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A SEQUENTIAL SAMPLING PLAN FOR ADULT TUBER FLEA BEETLES (EPITRIX TUBERIS GENTNER): DEALING WITH “EDGE EFFECTS”

Published online by Cambridge University Press:  31 May 2012

Michel Cusson ,
Robert S. Vernon  and
Bernard D. Roitberg
Michel Cusson
Affiliation:
Department of Biological Sciences, Centre for Pest Management, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6
Robert S. Vernon
Affiliation:
Agriculture Canada, Vancouver Research Station, 6660 West Marine Drive, Vancouver, British Columbia, Canada V6T 1X2
Bernard D. Roitberg
Affiliation:
Department of Biological Sciences, Centre for Pest Management, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6
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Abstract

We propose a sequential sampling plan for adult tuber flea beetles, Epitrix tuberis Gent., in potato fields, which is based on a confidence interval calculated around a critical density value (Iwao 1975) and which uses Taylor’s Power Law (Taylor 1961) to estimate the variance. Because of the highly edge-biased gradients of density displayed by this insect, separate sequential expressions have been calculated for densities at the edges and centers of fields.

In a survey of 12 commercial potato fields, spring-generation E. tuberis densities in centers of fields were always far below the threshold level of one beetle per 10 plants employed at the time of sampling. The survey also indicated that fields that have been sown with potatoes for 2 consecutive years have higher beetle densities than fields sown with potatoes for a 1st year. Edge:center density ratios, however, were the same for the two categories of fields.

Résumé

Nous proposons un programme d’échantillonnage séquentiel pour les adultes de l’altise du tubercule, Epitrix tuberis Gent., basé sur l’emploi d’un intervalle de confiance calculé autour d’une valeur critique de densité (Iwao 1975) et utilisant “Taylor's Power Law” (Taylor 1961) pour estimer la variance. En raison des densités d’altises généralement beaucoup plus élevées en bordure qu’au centre des champs, des expressions séquentielles différentes ont été calculées pour ces deux strates d’échantillonnage.

Dans le cadre d’une étude menée dans 12 champs commerciaux de pommes de terre, les densités d’altises de la génération hivernante, au centre des champs, étaient toujours de beaucoup inférieures à la valeur seuil d’une altise par 10 plants utilisée au moment de l’échantillonnage. De cette étude il est aussi ressorti que les champs dans lesquels les pommes de terre sont cultivées pour une 2ème année consécutive ont de plus fortes densités d’altises que ceux dans lesquels les pommes de terre sont cultivées pour une 1ère année. Cependant, les rapports de densité bordurexentre étaient les mêmes pour ces deux catégories de champs.

[Traduit par l’auteur]

Type
Articles
Information
The Canadian Entomologist , Volume 122 , Issue 3 , June 1990 , pp. 537 - 546
Copyright
Copyright © Entomological Society of Canada 1990

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References

Fulton, H.G., Banham, F.L., and Neilson, C.L.. 1955. The tuber flea beetle in British Columbia. Can. Dept. Agric. Ent. Div. Publ. No. 938.Google Scholar
Giles, K.I. 1987. Estimation of an economic threshold for the tuber flea beetle, Epitriẋ tuberis Gentner (Coleoptera: Chrysomelidae), on potato in British Columbia. Master of Pest Management thesis, Dept. of Biological Sciences, Simon Fraser University, Burnaby, B.C., Canada.Google Scholar
Green, R.H. 1970. On fixed precision level sequential sampling. Res. Popul. Ecol. 12: 249–251.CrossRefGoogle Scholar
Iwao, S. 1968. A new regression method for analysing the aggregation pattern of animal populations. Res. Popul. Ecol. 10: 1–20.CrossRefGoogle Scholar
Iwao, S. 1975. A new method of sequential sampling to classify populations relative to a critical density. Res. Popul. Ecol. 16: 281–288.CrossRefGoogle Scholar
Karandinos, M.G. 1976. Optimum sample size and comments on some published formulae. Bull. ent. Soc. Am. 22: 417–421.Google Scholar
Kleinbaum, D.G., and Kupper, L.L.. 1978. Applied regression analysis and other multivariable methods. Duxbury Press, North Scituate. p. 106.Google Scholar
Lloyd, M. 1967. ‘Mean crowding’. J. Anim. Ecol. 36: 1–30.CrossRefGoogle Scholar
Nyrop, J.P., and Simmons, G.A.. 1984. Errors incurred when using Iwao's sequential decision rule in insect sampling. Environ. Ent. 13: 1459–1465.CrossRefGoogle Scholar
Southwood, T.R.E. 1978. Ecological Methods with Special Reference to the Study of Insect Populations. Chapman and Hall, London.Google Scholar
Stern, V.M. 1973. Economic thresholds. A. Rev. Ent. 18: 259–280.CrossRefGoogle Scholar
Taylor, L.R. 1961. Aggregation, variance and the mean. Nature 189: 732–735.CrossRefGoogle Scholar
Taylor, L.R. 1965. A natural law for the spatial disposition of insects. Proc. 12th Int. Congr. Ent., London, 1964. pp. 396–397.Google Scholar
Taylor, L.R. 1971. Aggregation as a species characteristic. Stat. Ecol. 1: 357–377.Google Scholar
Taylor, L.R. 1984. Assessing and interpreting the spatial distributions of insect populations. A. Rev. Ent. 29: 321–357.CrossRefGoogle Scholar
Turgeon, J., and Régnière, J.. 1987. Development of sampling techniques for the spruce budmoth, Zeiraphera canadensis Mut. and Free. (Lepidoptera: Tortricidae). Can. Ent. 119: 239–249.CrossRefGoogle Scholar