Chimera and cluster collective states in a dispersal ecological network under state-dependent feedback control and complex habitat structure.

IF 1.8 4区 数学 Q3 ECOLOGY Journal of Biological Dynamics Pub Date : 2021-12-01 DOI:10.1080/17513758.2021.1992518
Yi Yang, Lirong Liu, Changcheng Xiang, Wenjie Qin
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Abstract

Pest control based on an economic threshold (ET) can effectively prevent excessive pest control measures such as pesticide abuse and overharvesting. The instinctive dispersal of pest populations in biological network patches for better survival poses challenges for pest management. As long as the pest density is controlled below the economic threshold and no pest outbreak occurs, the aim of pest management can be achieved and it is not necessary to completely remove the pests. This study focuses on the issues of chimera states and cluster solutions in regular bidirectional biological networks with state-dependent impulsive pest management. We consider the influence of two different control modes on the system states, namely global control and local control. Local control is found to be more likely to induce the chimera state. In addition, in the local coupling mode, a higher coupling strength is more likely to generate a coherent state, whereas a lower coupling strength is more likely to generate chimera and incoherent states. Furthermore, the cluster size is inversely related to the coupling strength under local coupling and global control.

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状态依赖反馈控制和复杂生境结构下弥散生态网络中的嵌合体和集群集体状态。
基于经济阈值(ET)的虫害防治可以有效防止滥用农药和过度采收等过度虫害防治措施。为了更好地生存,害虫种群本能地在生物网络斑块中扩散,这对害虫管理提出了挑战。只要将有害生物密度控制在经济阈值以下,不发生病虫害暴发,就可以达到有害生物治理的目的,不需要完全消灭有害生物。本文主要研究了具有状态依赖脉冲害虫管理的规则双向生物网络的嵌合体状态和聚类解问题。我们考虑了两种不同的控制模式对系统状态的影响,即全局控制和局部控制。局部控制更容易诱导嵌合体状态。此外,在局部耦合模式下,高耦合强度更容易产生相干态,而低耦合强度更容易产生嵌合态和非相干态。此外,在局部耦合和全局控制下,聚类大小与耦合强度成反比。
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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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