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Consistency of fuzzy rules in an ecological context

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  • Gutiérrez-Estrada, Juan C.
  • Pulido-Calvo, Inmaculada
  • Bilton, David T.

Abstract

In this paper, we assess the performance of fuzzy inference systems (FISs) and the consistency of fuzzy rules generated from a meta-analysis exploring diversity–environment relationships, in a system of temporary and fluctuating ponds located in two regions of southern England. The analyses focus on aquatic coleopteran assemblages, which act as excellent surrogates of wider freshwater macroinvertebrate diversity. Evaluated FISs were calibrated using evolutionary algorithms and the consistency of the rules examined using a consistency index specifically developed in this work. The best fit accounted for 76% of observed variability in the Shannon diversity index across ponds in the validation phase, which was 56 points better than the benchmark value established by a generalized additive model (GAM). The analysis of fuzzy rules indicated that the basic dynamics of this system are controlled by 8 rules. Another 10 complementary rules were detected, suggesting that more than a single dimension controlled the dynamics of the system. Therefore, water beetle diversity appears to be driven by a relatively short set of rules which relate diversity and environmental factors in a non-linear manner. These rules can be grouped according to their consistency levels, which reflect differences in coleopteran community composition.

Suggested Citation

  • Gutiérrez-Estrada, Juan C. & Pulido-Calvo, Inmaculada & Bilton, David T., 2013. "Consistency of fuzzy rules in an ecological context," Ecological Modelling, Elsevier, vol. 251(C), pages 187-198.
    • Handle: RePEc:eee:ecomod:v:251:y:2013:i:c:p:187-198
    DOI: 10.1016/j.ecolmodel.2012.12.013
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    References listed on IDEAS

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    1. Marten Scheffer & Steve Carpenter & Jonathan A. Foley & Carl Folke & Brian Walker, 2001. "Catastrophic shifts in ecosystems," Nature, Nature, vol. 413(6856), pages 591-596, October.
    2. Mouton, Ans M. & De Baets, Bernard & Van Broekhoven, Ester & Goethals, Peter L.M., 2009. "Prevalence-adjusted optimisation of fuzzy models for species distribution," Ecological Modelling, Elsevier, vol. 220(15), pages 1776-1786.
    3. Gutiérrez-Estrada, Juan C. & Bilton, David T., 2010. "A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters," Ecological Modelling, Elsevier, vol. 221(11), pages 1451-1462.
    4. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
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    1. Fan, Xing-Rong & Kang, Meng-Zhen & Heuvelink, Ep & de Reffye, Philippe & Hu, Bao-Gang, 2015. "A knowledge-and-data-driven modeling approach for simulating plant growth: A case study on tomato growth," Ecological Modelling, Elsevier, vol. 312(C), pages 363-373.

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