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

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.

Global changes and their environmental stressors have a significant impact on soil biodiversity-A meta-analysis

Identifying the main threats to soil biodiversity is crucial as soils harbor ∼60% of global biodiversity. Many previous meta-analyses investigating the impact of different global changes (GCs) on biodiversity have omitted soil fauna or are limited by the GCs studied. We conducted a broad-scale meta-analysis focused on soil fauna communities, analyzing 3,161 effect sizes from 624 publications studying climate change, land-use intensification, pollution, nutrient enrichment, invasive species and habitat fragmentation. Land-use intensification resulted in large reductions in soil fauna communities, especially for the larger-bodied groups. Unexpectedly, pollution caused the largest negative impact on soil biodiversity - particularly worrying due to continually increasing levels of pollution and poor mechanistic understanding of impacts relative to other GCs. Not all GCs and stressors were detrimental; organic-based nutrient enrichment often resulted in positive responses. Including soil biodiversity in large-scale analyses is vital to fully understand the impact of GCs across the different realms.

Number and dissimilarity of global change factors influences soil properties and functions

Soil biota and functions are impacted by various anthropogenic stressors, including climate change, chemical pollution or microplastics. These stressors do not occur in isolation, and soil properties and functions appear to be directionally driven by the number of global change factors acting simultaneously. Building on this insight, we here hypothesize that co-acting factors with more diverse effect mechanisms, or higher dissimilarity, have greater impacts on soil properties and functions. We created a factor pool of 12 factors and calculated dissimilarity indices of randomly-chosen co-acting factors based on the measured responses of soil properties and functions to the single factors. Results show that not only was the number of factors important, but factor dissimilarity was also key for predicting factor joint effects. By analyzing deviations of soil properties and functions from three null model predictions, we demonstrate that higher factor dissimilarity and a larger number of factors could drive larger deviations from null models and trigger more frequent occurrence of synergistic factor net interactions on soil functions (decomposition rate, cellulase, and β-glucosidase activity), which provides mechanistic insights for understanding high-dimensional effects of factors. Our work highlights the importance of considering factor similarity in future research on interacting factors.

Combined effects of heat waves and pesticide pollution on zooplankton communities: Does the timing of stressor matter?

Most studies assessing the combined effects of chemical and non-chemical stressors on aquatic ecosystems have been based on synchronous stressor applications. However, asynchronous exposure scenarios may be more common in nature, particularly for pulsed stressors such as heatwaves and pesticide concentration peaks. In this study, we investigated the single and combined effects of the insecticide chlorpyrifos (CPF) and a heatwave (HW) on a zooplankton community representative of a Mediterranean coastal wetland using synchronous (CPF+HW) and asynchronous (HW→CPF and CPF→HW) exposure scenarios. CPF was applied at a concentration of 0.8 µg/L (single pulse), and the HW was simulated by a temperature increase of 8°C above the control temperature (20°C) for 7 days in freshwater microcosms. The interaction between stressors in synchrony resulted in synergistic effects at the population level (Daphnia magna) and additive at the community level. The partial reduction of sensitive species resulted in an abundance increase of competing species that were more tolerant to the evaluated stressors (e.g. Moina sp.). The asynchronous exposure scenarios resulted in a similar abundance decline of sensitive populations as compared to the synchronous one; however, the timing of stressor resulted in different responses in the long term. In the HW→CPF treatment, the D. magna population recovered at least one month faster than in the CPF+HW treatment, probably due to survival selection and cross-tolerance mechanisms. In the CPF→HW treatment, the effects lasted longer than in the CPF+HW, and the population did not recover within the experimental period, most likely due to the energetic costs of detoxification and effects on internal damage recovery. The different timing and magnitude of indirect effects among the tested asynchronous scenarios resulted in more severe effects on the structure of the zooplankton community in the CPF→HW treatment. Our study highlights the relevance of considering the order of stressors to predict the long-term effects of chemicals and heatwaves both at the population and community levels.

Path analysis reveals combined winter climate and pollution effects on the survival of a marine top predator

Marine ecosystems are experiencing growing pressure from multiple threats caused by human activities, with far-reaching consequences for marine food webs. Determining the effects of multiple stressors is complex, in part, as they can affect different aspects of biological organisation (behaviour, individual traits and demographic rates). Determining the combined effects of stressors, through different biological pathways, is key to predict the consequences for the viability of populations threatened by global change. Due to their position in the food chain, top predators such as seabirds are considered more sensitive to environmental changes. Climate change is affecting the prey resources available for seabirds, through bottom-up effects, while organic pollutants can bioaccumulate in food chains with the greatest impacts on top predators. However, knowledge of their combined effects on population dynamics is scarce. Using a path analysis, we quantify the effects of climate change and pollution on the survival of adult great black-backed gulls, both directly and through effects of individuals' body mass. Warmer ocean temperatures in gulls' winter foraging areas in the North Sea were correlated with higher survival, potentially explained by shifts in prey availability associated with global climate change. We also found support for indirect negative effects of organochlorines, highly toxic pollutants to seabirds, on survival, which acted, in part, through a negative effect on body mass. The results from this path analysis highlight how, even for such long-lived species where variance in survival tends to be limited, two stressors still have had a marked influence on adult survival and illustrate the potential of path models to improve predictions of population variability under multiple stressors.

Impact of singular versus combinatorial environmental stress on RONS generation in Drosophila melanogaster larvae

We investigated environmentally correlated abiotic stressor desiccation (D), heat (H), and starvation (S) in the generation of reactive oxygen and nitrogen species (RONS) using Drosophila melanogaster larvae as an experimental model, subjected to either individual stressors or exposed to a combinatorial form of stressors (D + H, H + S, and D + S). The study was also extended to find synergistic endpoints where the impacts of all three stressors (D + H + S) were exerted simultaneously. We estimated the lethal time (LT20) at specific doses using regression and probit analyses based on the larval survival. LT20 values were used as the base-level parameter for further oxidative stress experimental analysis work. First, all stressors led to the activation of a typical common oxidative stress-mediated response irrespective of the mode of exposure. As envisaged, D. melanogaster larvae exhibited a homeostatic stress tolerance mechanism, triggering an antioxidant defense mechanism, indicated by an elevated level of total antioxidant capacity and enhanced activities of superoxide dismutase, catalase, glutathione reductase, and glutathione peroxidase. In all types of stress-exposed regimes, we found a negative impact of stressors on the activity of mitochondrial enzyme aconitase. Elevated levels of other oxidative stress markers, viz., lipid peroxidation, protein carbonyl content, and advanced oxidative protein products, were obvious although the increment was treatment-specific. Desiccation stress proved to be the most dominant stressor compared to heat and starvation. Among the combination of stressors, rather than a single stressor, D + H impacted more than other binary stress exposures. Focusing on the impact of singular versus combinatorial stress exposure on RONS generation, we observed an increase in the RONS level in both singular and combinatorial forms of stress exposure although the magnitude of the increment varied with the nature of stressors and their combinations. The present study indicated an "additive" effect when all three stressors (D + H + S) operate simultaneously, rather than a "synergistic" effect.

Corticosterone and glucose are correlated and show similar response patterns to temperature and stress in a free-living bird

Glucocorticoid (GC) hormones have traditionally been interpreted as indicators of stress, but the extent to which they provide information on physiological state remains debated. GCs are metabolic hormones that amongst other functions ensure increasing fuel (i.e. glucose) supply on the face of fluctuating energetic demands, a role often overlooked by ecological studies investigating the consequences of GC variation. Furthermore, because energy budget is limited, in natural contexts where multiple stimuli coexist, the organisms' ability to respond physiologically may be constrained when multiple triggers of metabolic responses overlap in time. Using free-living spotless starling (Sturnus unicolor) chicks, we experimentally tested whether two stimuli of different nature known to trigger a metabolic or GC response, respectively, cause a comparable increase in plasma GCs and glucose. We further tested whether response patterns differed when both stimuli occurred consecutively. We found that both experimental treatments caused increases in GCs and glucose of similar magnitude, suggesting that both variables fluctuate along with variation in energy expenditure, independently of the trigger. Exposure to the two stimuli occurring subsequently did not cause a difference in GC or glucose responses compared with exposure to a single stimulus, suggesting a limited capacity to respond to an additional stimulus during an ongoing acute response. Lastly, we found a positive and significant correlation between plasma GCs and glucose after the experimental treatments. Our results add to the increasing research on the role of energy expenditure on GC variation, by providing experimental evidence on the association between plasma GCs and energy metabolism.

Putting the Asymmetric Response Concept to the test: Modeling multiple stressor exposure and release in a stream food web

Communities in stream ecosystems often respond asymmetrically to increase and release of stressors, as indicated by slow and incomplete recovery. The Asymmetric Response Concept (ARC) posits that this is due to a shift in the relative importance of three mechanisms: tolerance, dispersal, and biotic interactions. In complex natural communities, these mechanisms may produce alternative outcomes through poorly understood indirect effects. To understand how the three mechanisms respond to different temporal stressor scenarios, we studied multiple scenarios using a stream food web model. We asked the following questions: Do groups of species decline as expected on the basis of individual tolerance rankings derived from laboratory experiments when they are embedded in a complex dynamic food web? Does the response of ecosystem function match that of communities? To address these questions, we aggregated data on individual tolerances at the level of functional groups and studied how single and multiple stressors affect food web dynamics and nutrient cycling. Multiple stressor scenarios involved different intensities of salt and temperature increase. Functional groups exhibited a different relative tolerance ranking between the laboratory and dynamic food web contexts. Salt as a single stressor had only minor and transient effects at low level but led to the loss of one or more functional groups at high level. In contrast, high temperature, alone or in combination with salt, caused the loss of functional groups at all tested levels. Patterns often differed between the response of communities and ecosystem function. We discuss our findings with respect to the ARC.

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.

Research on aquatic microcosm: Bibliometric analysis, toxicity comparison and model prediction

Recently, aquatic microcosms have attracted considerable attention because they can be used to simulate natural aquatic ecosystems. First, to evaluate the development of trends, hotspots, and national cooperation networks in the field, bibliometric analysis was performed based on 1841 articles on aquatic microcosm (1962-2022). The results of the bibliometric analysis can be categorized as follows: (1) Aquatic microcosm research can be summarized in two sections, with the first part focusing on the ecological processes and services of aquatic ecosystems, and the second focusing on the toxicity and degradation of pollutants. (2) The United States (number of publications: 541, proportion: 29.5%) and China (248, 13.5%) are the two most active countries. Second, to determine whether there is a difference between single-species and microcosm tests, that is, to perform different-tier assessments, the recommended aquatic safety thresholds in risk assessment [i.e., the community-level no effect concentration (NOECcommunity), hazardous concentrations for 5% of species (HC5) and predicted no effect concentration (PNEC)] were compared based on these tests. There was a significant difference between the NOECcommunity and HC5 (P < 0.05). Moreover, regression models predicting microcosm toxicity values were constructed to provide a reference for ecological systemic risk assessments based on aquatic microcosms.

Decline of a distinct coral reef holobiont community under ocean acidification

BACKGROUND

Microbes play vital roles across coral reefs both in the environment and inside and upon macrobes (holobionts), where they support critical functions such as nutrition and immune system modulation. These roles highlight the potential ecosystem-level importance of microbes, yet most knowledge of microbial functions on reefs is derived from a small set of holobionts such as corals and sponges. Declining seawater pH - an important global coral reef stressor - can cause ecosystem-level change on coral reefs, providing an opportunity to study the role of microbes at this scale. We use an in situ experimental approach to test the hypothesis that under such ocean acidification (OA), known shifts among macrobe trophic and functional groups may drive a general ecosystem-level response extending across macrobes and microbes, leading to reduced distinctness between the benthic holobiont community microbiome and the environmental microbiome.

RESULTS

We test this hypothesis using genetic and chemical data from benthic coral reef community holobionts sampled across a pH gradient from CO2 seeps in Papua New Guinea. We find support for our hypothesis; under OA, the microbiome and metabolome of the benthic holobiont community become less compositionally distinct from the sediment microbiome and metabolome, suggesting that benthic macrobe communities are colonised by environmental microbes to a higher degree under OA conditions. We also find a simplification and homogenisation of the benthic photosynthetic community, and an increased abundance of fleshy macroalgae, consistent with previously observed reef microbialisation.

CONCLUSIONS

We demonstrate a novel structural shift in coral reefs involving macrobes and microbes: that the microbiome of the benthic holobiont community becomes less distinct from the sediment microbiome under OA. Our findings suggest that microbialisation and the disruption of macrobe trophic networks are interwoven general responses to environmental stress, pointing towards a universal, undesirable, and measurable form of ecosystem changed. Video Abstract.

Ecology, ethology, and evolution in the Anthropocene

The 53rd Ontario Ecology, Ethology, and Evolution Colloquium (OE3C 2023) took place at Western University (London, Canada) on 25-27 May 2023, attracting 160 participants. This Meeting Review aims not only to recapitulate what was discussed during the event, but also to provide a brief synthesis of how biologists can move forward. The event was organised and run by graduate students and postdoctoral researchers from the Department of Biology at Western University. With three international keynote speakers, seventy talks, and fifty poster presentations, the OE3C 2023 spanned a wide range of contemporary research in Ecology, Ethology, and Evolution ("the 3 E's"). The colloquium theme was "Surviving the Anthropocene: future steps for the 3 E's under pressing planetary issues", which was complemented by illustrations depicting the fauna and flora of the "Canadian Anthropocene". Participants discussed what biologists and researchers can do regarding future climate and environmental catastrophes. The meeting culminated in a panel discussion comprising three climate change specialists who examined topics such as the Anthropocene and the Great acceleration, the living planet index, and carbon bombs. Although not exhaustive, these topics served as a starting point for the necessary discussions about how biologists can contribute to the fight for the survival of life on Earth.

Factors of global change affecting plants act at different levels of the ecological hierarchy

Plants and ecosystems worldwide are exposed to a wide range of chemical, physical, and biological factors of global change, many of which act concurrently. As bringing order to the array of factors is required in order to generate an enhanced understanding of simultaneous impacts, classification schemes have been developed. One such classification scheme is dedicated to capturing the different targets of global change factors along the ecological hierarchy. We build on this pioneering work, and refine the conceptual framework in several ways, focusing on plants and terrestrial systems: (i) we more strictly define the target level of the hierarchy, such that every factor typically has just one target level, and not many; (ii) we include effects above the level of the community, that is, there are effects also at the ecosystem scale that cannot be reduced to any level below this; (iii) we introduce the level of the landscape to capture certain land use change effects while abandoning the level below the individual. We discuss how effects can propagate along the levels of the ecological hierarchy, upwards and downwards, presenting opportunities for explaining non-additivity of effects of multiple factors. We hope that this updated conceptual framework will help inform the next generation of plant-focused global change experiments, specifically aimed at non-additivity of effects at the confluence of many factors.

Past and recent anthropogenic pressures drive rapid changes in riverine fish communities

Understanding how and why local communities change is a pressing task for conservation, especially in freshwater systems. It remains challenging because of the complexity of biodiversity changes, driven by the spatio-temporal heterogeneity of human pressures. Using a compilation of riverine fish community time series (93% between 1993 and 2019) across the Palaearctic, Nearctic and Australasia realms, we assessed how past and recent anthropogenic pressures drive community changes across both space and time. We found evidence of rapid changes in community composition of 30% per decade characterized by important changes in the dominant species, together with a 13% increase in total abundance per decade and a 7% increase in species richness per decade. The spatial heterogeneity in these trends could be traced back to the strength and timing of anthropogenic pressures and was mainly mediated by non-native species introductions. Specifically, we demonstrate that the negative effects of anthropogenic pressures on species richness and total abundance were compensated over time by the establishment of non-native species, a pattern consistent with previously reported biotic homogenization at the global scale. Overall, our study suggests that accounting for the complexity of community changes and its drivers is a crucial step to reach global conservation goals.

Microgeographic differentiation in thermal and antipredator responses and their carry-over effects across life stages in a damselfly

Global warming and invasive species, separately or combined, can impose a large impact on the condition of native species. However, we know relatively little about how these two factors, individually and in combination, shape phenotypes in ectotherms across life stages and how this can differ between populations. We investigated the non-consumptive predator effects (NCEs) imposed by native (perch) and invasive (signal crayfish) predators experienced only during the egg stage or during both the egg and larval stages in combination with warming on adult life history traits of the damselfly Ischnura elegans. To explore microgeographic differentiation, we compared two nearby populations differing in thermal conditions and predator history. In the absence of predator cues, warming positively affected damselfly survival, possibly because the warmer temperature was closer to the optimal temperature. In the presence of predator cues, warming decreased survival, indicating a synergistic effect of these two variables on survival. In one population, predator cues from perch led to increased survival, especially under the current temperature, likely because of predator stress acclimation phenomena. While warming decreased, predator cues increased larval development time with a proportionally stronger effect of signal crayfish cues experienced during the egg stage, indicating a negative carry-over effect from egg to larva. Warming and predator cues increased mass at emergence, with the predator effect driven mainly by exposure to signal crayfish cues during the egg stage, indicating a positive carry-over effect from egg to adult. Notably, warming and predator effects were not consistent across the two studied populations, suggesting a phenotypic signal of adaptation at a microgeographic scale to thermal conditions and predator history. We also observed pronounced shifts during ontogeny from synergistic (egg and early larval stage) toward additive (late larval stage up to emergence) effects between warming and predator stress. The results point out that population- and life-stage-specific responses in life-history traits to NCEs are needed to predict fitness consequences of exposure to native and invasive predators and warming in prey at a microgeographic scale.

A synthesis of anthropogenic stress effects on emergence-mediated aquatic-terrestrial linkages and riparian food webs

Anthropogenic stress alters the linkage between aquatic and terrestrial ecosystems in various ways. Here, we review the contemporary literature on how alterations in aquatic systems through environmental pollution, invasive species and hydromorphological changes carry-over to terrestrial ecosystems and the food webs therein. We consider both the aquatic insect emergence and flooding as pathways through which stressors can propagate from the aquatic to the terrestrial system. We specifically synthesize and contextualize results on the roles of pollutants in the emergence pathway and their top-down consequences. Our review revealed that the emergence and flooding pathway are only considered in isolation and that the overall effects of invasive species or pollutants on food webs at the water-land interface require further attention. While very few recent studies looked at invasive species, a larger number of studies focused on metal transfer compared to pesticides, pharmaceuticals or PCBs, and multiple stress studies up to now left aquatic-terrestrial linkages unconsidered. Recent research on pollutants and emergence used aquatic-terrestrial mesocosms to elucidate the effects of aquatic stressors such as the mosquito control agent Bti, metals or pesticides to understand the effects on riparian spiders. Quality parameters, such as the structural and functional composition of emergent insect communities, the fatty acid profiles, yet also the composition of pollutants transferred to land prove to be important for the effects on riparian spiders. Process-based models including quality of emergence are useful to predict the resulting top-down directed food web effects in the terrestrial recipient ecosystem. In conclusion, we present and recommend a combination of empirical and modelling approaches in order to understand the complexity of aquatic-terrestrial stressor propagation and its spatial and temporal variation.

A process framework for integrating stressor-response functions into cumulative effects models

Stressor-response (SR) functions quantify ecological responses to natural environmental variation or anthropogenic stressors. They are also core drivers of cumulative effects (CE) models, which are increasingly recognized as essential management tools to grapple with the diffuse footprint of human impacts. Here, we provide a process framework for the identification, development, and integration of SR functions into CE models, and highlight their consequential properties, behaviour, criteria for selecting appropriate stressors and responses, and general approaches for deriving them. Management objectives (and causal effect pathways) will determine the ultimate stressor and target response variables of interest (i.e., individual growth/survival, population size, community structure, ecosystem processes), but data availability will constrain whether proxies need to be used for the target stressor or response variables. Available data and confidence in underlying mechanisms will determine whether empirical or mechanistic (theoretical) SR functions are optimal. Uncertainty in underlying SR functions is often the primary source of error in CE modelling, and monitoring outcomes through adaptive management to iteratively refine parameterization of SR functions is a key element of model application. Dealing with stressor interactions is an additional challenge, and in the absence of known or suspected interaction mechanisms, controlling main effects should remain the primary focus. Indicators of suspected interaction presence (i.e., much larger or smaller responses to stressor reduction than expected during monitoring) should be confirmed through adaptive management cycles or targeted stressor manipulations. Where possible, management decisions should selectively take advantage of interactions to strategically mitigate stressor impacts (i.e., by using antagonisms to suppress stressor impacts, and by using synergisms to efficiently reduce them).

Toward a network perspective in coastal ecosystem management

Environmental management in coastal ecosystems has been challenged by the complex cumulative effects that occur when many small issues result in large ecological shifts. Current environmental management of these spaces focuses on identifying and limiting problematic stressors via a series of assessment techniques. Whilst there is a strong desire among managers to consider complexity in ecological responses to cumulative effects, current approaches for assessing risk focus on breaking down the issues into multiple cause and effect relationships. However, uncertainty arises when data and information for a place are limited, as is commonly the case, and this creates decision paralysis while more information is generated. Here, we discuss how ecological understanding of network interactions in coastal marine ecosystems can be used as a lens to bring together multiple lines of evidence and create actions. We list and describe four characteristics of marine ecosystem interaction networks including the possibility for; 1) indirect effects, 2) effects that emerge as stressor magnitude increases the number of network components implicated, 3) network interactions that amplify these indirect effects, and 4) feedbacks that reinforce or stabilise against indirect effects. We then link these four characteristics to three case studies of common coastal environmental issues to demonstrate how a general understanding of ecological interaction networks can enhance priorities for stressor management that can be applied even when specific data is limited.

Local buffer mechanisms for population persistence

Assessing and predicting the persistence of populations is essential for the conservation and control of species. Here, we argue that local mechanisms require a better conceptual synthesis to facilitate a more holistic consideration along with regional mechanisms known from metapopulation theory. We summarise the evidence for local buffer mechanisms along with their capacities and emphasise the need to include multiple buffer mechanisms in studies of population persistence. We propose an accessible framework for local buffer mechanisms that distinguishes between damping (reducing fluctuations in population size) and repelling (reducing population declines) mechanisms. We highlight opportunities for empirical and modelling studies to investigate the interactions and capacities of buffer mechanisms to facilitate better ecological understanding in times of ecological upheaval.

Sustainable transformation of agriculture requires landscape experiments

Transformation of agriculture to realise sustainable site-specific management requires comprehensive scientific support based on field experiments to capture the complex agroecological process, incite new policies and integrate them into farmers' decisions. However, current experimental approaches are limited in addressing the wide spectrum of sustainable agroecosystem and landscape characteristics and in supplying stakeholders with suitable solutions and measures. This review identifies major constraints in current field experimentation, such as a lack of consideration of multiple processes and scales and a limited ability to address interactions between them. It emphasizes the urgent need to establish a new category of landscape experimentation that empowers agricultural research on sustainable agricultural systems, aiming at elucidating interactions among various landscape structures and functions, encompassing both natural and anthropogenic features. It extensively discusses the key characteristics of landscape experiments and major opportunities to include them in the agricultural research agenda. In particular, simultaneously considering multiple factors, and thus processes at different scales and possible synergies or antagonisms among them would boost our understanding of heterogeneous agricultural landscapes. We also highlight that though various studies identified promising approaches with respect to experimental design and data analysis, further developments are still required to build a fully functional and integrated framework for landscape experimentation in agricultural settings.

Fifteen research needs for understanding climate change impacts on ecosystems and society in the Norwegian High North

There is an urgent need to understand and address the risks associated with a warming climate for ecosystems and societies in the Arctic and sub-Arctic regions. There are major gaps in our understanding of the complex effects of climate change-including extreme events, cascading impacts across ecosystems, and the underlying socioecological dynamics and feedbacks-all of which need collaborative efforts to be resolved. Here, we present results where climate scientists, ecologists, social scientists, and practitioners were asked to identify the most urgent research needs for understanding climate change impacts and to identify the actions for reducing future risks in catchment areas in the Norwegian High North, a region that encompasses both Arctic and sub-Arctic climates in northern Norway. From a list of 77 questions, our panel of 19 scientists and practitioners identified 15 research needs that should be urgently addressed. We particularly urge researchers to investigate cross-ecosystem impacts and the socioecological feedbacks that could amplify or reduce risks for society.

Mean species responses predict effects of environmental change on coexistence

Environmental change research is plagued by the curse of dimensionality: the number of communities at risk and the number of environmental drivers are both large. This raises the pressing question if a general understanding of ecological effects is achievable. Here, we show evidence that this is indeed possible. Using theoretical and simulation-based evidence for bi- and tritrophic communities, we show that environmental change effects on coexistence are proportional to mean species responses and depend on how trophic levels on average interact prior to environmental change. We then benchmark our findings using relevant cases of environmental change, showing that means of temperature optima and of species sensitivities to pollution predict concomitant effects on coexistence. Finally, we demonstrate how to apply our theory to the analysis of field data, finding support for effects of land use change on coexistence in natural invertebrate communities.

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.

The Influence of Lead and Acyrthosiphon pisum (Harris) on Generation of Pisum sativum Defense Signaling Molecules and Expression of Genes Involved in Their Biosynthesis

The main aim of this study was to understand the regulation of the biosynthesis of phytohormones as signaling molecules in the defense mechanisms of pea seedlings during the application of abiotic and biotic stress factors. It was important to identify this regulation at the molecular level in Pisum sativum L. seedlings under the influence of various concentrations of lead-i.e., a low concentration increasing plant metabolism, causing a hormetic effect, and a high dose causing a sublethal effect-and during feeding of a phytophagous insect with a piercing-sucking mouthpart-i.e., pea aphid (Acyrthosiphon pisum (Harris)). The aim of the study was to determine the expression level of genes encoding enzymes of the biosynthesis of signaling molecules such as phytohormones-i.e., jasmonates (JA/MeJA), ethylene (ET) and abscisic acid (ABA). Real-time qPCR was applied to analyze the expression of genes encoding enzymes involved in the regulation of the biosynthesis of JA/MeJA (lipoxygenase 1 (LOX1), lipoxygenase 2 (LOX2), 12-oxophytodienoate reductase 1 (OPR1) and jasmonic acid-amido synthetase (JAR1)), ET (1-aminocyclopropane-1-carboxylate synthase 3 (ACS3)) and ABA (9-cis-epoxycarotenoid dioxygenase (NCED) and aldehyde oxidase 1 (AO1)). In response to the abovementioned stress factors-i.e., abiotic and biotic stressors acting independently or simultaneously-the expression of the LOX1, LOX2, OPR1, JAR1, ACS3, NCED and AO1 genes at both sublethal and hormetic doses increased. Particularly high levels of the relative expression of the tested genes in pea seedlings growing at sublethal doses of lead and colonized by A. pisum compared to the control were noticeable. A hormetic dose of lead induced high expression levels of the JAR1, OPR1 and ACS3 genes, especially in leaves. Moreover, an increase in the concentration of phytohormones such as jasmonates (JA and MeJA) and aminococyclopropane-1-carboxylic acid (ACC)-ethylene (ET) precursor was observed. The results of this study indicate that the response of pea seedlings to lead and A. pisum aphid infestation differed greatly at both the gene expression and metabolic levels. The intensity of these defense responses depended on the organ, the metal dose and direct contact of the stress factor with the organ.

Warming overrides eutrophication effects on leaf litter decomposition in stream microcosms

Several human activities often result in increased nitrogen (N) and phosphorus (P) inputs to running waters through runoff. Although headwater streams are less frequently affected by these inputs than downstream reaches, the joint effects of moderate eutrophication and global warming can affect the functioning of these ecosystems, which represent two thirds of total river length and thus are of major global relevance. In a microcosm study representing streams from a temperate area (northern Spain), we assessed the combined effects of increased water temperature (10.0, 12.5, and 15.0 °C) and nutrient enrichment (control, high N, high P, and high N + P concentrations) on the key process of leaf litter decomposition (mediated by microorganisms and detritivores) and associated changes in different biological compartments (leaf litter, aquatic hyphomycetes and detritivores). While warming consistently enhanced decomposition rates and associated variables (leaf litter microbial conditioning, aquatic hyphomycete sporulation rates and taxon richness, and detritivore growth and nutrient contents), effects of eutrophication were weaker and more variable: P addition inhibited decomposition, addition of N + P promoted leaf litter conditioning, and detritivore stoichiometry was affected by the addition of both nutrients separately or together. In only a few cases (variables related to detritivore performance, but not microbial performance or leaf litter decomposition) we found interactions between warming and eutrophication, which contrasts with other experiments reporting synergistic effects. Our results suggest that both stressors can importantly alter the functioning of stream ecosystems even when occurring in isolation, although non-additive effects should not be neglected and might require exploring an array of ecosystem processes (not just leaf litter decomposition) in order to be detected.

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.

Identifying historical and future global change drivers that place species recovery at risk

Ecosystem management in the face of global change requires understanding how co-occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south-western Australia, small- and medium-sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long-term monitoring program to fit Bayesian state-space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change.

The Asymmetric Response Concept explains ecological consequences of multiple stressor exposure and release

Our capacity to predict trajectories of ecosystem degradation and recovery is limited, especially when impairments are caused by multiple stressors. Recovery may be fast or slow and either complete or partial, sometimes result in novel ecosystem states or even fail completely. Here, we introduce the Asymmetric Response Concept (ARC) that provides a basis for exploring and predicting the pace and magnitude of ecological responses to, and release from, multiple stressors. The ARC holds that three key mechanisms govern population, community and ecosystem trajectories. Stress tolerance is the main mechanism determining responses to increasing stressor intensity, whereas dispersal and biotic interactions predominantly govern responses to the release from stressors. The shifting importance of these mechanisms creates asymmetries between the ecological trajectories that follow increasing and decreasing stressor intensities. This recognition helps to understand multiple stressor impacts and to predict which measures will restore communities that are resistant to restoration.

Tipping points and interactive effects of chronic human disturbance and acute heat stress on coral diversity

Multiple anthropogenic stressors co-occur ubiquitously in natural ecosystems. However, multiple stressor studies often produce conflicting results, potentially because the nature and direction of stressor interactions depends upon the strength of the underlying stressors. Here, we first examine how coral α- and β-diversities vary across sites spanning a gradient of chronic local anthropogenic stress before and after a prolonged marine heatwave. Developing a multiple stressor framework that encompasses non-discrete stressors, we then examine interactions between the continuous and discrete stressors. We provide evidence of additive effects, antagonistic interactions (with heatwave-driven turnover in coral community composition diminishing as the continuous stressor increased), and tipping points (at which the response of coral Hill-richness to stressors changed from additive to near synergistic). We show that community-level responses to multiple stressors can vary, and even change qualitatively, with stressor intensity, underscoring the importance of examining complex, but realistic continuous stressors to understand stressor interactions and their ecological impacts.

Meta-analysis of three-stressor combinations on population-level fitness reveal substantial higher-order interactions

Although natural populations are typically subjected to multiple stressors, most past research has focused on single-stressor and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 142 ecological three-stressor interactions on species' populations from 38 published papers; the vast majority of these studies were from the past 10 years. We found that 95.8 % (n = 136) of the three-stressor combinations had either not been categorized before or resulted in different interactions than previously reported. We also found substantial levels of emergent properties-interactions that are not due to strong pairwise interactions within the combination but rather uniquely due to all three stressors being combined. Calculating net interactions-the overall accounting for all possible interactions within a combination including the emergent and all pairwise interactions-we found that the most prevalent interaction type is antagonism, corresponding to a smaller than expected effect based on single stressor effects. In contrast, for emergent interactions, the most prevalent interaction type is synergistic, resulting in a larger than expected effect based on single stressor effects. Additionally, we found that hidden suppressive interactions-where a pairwise interaction is suppressed by a third stressor-are found in the majority of combinations (74 %). Collectively, understanding multiple stressor interactions through applying an appropriate framework is crucial for answering fundamental questions in ecology and has implications for conservation biology and population management. Crucially, identifying emergent properties can reveal hidden suppressive interactions that could be particularly important for the ecological management of at-risk populations.

Thermal Performance Curves in a Polluted World: Too Cold and Too Hot Temperatures Synergistically Increase Pesticide Toxicity

Ecotoxicological studies typically cover only a limited part of the natural thermal range of populations and ignore daily temperature fluctuations (DTFs). Therefore, we may miss important stressor interaction patterns and have poor knowledge on how pollutants affect thermal performance curves (TPCs), which is needed to improve insights into the fate of populations to warming in a polluted world. We tested the single and combined effects of pesticide exposure and DTFs on the TPCs of low- and high-latitude populations of Ischnura elegans damselfly larvae. While chlorpyrifos did not have any effect at the intermediate mean temperatures (20-24 °C), it became toxic (reflecting synergisms) at lower (≤16 °C, reduced growth) and especially at higher (≥28 °C, reduced survival and growth) mean temperatures, resulting in more concave-shaped TPCs. Remarkably, these toxicity patterns were largely consistent at both latitudes and hence across a natural thermal gradient. Moreover, DTFs magnified the pesticide-induced survival reductions at 34 °C. The TPC perspective allowed us to identify different toxicity patterns and interaction types (mainly additive vs synergistic) across the thermal gradient. This highlights the importance of using thermal gradients to make more realistic predictions about the impact of pesticides in a warming world and of warming in a polluted world.

Transgenerational plasticity in a zooplankton in response to elevated temperature and parasitism

Organisms are increasingly facing multiple stressors, which can simultaneously interact to cause unpredictable impacts compared with a single stressor alone. Recent evidence suggests that phenotypic plasticity can allow for rapid responses to altered environments, including biotic and abiotic stressors, both within a generation and across generations (transgenerational plasticity). Parents can potentially "prime" their offspring to better cope with similar stressors or, alternatively, might produce offspring that are less fit because of energetic constraints. At present, it remains unclear exactly how biotic and abiotic stressors jointly mediate the responses of transgenerational plasticity and whether this plasticity is adaptive. Here, we test the effects of biotic and abiotic environmental changes on within- and transgenerational plasticity using a Daphnia-Metschnikowia zooplankton-fungal parasite system. By exposing parents and their offspring consecutively to the single and combined effects of elevated temperature and parasite infection, we showed that transgenerational plasticity induced by temperature and parasite stress influenced host fecundity and lifespan; offsprings of mothers who were exposed to one of the stressors were better able to tolerate elevated temperature, compared with the offspring of mothers who were exposed to neither or both stressors. Yet, the negative effects caused by parasite infection were much stronger, and this greater reduction in host fitness was not mitigated by transgenerational plasticity. We also showed that elevated temperature led to a lower average immune response, and that the relationship between immune response and lifetime fecundity reversed under elevated temperature: the daughters of exposed mothers showed decreased fecundity with increased hemocyte production at ambient temperature but the opposite relationship at elevated temperature. Together, our results highlight the need to address questions at the interface of multiple stressors and transgenerational plasticity and the importance of considering multiple fitness-associated traits when evaluating the adaptive value of transgenerational plasticity under changing environments.

Linking human impacts to community processes in terrestrial and freshwater ecosystems

Human impacts such as habitat loss, climate change and biological invasions are radically altering biodiversity, with greater effects projected into the future. Evidence suggests human impacts may differ substantially between terrestrial and freshwater ecosystems, but the reasons for these differences are poorly understood. We propose an integrative approach to explain these differences by linking impacts to four fundamental processes that structure communities: dispersal, speciation, species-level selection and ecological drift. Our goal is to provide process-based insights into why human impacts, and responses to impacts, may differ across ecosystem types using a mechanistic, eco-evolutionary comparative framework. To enable these insights, we review and synthesise (i) how the four processes influence diversity and dynamics in terrestrial versus freshwater communities, specifically whether the relative importance of each process differs among ecosystems, and (ii) the pathways by which human impacts can produce divergent responses across ecosystems, due to differences in the strength of processes among ecosystems we identify. Finally, we highlight research gaps and next steps, and discuss how this approach can provide new insights for conservation. By focusing on the processes that shape diversity in communities, we aim to mechanistically link human impacts to ongoing and future changes in ecosystems.

The cumulative impacts of anthropogenic stressors vary markedly along environmental gradients

Understanding the cumulative effects of multiple stressors on biodiversity is key to managing their impacts. Stressor interactions are often studied using an additive/antagonistic/synergistic typology, aimed at identifying situations where individual stressor effects are reduced or amplified when they act in combination. Here, we analysed variation in the family richness of stream macroinvertebrates in the groups Ephemeroptera, Plecoptera and Trichoptera (EPT) at 4658 sites spanning a 32° latitudinal range in eastern Australia in relation to two largely human-induced stressors, salinity and turbidity, and two environmental gradients, temperature and slope. The cumulative and interactive effect of salinity and turbidity on EPT family richness varied across the landscape and by habitat (edge or riffle) such that we observed additive, antagonistic and synergistic outcomes depending on the environmental context. Our findings highlight the importance of understanding the consistency of multiple stressor impacts, which will involve higher-order interactions between multiple stressors and environmental factors.

Stressor-response functions as a generalizable model for context dependence

Defining the context dependence of ecological states or processes is a fundamental goal of ecology. Stressor-response functions are the quantitative representation of context dependence, where the context (environmental contingency) is defined by location on the stressor (x) axis, and represents a unifying concept in biological science.

Managing the effects of multiple stressors on wildlife populations in their ecosystems: developing a cumulative risk approach

Assessing cumulative effects of human activities on ecosystems is required by many jurisdictions, but current science cannot meet regulatory demands. Regulations define them as effect(s) of one human action combined with other actions. Here we argue for an approach that evaluates the cumulative risk of multiple stressors for protected wildlife populations within their ecosystems. Monitoring effects of each stressor is necessary but not sufficient to estimate how multiple stressors interact to affect wildlife populations. Examining the mechanistic pathways, from cellular to ecological, by which stressors affect individuals can help prioritize stressors and interpret how they interact. Our approach uses health indicators to accumulate the effects of stressors on individuals and to estimate changes in vital rates, driving population status. We advocate using methods well-established in human health and integrating them into ecosystem-based management to protect the health of commercially and culturally important wildlife populations and to protect against risk of extinction for threatened species. Our approach will improve abilities to conserve and manage ecosystems but will also demand significant increases in research and monitoring effort. We advocate for increased investment proportional to the economic scale of human activities in the Anthropocene and their pervasive effects on ecology and biodiversity.

Time between Sequential Exposures to Multiple Stress Turns Antagonism into Synergism

Aquatic communities are exposed to repeated pulses of toxicants and environmental stressors. We hypothesize that the dose, order, and timing of stress events shape the interactions of these communities. For this, we conducted a fully-crossed, four-factorial, multiple stress exposure experiment to study the combined effects of Esfenvalerate and ultraviolet-B (UV-B) radiation related to the exposure timing and order on Daphnia magna. We revealed that initial exposure to low stress doses, independent of the stress type (UV-B or Esfenvalerate), significantly increased the resistance toward the second stressor. This beneficial effect was apparent only when the second stressor was applied immediately after the first stressor (p < 0.01). When the period between stressor applications was extended to 2 days, the antagonism between the two stressors turned into synergism. The stressor interaction could be predicted with an abstract-mechanistic model of the temporal dynamics of the early-stage stress response. With this model, the timing and order of exposures were able to successfully explain interactions observed in all treatments (model-R² = 1.0). We conclude that especially the duration of a break between exposures and the exposure dose have a decisive influence on interactions between toxicants and environmental stressors.

Blueprint for the ideal microplastic effect study: Critical issues of current experimental approaches and envisioning a path forward

This article presents a novel conceptual blueprint for an 'ideal', i.e., ecologically relevant, microplastic effect study. The blueprint considers how microplastics should be characterized and applied in laboratory experiments, and how biological responses should be measured to assure unbiased data that reliably reflect the effects of microplastics on aquatic biota. This 'ideal' experiment, although practically unachievable, serves as a backdrop to improve specific aspects of experimental research on microplastic effects. In addition, a systematic and quantitative literature review identified and quantified departures of published experiments from the proposed 'ideal' design. These departures are related mainly to the experimental design of microplastic effect studies failing to mimic natural environments, and experiments with limited potential to be scaled-up to ecosystem level. To produce a valid and generalizable assessment of the effect of microplastics on biota, a quantitative meta-analysis was performed that incorporated the departure of studies from the 'ideal' experiment (a measure of experimental quality) and inverse variance (a measure of the study precision) as weighting coefficients. Greater weights were assigned to experiments with higher quality and/or with lower variance in the response variables. This double-weighting captures jointly the technical quality, ecological relevance and precision of estimates provided in each study. The blueprint and associated meta-analysis provide an improved baseline for the design of ecologically relevant and technically sound experiments to understand the effects of microplastics on single species, populations and, ultimately, entire ecosystems.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

As most ecosystems are being challenged by multiple, co-occurring stressors, an important challenge is to understand and predict how stressors interact to affect biological responses. A popular approach is to design factorial experiments that measure biological responses to pairs of stressors and compare the observed response to a null model expectation. Unfortunately, we believe experiment sample sizes are inadequate to detect most non-null stressor interaction responses, greatly hindering progress. Using both real and simulated data, we show sample sizes typical of many experiments (<6) can (i) only detect very large deviations from the additive null model, implying many important non-null stressor-pair interactions are being missed, and (ii) potentially lead to mostly statistical outliers being reported. Computer code that simulates data under either additive or multiplicative null models is provided to estimate statistical power for user-defined responses and sample sizes, and we recommend this is used to aid experimental design and interpretation of results. We suspect that most experiments may require 20 or more replicates per treatment to have adequate power to detect nonadditive. However, estimates of power need to be made while considering the smallest interaction of interest, i.e., the lower limit for a biologically important interaction, which is likely to be system-specific, meaning a general guide is unavailable. We discuss ways in which the smallest interaction of interest can be chosen, and how sample sizes can be increased. Our main analyses relate to the additive null model, but we show similar problems occur for the multiplicative null model, and we encourage similar investigations into the statistical power of other null models and inference methods. Without knowledge of the detection abilities of the statistical tools at hand or the definition of the smallest meaningful interaction, we will undoubtedly continue to miss important ecosystem stressor interactions.

Predicting the effects of multiple global change drivers on microbial communities remains challenging

Microbial communities in many ecosystems are facing a broad range of global change drivers, such as nutrient enrichment, chemical pollution, and temperature change. These drivers can cause changes in the abundance of taxa, the composition of communities, and the properties of ecosystems. While the influence of single drivers is already described in numerous studies, the effect and predictability of multiple drivers changing simultaneously is still poorly understood. In this study, we used 240 highly replicable oxic/anoxic aquatic lab microcosms and four drivers (fertilizer, glyphosate, metal pollution, antibiotics) in all possible combinations at three different temperatures (20, 24, and 28°C) to shed light into consequences of multiple drivers on different levels of organization, ranging from species abundance to community and ecosystem parameters. We found (i) that at all levels of ecological organization, combinations of drivers can change the biological consequence and direction of effect compared to single drivers, (ii) that effects of combinations are further modified by temperature, (iii) that a larger number of drivers occurring simultaneously is often quite closely related to their effect size, and (iv) that there is little evidence that any of these effects are associated with the level of ecological organization of the state variable. These findings suggest that, at least in this experimental ecosystem approximating a stratified aquatic ecosystem, there may be relatively little scope for predicting the effects of combinations of drivers from the effects of individual drivers, or by accounting for the level of ecological organization in question, though there may be some scope for prediction based on the number of drivers that are occurring simultaneous. A priority, though also a considerable challenge, is to extend such research to consider continuous variation in the magnitude of multiple drivers acting together.

Understanding the combined effects of multiple stressors: A new perspective on a longstanding challenge

Wildlife populations and their habitats are exposed to an expanding diversity and intensity of stressors caused by human activities, within the broader context of natural processes and increasing pressure from climate change. Estimating how these multiple stressors affect individuals, populations, and ecosystems is thus of growing importance. However, their combined effects often cannot be predicted reliably from the individual effects of each stressor, and we lack the mechanistic understanding and analytical tools to predict their joint outcomes. We review the science of multiple stressors and present a conceptual framework that captures and reconciles the variety of existing approaches for assessing combined effects. Specifically, we show that all approaches lie along a spectrum, reflecting increasing assumptions about the mechanisms that regulate the action of single stressors and their combined effects. An emphasis on mechanisms improves analytical precision and predictive power but could introduce bias if the underlying assumptions are incorrect. A purely empirical approach has less risk of bias but requires adequate data on the effects of the full range of anticipated combinations of stressor types and magnitudes. We illustrate how this spectrum can be formalised into specific analytical methods, using an example of North Atlantic right whales feeding on limited prey resources while simultaneously being affected by entanglement in fishing gear. In practice, case-specific management needs and data availability will guide the exploration of the stressor combinations of interest and the selection of a suitable trade-off between precision and bias. We argue that the primary goal for adaptive management should be to identify the most practical and effective ways to remove or reduce specific combinations of stressors, bringing the risk of adverse impacts on populations and ecosystems below acceptable thresholds.

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.