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A DISTRIBUTION MODEL FOR EGG DEVELOPMENT IN MOUNTAIN PINE BEETLE

Published online by Cambridge University Press:  31 May 2012

J.A. Logan
Affiliation:
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, USA 80523
G.D. Amman
Affiliation:
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, USA 80523

Abstract

Mountain pine beetle (Dendroctonus ponderosae Hopkins) population dynamics, as well as potential for outbreaks and resulting tree mortality, are related in part to habitat temperature. As a first step in development of a life-stage, event-oriented simulation model, we have modeled the temperature-dependent development of the egg stage. The completed model includes a full description of variation in developmental rates and is capable of predicting duration and eclosion patterns for any temperature regime. This model was parameterized using data obtained from constant-temperature experiments at temperatures of 8, 10, 12.5, 15, 20, 25, and 30°C. Validation experiments were conducted for constant temperatures of 15, 17.5, 22.5, and 27.5°C and for variable-temperature regimes of 15±5 and 15±10°C. Validation results indicated that the model is capable of accurately describing the emergence curve for constant temperatures below 27.5°C. The model also faithfully represents emergence under variable temperatures of 15 ± 10°C. Potential reasons for lack of model fidelity in describing emergence at constant high temperatures and for 15 ± 5°C are discussed in the text.

Résumé

La dynamique des populations du dendroctone du pin ponderosa (Dendroctonus ponderosae Hopkins), de même que son potentiel épidémique et la mortalité des arbres qui en résulte, sont en partie dépendants de la température de l’habitat. Comme première étape dans le but d’élaborer un modèle de simulation du développement des stades, nous avons modélisé la relation entre le développement du stade oeuf et la température. Le modèle intégral comprend une description de la variation du taux de développement et peut prédire la durée et la courbe d’éclosion pour tout régime de température. Les paramètres du modèle ont été obtenus à partir d’expériences à température constante aux températures de 8, 10, 12,5, 15, 20, 25 et 30°C. Des tests de validation ont été effectués à 15, 17,5, 22,5 et 27,5°C et sous des régimes de température variable de 15 ± 5 et 15 ± 10°C. Les résultats de la validation indiquent que le modèle peut précisément prédire la courbe d’émergence à des températures constantes sous 27,5°C. Le modèle prévoit aussi fidèlement l’émergence à des températures variables de 15 ± 10°C. On discute des raisons possibles du manque de précision du modèle lorsqu’il s’agit de prédire l’émergence à des températures constantes plus élevées, et pour les régimes de 15 ± 5°C.

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1986

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References

Amman, G.D. 1973. Population changes of the mountain pine beetle in relation to elevation. Environ. Ent. 2: 541547.CrossRefGoogle Scholar
Amman, G.D., and Cole, W.E.. 1983. Mountain pine beetle dynamics in lodgepole pine forests. Part II. population dynamics. USDA For. Serv. Gen. Tech. Rep. INT-145. 59 pp.Google Scholar
Barfield, C.S., Sharpe, P.J.H., and Bottrell, D.G.. 1977. A temperature-driven developmental model for the parasite Bracon mellitor (Hymenoptera: Braconidae). Can. Ent. 109: 15031514.CrossRefGoogle Scholar
Berryman, A.A. 1976. Theoretical explanation of mountain pine beetle dynamics in lodgepole pine forests. Environ. Ent. 5: 12251233.CrossRefGoogle Scholar
Berryman, A.A., Amman, G.D., and Stark, R.W. (Tech. Eds.). 1978. Theory and practice of mountain pine beetle management in lodgepole pine forests. Symp. Proc., Forest, Wildlife and Range Exp. Stn., University of Idaho, Moscow. 224 pp.Google Scholar
Cole, W.E. 1981. Some risks and causes of mortality in mountain pine beetle populations: A long-term analysis. Res. Popul. Ecol. 23: 116144.CrossRefGoogle Scholar
Cole, W.E., and Amman, G.D.. 1980. Mountain pine beetle dynamics in lodgepole pine forests. Part I. Course of an infestation. USDA For. Serv. Gen. Tech. Rep. INT-89. 56 pp.Google Scholar
Cole, W.E., Amman, G.D., and Jensen, C.E.. 1976. Mathematical models for the mountain pine beetle – lodgepole pine interaction. Environ. Ent. 5: 1119.CrossRefGoogle Scholar
Ferro, D.N., Logan, J.A., Voss, R.H., and Elkinton, J.S.. 1985. Colorado potato beetle (Coleoptera: Chrysomelidae) temperature-dependent growth and feeding rates. Environ. Ent. 14: 343348.CrossRefGoogle Scholar
Furniss, R.L., and Carolin, U.M.. 1977. Insects of western forests. USDA For. Serv. Misc. Publ. 1339. 365 pp.Google Scholar
Hilbert, D.W., and Logan, J.A.. 1983 a. An empirical model of nymphal development for the migratory grasshopper (Melanoplus sanguinipes). Environ. Ent. 12: 15.CrossRefGoogle Scholar
Hilbert, D.W., and Logan, J.A.. 1983 b. Nonlinear models and temperature-dependent development in arthropods — a reply to Dr. Jerome A. Onsager. Environ. Ent. 12: i.Google Scholar
Kaufmann, O. 1932. Einige Bemerkungen über den Einfluss von Temperaturschwankungen auf die Entwicklungsdauer und Streuung bei Insekten und seine graphische Darstellung durch Kettenlinie und Hyperbel. Z. Morphol. Ökol. Tiere. 25: 354361.CrossRefGoogle Scholar
Logan, J.A., Wollkind, D.J., Hoyt, S.C., and Tanigoshi, L.K.. 1976. An analytic model for description of temperature-dependent rate phenomena in arthropods. Environ. Ent. 5: 11301140.CrossRefGoogle Scholar
Lyon, R.L. 1958. A useful secondary sex character in Dendroctonus bark beetles. Can. Ent. 90: 582584.CrossRefGoogle Scholar
Onsager, J.A. 1983. Comments on “empirical model of nymphal development for the migratory grasshopper, Melanoplus sanguinipes (Orthoptera: Acrididae).” Environ. Ent. 12: v–vi.CrossRefGoogle Scholar
Powell, J.M. 1967. A study of habitat temperatures of the bark beetle, Dendroctonus ponderosae Hopkins, in lodgepole pine. Agric. Meterol. 4: 189201.CrossRefGoogle Scholar
Regniere, J. 1984. A method of describing and using the variability in development rates for the simulation of insect phenology., Can. Ent. 116: 13671376.CrossRefGoogle Scholar
Safranyik, L. 1978. Effects of climate and weather on mountain pine beetle populations. pp 77–84 in Berryman, A.A., Amman, G.D., and Stark, R.W. (Tech. Eds.), Theory and Practice of Mountain Pine Beetle Management in Lodgepole Pine Forests. Symp. Proc., Forest, Wildlife and Range Exp. Stn., University of Idaho, Moscow. 224 pp.Google Scholar
Safranyik, L., Shrimpton, D.M., and Whitney, H.S.. 1974. Management of lodgepole pine to reduce losses from the mountain pine beetle. Dept. Environ., Can. For. Serv., Pacific For. Res. Centre, Tech. Rep. 1. 24 pp.Google Scholar
Sharpe, P.J.H., Curry, G.L., DeMichele, D.W., and Cole, C.L.. 1977. Distribution model of organisms development times. J. Theor. Biol. 66: 2128.CrossRefGoogle ScholarPubMed
Sharpe, P.J.H., and DeMichele, D.W.. 1977. Reaction kinetics of poikilotherm development. J. Theor. Biol. 64: 649670.CrossRefGoogle ScholarPubMed
Stinner, R.E., Butler, G.D., Bacheler, J.S., and Tuttle, C.. 1975. Simulation of temperature-dependent development in population dynamics models. Can. Ent. 197: 11671244.CrossRefGoogle Scholar
Swartzman, G. 1979. Evaluation of ecological simulation models. pp. 295318in Patil, P., and Rosenzweig, M. (Eds.), Contemporary Quantitative Ecology and Related Economerics. Int. Co-op. Publ. House, Fairland, MD.Google Scholar
Tanigoshi, L.K., and Logan, J.A.. 1979. Tetranychid development under variable temperature regimes. pp. 165175in Rodriquez, J.G., (Ed.), Recent Advances in Acarology, Vol. 1. Academic Press, New York.CrossRefGoogle Scholar
Thomson, A.J., and Shrimpton, D.M.. 1984. Weather associated with the start of mountain pine beetle outbreaks. Can. J. For. Res. 14: 55258.CrossRefGoogle Scholar
Wagner, T.L., Wu, H., Sharpe, P.J.H., and Coulson, R.N.. 1984. Modeling distributions of insect development time: A literature review and application of the Weibull function. Ann. ent. Soc. Am. 77: 475483.CrossRefGoogle Scholar
Wexler, A., and Hasegawa, S.. 1954. Relative humidity – temperature relationships of some saturated salt solutions in the temperature range 0° to 50°C. J. Res. Natl. Bur. Stand. 53: 1926.CrossRefGoogle Scholar