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Estimation of Local Mean Population Densities of Japanese Beetle Grubs (Scarabaeidae: Coleoptera)

Dalthorp, D. ; Nyrop, J. ; Villani, M.

In: Environmental Entomology, 1999, vol. 28, no. 2, p. 255-265

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    Title
    • Estimation of Local Mean Population Densities of Japanese Beetle Grubs (Scarabaeidae: Coleoptera)
    Author
    • Dalthorp, D.. Department of Entomology, Cornell University, NYSAES, Geneva, NY 14456
    • Nyrop, J.. Department of Entomology, Cornell University, NYSAES, Geneva, NY 14456
    • Villani, M.. Department of Entomology, Cornell University, NYSAES, Geneva, NY 14456
    Document Type
    • Postprint
    Language
    • English
    Published in
    • Environmental Entomology, 1999, vol. 28, no. 2, p. 255-265. Oxford University Press
    Other Version
    OAI-PMH Identifier
    • oai:doc.rero.ch:303232
    Summary
    Insect populations tend to be patchy in distribution. Even when the mean population density is low, there may be local patches with high densities. As a result, estimates of mean populations may provide little information about the size or intensity of local patches within the sampled area. We compared the following 3 methods of estimating local population densities of insects: (1) with moving averages, a local mean population density is estimated as the mean of samples taken within a given radius of a central point, (2) with inverse distances, local means are estimated as weighted averages of samples; each sample is given a weight proportional to a power of the reciprocal of its distance from the center of the region for which the mean is to be estimated, (3) kriging is a geostatistical algorithm for estimating local means as weighted averages of samples. Weighting is based on the spatial covariance of the samples, or the degree to which samples that are near to each other are related. The first 2 methods are relatively easy to calculate but were unreliable when used with standard parameters to estimate local Japanese beetle grub densities. When an optimum radius was used with moving averages and an optimum exponent was used with inverse distances, the advantage of ease of calculation was lost, yet both methods were still inferior to kriging in providing accurate estimates of local means