Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T07:57:10.118Z Has data issue: false hasContentIssue false

Dispersion patterns and sequential sampling plans for Megalurothrips sjostedti (Trybom) (Thysanoptera: Thripidae) in cowpeas

Published online by Cambridge University Press:  10 July 2009

A. B. Salifu
Affiliation:
Department of Biological Sciences, Wye College, University of London, Ashford, Kent, TN25 5AH, UK
C. J. Hodgson*
Affiliation:
Department of Biological Sciences, Wye College, University of London, Ashford, Kent, TN25 5AH, UK
*
* All correspondence should be sent to the second author in the first instance.

Abstract

The within-plant dispersion characteristics of Megalurothrips sjostedti (Trybom) on cowpeas were determined in studies in Nigeria. Iwao's regression procedure and Taylor's power law analysis were used to determine the relationship between the mean and variance of thrips counts. Both methods showed that adult thrips were randomly distributed within cowpea plants at initial low populations. At later high densities, Iwao's method provided a better fit of the population dispersion of larvae and adults and showed that both were aggregated. The negative binomial best described this aggregation at high population densities. Sequential count plans suitable for pest management surveys were developed using critical stop lines derived from Iwao's regression procedure and Taylor's power law, but the latter was found to require less effort to achieve the same level of precision. There was a functional relationship between the variance and mean of untransformed population counts, and the suitability of transformation functions is discussed.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 1987

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arbous, A. G. & Kerrick, J. E. (1951). Accident statistics and the concept of accident-proneness.—Biometrics 7, 340432.CrossRefGoogle Scholar
Bliss, C. I. & Fisher, R. A. (1953). Fitting the negative binomial distribution to biological data and note on the efficient fitting of the negative binomial.—Biometrics 9, 176200.CrossRefGoogle Scholar
Davies, R. G. (1971). Computer programming in quantitative biology.—462 pp. London, Academic Press.Google Scholar
Green, R. H. (1970). On fixed precision level sequential sampling.—Researches Popul. Ecol. 12, 249251.CrossRefGoogle Scholar
Harcourt, D. G. (1961). Design of a sampling plan for studies on the population dynamics of the diamondback moth, Plutella maculipennis (Curt.) (Lepidoptera: Plutellidae).—Can. Ent. 93, 820831.CrossRefGoogle Scholar
Healy, M. J. R. & Taylor, L. R. (1962). Tables for power-law transformations.—Biometrika 49, 557559.CrossRefGoogle Scholar
Iwao, S. (1968). A new regression method for analysing the aggregation pattern of animal populations.—Researches Popul. Ecol. 10, 120.CrossRefGoogle Scholar
Iwao, S. & 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.—Researches Popul. Ecol. 10, 210214.CrossRefGoogle Scholar
Iwao, S. & Kuno, E. (1971). An approach to the analysis of aggregation pattern in biological populations.—pp. 461513in Patil, G. P., Pielou, E. C. & Waters, W. E. (Eds.). Statistical ecology. Vol. 1.—University Park, Penn. St. Univ. Press.Google Scholar
Kogan, M. & Herzog, D. C. (Eds.) (1980). Sampling methods in soybean entomology.—587 pp. New York, Springer-Verlag.CrossRefGoogle Scholar
Kuno, E. (1969). A new method of sequential sampling to obtain the population estimates with a fixed level of precision.—Researches Popul. Ecol. 11, 127136.CrossRefGoogle Scholar
Latheef, M. A. & Pass, B. C. (1974). Spatial distribution patterns of Hypera postica in Kentucky alfalfa fields.—Environ. Entomol. 3, 866871.CrossRefGoogle Scholar
Lloyd, M. (1967). Mean crowding.—J. Anim. Ecol. 36, 130.CrossRefGoogle Scholar
Salifu, A. B. (1982). Biology of cowpea flower thrips and host plant resistance.—115 pp. M.Sc. Thesis, Univ. Ghana.Google Scholar
Sevacherian, V. & Stern, V. M. (1972). Spatial distribution patterns of lygus bugs in California cotton fields.—Environ. Entomol. 1, 695704.CrossRefGoogle Scholar
Snedecor, G. W. & Cochran, W. G. (1967). Statistical methods.—593 pp. Ames, Iowa St. Univ. Press.Google Scholar
Southwood, T. R. E. (1978). Ecological methods with particular reference to the study of insect populations.—2nd edn, 524 pp. London, Chapman & Hall.Google Scholar
Taylor, L. R. (1961). Aggregation, variance and the mean.—Nature, Lond. 189, 732735.CrossRefGoogle Scholar