Hostname: page-component-848d4c4894-8kt4b Total loading time: 0 Render date: 2024-07-08T00:02:44.377Z Has data issue: false hasContentIssue false

DEVELOPMENT AND VALIDATION OF A FIXED-PRECISION SEQUENTIAL SAMPLING PLAN FOR ESTIMATING BROOD ADULT DENSITY OF DENDROCTONVS PSEUDOTSUGAE (COLEOPTERA: SCOLYTIDAE)

Published online by Cambridge University Press:  31 May 2012

José F. Negrón*
Affiliation:
Rocky Mountain Research Station, USDA Forest Service, 240 W. Prospect, Fort Collins, Colorado, USA 80526
Willis C. Schaupp
Affiliation:
Forest Health Management, Lakewood Service Center, USDA Forest Service, P.O. Box 25127, Lakewood, Colorado, USA 80225
Erik Johnson
Affiliation:
Forest Health Management, Lakewood Service Center, USDA Forest Service, P.O. Box 25127, Lakewood, Colorado, USA 80225
*
1 Author to whom all corresponding should be addressed (E-mail: [email protected]).

Abstract

The Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, attacks Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco (Pinaceae), throughout western North America. Periodic outbreaks cause increased mortality of its host. Land managers and forest health specialists often need to determine population trends of this insect. Bark samples were obtained from 326 trees distributed over 21 stands during a 2-year period in late winter to early spring of 1997 and 1998 in the Colorado Front Range. The variance to mean relationship of brood adults was examined using the Taylor power law, and a fixed-precision sampling plan was developed using Green’s method. Stop lines and minimum number of samples required to estimate brood adult density per 0.046 m2 with precision levels of 0.1, 0.2, and 0.3 were calculated. A resampling simulation conducted with an independent data set indicated that desired precision levels were not met. Theoretical precision levels were adjusted until desired precision levels were achieved. Average number of samples needed to estimate brood adult densities up to 25.1 adults per 0.046 m2 with precision levels of 0.09, 0.2, and 0.3 were 91, 20, and 8, respectively. For densities greater than 25.1 brood adults per 0.046 m2, conservative estimates are obtained with 72, 15, and 6 samples for precision levels of 0.09, 0.2, and 0.3, respectively. An emergence ratio can be obtained by dividing the estimated density of brood adults by twice the number of gallery starts. This system provides the user with an immediate assessment of the population trend of Douglas-fir beetle. The data collected compare favorably with data from other Douglas-fir beetle outbreaks reported in the literature. The use of this plan outside the Colorado Front Range, or by sampling at a different height, should be cautioned until additional data from other locations and sampling heights are examined.

Résumé

Le Dendroctone du Douglas, Dendroctonus pseudotsugae Hopkins, s’attaque aux sapins de Douglas, Pseudotsuga menziesti (Mirb.) Franco (Pinaceae), dans tout l’ouest nord-américain. Les épidémies périodiques entraînent une hausse de la mortalité chez les hôtes. Les responsables de l’aménagement des terres et les spécialistes en foresterie ont souvent besoin d’évaluer les tendances démographiques de cet insecte. Des échantillons d’écorce ont été recueillis sur 326 arbres répartis dans 21 boisés au cours d’une période de 2 ans, à la fin de l’hiver et au début du printemps en 1997 en 1998 dans la chaîne de montagnes Colorado Front Range. Le rapport entre la variance et la moyenne a été étudié chez la progéniture émergente à l’aide de la loi de puissance de Taylor et un plan d’échantillonnage à précision pré-établie a été conçu selon la méthode de Green. Les lignes d’arrêt et le nombre minimum d’échantillons nécessaires pour estimer la densité des adultes émergés par 0,046 m2 à des niveaux de précision de 0,1, 0,2 et 0,3 ont été calculés. La simulation d’un nouvel échantillonnage avec une nouvelle matrice indépendante de données a permis de constater que les niveaux de précision n’ont pas été atteints. Les niveaux de précision théoriques ont été ajustés jusqu’à ce que les niveaux de précision désirés soient obtenus. Le nombre d’échantillons requis pour estimer la densité des adultes à l’émergence jusqu’à 25,1 adultes par 0,046 m2 était de 91 à un niveau de précision de 0,09, de 20 à un niveau de 0,2 et de 8 à un niveau de 0,03. Aux densités supérieures à 25,1 adultes par 0,046 m2, des estimations conservatrices de 72 (0,09), 15 (0,02) et 6 (0,03) échantillons ont été obtenues. Un rapport à l’émergence peut être calculé en divisant la densité estimée d’adultes par deux fois le nombre de galeries commencées. Ce système fournit à l’utilisateur une estimation immédiate de la tendance démographique du dendroctone. Ces données se comparent favorablement à celles obtenues au cours d’épidémies de dendroctones mentionnées dans la littérature. L’utilisation de ce plan en dehors de cette chaîne de montagnes, ou l’échantillonnage à d’autres hauteurs est à déconseiller si l’on n’obtient pas d’abord des données additionnelles sur d’autres localités et hauteurs d’échantillonnage.

[Traduit par la Rédaction]

Type
Articles
Copyright
Copyright © Entomological Society of Canada 2000

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

Badenhausser, I. 1996. Sequential sampling of Brachycaudus helichrysi (Homoptera: Aphididae) in sunflower fields. Journal of Economic Entomology 89: 1460–7CrossRefGoogle Scholar
Boeve, P.J., Weiss, M. 1998. Spatial distribution and sampling plans with fixed levels of precision for cereal aphids (Homoptera: Aphididae) infesting spring wheat. The Canadian Entomologist 130: 6777CrossRefGoogle Scholar
Burkness, E.C., Hutchison, W.D. 1998. Development and validation of a fixed-precision sampling plan for estimating striped cucumber beetle (Coleoptera: Chrysomelidae) density in cucurbits. Environmental Entomology 27: 178–83CrossRefGoogle Scholar
Chansler, J.F. 1968. Douglas-fir beetle brood densities and infestation trends on a New Mexico study area. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Research Note RN-125Google Scholar
Fredericks, S.E., Jenkins, M.J. 1988. Douglas-fir beetle (Dendroctonus pseudotsugae Hopkins, Coleoptera: Scolytidae) brood production on Douglas-fir defoliated by western spruce budworm (Choristoneura occidentalis Freeman, Lepidoptera: Tortricidae) in Logan Canyon, Utah. Great Basin Naturalist 48: 348–51Google Scholar
Furniss, M.M. 1962. Infestation patterns of Douglas-fir beetle in standing and windthrown trees in southern Idaho. Journal of Economic Entomology 55: 486–91CrossRefGoogle Scholar
Furniss, M.M. 1965. Susceptibility of fire-injured Douglas-fir to bark beetle attack in southern Idaho. Journal of Forestry 63: 811Google Scholar
Furniss, M.M., McGregor, M.D., Foiles, M.W., Partridge, A.D. 1979. Chronology and characteristics of a Douglas-fir beetle outbreak in northern Idaho. USDA Forest Service, Intermountain Forest and Range Experiment Sation, General Technical Report GTR-INT-59Google Scholar
Furniss, R.L., Carolin, V.M. 1977. Western forest insects. USDA Forest Service, Miscellaneous Publication 1339Google Scholar
Goldberger, A.S. 1968. On the interpretation and estimation of Cobb-Douglas functions. Econometrica 36: 464–72CrossRefGoogle Scholar
Green, R.H. 1970. On fixed precision level sequential sampling. Research Population Ecology (Kyoto) 12: 249–51CrossRefGoogle Scholar
Heinz, K.M., Chaney, W.E. 1995. Sampling for Liriomiza huidobrensis (Diptera: Agromyzidae) larvae and damage in celery. Environmental Entomology 24: 204–11CrossRefGoogle Scholar
Hutchison, W.D., Hogg, D.B., Poswall, M.A., Berberet, R.C., Cuperus, G.W. 1988. Implications of the stochastic nature of Kuno's and Green's fixed-precision stop lines: sampling plans for the pea aphid (Homoptera: Aphididae) in alfalfa as an example. Journal of Economic Entomology 81: 749–58CrossRefGoogle Scholar
Johnson, N.E., Belluschi, P.G. 1969. Host-finding behavior of the Douglas-fir beetle. Journal of Forestry 67: 290–5Google Scholar
Knight, F.B. 1960. Sequential sampling of Black Hills beetle populations. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Research Note RN-48Google Scholar
Kuno, E. 1969. A new method of sequential sampling to classify populations relative to a critical density. Research Population Ecology (Kyoto) 11: 127–36CrossRefGoogle Scholar
Kuno, E. 1972. Some notes on population estimation by sequential sampling. Research Population Ecology (Kyoto) 14: 5873CrossRefGoogle Scholar
Lessard, E.D., Schmid, J.M. 1990. Emergence, attack densities, and host relationships for the Douglas-fir beetle (Dendroctonus pseudotsugae Hopkins) in northern Colorado. Great Basin Naturalist 50: 333–8Google Scholar
Lynch, A.M., Fowler, G.W., Simmons, G.A. 1990. Sequential sampling plans for spruce budworm (Lepidoptera: Tortricidae) egg mass density using Monte Carlo simulation. Journal of Economic Entomology 83: 1479–84CrossRefGoogle Scholar
McMullen, L.H., Atkins, M.D. 1961. Intraspecific competition as a factor in the natural control of the Douglas-fir beetle. Forest Science 7: 197203Google Scholar
McMullen, L.H., Atkins, M.D. 1962. On the flight and host selection of the Douglas-fir beetle, Dendroctonus pseudotsugae Hopk. (Coleoptera: Scolytidae). The Canadian Entomologist 94: 1309–25CrossRefGoogle Scholar
Naranjo, S.E., Flint, H.M. 1994. Spatial distribution of preimaginal Bemisia tabaci (Homoptera: Aleyrodidae) in cotton and development of fixed-precision sequential sampling plans. Environmental Entomology 23: 254–66CrossRefGoogle Scholar
Naranjo, S.E., Hutchison, W.D. 1997. Validation of arthropod sampling plans using a resampling approach: software and analysis. American Entomologist 43: 4857CrossRefGoogle Scholar
Negrón, J.F. 1998. Probability of infestation and extent of mortality associated with the Douglas-fir beetle in the Colorado Front Range. Forest Ecology and Management 107: 7185CrossRefGoogle Scholar
Negrón, J.F., Schaupp, W.C., Gibson, K.E., Anhold, J., Hansen, D., Thier, R., Mocetini, P. 1999. Estimating extent of mortality associated with the Douglas-fir beetle in the Central and Northern Rockies. Western Journal of Applied Forestry 14: 121–7CrossRefGoogle Scholar
O'Rourke, P.K., Burkness, E.C., Hutchison, W.D. 1998. Development and validation of a fixed-precision sequential sampling plan for aster leafhopper (Homoptera: Cicadellidae) in carrot. Environmental Entomology 27: 1463–8CrossRefGoogle Scholar
Rudinsky, J.A. 1966. Host selection and invasion by the Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, in coastal Douglas-fir forests. The Canadian Entomologist 98: 98111CrossRefGoogle Scholar
Southwood, T.R.E. 1978. Ecological methods. 2nd ed. New York: Chapman & HallGoogle Scholar
Stark, R.W. 1952. Sequential sampling of the lodgepole needle miner. Forestry Chronicle 28: 5760CrossRefGoogle Scholar
Taylor, L.R. 1961. Aggregation, variance, and the mean. Nature (London) 189: 732–5CrossRefGoogle Scholar
Taylor, L.R., Woiwood, I.P. 1982. Comparative synoptic dynamics. I. Relationships between inter- and intraspecific spatial and temporal variance/mean population parameters. Journal of Animal Ecology 51: 879906CrossRefGoogle Scholar
Taylor, R.A.J., Lindquist, R.K., Shipp, J.L. 1998. Variation and consistency in spatial distribution as measured by Taylor's power law. Environmental Entomology 27: 191201CrossRefGoogle Scholar
Wald, A. 1947. Sequential analysis. New York: WileyGoogle Scholar
Waters, W.E. 1955. Sequential sampling in forest insect surveys. Forest Science 1: 6879Google Scholar
Wright, L.C., Berryman, A.A., Wickman, B.E. 1984. Abundance of the fir engraver, Scolytus ventralis, and the Douglas-fir beetle, Dendroctonus pseudotsugae, following tree defoliation by the Douglas-fir tussock moth, Orgyia pseudotsugata. The Canadian Entomologist 116: 293305CrossRefGoogle Scholar