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Egg distributions and the information a solitary parasitoid has and uses for its oviposition decisions.
Lia Hemerika*, Nelly van der Hoevenb and J.J.M. van Alphenc
- Department of Mathematical and Statistical Methods, Wageningen University, Dreijenlaan 4, Wageningen 6703 HA, Netherlands
- Department of Theoretical Evolutionary Biology, Leiden University, IEES, P.O. Box 9516, Leiden 2300 RA, Netherlands
- Department of Animal Ecology, Leiden University, IEES, P.O. Box 9516, Leiden 2300 RA, Netherlands
*: Corresponding Author
Summary
Approximately three decades ago the question was first answered "whether parasitoids are able to assess the number or origin of eggs in a host" for a solitary parasitoid, Leptopilina heterotoma, by fitting theoretically derived distributions to empirical ones. We extend the set of different theoretically postulated distributions of eggs among hosts by combining searching modes and abilities in assessing host quality. In the models, parasitoids search either randomly (Poisson) (1) or by vibrotaxis (Negative Binomial) (2). Parasitoids are: (a) assumed to treat all hosts equally, (b) able to distinguish them in unparasitised and parasitised hosts only, (c) able to distinguish them by the number of eggs they contained, or (d) able to recognise their own eggs. Mathematically tractable combinations of searching mode (1 and 2) and abilities (a,b,c,d) result in seven different models (M1a, M1b, M1c, M1d, M2a, M2b and M2c). These models have been simulated for a varying number of searching parasitoids and various mean numbers of eggs per host. Each resulting distribution is fitted to all theoretical models. The model with the minimum Akaike's information criterion (AIC) is chosen as the best fitting for each simulated distribution. We thus investigate the power of the AIC and for each distribution with a specified mean number of eggs per host we derive a frequency distribution for classification. Firstly, we discuss the simulations of models including random search (M1a, M1b, M1c and M1d). For M1a, M1c and M1d the simulated distributions are correctly classified in at least 70% of all cases. However, in a few cases model M1b is only properly classified for intermediate mean values of eggs per host. The models including vibrotaxis as searching behaviour (M2a, M2b and M2c) cannot be distinguished from those with random search if the mean number of eggs per host is low. Among the models incorporating vibrotaxis the three abilities are detected analogously as in models with random search. Experiments with two species of solitary parasitoids (L. heterotoma and Asobara tabida) are conducted. All theoretically postulated distributions are separately fitted to the resulting experimental egg distributions. The AIC criterion is used to choose the best fitting theoretical distribution. For both parasitoid species the frequency distribution of best fitting models for experimental data is compared to the classification of distributions generated by simulations. This leads to the conclusion that both L. heterotoma and A. tabida are able to distinguish between parasitised and unparasitised hosts. For L. heterotoma the results point to an ability to assess the number of eggs in a host, whereas A. tabida does not seem to have this ability. This difference suggests that an egg is more valuable for L. heterotoma than for A. tabida.
keywords: AIC; Akaike's information criterion; Asobara tabida; Avoidance; Egg distribution; Leptopilina heterotoma; Solitary parasitoid; Superparasitism
Acta Biotheoretica 50: 167-188, 2002
Selection from publications of Nelly van der
Hoeven
Is it safe to pool the Blank Control Data with the Solvent Control data? N. van der Hoeven,
Ecotoxicol. Environm. Safety, 73:1480-1483, 2010
Multi-criteria decision analysis of test endpoints for detecting the effects of endocrine active substances in fish full life cycle tests.
M. Crane, M. Gross, P. Matthiessen, G.T. Ankley, S. Axford, P. Bjerregaard, R. Brown, P. Chapman, M. Dorgeloh, M. Galay-Burgos, J. Green, C. Hazlerigg, J. Janssen, K. Lorenzen, J. Parrott, H. Rufli, C. Schäfers, M. Seki, H.C. Stolzenberg, N. van der Hoeven, D. Vethaak, IJ. Winfield, S. Zok & J. Wheeler
Integr Environ Assess Manag., 6: 378-389, 2010
Exposure analysis of bisphenol A in surface water systems in North America and Europe. (PMID:19746705)
G.M. Klecka, C.A. Staples, K.E. Clark, N. van der Hoeven, D.E. Thomas & S.G. Hentges
Environmental Science & Technology, 43: 6145-6150, 2009
The Minimum Significant Difference at the NOEC calculated with a non-parametric test.
Hoeven, N. van der,
In: Proceedings of the 30th Anniversary Meeting of the Netherlands Society of Toxicology, june 2009. p. 122
Calculation of the Minimum Significant Difference at the NOEC using a non-parametric test.
Hoeven, N. van der,
Ecotoxicol. Environm. Safety, 70: 61-66, 2008
Does bisphenol a induce superfeminization in Marisa cornuarietis?
Part I: Intra- and inter-laboratory variability in test endpoints. Forbes, V.E., H. Selck, A. Palmqvist, J. Aufderheide, R. Warbritton, N. Pounds, R. Thompson, N. van der Hoeven & N. Caspers
Ecotoxicol. Environm. Safety, 66: 309-318, 2007
Does bisphenol A induce superfeminization in Marisa cornuarietis?
Part II: Toxicity test results and requirements for statistical
power analyses. Forbes, V.E., J. Aufderheide, R. Warbritton, N. van der Hoeven & N. Caspers
Ecotoxicol. Environm. Safety, 66: 319-325, 2007
Statistical issues in fish life-cycle tests with many endpoints.
Hoeven, N. van der & D.R. Dietrich,
Abstract and poster for SETAC Europe, May 2005, Lille
The probability to select the correct model using likelihood-ratio based criteria in choosing between two nested models of which the more extended one is true.
Hoeven, N. van der,
Journal of Statistical Planning and Inference, 135: 477-486, 2005
Effects of bisphenol A on adult fathead minnow (P. promelas) gonadal histology: a 42-day exposure study.
Dietrich, D.R., J. Wolf, A.R. Brown, J.E. Caunter, N. van der Hoeven & U. Friederich,
Abstract and poster for the Cluster workshop on Ecological relevance of chemically induced endocrine disruption in wildlife. University of Exeter, july 2004.
The Netherlands working group on Statistics and Ecotoxicology: Statistics and Models for Risk Assessment.
Hoeven, N. van der,
In: Proceedings of the Jubilee Annual Meeting of the Netherlands Society of Toxicology, june 2004. p. 114
Current issues in statistics and models for Ecotoxicological Risk Assessment.
Hoeven, N. van der,
Acta Biotheoretica 52: 201-217, 2004
Balancing statistics and ecology: on the lumping of experimental data for model selection.
Hoeven, N. van der, L. Hemerik & P.A. Jansen. In: T.A.C. Reydon & L. Hemerik (Eds): Current themes in Theoretical Biology: A Dutch Perspective. pp 233-265. Springer, Dordrecht, The Netherlands, 2004.
Using marine bioassays to classify the toxicity of Dutch harbour sediments. Stronkhorst, J., C. Schipper, J. Brils, M. Dubbeldam, J. Postma & N. van der Hoeven
Environmental Toxicology and Chemistry, 22: 1535-1547, 2003
What can egg distributions of solitary parasitoids tell us about the information the parasitoid has and uses for its oviposition decisions? Hemerik, L.,N. van der Hoeven &
J. J.M. van Alphen, Acta Biotheoretica, 50: 167-188, 2002
Statistical tests and power analysis for three in-vivo bioassays
to determine the quality of marine sediments. Hoeven, N. van der, B. J. Kater &
J. F. Pieters, Environmetrics 13: 281-293, 2002
Significance tables for the exact variance test for the Poisson
distribution with alternative underdispersion. N. van der Hoeven & L Hemerik,
Environmental and Ecological Statistics 9: 201-213, 2002
Estimating the 5-percentile of the species sensitivity
distribution without any assumptions about the distribution. N. van der Hoeven,
Ecotoxicology 10: 25-34, 2001
Power analysis for the NOEC: What is the probability to detect
small toxic effects on three different species using the appropriate standardized test
protocols? N. van der Hoeven, Ecotoxicology 7: 355-361, 1998
The acute toxicity of selected alkylphenols on young and adult
Daphnia magna. A.A.M. Gerritsen, N. van der Hoeven & A. Pielaat,
Ecotoxicol. Environm. Safety 39: 227-232. 1998
The ecotoxicity and the biodegradability of lactic acid, alkyl
lactate esters and lactic acid salts. C.T. Bowmer, R.N. Hooftman, A.O. Hanstveit,
P.W.M. Venderbosch & N. van der Hoeven, Chemosphere 37:
1317-1333, 1998
How to measure no effect? Part I: Towards a new measure of
chronic toxicity in ecotoxicology. Introduction and workshop results. N. van der Hoeven,
F. Noppert & A. Leopold, Environmetrics 8: 241-248, 1997
How to measure no effect? Part III: Statistical aspects of
NOEC, ECx and NEC estimates. N. van der Hoeven, Environmetrics 8: 255-261, 1997
The effect of chlorpyrifos on individuals of Daphnia
pulex in laboratory and field. N. van der Hoeven & A.A.M. Gerritsen,
Environm. Toxicol. Chem. 16: 2438-2447, 1997
A model based on soil structural aspects describing the fate of
genetically modified bacteria in soil. N. van der Hoeven & J.D. van Elsas,
Ecological Modelling 89: 161-173, 1996
Competition between cohorts of juvenile Daphnia
magna. E.L. Enserink, N. van der Hoeven, M. Smith, M. van der Klis & M.A.
van der Gaag, Archiv für Hydrobiologie 136: 433-454, 1996
Reliability of quantitative toxicity test results: from
experimental control to data processing. Enserink, E.L. & N. van der Hoeven,
The Science of the Total Environment, suppl. 1993, Proceedings of the Second
European Conference on Ecotoxicology, eds. W. Slooff & H. de Kruijf, p. 699-704,
1993
LC50 estimates and their confidence intervals. The case that
only one test concentration has partial effect. N. van der Hoeven, Water
Research 25: 401-408, 1991
Effects of toxicants on individuals and populations of Daphnia,
a simulation study. N. van der Hoeven, Comparative Biochemistry and
Physiology 100C: 283-286, 1991
Effect of 3,4-dichloroaniline and metavanadate on Daphnia
populations. N. van der Hoeven, Ecotoxicology and Environmental Safety
20: 53-70, 1990
Salmonella test: Relation between mutagenicity and number of
revertant colonies. N. van der Hoeven, S.A.L.M. Kooijman & W.K. de Raat,
Mutation Research 234: 289-302, 1990
Superparasitism as an ESS: to reject or not to reject, that is
the question. N. van der Hoeven & L. Hemerik, J. of Theoretical Biology
146: 467-482, 1990
Population consequences of a physiological model for individual
development S.A.L.M. Kooijman, N. van der Hoeven & D.C. van der Werf,
Functional Ecology 3: 325-336, 1989
Oscillations in Daphnia populations. N. van der
Hoeven, A.M. de Roos & S.A.L.M. Kooijman, Econieuws 2, 7-8,
1989
The population dynamics of Daphnia at constant food supply: a
review, re-evaluation and analysis of experimental series from the literature. N. van
der Hoeven, Netherlands Journal of Zoology 39: 126-155, 1989
Random elements in a population model based on individual
development. N. van der Hoeven, in: Ecodynamics, Proc. Int. Workshop at Jülich,
FRG, 19-20 Oct. 1987. Eds. W. Wolff, C.J. Soeder & F.R. Drepper, pp 333-342,
Research Notes in Physics, Springer Verlag., 1988
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