Descriptive Modeling of the Dynamical Systems and Determination of Feedback Homeostasis at Different Levels of Life Organization

Acta Biotheor. 2018 Sep;66(3):177-199. doi: 10.1007/s10441-018-9321-3. Epub 2018 May 24.

Abstract

The state-of-art research in the field of life's organization confronts the need to investigate a number of interacting components, their properties and conditions of sustainable behaviour within a natural system. In biology, ecology and life sciences, the performance of such stable system is usually related to homeostasis, a property of the system to actively regulate its state within a certain allowable limits. In our previous work, we proposed a deterministic model for systems' homeostasis. The model was based on dynamical system's theory and pairwise relationships of competition, amensalism and antagonism taken from theoretical biology and ecology. However, the present paper proposes a different dimension to our previous results based on the same model. In this paper, we introduce the influence of inter-component relationships in a system, wherein the impact is characterized by direction (neutral, positive, or negative) as well as its (absolute) value, or strength. This makes the model stochastic which, in our opinion, is more consistent with real-world elements affected by various random factors. The case study includes two examples from areas of hydrobiology and medicine. The models acquired for these cases enabled us to propose a convincing explanation for corresponding phenomena identified by different types of natural systems.

Keywords: Dynamical systems; Feedback relations; Homeostasis; Markov chains; Stochastic models.

MeSH terms

  • Adolescent
  • Algorithms
  • Animals
  • Armenia
  • Biomass
  • Ecology
  • Eutrophication
  • Heart / physiology
  • Heart Diseases / physiopathology
  • Homeostasis
  • Humans
  • Life
  • Markov Chains
  • Massachusetts
  • Models, Biological
  • Models, Cardiovascular
  • Models, Statistical
  • Normal Distribution
  • Probability
  • Species Specificity
  • Stochastic Processes*
  • Systems Biology*
  • Zooplankton