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

• Published in: arXiv.org
• Main Authors: Abboud, Candy, Bonnefon, Olivier, Parent, Eric, Soubeyrand, Samuel
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 01.08.2018
• Subjects: Absorption; Adaptive algorithms; Adaptive sampling; Bayesian analysis; Chronology; Diffusion; Importance sampling; Initial conditions; Mathematical models; Partial differential equations; Statistical inference
• ISSN: 2331-8422

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 \textit{Xylella fastidiosa}, a phytopathogenic bacterium detected in South Corsica in 2015, France.