Application of a Mechanistic Model to Explore Management Strategies for Biological Control of an Agricultural Pest
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Date
2024
Authors
Barton, M.G.
Parry, H.
Umina, P.A.
Binns, M.R.
Heddle, T.
Hoffmann, A.A.
Holloway, J.
Severtson, D.
Van Helden, M.
Ward, S.
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Journal article
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Agriculture, 2024; 14(1):14010150-1-14010150-13
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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, and Sarina Macfadyen
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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.
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).