Uncertainity and Arbitrariness in Ecosystems Modelling: A Lake Modelling Example

Fedra, K., Straten, G. van, & Beck, M.B. (1980). Uncertainity and Arbitrariness in Ecosystems Modelling: A Lake Modelling Example. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-80-087

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Abstract

Mathematical models of ecosystems are considerable simplifications of reality, and the data upon which they are based are usually scarce and uncertain. Calibration of large, complex models depends upon arbitrary assumptions and choices, and frequently calibration procedures do not deal adequately with the uncertainty in the data describing the system under study. Since much of the uncertainty and arbitrariness in ecological modeling is inevitable, because of both practical as well as theoretical limitations, model-based predictions should at least reveal their dependence on, and sensitivity to, uncertainty and arbitrary assumptions. The paper proposes a method that explicitly takes into account the uncertainty associated with data for modeling. By reference to a qualitative and somewhat vague definition of system behavior in terms of allowable ranges, an ensemble of acceptable parameter vectors for the model may be identified. This contrasts directly with a more conventional approach to model calibration, in which a quantitative (squared-error) criterion is minimized and through which a supposedly "unique" and "best" set of parameters can be derived. The ensemble of parameter vectors is then used for the simulation of a multitude of future systems behavior patterns, so that the uncertainty in the initial data and assumptions is preserved, and the thus predicted future systems response can be interpreted in a probabilistic manner.

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