Journal of Chemical Ecology

, Volume 22, Issue 11, pp 2133–2155 | Cite as

Temporal clumping of bark beetle arrival at pheromone traps: Modeling anemotaxis in chaotic plumes

  • John A. Byers


The sequence of arrival of the bark beetlesIps typographus andPityogenes chalcographus (Coleoptera: Scolytidae) at traps baited with their synthetic pheromones was monitored with a portable fraction collector. Histograms of the natural arrival patterns of both species were nonrandom and clumped at shorter time scales (1-, 2-, 4-, 5-, or 6-min cells) but appeared random at larger time scales (10, 20 or 30 min). Monte Carlo generation of similar histograms showed them to be random at all of these time scales. A stochastic computer model could graphically simulate insect orientation to odor sources based on present theories of odor-modulated anemotaxis and casting. Although this model was used throughout, since it assumes only that insects cast perpendicular to the current wind direction, a second model could slightly improve orientation success. However, the second model requires that the insect remember its ground path (upwind) prior to losing the plume (after an abrupt wind direction change). The effects of casting and flight parameters on orientation success and randomness of arrival sequence within various plumes were determined by simulation. Similarly, the effects of random walks in plume direction, plume width, and wind speed were explored. The results showed that dynamic random variations in plume direction and especially wind speed could cause an otherwise random arrival sequence (e.g., under constant wind) to become clumped and nonrandom. Therefore, the clumped arrival patterns of bark beetles and other insects, includingSpodoptera litura, at pheromone sources could result from random-walk fluctuations in wind speed and wind direction.

Key Words

Orientation attraction odor-modulated anemotaxis pheromone plumes casting simulation models Coleoptera Scolytidae Lepidoptera Anemotaxis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baker, T. C. 1989. Pheromones and flight behavior, pp. 231–255,in G. J. Goldsworthy and C. H. Wheeler (eds.) Insect Flight. CRC Press, Boca Raton, Florida.Google Scholar
  2. Baker, T. C., andHaynes, K. F. 1987. Manoeuvres used by flying male oriental fruit moths to relocate a sex pheromone plume in an experimentally shifted wind-field.Physiol. Entomol. 12:263–279.Google Scholar
  3. Baker, T. C., andRoelofs, W. L. 1981. Initiation and termination of Oriental fruit mth male response to pheromone concentrations in the field.Environ. Entomol. 10:211–218.Google Scholar
  4. Bakke, A., Frøyen, P., andSkattebøl, L. 1977. Field response to a new pheromonal compound isolated fromIps typographus.Naturwissenschaften 64:98.Google Scholar
  5. Bakke, A., Saether, T., andKvamme, T. 1983. Mass trapping of the spruce bark beetleIps typographus. Pheromone and trap technology.Medd. Norsk Inst. Skogforsk. 38:1–35.Google Scholar
  6. Bossert, W. H., andWilson, E. O. 1963. The analysis of olfactory communication among animals.J. Theor. Biol. 5:443–469.PubMedGoogle Scholar
  7. Byers, J. A. 1983. Electronic fraction collector used for insect sampling in the photoperiod-induced diel emergence of bark beetles.Physiol. Entomol. 8:133–138.Google Scholar
  8. Byers, J. A. 1988. Upwind flight orientation to pheromone in western pine beetle tested with rotating windvane traps.J. Chem. Ecol. 14:189–212.Google Scholar
  9. Byers, J. A. 1991. Simulation of mate-finding behaviour in pine shoot beetles,Tomicus piniperda.Anim. Behav. 41:649–660.Google Scholar
  10. Byers, J. A. 1992. Dirichlet tessellation of bark beetle spatial attack points.J. Anim. Ecol. 61:759–768.Google Scholar
  11. Byers, J. A. 1993. Simulation and equation models of insect population control by pheromone-baited traps.J. Chem. Ecol. 19:1939–1956.Google Scholar
  12. Byers, J. A., andLöfqvist, J. 1989. Flight initiation and survival in the bark beetlelps typographus (Coleoptera: Scolytidae) during the spring dispersal.Holarct. Ecol. 12:432–440.Google Scholar
  13. Byers, J. A., Birgersson, G., Löfqvist, J., andBergström, G. 1988. Synergistic pheromones and monoterpenes enable aggregation and host recognition by a bark beetle,Pityogenes chalcographus.Naturwissenschaften 75:153–155.Google Scholar
  14. Byers, J. A., Anderbrant, O., andLöfqvist, J. 1989. Effective attraction radius: A method for comparing species attractants and determining densities of flying insects.J. Chem. Ecol. 15:749–765.Google Scholar
  15. Byers, J. A., Birgersson, G., Löfqvist, J., Appelgren, M., andBergstrom, G. 1990. Isolation of pheromone synergists of bark beetle,Pityogenes chalcographus, from complex insect-plant odors by fractionation and subtractive-combination bioassay.J. Chem. Ecol. 16:861–876.Google Scholar
  16. Choudhury, J. H., andKennedy, J. S. 1980. Light versus pheromone-bearing wind in the control of flight direction by bark beetles,Scolytus multistriatus.Physiol. Entomol. 5:207–214.Google Scholar
  17. David, C. T., Kennedy, J. S., Ludlow, A. R., Perry, J. N., andWall, C. 1982. A reappraisal of insect flight towards a distanct point source of wind-borne odor.J. Chem. Ecol. 8:1207–1215.Google Scholar
  18. Elkinton, J. S. andCardé, R. T. 1984. Odor dispersion, pp. 73–91,in W. J. Bell and R. T. Cardé (eds.) Chemical Ecology of Insects. Chapman and Hall, London.Google Scholar
  19. Elkinton, J. S., Cardé, R. T., andMason, C. J. 1984. Evaluation of time-averaged dispersion models for estimating pheromone concentration in a deciduous forest.J. Chem. Ecol. 10:1081–1108.Google Scholar
  20. Fares, Y., Sharpe, P. J. H., andMagnuson, C. E. 1980. Pheromone dispersion in forests.J. Theor. Biol. 84:335–359.PubMedGoogle Scholar
  21. Francke, W., Heemann, V., Gerken, B., Renwick, J. A. A., andVitè, J. P. 1977. 2-Ethyl-1-6-dioxaspiro[4.4]nonane, principal aggregation pheromone ofPityogenes chalcographus (L.).Naturwissenschaften 64:590–591.Google Scholar
  22. Helland, I. S., Hoff, J. M., andAnderbrant, O. 1984. Attraction of bark beetles (Coleoptera: Scolytidae) to a pheromone trap: Experiment and mathematical models.J. Chem. Ecol. 10:723–752.Google Scholar
  23. Kennedy, J. S. 1939. The visual responses of flying mosquitoes.Proc. Zool. Soc. London A 109:221–242.Google Scholar
  24. Kennedy, J. S. 1983. Zigzagging and casting as a response to windborne odour: A review.Physiol. Entomol. 8:109–120.Google Scholar
  25. Lindgren, B. S., Borden, J. H., Chong, L., Friskie, L. M., andOrr, D. B. 1983. Factors influencing the efficiency of pheromone baited traps for 3 species of ambrosia beetles (Coleoptera: Scolytidae).Can. Entomol. 115:303–314.Google Scholar
  26. Murlis, J., andJones, C. D. 1981. Fine-scale structure of odour plumes in relation to insect orientation to distant pheromone and other attractant sources.Physiol. Entomol. 6:71–86.Google Scholar
  27. Nakamura, K., andKawasaki, K. 1977. The active space of theSpodoptera litura (F.) sex pheromone and the pheromone component determining this space.Appl. Entomol. Zool. 12:162–177.Google Scholar
  28. Nakamura, K., andKawasaki, K. 1984. Male catches ofSpodoptera litura (F.) in pheromone traps under fluctuating wind velocity: Validity of the Actie space model.Appl. Entomol. Zool. 19:192–201.Google Scholar
  29. Ripley, B. D. 1981. Spatial Statistics. John Wiley & Sons, New York.Google Scholar
  30. Sabelis, M. W., andSchippers, P. 1984. Variable wind directions and anemotactic strategies of searching for an odour plume.Oecologia 63:225–228.Google Scholar
  31. Salom, S. M., andMcLean, J. A. 1991a. Flight behavior of scolytid beetle in response to semiochemicals at different wind speeds.J. Chem. Ecol. 17:647–661.Google Scholar
  32. Salom, S. M., andMcLean, J. A. 1991b. Environmental influences on dispersal ofTrypodendron lineatum (Coleoptera: Scolytidae).Environ. Entomol. 20:565–576.Google Scholar
  33. Tilden, P. E., Bedard, W. D., Lindahl, K. Q., Jr, andWood, D. L. 1983. TrappingDendroctonus brevicomis: Changes in attractant release rate, dispersion of attractant, and silhouette.J. Chem. Ecol. 9:311–321.Google Scholar
  34. Von Keyserlingk, H. C. 1984. Close range orientation of flying Lepidoptera to pheromone sources in a laboratory wind tunnel and the field.Med. Facult. Land. Rijksuniv. Gent 49:683–689.Google Scholar
  35. Worner, S. P. 1991. Use of models in applied entomology: the need for perspective.Environ. Entomol. 20:768–773.Google Scholar

Copyright information

© Plenum Publishing Corporation 1996

Authors and Affiliations

  • John A. Byers
    • 1
  1. 1.Department of Plant ProtectionChemical Ecology Swedish University of Agricultural SciencesAlnarpSweden

Personalised recommendations