Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/31970
Title: Multiscale approach to pest insect monitoring: Random walks, pattern formation, synchronization, and networks
Authors: Petrovskii, Sergei
Petrovskaya, N.
Bearup, Daniel
First Published: 14-Feb-2014
Publisher: Elsevier
Citation: Physics of Life Reviews, 2014, 11 (3), pp. 467-525
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.
DOI Link: 10.1016/j.plrev.2014.02.001
ISSN: 1571-0645
eISSN: 1873-1457
Links: http://www.sciencedirect.com/science/article/pii/S1571064514000244
http://hdl.handle.net/2381/31970
Embargo on file until: 14-Feb-2018
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Physics of Life Reviews 11 (3), 2014 10.1016/j.plrev.2014.02.001
Appears in Collections:Published Articles, Dept. of Mathematics

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