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SAMPLING PLANS FOR ESTIMATING ACHENE DAMAGE BY THE RED SUNFLOWER SEED WEEVIL (COLEOPTERA: CURCULIONIDAE)

Published online by Cambridge University Press:  31 May 2012

Chengwang Peng
Affiliation:
Department of Entomology, North Dakota State University, Fargo, North Dakota, USA 58105
Gary J. Brewer
Affiliation:
Department of Entomology, North Dakota State University, Fargo, North Dakota, USA 58105

Abstract

A sampling plan for the estimation of the number of achenes damaged by the red sunflower seed weevil, Smicronyx fulvus LeConte, is useful in evaluating the efficiency of weevil management strategies. The objective of this study was to determine the distribution pattern of the damaged achenes that would allow the development of a fixed-sample-size plan for estimation of the damaged achenes. Taylor’s power law and Iwao’s patchiness regression were used to analyze the distribution pattern of the damaged achenes. Slopes from both models were >1, indicating an aggregated spatial pattern. The intercepts and slopes from both models were used to calculate the minimal mean number of damaged achenes per sunflower head that can be estimated for a given sample size and precision level. If the mean number of damaged achenes per head is low (<20), the plan developed using the parameters of Taylor’s power law requires significantly more samples than the plan using the parameters of Iwao’s patchiness regression to estimate the same density of damaged achenes. If the mean number of damaged achenes per head is high (>30), the two plans give similar results. If both low and high damage situations are considered, Taylor’s plan is preferred to Iwao’s plan. At the 0.10 precision level, Taylor’s plan requires approximately 40 samples (heads) to estimate a mean of about 200 damaged achenes per head (≈ current economic injury level).

Résumé

L’élaboration d’un plan d’échantillonnage propre à estimer le nombre d’akènes endommagés par le charançon du tournesol Smicronyx fulvus LeConte peut s’avérer très utile dans l’évaluation de l’efficacité des stratégies de lutte contre l’insecte. Nous avons tenté de déterminer quel type de répartition des akènes endommagés pourrait le mieux nous aider à mettre au point un plan d’échantillonnage à échantillon de taille fixe permettant l’estimation du nombre d’akènes endommagés. La loi de Taylor et la régression de contagion d’Iwao ont été utilisées pour analyser le type de répartition des akènes endommagés. Les pentes des deux modèles étaient >1, ce qui reflète une répartition spatiale contagieuse. Les intersects et les pentes des deux modèles ont ensuite servi à calculer le nombre moyen minimal d’akènes endommagés par inflorescence qui puisse être estimé pour un échantillon de taille donnée à un niveau de précision donné. Si le nombre moyen d’akènes endommagés par inflorescence est faible (<20), le plan élaboré à partir des paramètres de la loi de Taylor demande un nombre plus grand d’échantillons que le plan élaboré à partir de la régression d’Iwao pour aboutir à la même densité d’akènes endommagés. Si le nombre moyen d’akènes endommagés par inflorescence est élevé (>30), les deux plan aboutissent aux mêmes résultats. Dans les cas où les deux situations sont prises en considération, le plan de Taylor est préférable à celui d’Iwao. À un niveau de précision de 0,10, le plan de Taylor nécessite environ 40 échantillons (inflorescences) pour estimer une moyenne d’environ 200 akènes endommagés par inflorescence (à peu près le seuil économique courant).

[Traduit par la Rédaction]

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1995

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References

Boivin, G., and Vincent, C.. 1983. Sequential Sampling for Pest Control Programs. Project No. 923. Research Branch, Agriculture Canada, Saint-Jean-sur-Richelieu. 29 pp.CrossRefGoogle Scholar
Charlet, L.D., and Oseto, C.Y.. 1982. Spatial pattern of Smicronyx fulvus (Coleoptera: Curculionidae) in cultivated sunflower, based on damage assessment. Journal of the Kansas Entomological Society 55: 351353.Google Scholar
Iwao, S. 1968. A new regression method for analyzing the aggregation pattern of animal populations. Research on Population Ecology 10: 120.CrossRefGoogle Scholar
Karandinos, M.G. 1976. Optimal sample size and comments on some published formulae. Bulletin of the Entomological Society of America 22: 417421.CrossRefGoogle Scholar
Lloyd, M. 1967. Mean crowding. Journal of Animal Ecology 36: 130.CrossRefGoogle Scholar
Oseto, C.Y., and Braness, G.A.. 1979. Bionomics of Smicronyx fulvus (Coleoptera: Curculionidae) on cultivated sunflower, Helianthus annuus. Annals of the Entomological Society of America 72: 534–528.CrossRefGoogle Scholar
Oseto, C.Y., and Braness, G.A.. 1980. Chemical control and bioeconomics of Smicronyx fulvus on cultivated sunflower in North Dakota. Journal of Economic Entomology 73: 218220.CrossRefGoogle Scholar
Oseto, C.Y., and Korman, A.K.. 1986. Sunflower development and achene damage caused by seed weevil, Smicronyx fulvus (Coleoptera: Curculionidae). Journal of Economic Entomology 79: 355358.CrossRefGoogle Scholar
Peng, C., and Brewer, G.J.. 1994. Spatial distribution of the red sunflower seed weevil (Coleoptera: Curculionidae) on sunflower. Environmental Entomology 23: 11011105.CrossRefGoogle Scholar
SAS Institute. 1987. SAS User's Guide: Statistics. SAS Institute, Cary, NC.Google Scholar
Schneiter, A.J., and Miller, J.F.. 1981. Description of sunflower growth stages. Crop Science 21: 901903.CrossRefGoogle Scholar
Sokal, R.R., and Rohlf, F.J.. 1981. Biometry, 2nd ed. Freeman, San Francisco, CA. 859 pp.Google Scholar
Southwood, T.R.E. 1978. Ecological Methods with Particular Reference to the Study of Insect Populations, 2nd ed. Wiley, New York, NY. 524 pp.Google Scholar
Taylor, L.R. 1961. Aggregation, variance and the mean. Nature 189: 732735.CrossRefGoogle Scholar
Taylor, L.R. 1984. Assessing and interpreting the spatial distributions of insect populations. Annual Review of Entomology 29: 321357.CrossRefGoogle Scholar
Xu, R., Chao, C., and van Lenteren, J.C.. 1993. The parasite–host relationship between Encarsia formosa Gahan (Gym., Aphelinidae) and Trialeurodes vaporariorum (Westwood) (Hom., Aleyrodidae), XXIII. Application of different sampling methods on spatially stabilized whitefly adult populations. Journal of Applied Entomology 116: 199211.Google Scholar