Regression Estimators for Late-Instar Gypsy Moth Larvae at Low Population Densities

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Abstract:

Two regression estimators were developed for determining densities of late-instar gypsy moth, Lymantria dispar (Lepidoptera: Lymantriidae), larvae from burlap band and pyrethrin spray counts on oak trees in Vermont, Massachusetts, Connecticut, and New York. Studies were conducted by marking larvae on individual burlap-banded trees within 15-m diameter plots and recapturing them with pyrethrin sprays to tree crowns at night. Both estimators are based on data that are relatively easy and inexpensive to gather in the field. The estimator for individual trees may be useful in determining relative densities, but the plot estimator, which had an R² of 0.99, can be used with a high degree of confidence for determining absolute densities in plots containing several oak trees. Validation of the plot density estimator at five sites in Maryland demonstrated its utility for sampling late-instar gypsy moth. Both estimators were valid only when previous years' egg-mass densities were ≤75/ha and decreased in efficiency when prior year egg masses were ≥495/ha. These estimates are best suited for density estimates in sparse or building gypsy moth populations in which other procedures are especially difficult to use or evaluate. For. Sci. 35(3):789-800.

Keywords: Sampling; burlap bands; density estimates; late-instar larvae

Document Type: Journal Article

Affiliations: Mathematical Statistician, USDA Forest Service, Southeastern Forest Experiment Station, Carlton Street, Athens, GA 30602

Publication date: September 1, 1989

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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