• Journal of Environmental Science International
• /
• v.20 no.2
• /
• pp.155-161
• /
• 2011

In application and discussion of population structure and phenotypic divergence in plant community, the classic Lotka-Volterra models of competition and spatial model are conceived as a mechanism that is composed by multiple interacting processes. Both the Lotka-Volterra and spatial simulation formulae predict that species diversity increases with genotypic richness (GR). The two formulae are also in agreement that species diversity generally decreases within increasing niche breadth (NB) and increases with increasing potential genotypic range (PGR). Across the entire parameter space in the Lotka-Volterra model and most of the parameter space in the spatial simulations, variance in community composition decreased with increasing genotypic richness. This was, in large part, a consequence of selecting genotypes randomly from a set pool.

• Journal for History of Mathematics
• /
• v.33 no.3
• /
• pp.167-177
• /
• 2020

Cooperative behavior may seem contrary to the notion of natural selection and adaptation, but is widely observed in nature, from the genetic level to the organism. The origin and persistence of cooperative behavior has long been a mystery to scientists studying evolution and ecology. One of the important research topics in the field of evolutionary ecology and behavioral ecology is to find out why cooperation is maintained over time. In this paper we take a historical overview of mathematical models representing cooperative relationships from the perspective of mathematical biology, which studies population dynamics between interacting biological groups, and analyze the mathematical characteristics and meanings of these cooperative models.

• Journal for History of Mathematics
• /
• v.26 no.2_3
• /
• pp.197-210
• /
• 2013

The late 18C Malthus studied population growth for the first time, Verhulst the logistic model in 19C and, after that, the study of the predation competition between two species resulted in the appearance of Lotka-Volterra model and modified model supported by Gause's experiment with bacteria. Instable coexistence equilibrium being found, Solomon and Holling proposed functional and numerical response considering limited abilities of predator on prey, which applied to Lotka Volterra model. Nicholson and Baily, considering the predation between host and parasitoid in discrete time, made a model. In 20C there were developed various models of disease dynamics with the help of mathematics and real data and named SIS, SIR or SEIR on the basis of dynamical phenomena.

• Journal for History of Mathematics
• /
• v.25 no.1
• /
• pp.45-56
• /
• 2012

Mathematical biology has been recognized its importance recently and widely studied in the fields of mathematics, biology, medical sciences, and immunology. Mathematical ecology is an academic field that studies how populations of biological species change as times flows at specific locations in their habitats. It was the earliest form of the research field of mathematical biology and has been providing its basis. This article deals with various form of interactions between two biological species in a common habitat. Mathematical models of predator-prey type, competitive type, and simbiotic type are investigated.

• Korean Journal of Ecology and Environment
• /
• v.37 no.3 s.108
• /
• pp.304-312
• /
• 2004

The transient dynamics of three-trophic populations (prey, predator, and super predator) using ratio-dependent models responding to environmental impacts is analyzed. Environmental factors were divided into two parts: periodic factor (e.g., temperature) and general noise. Periodic factor was addressed as a frequency and bias, while general noise was expressed as a Gaussian distribution. Temperature bias ${\varepsilon}$, temperature frequency ${\Omega}$, and Gaussian noise amplitude ${\`{O}}$ accordingly revealed diverse status of population dynamics in three-trophic food chain, including extinction of species. The model showed stable limit cycles and strange attractors in the long-time behavior depending upon various values of the parameters. The dynamic behavior of the system appeared to be sensitive to changes in environmental input. The parameters of environmental input play an important role in determining extinction time of super predator and predator populations.