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The role of sensitivity analysis in ecological modelling

Author

Listed:
  • Cariboni, J.
  • Gatelli, D.
  • Liska, R.
  • Saltelli, A.

Abstract

This work illustrates available best practices to run a sensitivity analysis for ecological models. The properties of recommended methods and their ranges of application are illustrated by applying the sensitivity analysis techniques to two test cases. The first one is a classic Lotka–Volterra model, while the second one is a study on a fish population dynamics. Both quantitative and qualitative approaches are applied and the differences between local and global techniques are highlighted by using the test cases.

Suggested Citation

  • Cariboni, J. & Gatelli, D. & Liska, R. & Saltelli, A., 2007. "The role of sensitivity analysis in ecological modelling," Ecological Modelling, Elsevier, vol. 203(1), pages 167-182.
    • Handle: RePEc:eee:ecomod:v:203:y:2007:i:1:p:167-182
    DOI: 10.1016/j.ecolmodel.2005.10.045
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    References listed on IDEAS

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    1. Lomborg,Bjørn, 2001. "The Skeptical Environmentalist," Cambridge Books, Cambridge University Press, number 9780521010689.
    2. Saltelli A. & Tarantola S., 2002. "On the Relative Importance of Input Factors in Mathematical Models: Safety Assessment for Nuclear Waste Disposal," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 702-709, September.
    3. Saltelli, Andrea & Bolado, Ricardo, 1998. "An alternative way to compute Fourier amplitude sensitivity test (FAST)," Computational Statistics & Data Analysis, Elsevier, vol. 26(4), pages 445-460, February.
    4. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
    5. Saltelli, A. & Andres, T. H. & Homma, T., 1993. "Sensitivity analysis of model output : An investigation of new techniques," Computational Statistics & Data Analysis, Elsevier, vol. 15(2), pages 211-238, February.
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