Predictive modelling of metal mixture toxicity to Daphnia magna populations

Current practice of environmental risk assessment lacks ecological realism, because it depends mostly on toxicity of single substances to individual organisms. It is desirable to develop mechanistic, predictive models that take mixture toxicity on higher levels of organization into account. We conducted a population experiment with Daphnia magna exposed to Cu-Ni-Zn mixtures and the single metals, in order to calibrate a Dynamic Energy Budget Individual-Based Model (DEB-IBM) with single-metal population data and generate blind predictions on mixture toxicity. Metals with different physiological modes of action (PMoA) can be implemented independently in the DEB-IBM, without making further assumptions concerning mixture toxicity. For metals with the same PMoA, we assume no interactions between metals.We first explored approaches to calibrate a DEB-IBM with population-level data, which imposes constraints on parameter estimation as compared to conventional DEB-IBM calibration with individual-level data.We further evaluated the predictive capacity of the DEBbased approach in comparison with common reference models IA and Concentration Addition (CA). While the performance of CA and IA was concentration-dependent, the DEB-IBM has the capacity to capture such trends, because mixture toxicity is an emergent property and interactions between organisms can be taken into account. We conclude that an approach based on DEB-IBMs is a promising way forward to generate predictive models and enhance understanding of mixture toxicity at higher levels of biological organization

Extrapolation of Zinc toxicity from individuals to communities in three Daphnia species

There is growing evidence that, in order to effectively assess the risk of chemicals, it is crucial to take the role of species interactions into account. Due to the large number of possible species assemblies, it is desirable to develop predictive, mechanistic models that can be calibrated with standard toxicity data. Therefore, we have conducted life-table experiments with Daphnia magna, D. pulex and D. longispina, exposed to Cu, Ni and Zn, in order to calibrate individual-based models based on Dynamic Energy Budget Theory (DEB-IBM). We derived DEB parameters from control data and calibrated modules for lethal and sublethal effects of Cu, Ni and Zn. Species were combined in silico into binary and tertiary communities and community dynamics under metal exposure were simulated. In the DEB-IBM, interspecific interactions emerge from physiological properties via competition for a shared resource. Each DEB parameter has direct or indirect consequences for resource utilization, and therefore for species interactions. Chemical stressors have the potential to alter these interactions, because effects are implemented as changes in DEB parameters. We modelled the effects of metals on two community-level endpoints, productivity and community structure. The two endpoints are inherently different because only productivity is subject to functional redundancy, leading to large differences in community-level sensitivity, based on which endpoint is chosen. While effects of metals on community-level endpoints can in principle be deduced from DEB theory, experiments to validate the predictions generated with the DEB-IBM are still lacking, and are crucial to evaluate the usefulness of our approach in application. We believe that the use of DEB-IBMs to investigate effects of chemical stressors on higher levels of biological organizations can be fruitful, because data for calibration can be generated relatively easily and models can be developed from established, biology-based frameworks

Mechanistic modelling of Zinc toxicity to the green algae Desmodesmus subspicatus: Interactions between Phosphorus levels, light and temperature and long-term toxicity in flow-through systems

To increase the ecological realism of Ecological Risk Assessment (ERA), the ability to extrapolate toxic effects from individual-level toxicity tests to more ecologically relevant endpoints is desirable. Here, we calibrated a mechanistic model of algal Phosphorus uptake and growth for the green algae Desmodesmus subspicatus to extrapolate Zinc toxicity from batch- to flow-through systems, and across a wide range of Phosphorus, light and temperature levels. For model calibration, we used standard toxicity data, the results of which (response of relative growth rate) were used to estimate concentrationresponse parameters of the mechanistic model. To generate predictions, we simulated a flow-through system and derived population growth rates as well as 10 day-cell densities as endpoints. Model predictions were associated with considerable uncertainty due to the limited calibration dataset. While only growth rates were reported in the original study, some time-series data (e.g. cell densities over time) is needed to reliably infer model parameters. The model predicted D. subspicatus populations to be more sensitive to Zn in flowthrough compared to batch systems, and no considerable effect of Phosphorus levels on Zn sensitivity across the entire range of physiologically relevant values. Temperature and light increased Zn sensitivity (up to factor of 8) as either factor became more limiting. The highest sensitivity was predicted for cold and hypertrophic conditions. Our results suggest that Zn sensitivity of D. subspicatus is largely unaffected by Phosphorus levels in flow-through systems, but light and temperature limitation can increase sensitivity considerably. This highlights the need to take environmentally relevant scenarios into account in ERA

Mechanistic modelling of Nickel toxicity to the green algae Raphidocelis subcapitata: Interactions between P levels and long-term toxicity in flow-through systems

Standard toxicity tests for primary producers do not take into account that under natural conditions, primary producers encounter varying nutrient availability, which might in turn modify toxicity. This limits ecological realism of Environmental Risk Assessment (ERA), for which toxicity data on primary producers is always necessary. We implemented and calibrated a mechanistic model of Ni toxicity to the green algae and standard test organism Raphidocelis subcapitata (formerly known as Pseudokirchneriella subcapitata). By explicitly modelling P uptake and usage, it is possible to simulate Ni toxicity at any P level. We extrapolated Ni toxicity to an array of P levels, ranging from oligotrophic to hypereutrophic, to predict the relationship between nutrient availability and Ni toxicity, assuming that algal P status does not directly influence Ni toxicity. Mechanistic effect modelling predicted minor negative effects of P limitation on Ni sensitivity. These trends might depend on certain modelling assumptions. Populations were predicted to be most sensitive at hypereutrophic conditions with respect to both considered endpoints, though fold-changes in sensitivity between P levels did not exceed a factor of 1.6

Mechanistic modelling of Zinc toxicity to the green algae Raphidocelis subcapitata: Interactions between P levels, temperature and light and long-term toxicity in flow-through systems

To increase the ecological realism of Ecological Risk Assessment (ERA), the ability to extrapolate toxic effects from individual-level toxicity tests to more ecologically relevant endpoints is desirable. Here, we calibrated a mechanistic model of algal Phosphorus uptake and growth for the green algae Raphidocelis subcapitata to extrapolate Zinc toxicity from batch- to flow-through systems, and across a wide range of Phosphorus, light and temperature levels. For model calibration, we used standard toxicity data, the results of which (cell densities over time) were used to estimate maximum growth rate and concentration-response parameters. To generate predictions, we simulated a flow-through system and derived population growth rates as well as 10 day-cell densities (~equilibrium) as endpoints. The model predicted R. subcapitata populations to be more sensitive to Zn in flow-through compared to batch systems, and an up to 1.3-fold decrease in EC10s with increasing Phosphorus levels (from oligotrophic to hypereutrophic). Temperature and light increased Zn sensitivity (up to factor of 1.65, physiologically relevant range) as either factor became more limiting. The biggest difference between simulated and originally reported EC10s was found for 10-day density at eutrophic conditions (factor of 1.7). Our results suggest that Zn sensitivity of R. subcapitata might be affected by different environmental factors (P, light, temperature) in different ways (decreasing sensitivity with increasing P limitation, increasing sensitivity with increasing light and temperature limitation), highlighting the need to take environmentally relevant scenarios into account in ERA

Extrapolation of Zinc toxicity to Daphnia longispina from Individuals to Populations

To increase the ecological realism of Ecological Risk Assessment (ERA), the ability to extrapolate toxic effects from individual-level toxicity tests to more ecologically relevant, population-level endpoints is desirable. Here, we calibrated an Individualbased models based on Dynamic Energy Budget Theory (DEB-IBM) for the waterflea Daphnia longispina to extrapolate Zinc toxicity from the individual to the population level. For model calibration, we conducted life-table experiments, the results of which (survival, growth and reproduction) were used to estimate DEB and Zinc toxicity parameters. The statistical comparison of model fits with observed life-table data slightly favored Cost of Reproduction as the most likely physiological mode of action (pMoA), although Costs of Growth could, based on visual inspection of the fits, not be entirely excluded. Using the calibrated DEB-IBM, predicted population-level effects manifested in terms of reduced population growth rates as well as reduced carrying capacities, including the potential for recovery of the population. It remains to be validated whether all predicted population dynamics patterns would be reproducible in a true microcosm experiment or in the field, given that food dynamics there can be different compared to those used in our model simulations. An important practical implication of our work in terms of risk assessment applications is that, in comparison with the standard individual-level 21d-reproduction endpoint, the population-level endpoints were consistently less sensitive, with individual-level sensitivity exceeding population-level sensitivity by a factor of 3.7 and 2.6, depending on the choice of population-level endpoint

Mechanistic modelling of Silver toxicity to the green algae Raphidocelis subcapitata : interactions between P levels and long-term toxicity in flow-through systems

Standard toxicity tests for primary producers do not take into account that under natural conditions, primary producers encounter varying nutrient availability, which might in turn modify toxicity. This limits ecological realism of Environmental Risk Assessment (ERA), for which toxicity data on primary producers is always necessary. We implemented and calibrated a mechanistic model of Ag toxicity to the green algae and standard test organism Raphidocelis subcapitata (also known as Pseudokirchneriella subcapitata). By explicitly modelling P uptake and usage, it is possible to simulate Ag toxicity at any P level. We extrapolated Ag toxicity to an array of P levels, ranging from oligotrophic to hypereutrophic, to predict the relationship between nutrient availability and Ag toxicity, assuming that algal P status does not directly influence Ag toxicity. Mechanistic effect modelling predicted minor negative effects of P limitation on Ag sensitivity. These trends might depend on certain modelling assumptions. Populations were predicted to be most sensitive at hypereutrophic conditions with respect to growth rates, with fold-changes in sensitivity between P levels not exceeding a factor of 1.3. With respect to 10-day population density, populations were predicted to be most sensitive at oligotrophic conditions, but the predicted effects of P on toxicity were small (0.93-fold change in EC10)