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Mathematical modelling — a management tool for aquatic ecosystems?
Helgoländer Meeresuntersuchungen volume 34, pages 221–235 (1980)
Abstract
Mathematical modelling may serve as a rational and powerful tool in the management of complex ecosystems. However, ecosystem models are drastic simplifications of the real world. As a rule they are based on a rather incomplete and scattered knowledge of the system in question. Furthermore, ecological systems and in particular marine systems are characterised by a high degree of complexity, spatial and functional heterogeneity, nonlinearity, complex behavioural features such as adptation and self-organisation, and a considerable stochastic element. Nevertheless, if management is to be based on predictions from mathematical models — and it has to be based on some kind of “model” in at least a broad sense — we need an estimate of prediction accuracy in terms of the management variables and constraints. One possible approach to model uncertainty is a probabilistic interpretation of model predictions, generated by use of Monte-Carlo techniques. Fuzzy data sets and ranges are used. The resulting model response allows the derivation of measures for model credibility. Probability distributions can be computed for certain system states under (un)certain input conditions, representing the effects of insufficient data and structural uncertainty on model-based predictions. Such analysis indicates that prediction uncertainty increases, not only with the uncertainty in the data, but also with increasing “distance” from the empirical conditions, and with time. Present ecoystem models can be a tool for qualitative discrimination between different management alternatives, rather than a credible means for detailed quantitative predictions of system response to a wide range of input conditions.
Literature cited
Andersen, K. P. & Ursin, E., 1977. A multispecies extension of the Beverton and Holt theory of fishing, with accounts of phosphorus circulation and primary production. — Meddr Danm. Fisk. — og Havunders. N. S.7, 319–435.
Bigelow, J. H. & De Haven, J. C., 1977. Protecting an estuary from floods — policy analysis of the Oosterschelde. Vol. V: Anaerobic conditions and related ecological disturbances. — RAND, R-2121/5-NETH.
Bigelow, J. H., Bolten, J. G. & De Haven, J. C., 1977. Protecting an estuary from floods — a policy analysis of the Oosterschelde. Vol. 4: Assessment of algae blooms, a potential ecological disturbance. — RAND, R-2121/4-NETH.
Bigelow, J. H., Dzitzer, C. & Peeters, J. H., 1978. Protecting an estuary from Floods — a policy analysis of the Oosterschelde. Vol. 2: Assessment of long-run ecological balances: an addendum (calibration data). — RAND, R-2121/3A-NETH.
Bigelow, J. H., De Haven, J.C., Dzitzer, C., Eilers, P. & Peeters, J. C. H., 1977. Protecting an estuary from floods — a policy analysis of the Oosterschelde. Vol. 3: Assessment of long-run ecological balances. — RAND, R-2121/3-NETH.
Biswas, A. K., 1975. Mathematical modelling and environmental decision-making. — Ecol. Modell.1, 31–48.
Chen, K. W. & Orlob, G. T., 1975. Ecological simulation for aquatic environments. In: Systems analysis and simulation in ecology. Ed. by B. C. Patten. Acad. Press, New York,3, 475–587.
Clark, W. C., Jones, D. D. & Holling, C. S., 1979. Lessons for ecological policy design: a case study of ecosystem management. — Ecol. Modell.7, 1–53.
Di Toro, D. M. & van Straten, G., 1979. Uncertainty in the parameters and predictions of phytoplankton models. International Institute for Applied Systems Analysis, Laxenburg, 34 pp. (WP-79-27).
Fedra, K., 1979a. Modelling biological processes in the aquatic environment (with special reference to adaptation). International Institute for Applied Systems Analysis, Laxenburg, 56 pp. (WP-79-20).
Fedra, K., 1979b. A stochastic approach to model uncertainty: a lake modelling example. International Institute for Applied Systems Analysis, Laxenburg, 46 pp. (WP-79-63).
Fedra, K., van Straten, G. & Beck, M. B., 1980. Uncertainty and Arbitrariness in ecosystems modelling: a lake modelling example. International Institute for Applied Systems Analysis, Laxenburg, 39 pp. (WP-80-87).
Goldberg, E. D., McCave, I. N., O'Brien, J. J. & Steele, J. M. (Eds), 1977. Marine modelling. Wiley-Interscience, New York, 895 pp.
Hedgpeth, J. W., 1977. Models and muddles. Some philosophical observations. — Helgoländer wiss. Meeresunters.30, 92–104.
Hilborn, R., 1979. Some failures and successes in applying systems analysis to ecological systems. — J. appl. Systems Analysis6, 25–31.
Holling, C. S., (Ed.), 1978. Adaptive environmental assessment and management. Wiley, Chichester, 377 pp.
IAHS-AISH, 1978. Modelling the water quality of the hydrological cycle. Proceedings of the Baden Symposium, Sept. 1978. IAHS-AISH Publ.125, 1–382.
Imboden, D. & Gächter, R., 1978. A dynamic lake model for trophic state prediction. — Ecol. Modell.4, 77–98.
International Institute for Applied Systems Analysis, 1979. Adaptive environmental assessment and management: current progress and prospects for the approach. Summary report of the first Policy Seminar 18–21 June, 1979. International Institute for Applied Systems Analysis, Laxenburg, CP-79-9, 123 pp.
James, L. D., Bowles, D. S., James, R. W. & Canfield, R. V., 1979. Estimation of water surface elevation probabilities and associated damages for the Great Salt Lake. Utah State University, Water Resources Planning Series UWRL/P-79/03, 182 pp.
Jørgensen, S.E. (Ed.), 1979. State-of-the-art in ecological modelling. Proceedings of the Conference on Ecological Modelling, Copenhagen, Denmark, 28 August–2 September 1978. International Society for Ecological Modelling, 891 pp.
Kremer, J. N. & Nixon, S. W., 1978. A coastal marine ecosystem: simulation and analysis. Springer, Berlin, 217 pp.
Mason, C. M. (Ed.), 1979. The effective management of resources. The international politics of the North Sea. Frances Pinter, London, 268 pp.
Meadows, D. H., Meadows, D. I., Randers, J. & Behrens, W. W., 1972. The limits to growth. Universe Books, New York, 205 pp.
O'Brien, J. J. & Wroblisnki, J. S., 1976. A simulation of the mesoscale distribution of the lower marine trophic levels off West Florida. In: Systems analysis and simulation in ecology. Ed. by B. C. Patten. Acad. Press, New York,4, 63–110.
Reckhow, K. H., 1979. Empirical lake models for phosphorus: development, applications, limitations and uncertainty 193–222. In: Perspectives on lake ecosystem modeling. Ed. by D. Scavia & A. Robertson. Ann Arbor Science Publ., Ann Arbor, Mich., 183–221 pp.
Reichel, F. & Dyck, S., 1979. Stochastische geohydraulische Berechnungsverfahren für die Projektierung der Tagbauentwässerung — Notwendigkeit, Ziele, Verfahren. — Neue Bergbautechn.9 (1), 6–10.
Scavia, D. & Robertson, A. (Eds.), 1979. Perspectives on lake ecosystem modeling. Ann Arbor Science, Publ., Ann Arbor, Mich. 326 pp.
Spear, R. C. & Hornberger, G. M., 1978. Eutrophication in Peel Inlet: an analysis of behaviour and sensitivity of a poorly defined system. — Cres. Rep. AS/P 24, 99 pp.
Steele, J. H., 1974. The structure of marine ecosystems. Harvard Univ. Press, Cambridge, 128 pp.
Steele, J. H. (Ed.), 1978. Spatial patterns in plankton communities. Plenum Press, New York, 470 pp. (NATO Conference Series, Ser. 4: Marine Sciences, Vol. 3).
Straskraba, M., 1979. Natural control mechanisms in models of aquatic ecosystems. — Ecol. Modell.6, 305–321.
van Straten, G. & de Boer, B., 1979. Sensitivity to uncertainty in a phytoplankton-oxygen model for lowland streams. International Institute for Applied Systems Analysis, Laxenburg, WP-79-28, 21 pp.
Vinogradov, M. E. & Menshutkin, V. V., 1977. The modeling of opensea ecosystems In: Marine modelling. Ed. by E. D. Goldberg, J. N. McCave, J. J. O'Brien & J. M. Steele. Wiley-Interscience, New York, 891–921.
Walsh, J. J. & Howe, S. O., 1976. Protein from the sea: a comparison of the simulated nitrogen and carbon productivity of the Peru upwelling ecoystem. In: Systems analysis and simulation in ecology. Ed. by B. C. Patten. Acad. Press, New York,v, 47–61.
Walters, C. J., 1975. Optimal harvest strategies for salmon in relation to environmental variability and uncertain production parameters. — J. Fish. Res. Bd Can.32, 1777–1784.
Watt, K. E. F., 1977. Why won't anyone believe us? — Simulation28, 1–3.
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Fedra, K. Mathematical modelling — a management tool for aquatic ecosystems?. Helgolander Meeresunters 34, 221–235 (1980). https://doi.org/10.1007/BF01984042
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DOI: https://doi.org/10.1007/BF01984042