Department of Computer Science and languages, University of Málaga, Spain.
Artif Life. 2012 Spring;18(2):199-222. doi: 10.1162/artl_a_00059. Epub 2012 Feb 22.
Understanding the dynamics of biodiversity has become an important line of research in theoretical ecology and, in particular, conservation biology. However, studying the evolution of ecological communities under traditional modeling approaches based on differential calculus requires species' characteristics to be predefined, which limits the generality of the results. An alternative but less standardized methodology relies on intensive computer simulation of evolving communities made of simple, explicitly described individuals. We study here the formation, evolution, and diversity dynamics of a community of virtual plants with a novel individual-centered model involving three different scales: the genetic, the developmental, and the physiological scales. It constitutes an original attempt at combining development, evolution, and population dynamics (based on multi-agent interactions) into one comprehensive, yet simple model. In this world, we observe that our simulated plants evolve increasingly elaborate canopies, which are capable of intercepting ever greater amounts of light. Generated morphologies vary from the simplest one-branch structure of promoter plants to a complex arborization of several hundred thousand branches in highly evolved variants. On the population scale, the heterogeneous spatial structuration of the plant community at each generation depends solely on the evolution of its component plants. Using this virtual data, the morphologies and the dynamics of diversity production were analyzed by various statistical methods, based on genotypic and phenotypic distance metrics. The results demonstrate that diversity can spontaneously emerge in a community of mutually interacting individuals under the influence of specific environmental conditions.
理解生物多样性的动态变化已经成为理论生态学,特别是保护生物学的一个重要研究方向。然而,在基于微积分的传统建模方法下研究生态群落的进化时,需要预先定义物种的特征,这限制了结果的普遍性。另一种方法则不太标准化,但依赖于对由简单、明确描述的个体组成的进化群落进行密集的计算机模拟。在这里,我们研究了一个具有新颖个体中心模型的虚拟植物群落的形成、进化和多样性动态,该模型涉及三个不同的尺度:遗传、发育和生理尺度。这是将发育、进化和种群动态(基于多主体交互)结合到一个综合而简单的模型中的一次原创尝试。在这个世界中,我们观察到我们模拟的植物进化出越来越复杂的树冠,这些树冠能够拦截越来越多的光线。生成的形态从最简单的启动植物的单枝结构到高度进化的变体中的几十万分支的复杂分枝各不相同。在种群尺度上,植物群落在每一代的异质空间结构仅取决于其组成植物的进化。使用这个虚拟数据,通过基于基因型和表型距离度量的各种统计方法,分析了形态和多样性产生的动态。结果表明,在特定环境条件的影响下,相互作用的个体群落中可以自发产生多样性。