On the relationships between bioassays and dynamics in chemically stressed, aquatic population models

Authors

  • Thomas G. Hallam Graduate Program in Ecology, University of Tennessee, Knoxville, TN 37996-1300, USA
  • Graciela A. Canziani Graduate Program in Ecology, University of Tennessee, Knoxville, TN 37996-1300, USA
  • Konstadia Lika Department of Mathematics, University of Tennessee, Knoxville, TN 37996-1300, USA

Abstract

One purpose c fthis article isto synthesize some recentresults on the dynamics of mathematical models of chemically stressed aquatic populations and communities; in particular, we (1) illustrate some of the difficulties that might arise from extrapolation of bioassay results to dynamic, chemically stressed population and community models; and (2) indicate different ways in which chemicals can affect the dynamics of population models. Bioassays, an important component of ecological impact and risk assessment, can be. misleading if extrapolated to settings beyond experimental boundaries. Extrapolation of bioassays to the populations and community levels can not be direct because derived information is usually specific for a subset of individuals and obtained under experimental constraints on time and parameters. We present examples derived from a mathematical setting where consequences of bioassays, even when employed as the fundamental determinant of stress in the systeni, have no predictable relationship to the ultimate effect of the chemical on the system. The first illustration, at the population level, demonstrates that sublethal effects of a lipophilic chemical with a reversible mode of action on individuals attained at concentrations well below the LC50, indeed even below the EC50 for growth, can drive the population to extinction so that the chemically stressed population is much more severely damaged than predicted by hioassays. The second illustration at the community level indicates that results of bioassays can also indicate outcomes that (ire worse than actually occurs for the community. Finally, we compare the outcome of a spectral analysis oftime series of a sequence of chemically stressed populations, demonstrating that complex effects of lipophilic chemicals on population dynamics are not readily identifiahle from spectral signatures.

References

Bracewell, R.N. 1984. The Fast Hartley Transform. Proceedings of the IEEE 72:1010-1018.

De Wolf, W.J.H. Canton, J.W. Deneer, R.C.C. Wegman and J L.M. Hennens. 1988. Quantitative structure - activity relationships and mixture-toxicity studies of mixtures of alcohols and chlorohydrocarbons reproducibility of effects on growth of reproduction Daphnia magna. Aquat. Toxicol. 12:39-49.

Hallam, T.G., G.A. Canziani and R.R. Lassiter. 1993. Sublethal narcosis and population persistence: A modeling study on growth effects. Environ. Toxicol. Cheat. 12:947-954.

Hallam, T.G., R. Lassiter, J. Li, L. Suárez. 1990x.Modeling individuals employing an integrated energy response: Application to Daphnia. Ecology 71:938-954.

Hallam, T.G., R.R. Lassiter, J. Li andW. McKinney. 19901). Toxic ant induced mortality in models of Daphnia populations. Environ. Toxicol. Chem. 9:597-621.

Hennens, J., H. Canton, P. Janssen and R. De Jong. 1984. Quantitative structure—activity relationships and toxicity studies of mixtures of chemicals with anesthetic potency: Acute lethal and sublethal toxicity to Daphnia magna. Aquat. Toxicol. 5:143-154.

Hennens, J., E. Brockhuyzen, H. Canton and R. Wegman. 1985.QSARs and mixture toxicity studies of alcohols and chlorohydrocarbons: Effects on growth of Daphnia magna. Aqua[. Toxicol. 6:209-217.

Jaworska, J.S., T.G. Hallam, S.M. Henson, W.R. McKinney and R.R. Lassiter. 1996. Ecotoxicology of predator- prey communities: an individual-based modeling approach. In: J.S. Hughes et al., Editors. Environmental Toxicology and Risk Assessment, Third Volume. ASTM STP 1218. American Society for Testing and Materials, Philadelphia. 157-172.

Jaworska, J.S., T.G. Hallam and T.W. Schultz. 1996x. A community model of the ciliate Tetrahymena and the bacteria E. coli, I. Individual - based models of Tetrahymena and E. coli. Bull. Math. Biol. 58:247-264.

Jaworska, J.S., T.G. Hallam and T.W. Schultz. 1996b. A community model of the ciliate Tetrahymena and the bacteria E. coli, II. Interactions in a batch system. Bull. Math. Biol. 58:265-283.

Jaworska, J.S., T.G. Hallam and T.W. Schultz. 1996c. Chronic effects of nonlpolar narcotics on a microbial community in a batch culture: A modeling study. Environ. Toxicol. Chem. (in press).

Kersting, K. 1975. The use of microsystems for the evaluation of the effects of toxicants. Hydrobiol. Bull. 9:102-108.

Press, W.H., B.P. Flanney, S.A. Tenkolsky and W.T. Vetterling. 1988. Numerical Recipes in Fortran. Cambridge University Press.

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Published

1996-06-01

How to Cite

Hallam, T. G., Canziani, G. A., & Lika, K. (1996). On the relationships between bioassays and dynamics in chemically stressed, aquatic population models. Ecología Austral, 6(1), 045–054. Retrieved from https://ojs.ecologiaaustral.com.ar/index.php/Ecologia_Austral/article/view/1666

Issue

Vol. 6 No. 1 (1996)

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Articles

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