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A simple Markovian individual-based model as a means of understanding forest dynamics

机译:一个简单的基于马尔科夫个体的模型作为理解森林动力学的一种手段

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The forests are ecological systems of great complexity which present interaction phenomena associated with the competition between individuals of the same and of different species. This competition is about access to resources (light, water, nutrients, etc.). The scales of forest ecosystems are very long. For this reason we use in this framework Markovian modelling for space and time evolution of population distribution, thanks to an individual-based model in the form of a stochastic branching process. Understanding the behaviour of individual-based models of forest dynamics becomes difficult as their complexity increases. A useful strategy consists in simplifying parts of the original model in order to simulate a simplified version of forest dynamics. This strategy is adopted to understand the spatial pattern structured population in a simple individual-based model. The model is made of two components: birth or recruitment and death (natural mortality and mortality due to competition). The interplay between the spatial pattern of trees and the- competition/dispersion level is thus understood and the excessive impact of the low dispersion that favours the establishment of clusters is diagnosed.
机译:森林是高度复杂的生态系统,呈现出与同一物种和不同物种之间的竞争有关的相互作用现象。这场比赛是关于获取资源(光,水,养分等)的。森林生态系统的规模非常长。因此,由于随机分支过程形式的基于个人的模型,我们在此框架中使用马尔可夫模型进行人口分布的时空演化。随着森林复杂性的增加,了解基于个体的森林动力学模型的行为变得困难。一种有用的策略是简化原始模型的各个部分,以模拟森林动力学的简化版本。采用这种策略可以在基于个人的简单模型中理解空间格局结构化的种群。该模型由两个部分组成:出生或征募与死亡(自然死亡率和竞争引起的死亡率)。因此,可以理解树木的空间模式与竞争/分散水平之间的相互作用,并且可以诊断出低分散的过度影响,有利于集群的建立。

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