Skip to main content
Log in

Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling

  • Published:
Ecotoxicology Aims and scope Submit manuscript


Individual-based models (IBMs) predict how dynamics at higher levels of biological organization emerge from individual-level processes. This makes them a particularly useful tool for ecotoxicology, where the effects of toxicants are measured at the individual level but protection goals are often aimed at the population level or higher. However, one drawback of IBMs is that they require significant effort and data to design for each species. A solution would be to develop IBMs for chemical risk assessment that are based on generic individual-level models and theory. Here we show how one generic theory, Dynamic Energy Budget (DEB) theory, can be used to extrapolate the effect of toxicants measured at the individual level to effects on population dynamics. DEB is based on first principles in bioenergetics and uses a common model structure to model all species. Parameterization for a certain species is done at the individual level and allows to predict population-level effects of toxicants for a wide range of environmental conditions and toxicant concentrations. We present the general approach, which in principle can be used for all animal species, and give an example using Daphnia magna exposed to 3,4-dichloroaniline. We conclude that our generic approach holds great potential for standardized ecological risk assessment based on ecological models. Currently, available data from standard tests can directly be used for parameterization under certain circumstances, but with limited extra effort standard tests at the individual would deliver data that could considerably improve the applicability and precision of extrapolation to the population level. Specifically, the measurement of a toxicant’s effect on growth in addition to reproduction, and presenting data over time as opposed to reporting a single EC50 or dose response curve at one time point.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others


  • Álvarez OA, Jager T, Colao BN, Kammenga JE (2006) Temporal dynamics of effect concentrations. Environ Sci Technol 40(7):2478–2484

    Article  Google Scholar 

  • Ashauer R, Agatz A, Albert C, Ducrot V, Galic N, Hendriks J, Jager T, Kretschmann A, O’Conner I, Rubach MN, Nyman A, Schmitt W, Stadnicka J, van den Brink PJ, Preuss TG (2011) Toxicokinetic-toxicodynamic modeling of quantal and graded sublethal endpoints: a brief discussion of concepts. Environ Toxicol Chem 30(11):2519–2524

    Article  CAS  Google Scholar 

  • Baas J, Jager T, Kooijman SALM (2010) Understanding toxicity as processes in time. Sci Total Environ 408(18):3735–3739

    Article  CAS  Google Scholar 

  • de Roos AM, Persson L (2013) Population and community ecology of ontogenetic development. Princeton University Press

  • Elendt BP (1990a) Influence of water composition on the chronic toxicity of 3,4-dichloroaniline to Daphnia magna. Water Res 24(9):1169–1172

    Article  CAS  Google Scholar 

  • Elendt BP (1990b) Influence of water composition on the chronic toxicity of 3,4-dichloroaniline to Daphnia magna. Water Res 24(9):1169–1172

    Article  CAS  Google Scholar 

  • Forbes VE, Hommen U, Thorbek P, Heimbach F, van den Brink PJ, Wogram J, Thulke HH, Grimm V (2009) Ecological models in support of regulatory risk assessments of pesticides: developing a strategy for the future. Integr Environ Assess Manag 5(1):167–172

    Article  CAS  Google Scholar 

  • Forbes VE, Olsen M, Palmqvist A, Calow P (2010) Environmentally sensitive life cycle traits have low elasticity: implications for theory and practice. Ecol Appl 20(5):1449–1455

    Article  Google Scholar 

  • Grimm V, Railsback SF (2012) Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology. Philos Trans R Soc B Biol Sci 367(1586):298–310

    Article  Google Scholar 

  • Grimm V, Revilla E, Berger U, Jeltsch F, Mooij WM, Railsback SF, Thulke HH, Weiner J, Wiegand T, DeAngelis DL (2005) Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310(5750):987–991

    Google Scholar 

  • Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback S, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman R, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198(1):115–126

    Article  Google Scholar 

  • Grimm V, Ashauer R, Forbes V, Hommen U, Preuss TG, Schmidt A, van den Brink PJ, Wogram J, Thorbek P (2009) CREAM: a European project on mechanistic effect models for ecological risk assessment of chemicals. Environ Sci Pollut Res 16(6):614–617

    Article  Google Scholar 

  • Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221(23):2760–2768

    Article  Google Scholar 

  • Gurney WSC, Middleton DAJ, Nisbet RM, McCauley E, Murdoch W, de Roos AM (1996) Individual energetics and the equilibrium demography of structured populations. Theor Popul Biol 49(3):344–368

    Article  Google Scholar 

  • Heckmann LH, Baas J, Jager T (2010) Time is of the essence. Environ Toxicol Chem 29(6):1396–1398

    CAS  Google Scholar 

  • Jager T, Heugens EH, Kooijman SA (2006) Making sense of ecotoxicological test results: towards application of process-based models. Ecotoxicology 15(3):305–314

    Article  CAS  Google Scholar 

  • Jager T, Vandenbrouck T, Baas J, de Coen WM, Kooijman SALM (2010) A biology-based approach for mixture toxicity of multiple endpoints over the life cycle. Ecotoxicology 19(2):351–361

    Article  CAS  Google Scholar 

  • Kendall RJ, Lacher TE (1994) Wildlife toxicology and population modeling, SETAC special publication. Lewis Publishers, Boca Raton

    Google Scholar 

  • Kooijman SALM, Bedaux JJM (1996) Analysis of toxicity tests on Daphnia survival and reproduction. Water Res 30(7):1711–1723

    Article  CAS  Google Scholar 

  • Kooijman SALM, Metz JAJ (1984) On the dynamics of chemically stressed populations: the deduction of population consequences from effects on individuals. Ecotoxicol Environ Saf 8:254–274

    Article  CAS  Google Scholar 

  • Kooijman SALM, Sousa T, Pecquerie L, Van der Meer J, Jager T (2008) From food-dependent statistics to metabolic parameters, a practical guide to the use of dynamic energy budget theory. Biol Rev 83(4):533–552

    Article  CAS  Google Scholar 

  • Kooiman SALM (2010) Dynamic energy budget theory for metabolic organisation. Cambridge University Press

  • Lika K, Kearney MR, Freitas V, van der Veer HW, van der Meer J, Wijsman JW, Pecquerie L, Kooijman SA (2011) The “covariation method” for estimating the parameters of the standard Dynamic Energy Budget model I: philosophy and approach. J Sea Res 66(4):270–277

    Article  Google Scholar 

  • Martin BT, Zimmer EI, Grimm V, Jager T (2012) Dynamic Energy Budget theory meets individual-based modelling: a generic and accessible implementation. Methods Ecol Evol 3(2):445–449

    Article  Google Scholar 

  • Martin BT, Jager T, Nisbet RM, Pruess TG, Grimm V (in press) Predicting population dynamics from the properties of individuals: a cross-level test of Dynamic Energy Budget theory. Am Nat. doi:10.1086/669904

  • Muller EB, Nisbet RM, Berkley HA (2010) Sublethal effects of toxic compounds on dynamic energy budgets; model formulation. Ecotoxicology 19:48–60

    Article  CAS  Google Scholar 

  • Munns WR Jr (2006) Assessing risks to wildlife populations from multiple stressors: overview of the problem and research needs. Ecol Soc 11(1):23

    Google Scholar 

  • Nisbet RM, Muller EB, Lika K, Kooijman SALM (2000) From molecules to ecosystems through Dynamic Energy Budget models. J Anim Ecol 69:913–926

    Article  Google Scholar 

  • Pastorok RA, Bartell SM, Ferson S, Ginzburg LR (eds) (2001) Ecological modeling in risk assessment: chemical effects on populations, ecosystems, and landscapes. CRC Press, Boca Raton

  • Preuss TG, Hommen U, Alix A, Ashauer R, van den Brink PJ, Chapman P, Ducrot V, Forbes V, Grimm V, Schäfer D, Streissl F, Thorbek P (2009) Mechanistic effect models for ecological risk assessment of chemicals (MEMoRisk)—a new SETAC Europe Advisory Group. Environ Sci Pollut Res 16:250–252

    Article  Google Scholar 

  • Preuss TG, Hammers-Wirtz M, Ratte HT (2010) The potential of individual based population models to extrapolate effects measured at standardized test conditions to relevant environmental conditions—an example for 3,4-dichloroaniline on Daphnia magna. J Environ Monit 12(11):2070–2079

    Article  CAS  Google Scholar 

  • Railsback SF, Grimm V (2011) Individual-based modeling: a practical introduction. Princeton University Press

  • Railsback SF, Harvey BC (2002) Analysis of habitat-selection rules using an individual-based model. Ecology 83(7):1817–1830

    Google Scholar 

  • Sokull-Kluettgen B (1998) Die kombinierte Wirkung von Nahrungsangebot und 3,4-Dichloranilin auf die Lebensdaten von zwei nahverwandten Cladocerenarten, Daphnia magna und Ceriodaphnia quadrangula. Shaker, Aachen

  • Sousa T, Domingos T, Kooijman SALM (2008) From empirical patterns to theory: a formal metabolic theory of life. Philos Trans R Soc B: Biol Sci 363(1502):2453–2464

    Article  Google Scholar 

  • Stillman RA, Goss-Custard JD (2010) Individual-based ecology of coastal birds. Biol Rev 85(3):413–434

    Article  Google Scholar 

  • Thorbek P, Forbes VE, Heimback F, Hommen U, Thulke HH, Van den Brink PJ, Wogram J, Grimm V (2010) Ecological models for regulatory risk assessments of pesticides: Developing a strategy for the future. CRC press, Boca Raton

    Google Scholar 

  • Wiegand T, Jeltsch F, Hanski I, Grimm V (2003) Using pattern-oriented modeling for revealing hidden information: a key for reconciling ecological theory and application. Oikos 100(2):209–222

    Article  Google Scholar 

  • Wilensky U (1999) NetLogo. Center for connected learning and computer-based modeling. Northwestern University, Evanston

Download references


We thank two anonymous reviewers for comments that improved the quality of the manuscript. BTM, TJ, TP, and VG acknowledge support from by the European Union under the 7th Framework Programme (project acronym CREAM, contract number PITN-GA-2009-238148). RMN acknowledges support from US National Science Foundation under grant EF-0742521, and from the US National Science Foundation and the US Environmental Protection Agency under Cooperative Agreement Number EF 0830117.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Benjamin T. Martin.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 173 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Martin, B.T., Jager, T., Nisbet, R.M. et al. Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling. Ecotoxicology 22, 574–583 (2013).

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: