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Bayesian network (BN) models are increasingly used as tools to support probabilistic environmental risk assessments (ERAs), because they can better account for uncertainty compared with the simpler approaches commonly used in traditional ERA. We used BNs as metamodels to link various sources of information in a probabilistic framework, to predict the risk of pesticides to aquatic communities under given scenarios. The research focused on rice fields surrounding the Albufera Natural Park (Valencia, Spain), and considered three selected pesticides: acetamiprid (an insecticide), 2-methyl-4-chlorophenoxyacetic acid (MCPA; a herbicide), and azoxystrobin (a fungicide). The developed BN linked the inputs and outputs of two pesticide models: a process-based exposure model (Rice Water Quality [RICEWQ]), and a probabilistic effects model (Predicts the Ecological Risk of Pesticides [PERPEST]) using case-based reasoning with data from microcosm and mesocosm experiments. The model characterized risk at three levels in a hierarchy: biological endpoints (e.g., molluscs, zooplankton, insects, etc.), endpoint groups (plants, invertebrates, vertebrates, and community processes), and community. The pesticide risk to a biological endpoint was characterized as the probability of an effect for a given pesticide concentration interval. The risk to an endpoint group was calculated as the joint probability of effect on any of the endpoints in the group. Likewise, community-level risk was calculated as the joint probability of any of the endpoint groups being affected. This approach enabled comparison of risk to endpoint groups across different pesticide types. For example, in a scenario for the year 2050, the predicted risk of the insecticide to the community (40% probability of effect) was dominated by the risk to invertebrates (36% risk). In contrast, herbicide-related risk to the community (63%) resulted from risk to both plants (35%) and invertebrates (38%); the latter might represent (in the present study) indirect effects of toxicity through the food chain. This novel approach combines the quantification of spatial variability of exposure with probabilistic risk prediction for different components of aquatic ecosystems. Environ Toxicol Chem 2024;43:182-196. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Mayfly nymphs are among the most sensitive taxa to neonicotinoids. The present study presents the acute and chronic toxicity of 3 neonicotinoids (imidacloprid, thiacloprid, and thiamethoxam) to a mayfly species (Cloeon dipterum) and some notes on the seasonality of the toxicity of imidacloprid to C. dipterum and 5 other invertebrate species. Imidacloprid and thiamethoxam showed equal acute and chronic toxicity to a winter generation of C. dipterum, whereas thiacloprid was approximately twice as toxic. The acute and chronic toxicity of imidacloprid was much higher for the C. dipterum summer generation than for the winter one. The acute toxicity differs by a factor of 20 for the 96-h 50% effective concentration (EC50) and by a factor of 5.4 for the chronic 28-d EC50. Temperature had only a slight effect on the sensitivity of C. dipterum to imidacloprid because we only found a factor of 1.7 difference in the 96-h EC50 between tests performed at 10 °C and 18 °C. The difference in sensitivity between summer and overwintering generations was also found for 3 other insect species. The results indicate that if the use and environmental fate of the 3 neonicotinoids are comparable, replacing imidacloprid by another neonicotinoid might not reduce the environmental impact on the mayfly nymph C. dipterum. The results also show the importance of reporting which generation is tested because sensitivity values of insects in the summer might be underestimated by the experiments performed with neonicotinoids and an overwintering population., (© 2015 SETAC.)

Because aquatic macroinvertebrates may be exposed regularly to pesticides in edge-of-the-field water bodies, an accurate assessment of potential adverse effects and subsequent population recovery is essential. Standard effect risk assessment tools are not able to fully address the complexities arising from multiple exposure patterns, nor can they properly address the population recovery process. In the present study, we developed an individual-based model of the freshwater amphipod Gammarus pulex to evaluate the consequences of exposure to 4 compounds with different modes of action on individual survival and population recovery. Effects on survival were calculated using concentration-effect relationships and the threshold damage model (TDM), which accounts for detailed processes of toxicokinetics and toxicodynamics. Delayed effects as calculated by the TDM had a significant impact on individual survival and population recovery. We also evaluated the standard assessment of effects after short-term exposures using the 96-h concentration-effect model and the TDM, which was conservative for very short-term exposure. An integration of a TKTD submodel with a population model can be used to explore the ecological relevance of ecotoxicity endpoints in different exposure environments., (© 2014 SETAC.)

Increased temperature and other environmental effects of global climate change (GCC) have documented impacts on many species (e.g., polar bears, amphibians, coral reefs) as well as on ecosystem processes and species interactions (e.g., the timing of predator-prey interactions). A challenge for ecotoxicologists is to predict how joint effects of climatic stress and toxicants measured at the individual level (e.g., reduced survival and reproduction) will be manifested at the population level (e.g., population growth rate, extinction risk) and community level (e.g., species richness, food-web structure). The authors discuss how population- and community-level responses to toxicants under GCC are likely to be influenced by various ecological mechanisms. Stress due to GCC may reduce the potential for resistance to and recovery from toxicant exposure. Long-term toxicant exposure can result in acquired tolerance to this stressor at the population or community level, but an associated cost of tolerance may be the reduced potential for tolerance to subsequent climatic stress (or vice versa). Moreover, GCC can induce large-scale shifts in community composition, which may affect the vulnerability of communities to other stressors. Ecological modeling based on species traits (representing life-history traits, population vulnerability, sensitivity to toxicants, and sensitivity to climate change) can be a promising approach for predicting combined impacts of GCC and toxicants on populations and communities., (Copyright © 2012 SETAC.)

The problem of how to deal with species sensitivity differences to toxic substances has been addressed successfully with the species sensitivity distribution (SSD), yet this has not increased understanding about the underlying mechanisms of sensitivity. Other researchers have identified the mode of action of chemicals and also biological traits of species as determinants for sensitivity, yet no systematic approach combines these factors. To achieve this, first existing data on organophosphate, carbamate, and pyrethroid toxicity and mode of action and also species trait information were mined. Second, we linked taxon sensitivity to their traits at the family level to generate empirical and mechanistic hypotheses about sensitivity-trait relationships. In this way, a mode-specific sensitivity (MSS) ranking method was developed, and tested at the taxonomic level of family and genus. The application of several quality criteria indicated overall confidence in rankings, but confidence in exact taxon rank was less certain, due to data insufficiency for certain groups. The MSS rankings were found to be applicable for trait-based approaches and were successfully linked to existing trait data to identify traits with predictive potential. Although this empirical analysis cannot test causality relationships between traits and sensitivity, testable hypotheses were generated, for further experimental investigation. Single traits as well as combinations of traits can be used to predict laboratory sensitivity to the substances tested, although associations were not as strong as in previous studies. We conclude that existing trait data are not suitable for every trait-based research question and that important traits remain to be identified and quantified in relation to the processes of toxicity, i.e., the toxicokinetics and toxicodynamics., (Copyright 2009 SETAC.)