Reaction-diffusion models of invasive tree pest spread: quantifying the expansion of oak processionary moth in the UK

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Autori principali: McKeown, Jamie P., Wadkin, Laura E., Parker, Nick G., Golightly, Andrew, Baggaley, Andrew W.
Natura: Preprint
Pubblicazione: 2025
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author McKeown, Jamie P.
Wadkin, Laura E.
Parker, Nick G.
Golightly, Andrew
Baggaley, Andrew W.
author_facet McKeown, Jamie P.
Wadkin, Laura E.
Parker, Nick G.
Golightly, Andrew
Baggaley, Andrew W.
contents UK woodlands, forests, and urban treescapes are under threat from invasive species, exacerbated by climate change, trade, and transport. Invasive tree pests debilitate their host and disrupt forest ecosystems, thus it is imperative to quantitatively model and predict their spread. Addressing this, we model the spread of an invasive pest using a spatiotemporal reaction-diffusion equation, representing the spatial distribution as a population density field. We solve this intractable equation numerically and, from the solution, we determine first arrival times of the pest at locations in the field. The adopted model permits us to obtain the expansion rate of pest spread directly from the model parameters, which we infer in the Bayesian paradigm, using a Markov chain Monte Carlo scheme. We apply our framework to the ongoing spread of oak processionary moth in the UK, an outbreak which continues to grow despite management efforts. We demonstrate that our approach effectively captures the spread of the pest and that this has occurred at a non-constant expansion rate. The proposed framework is a powerful tool for quantitatively modelling the spread of an invasive tree pest and could underpin future prediction and management approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2509_14166
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Reaction-diffusion models of invasive tree pest spread: quantifying the expansion of oak processionary moth in the UK
McKeown, Jamie P.
Wadkin, Laura E.
Parker, Nick G.
Golightly, Andrew
Baggaley, Andrew W.
Populations and Evolution
Quantitative Methods
92D40, 92-10
UK woodlands, forests, and urban treescapes are under threat from invasive species, exacerbated by climate change, trade, and transport. Invasive tree pests debilitate their host and disrupt forest ecosystems, thus it is imperative to quantitatively model and predict their spread. Addressing this, we model the spread of an invasive pest using a spatiotemporal reaction-diffusion equation, representing the spatial distribution as a population density field. We solve this intractable equation numerically and, from the solution, we determine first arrival times of the pest at locations in the field. The adopted model permits us to obtain the expansion rate of pest spread directly from the model parameters, which we infer in the Bayesian paradigm, using a Markov chain Monte Carlo scheme. We apply our framework to the ongoing spread of oak processionary moth in the UK, an outbreak which continues to grow despite management efforts. We demonstrate that our approach effectively captures the spread of the pest and that this has occurred at a non-constant expansion rate. The proposed framework is a powerful tool for quantitatively modelling the spread of an invasive tree pest and could underpin future prediction and management approaches.
title Reaction-diffusion models of invasive tree pest spread: quantifying the expansion of oak processionary moth in the UK
topic Populations and Evolution
Quantitative Methods
92D40, 92-10
url https://arxiv.org/abs/2509.14166