Numerical solution and sensitivity analysis of a Fisher–KPP equation with nonlocal diffusion and free boundaries

Abstract This paper considers a model describing population dynamics where diffusion is nonlocal and habitat boundaries expand based on population flux. The population distribution is governed by a nonlocal Fisher–KPP equation with free boundaries. We propose a Front-Tracking method coupled with a fourth-order Runge–Kutta scheme for time integration, which adaptively manages the computational grid. For comparison, we outline the Front-Fixing approach, which transforms the problem into a fixed domain. Numerical simulations are performed for different scenarios, comparing the accuracy and behavior of both proposed methods. Furthermore, a variance-based global sensitivity analysis using Sobol’ indices is conducted to identify the influence of key model parameters on the final habitat length. Results show that the initial habitat size and the boundary expansion rate are the most influential parameters affecting the final domain length, with their relative importance depending on the distributions of the chosen input parameters.

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Publication Details

Journal
SeMA Journal
Published
2026-08-17
DOI
https://doi.org/10.1007/s40324-026-00439-6
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Numerical solution and sensitivity analysis of a Fisher–KPP equation with nonlocal diffusion and free boundaries

Vera N. Egorova, M.-C. Casabán, L. Jódar, M. Fakharany
SeMA Journal
Mathematical and Theoretical Epidemiology and Ecology Models
article

Numerical solution and sensitivity analysis of a Fisher–KPP equation with nonlocal diffusion and free boundaries

Vera N. Egorova, M.-C. Casabán, L. Jódar, M. Fakharany
article en

Abstract

Abstract This paper considers a model describing population dynamics where diffusion is nonlocal and habitat boundaries expand based on population flux. The population distribution is governed by a nonlocal Fisher–KPP equation with free boundaries. We propose a Front-Tracking method coupled with a fourth-order Runge–Kutta scheme for time integration, which adaptively manages the computational grid. For comparison, we outline the Front-Fixing approach, which transforms the problem into a fixed domain. Numerical simulations are performed for different scenarios, comparing the accuracy and behavior of both proposed methods. Furthermore, a variance-based global sensitivity analysis using Sobol’ indices is conducted to identify the influence of key model parameters on the final habitat length. Results show that the initial habitat size and the boundary expansion rate are the most influential parameters affecting the final domain length, with their relative importance depending on the distributions of the chosen input parameters.

SeMA Journal
Universidad de Cantabria (ES), Tanta University (EG), Universitat Politècnica de València (ES)
Universidad de Cantabria
Openalex Percentile: Top 8%
Mathematical and Theoretical Epidemiology and Ecology Models
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