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富集悖论:一种具有记忆的分数阶微分方法。

Paradox of enrichment: A fractional differential approach with memory.

作者信息

Rana Sourav, Bhattacharya Sabyasachi, Pal Joydeep, N'Guérékata Gaston M, Chattopadhyay Joydev

机构信息

Agricultural and Ecological Research Unit, Indian Statistical Institute, 203, B.T. Road, Kolkata 700108, India.

Department of Mathematics, Morgan State University, Baltimore, MD 21251, USA.

出版信息

Physica A. 2013 Sep 1;392(17):3610-3621. doi: 10.1016/j.physa.2013.03.061. Epub 2013 Apr 10.

Abstract

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.

摘要

罗森茨威格提出的富集悖论(PoE)[M. 罗森茨威格,《富集悖论》,《科学》171(1971)385 - 387]仍是生态学中的一个基本问题。大多数解决方案是在个体物种组织层面提出的,而缺乏群落层面的解决方案。了解学习和记忆如何改变对物种的行为反应是在物种和群落层面建立关键联系的一个关键因素。通过这两个组织层面解决PoE可被解释为微观和宏观层面的解决方案。分数阶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一个出色的工具。这些导数可以通过同时考虑的两个时间尺度进行物理解释:理想的、均匀流动的均匀局部时间,以及宇宙(非均匀)非局部时间。已经提出了几种机制和理论来解决PoE问题,但由于大多数研究都集中在局部效应而忽略了捕捉记忆的非局部效应,所以仍然缺乏一个被普遍接受的理论。在这里,我们构建了罗森茨威格模型的分数阶对应模型,并分析了一个系统的稳定性行为。我们得出结论,记忆效应参数存在一个阈值,超过该阈值,罗森茨威格模型是稳定的,并且可以用作通过分数阶微分方程从新视角解决PoE的潜在工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c00a/7127129/e3cddafed806/gr1.jpg

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