A physiologically driven mathematical simulation model as a tool for extension of results from laboratory tests to ecosystem effects

  • Jørgen Aagaard Axelsen


One of the great challenges in ecotoxicology is to extrapolate results from exposure-effect experiments in the laboratory to a prediction or understanding of exposure-effect relationships at ecosystem level. A range of tests has been developed or is under development (Kula et al., 1995) for the assessment of exposure - effect relationships in terrestrial systems. Most of these are single-species tests and the interpretation of the results are problematic because they do not include the interactions, which take place in a community consisting of a large number of interacting species under natural climatic conditions


Prey Species Natural Climatic Condition Mathematical Simulation Model Poikilotherm Organism Microcosm Test 
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  1. Axelsen, J.A. (1994) Analysis of host-parasitoid relationships in an agricultural ecosystem. A computer simulation. Ecol. Modelling, 73, 189–203.CrossRefGoogle Scholar
  2. Axelsen, J.A., Holst, N., Hamers, T. and Krogh, P.H. (1997a) Simulations of the predator-prey interactions in a two species ecotoxicological test system.Google Scholar
  3. Axelsen, J. A., Holmstrup, M. and Krogh, P.H. (1997b). A simulation study of the impact of synchronisation, temperature and selection of individuals for the results of ecotoxicological tests with the Collembola Folsomia fimetaria L. and the predatory mite Hypoaspis aculeifer Canestrini. Pedobiologica, in press.Google Scholar
  4. Barnthouse, L.W. (1992) The role of models in ecological risk assessment: a 1990’s perspective. Environ. Toxicol. Chem,11, 1751–60.CrossRefGoogle Scholar
  5. Bartell, S.M., Gardner, R.H. and O Neill, R.V. (1992) Ecological Risk Estimation, Lewis Publishers, Boca Raton, Florida.Google Scholar
  6. Graf, B. and Hill, J.E. (1992) Modelling the competition for light and nitrogen between rice and Echinochloa crus-galli. Agricult. Syst, 40 345–59.CrossRefGoogle Scholar
  7. Graf, B., Baumgärtner, J. and Gutierrez, A.P. (1990a) Modeling agroecosystem dynamics with the metabolic pool approach. Mitt. Schweiz. Entomol. Ges, 63 465–76.Google Scholar
  8. Graf, B., Rakotobe, O., Zahner, P., Dellucchi, V. and Gutierrez, A.P. (1990b) A simulation model for the dynamics of rice growth and development: Part I — The carbon balance. Agricult. Syst, 32, 341–65.CrossRefGoogle Scholar
  9. Graf, B., Gutierrez, A.P., Rakotobe, O., Zahner, P. and Delluchi, V. (1990c) A simulation model for the dynamics of rice growth and development. Part II — the competition with weeds for nitrogen and light. Agricult. Syst, 32 367–92.CrossRefGoogle Scholar
  10. Gutierrez, A.P., Baumgärtner, J.U. and Hagen, K.S. (1981) A conceptual model for growth, development and reproduction in the ladybird beetle Hippodamia convergens G.-M. (Coccinellidae: Coleoptera). Can. Ent, 113 21–33.CrossRefGoogle Scholar
  11. Gutierrez, A.P., Baumgärtner, J.U. and Summers, C.G. (1984) Multitrophic models of predator—prey energetics. Can. Ent, 116 923–63.CrossRefGoogle Scholar
  12. Gutierrez, A.P., Schulthess, F., Wilson, L.T., Villacorta, A.M., Ellis, C.K. and Baumgärtner, J.U. (1987) Energy acquisition and allocation in plants and insects: a hypothesis for the possible role of hormones in insect feeding patterns. Can. Ent, 119 109–29.CrossRefGoogle Scholar
  13. Gutierrez, A.P., Wermelinger, B., Schulthess, F., Baumgärtner, J.U., Herren, H.R., Ellis, C.K. and Yaninek, J.S. (1988a) Analysis of biological control of cassava pests in Africa. I. Simulation of carbon, nitrogen and water dynamics in carbon. J. Appl. Ecol, 25 901–20.CrossRefGoogle Scholar
  14. Gutierrez, A.P., Neuenschwander, P., Schulthess, F., Herren, H.R., Baumgärtner, J.U., Wermelinger, B., Löhr, B. and Ellis, C.K. (1988b) Analysis of biological control of cassava pests in Africa. II. Cassava mealybug Phaenococcus manihoti. J. Appl. Ecol, 25 921–40.CrossRefGoogle Scholar
  15. Gutierrez, A.P., Yaninek, J.S., Wermelinger, B., Herren, H.R. and Ellis, C.K. (1988c) Analysis of biological control of cassava pests in Africa. III. Cassava green mite Mononychellus tanajoa. J. Appl. Ecol, 25, 941–50.CrossRefGoogle Scholar
  16. Gutierrez, A.P, Dos Santos, W.J., Villacorta, A., Pizzamiglio, M.A., Ellis, C.K., Caarvalho, L.H. and Stone N.D. (1991) Modelling the interaction of cotton and the cotton boll weevil. I. A comparison of growth and development of cotton varieties. J. Appl. Ecol, 28 371–97.CrossRefGoogle Scholar
  17. Gutierrez, A.P., Mariot, E.J., Cure, J.R., Wagner Riddle, C.S., Ellis, C.K., and Villacorta, A.M. (1994) A model of bean (Phaseolus vulgaris L.) growth types I—III: factors affecting yield. Agric. Syst, 44 35–63.CrossRefGoogle Scholar
  18. Hanratty, M.P. and Stay, F.S. (1994). Field evaluation of the littoral ecosystem risk assessment model’s predictions of the effects of chlorpyrifos. J. Appl. Ecol, 31 439–53.CrossRefGoogle Scholar
  19. Hommen, U., Poethke, H.-J., Dülmer, U. and Ratte, H.T. (1993) Simulation models to predict ecological risk of toxins in freshwater systems. ICES J. Mar. Sci, 50 337–47.CrossRefGoogle Scholar
  20. Kooijman, S.A.L.M., Hanstveit, A.O. and Van der Hoeven, N. (1987) Research on the physiological basis of population dynamics in relation to ecotoxicology. Wat. Sci. Tech, 19 21–37.Google Scholar
  21. Krogh, P.H. (1995) Effects of pesticides on the reproduction of Hypoaspis aculeifer (Gamasida: Laelapidae) in the laboratory. Acta Zool. Fenn, 196 333–7.Google Scholar
  22. Kula, H., Heimbach, U. and Lake, H. (eds) (1995) Progress Report 1994 of SECO-FASE, Third Technical Report. Development,improvement and standardization of test systems for assessing sublethal effects of chemicals on fauna in the soil ecosystem National Environmental Research Institute, Denmark.Google Scholar
  23. Lacey, R.F. and Mallett, M.J. (1991) Further statistical analysis of the EEC ring test of a method for determining the effects of chemicals on the growth-rate of fish. Room Document 3. OECD Ad-Hoc Meeting of Experts on Aquatic Toxicology, at WRC Medmenham, 10–12 December 1991.Google Scholar
  24. Lamb, R.J., Gerber, G.H. and Atkinson, G.F. (1984) Comparison of developmental rate curves Applied to egg hatching data of Entomoscelis americana Brown (Coleoptera: Chrysomelidae). Environ. Entomol, 13, 868–72.Google Scholar
  25. Manetch, T.J. (1976) Time-varying distributed delays and their use in aggregative models of large systems. IEEE Transactions on systems, man, and cybernetics, 8 547–53.CrossRefGoogle Scholar
  26. Sharpe, P.J.H. and Hu, L.C. (1980) Reaction kinetics of nutrition dependent poikilotherm development. J. Theor. Biol, 82, 317–33.CrossRefGoogle Scholar
  27. Sharpe, P.J.H., Curry, G.L., DeMichele, D.W. and Cole, C.L. (1977) Distribution model of organism development times. J. Theor. Biol, 66 21–38.CrossRefGoogle Scholar
  28. Stinner, R.E., Gutierrez, A.P. and Butler, G.D. (1974) An algorithm for temperature-dependent growth rate simulation. Can. Ent, 106 519–24.CrossRefGoogle Scholar
  29. Tamó, M., Baumgärtner, J. and Gutierrez, A.P. (1993) Analysis of the cowpea agro-ecosystem in West Africa. II Modelling the interactions between cowpea and the bean flower thrips Megalurothrips sjostedti (Trybom) (Thysanoptera, Thripidae). Ecol. Modelling, 70 89–113.CrossRefGoogle Scholar
  30. Taylor, F. (1981) Ecology and evolution of physiological time in insects. Am. Nat, 117 1–23.CrossRefGoogle Scholar
  31. Uvarov, B.P. (1931) Insects and climate. Trans. Entomol. Soc. London, 79 1–247.CrossRefGoogle Scholar
  32. Vansickle, J. (1977) Attrition in distributed delay models. IEEE Transactions on systems, man, and cybernetics, 7 635–8.CrossRefGoogle Scholar
  33. Wagner, T.L., Wu, H.-I., Sharpe, P.J.H., Schoolfield, R.M. and Coulson, R.N. (1984) Modelling insect developmental rates: a literature review and application of a biophysical model. Ann. Entomol. Soc. Am, 77 208–25.Google Scholar

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© Springer Science+Business Media Dordrecht 1997

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  • Jørgen Aagaard Axelsen

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