Sublethal toxicant effects with dynamic energy budget theory: model formulation

Behavioral biomarkers in fishes: A non-lethal approach to assess the effects of chemical pollution on freshwater ecosystems

The expansion of the human population and the escalating use of chemical products pose a considerable threat to aquatic biodiversity. Consequently, there is an imperative need for the implementation of non-lethal, cost-effective, and easily deployable biomonitoring tools. In this context, fish and their behavior as biomarkers have gained prominence in monitoring of freshwater ecosystems. The aim of this study was to assess the state of art in the use of behavioral biomarkers in ecotoxicology, emphasizing their role as informative tools for global environmental monitoring. Through a systematic literature search, ninety-two articles focusing on the evaluation of behavioral changes in freshwater fish in response to pollution were identified. The most prevalent keywords were "behavior" (7%) and "zebrafish" (6%). Experiments were conducted in countries with expansive territories, such as the United States (18%) and Brazil (17%). Exotic species were primarily employed (58%), with Danio rerio (26%) being the most frequently studied species. Among pollutants, pesticides (32%) and medicines (25%) were the most frequently studied, while locomotion (38%) and social behaviors (18%) were the most frequently evaluated behaviors. Across these studies, authors consistently reported significant changes in the behavior of fish exposed to contaminants, including decreased swimming speed and compromised feeding efficiency. The review findings affirm that evaluating behavioral biomarkers in freshwater fish offers an informative, non-lethal, cost-effective, and easily implementable approach to understanding pollution impacts on freshwater ecosystems. Although few studies on behavioral biomarkers were available to date, the number has rapidly increased in recent years. Furthermore, a variety of novel approaches and study models are being included. Research into behavioral biomarkers is crucial for understanding and managing environmental risks in freshwater ecosystems. Nevertheless, further studies are needed to enhance our understanding of behavioral toxicity indicators, considering factors such as life stage, sex, and breeding season in the tested species.

Sublethal effects of binary mixtures of Cu2+ and Cd2+ on Daphnia magna: Standard Dynamic Energy Budget (DEB) model analysis

Dynamic Energy Budget theory (DEB) describes mass and energy fluxes that occur in living organisms. DEB models were successfully used to assess the influence of stress, including toxic substances, and changes in pH and temperature, on different organisms. In this study, the Standard DEB model was used to evaluate the toxicity of copper and cadmium ions and their binary mixtures on Daphnia magna. Both metal ions have a significant influence on daphnia growth and reproduction. Different physiological modes of action (pMoA) were applied to primary DEB model parameters. Model predictions for chosen modes of interaction of mixture components were evaluated. The goodness of model fit and the model prediction was assessed to indicate the most likely pMoA and interaction mode. Copper and cadmium influence more than one DEB model primary parameter. Different pMoAs can result in similar model fits, and therefore it is difficult to identify pMoA only by evaluation of the goodness of fit of the model to the growth and reproduction data. Some critical discussion and ideas for model development are therefore provided.

Bioremediation of polycyclic aromatic hydrocarbons in crude oil by bacterial consortium in soil amended with Eisenia fetida and rhamnolipid

The present study investigated the concerted effort of Eisenia fetida and rhamnolipid JBR-425 in combination with a five-member bacterial consortium exhibiting elevated degradation levels of low and high molecular weight polycyclic aromatic hydrocarbons (PAH) from soil contaminated with Digboi crude oil. Application of bacterial consortium (G2) degraded 30-89% of selected PAH from the artificial soil after a 45-day post-exposure, in which chrysene showed the highest level of degradation with 89% and benzo(a)pyrene is the lowest with 30%, respectively. Moreover, an acute exposure study observed that earthworm biomass decreased, and mortality rates increased with increasing crude oil concentrations (0.25 to 2%). Earthworms with a 100% survival rate at 1% crude oil exposure suggest the tolerance potential and its mutual involvement in the bioremediation of crude oil with selected bacterial consortia. Bacterial consortium assisted with E. fetida (G3) showed 98% chrysene degradation with a slight change in benzo(a)pyrene degradation (35%) in crude oil spiked soil. Besides, the most dominant PAH in crude oil found in the current work, fluoranthene, undergoes 93% and 70% degradation in G3 and G5 groups, respectively. However, rhamnolipid JBR-425 coupled with the bacterial consortium (G5) has resulted in 97% degradation of chrysene and 33% for benzo(a)pyrene. Overall, bacterial consortium assisted with earthworm group has shown better degradation of selected PAH than bacterial consortium with biosurfactant. Catalase (CAT), glutathione reductase (GST) activity and MDA content was found to be reduced in earthworms after sub-lethal exposure, suggesting oxidative stress prevalence via reactive oxygen species (ROS). Hence, the findings of the present work suggest that the application of a bacterial consortium, along with earthworm E. fetida, has huge potential for field restoration of contaminated soil with PAH and ecosystem sustainability.

Modelling the effects of the pyrethroid insecticide cypermethrin on the life cycle of the soil dwelling annelid Enchytraeus crypticus, an original experimental design to calibrate a DEB-TKTD model

The Dynamic Energy Budget theory (DEB) enables ecotoxicologists to model the effects of chemical stressors on organism life cycles through the coupling of toxicokinetic-toxicodynamic (TK-TD) models. While good progress has been made in the application of DEB-TKTD models for aquatic organisms, applications for soil fauna are scarce, due to the lack of dedicated experimental designs suitable for collecting the required time series effect data. Enchytraeids (Annelida: Clitellata) are model organisms in soil ecology and ecotoxicology. They are recognised as indicators of biological activity in soil, and chemical stress in terrestrial ecosystems. Despite this, the application of DEB-TKTD models to investigate the impact of chemicals has not yet been tested on this family. Here we assessed the impact of the pyrethroid insecticide cypermethrin on the life cycle of Enchytraeus crypticus. We developed an original experimental design to collect the data required for the calibration of a DEB-TKTD model for this species. E. crypticus presented a slow initial growth phase that has been successfully simulated with the addition of a size-dependent food limitation for juveniles in the DEB model. The DEB-TKTD model simulations successfully agreed with the data for all endpoints and treatments over time. The highlighted physiological mode of action (pMoA) for cypermethrin was an increase of the growth energy cost. The threshold for effects on survival was estimated at 73.14 mg kg^- 1, and the threshold for effects on energy budget (i.e., sublethal effects) at 19.21 mg kg^- 1. This study demonstrates that DEB-TKTD models can be successfully applied to E. crypticus as a representative soil species, and may improve the ecological risk assessment for terrestrial ecosystems, and our mechanistic understanding of chemical effects on non-target species.

Large size (>100-μm) microplastics are not biomagnifying in coastal marine food webs of British Columbia, Canada

Microplastics (MPs) contamination in marine environments is of increasing concern, as plastic particles are globally ubiquitous across ecosystems. A large variety of aquatic taxa ingest MPs, but the extent to which animals accumulate and transfer MPs through food webs is largely unknown. In this study, we quantified MP uptake in bivalves, crabs, echinoderms, and fish feeding at different trophic levels at three sites on southern Vancouver Island. We paired stable-isotope food web analysis with MP concentrations in digestive tracts across all trophic levels and in fish livers. We then used Bayesian generalized linear mixed models to explore whether bioaccumulation and biomagnification were occurring. Our results showed that MPs (100-5000 μm along their longest dimension) are not biomagnifying in marine coastal food webs, with no correlation between the digestive tract or fish liver MP concentrations and trophic position of the various species. Ecological traits did, however, affect microplastic accumulation in digestive tracts, with suspension feeder and smaller-bodied planktivorous fish ingesting more MPs by body weight. Trophic transfer occurred between prey and predator for rockfish, but higher concentrations in full stomachs compared with empty ones suggested rapid excretion of ingested MPs. Collectively, our findings suggested the movement of MP through marine food webs is facilitated by species-specific mechanisms, with contamination susceptibility a function of species biology, not trophic position. Furthermore, the statistical methods we employ, including machine learning for classifying unknown particles and a probabilistic way to account for background contamination, are universally applicable to the study of microplastics. Our findings advance understanding of how MPs enter and move through aquatic food webs, suggesting that lower-trophic-level animals are more at risk of ingesting >100-μm MPs, relative to higher-trophic-level animals. Our work also highlights the need to advance the study of <100-μm MPs, which are still poorly understood and may need to be considered separately in ecological risk assessments.

Effects of the toxic dinoflagellate Alexandrium catenella on the behaviour and physiology of the blue mussel Mytilus edulis

The effects of harmful algae on bivalve physiology are complex and involve both physiological and behavioural responses. Studying those responses is essential to better describe and predict their impact on shellfish aquaculture and health risk for humans. In this study we recorded for two months the physiological response of the blue mussel Mytilus edulis from Eastern Canada to a one-week exposure to a paralytic shellfish poisoning producing dinoflagellate strain of Alexandrium catenella, isolated from the St Lawrence estuary, Canada. Mussels in a 'control' treatment were fed continuously with a non-toxic diet, while mussels in a 'starvation' treatment were fed the same non-toxic diet the first week and subsequently starved for seven weeks. Mussels in a 'toxic' treatment received A. catenella for one week before being starved until the end of the experiment. Over a two-month experiment we monitored shell and tissue growth, filtration capacity, respiration rate, byssal attachment strength, valve opening behaviour, and toxin content in tissues. Mussels fed normally on the toxic dinoflagellate and accumulated an average of 51.6 µg STXeq 100 g^-1 after one week of exposure. After seven weeks of depuration, about half of the specimen showed levels around 18 µg STXeq 100 g^-1. The condition index of exposed mussels ('toxic' treatment) decreased rapidly from the start as compared to mussels that received a one-week non-toxic diet ('starvation' treatment). Oxygen consumption rates increased in the 'toxic' treatment before leveling out with that of mussels from the 'starvation' treatment. Valve opening amplitude was lower in the 'toxic' treatment during and following the exposure. Average valve closure duration was higher right after the exposure, during the peak of mussel tissue intoxication. No significant change in byssal thread strength was observed through time in each treatment but less force was required to detach mussels from the 'toxic' and 'starvation' treatments. The number of byssus threads produced by mussels exposed to the toxic dinoflagellate was also lower than in the control group. These results represent advancements in our understanding of the impacts of harmful algae on bivalves and contribute to the development of mitigation measures necessary to both the safety of consumers and the sustainability of aquaculture operations.

Conventional and nano-copper pesticides are equally toxic to the estuarine amphipod Leptocheirus plumulosus

Modern nano-engineered pesticides have great promise for agriculture due to their extended, low dose release profiles that are intended to increase effectiveness but reduce environmental harm. Whether nanopesticides, including copper (Cu) formulations, cause reduced levels of toxicity to non-target aquatic organisms is unclear but important to assess. Predicting how aquatic species respond to incidental exposure to Cu-based nanopesticides is challenging because of the expected very low concentrations in the environment, and the two forms of exposure that may occur, namely to Cu ions and Cu nanoparticles. We conducted Cu speciation, tissue uptake, and 7-day toxicity laboratory experiments to test how a model estuarine organism, the amphipod Leptocheirus plumulosus, responded to two popular Cu-based nanopesticides, CuPRO and Kocide, and conventional CuCl₂. Exposure concentrations ranged from 0 to 2.5 ppm, which were similar to those found in estuarine water located downstream of agricultural fields. Cu dissolution rates were much slower for the nanopesticides than the ionic formula, and Cu body burden in amphipods increased approximately linearly with the nominal exposure concentration. Amphipod survival declined in a normal dose-response manner with no difference among Cu formulations. Growth and movement rates after 7 days revealed no difference among exposure levels when analyzed with conventional statistical methods. By contrast, analysis of respiration rates, inferred from biomass measurements, with a bioenergetic toxicodynamic model indicated potential for population-level effects of exposure to very low-levels of the two nanopesticides, as well as the control contaminant CuCl₂. Our results indicate that toxicity assessment of environmental trace pollutant concentrations may go undetected with traditional ecotoxicological tests. We present a process integrating toxicity test results and toxicodynamic modeling that can improve our capacity to detect and predict environmental impacts of very low levels of nanomaterials released into the environment.

Applying a mechanistic model to predict interacting effects of chemical exposure and food availability on fish populations

The potential environmental impacts of chemical exposures on wildlife are of growing concern. Freshwater ecosystems are vulnerable to chemical effects and wildlife populations, including fish, can be exposed to concentrations known to cause adverse effects at the individual level. Wild fish populations are also often subjected to numerous other stressors simultaneously which in temperate climates often include sustained periods of food limitation. The potential interactive effects of chemical exposures and food limitation on fish populations are however difficult to establish in the field. Mechanistic modelling approaches can be employed to help predict how the physiological effects of chemicals and food limitation on individuals may translate to population-level effects. Here an energy budget-individual-based model was developed and the control (no chemical) model was validated for the three-spined stickleback. Findings from two endocrine active chemical (EAC) case studies, (ethinyloestradiol and trenbolone) were then used to investigate how effects on individual fecundity translated into predicted population-level effects for environmentally relevant exposures. The cumulative effects of chemical exposure and food limitation were included in these analyses. Results show that effects of each EAC on the population were dependent on energy availability, and effects on population abundance were exacerbated by food limitation. Findings suggest that chemical effects and density dependent food competition interact to determine population responses to chemical exposures. Our study illustrates how mechanistic modelling approaches might usefully be applied to account for specific chemical effects, energy budgets and density-dependent competition, to provide a more integrated evaluation of population outcomes in chemical risk assessments.

Towards a spatiotemporally explicit toxicokinetic-toxicodynamic model for earthworm toxicity

The aim of the environmental risk assessment of chemicals is the prevention of unacceptable adverse effects on the environment. Therefore, the risk assessment for in-soil organisms, such as earthworms, is based on two key elements: the exposure assessment and the effect assessment. In the current risk assessment scheme, these two elements are not linked. While for the exposure assessment, advanced exposure models can take the spatial and temporal scale of substances into account, the effect assessment in the lower tiers considers only a limited temporal and spatial variability. However, for soil organisms, such as earthworms, those scales play a significant role as species move through the soil in response to environmental factors. To overcome this gap, we propose a conceptual integration of pesticide exposure, ecology, and toxicological effects on earthworms using a modular modeling approach. An essential part of this modular approach is the environment module, which utilizes exposure models to provide spatially and temporally explicit information on environmental variables (e.g., temperature, moisture, organic matter content) and chemical concentrations. The behavior module uses this information and simulates the feeding and movement of different earthworm species using a trait-based approach. The resulting exposure can be processed by a toxicokinetic-toxicodynamic (TKTD) module. TKTD models are particularly suitable to make effect predictions for time-variable exposure situations as they include the processes of uptake, elimination, internal distribution, and biotransformation of chemicals and link the internal concentration to an effect at the organism level. The population module incorporates existing population models of different earthworm species. The modular approach is illustrated using a case study with an insecticide. Our results emphasize that using a modular model approach will facilitate the integration of exposure and effects and thus enhance the risk assessment of soil organisms.

Similar individual-level responses to stressors have different population-level consequences among closely related species of trout

In this paper, we applied an individual-based model to study the population-level impacts of sub-lethal stressors affecting the metabolic pathways of three closely related trout species: Oncorhynchus mykiss (rainbow trout, RT), Salmo trutta (brown trout, BT) and Oncorhynchus calrki stomias (greenback cutthroat trout, GCT). Both RT and BT are well-studied species, and the former is widely used as a standard cold-water test species. These species are known to outcompete GCT, which is listed as threatened under the US Endangered Species Act. Our goal was to understand the extent to which stressor effects, which are often measured at the individual level, on taxonomically-related (i.e., surrogate) species can be informative of impacts on population dynamics in species that cannot be tested (e.g., listed species). When comparing stressor effects among species, we found that individual-level responses to each stressor were qualitatively comparable. Individual lengths and number of eggs decreased by similar percentages with respect to baseline, even if small quantitative differences were present depending on the physiological mode of action of the stressor. Individual-level effects in GCT were slightly greater when ingestion efficiency decreased, whereas effects in GCT and RT were greater when maintenance costs increased, and effects in BT were slightly greater when costs of growth increased. In contrast, results at the population level differed markedly among species with GCT the most impacted by sub-lethal stress effects on individual metabolism. Our findings suggest that using non-listed species to assess the risks of stressors to listed species populations may be misleading, even if the species are closely related and show similar individual-level responses. Mechanistic population models that incorporate species life history and ecology can improve inter-species extrapolation of stressor effects.

Bioenergetic responses of freshwater mussels Unio tumidus to the combined effects of nano-ZnO and temperature regime

Bivalves from the cooling reservoirs of electrical power plants (PP) are exposed to the chronic heating and chemical pollution making them a suitable model to study the combined effects of these stressors. We investigated the effect of in situ exposures to chemical and thermal pollution in the PP cooling ponds on the metabolic responses of unionid bivalves (Unio tumidus) to a novel widespread pollutant, ZnO nanoparticles (nZnO). Male U. tumidus from the reservoirs of Dobrotvir and Burshtyn PPs (DPP and BPP) were maintained in clean water at 18 °C, or exposed for 14 days to one of the following conditions: nZnO (3.1 μM) or Zn²⁺ (3.1 μM, a positive control for Zn impacts) at 18 °C, elevated temperature (T, 25 °C), or nZnO at 25 °C (nZnO + T). Baseline levels of glycogen, lipids and ATP were similar in the two studied populations, whereas the levels of proteins, lactate/pyruvate ratio (L/P) and extralysosomal cathepsin D level were higher in the tissues of BPP mussels. The levels of glycogen and glucose declined in most experimental exposures indicating elevated energy demand except for a slight increase in the digestive gland of warming-exposed BPP mussels and in the gills of the nZnO + T-exposed DPP-mussels. Experimental exposures stimulated cathepsin D activity likely reflecting onset of autophagic processes to compensate for stress-induced energy demand. No depletion of ATP in Zn-containing exposures was observed indicating that the cellular metabolic adjustments were sufficient for such compensation. Unexpectedly, experimental warming mitigated most metabolic responses to nZnO in co-exposures. Our data thus indicate that metabolic effects of nZnO strongly depend on the environmental context of the mussels (such as temperature and acclimation history) which must be taken into account for the molecular and cellular biomarker-based assessment of the nanoparticle effects in the field.

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

Mixed phylogenetic signal in fish toxicity data across chemical classes

Chemical use in society is growing rapidly and is one of the five major pressures on biodiversity worldwide. Since empirical toxicity studies of pollutants generally focus on a handful of model organisms, reliable approaches are needed to assess sensitivity to chemicals across the wide variety of species in the environment. Phylogenetic comparative methods (PCM) offer a promising approach for toxicity extrapolation incorporating known evolutionary relationships among species. If phylogenetic signal in toxicity data is high, i.e., closely related species are more similarly sensitive as compared to distantly related species, PCM could ultimately help predict species sensitivity when toxicity data are lacking. Here, we present the largest ever test of phylogenetic signal in toxicity data by combining phylogenetic data from fish with acute mortality data for 42 chemicals spanning 10 different chemical classes. Phylogenetic signal is high for some chemicals, particularly organophosphate pesticides, but not necessarily for many chemicals in other classes (e.g., metals, organochlorines). These results demonstrate that PCM may be useful for toxicity extrapolation in untested species for those chemicals with clear phylogenetic signal. This study provides a framework for using PCM to understand the patterns and causes of variation in species sensitivity to pollutants.

Physiological modes of action across species and toxicants: the key to predictive ecotoxicology

As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.

Nanomaterial libraries and model organisms for rapid high-content analysis of nanosafety

Safety analysis of engineered nanomaterials (ENMs) presents a formidable challenge regarding environmental health and safety, due to their complicated and diverse physicochemical properties. Although large amounts of data have been published regarding the potential hazards of these materials, we still lack a comprehensive strategy for their safety assessment, which generates a huge workload in decision-making. Thus, an integrated approach is urgently required by government, industry, academia and all others who deal with the safe implementation of nanomaterials on their way to the marketplace. The rapid emergence and sheer number of new nanomaterials with novel properties demands rapid and high-content screening (HCS), which could be performed on multiple materials to assess their safety and generate large data sets for integrated decision-making. With this approach, we have to consider reducing and replacing the commonly used rodent models, which are expensive, time-consuming, and not amenable to high-throughput screening and analysis. In this review, we present a ‘Library Integration Approach’ for high-content safety analysis relevant to the ENMs. We propose the integration of compositional and property-based ENM libraries for HCS of cells and biologically relevant organisms to be screened for mechanistic biomarkers that can be used to generate data for HCS and decision analysis. This systematic approach integrates the use of material and biological libraries, automated HCS and high-content data analysis to provide predictions about the environmental impact of large numbers of ENMs in various categories. This integrated approach also allows the safer design of ENMs, which is relevant to the implementation of nanotechnology solutions in the pharmaceutical industry.

Impaired ecosystem process despite little effects on populations: modeling combined effects of warming and toxicants

Freshwater ecosystems are exposed to many stressors, including toxic chemicals and global warming, which can impair, separately or in combination, important processes in organisms and hence higher levels of organization. Investigating combined effects of warming and toxicants has been a topic of little research, but neglecting their combined effects may seriously misguide management efforts. To explore how toxic chemicals and warming, alone and in combination, propagate across levels of biological organization, including a key ecosystem process, we developed an individual-based model (IBM) of a freshwater amphipod detritivore, Gammarus pseudolimnaeus, feeding on leaf litter. In this IBM, life history emerges from the individuals' energy budgets. We quantified, in different warming scenarios (+1-+4 °C), the effects of hypothetical toxicants on suborganismal processes, including feeding, somatic and maturity maintenance, growth, and reproduction. Warming reduced mean adult body sizes and population abundance and biomass, but only in the warmest scenarios. Leaf litter processing, a key contributor to ecosystem functioning and service delivery in streams, was consistently enhanced by warming, through strengthened interaction between the detritivorous consumer and its resource. Toxicant effects on feeding and maintenance resulted in initially small adverse effects on consumers, but ultimately led to population extinction and loss of ecosystem process. Warming in combination with toxicants had little effect at the individual and population levels, but ecosystem process was impaired in the warmer scenarios. Our results suggest that exposure to the same amount of toxicants can disproportionately compromise ecosystem processing depending on global warming scenarios; for example, reducing organismal feeding rates by 50% will reduce resource processing by 50% in current temperature conditions, but by up to 200% with warming of 4 °C. Our study has implications for assessing and monitoring impacts of chemicals on ecosystems facing global warming. We advise complementing existing monitoring approaches with directly quantifying ecosystem processes and services.

Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton

High Throughput Screening (HTS) using in vitro assessments at the subcellular level has great promise for screening new chemicals and emerging contaminants to identify high-risk candidates, but their linkage to ecological impacts has seldom been evaluated. We tested whether a battery of subcellular HTS tests could be used to accurately predict population-level effects of engineered metal nanoparticles (ENPs) on marine phytoplankton, important primary producers that support oceanic food webs. To overcome well-known difficulties of estimating ecologically meaningful toxicity parameters, we used novel Dynamic Energy Budget and Toxicodynamic (DEBtox) modeling techniques to evaluate impacts of ENPs on population growth rates. Our results show that population growth was negatively impacted by all four ENPs tested, but the HTS tests assessing many cell/physiological functions lacked predictive power at the population level. However, declining photosynthetic efficiency, a traditional physiological endpoint for photoautotrophs, was a good predictor of population level effects in phytoplankton. DEBtox techniques provided robust estimates of EC₁₀ for population growth rates in exponentially growing batch cultures of phytoplankton, and should be widely useful for ecotoxicological testing. Adoption of HTS approaches for ecotoxicological assessment should carefully evaluate the predictive power of specific assays to minimize the risk that effects at higher levels of biological organization may go undetected.

Extending standard testing period in honeybees to predict lifespan impacts of pesticides and heavy metals using dynamic energy budget modelling

Concern over reported honeybee (Apis mellifera spp.) losses has highlighted chemical exposure as a risk. Current laboratory oral toxicity tests in A. mellifera spp. use short-term, maximum 96 hour, exposures which may not necessarily account for chronic and cumulative toxicity. Here, we use extended 240 hour (10 day) exposures to examine seven agrochemicals and trace environmental pollutant toxicities for adult honeybees. Data were used to parameterise a dynamic energy budget model (DEBtox) to further examine potential survival effects up to 30 day and 90 day summer and winter worker lifespans. Honeybees were most sensitive to insecticides (clothianidin > dimethoate ≫ tau-fluvalinate), then trace metals/metalloids (cadmium, arsenic), followed by the fungicide propiconazole and herbicide 2,4-dichlorophenoxyacetic acid (2,4-D). LC₅₀s calculated from DEBtox parameters indicated a 27 fold change comparing exposure from 48 to 720 hours (summer worker lifespan) for cadmium, as the most time-dependent chemical as driven by slow toxicokinetics. Clothianidin and dimethoate exhibited more rapid toxicokinetics with 48 to 720 hour LC₅₀s changes of <4 fold. As effects from long-term exposure may exceed those measured in short-term tests, future regulatory tests should extend to 96 hours as standard, with extension to 240 hour exposures further improving realism.

The pros and cons of ecological risk assessment based on data from different levels of biological organization

Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

Oyster reproduction is affected by exposure to polystyrene microplastics

Plastics are persistent synthetic polymers that accumulate as waste in the marine environment. Microplastic (MP) particles are derived from the breakdown of larger debris or can enter the environment as microscopic fragments. Because filter-feeder organisms ingest MP while feeding, they are likely to be impacted by MP pollution. To assess the impact of polystyrene microspheres (micro-PS) on the physiology of the Pacific oyster, adult oysters were experimentally exposed to virgin micro-PS (2 and 6 µm in diameter; 0.023 mg·L(-1)) for 2 mo during a reproductive cycle. Effects were investigated on ecophysiological parameters; cellular, transcriptomic, and proteomic responses; fecundity; and offspring development. Oysters preferentially ingested the 6-µm micro-PS over the 2-µm-diameter particles. Consumption of microalgae and absorption efficiency were significantly higher in exposed oysters, suggesting compensatory and physical effects on both digestive parameters. After 2 mo, exposed oysters had significant decreases in oocyte number (-38%), diameter (-5%), and sperm velocity (-23%). The D-larval yield and larval development of offspring derived from exposed parents decreased by 41% and 18%, respectively, compared with control offspring. Dynamic energy budget modeling, supported by transcriptomic profiles, suggested a significant shift of energy allocation from reproduction to structural growth, and elevated maintenance costs in exposed oysters, which is thought to be caused by interference with energy uptake. Molecular signatures of endocrine disruption were also revealed, but no endocrine disruptors were found in the biological samples. This study provides evidence that micro-PS cause feeding modifications and reproductive disruption in oysters, with significant impacts on offspring.

Oyster reproduction is affected by exposure to polystyrene microplastics

Plastics are persistent synthetic polymers that accumulate as waste in the marine environment. Microplastic (MP) particles are derived from the breakdown of larger debris or can enter the environment as microscopic fragments. Because filter-feeder organisms ingest MP while feeding, they are likely to be impacted by MP pollution. To assess the impact of polystyrene microspheres (micro-PS) on the physiology of the Pacific oyster, adult oysters were experimentally exposed to virgin micro-PS (2 and 6 µm in diameter; 0.023 mg·L(-1)) for 2 mo during a reproductive cycle. Effects were investigated on ecophysiological parameters; cellular, transcriptomic, and proteomic responses; fecundity; and offspring development. Oysters preferentially ingested the 6-µm micro-PS over the 2-µm-diameter particles. Consumption of microalgae and absorption efficiency were significantly higher in exposed oysters, suggesting compensatory and physical effects on both digestive parameters. After 2 mo, exposed oysters had significant decreases in oocyte number (-38%), diameter (-5%), and sperm velocity (-23%). The D-larval yield and larval development of offspring derived from exposed parents decreased by 41% and 18%, respectively, compared with control offspring. Dynamic energy budget modeling, supported by transcriptomic profiles, suggested a significant shift of energy allocation from reproduction to structural growth, and elevated maintenance costs in exposed oysters, which is thought to be caused by interference with energy uptake. Molecular signatures of endocrine disruption were also revealed, but no endocrine disruptors were found in the biological samples. This study provides evidence that micro-PS cause feeding modifications and reproductive disruption in oysters, with significant impacts on offspring.

Quantitative Adverse Outcome Pathway Analysis of Hatching in Zebrafish with CuO Nanoparticles

This study develops and evaluates a mechanistic model of the hatching of zebrafish eggs that were exposed to CuO engineered nanoparticles (ENP) in a high-throughput screening system and places this model in an adverse outcome pathway (AOP) that also includes CuO ENP dissolution and Cu bioaccumulation. Cu(2+) inhibits the proteolytic activity of Zebrafish Hatching Enzyme 1 and thereby delay or impair hatching success. This study demonstrates that noncompetitive inhibition kinetics describe the impact of dissolved Cu on hatching; it is estimated that indefinitely long exposure to 1.88 μM dissolved Cu in the environment reduces hatching enzyme activity by 50%. The complexity arising from CuO ENP dissolution and CuO ENP assisted bioaccumulation of Cu has led to apparently contradictory findings about ion versus "nano" effects on hatching. Model-mediated data analyses indicate that, relative to copper salts, CuO ENPs increase the uptake rates of Cu into the perivitelline space up to 8 times. The toxicity assessment framework in this study can be adapted to accommodate other types of toxicant, environmental samples and other aquatic oviparous species.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

Disruption of amylase genes by RNA interference affects reproduction in the Pacific oyster Crassostrea gigas

Feeding strategies and digestive capacities can have important implications for variation in energetic pathways associated with ecological and economically important traits, such as growth or reproduction in bivalve species. Here, we investigated the role of amylase in the digestive processes of Crassostrea gigas, using in vivo RNA interference. This approach also allowed us to investigate the relationship between energy intake by feeding and gametogenesis in oysters. Double-stranded (ds)RNA designed to target the two α-amylase genes A and B was injected in vivo into the visceral mass of oysters at two doses. These treatments caused significant reductions in mean mRNA levels of the amylase genes: -50.7% and -59% mRNA A, and -71.9% and -70.6% mRNA B in 15 and 75 µg dsRNA-injected oysters, respectively, relative to controls. Interestingly, reproductive knock-down phenotypes were observed for both sexes at 48 days post-injection, with a significant reduction of the gonad area (-22.5% relative to controls) and germ cell under-proliferation revealed by histology. In response to the higher dose of dsRNA, we also observed reductions in amylase activity (-53%) and absorption efficiency (-5%). Based on these data, dynamic energy budget modeling showed that the limitation of energy intake by feeding that was induced by injection of amylase dsRNA was insufficient to affect gonadic development at the level observed in the present study. This finding suggests that other driving mechanisms, such as endogenous hormonal modulation, might significantly change energy allocation to reproduction, and increase the maintenance rate in oysters in response to dsRNA injection.

Dynamic energy budget modeling reveals the potential of future growth and calcification for the coccolithophore Emiliania huxleyi in an acidified ocean

Ocean acidification is likely to impact the calcification potential of marine organisms. In part due to the covarying nature of the ocean carbonate system components, including pH and CO2 and CO3(2-) levels, it remains largely unclear how each of these components may affect calcification rates quantitatively. We develop a process-based bioenergetic model that explains how several components of the ocean carbonate system collectively affect growth and calcification rates in Emiliania huxleyi, which plays a major role in marine primary production and biogeochemical carbon cycling. The model predicts that under the IPCC A2 emission scenario, its growth and calcification potential will have decreased by the end of the century, although those reductions are relatively modest. We anticipate that our model will be relevant for many other marine calcifying organisms, and that it can be used to improve our understanding of the impact of climate change on marine systems.

Implementation of a multidisciplinary approach to solve complex nano EHS problems by the UC Center for the Environmental Implications of Nanotechnology

UC CEIN was established with funding from the US National Science Foundation and the US Environmental Protection Agency in 2008 with the mission to study the impact of nanotechnology on the environment, including the identification of hazard and exposure scenarios that take into consideration the unique physicochemical properties of engineered nanomaterials (ENMs). Since its inception, the Center has made great progress in assembling a multidisciplinary team to develop the scientific underpinnings, research, knowledge acquisition, education and outreach that is required for assessing the safe implementation of nanotechnology in the environment. In this essay, the development of the infrastructure, protocols, and decision-making tools that are required to effectively integrate complementary scientific disciplines allowing knowledge gathering in a complex study area that goes beyond the traditional safety and risk assessment protocols of the 20th century is outlined. UC CEIN's streamlined approach, premised on predictive hazard and exposure assessment methods, high-throughput discovery platforms and environmental decision-making tools that consider a wide range of nano/bio interfaces in terrestrial and aquatic ecosystems, demonstrates the implementation of a 21st-century approach to the safe implementation of nanotechnology in the environment.

Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling

Individual-based models (IBMs) predict how dynamics at higher levels of biological organization emerge from individual-level processes. This makes them a particularly useful tool for ecotoxicology, where the effects of toxicants are measured at the individual level but protection goals are often aimed at the population level or higher. However, one drawback of IBMs is that they require significant effort and data to design for each species. A solution would be to develop IBMs for chemical risk assessment that are based on generic individual-level models and theory. Here we show how one generic theory, Dynamic Energy Budget (DEB) theory, can be used to extrapolate the effect of toxicants measured at the individual level to effects on population dynamics. DEB is based on first principles in bioenergetics and uses a common model structure to model all species. Parameterization for a certain species is done at the individual level and allows to predict population-level effects of toxicants for a wide range of environmental conditions and toxicant concentrations. We present the general approach, which in principle can be used for all animal species, and give an example using Daphnia magna exposed to 3,4-dichloroaniline. We conclude that our generic approach holds great potential for standardized ecological risk assessment based on ecological models. Currently, available data from standard tests can directly be used for parameterization under certain circumstances, but with limited extra effort standard tests at the individual would deliver data that could considerably improve the applicability and precision of extrapolation to the population level. Specifically, the measurement of a toxicant's effect on growth in addition to reproduction, and presenting data over time as opposed to reporting a single EC50 or dose response curve at one time point.

Chronic effects of carbamazepine on life-history strategies of Ceriodaphnia dubia in three successive generations

Trace quantities of pharmaceuticals are continuously being discharged into the environment through domestic and industrial wastewater effluents, causing concern among scientists and regulators regarding potential long-term impacts on aquatic ecosystems. These compounds and their metabolites are constantly interacting with organisms at various life-cycle stages and may differentially influence the development of embryonic, larval, juvenile, and adult stages. To understand the possible cumulative effects of exposure to carbamazepine (CBZ), a multigenerational approach was taken in which survival, reproduction, respiration, growth, brood size, and biomass of Ceriodaphnia dubia were assessed at sublethal concentrations over the course of three successive generations. CBZ exposure significantly decreased fecundity at 196.7 μg/L in the F0 and F1 generations over 2 weeks and acclimatized at 264.6 μg/L in the F2 generation. Similarly, a significant decrease of neonate dry weight was observed at the 196.7 μg/L CBZ treatment in the F1 generation, and it acclimatized at 264.6 μg/L treatment level in the F2 generation. Median time to first brood release was significantly delayed at 264.6 μg/L in the F2 generation, indicating slower maturation. Results over three successive generations are not different than what one would obtain by testing simply the F0 generation. Furthermore, the effects measured were observed at concentrations two orders of magnitude higher than are environmentally relevant, and it is unlikely that CBZ poses a substantial risk to the environment regarding the end points measured in this study. However, additional research through laboratory and field multigenerational studies may be required to understand the overall risk of CBZ to other nontarget organisms.

Ecological nanotoxicology: integrating nanomaterial hazard considerations across the subcellular, population, community, and ecosystems levels

Research into the health and environmental safety of nanotechnology has seriously lagged behind its emergence in industry. While humans have often adopted synthetic chemicals without considering ancillary consequences, the lessons learned from worldwide pollution should motivate making nanotechnology compatible with environmental concerns. Researchers and policymakers need to understand exposure and harm of engineered nanomaterials (ENMs), currently nanotechnology's main products, to influence the ENM industry toward sustainable growth. Yet, how should research proceed? Standard toxicity testing anchored in single-organism, dose-response characterizations does not adequately represent real-world exposure and receptor scenarios and their complexities. Our approach is different: it derives from ecology, the study of organisms' interactions with each other and their environments. Our approach involves the characterization of ENMs and the mechanistic assessment of their property-based effects. Using high throughput/content screening (HTS/HCS) with cells or environmentally-relevant organisms, we measure the effects of ENMs on a subcellular or population level. We then relate those effects to mechanisms within dynamic energy budget (DEB) models of growth and reproduction. We reconcile DEB model predictions with experimental data on organism and population responses. Finally, we use microcosm studies to measure the potential for community- or ecosystem-level effects by ENMs that are likely to be produced in large quantities and for which either HTS/HCS or DEB modeling suggest their potential to harm populations and ecosystems. Our approach accounts for ecological interactions across scales, from within organisms to whole ecosystems. Organismal ENM effects, if propagated through populations, can alter communities comprising multiple populations (e.g., plant, fish, bacteria) within food webs. Altered communities can change ecosystem services: processes that cycle carbon, nutrients, and energy, and regulate Earth's waters and atmosphere. We have shown ENM effects on populations, communities, and ecosystems, including transfer and concentration of ENMs through food chains, for a range of exposure scenarios; in many cases, we have identified subcellular ENM effects mechanisms. To keep pace with ENM development, rapid assessment of the mechanisms of ENM effects and modeling are needed. DEB models provide a method for mathematically representing effects such as the generation of reactive oxygen species and their associated damage. These models account for organism-level effects on metabolism and reproduction and can predict outcomes of ENM-organism combinations on populations; those predictions can then suggest ENM characteristics to be avoided. HTS/HCS provides a rapid assessment tool of the ENM chemical characteristics that affect biological systems; such results guide and expand DEB model expressions of hazard. Our approach addresses ecological processes in both natural and managed ecosystems (agriculture) and has the potential to deliver timely and meaningful understanding towards environmentally sustainable nanotechnology.

Individual sensitivity distribution evaluation from survival data using a mechanistic model: implications for ecotoxicological risk assessment

Two main alternatives are typically used to model mechanistically dose-survival relationship in ecotoxicity tests. Effects are related to a concentration of concern, for instance body concentration, and, to account for their differences relative to time-to-death, individuals have either different concentration thresholds for death ("individual tolerance approach"), or equal probability to die, with death occurring randomly ("stochastic death approach"). A general framework to unify both approaches has recently been proposed. We derived a model from this framework to analyse five datasets (daphnids exposed to selenium, guppies exposed to dieldrin and second, third and fourth instars chironomids exposed to copper), by extending the standard stochastic death approach. We showed the possibility to estimate properly the toxicity parameters together with inter-organisms differences of sensitivity for at least one of these parameters (here the threshold for effect). For the daphnids, there was no improvement of using the extended model, which confirms the expected low variability among genetically identical individuals. For all the other datasets, our model outperformed the standard approach without accounting for differences of sensitivity. We estimated coefficients of variations in the distribution of the logarithm of the threshold from 44% to 4% and showed, for chironomids, a decrease of inter-individual differences of sensitivity with the age of the larvae. All standard threshold estimates were close but above the medium value of the distribution in the new approach, which means that a concentration equal to the standard threshold would ultimately result in the death of more than half of the exposed organisms. A more relevant parameter, such as the concentration protecting 95% of the population, would be 2-4 times inferior to the standard threshold.

Reproductive and developmental toxicity of dioxin in fish

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD or dioxin) is a global environmental contaminant and the prototypical ligand for investigating aryl hydrocarbon receptor (AHR)-mediated toxicity. Environmental exposure to TCDD results in developmental and reproductive toxicity in fish, birds and mammals. To resolve the ecotoxicological relevance and human health risks posed by exposure to dioxin-like AHR agonists, a vertebrate model is needed that allows for toxicity studies at various levels of biological organization, assesses adverse reproductive and developmental effects and establishes appropriate integrative correlations between different levels of effects. Here we describe the reproductive and developmental toxicity of TCDD in feral fish species and summarize how using the zebrafish model to investigate TCDD toxicity has enabled us to characterize the AHR signaling in fish and to better understand how dioxin-like chemicals induce toxicity. We propose that such studies can be used to predict the risks that AHR ligands pose to feral fish populations and provide a platform for integrating risk assessments for both ecologically relevant organisms and humans.

Biology-based modeling to analyze uranium toxicity data on Daphnia magna in a multigeneration study

Recent studies have investigated chronic toxicity of waterborne depleted uranium on the life cycle and physiology of Daphnia magna. In particular, a reduction in food assimilation was observed. Our aims here were to examine whether this reduction could fully account for observed effects on both growth and reproduction, for three successive generations, and to investigate through microscope analyses whether this reduction resulted from direct damage to the intestinal epithelium. We analyzed data obtained by exposing Daphnia magna to uranium over three successive generations. We used energy-based models, which are both able to fit simultaneously growth and reproduction and are biologically relevant. Two possible modes of action were compared - decrease in food assimilation rate and increase in maintenance costs. In our models, effects were related either to internal concentration or to exposure concentration. The model that fitted the data best represented a decrease in food assimilation related to exposure concentration. Furthermore, observations of consequent histological damage to the intestinal epithelium, together with uranium precipitates in the epithelial cells, supported the assumption that uranium has direct effects on the digestive tract. We were able to model the data in all generations and showed that sensitivity increased from one generation to the next, in particular through a significant increase of the intensity of effect, once the threshold for appearance of effects was exceeded.

Systems biology: leading the revolution in ecotoxicology

The rapid development of new technologies such as transcriptomics, proteomics, and metabolomics (Omics) are changing the way ecotoxicology is practiced. The data deluge has begun with genomes of over 65 different aquatic species that are currently being sequenced, and many times that number with at least some level of transcriptome sequencing. Integrating these top-down methodologies is an essential task in the field of systems biology. Systems biology is a biology-based interdisciplinary field that focuses on complex interactions in biological systems, with the intent to model and discover emergent properties of the system. Recent studies demonstrate that Omics technologies provide valuable insight into ecotoxicity, both in laboratory exposures with model organisms and with animals exposed in the field. However, these approaches require a context of the whole animal and population to be relevant. Powerful approaches using reverse engineering to determine interacting networks of genes, proteins, or biochemical reactions are uncovering unique responses to toxicants. Modeling efforts in aquatic animals are evolving to interrelate the interacting networks of a system and the flow of information linking these elements. Just as is happening in medicine, systems biology approaches that allow the integration of many different scales of interaction and information are already driving a revolution in understanding the impacts of pollutants on aquatic systems.

Impacts of metal oxide nanoparticles on marine phytoplankton

Information on the toxicity of environmentally relevant concentrations of nanoparticles in marine ecosystems is needed for informed regulation of these emerging materials. We tested the effects of two types of metal oxide nanoparticles, TiO(2) and ZnO, on population growth rates of four species of marine phytoplankton representing three major coastal groups (diatoms, chlorophytes, and prymnesiophytes). These metal oxide nanoparticles (NPs) are becoming common components in many industrial, household, and cosmetic products that are released into coastal ecosystems. Titania NPs showed no measurable effect on growth rates of any species, while ZnO NPs significantly depressed growth rate of all four species. ZnO NPs aggregated rapidly in seawater, forming particles >400 nm hydrodynamic diameter within 30 min, and dissolved quickly, reaching equilibrium concentrations within 12 h. Toxicity of ZnO NPs to phytoplankton was likely due to dissolution, release, and uptake of free zinc ions, but specific nanoparticulate effects may be difficult to disentangle from effects due to free zinc ions. A modeling approach based on a Dynamic Energy Budget (DEB) framework was used to estimate sublethal effects of the two NPs on phytoplankton populations. Concentrations that were estimated to have no effect on population growth (NEC) were (one standard error in parentheses) 428 (58) μg L(-1) ZnO for the diatom Skeletonema marinoi and 223 (56) μg L(-1) for Thalassiosira pseudonana. NEC could not be estimated for the other taxa but were within the range of 500-1000 μg L(-1). Our results suggest that effects of metal oxide NPs on marine organisms is likely to vary with particle type and organism taxonomy.

Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants

We investigate the effectiveness of a sublethal toxic effect model embedded in Dynamic Energy Budget (DEB) theory for the analysis of field data. We analyze the performance of two species of mussels, Mytilus galloprovincialis and M. californianus, near a diffuser discharging produced water in the Southern California Bight, California. Produced water is a byproduct of oil production consisting of fossil water together with compounds added during the extraction process, and generally contains highly elevated levels of pollutants relative to sea water. Produced water negatively affects the production of somatic and reproductive biomass in both mussel species; we show that these negative effects can be quantified with our DEB-based modeling framework through the estimation of toxic effect scaling parameters. Our analyses reveal that the toxic impact of produced water on growth and reproduction of M. californianus is substantially higher than for M. galloprovincialis. Projections of the expected lifetime production of gonad biomass indicate that the environmental impact of produced water can be as large as 100%, whereas short-term assessment without the use of DEB theory projects a maximum effect of only 30%.