Retkute Renata, Thurston William, Cressman Keith, Gilligan Christopher A
Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, United Kingdom.
Met Office, Fitzroy Road, Exeter, United Kingdom.
PLoS Comput Biol. 2024 Dec 19;20(12):e1012562. doi: 10.1371/journal.pcbi.1012562. eCollection 2024 Dec.
There is an urgent need for mathematical models that can be used to inform the deployment of surveillance, early warning and management systems for transboundary pest invasions. This is especially important for desert locust, one of the most dangerous migratory pests for smallholder farmers. During periods of desert locust upsurges and plagues, gregarious adult locusts form into swarms that are capable of long-range dispersal. Here we introduce a novel integrated modelling framework for use in predicting gregarious locust populations. The framework integrates the selection of breeding sites, maturation through egg, hopper and adult stages and swarm dispersal in search of areas suitable for feeding and breeding. Using a combination of concepts from epidemiological modelling, weather and environment data, together with an atmospheric transport model for swarm movement we provide a tool to forecast short- and long-term swarm movements. A principal aim of the framework is to provide a practical starting point for use in the next upsurge.
迫切需要能够为跨界害虫入侵的监测、预警和管理系统的部署提供信息的数学模型。这对于沙漠蝗虫来说尤为重要，沙漠蝗虫是对小农户最危险的迁徙害虫之一。在沙漠蝗虫数量激增和暴发期间，群居的成年蝗虫会形成能够远距离扩散的蝗群。在此，我们引入了一种用于预测群居蝗虫种群的新型综合建模框架。该框架整合了繁殖地的选择、从卵、若虫到成虫阶段的发育以及蝗群为寻找适合觅食和繁殖的区域而进行的扩散。通过结合流行病学建模的概念、天气和环境数据以及用于蝗群移动的大气传输模型，我们提供了一个预测短期和长期蝗群移动的工具。该框架的一个主要目标是为下一次数量激增时的实际应用提供一个起点。
