Hostname: page-component-76fb5796d-dfsvx Total loading time: 0 Render date: 2024-04-26T04:18:11.543Z Has data issue: false hasContentIssue false

Long range forecasts of the numbers of Helicoverpa punctigera and H. armigera (Lepidoptera: Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

Published online by Cambridge University Press:  09 March 2007

D.A. Maelzer
Affiliation:
School of Land and Food, The University of Queensland, Gatton, Queensland, 4343Australia Department of Zoology and Entomology, The University of Queensland, St Lucia, Queensland, 4072Australia
M.P. Zalucki*
Affiliation:
Department of Zoology and Entomology, The University of Queensland, St Lucia, Queensland, 4072Australia
*
*Fax: (07) 3365 1922 E-mail: m.zalucki@mailbox.uq.edu.au

Abstract

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hübner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6–15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

Type
Research Article
Copyright
Copyright © Cambridge University Press 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

Allan, R., Lindsay, J. & Parker, D. (1996) El Niño-Southern Oscillation and Climatic Variability. 405 pp. Collingwood, Victoria, Australia, CSIRO.Google Scholar
Bliss, C.I. (1967) Statistics in biology, vol.1. 558 pp. New York, McGraw-Hill, Inc.Google Scholar
Bommarco, R. & Ekbom, B. (1995) Phenology and prediction of pea aphid infestations on peas. International Journal of Pest Management 41, 109113.Google Scholar
Bouma, M.J. & Vanderkaay, H.J. (1996) The El Niño Southern Oscillation and the historic malaria epidemics on the Indian subcontinent and Sri Lanka: an early warning system for future epidemics. Tropical Medicine and International Health 1, 8698.CrossRefGoogle ScholarPubMed
Clewett, J.F., Howden, S.M., McKeon, G.M. & Rose, C.W. (1991) Use of systems analysis and the Southern Oscillation Index to optimise management of grain sorghum production from a farm dam irrigation system. pp. 307328. in Muchow, R.C. & Bellamy, J.A. (Eds).Climatic risk in crop production. Models and management for the semi-arid tropics and sub-tropics. Wallingford, CAB International.Google Scholar
Clewett, J.F., Clarkson, N.M., Owens, D.T. & Abrecht, D.G. (1994) Australian rainman: rainfall information for better management. Brisbane, Department of Primary Industries.Google Scholar
Dent, D. (1991) Insect pest management. 604 pp. Wallingford, CAB International.Google Scholar
Drake, V.A. & Farrow, R.A. (1988) Te influence of atmospheric structure and motions on insect migration. Annual Review of Entomology 33, 183210.Google Scholar
Draper, N.R. & Smith, H. (1981) Applied regression analysis. 2nd edn, 699 pp. New York, John Wiley.Google Scholar
Fletcher, B.S. (1987) The biology of dacine fruit flies. Annual Review of Entomology 32, 115144.CrossRefGoogle Scholar
Forrester, N.W., Cahill, M., Bird, L.J. & Layland, J.K. (1993) Management of pyrethroid and endosulphan resistance in Helicoverpa armigera(Lepidoptera: Noctuidae) in Australia. Bulletin of Entomological Research Supplement Series. Supplement No. 1, 132 pp.Google Scholar
Gleick, J. (1988) Chaos. UK, William Heinemann Ltd.Google Scholar
Haggis, M.J. (1996) Forecasting the severity of seasonal outbreaks of African armyworm, Spodoptera exempta (Lepidoptera: Noctuidae) in Kenya from the previous year's rainfall. Bulletin of Entomological Research 86, 129136.CrossRefGoogle Scholar
Hales, S., Weinstein, P. & Woodward, A. (1996) Dengue fever epidemics in the South Pacific: driven by El Niño Southern Oscillation?. Lancet 348, no. 9042Google Scholar
Hammer, G.L. & Muchow, R.C. (1991) Quantifying climatic risk to sorghum in Australia's semi-arid tropics and subtropics: model development and simulation. pp. 205231. in Muchow, R.C. & Bellamy, J.A. (Eds). Climatic risk in crop production. Models and management for the semi-arid tropics and sub-tropics. Wallingford, CAB International.Google Scholar
Hammer, G.L., KcKeon, G.M., Clewett, J.F. & Woodruff, D.R. (1991) Usefulness of seasonal climate forecasts in crop and pasture management. pp. 1523 in Proceedings: Conference on Agricultural Meteorology. Bureau of Meteorology, Box 1289K, Melbourne, Victoria, Australia, 3001.Google Scholar
Harvey, A.W. & Mallya, G.A. (1995) Predicting the severity of Spodoptera exempta (Lepidoptera: Noctuidae) outbreak seasons in Tanzania. Bulletin of Entomological Research 85, 479487.Google Scholar
Holton, I. (1998) Prediction of growing season rainfall and crop yields in southern Australia. Australian Meteorological Magazine 47, 327338.Google Scholar
Hunter, D.M. (1996) Rapport entre les pullulations du Criquet australien, Chortoicetes terminifera (Walker) (Orthoptera: Acrididae) et la pluviometrie dans l'interieur aride de l'Australien. Secheresse 7, 8790.Google Scholar
Jobson, J.D. (1991) Applied multivariate data analysis. Vol. 1: regression and experimental design. 621 pp. New York, Springer-Verlag.Google Scholar
Kyi, A., Zalucki, M.P. & Titmarsh, I.J. (1991) Factors affecting the survival of the early stages of Heliothis armigera (Hübner) (Lepidoptera; Noctuidae). Bulletin of Entomological Research 81, 263271.Google Scholar
Maelzer, D.A. (1964) Rainfall and changes in abundance ofAphodius tasmaniae Hope (Coleoptera: Scarabaeidae) in the lower S.E. of South Australia. Australian Journal of Zoology 12, 263278.Google Scholar
Maelzer, D.A. & Zalucki, M.P. (1999) Analysis and interpretation of long term light trap data for Helicoverpa spp. (Lepidoptera: Noctuidae) in Australia: the effect of climate and crop host plants. Bulletin of Entomological Research 89, 455464.Google Scholar
Maelzer, D.A., Zalucki, M.P. & Laughlin, R. (1996) Analysis and interpretation of long term light trap data for Helicoverpa punctigera (Lepidoptera: Noctuidae) in Australia: population changes and forecasting pest pressure. Bulletin of Entomological Research 86, 547557.Google Scholar
May, A.W.S. (1961) A taxonomic and ecological study of the Dacinae (Family: Trypetidae). PhD thesis, University of Queensland, Brisbane, Queensland, Australia.Google Scholar
McBride, J.L. & Nicholls, N. (1983) Seasonal relationship between Australian and the Southern Oscillation. Monthly Weather Review 111, 19982004.2.0.CO;2>CrossRefGoogle Scholar
McDonald, G., New, T.R. & Farrow, R.A. (1995) Geographical and temporal distribution of the common armyworm, Mythimna convecta (Lepidoptera: Noctuidae) in eastern Australia: larval habitats and outbreaks. Australian Journal of Zoology 43, 601629.CrossRefGoogle Scholar
Meinke, H., Stone, R.C., & Hammer, G.L. (1996) SOI phases and climatic risk to peanut production: a case study for northern Australia. International Journal of Climatology 16, 783789.Google Scholar
Mosteller, F. & Tukey, J.W. (1977) Data analysis and regression; a second course in statistics. 588 pp. New York, Addison-Wesley.Google Scholar
Mosteller, F., Rourke, R.E.K. & Thomas, G.B. (1973) Probability with statistical applications. 2nd. edn, 527 pp. New York, Addison-Wesley.Google Scholar
Nicholls, N. (1986) A method for predicting Murray Valley encephalitis in southeast Australia using the Southern Oscillation. Australian Journal of Biological and Medical Sciences 64, 587594.CrossRefGoogle ScholarPubMed
Nicholls, N. (1986) Use of the `southern oscillation to predict Australian sorghum yield. Agricultural and Forest Meteorology 38, 915.Google Scholar
Nicholls, N. (1991) Teleconnections and health. pp. 493509in Glantz, M., Katz, R. & Nicholls, N. (Eds) ENSO teleconnections lining worldwide climatic anomalies: scientific basis and social impacts. Cambridge, Cambridge University Press.Google Scholar
Nicholls, N., Lavery, B., Frederiksen, C., Drosdowsky, W. & Torok, S. (1996) Recent apparent changes in relationships between the El Niño-Southern Oscillation and Australian rainfall and temperature. Geophysical Research Letters 23, 33573360.Google Scholar
Oertel, A., Zalucki, M.P., Maelzer, D.A., Fitt, G.P. & Sutherst, R. (1998) Variation in the size of the first spring generation of Helicoverpa punctigera: the effect of weather in winter breeding areas. Australian Journal of Entomology 38, 99103.Google Scholar
Partridge, I.J. (1994) Will it rain? The effects of the Southern Oscillation and El Niño on Australia. 56 pp. Queensland Department of Primary Industries; Information Series Q194015.Google Scholar
Pittock., A.B. (1975) Climatic change and the pattern of variation in Australian rainfall. Search 6, 498504.Google Scholar
Rhodes, A.A., Morse, J.G. & Robertson, C.A. (1989) A simple multigeneration phenology model: application to Scirtothrips citri (Thysanoptera: Thripidae) prediction on California oranges. Agriculture, Ecosystems and Environment 25, 299313.Google Scholar
Rimmington, G.M. & Nicholls, N. (1993) Forecasting wheat yields in Australia with the Southern Oscillation Index. Australian Journal of Agricultural Research 44, 625632.Google Scholar
Stone, R. & Auliciems, A. (1992) SOI phase relationships with rainfall in eastern Australia. International Journal of Climatology 12, 625636.Google Scholar
Stone, R.C., Hammer, G.L. & Marcussen, T. (1996) Prediction of global rainfall probabilities using phases of the Southern Oscillation Index. Nature 384, 252255.CrossRefGoogle Scholar
Stone, R.C., Nicholls, N. & Hammer, G.L. (1996) Frost in Northern Australia: trends and influence of phases of the Southern Oscillation. Journal of Climate 9, 18961909.2.0.CO;2>CrossRefGoogle Scholar
Tabachnick, B.G. & Fidell, L.S. (1989) Using multivariate statistics. 2nd edn, 746 pp. New York, Harper and Row.Google Scholar
Titmarsh, I.J. (1993) Mortality of immature Lepidoptera: a case study with Heliothis species (Lepidoptera; Noctuidae) in agricultural crops on the Darling Downs. PhD thesis. The University of Queensland, Brisbane.Google Scholar
Varley, G.C., Gradwell, G.R. & Hassell, M.P. (1973) Insect population ecology: an analytical approach. 191 pp. Oxford, Blackwell.Google Scholar
Waldren, K.J. (1991) Heliothis in Western Australia: pest status and current research. pp. 7376 in Twine, P.H. & Zalucki, M.P. (Eds) A review of Heliothis research in Australia. Queensland Department of Primary Industries Conference and Workshop Series, Brisbane.Google Scholar
Wesolowsky, G.O. (1976) Multiple regression and analysis of variance. 292 pp. John Wiley & Sons, Inc.Google Scholar
Willcocks, J.R., McKeon, G.M. & Day, K.A. (1991) Using the Southern Oscillation Index to predict the growth of Heteropogon contortus pasture in southeast Queensland. pp 3639 in Proceedings: Conference on Agricultural Meteorology. Bureau of Meteorology, Melbourne, Victoria, Australia.Google Scholar
Zalucki, M.P., Gregg, P.C., Fitt, G.P., Murray, D.A.H., Twine, P. & Jones, C. (1994) Ecology of Helicoverpa armigera (Hübner) and H. punctigera (Wallengren) in the inland of Australia: larval sampling and host plant relationships during winter and spring. Australian Journal of Zoology 42, 329346.CrossRefGoogle Scholar