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Different methods, different results: temporal trends in the study of nested subset patterns in parasite communities

Published online by Cambridge University Press:  10 September 2007

J. T. TIMI  and
R. POULIN
J. T. TIMI*
Affiliation:
Laboratorio de Parasitología, Departamento de Biología, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Mar del Plata, Funes 3350, (7600) Mar del Plata, Argentina, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
R. POULIN
Affiliation:
Department of Zoology, University of Otago, P.O. Box 56, Dunedin 9054, New Zealand
*
*Corresponding author: Laboratorio de Parasitología, Departamento de Biología, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Mar del Plata. Funes 3350, (7600) Mar del Plata, Argentina. Tel: +54 223 4752426. Fax: +54 223 4753150. E-mail: jtimi@mdp.edu.ar
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Summary

The search for nested subset patterns has become a powerful tool for understanding the processes shaping parasite communities. Here, we re-examine the results of past studies on nestedness in parasite communities, to assess how sensitive they are to the analytical method used. Using the metric N and the null model RANDOM1, the first method available to study nested patterns, early studies concluded that nestedness was infrequent in parasite communities. In contrast later studies, using instead the metric T and the nestedness temperature calculator (NTC), found that nested subset patterns were very common in parasite communities. Recently, a new algorithm, the binary matrix nestedness temperature calculator (BINMATNEST), has been proposed to quantify nestedness. Using data on 31 helminth communities of fish hosts, we show that applying the NTC yields consistently more significant nested patterns than when N and RANDOM1 are used on the same data. The use of BINMATNEST produced results that depend on the choice of the null model. To provide a benchmark, a straightforward comparison between the observed frequencies of co-occurrences of species with those expected from their prevalence under random assembly was also made for each community. This test indicates that random structure occurs in practically all communities, even those where one of the nestedness analyses found a significant pattern. We demonstrate that the probability of finding a nested pattern in a parasite community depends entirely on the metric and null model chosen for analysis.

Keywords

nested subset analysesparasite communitiesnull modelscommunity structure
Type
Research Article
Information
Parasitology , Volume 135 , Issue 1 , January 2008 , pp. 131 - 138
Copyright
Copyright © Cambridge University Press 2007

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