Numerical bifurcation analysis of turing and symmetry broken patterns of a PDE model for vegetation dynamics.

IF 2.7 4区 数学 Q2 BIOLOGY
Konstantinos Spiliotis, Lucia Russo, Constantinos Siettos, Francesco Giannino
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引用次数: 0

Abstract

We study the mechanisms of pattern formation for vegetation dynamics in water-limited regions. Our analysis is based on a set of two partial differential equations (PDEs) of reaction-diffusion type for the biomass and water, and one ordinary differential equation (ODE) describing the dependence of the toxicity on the biomass. We perform a linear stability analysis in the one-dimensional finite space, we derive analytically the conditions for the appearance of Turing instability that gives rise to spatio-temporal patterns emanating from the homogeneous solution, and provide its dependence with respect to the size of the domain. Furthermore, we perform a numerical bifurcation analysis in order to study the pattern formation of the inhomogeneous solution, with respect to the precipitation rate, thus analyzing the stability and symmetry properties of the emanating patterns. Based on the numerical bifurcation analysis, we have found new patterns, which form due to the onset of secondary bifurcations from the primary Turing instability, thus giving rise to a multistability of asymmetric solutions.

植被动力学PDE模型图灵和对称破缺模式的数值分岔分析。
研究了缺水地区植被动态格局形成的机制。我们的分析是基于一组两个反应扩散型的偏微分方程(PDEs)和一个描述毒性对生物量依赖的常微分方程(ODE)。我们在一维有限空间中进行线性稳定性分析,我们解析地推导出图灵不稳定性出现的条件,这些条件导致了齐次解产生的时空模式,并提供了它与域大小的依赖性。此外,我们进行了数值分岔分析,以研究非均匀解的模式形成,相对于降水速率,从而分析了发射模式的稳定性和对称性。在分岔分析的基础上,我们发现了非对称解的多重稳定性,这些新模式是由初级图灵不稳定性开始的二次分岔而形成的。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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