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Paradox of enrichment: A fractional differential approach with memory

机译:浓缩悖论:带记忆的分数微分方法

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The paradox of enrichment (PoE) proposed by Rosenzweig [M. Rosenzweig, The paradox of enrichment, Science 171 (1971) 385-387] is still a fundamental problem in ecology. Most of the solutions have been proposed at an individual species level of organization and solutions at community level are lacking. Knowledge of how learning and memory modify behavioral responses to species is a key factor in making a crucial link between species and community levels. PoE resolution via these two organizational levels can be interpreted as a microscopic- and macroscopic-level solution. Fractional derivatives provide an excellent tool for describing this memory and the hereditary properties of various materials and processes. The derivatives can be physically interpreted via two time scales that are considered simultaneously: the ideal, equably flowing homogeneous local time, and the cosmic (inhomogeneous) non-local time. Several mechanisms and theories have been proposed to resolve the PoE problem, but a universally accepted theory is still lacking because most studies have focused on local effects and ignored non-local effects, which capture memory. Here we formulate the fractional counterpart of the Rosenzweig model and analyze the stability behavior of a system. We conclude that there is a threshold for the memory effect parameter beyond which the Rosenzweig model is stable and may be used as a potential agent to resolve PoE from a new perspective via fractional differential equations.
机译:Rosenzweig提出的浓缩悖论(PoE)[M. Rosenzweig,《致富悖论》,科学171(1971)385-387]仍然是生态学中的一个基本问题。大多数解决方案是在组织的单个物种级别上提出的,而在社区级别上则缺少解决方案。关于学习和记忆如何改变对物种的行为反应的知识是在物种与群落水平之间建立关键联系的关键因素。通过这两个组织级别的PoE解析可以解释为微观和宏观级别的解决方案。小数导数为描述这种记忆以及各种材料和过程的遗传特性提供了极好的工具。可以通过同时考虑的两个时标在物理上解释这些导数:理想的,相等地流动的均质本地时间和宇宙(非均质)非本地时间。已经提出了几种机制和理论来解决PoE问题,但是由于大多数研究都集中在捕获内存的局部效应而忽略了非局部效应,因此仍缺乏一种普遍接受的理论。在这里,我们制定了Rosenzweig模型的分数对应物,并分析了系统的稳定性行为。我们得出结论,对于记忆效应参数存在一个阈值,超过该阈值的Rosenzweig模型是稳定的,并且可以用作通过分数阶微分方程从新角度解析PoE的潜在代理。

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