通过减少个人成长来实现等级竞争

IF 2.2 4区 数学 Q2 BIOLOGY
Carles Barril, Àngel Calsina, Odo Diekmann, József Z. Farkas
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引用次数: 0

摘要

我们考虑的是一个按大小分级的种群,即每个个体的生长速度只取决于较大个体的存在。举个具体的例子,我们可以想象一下森林,在森林中,一棵树的光照入射率(以及它的生长速度)会受到高大树木遮挡的影响。这种大小结构的种群模型的经典公式是一个一阶准线性偏微分方程,并配有一个非局部边界条件。不过,该模型也可以表述为人口出生率的延迟方程,更确切地说,是标量更新方程。在讨论了延迟方程的好求解性之后,我们分析了根据模型的函数参数,该方程可以有多少个静态出生率。我们特别指出,在合理且相当一般的假设条件下,除了微不足道的出生率(与没有个体且人口出生率为零的状态相关)之外,只能存在一种静态出生率。我们给出了这种非三稳态出生率存在的条件,并利用延迟方程的线性化稳定性原理分析了它的稳定性。最后,我们将结果与该模型的另一种偏微分方程公式联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On hierarchical competition through reduction of individual growth

We consider a population organised hierarchically with respect to size in such a way that the growth rate of each individual depends only on the presence of larger individuals. As a concrete example one might think of a forest, in which the incidence of light on a tree (and hence how fast it grows) is affected by shading by taller trees. The classic formulation of a model for such a size-structured population employs a first order quasi-linear partial differential equation equipped with a non-local boundary condition. However, the model can also be formulated as a delay equation, more specifically a scalar renewal equation, for the population birth rate. After discussing the well-posedness of the delay formulation, we analyse how many stationary birth rates the equation can have in terms of the functional parameters of the model. In particular we show that, under reasonable and rather general assumptions, only one stationary birth rate can exist besides the trivial one (associated to the state in which there are no individuals and the population birth rate is zero). We give conditions for this non-trivial stationary birth rate to exist and analyse its stability using the principle of linearised stability for delay equations. Finally, we relate the results to the alternative, partial differential equation formulation of the model.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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