Abstract
The dynamic energy budget (DEB) theory for metabolic organisation specifies quantitatively the processes of uptake of substrate by organisms and its use for the purpose of maintenance, growth, maturation and reproduction. It applies to all organisms. Animals are special because they typically feed on other organisms. This couples the uptake of the different required substrates, and their energetics can, therefore, be captured realistically with a single reserve and a single structure compartment in biomass. Effects of chemical compounds (e.g. toxicants) are included by linking parameter values to internal concentrations. This involves a toxico-kinetic module that is linked to the DEB, in terms of uptake, elimination and (metabolic) transformation of the compounds. The core of the kinetic module is the simple one-compartment model, but extensions and modifications are required to link it to DEBs. We discuss how these extensions relate to each other and how they can be organised in a coherent framework that deals with effects of compounds with varying concentrations and with mixtures of chemicals. For the one-compartment model and its extensions, as well as for the standard DEB model for individual organisms, theory is available for the co-variation of parameter values among different applications, which facilitates model applications and extrapolations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kooijman SALM (2000) Dynamic energy and mass budgets in biological systems. Cambridge University Press, New York
Kooijman SALM (2001) Quantitative aspects of metabolic organization; A discussion of concepts. Phil Trans R Soc B 356:331–349
Kooijman SALM (1997) Process-oriented descriptions of toxic effects. In: Schüürmann G, Markert B (eds) Ecotoxicology, pp. 483–519. Spektrum Akademischer Verlag, Heidelberg
Kooijman SALM, Andersen T, Kooi BW (2004) Dynamic energy budget representations of stoichiometric constraints to population models. Ecol 85:1230–1243
Kooijman SALM, Grasman J, Kooi BW (2007) A new class of non-linear stochastic population models with mass conservation. Math Biosci 210:378–394
Kooi BW, Kelpin FDL (2003) Structured population dynamics, a modeling perspective. Comm theor Biol 8:125–168
Kooijman SALM, Kooi BW, Hallam TG (1999) The application of mass and energy conservation laws in physiologically structured population models of heterotrophic organisms. J theor Biol 197:371–392
Nisbet RM, Muller EB, Brooks AJ, Hosseini P (1997). Models relating individual and population response to contaminants. Environ Mod Assess 2:7–12
Sousa T, Domingos T, Kooijman SALM (2008) From empirical patterns to theory: A formal metabolic theory of life. Phil Trans R Soc B 363:2453–2464
Kooijman SALM, Troost TA (2007) Quantitative steps in the evolution of metabolic organisation as specified by the dynamic energy budget theory. Biol Rev 82:1–30
Leeuwen IMM van, Kelpin FDL, Kooijman SALM (2002) A mathematical model that accounts for the effects of caloric restriction on body weight and longevity. Biogerontol 3:373–381
Leeuwen IMM van, Zonneveld C, Kooijman SALM (2003) The embedded tumor: Host physiology is important for the interpretation of tumor growth. Brit J Cancer 89:2254–2263
Brack W, Bakker J, Deerenberg C, Deckere E de, Gils J van, Hein M, Jurajda P, Kooijman S, Lamoree M, Lek S, López de Alda MJ, Marcomini A, Muñoz I, Rattei S, Segner H, Thomas K, Ohe P van der, Westrich B, Zwart D de, Schmitt-Jansen M (2005) Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity. Environ Sci Pollut Res 12:252–256
Barber MC (2003) A review and comparison of models for predicting dynamic chemical bioconcentration in fish. Environ Toxicol Chem 22(9):1963–1992
Mackay D, Fraser A (2000) Bioaccumulation of persistent organic chemicals: mechanisms and models. Environ Pollut 110:375–391
Kooijman SALM, Jager T, Kooi BW (2004) The relationship between elimination rates and partition coefficients of chemical compounds. Chemosphere 57:745–753
Janssen MPM, Bergema WF (1991) The effect of temperature on cadmium kinetics and oxygen consumption in soil arthropods. Environ Toxicol Chem 10:1493–1501
Godfrey K (1983) Compartmental models and their application. Academic Press, London
Jacquez JA (1972) Compartmental analysis in biology and medicine. Elsevier, Amsterdam
Spurgeon DJ, Hopkin SP (1999) Comparisons of metal accumulation and excretion kinetics in earthworms (Eisenia fetida) exposed to contaminated field and laboratory soils. Appl Soil Ecol 11:227–243
Sheppard SC, Evenden WG, Cronwell TC(1997) Depuration and uptake kinetics of I, Cs, Mn, Zn and Cd by the earthworm (Lumbricus terrestris) in radiotracerspiked litter. Environ Toxicol Chem 16:2106–2112
Vijver MG, Vink JPM, Jager T, Wolterbeek HT, Straalen NM van, Gestel CAM van (2005) Elimination and uptake kinetics of Zn and Cd in the earthworm Lumbricus rubellus exposed to contaminated floodplain soil. Soil Biol Biochem 10:1843–1851
Kooijman SALM, Baas J, Bontje D, Broerse M, Jager T, Gestel CAM van, Hattum B van (2007) Scaling relationships based on partition coefficients and body sizes have similarities and interactions. SAR QSAR Environ Res 18:315–330
Kooijman SALM, Haren RJF van (1990) Animal energy budgets affect the kinetics of xenobiotics. Chemosphere 21:681–693
Finch CE (1994) Longevity, senescence, and the genome. University of Chicago Press, Chicago
Haren RJF van, Schepers HE, Kooijman SALM (1994) Dynamic energy budgets affect kinetics of xenobiotics in the marine mussel Mytilus edulis. Chemosphere 29:163–189
Molen GW van der, Kooijman SALM, Wittsiepe J, Schrey P, Flesch-Janys D, Slob W (2000) Estimation of dioxin and furan elimination rates from cross-sectional data using a pharmacokinetic model. J Exp Anal Environ Epidemiol 10:579–585
Peters RH (1983) The ecological implications of body size. Cambridge University Press, Cambridge
Wagner JG (1958) The kinetics of alcohol elimination in man. Acta Pharmacol Toxicol 14: 265–289
Tielens AGM (1982) The energy metabolism of the juvenile liver fluke, Fasciola hepatica, during its development in the vertebrate host. PhD thesis, Utrecht University, The Netherlands
Jager T, Heugens EHW, Kooijman SALM (2006) Making sense of ecotoxicological test results: towards process-based models. Ecotoxicol 15:305–314
Jager T, Crommentuijn T, Gestel CAM van, Kooijman SALM (2004) Simultaneous modelling of multiple endpoints in life-cycle toxicity tests. Environ Sci Technol 38:2894–2900
Péry ARR, Flammarion P, Vollat B, Bedaux JJM, Kooijman SALM, Garric J (2002) Using a biology-based model (debtox) to analyse bioassays in ecotoxicology: Opportunities and recommendations. Environ Toxicol Chem 21:459–465
Kooijman SALM, Bedaux JJM (1996) Analysis of toxicity tests on Daphnia survival and reproduction. Water Res 30:1711–1723
Kooijman SALM, Bedaux JJM (1996) Analysis of toxicity tests on fish growth. Water Res 30:1633–1644
Leeuwen IMM van, Zonneveld C (2001) From exposure to effect: A comparison of modeling approaches to chemical carcinogenesis. Mut Res 489:17–45
Péry ARR, Bedaux JJM, Zonneveld C, Kooijman SALM (2001) Analysis of bioassays with time-varying concentrations. Water Res 35:3825–3832
Alda Alvarez O, Jager T, Nunez Colao B, Kammenga JE (2006) Temporal dynamics of effect concentrations. Environ Sci Technol pages 2478–2484
Klepper O, Bedaux JJM (1997) A robust method for nonlinear parameter estimation illustrated on a toxicological model. Nonlin Anal 30:1677–1686
Klepper O, Bedaux JJM (1997) Nonlinear parameter estimation for toxicological threshold models. Ecol Modell 102:315–324
Pieters BJ, Jager T, Kraak MHS, Admiraal W (2006) Modeling responses of Daphnia magna to pesticide pulse exposure under varying food conditions: Intrinsic versus apparent sensitivity. Ecotoxicol 15:601–608
Brandt BW, Kelpin FDL, Leeuwen IMM van, Kooijman SALM (2004) Modelling microbial adaptation to changing availability of substrates. Water Res 38:1003–1013
Brandt BW, Leeuwen IMM van, Kooijman SALM (2003) A general model for multiple substrate biodegradation. Application to co-metabolism of non structurally analogous compounds. Water Res 37:4843–4854
Brandt BW, Kooijman SALM (2000) Two parameters account for the flocculated growth of microbes in biodegradation assays. Biotech Bioeng 70:677–684
Jager T, Kooijman SALM (2005) Modeling receptor kinetics in the analysis of survival data for organophosphorus pesticides. Environ Sci Technol 39:8307–8314
Muller EB, Nisbet RM (1997) Modeling the effect of toxicants on the parameters of dynamic energy budget models. In: Dwyer FJ, Doane TR, Hinman ML (eds) Environmental Toxicology and Risk Assessment: Modeling and Risk Assessment, Vol 6. American Society for Testing and Materials, Philadelphia, PA
Baas J, Houte BPP van, Gestel CAM van, Kooijman SALM (2007) Modelling the effects of binary mixtures on survival in time. Environ Toxicol Chem 26:1320–1327
Andersen JS, Bedaux JJM, Kooijman SALM, Holst H (2000) The influence of design parameters on statistical inference in non-linear estimation; a simulation study based on survival data and hazard modelling. J Agri Biol Environ Stat 5:323–341
Baas J, Jager T, Kooijman SALM (2009) Estimation of no effect concentrations from exposure experiments when values scatter among individuals. Ecol Model 220:411–418
Kooijman SALM, Bedaux JJM (1996) Some statistical properties of estimates of no-effects concentrations. Water Res 30:1724–1728
Kooijman SALM (2009) What the egg can tell about its hen: embryo development on the basis of dynamic energy budgets. J Math Biol 58:377–394
Kooijman SALM (1986) Energy budgets can explain body size relations. J theor Biol 121: 269–282
Kleiber M (1932) Body size and metabolism. Hilgardia 6:315–353
Lika K, Kooijman SALM (2003) Life history implications of allocation to growth versus reproduction in dynamic energy budgets. Bull Math Biol 65:809–834
Kooijman SALM (1985) Toxicity at population level. In: Cairns J (ed) Multispecies toxicity testing, pp. 143–164. Pergamon Press, New York
Alda Alvarez O, Jager T, Kooijman SALM, Kammenga J (2005) Responses to stress of Caenorhabditis elegans populations with different reproductive strategies. Func Ecol 19: 656–664
Kooijman SALM (1988) Strategies in ecotoxicological research. Environ Aspects Appl Biol 17(1):11–17
Kooi BW, Bontje D, Voorn GAK van, Kooijman SALM (2008) Sublethal contaminants effects in a simple aquatic food chain. Ecol Modell 112:304–318
Kooijman SALM, Hanstveit AO, Nyholm N (1996) No-effect concentrations in alga growth inhibition tests. Water Res 30:1625–1632
Kooijman SALM, Sousa T, Pecquerie L, Meer J van der, Jager T (2008) From food-dependent statistics to metabolic parameters, a practical guide to the use of dynamic energy budget theory. Biol Rev 83:533–552
Kooijman SALM, Bedaux JJM, Slob W (1996) No-effect concentration as a basis for ecological risk assessment. Risk Anal 16:445–447
Acknowledgements
This research has been supported financially by the European Union (European Commission, FP6 Contract No. 003956 and No 511237-GOCE).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Kooijman, S.A.L.M., Baas, J., Bontje, D., Broerse, M., van Gestel, C.A.M., Jager, T. (2009). Ecotoxicological Applications of Dynamic Energy Budget Theory. In: Devillers, J. (eds) Ecotoxicology Modeling. Emerging Topics in Ecotoxicology, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0197-2_9
Download citation
DOI: https://doi.org/10.1007/978-1-4419-0197-2_9
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-0196-5
Online ISBN: 978-1-4419-0197-2
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)