, Volume 40, Issue 2, pp 235–262 | Cite as

Assessing superparasitism with a model combining the functional response and the egg distribution of parasitoids

  • R. Arditi
  • O. Glaizot


A model for superparasitism in insect parasitoids is developed. This model combines the study of superparasitism in terms of distribution of eggs among hosts (for a given number of hosts) and in terms of functional response (number of hosts attacked for a varying number of hosts available). Thus, it gives a synthetic treatment of problems that had been previously handled with separate models (e.g., Bakkeret al. (1972) on one hand and Arditi (1983) on the other hand). The combined model involves several parameters, among which important ones are the propensity to superparasitise, δ, and the average handling times spent on healthy and parasitised hosts, Th and Tp. Special cases are those of an indiscriminate parasitoid (δ=1 and Tp=Th) and of a “predator-like” parasitoid (δ=0 and Tp=0).

In this paper, the emphasis is put on the problems related with model identification and parameter estimation from experimental data. According to the data available, three situations are considered: egg distribution alone, functional response alone, and both combined.

The main conclusions are the following. (i) Egg distributions are described correctly when the parasitoid/host ratio is not too high. When the situation is very strained, i.e., when a small number of hosts are available per parasitoid, superparasitism occurs more frequently than predicted by the model. (ii) Functional response data are usually not precise enough to estimate all model parameters, particularly Tp. That is, it will usually not be possible to assess the discrimination capacity of a given species on the basis of a functional response curve only. (iii) If both a functional response and the corresponding egg distributions are available, it is better to fit the egg distribution model first and, depending on the estimated value of δ, to fit thereafter the appropriate functional response model.


parasitoids superparasitism functional response egg distribution parameter estimation non-linear regression 


Un modèle du superparasitisme chez les insectes parasitoïdes est développé. Ce modèle combine d'une part la distribution des œufs au sein des hôtes (pour un nombre donné d'hôtes) et d'autre part la réponse fonctionnelle (nombre d'hôtes attaqués pour différents nombres d'hôtes disponibles). Ce modèle propose ainsi une synthèse de deux approches habituellement considérées séparément (p. ex. Bakkeret al. (1972) d'un côté et Arditi (1983) d'un autre côté). Le modèle combiné utilise plusieurs paramètres, parmi lesquels la tendance à superparasiter, δ, et les temps moyens de manipulation des hôtes, Th et Tp. Deux cas particuliers décrivent un parasitoïde non-discriminateur (δ=1 et Tp=Th) et un discriminateur parfait, semblable à un prédateur (δ=0 et Tp=0).

Dans cet article, l'accent est mis sur les problèmes d'identification du modèle et d'estimation des paramètres à partir de données expérimentales de la littérature. Trois situations sont examinées, selon les données à disposition: la distribution des œufs seule, la réponse fonctionnelle seule ou les deux combinées.

Les conclusions principales sont les suivantes: (i) la distribution des œufs est correctement décrite par le modèle lorsque le rapport hôtes/parasitoïdes est suffisamment grand. Le superparasitisme est plus fréquent que prédit par le modèle lorsque le nombre d'hôtes par parasitoïde devient faible. (ii) La tendance à superparasiter n'a que très peu d'effet sur la réponse fonctionnelle. Les données sont donc en général insuffisantes pour estimer les paramètres, en particulier Tp, rendant difficile la qualification d'un parasitoïde comme discriminateur ou non à partir de la réponse fonctionnelle seulement. (iii) Lorsque les deux types de données sont à disposition, il est plus efficace d'ajuster tout d'abord le modèle de distribution des œufs puis, en fonction de la valeur de δ obtenue, d'ajuster le modèle de la réponse fonctionnelle correspondante.


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Copyright information

© Lavoisier Abonnements 1995

Authors and Affiliations

  • R. Arditi
    • 1
    • 2
    • 3
  • O. Glaizot
    • 3
    • 4
  1. 1.Ecologie des populations et communautés, URA 2154Université Paris-Sud XIOrsay CedexFrance
  2. 2.Institut national agronomique Paris-GrignonParis Cedex 05France
  3. 3.Institut de zoologie et d'écologie animaleUniversité de LausanneLausanneSuisse
  4. 4.Biology DepartmentDalhousie UniversityHalifaxCanada

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