title: Multiscale approach to pest insect monitoring: random walks, pattern formation, synchronization, and networks.
abstract: Pest insects pose a significant threat to food production worldwide resulting in annual losses worth hundreds of billions of dollars. Pest control attempts to prevent pest outbreaks that could otherwise destroy a sward. It is good practice in integrated pest management to recommend control actions (usually pesticides application) only when the pest density exceeds a certain threshold. Accurate estimation of pest population density in ecosystems, especially in agro-ecosystems, is therefore very important, and this is the overall goal of the pest insect monitoring. However, this is a complex and challenging task; providing accurate information about pest abundance is hardly possible without taking into account the complexity of ecosystems' dynamics, in particular, the existence of multiple scales. In the case of pest insects, monitoring has three different spatial scales, each of them having their own scale-specific goal and their own approaches to data collection and interpretation. In this paper, we review recent progress in mathematical models and methods applied at each of these scales and show how it helps to improve the accuracy and robustness of pest population density estimation.
authors.affiliation: Department of Mathematics, University of Leicester, University Road, Leicester LE1 7RH, UK.
authors.forename: Sergei
authors.initials: S
authors.lastname: Petrovskii
authors.affiliation: School of Mathematics, University of Birmingham, Birmingham B15 2TT, UK.
authors.forename: Natalia
authors.initials: N
authors.lastname: Petrovskaya
authors.affiliation: Department of Mathematics, University of Leicester, University Road, Leicester LE1 7RH, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Bearup
mesh_terms: D000818:Animals; D006801:Humans; D007255:Information Services; D007300:Insect Control; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D010572:Pest Control, Biological
keywords: Diffusion; Dispersal; Insect monitoring; Levy walk; Numerical integration; Trapping