Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits

In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

Horizontal and vertical diversity jointly shape food web stability against small and large perturbations

The biodiversity of food webs is composed of horizontal (i.e. within trophic levels) and vertical diversity (i.e. the number of trophic levels). Understanding their joint effect on stability is a key challenge. Theory mostly considers their individual effects and focuses on small perturbations near equilibrium in hypothetical food webs. Here, we study the joint effects of horizontal and vertical diversity on the stability of hypothetical (modelled) and empirical food webs. In modelled food webs, horizontal and vertical diversity increased and decreased stability, respectively, with a stronger positive effect of producer diversity on stability at higher consumer diversity. Experiments with an empirical plankton food web, where we manipulated horizontal and vertical diversity and measured stability from species interactions and from resilience against large perturbations, confirmed these predictions. Taken together, our findings highlight the need to conserve horizontal biodiversity at different trophic levels to ensure stability.

Community- and ecosystem-level effects of multiple environmental change drivers: Beyond null model testing

Understanding the joint effect of multiple drivers of environmental change is a key scientific challenge. The dominant approach today is to compare observed joint effects with predictions from various types of null models. Drivers are said to combine synergistically (antagonistically) when their observed joint effect is larger (smaller) than that predicted by the null model. Here, I argue that this approach does not promote understanding of effects on important community- and ecosystem-level variables such as biodiversity and ecosystem function. I use ecological theory to show that different mechanisms can lead to the same deviation from a null model's prediction. Inversely, I show that the same mechanism can lead to different deviations from a null model's prediction. These examples illustrate that it is not possible to make strong mechanistic inferences from null models. Next, I present an alternative framework to study such effects. This framework makes a clear distinction between two different kinds of drivers (resource ratio shifts and multiple stressors) and integrates both by incorporating stressor effects into resource uptake theory. I show that this framework can advance understanding because of three reasons. First, it forces formalization of "multiple stressors," using factors that describe the number and kind of stressors, their selectivity and dynamic behaviour, and the initial trait diversity and tolerance among species. Second, it produces testable predictions on how these factors affect biodiversity and ecosystem function, alone and in combination with resource ratio shifts. Third, it can fail in informative ways. That is, its assumptions are clear, so that different kinds of deviations between predictions and observed effects can guide new experiments and theory improvement. I conclude that this framework will more effectively progress understanding of global change effects on communities and ecosystems than does the current practice of null model testing.

Links Between Heathland Fungal Biomass Mineralization, Melanization, and Hydrophobicity

Comprehending the decomposition process is crucial for our understanding of the mechanisms of carbon (C) sequestration in soils. The decomposition of plant biomass has been extensively studied. It revealed that extrinsic biomass properties that restrict its access to decomposers influence decomposition more than intrinsic ones that are only related to its chemical structure. Fungal biomass has been much less investigated, even though it contributes to a large extent to soil organic matter, and is characterized by specific biochemical properties. In this study, we investigated the extent to which decomposition of heathland fungal biomass was affected by its hydrophobicity (extrinsic property) and melanin content (intrinsic property). We hypothesized that, as for plant biomass, hydrophobicity would have a greater impact on decomposition than melanin content. Mineralization was determined as the mineralization of soil organic carbon (SOC) into CO₂ by headspace GC/MS after inoculation by a heathland soil microbial community. Results show that decomposition was not affected by hydrophobicity, but was negatively correlated with melanin content. We argue that it may indicate that either melanin content is both an intrinsic and extrinsic property, or that some soil decomposers evolved the ability to use surfactants to access to hydrophobic biomass. In the latter case, biomass hydrophobicity should not be considered as a crucial extrinsic factor. We also explored the ecology of decomposition, melanin content, and hydrophobicity, among heathland soil fungal guilds. Ascomycete black yeasts had the highest melanin content, and hyaline Basidiomycete yeasts the lowest. Hydrophobicity was an all-or-nothing trait, with most isolates being hydrophobic.

The combined and interactive effects of zinc, temperature, and phosphorus on the structure and functioning of a freshwater community

Ecotoxicological studies mainly consist of single-species experiments evaluating the effects of a single stressor. However, under natural conditions aquatic communities are exposed to a mixture of stressors. The present study aimed to identify how the toxicity of zinc (Zn) is affected by increased temperature and increased phosphorus (P) supply and how these interactions vary among species, functional groups, and community structure and function. Aquatic microcosms were subjected to 3 Zn concentrations (background, no Zn added, and 75 and 300 μg Zn/L), 2 temperatures (16-19 and 21-24 °C), and 2 different P additions (low, 0.02, and high, 0.4 mg P L^-1  wk^-1 ) for 5 wk using a full factorial design. During the study, consistent interactions between Zn and temperature were only rarely found at the species level (4%), but were frequently found at the functional group level (36%), for community structure (100%) and for community function (100%; such as dissolved organic carbon concentrations and total chlorophyll). The majority of the Zn × temperature interactions were observed at 300 μg Zn/L and generally indicated a smaller effect of Zn at higher temperature. Furthermore, no clear indication was found that high P addition by itself significantly affected the overall effects of Zn on the community at any level of organization. Interestingly, though, 90% of all the Zn × temperature interactions observed at the species, group, and community composition level were found under high P addition. Collectively, the results of our study with the model chemical Zn suggest that temperature and phosphorus loading to freshwater systems should be accounted for in risk assessment, because these factors may modify the effects of chemicals on the structure and functioning of aquatic communities, especially at higher levels of biological organization. Environ Toxicol Chem 2018;37:2413-2427. © 2018 SETAC.

Selective and context-dependent effects of chemical stress across trophic levels at the basis of marine food webs

Human activities increasingly impact the functioning of marine food webs, but anthropogenic stressors are seldom included in ecological study designs. Diet quality, as distinct from just diet quantity, has moreover rarely been highlighted in food web studies in a stress context. We measured the effects of metal and pesticide stress (copper and atrazine) on the contribution of a benthic intertidal diatom community to two processes that are key to the functioning of intertidal systems: biomass (diet quantity) and lipid (diet quality) production. We then examined if stressors affected diatom functioning by selectively targeting the species contributing most to functioning (selective stress effects) or by changing the species' functional contribution (context-dependent effects). Finally, we tested if stress-induced changes in diet quality altered the energy flow to the diatoms' main grazers (harpacticoid copepods). Diatom diet quantity was reduced by metal stress but not by low pesticide levels due to the presence of an atrazine-tolerant, mixotrophic species. Selective effects of the pesticide reduced diatom diet quality by 60% and 75% at low and high pesticide levels respectively, by shifting diatom community structure from dominance by lipid-rich species toward dominance by an atrazine-tolerant, but lipid-poor, species. Context-dependent effects did not affect individual diatom lipid content at low levels of both stressors, but caused diatoms to lose 40% of their lipids at high copper stress. Stress-induced changes in diet quality predicted the energy flow from the diatoms to their copepod consumers, which lost half of their lipids when feeding on diatoms grown under low and high pesticide and high metal stress. Selective pesticide effects were a more important threat for trophic energy transfer than context-dependent effects of both stressors, with shifts in diatom community structure affecting the energy flow to their copepod grazers at stress levels where no changes in diatom lipid content were detected.

Biodiversity effects on ecosystem functioning respond unimodally to environmental stress

Understanding how biodiversity (B) affects ecosystem functioning (EF) is essential for assessing the consequences of ongoing biodiversity changes. An increasing number of studies, however, show that environmental conditions affect the shape of BEF relationships. Here, we first use a game-theoretic community model to reveal that a unimodal response of the BEF slope can be expected along environmental stress gradients, but also how the ecological mechanisms underlying this response may vary depending on how stress affects species interactions. Next, we analysed a global dataset of 44 experiments that crossed biodiversity with environmental conditions. Confirming our main model prediction, the effect of biodiversity on ecosystem functioning tends to be greater at intermediate levels of environmental stress, but varies among studies corresponding to differences in stress-effects on species interactions. Together, these results suggest that increases in stress from ongoing global environmental changes may amplify the consequences of biodiversity changes.

Shifts of community composition and population density substantially affect ecosystem function despite invariant richness

There has been considerable focus on the impacts of environmental change on ecosystem function arising from changes in species richness. However, environmental change may affect ecosystem function without affecting richness, most notably by affecting population densities and community composition. Using a theoretical model, we find that, despite invariant richness, (1) small environmental effects may already lead to a collapse of function; (2) competitive strength may be a less important determinant of ecosystem function change than the selectivity of the environmental change driver and (3) effects on ecosystem function increase when effects on composition are larger. We also present a complementary statistical analysis of 13 data sets of phytoplankton and periphyton communities exposed to chemical stressors and show that effects on primary production under invariant richness ranged from -75% to +10%. We conclude that environmental protection goals relying on measures of richness could underestimate ecological impacts of environmental change.

The Consequences of Nonrandomness in Species-Sensitivity in Relation to Functional Traits for Ecosystem-Level Effects of Chemicals

Estimating ecosystem-level effects from single-species bioassays is a major challenge in environmental risk assessment. Most extrapolation procedures are based on the implicit assumption that species sensitivities are random with regard to their functional traits. Here, we explore how nonrandomness in species sensitivities affects how species-level and ecosystem level effects of chemical exposure correspond. The effect of a correlation between the trait value under control conditions and the sensitivity of the trait to chemical stress is studied for two traits (per capita growth rate and monoculture yield) under constant and temporary exposure. Theoretical model predictions are thereby validated against a 3-week microcosm experiment, in which eight marine diatoms systems with different correlations between trait values and sensitivities were temporary (1 week) or constantly (3 weeks) exposed to two concentrations of the herbicide atrazine (100 and 250 μg L^-1). Negative correlations increased the reduction in ecosystem functioning (productivity) by atrazine for both traits. However, correlations in the per capita growth rate affected productivity only shortly following changes in environmental conditions, whereas correlations in the monoculture yield affected productivity throughout exposure. Correlations between species sensitivities and functional trait values can thus help to identify when ecosystem-level effects are likely to exceed species-level effects.

The combined effects of biotic and abiotic stress on species richness and connectance

Food web structure and species richness are both subject to biotic (e.g. predation pressure and resource limitation) and abiotic stress (e.g. environmental change). We investigated the combined effects of both types of stress on richness and connectance, and on their relationship, in a predator-prey system. To this end, we developed a mathematical two trophic level food-web model to investigate the effects of biotic and abiotic stress on food web connectance and species richness. We found negative effects of top-down and bottom-up control on prey and predator richness, respectively. Effects of top-down and bottom-up control were stronger when initial connectance was high and low, respectively. Bottom-up control could either aggravate or buffer negative effects of top-down control. Abiotic stress affecting predator richness had positive indirect effects on prey richness, but only when initial connectance was low. However, no indirect effects on predator richness were observed following direct effects on prey richness. Top-down and bottom-up control selected for weakly connected prey and highly connected predators, thereby decreasing and increasing connectance, respectively. Our simulations suggest a broad range of negative and positive richness-connectance relationships, thereby revisiting the often found negative relationship between richness and connectance in food webs. Our results suggest that (1) initial food-web connectance strongly influences the effects of biotic stress on richness and the occurrence of indirect effects on richness; and (2) the shape of the richness-connectance relationship depends on the type of biotic stress.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

European environmental scenarios of chemical bioavailability in freshwater systems

In exposure prediction for environmental risk assessment, the transition to more dynamic and realistic modelling approaches and scenarios has been recently identified as a major challenge, since it would allow a more accurate prediction of bioavailable concentrations and their variations in space and time. In this work, an improved version of the multimedia model ChimERA fate, including a phytoplankton compartment and equations to calculate phytoplankton, detritus and dissolved organic matter variations in time, was developed. The model was parameterized to simulate five dynamic scenarios for shallow meso-eutrophic water bodies based on a latitudinal gradient (in Europe); such scenarios include seasonal profiles of water temperature, phytoplankton biomass, detritus, and dissolved organic matter. Model runs were performed for each scenario for 8 hydrophobic chemicals (PCB congeners), with the aim of investigating the influence of scenario characteristics and compound properties on bioavailable concentrations. The key processes were adsorption/uptake by phytoplankton and deposition to sediment of detritus-bound chemicals. The northern scenarios ("Scandinavia" and "UK") showed the highest bioavailable concentrations, with annual maximum/minimum concentration up to 25; in contrast, for example, maximum concentrations in the "Mediterranean" scenario were lower by a factor of 2 to 9 with respect to the northern ones (depending on chemical hydrophobicity), due to the generally higher biomass and carbon levels, and showed only limited seasonal variability (up to a factor of 4). These results highlight the importance of including biomass and organic carbon dynamics in both modelling approaches and scenarios for the evaluation of exposure concentrations in aquatic environments.

Time-varying effects of aromatic oil constituents on the survival of aquatic species: Deviations between model estimates and observations

There is a need to study the time course of toxic chemical effects on organisms because there might be a time lag between the onset of chemical exposure and the corresponding adverse effects. For aquatic organisms, crude oil and oil constituents originating from either natural seeps or human activities can be relevant case studies. In the present study the authors tested a generic toxicokinetic model to quantify the time-varying effects of various oil constituents on the survival of aquatic organisms. The model is based on key parameters applicable to an array of species and compounds with baseline toxicity reflected by a generic, internal toxicity threshold or critical body burden (CBB). They compared model estimates with experimental data on the effects of 8 aromatic oil constituents on the survival of aquatic species including crustaceans and fish. The average model uncertainty, expressed as the root mean square error, was 0.25 (minimum-maximum, 0.04-0.67) on a scale between 0 and 1. The estimated survival was generally lower than the measured survival right after the onset of oil constituent exposure. In contrast, the model underestimated the maximum mortality for crustaceans and fish observed in the laboratory. Thus, the model based on the CBB concept failed to adequately predict the lethal effects of the oil constituents on crustaceans and fish. Possible explanations for the deviations between model estimates and observations may include incorrect assumptions regarding a constant lethal body burden, the absence of biotransformation products, and the steady state of aromatic hydrocarbon concentrations in organisms. Clearly, a more complex model approach than the generic model used in the present study is needed to predict toxicity dynamics of narcotic chemicals. Environ Toxicol Chem 2017;36:128-136. © 2016 SETAC.

Reintroducing Environmental Change Drivers in Biodiversity-Ecosystem Functioning Research

For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change.

Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions

Environmental stress changes the relationship between biodiversity and ecosystem functions, but the underlying mechanisms are poorly understood. Because species interactions shape biodiversity-ecosystem functioning relationships, changes in per capita interactions under stress (as predicted by the stress gradient hypothesis) can be an important driver of stress-induced changes in these relationships. To test this hypothesis, we measure productivity in microalgae communities along a diversity and herbicide gradient. On the basis of additive partitioning and a mechanistic community model, we demonstrate that changes in per capita interactions do not explain effects of herbicide stress on the biodiversity-productivity relationship. Instead, assuming that the per capita interactions remain unaffected by stress, causing species densities to only change through differences in stress tolerance, suffices to predict the stress-induced changes in the biodiversity-productivity relationship and community composition. We discuss how our findings set the stage for developing theory on how environmental stress changes biodiversity effects on ecosystem functions.

Crude oil affecting the biomass of the marine copepod Calanus finmarchicus: Comparing a simple and complex population model

In the current study differences were evaluated between a complex 3D multistage population model (SINMOD) and a simpler consumer-resource population model for estimating the effects of crude oil on the marine copepod Calanus finmarchicus. The SINTEF OSCAR model was used to simulate hypothetical oil spills in the Lofoten area in 1995, 1997, and 2001. Both population models simulated a negligible effect of crude oil on the Calanus' biomass when assuming low species sensitivity. The simple model estimated a larger effect on the biomass (up to a 100% decline) compared to the complex model (maximum decline of 60-80%) at high species sensitivity to crude oil. These differences may be related to the inclusion of copepod advection in the complex model. Our study showed that if little data is available to parameterize a model, or if computational resources are scarce, the simple model could be used for risk screening. Nevertheless, the possibility of including a dilution factor for time-varying biomass should be examined to improve the estimations of the simple model. The complex model should be used for a more in depth risk analysis, as it includes physical processes such as the drift of organisms and differentiation between developmental stages.

Realistic environmental mixtures of hydrophobic compounds do not alter growth of a marine diatom

In this paper we determine whether a realistic mixture of hydrophobic chemicals affects the growth dynamics of a marine diatom and how this effect compares to the effect of temperature, light regime and nutrient conditions. To do so, we examine the specific growth rate of Phaeodactylum tricornutum in a 72 h algal growth inhibition test using a full factorial design with three nutrient regimes, two test temperatures, three light intensities and three chemical exposures. Passive samplers were used to achieve exposure to realistic mixtures of organic chemicals close to ambient concentrations. Nutrient regime, temperature and time interval (24, 48 and 72 h) explained 85% of the observed variability in the experimental data. The variability explained by chemical exposure was about 1%. Overall, ambient concentrations of hydrophobic compounds present in Belgian coastal waters, and for which the passive samplers have affinity, are too low to affect the intrinsic growth rate of P. tricornutum.

Population-level effects and recovery of aquatic invertebrates after multiple applications of an insecticide

Standard risk assessment of plant protection products (PPP) combines "worst-case" exposure scenarios with effect thresholds using assessment (safety) factors to account for uncertainties. If needed, risks can be addressed applying more realistic conditions at higher tiers, which refine exposure and/or effect assessments using additional data. However, it is not possible to investigate the wide range of potential scenarios experimentally. In contrast, ecotoxicological mechanistic effect models do allow for addressing a multitude of scenarios. Furthermore, they may aid the interpretation of experiments such as mesocosm studies, allowing extrapolation to conditions not covered in experiments. Here, we explore how to use mechanistic effect models in the aquatic risk assessment of a model insecticide (Modelmethrin), applied several times per season but rapidly dissipating between applications. The case study focuses on potential effects on aquatic arthropods, the most sensitive group for this substance. The models provide information on the impact of a number of short exposure pulses on sensitive and/or vulnerable populations and, when impacted, assess recovery. The species to model were selected based on their sensitivity in laboratory and field (mesocosm) studies. The general unified threshold model for survival (GUTS) model, which describes the toxicokinetics and toxicodynamics of chemicals in individuals, was linked to 3 individual-based models (IBM), translating individual survival of sensitive organisms into population-level effects. The impact of pulsed insecticide exposures on populations were modeled using the spatially explicit IBM metapopulation model for assessing spatial and temporal effects of pesticides (MASTEP) for Gammarus pulex, the Chaoborus IBM for populations of Chaoborus crystallinus, and the "IdamP" model for populations of Daphnia magna. The different models were able to predict the potential effects of Modelmethrin applications to key arthropod species inhabiting different aquatic ecosystems; the most sensitive species were significantly impacted unless respective mitigation measures were implemented (buffer zones resulting in reduced exposure). As expected the impact was stronger in shallow ditches as compared to deeper pond scenarios. Furthermore, as expected, recovery depended on factors such as temperature (affecting population growth rate and number of generations) and the occurence of nonimpacted aquatic ecosystems (their frequency and connectivity). These model predictions were largely in line with field observations and/or the results of a mesocosm study, providing additional evidence on the suitability and reliability of the models for risk assessment purposes. Because of their flexibility, models may predict the likelihood of unacceptable effects-based on previously defined protection goals-for a range of insecticide exposure scenarios and freshwater habitats.