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Application of a Mechanistic Model to Explore Management Strategies for Biological Control of an Agricultural Pest

Author

Listed:
  • Madeleine G. Barton

    (Commonwealth Science and Industrial Research Organisation (CSIRO), Canberra, ACT 2601, Australia)

  • Hazel Parry

    (Commonwealth Science and Industrial Research Organisation (CSIRO), Canberra, ACT 2601, Australia)

  • Paul A. Umina

    (School of BioSciences, The University of Melbourne, Parkville, VIC 3052, Australia
    Cesar Australia, Brunswick, VIC 3056, Australia)

  • Matthew R. Binns

    (Commonwealth Science and Industrial Research Organisation (CSIRO), Canberra, ACT 2601, Australia)

  • Thomas Heddle

    (South Australian Research and Development Institute, Urrbrae, SA 5064, Australia)

  • Ary A. Hoffmann

    (School of BioSciences, The University of Melbourne, Parkville, VIC 3052, Australia)

  • Joanne Holloway

    (Department of Primary Industries, Wagga Wagga, NSW 2650, Australia)

  • Dustin Severtson

    (Department of Primary Industries and Regional Development, Northam, WA 6401, Australia)

  • Maarten Van Helden

    (South Australian Research and Development Institute, Urrbrae, SA 5064, Australia
    School of Agriculture, Food and Wine, University of Adelaide, Adelaide, SA 5005, Australia)

  • Samantha Ward

    (School of BioSciences, The University of Melbourne, Parkville, VIC 3052, Australia
    Cesar Australia, Brunswick, VIC 3056, Australia)

  • Rachel Wood

    (Department of Primary Industries, Wagga Wagga, NSW 2650, Australia)

  • Sarina Macfadyen

    (Commonwealth Science and Industrial Research Organisation (CSIRO), Canberra, ACT 2601, Australia)

Abstract

Despite the known benefits of integrated pest management, adoption in Australian broadacre crops has been slow, in part due to the lack of understanding about how pests and natural enemies interact. We use a previously developed process-based model to predict seasonal patterns in the population dynamics of a canola pest, the green peach aphid ( Myzus persicae ), and an associated common primary parasitic wasp ( Diaeretiella rapae ), found in this cropping landscape. The model predicted aphid population outbreaks in autumn and spring. Diaeretiella rapae was able to suppress these outbreaks, but only in scenarios with a sufficiently high number of female wasps in the field (a simulated aphid:wasp density ratio of at least 5:1 was required). Model simulations of aphid-specific foliar pesticide applications facilitated biological control. However, a broad-spectrum pesticide negated the control provided by D. rapae , in one case leading to a predicted 15% increase in aphid densities compared to simulations in which no pesticide was applied. Biological and chemical control could therefore be used in combination for the successful management of the aphid while conserving the wasp. This modelling framework provides a versatile tool for further exploring how chemical applications can impact pests and candidate species for biological control.

Suggested Citation

  • Madeleine G. Barton & Hazel Parry & Paul A. Umina & Matthew R. Binns & Thomas Heddle & Ary A. Hoffmann & Joanne Holloway & Dustin Severtson & Maarten Van Helden & Samantha Ward & Rachel Wood & Sarina , 2024. "Application of a Mechanistic Model to Explore Management Strategies for Biological Control of an Agricultural Pest," Agriculture, MDPI, vol. 14(1), pages 1-14, January.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:1:p:150-:d:1322594
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