Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-13T11:30:26.319Z Has data issue: false hasContentIssue false
  • English
  • Français

DIET, TEMPERATURE, AND THE LOGISTIC MODEL OF DEVELOPMENTAL RATE FOR TRIBOLIUM CONFUSUM (COLEOPTERA: TENEBRIONIDAE)1

Published online by Cambridge University Press:  31 May 2012

R. J. Lamb  and
S. R. Loschiavo
R. J. Lamb
Affiliation:
Research Station, Agriculture Canada, Winnipeg, Manitoba R3T 2M9
S. R. Loschiavo
Affiliation:
Research Station, Agriculture Canada, Winnipeg, Manitoba R3T 2M9
Get access Rights & Permissions [Opens in a new window]

Abstract

The developmental rates of individual larvae of Tribolium confusum Jacquelin duVal were measured at five temperatures on three diets to quantify the interaction between these two environmental factors. No significant differences in survival were detected but developmental times were affected by both factors. A logistic equation accurately described the relationship between mean developmental rate and temperature for each diet. The variance in developmental rate was a linear function of the mean developmental rate, and the mean accounted for more of the differences in variance than diet or temperature.

The effect of diet was greatest at the temperature which caused the highest developmental rate. It decreased as temperature decreased. This effect could be accounted for by varying the coefficient K, the asymptote of the logistic equation. The coefficient K showed a positive linear relationship to the lysine content of the diet. This coefficient may provide a compact and quantitative means of summarizing the interaction of environmental factors such as diet and temperature in the logistic model for the developmental rate of insects.

Résumé

Les taux de développement de larves de Tribolium confusum Jacquelin duVal ont été mesurés à cinq températures et trois rations différentes pour quantifier l’interaction de ces deux facteurs ambiantaux. On n’a décelé aucune différence significative dans la survie, mais les deux facteurs ont influé sur les temps de développement. L’équation logistique décrit avec précision les rapports entre le taux de développement moyen et la température pour chaque ration. La variance du taux de développement est fonction linéaire du taux de développement moyen, et cette moyenne explique davantage les différences de variance que la ration ou la température.

L’effet de la ration est plus marqué à la température qui permet le taux de développement le plus rapide, mais diminue avec la baisse de température. Cet effet pourrait s’expliquer par la variation du coefficient K, l’asymptote de l’équation logistique. Le coefficient montre une corrélation linéaire positive avec la teneur en lysine de la ration. Il pourrait fournir un moyen commode et quantitatif pour résumer l’interaction de facteurs ambiantaux comme la ration et la température dans le cadre du modèle logistique appliqué au taux de développement des insectes.

Type
Articles
Information
The Canadian Entomologist , Volume 113 , Issue 9 , September 1981 , pp. 813 - 818
Copyright
Copyright © Entomological Society of Canada 1981

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andrewartha, H. G. and Birch, L. C.. 1954. The Distribution and Abundance of Animals. University Chicago Press.Google Scholar
Brown, M. B. (Ed.). 1977. BMDP-77 Biomedical Computer Programs. University California Press, Berkeley.Google Scholar
Davidson, J. 1944. On the relationship between temperature and rate of development of insects at constant temperatures. J. Anim. Ecol. 13: 26–38.CrossRefGoogle Scholar
Hardman, J. M. 1976 a. Life table data for use in deterministic and stochastic simulation models predicting the growth of insect populations under malthusian conditions. Can. Ent. 108: 897–906.CrossRefGoogle Scholar
Hardman, J. M. 1976 b. Deterministic and stochastic models simulating the growth of insect populations over a range of temperatures under malthusian conditions. Can. Ent. 108: 907–924.CrossRefGoogle Scholar
Howe, R. W. 1960. The effects of temperature and humidity on the rates of development and the mortality of Tribolium confusum Duval (Coleoptera, Tenebrionidae). Ann. appl. Biol. 48: 363–376.CrossRefGoogle Scholar
Loschiavo, S. R. 1980. An insect bioassay to evaluate feed barley of different lysine content. J. Sci. Food Agric. 31: 351–354.CrossRefGoogle Scholar
Messenger, P. S. 1959. Bioclimatic studies with insects. A. Rev. Ent. 4: 183–206.CrossRefGoogle Scholar
Sokoloff, A. 1974. The Biology of Tribolium. Vol. 2. Clarendon Press, Oxford.Google Scholar
Steel, R. G. D. and Torrie, J. H.. 1960. Principles and Procedures of Statistics. McGraw-Hill, N. Y.Google Scholar
Stinner, R. E., Gutierrez, A. P., and Butler, G. D. Jr. 1974. An algorithm for temperature-dependent growth rate simulation. Can. Ent. 106: 519–524.CrossRefGoogle Scholar