Literature DB >> 15990117

Density-dependence as a size-independent regulatory mechanism.

Harold P de Vladar1.   

Abstract

The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.

Mesh:

Year:  2005        PMID: 15990117     DOI: 10.1016/j.jtbi.2005.05.014

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

1.  In vitro ovine articular chondrocyte proliferation: experiments and modelling.

Authors:  L Mancuso; M I Liuzzo; S Fadda; M Pisu; A Cincotti; M Arras; G La Nasa; A Concas; G Cao
Journal:  Cell Prolif       Date:  2010-04-14       Impact factor: 6.831

2.  Experimental analysis and modelling of in vitro proliferation of mesenchymal stem cells.

Authors:  L Mancuso; M I Liuzzo; S Fadda; M Pisu; A Cincotti; M Arras; E Desogus; F Piras; G Piga; G La Nasa; A Concas; G Cao
Journal:  Cell Prolif       Date:  2009-07-10       Impact factor: 6.831

3.  Oscillations in growth of multicellular tumour spheroids: a revisited quantitative analysis.

Authors:  A S Gliozzi; C Guiot; R Chignola; P P Delsanto
Journal:  Cell Prolif       Date:  2010-08       Impact factor: 6.831

4.  Simultaneous identification of growth law and estimation of its rate parameter for biological growth data: a new approach.

Authors:  Amiya Ranjan Bhowmick; Gaurangadeb Chattopadhyay; Sabyasachi Bhattacharya
Journal:  J Biol Phys       Date:  2014-01-10       Impact factor: 1.365

5.  Measuring differences between phenomenological growth models applied to epidemiology.

Authors:  Raimund Bürger; Gerardo Chowell; Leidy Yissedt Lara-Díaz
Journal:  Math Biosci       Date:  2021-02-08       Impact factor: 2.144

6.  Scaling, growth and cyclicity in biology: a new computational approach.

Authors:  Pier Paolo Delsanto; Antonio S Gliozzi; Caterina Guiot
Journal:  Theor Biol Med Model       Date:  2008-02-29       Impact factor: 2.432

  6 in total

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