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Taxis-driven complex patterns of a plankton model

Mengxin Chen, Seokjun Ham, Junseok Kim

2024Chaos An Interdisciplinary Journal of Nonlinear Science13 citationsDOIOpen Access PDF

Abstract

This paper reports an important conclusion that self-diffusion is not a necessary condition for inducing Turing patterns, while taxis could establish complex pattern phenomena. We investigate pattern formation in a zooplankton-phytoplankton model incorporating phytoplankton-taxis, where phytoplankton-taxis describes the zooplankton that tends to move toward the high-densities region of the phytoplankton population. By using the phytoplankton-taxis sensitivity coefficient as the Turing instability threshold, one shows that the model exhibits Turing instability only when repulsive phytoplankton-taxis is added into the system, while the attractive-type phytoplankton-taxis cannot induce Turing instability of the system. In addition, the system does not exhibit Turing instability when the phytoplankton-taxis disappears. Numerically, we display the complex patterns in 1D, 2D domains and on spherical and zebra surfaces, respectively. In summary, our results indicate that the phytoplankton-taxis plays a pivotal role in giving rise to the Turing pattern formation of the model. Additionally, these theoretical and numerical results contribute to our understanding of the complex interaction dynamics between zooplankton and phytoplankton populations.

Topics & Concepts

TaxisPhytoplanktonTuringZooplanktonPopulationPhysicsOceanographyStatistical physicsComputer scienceBiologyEcologyGeologyNutrientSociologyBotanyProgramming languageDemographyNonlinear Dynamics and Pattern FormationMathematical and Theoretical Epidemiology and Ecology ModelsMathematical Biology Tumor Growth
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