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RELATIONSHIPS BETWEEN SPRUCE BUDWORM (LEPIDOPTERA: TORTRICIDAE) EGG MASS DENSITY AND RESULTANT DEFOLIATION OF BALSAM FIR AND WHITE SPRUCE1

Published online by Cambridge University Press:  31 May 2012

T.J. Lysyk
Affiliation:
Agriculture Canada Research Station, Lethbridge, Alberta, Canada T1J 4B1

Abstract

Annual spruce budworm, Choristoneura fumiferana (Clemens), survey data were subjected to multiple and logistic regression analyses to examine the relationship between egg mass density in the fall and resultant defoliation the next season. Egg mass density was the most important variable associated with resultant defoliation, followed by current defoliation, regional population trends, host species, and sprays. Together, these accounted for 60% of the variation in resultant defoliation. Balsam fir [Abies balsamea (L.) Miller] suffered greater levels of defoliation than white spruce [Picea glauca (Moench) Voss] at a given egg mass density. Resultant defoliation of balsam fir also showed a steeper response to egg mass density than resultant defoliation of white spruce. Levels of current defoliation increased susceptibility to defoliation in a similar manner between species, as did regional population trends. Sprays were more effective at reducing resultant defoliation on balsam fir than on white spruce but, overall, did not confer a high level of foliage protection. Predictions of resultant defoliation using the multiple regression models had confidence limits averaging 75%, which are too large to be useful for predictive purposes. The logistic regression equations could be used to predict the probability of a stand receiving light or severe defoliation.

Résumé

Des données de relevés annuels des populations de la tordeuse des bourgeons de l’épinette, Choristoneura fumiferana (Clemens), ont été soumises à des analyses de régressions multiple et logistique afin d’examiner la relation entre la densité des masses d’oeufs à l’automne et la défeuillaison qui en résulte l’année suivante. La densité des masses d’oeufs a été la plus importante variable associée à la défeuillaison, suivie par la défeuillaison de l’année courante, les tendances régionales des niveaux de population, l’espèce de plante hôte et les arrosages. Mises ensemble, ces variables ont expliqué 60% de la variation dans la défeuillaison. Le sapin baumier [Abies balsamea (L.) Miller] a subi des niveaux de défeuillaison plus élevés que l’épinette blanche [Picea glauca (Moench) Voss] à une densité d’oeufs donnée. Le sapin baumier a répondu de façon plus abrupte, en terme de défeuillaison, à la densité des masses d’oeufs, que l’épinette blanche. Les niveaux de défeuillaison de l’années courante, ainsi que les tendances régionales des niveaux de population, ont augmenté la susceptibilité à la défeuillaison de façon semblable pour les deux espèces. Les arrosages ont été plus efficaces dans la réduction de la défeuillaison du sapin baumier que de l’épinette blanche, mais dans l’ensemble, n’ont pas offert un haut niveau de protection au feuillage. Les prédictions des défeuillaisons, utilisant des models de régression multiple, avaient des intervalles de confiance d’en moyenne 75%, ce qui est trop élevé pour rendre ce type de prédiction utile. Les équations de régression logistique pourraient être utilisées pour prédire la probabilité qu’un peuplement sera sujet à une défeuillaison légère ou sévère.

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1990

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References

Dorais, L.F., and Kettela, E.G.. 1982. A review of entomological survey and assessment techniques used in regional spruce budworm, Choristoneura fumiferana (Clem.), surveys and in the assessment of operational spray programs. Report of Committee for Standardization of Survey and Assessment Techniques, Eastern Spruce Budworm Council, Quebec City, P.Q.43 pp.Google Scholar
Fleming, R.A., Shoemaker, C.A., and Stedinger, J.R. 1984. An assessment of the impact of large scale spraying operations on the regional dynamics of spruce budworm (Lepidoptera: Tortricidae) populations. Can. Ent. 116: 633644.CrossRefGoogle Scholar
Gujarati, D. 1970 a. Use of dummy variables in testing for equality between sets of coefficients in two linear regressions: a note. Am. Statistician 24: 5052.Google Scholar
Gujarati, D. 1970 b. Use of dummy variables in testing for equality between sets of coefficients in linear regressions: a generalization. Am. Statistician 24: 1822.Google Scholar
Koller, C.N., and Leonard, D.E.. 1981. Comparison of energy budgets for spruce budworm Choristoneura fumiferana (Clemens) on balsam fir and white spruce. Oecologia 49: 1420.CrossRefGoogle Scholar
Lysyk, T.J., and Sanders, C.J.. 1987. A method for sampling endemic populations of the spruce budworm (Lepidoptera: Tortricidae) based on proportion of empty sample units. Great Lakes For. Cent. Inf. Rep. O-X-382. 17 pp.Google Scholar
Morris, R.F. 1954. A sequential sampling technique for spruce budworm egg surveys. Can. J. Zool. 32: 302313.CrossRefGoogle Scholar
Morris, R.F. 1955. The development of sampling techniques for forest insect defoliators, with particular reference to the spruce budworm. Can. J. Zool. 33: 225294.CrossRefGoogle Scholar
Régnière, J., Lysyk, T.J., and Auger, M.. 1989. Population density estimation of spruce budworm, Choristoneura fumiferana (Clem.) (Lepidoptera: Tortricidae) on balsam fir and white spruce from 45-cm mid-crown branch tips. Can. Ent. 121: 267281.CrossRefGoogle Scholar
Royama, T. 1984. Population dynamics of the spruce budworm Choristoneura fumiferana. Ecol. Monogr. 54: 429462.CrossRefGoogle Scholar
Sanders, C.J. 1980. A summary of current techniques used for sampling spruce budworm populations and estimating defoliation in eastern Canada. Great Lakes For. Cent. Inf. Rep. O-X-306. 33 pp.Google Scholar
SAS Institute Inc. 1985. SAS User's Guide: Statistics, Version 5. SAS Institute Inc., Cary, NC. 965 pp.Google Scholar
SAS Institute Inc. 1986. SUGI Supplemental Library User's Guide, Version 5 edition. SAS Institute Inc., Cary, NC. 662 pp.Google Scholar
Webb, F.E., Cameron, D.G., and MacDonald, D.R.. 1956. Studies of aerial spraying against the spruce budworm in New Brunswick. V. Techniques for large-scale egg and defoliation surveys 1953–55. Interim Report 1955-8 Forest Biology Laboratory, Fredericton, N.B.Google Scholar