Stationary and non-stationary pattern formation over fragmented habitat. (September 2022)

• Record Type: Journal Article
• Authors: Banerjee, Malay; Pal, Swadesh; Roy Chowdhury, Pranali
• Is Part Of: Chaos, solitons and fractals. Volume 162(2022)
• Publication Date: 2022-09
• Subjects: Allee effect -- Hopf bifurcation -- Turing bifurcation -- Spatial pattern -- Transients; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2022.112412
• Languages: English
• ISSNs: 0960-0779

Abstract

Abstract: Spatio-temporal pattern formation over the square and rectangular domain has received significant attention from researchers. A wide range of stationary and non-stationary patterns produced by two interacting populations is abundant in the literature. Fragmented habitats are widespread in reality due to the irregularity of the landscape. This work considers a prey-predator model capable of producing a wide range of stationary and time-varying patterns over a complex habitat. The complex habitat is assumed to have consisted of two rectangular patches connected through a corridor. Our main aim is to explain how the shape and size of the fragmented habitat regulate the spatio-temporal pattern formation at the initial time. The analytical conditions are derived to ensure the existence of a stationary pattern and illustrate the role of the most unstable eigenmodes in determining the number of patches for the stationary pattern. Exhaustive numerical simulations help to explain the effect of the spatial domain size and shape on the transient patterns and the duration of the transients. Highlights: Spatio-temporal pattern formation by a Bazykin type model is considered. The range of unstable modes related to Turing instability is identified. Pattern formation is considered over a fragmented domain. Stationary and time-varying spatial patterns are obtained. Transient patterns and their duration are studied numerically.