IDamP-model

Contact: Preuss, Thomas, Dr.

An individual-based population model was developed to predict the population dynamics of D. magna from individual life-history traits observed in experiments with different feeding conditions with and without the impact of a toxicant.

 

Model description

The individual-based modelling approach was chosen for the Daphnia model because it is very diverse and many aspects of biological systems can be simulated. It also offers several advantages for model testing, e.g. testing model predictions on two levels of organisation, the individual and the population. Within the model, each daphnid passes its individual life cycle (Fig. 1) including feeding on algae, aging, growing, developing and - when maturity is reached - reproducing. The modelled life cycle is driven by the amount of ingested algae and the density of the Daphnia population: At low algae densities the population dynamics is mainly driven by food supply, when the densities of algae are high, the limiting factor is "crowding" (a density-dependent mechanism due to chemical substances released by the animals or physical contact, but independent of food competition). An detailed description of the model is given in Preuss et al. 2009.

 

Fig. 1: Conceptual diagram of the asexual life-cycle of Daphnia magna.
Rectangles indicate processes on the individual level and queries are expressed in rhombs.

 

Model calibration

The model was calibrated using data from life-cycle tests at flow-through conditions with different levels of algae concentrations. In addition to the average life-cycle parameters for different food levels, the variability between the individuals was considered by stochastic assignment of values from the observed distributions in the experiments to each individual property. Since modelling of field studies imply variable temperature scenarios, impact of temperature on all processes within the IDamP-model were tested on literature data and implemented in the IDamP.

 

Applications for ecotoxicology

The effects of toxicants can be implemented by using data of the daphnia immobilisation test (OECD 202) and daphnia reproduction test (OECD 211). The model was tested for nonylphenol and 3,4-dichloroaniline, two substances with different mode of actions for D. magna. Nonylphenol act mainly by toxicity, whereas 3,4-Dichloraniline acts mainly on reproduction.

 

Included environmental processes

Food, Density, Temperature

 

Included effect models

  • Immediate Response (Concentration-response relationships) for toxicity as well as inhibition of reproduction and filtration rate
  • A TKTD model for survival (GUTS, Jager et al. 2011)

 

History of the model

Fitsch V (1990): Laborversuche und Simulationen zur kausalen Analyse der Populationsdynamik von Daphnia magna. Dissertation, RWTH Aachen

Dülmer U (1998): Konkurrenzbeziehung zweier Cladocerenarten unter Fremdstoffeinfluß - Analyse anhand von Experimenten und individuenbasierter Simulation. Diss. RWTH Aachen, Shaker Verlag, Aachen

Hommen (1998): Ökosystemmodelle von Modellökosystemen, Diss. RWTH Aachen, Shaker Verlag, Aachen

Rubach (2005): Wirkung von Nonylphenol auf Populationen von Daphnia magna.

 

Published model description

Preuss, T.G.; Hammers-Wirtz, M.; Hommen, U.; Rubach, M.N.; Ratte, H.T. (2009): Development and validation of an individual based Daphnia magna population model: The influence of crowding on population dynamics. Ecol. Model. 220: 310-329.

 

Published data for calibration and validation

Klüttgen B, Kuntz N, Ratte HT (1996): Combined effects of 3,4-dichloroaniline and food concentration on life table data of two related cladocerans, Daphnia magna and Ceriodaphnia quadrangula. Chemosphere 32, 2015-2028.

 

Published applications

Agatz A, Cole TA, Preuss TG, Zimmer EI, Brown CD. 2013. Feeding inhibition explains effects of imidacloprid on the growth, maturation, reproduction and survival of Daphnia magna. Environmental Science and Technology 47: 2909–2917.

Gergs A, Zenker A, Grimm V, Preuss TG. 2013. Chemical and natural stressors combined: from cryptic effects to population extinction. Scientific reports (Nature publishing group). DOI:10.1038/srep02036.

Gabsi F, Hammers-Wirtz M, Grimm V, Schäffer A,  Preuss TG.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. Article In press. DOI:http://dx.doi.org/10.1016/j.ecolmodel.2013.06.018

Gabsi F, Schäffer A, Preuss TG. Predicting the sensitivity of populations from individual exposure to chemicals: The role of ecological interactions.  Environmental Toxicology and Chemistry. Article in press DOI: http://onlinelibrary.wiley.com/doi/10.1002/etc.2409

Preuss, T.G.; Hammers-Wirtz, M; Ratte, H.T. (2010): The potential of individual based population models to extrapolate effects measured at standardized test conditions to environmental relevant conditions - an example for 3,4-dichloroaniline on Daphnia magna. J. Env. Monit. 12: 2070-2079

Hommen U, Ratte HT (2002): Population models to extrapolate from extended laboratory studies to probabilistic endpoints. In: Andy Hart (ed.) Report of the European workshop on Probabilistic Risk Assessment for the Environmental Impacts of Plant Protection Products (EUPRA). www.eupra.com, p. 85

Ratte HT (1996): Statistical implications of end-point selection and inspection interval in the Daphnia reproduction test - a simulation study. Environ. Toxicol. Chem. 15, 1831-1843.

Hommen U, Dülmer U, Ratte HT (1994): Monte-Carlo simulations in ecological risk assessment.- In: J Grasman & G van Straten (eds.): Predictability and Nonlinear Modelling in Natural Sciences and Economics, Kluwer, Dordrecht, p. 460-470

Hommen U, Poethke H J, Dülmer U, Ratte HT (1993): Simulation models to predict ecological risks of toxins in freshwater systems. ICES Journal of Marine Science 50, 337-347

 

Projects

CREAM (2009-2013): Modelling the Effects of toxicants on population recovery and extinction – Example of Daphnia magna for toxicants with different mechanisms of action.

PEvEP (2006-2009): Prediction of effects from variable exposure scenarios to plankton communities

 

Selected Platform and poster presentations

Gabsi F., Hammers-Wirtz M., Grimm V.,  Schäffer A. and Preuss T.G. 2013: Mechanistic effect modeling for capturing individual and population level effects of a chemical where standard risk assessment failed to be protective for populations. Platform presentation at the Symposium for the European Freshwater Sciences in Münster (Germany).

Gabsi F., Schäffer A. and Preuss T.G. 2013:  A modelling approach to characterize sub-lethal responses of Daphnia magna populations to chemicals in the presence of environmental stressors.” Platform presentation at the 23rd SETAC annual meeting in Glasgow, UK.

Gabsi F., Hammers-Wirtz M. and Preuss T.G. 2012: Do we need modeling for a conservative risk assessment of chemicals? An investigation on Daphnia magna populations. Poster presentation at the 6th SETAC World Congress / SETAC Europe 22nd Annual Meeting. Berlin, Germany.

Gabsi F. and Preuss T.G. 2011: Modelling the effects of toxicants on population recovery and extinction – Example of Daphnia magna for toxicants with different mechanisms of action. Poster presentation at the Marie Curie Researchers Symposium. Warsaw, Poland.

Gergs A., Rhiem S, Preuss TG (2011): Sensitivity shift in Daphnia magna population response caused by size selective predation. SETAC Europe 21th Annual Meeting, Milan, Italy

Preuss TG, Bruns E, Thorbek P, Hammers-Wirtz, Schäfer D, Goerlitz G, Ratte HT, Strauss T (2010): Can population modelling answer urgent unresolved questions for ecological risk assessment - lessons learnt from daphnia. SETAC North America 31st Annual Meeting, Portland Oregon, US

Preuss, T.G.; Bruns, E.; Schäfer , D.; Goerlitz , G.; Ratte , H.T. (2009): Prediction of effects from FOCUS-scenarios to populations of D. magna – Comparison of measured data and modelling results for triphenyltin. SETAC Europe 19th Annual Meeting, Göteburg, Sweden.

Preuss, T.G.; Strauß, T.; Ratte, H.T. (2008): How detailed do we have to model to predict extinction probabilities and recovery time for populations? SETAC World Congress, Sydney, Australien.

Preuss, T.G.; Bruns, E.; Schäfer, D.; Görlitz, G.; Ratte, H.T. (2008): Prediction of effects from variable exposure scenarios to populations of D. magna - Application of an individual-based population model. SETAC Europe 18th Annual Meeting, Warschau, Polen.

Preuss, T.G.; Hammers-Wirtz, M.; Ratte, H.T. (2007): Ein individuenbasiertes Daphnia magna Populationsmodel zur Vorhersage von Effekten auf Populationsebene. SETAC-GLB Jahresversammlung, Leipzig, Deutschland.

Preuss, T.G.; Hammers-Wirtz, M; Ratte, H.T. (2007): An individual-based Daphnia magna population model can be used to predict the ecological Relevance of sublethal endpoints. SETAC Europe 17th Annual Meeting, Oporto, Portugal.

Rubach, M.N.; Preuß, T.G; Hammers-Wirtz, M.; Ratte, H.T. (2005): Modelling the effects of nonylphenol on populations of Daphnia magna. SETAC Europe 15th Annual Meeting, Lille, Frankreich.

 

Cited literature

Ashauer R, Boxall A, Brown C. 2006. Predicting effects on aquatic organisms from fluctuating or pulsed exposure to pesticides. Environ Toxicol Chem 25 (7):1899-912.

Ashauer R, Boxall ABA, Brown CD. 2007. A new ecotoxicological model to simulate survival of aquatic invertebrates after exposure to fluctuating and sequential pulses of pesticides. Environ Sci Technol 41 (4): 1480-1486.

Grimm, V. and Railsback, S.F., 2005. Individual-Based Modeling and Ecology. Princeton University Press, Princeton.

Grimm V., Revilla E., Berger U., Jeltsch F., Mooij W.M., Railsback S.F., Thulke H.-H., Weiner J., Wiegand T. and DeAngelis D.L., 2005. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science, 310, 987-991.

Kooijman, S.A.L.M., 2000. Dynamic energy budgets in biological systems. Theory and applications in ecotoxicology. Cambridge Univ. Press.

Lee JH, Landrum PF, Koh CH. 2002. Prediction of time-dependent PAH toxicity in Hyalella azteca using a damage assessment model. Environ Sci Technol 36 (14):3131-3138.