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Spatiotemporal Patterns Formed by a Discrete Nutrient-Phytoplankton Model with Time Delay

机译:由离散的营养 - 浮游植物模型形成时滞的时滞模型

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In this research, a continuous nutrient-phytoplankton model with time delay and Michaelis–Menten functional response is discretized to a spatiotemporal discrete model. Around the homogeneous steady state of the discrete model, Neimark–Sacker bifurcation and Turing bifurcation analysis are investigated. Based on the bifurcation analysis, numerical simulations are carried out on the formation of spatiotemporal patterns. Simulation results show that the diffusion of phytoplankton and nutrients can induce the formation of Turing-like patterns, while time delay can also induce the formation of cloud-like pattern by Neimark–Sacker bifurcation. Compared with the results generated by the continuous model, more types of patterns are obtained and are compared with real observed patterns.
机译:在该研究中,将具有时间延迟和Michaelis-Menten功能反应的连续营养素-Phytoplankton模型被离散地分散到时空离散模型。围绕离散模型的均匀稳态,研究了NeiMark-Sacker分叉和图灵分叉分析。基于分叉分析,对时尚图案的形成进行了数值模拟。仿真结果表明,浮游植物和营养素的扩散可以诱导形成样图案的形成,而时间延迟也可以通过Neimark-Sacker分叉形成云样图案的形成。与由连续模型产生的结果相比,获得了更多类型的图案,并与真实观察的图案进行比较。

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