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SEQUENTIAL SAMPLING OF ADULT NORTHERN AND WESTERN CORN ROOTWORMS (COLEOPTERA: CHRYSOMELIDAE) IN SOUTHERN ONTARIO

Published online by Cambridge University Press:  31 May 2012

H.J. McAuslane ,
C.R. Ellis  and
O.B. Allen
H.J. McAuslane
Affiliation:
Department of Environmental Biology, University of Guelph, Guelph, Ontario, Canada N1G 2W1
C.R. Ellis
Affiliation:
Department of Environmental Biology, University of Guelph, Guelph, Ontario, Canada N1G 2W1
O.B. Allen
Affiliation:
Departments of Animal and Poultry Science, and Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada N1G 2W1
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Abstract

Three sequential-sampling plans were developed for adult Diabrotica barberi Smith and Lawrence and D. virgifera virgifera LeConte in field corn in southern Ontario. The distribution of both species was well approximated by the negative binomial distribution and obeyed Taylor’s power law. Two plans, following the methods of Kuno (1969) and Green (1970), estimated populations with predetermined precision. The third plan, based on Wald’s (1947) sequential probability ratio test, categorized populations relative to an economic threshold. Different sequential-sampling plans were constructed for 1st-year fields and for all other fields because the parameter k, measuring the extent of aggregation of the beetles, differed between these two classes of fields. Decision equations for Wald’s plan in 1st-year fields were: D1 = 0.98n − 17.75 and D2 = 0.98n + 13.82. Decision equations for 2nd-year or older fields were: D1 = 0.99n − 13.42 and D2 = 0.99n + 10.45. The use of Wald’s plan reduced the required sample size by 55% in 1st-year fields, and by 48% in all other fields. The savings associated with the other sequential-sampling plans were not significant.

Résumé

Trois plans d’échantillonnage séquentiel ont été développés pour estimer les populations adultes de Diabrotica barberi Smith et Lawrence et D. virgifera virgifera LeConte, retrouvées dans le maïs fourrage du sud de l’Ontario. La distribution négative binomiale a bien approximé les distributions de ces deux espèces. Ces deux distributions obéissaient aussi à la loi de puissance de Taylor. Deux plans, suivant les méthodes de Kuno (1969) et de Green (1970), estimaient les populations avec des niveaux de précision pré-determinées. Le troisième plan, basé sur Wald (1947), catégorisait les populations relativement au seuil économique. Des plans différents ont été développé pour les champs de 1 an et pour les autres champs plus âgés parce que le paramètre k, qui mesure l’aggrégation des coléoptères, différait entre ces deux catégories de champs. Les équations de décision du plan de Wald pour les champs de 1 an étaient:D1 = 0,98n − 17,75 et D2 = 0,98n + 13,82. Les équations pour les champs plus âgés étaient:D1 = 0,99n − 13,42 et D2 = 0,99n + 10,45. L’usage du plan de Wald a réduit le nombre d’échantillons requis de 55% pour les champs de 1 an, et de 48% pour les autres champs. Les épargnes associées avec les deux autres plans d’échantillonnage séquentiel n’étaient pas significatives.

Type
Articles
Information
The Canadian Entomologist , Volume 119 , Issue 6 , June 1987 , pp. 577 - 585
Copyright
Copyright © Entomological Society of Canada 1987

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References

Anonymous. 1985. Field Crop Recommendations. Ont. Min. Agric. Food Publ. 296.Google Scholar
Bliss, C.I., and Owen, A.R.G.. 1958. Negative binomial distributions with a common k. Biometrika 45: 37–58.CrossRefGoogle Scholar
Fisher, J.R. 1985. Comparison of controlled infestations of Diabrotica virgifera virgifera and Diabrotica barberi (Coleoptera: Chrysomelidae) on corn. J. econ. Ent. 78: 1406–1408.CrossRefGoogle Scholar
Foster, R.E., Tollefson, J.J., and Steffey, K.L.. 1982. Sequential sampling plans for adult corn rootworms (Coleoptera: Chrysomelidae). J. econ. Ent. 75: 791–793.CrossRefGoogle Scholar
Green, R.H. 1970. On fixed precision level sequential sampling. Res. Popul. Ecol. (Kyoto) 12: 249–251.CrossRefGoogle Scholar
Iwao, S. 1975. A new method of sequential sampling to classify populations relative to a critical density. Res. Popul. Ecol. (Kyoto) 16: 281–288.CrossRefGoogle Scholar
Iwao, S., and Kuno, E.. 1968. Use of the regression of mean crowding on mean density for estimating sample size and the transformation of data for the analysis of variance. Res. Popul. Ecol. (Kyoto) 10: 210–214.CrossRefGoogle Scholar
Karandinos, M.G. 1976. Optimum sample size and comments on some published formulae. Bull. ent. Soc. Am. 22: 417–421.Google Scholar
Kuno, E. 1969. A new method of sequential sampling to obtain the population estimates with a fixed level of precision. Res. Popul. Ecol. (Kyoto) 11: 127–136.CrossRefGoogle Scholar
Sawyer, A.J. 1985. Efficient monitoring of the density of adult northern corn rootworm (Coleoptera: Chrysomelidae) in field corn. Can. Ent. 117: 171–183.CrossRefGoogle Scholar
Stamm, D.E., Mayo, ZB, Campbell, J.B., Witkowski, J.F., Andersen, L.W., and Kozub, R.. 1985. Western corn rootworm (Coleoptera: Chrysomelidae) beetle counts as a means of making larval control recommendations in Nebraska. J. econ. Ent. 78: 794–798.CrossRefGoogle Scholar
Steffey, K.L., and Tollefson, J.J.. 1982. Spatial dispersion patterns of northern and western corn rootworm adults in Iowa cornfields. Environ. Ent. 11: 283–286.CrossRefGoogle Scholar
Taylor, L.R. 1961. Aggregation, variance and the mean. Nature 189: 732–735.CrossRefGoogle Scholar
Taylor, L.R. 1984. Assessing and interpreting the spatial distributions of insect populations. A. Rev. Ent. 29: 321–357.CrossRefGoogle Scholar
Taylor, L.R., Woiwod, I.P., and Perry, J.N.. 1978. The density-dependence of spatial behavior and the rarity of randomness. J. anim. Ecol. 47: 383–406.CrossRefGoogle Scholar
Wald, A. 1947. Sequential analysis. John Wiley and Sons, New York. 212 pp. (Reprinted Dover Publ. Inc., New York, 1973.) (Original reference not seen.)Google Scholar
Waters, W.E. 1955. Sequential sampling in forest insect surveys. For. Sci. 1: 68–79.Google Scholar
Willson, L.J., and Folks, J.L.. 1983. Sequential estimation of the mean of the negative binomial distribution. Biometrics 40: 109–117.CrossRefGoogle Scholar