论文标题

分析竞争指数在异质植物种群中引起的动力学:从基于个体的模型到宏观模型

Analysis of the dynamics induced by a competition index in a heterogeneous population of plants: from an individual-based model to a macroscopic model

论文作者

Della Noce, Antonin, Cournède, Paul-Henry

论文摘要

竞争指数是经常在生态学中使用的模型来说明密度和资源分布对植物种群增长的影响。他们允许通过在人群量表上集成相对易于收集的信息来定义简单的基于个体的模型,该信息通过平均场限制参数概括为宏观量表。尽管如此,据我们所知,在竞争指数上的条件或人口初始配置的条件下,很少有工作从数学上保证了从个人规模到人口规模的通过。我们在本文中考虑了文献中通常使用的竞争指数,这是根据植物尺寸及其各自的距离的度量,以成对潜力的平均水平表示。与有关混合效应模型的文献一致,假定种群是异质的,生长参数的个体差异。给出了初始配置的足够条件,以便很好地定义了以非线性微分方程制度的形式的总体动力学。然后,与无限拥挤的人群相关的平均场分布的特征是特征流动,并且还证明了对人口规模增加的分布的收敛。数值模拟说明了异质种群的动力学,并使用拉格朗日方案可视化平均场动力学。

Competition indices are models frequently used in ecology to account for the impact of density and resource distribution on the growth of a plant population. They allow to define simple individual-based models, by integrating information relatively easy to collect at the population scale, which are generalized to a macroscopic scale by mean-field limit arguments. Nevertheless, up to our knowledge, few works have studied under which conditions on the competition index or on the initial configuration of the population the passage from the individual scale to the population scale is mathematically guaranteed. We consider in this paper a competition index commonly used in the literature, expressed as an average over the population of a pairwise potential depending on a measure of plants' sizes and their respective distances. In line with the literature on mixed-effect models, the population is assumed to be heterogeneous, with inter-individual variability of growth parameters. Sufficient conditions on the initial configuration are given so that the population dynamics, taking the form of a system of non-linear differential equations, is well defined. The mean-field distribution associated with an infinitely crowded population is then characterized by the characteristic flow, and the convergence towards this distribution for an increasing population size is also proved. The dynamics of the heterogeneous population is illustrated by numerical simulations, using a Lagrangian scheme to visualize the mean-field dynamics.

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