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Dating and localizing an invasion from post-introduction data and a coupled reaction–diffusion–absorption model

机译:从引入后的数据和耦合的反应-扩散-吸收模型确定入侵的日期和位置

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摘要

Invasion of new territories by alien organisms is of primary concern for environmental and health agencies and has been a core topic in mathematical modeling, in particular in the intents of reconstructing the past dynamics of the alien organisms and predicting their future spatial extents. Partial differential equations offer a rich and flexible modeling framework that has been applied to a large number of invasions. In this article, we are specifically interested in dating and localizing the introduction that led to an invasion using mathematical modeling, post-introduction data and an adequate statistical inference procedure. We adopt a mechanistic-statistical approach grounded on a coupled reaction–diffusion–absorption model representing the dynamics of an organism in an heterogeneous domain with respect to growth. Initial conditions (including the date and site of the introduction) and model parameters related to diffusion, reproduction and mortality are jointly estimated in the Bayesian framework by using an adaptive importance sampling algorithm. This framework is applied to the invasion of Xylella fastidiosa, a phytopathogenic bacterium detected in South Corsica in 2015, France.Electronic supplementary materialThe online version of this article (10.1007/s00285-019-01376-x) contains supplementary material, which is available to authorized users.
机译:外来生物入侵新领土是环境和卫生机构的首要关注,并且一直是数学建模的核心主题,特别是在重建外来生物过去的动态并预测其未来空间范围方面。偏微分方程提供了一个丰富而灵活的建模框架,该框架已应用于大量入侵。在本文中,我们特别感兴趣的是使用数学建模,引入后的数据和适当的统计推断程序来对导致入侵的引言进行约会和本地化。我们采用了一种基于机制-统计的方法,该方法基于反应-扩散-吸收耦合模型,该模型代表了生物在异质域中相对于生长的动态。通过使用自适应重要性抽样算法,在贝叶斯框架中共同估算了初始条件(包括引种的日期和地点)以及与扩散,繁殖和死亡有关的模型参数。此框架适用于2015年在法国南科西嘉发现的植物病原菌Xylella fastidiosa的入侵电子补充材料本文的在线版本(10.1007 / s00285-019-01376-x)包含补充材料,授权用户。

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