A realistic modelling framework to characterize individual- and population- level effects of chemicals on Daphnia magna. Implications for ecological risk assessment
The ultimate goal of ecological risk assessment (ERA) in the context of authorization or registration of chemicals is to protect (non-target) populations in natural systems from adverse effects due to exposure to the chemical. Extrapolation of effects from laboratory single species tests to the population level is a prominent challenge in ERA, which is now being circumvented by the use of safety or assessment factors. In fact, individual responses to chemical exposure do not directly translate into population-level effects but other important factors also control the population dynamics under natural and stressed conditions. These include the life-history traits of the species, density dependence effects, the natural inter individual variability, biological interactions like predation and interspecific competition, as well as the mode of action of the toxicant.
Accounting for these different features goes far beyond the standard toxicity tests currently adopted in risk assessment. For a more scientifically sound approach for extrapolation, the use of mechanistic effect models is being increasingly advocated as they allow accounting for the toxicant properties as well as for the relevant processes that intervene in the natural regulation of population dynamics. In my research project, I contribute to demonstrating the power of this tool by addressing research questions that are currently perceived as hampering the realism of ERA.
My research project addressed the following topics:
- Accounting for the natural variation of neonate fitness with environmental factors
- Understanding the modes of action of toxicants at the level of individuals and extrapolating effects to the population level using a realistic modelling framework.
- Improving the realism of risk assessment of chemicals and determining relevant ecological factors and processes which are susceptible to alter population sensitivities to the chemical.
- Investigating the recovery potential of daphnid populations in relation to the environmental scenario.
Accounting for the variation of neonate fitness with environmental factors under natural and toxicant conditions
Offspring fitness determines vital individual processes in Daphnia magna like growth, size at first reproduction or size-selective predation, which in turn affect higher-order processes such as population growth rate, population survival rates or resistance to starvation. Therefore, models addressing population dynamics should consider this natural variability. Offspring fitness is ususally estimated as a measure of the offspring weight or size. We investigated the multiple maternal and environmental effects on the neonate body size in Daphnia magna. Data analysis revealed that some environmental factors were the main determinants of the variation in this trait while others had less impact. Using step-wise multiple regression analysis, we developed an empirical model for the offspring size variation with the relevant maternal and environmental variables. The model also accounted for density-dependence effects. The validity of the multivariate model was tested against an independent dataset. The model accurately predicted the offspring size despite several genetic and environmental differences compared to the data used for parameterization. For more details, see Gabsi et al. (2014).
Identifying toxicant’s mode of action triggering population level effects
For this study we chose a toxicant for which the calculated PNEC derived from acute/chronic tests induced effects on populations of exposed Daphnia, which means that for this substance, risk assessment failed to be protective for daphnid populations. Contrary to classical toxicants which induce a reduction in the clutch size, this substance induces hormetic effects (53% compared to the control) at the expense of decreasing neonate body length (fitness). In addition to effects on reproduction, effects are detected on individual survival as well as on the F1 generation where they cause even stronger negative effects than in the original generation.
I apply an established individual-based population model (IBM) for Daphnia magna (IDamP, Preuss et al. 2009). IDamP is an individual-based population model that predicts the population dynamics of Daphnia magna based on individual life cycles including feeding, somatic growth, development, reproduction and survival processes. The main drivers of these processes are the food conditions and, via crowding effects, the density of the population.
IDamP addresses a laboratory scale of vessels maintained at 20 °C and with the algae Desmodesmus subspicatus as a food source. Population dynamics including population capacity and size structure emerge from the interactions of the individuals with each other (intra-specific competition) and with their environment (food concentration). IDamP was implemented in Delphi using Embarcadero 2010 RAD studio XE2. It is documented using the ODD (Overview, Design concepts, Detail; Grimm et al. 2006) protocol for describing individual-based models (Preuss et al. 2009).
Population tests’ results Tested scenarios
Regression models for reproduction and TKTD models for survival (GUTS, Jager et al. 2011) were calibrated to experimental data and used in combination with the IBM to extrapolate effects to the population level. Simulations are run for different scenarios regarding the toxicant’s effects: survival toxicity, reproductive toxicity, or survival and reproductive toxicity. Both assumptions for describing toxicodynamics, the stochastic death (SD) and the individual tolerance (IT), were tested. Results showed that the effects on reproduction and survival did not fully explain the observed reduction in population size. In addition, F1 generation effects triggered the observed reduction in population size. Using an IBM combined to a TK/TD model allowed to capture the multiple organism level effects of a chemical and detect the hidden mechanisms controlling for Daphnia populations by testing several effect scenarios, which cannot be done otherwise than with modelling. For more details, see Gabsi et al. 2013a and TRACE documentation for the IDamP model including the case study on Dispersogen A effects on Daphnia.
Integrating environmental realism for a more realistic risk prediction of population responses to chemicals
Effects of a competitor and a predator were implemented in IDamP following a worst-case approach. Competition effects were implemented in a dynamic manner: individuals of the competitive population undergo the same life cycle processes as those of the original one. The 2 populations compete for 1 food source and for space (crowding). The competitive population is assumed to have a slightly lower filtration rate than the original one. In the simulations, the competitor is assumed to be not sensitive to chemical stress. Predation was accounted for by implementing the feeding behaviour of Chaoborus crystallinus larvae on Daphnia.In the simulations, Chaoborus was assumed to be not sensitive to the chemical.
Results showed that equal toxicity inhibition levels differently affect the population abundance with and without species interactions. In addition, population responses to the same chemical are highly sensitive to the environmental stressor (predator or competitor) and to the food level. The ecological and toxicological interactions translated into synergistic, antagonistic or potentiating effects on population abundance. From the results of this study we conclude that population resilience cannot be attributed to chemical stress only. Accounting for the relevant ecological interactions would reduce uncertainties when extrapolating chemicals’ effects from individuals to the population level. For more details, see Gabsi et al. 2013b.
Predicting population recovery from chemical stress exposure in an environmentally relevant context
We used lethal toxicity levels on individuals as probability to die in percent. Population recovery was simulated with and without species interactions (competition and predation) at different temperature and feeding conditions. Population recovery is defined as the number of days needed to return to an abundance that is not significantly different from the abundance of the control population under the same simulated environmental conditions. Model simulation results revealed the implication of important ecological aspects in determining population recovery from chemical exposure. These aspects emerged from the competition type (contest competition) and the feeding behavior of the predator which altered population recovery. Furthermore, the same type of species interactions yielded different impacts on recovery when food or temperature conditions changed. From these different findings, we can infer that no specific role can be attributed to any abiotic or biotic variable in isolation. Only the complex interactive mechanisms between the different factors constituting the full environmental scenario can determine their mutual roles in controlling the resilience of populations to chemical stress exposure. unless the complex interactive mechanisms between the variables constituting the full environmental scenario are simultaneously taken into account in the framework of chemicals’ risk assessment, we cannot achieve a complete understanding of the mechanisms controlling population recovery. The use of validated mechanistic effect models can be used to test different exposure scenarios and would consequently significantly reduce the uncertainty in recovery estimates.
Gabsi F, Hammers-Wirtz M, Grimm V, Schäffer A and Preuss TG (in press) Coupling different mechanistic effect models for capturing individual- and population- level effects of chemicals: Lessons from a case where standard risk assessment failed. Ecological Modelling http://dx.doi.org/10.1016/j.ecolmodel.2013.06.018
Gabsi F., Schäffer A and Preuss TG (accepted manuscript). Predicting the sensitivity of populations from individual exposure to chemicals: The role of ecological interactions. Accepted for publication in Environmental Toxicology and Chemistry DOI: 10.1002/etc.2409
Gabsi F., Glazier D., Hammers-Wirtz M., Ratte HT. & Preuss TG. 2014. How do maternal traits and environmental factors determine offspring size in Daphnia magna? International Journal of Limnology. 50 (1): 9-18.
Agatz A, Hammers-Wirtz M, Gabsi F, Ratte HT., Brown CD. & Preuss TG. 2012. Promoting effects on reproduction increase population vulnerability of Daphnia magna. Environmental Toxicology and Chemistry 31(7): 1604–1610.
Last updated: January 30th 2014