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Definition and calculation of uncertainty in ecological process models

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  • Turley, Marianne C.
  • Ford, E. David

Abstract

We present a method of multi-criteria assessment for the analysis of process model uncertainty that combines analysis of model structure, parameters and data requirements. There are three components in calculation and definition of uncertainty.(1)Assessment criteria: Uncertainty in a process model is reduced as the model can simultaneously simulate an increased number of assessment criteria selected to test specific aspects of the theory being investigated, and within acceptable limits set for those criteria. This reduces incomplete specification of the model—the characteristic that a model may explain some, but not all, of the observed features of a phenomenon. The calculation required is computation of the Pareto set which provides the list of simultaneously achieved criteria within specified ranges.(2)Parameter values: Uncertainty in a process model is reduced as the distribution of values for parameters simulating multiple assessment criteria within their acceptable limits becomes unimodal and with reduced range. This reduces non-uniqueness in the model—the characteristic that there may be alternative representations and no a priori way of deciding between them. The calculation required is analysis of parameter values within each group of the Pareto set, for their distributions and possible correlations which contributes to a definition of non-uniqueness in terms of whether multiple modes in parameter values are equally plausible.(3)Data and information: Uncertainty in a process model is reduced as the acceptable limits for assessment criteria are defined with increasing precision. The calculations required are to define acceptability ranges for the assessment criteria either through empirical investigations or through inference from related theories. This provides a definition of the relationship of the model to empirical and theoretical construction thought to be important.

Suggested Citation

  • Turley, Marianne C. & Ford, E. David, 2009. "Definition and calculation of uncertainty in ecological process models," Ecological Modelling, Elsevier, vol. 220(17), pages 1968-1983.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:17:p:1968-1983
    DOI: 10.1016/j.ecolmodel.2009.04.046
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    References listed on IDEAS

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    1. Callies, U. & Scharfe, M. & Ratto, M., 2008. "Calibration and uncertainty analysis of a simple model of silica-limited diatom growth in the Elbe River," Ecological Modelling, Elsevier, vol. 213(2), pages 229-244.
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    2. Li, Linjun & Lu, Hongfang & Campbell, Daniel E. & Ren, Hai, 2011. "Methods for estimating the uncertainty in emergy table-form models," Ecological Modelling, Elsevier, vol. 222(15), pages 2615-2622.
    3. Perz, Stephen G. & Muñoz-Carpena, Rafael & Kiker, Gregory & Holt, Robert D., 2013. "Evaluating ecological resilience with global sensitivity and uncertainty analysis," Ecological Modelling, Elsevier, vol. 263(C), pages 174-186.
    4. Marzloff, Martin P. & Johnson, Craig R. & Little, L. Rich & Soulié, Jean-Christophe & Ling, Scott D. & Frusher, Stewart D., 2013. "Sensitivity analysis and pattern-oriented validation of TRITON, a model with alternative community states: Insights on temperate rocky reefs dynamics," Ecological Modelling, Elsevier, vol. 258(C), pages 16-32.
    5. Huang, Jiacong & Gao, Junfeng & Liu, Jutao & Zhang, Yinjun, 2013. "State and parameter update of a hydrodynamic-phytoplankton model using ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 263(C), pages 81-91.

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