相互作用生态群落Lotka-Volterra模型的主方程和相对物种丰度分布。

IF 1.5 4区 生物学 Q4 Agricultural and Biological Sciences
Armando Bazzani, Claudia Sala, Enrico Giampieri, Gastone Castellani
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引用次数: 3

摘要

描述:了解控制相互作用物种动态的因素是生态学的一个基本问题。不同物种间相互作用的性质通常不被完全理解,但根据生态位模型的预测,物种相互作用在生态系统特性中起着重要作用。然而,最近的研究指出,Hubbell提出的非相互作用物种与周围环境外部源的中性假设可以解释生态系统达到静止状态时的相对物种丰度分布。本文利用适应度景观的概念,引入了一个随机动态模型,描述了不同群落在平稳状态下的演化。平均动力学可以与具有相互作用的Lotka-Volterra方程组相关联。然后推导出满足热力学平衡详细平衡条件的主方程,并可以解析计算稳态附近的相对物种丰度分布为多项负分布。这些结果提出了一种综合理论的可能方法,该理论结合了生态位理论和哈贝尔的RSA分布中性理论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Master equation and relative species abundance distribution for Lotka-Volterra models of interacting ecological communities.
DESCRIPTION Understanding the factors that control the dynamics of interacting species is a fundamental problem in ecology. The nature of the interactions among different species is usually not completely understood, but it is assumed that the species interaction plays an important role in the ecosystem properties as predicted by the niches models for an ecosystem. However, recent studies point out as the neutral hypothesis proposed by Hubbell of non-interacting species with an external source from the surrounding environment, allows to explain the relative species abundance distribution when the ecosystem has reached a stationary situation. In this paper we use the concept of fitness landscape to introduce a random dynamical model that describes the evolution of different communities near a stationary situation. The average dynamics can be associated to a system of Lotka-Volterra equations with mutualistic interactions. Then we derive a Master equation that satisfies the detailed balance condition of thermodynamical equilibria and allows to analytically compute the relative species abundance distribution near the stationary state as a multinomial negative distribution. These results suggest a possible approach to a synthetic theory that joins the niche theories and the Hubbell's neutral theory for RSA distribution.
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来源期刊
Theoretical Biology Forum
Theoretical Biology Forum 生物-生物学
CiteScore
0.70
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