Modelling a targeted use of pesticide procedure for pest populations with heterogeneous spatial distributions

Research output: Contribution to journalArticle

Authors

Colleges, School and Institutes

External organisations

  • Harper Adams University

Abstract

Commercial and environmental considerations have led to increased pressure to reduce pesticide use in agricultural crops resulting in a growing interest in development of pesticide application protocols that allow for their targeted use. In this paper, we revisit a standard decision-making protocol for pesticide application and introduce protocol modifications to apply pesticide to selected spatial sub-domains in the agricultural field. The baseline case we
consider is the control of populations of the grey field slug (Deroceras reticulatum) in commercial fields. It is well known that slugs have strongly heterogeneous (patchy) spatial distribution and we show that targeting patches with higher slug density only, may offer significant potential for reducing the use of pesticides. An approach to incorporating targeted application of pesticide into a control protocol with treatment decisions based on a threshold population
abundance will be discussed. The benefits of the targeted use of pesticides will be clearly demonstrated using data on slug abundance collected in commercial fields. We then argue that employing a single threshold for decision-making in the pesticide application protocol is not the most efficient way to assess risks associated with the population abundance when pesticide is applied selectively. It will be shown that a protocol for targeted use of pesticides depends heavily on the definition of a spatial density patch in heterogeneous spatial distribution, and a single decision-making parameter such as the population threshold
cannot accommodate important information about the patch size. Hence an alternative is to introduce two controlling parameters into the protocol in order to quantify the pest abundance in each patch and patch size separately and we discuss this approach in the paper.

Details

Original languageEnglish
JournalEcological Modelling
Publication statusAccepted/In press - 28 Mar 2020