When managers forage for pests: Implementing the functional response in pest management

Journal Article · 19 November 2018 · Ecological Modelling

DOI: https://doi.org/10.1016/j.ecolmodel.2018.10.013 · OSTI ID:1524376

Kunegel-Lion, Melodie ^[1]; Goodsman, Devin W.  ^[2]; Lewis, Mark A. ^[1]

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1. Univ. of Alberta, Edmonton, AB (Canada)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

In this work, we explore how the functional response framework can be implemented in pest management. Here, managers take the role of predators foraging on pests and facing monetary costs for survey and control in a spatial domain where the pest distribution and control strategy do not have to be random. To investigate this framework quantitatively, we simulated various management processes on different pest spatial distributions using a spatially-explicit individual-based model and Monte-Carlo simulations, and also confirmed some of the results analytically. By graphing the number of pests controlled versus pest density, we obtained management functional response curves. Whether the management functional response was shaped like a type I, type II or type III functional response depended on the management costs and the search area. Yet, the management spatial strategy and the pest spatial distribution had little effect on the functional response. We applied our model to the management of mountain pine beetle epidemic in Cypress Hills, Saskatchewan, Canada, with simulations matching the real number of attacked trees controlled by managers. We showed how to make an analogy between functional responses in predator–prey interactions and in human–pest interactions and thereby, apply insights from the functional response framework to pest management.

• Research Organization: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: 89233218CNA000001
• OSTI ID: 1524376
• Report Number(s): LA-UR-17-30015
• Journal Information: Ecological Modelling, Journal Name: Ecological Modelling Journal Issue: C Vol. 396; ISSN 0304-3800
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English