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Modelling the impact of flooding stress on the growth performance of woody species using fuzzy logic

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  • Glenz, C.
  • Iorgulescu, I.
  • Kienast, F.
  • Schlaepfer, R.

Abstract

Among the driving processes responsible for riparian forest dynamics the species-specific impact of flooding on the development of woody plants plays a key role—particularly for lowland rivers. Only a few of the forest succession models currently in use incorporate the flooding stress response of trees. This situation is mainly due to the incomplete investigation of the flooding tolerance processes and the related abiotic and biotic factors. In an attempt to use the wide-ranging but still rather vague knowledge available on flooding stress, the research presented in this paper proposes an approach to model tree response to flooding using the fuzzy set theory. The model is illustrated for the case of central European species. Flooding stress response to the abiotic factors of duration, depth and frequency of flooding differs according to five flooding tolerance classes and is expressed by means of a growth factor that limits optimal tree growth. We show that existing fuzzy set theory is able to generate and calibrate a flood stress response model which in turn can be incorporated into more complex forest succession models adapted to riparian areas.

Suggested Citation

  • Glenz, C. & Iorgulescu, I. & Kienast, F. & Schlaepfer, R., 2008. "Modelling the impact of flooding stress on the growth performance of woody species using fuzzy logic," Ecological Modelling, Elsevier, vol. 218(1), pages 18-28.
  • Handle: RePEc:eee:ecomod:v:218:y:2008:i:1:p:18-28
    DOI: 10.1016/j.ecolmodel.2008.06.008
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    References listed on IDEAS

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    1. Granger, Clive W. J., 1996. "Introducing Non-Linearity Into Cointegration," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 16(2), November.
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    Cited by:

    1. You, L. & Li, Y.P. & Huang, G.H. & Zhang, J.L., 2014. "Modeling regional ecosystem development under uncertainty – A case study for New Binhai District of Tianjin," Ecological Modelling, Elsevier, vol. 288(C), pages 127-142.
    2. Li, Y.P. & Huang, G.H. & Zhang, N. & Nie, S.L., 2011. "An inexact-stochastic with recourse model for developing regional economic-ecological sustainability under uncertainty," Ecological Modelling, Elsevier, vol. 222(2), pages 370-379.

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