Species interactions are often suggested as an important factor when assessing the effects of chemicals on higher levels of biological organization. Nevertheless, the contribution of intraspecific and interspecific interactions to chemical effects on populations is often overlooked. In the present study, Daphnia magna populations were initiated with different levels of intraspecific competition, interspecific competition, and predation and exposed to pyrene pulses. Generalized linear models were used to test which of these factors significantly explained population size and structure at different time points. Pyrene had a negative effect on total population densities, with effects being more pronounced on smaller D. magna individuals. Among all species interactions tested, predation had the largest negative effect on population densities. Predation and high initial intraspecific competition were shown to interact antagonistically with pyrene exposure. This was attributed to differences in population structure before pyrene exposure and pyrene-induced reductions in predation pressure by Chaoborus sp. larvae. The present study provides empirical evidence that species interactions within and between populations can alter the response of aquatic populations to chemical exposure. Therefore, such interactions are important factors to be considered in ecological risk assessments.
Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (DEBtox) and the general unified threshold model for survival (GUTS) are wellestablished theoretical frameworks that describe sublethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long-term effects on populations. We used DEBtox and GUTS in an individual-based model (IBM) framework to predict both single and combined effects of copper and zinc on Daphnia magna populations. The model was calibrated based on standard chronic toxicity test results with the single substances. A mixture toxicity implementation based on the general independent action model for mixtures was developed and validated with data from a population experiment with copper and zinc mixtures. Populationlevel effects of exposure to individual metals were accurately predicted by DEB-IBM. The DEB-IBM framework also allowed us to identify the potential mechanisms underlying these observations. Under independent action the DEB-IBM was able to predict the population dynamics observed in populations exposed to the single metals and their mixtures (R 2 > 65% in all treatments). Our modeling shows that it is possible to extrapolate from single-substance effects at the individual level to mixture toxicity effects at the population level, without the need for mixture toxicity data at the individual level from standard mixture toxicity tests. The application of such modeling techniques can increase the ecological realism in risk assessment.
Ecological impact assessment modeling systems are valuable support tools for managing impacts from commercial activities on marine habitats and species. The inclusion of toxic effects modeling in these systems is predicated on the availability and quality of ecotoxicology data. Here we report on a data gathering exercise to obtain toxic effects data on oil compounds for a selection of cold-water marine species of fish and plankton associated with the Barents Sea ecosystem. Effects data were collated from historical and contemporary literature resources for the endpoints mortality, development, growth, bioaccumulation and reproduction. Evaluating the utility and applicability of these data for modeling, we find that data coverage is limited to a sub-set of the required endpoints. There is a need for new experimental studies for zooplankton focused on the endpoints development and bioaccumulation and for larvae and juvenile fish focused on growth and development.
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