A cellular automata model for a community comprising two plant species of different growth forms

Abstract

A cellular automata computer model for the interactions between two plant species of different growth forms-the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb-is considered. Computer experiments on the self maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phy togenous field have been conducted. As has been shown, all the studied factors determine the number of indi viduals and self sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long term developmental dynamics of the plants belonging to the selected growth forms.

Distribution pattern simulation of multiple emergent plants in river riparian zones

“…Previous studies on plant distribution simulation have focused on emergent plant communities, and have not reflected the competitive relationship between emergent plants in different niches (Balzter et al, 1998; Frolov et al, 2015; Wang et al, 2003). Interspecies competition, though, will have a profound impact on the spread of emergent plants.…”

“…It is feasible to use CA to simulate and predict the dynamic changes of emergent plants in RRZ. This model replaces the conventional method of obtaining the fixed transformation rules of CA in time and space based on spatial statistics, and effectively avoids the inference of complex system uncertainty (Fan et al, 2019; Frolov et al, 2015). It realizes the dynamic evolution simulation of multiple emergent plant population distribution in RRZ.…”

“…The CA model is used to simulate and predict the dynamic evolution process of the plant landscape, which reflects the law of plant distribution and spread. It proves that it is feasible to use the CA model to simulate the dynamic evolution of plant landscape (Frolov, Zubkova, & Komarov, 2015; Sprott, Bolliger, & David, 2002; Sui & Zeng, 2001; Wang, Kropff, Lammert, Christensen, & Hansen, 2003). Combining the data of the emergent plants observed on a small local scale with the neighbourhood transformation rules, the CA model is used to simulate the dynamic characteristics of the emergent plant community on a larger scale, which can reflect the overall evolutionary law of the emergent plant community (Ye, Chen, Blanckaert, & Ma, 2013).…”

Spatial Distribution of Organic Matter and Nitrogen in the Entic Podzols of the Prioksko-Terrasnyi Reserve and Its Relationship with the Structure of Forest Phytocenoses

“…Simulation of the dynamics of forest phytocenoses is mainly evolved towards creating individually oriented spatially distributed models of tree stands and ground vegetation, in which each plant is characterized by particular coordinates in the space of the modeling grid. It enables, for example, the calculation of the root nutrition zones of plants depending on the age, species-specific sizes, and growing conditions [20,36,38,55,57]. There are also approaches to modeling the dynamics of spatial microgroups of plants in the forest ground cover in relation to edaphic conditions of habitats [37].…”

Interspecific competition in perennial sedentary organisms: An individual‐based model

“…Earlier articles dealing with individual‐based spatial explicit modeling of the dynamics of a system comprising two plant species analyzed the influence of different traits not directly connected to the process of competition, such as different forms and rates of growth, mortality rate, or dispersal range on the outcome of interspecific competition (e.g., Dislich et al, 2010; Frolov et al, 2015), or dealing with outcomes of competition which are not directly connected to the dynamics of the system (e.g., age‐related decline in forest production [Berger et al, 2004] or performance and architecture of individuals [Bittebiere et al, 2012]).…”