature, predictive models often do not account for them due to perceived difficulties in the interpretation of results. We used Irish river monitoring data from 177 river sites to investigate if multiple stressor-response models can be improved by accounting for nonlinearity, interactions in stressor-response relationships and environmental context dependencies. Out of the six models of distinct biological responses, five models benefited from the inclusion of nonlinearity while all six benefited from the inclusion of interactions. The addition of nonlinearity means that we can better see the exponential increase in Trophic Diatom Index (TDI3) as phosphorus increases, inferring ecological conditions deteriorating at a faster rate with increasing phosphorus. Furthermore, our results show that the relationship between stressor and response has the potential to be dependent on other variables, as seen in the interaction of elevation with both siltation and nutrients in relation to Ephemeroptera, Plecoptera and Trichoptera (EPT) richness. Both relationships weakened at higher elevations, perhaps demonstrating that there is a decreased capacity for resilience to stressors at lower elevations due to greater cumulative effects. Understanding interactions such as this is vital to managing ecosystems. Our findings provide empirical support for the need to further develop and employ more complex modelling techniques in environmental assessment and management.

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.

Effects of agriculture on river biota differ between crop types and organism groups

While the general effects of agricultural land use on riverine biota are well documented, the differential effects of specific crop types on different riverine organism groups, remain largely unexplored. Here we used recently published land use data distinguishing between specific crop types and a Germany-wide dataset of 7748 sites on the ecological status of macroinvertebrates, macrophytes and diatoms and applied generalized linear mixed models to unravel the associations between land use types, crop types, and the ecological status. For all organism groups, associations of specific crop types with biota were stronger than those of urban land use. For macroinvertebrates and macrophytes, strong negative associations were found for pesticide intensive permanent crops, while intensively fertilized crops (maize, intensive cereals) affected diatoms most. These differential associations highlight the importance of distinguishing between crop types and organism groups and the urgency to buffer rivers against agricultural stressors at the catchment scales and to expand sustainably managed agriculture.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Hot and heavy: Responses of ragworms (Hediste diversicolor) to copper-spiked sediments and elevated temperature

Sediment contamination and seawater warming are two major stressors to macrobenthos in estuaries. However, little is known about their combined effects on infaunal organisms. Here we investigated the responses of an estuarine polychaete Hediste diversicolor to metal-contaminated sediment and increased temperature. Ragworms were exposed to sediments spiked with 10 and 20 mg kg^-1 of copper at 12 and 20 °C for three weeks. No considerable changes were observed in the expression of genes related to copper homeostasis and in the accumulation of oxidative stress damage. Dicarbonyl stress was attenuated by warming exposure. Whole-body energy reserves in the form of carbohydrates, lipids and proteins were little affected, but the energy consumption rate increased with copper exposure and elevated temperature indicating higher basal maintenance costs of ragworms. The combined effects of copper and warming exposures were mostly additive, with copper being a weak stressor and warming a more potent stressor. These results were replicable, as confirmed by two independent experiments of similar settings conducted at two different months of the year. This study suggests the higher sensitivity of energy-related biomarkers and the need to search for more conserved molecular markers of metal exposure in H. diversicolor.

Twenty-eight years of ecosystem recovery and destabilisation: Impacts of biological invasions and climate change on a temperate river

Most river ecosystems are exposed to multiple anthropogenic stressors affecting the composition and functionality of benthic communities. Identifying main causes and detecting potentially alarming trends in time depends on the availability of long-term monitoring data sets. Our study aimed to improve the knowledge about community effects of multiple stressors that is needed for effective, sustainable management and conservation. We conducted a causal analysis to detect the dominant stressors and hypothesised that multiple stressors, such as climate change and multiple biological invasions, reduce biodiversity and thus endanger ecosystem stability. Using a data set from 1992 to 2019 for the benthic macroinvertebrate community of a 65-km stretch of the upper Elbe river in Germany, we evaluated the effects of alien species, temperature, discharge, phosphorus, pH and abiotic conditional variables on the taxonomic and functional composition of the benthic community and analysed the temporal behaviour of biodiversity metrics. We observed fundamental taxonomic and functional changes in the community, with a shift from collectors/gatherers to filter feeders and feeding opportunists preferring warm temperatures. A partial dbRDA revealed significant effects of temperature and alien species abundance and richness. The occurrence of distinct phases in the development of community metrics suggests a temporally varying impact of different stressors. Taxonomic and functional richness responded more sensitively than the diversity metrics whereas the functional redundancy metric remained unchanged. Especially the last 10-year phase, however, showed a decline in richness metrics and an unsaturated, linear relationship between taxonomic and functional richness, which rather indicates reduced functional redundancy. We conclude that the varying anthropogenic stressors over three decades, mainly biological invasions and climate change, affected the community severely enough to increase its vulnerability to future stressors. Our study highlights the importance of long-term monitoring data and emphasises a careful use of biodiversity metrics, preferably considering also community composition.

Adverse effects of the pesticide chlorpyrifos on the physiology of a damselfly only occur at the cold and hot extremes of a temperature gradient

Ecotoxicological studies considerably improved realism by assessing the toxicity of pollutants at different temperatures. Nevertheless, they may miss key interaction patterns between pollutants and temperature by typically considering only part of the natural thermal gradient experienced by species and ignoring daily temperature fluctuations (DTF). We therefore tested in a common garden laboratory experiment the effects of the pesticide chlorpyrifos across a range of mean temperatures and DTF on physiological traits (related to oxidative stress and bioenergetics) in low- and high-latitude populations of Ischnura elegans damselfly larvae. As expected, the impact of chlorpyrifos varied along the wide range of mean temperatures (12-34 °C). None of the physiological traits (except the superoxide anion levels) were affected by chlorpyrifos at the intermediate mean temperatures (20-24 °C). Instead, most of them were negatively affected by chlorpyrifos (reduced activity levels of the antioxidant defense enzymes superoxide dismutase [SOD], catalase [CAT] and peroxidase [PER], and a reduced energy budget) at the very high (≥28 °C) or extreme high temperatures (≥32 °C), and to lesser extent at the lower mean temperatures (≤16 °C). Notably, at the lower mean temperatures the negative impact of chlorpyrifos was often only present or stronger under DTF. Although the chlorpyrifos effects on the physiological traits greatly depended on the experimentally imposed thermal gradient, patterns were mainly consistent across the natural latitude-associated thermal gradient, indicating the generality of our results. The thermal patterns in chlorpyrifos-induced physiological responses contributed to the observed toxicity patterns in life history (reduced survival and growth at low and high mean temperatures). Taken together, our results underscore the importance of evaluating pesticide toxicity along a temperature gradient and of taking a mechanistic approach with a focus on physiology, to improve our understanding of the combined effects of pollutants and temperature in natural populations.

Microplastics increases the heat tolerance of Daphnia magna under global warming via hormetic effects

The ecological risk assessment of microplastics under global warming receives increasing attention. Yet, such studies mostly focused on increased mean temperatures (MT), ignoring another key component of global warming, namely daily temperature fluctuations (DTF). Moreover, we know next to nothing about the combined effects of multigenerational exposure to microplastics and warming. In this study, Daphnia magna was exposed to an environmentally relevant concentration of polystyrene microplastics (5 μg L-1) under six thermal conditions (MT: 20 ℃, 24 ℃; DTF: 0 ℃, 5 ℃, 10 ℃) over two generations to investigate the interactive effects of microplastics and global warming. Results showed that microplastics had no effects on Daphnia at standard thermal conditions (constant 20 °C). Yet, microplastics increased the fecundity, heat tolerance, amount of energy storage, net energy budget and cytochrome P450 activity, and decreased the energy consumption when tested under an increased MT or DTF, indicating a hormesis effect induced by microplastics under warming. The unexpected increase in heat tolerance upon exposure to microplastics could be partly explained by the reduced energy consumption and/or increased energy availability. Overall, the present study highlighted the importance of including DTF and multigenerational exposure to improve the ecological risk assessment of microplastics under global warming.