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Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
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Updated: Jun 22, 2026

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
07:41

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Published on: July 30, 2019

How could the Gompertz-Makeham law evolve.

A Golubev1

  • 1Institute of Experimental Medicine, 12 Akademika Pavlova Str., Saint-Petersburg 197376, Russia. lxglbv@rambler.ru

Journal of Theoretical Biology
|June 4, 2009
PubMed
Summary

Biological mortality arises from chemical decomposition, with aging linked to declining disintegration barriers (E). This explains age-related mortality patterns and aligns with antagonistic pleiotropy theory in aging research.

Area of Science:

  • Biophysics
  • Evolutionary Biology
  • Biochemistry

Background:

  • Life's origin is rooted in chemical processes.
  • Biological systems inherit chemical decomposition kinetics.
  • The Arrhenius equation describes chemical decomposition (k = A*exp(-E/RT)).

Purpose of the Study:

  • To propose a model for biological mortality kinetics originating from chemical decomposition.
  • To explain age-related mortality patterns and survivorship curves.
  • To link functional decline to resource allocation and antagonistic pleiotropy.

Main Methods:

  • Applying chemical decomposition kinetics (Arrhenius equation) to biological mortality.
  • Developing numerical models to simulate functional changes and mortality.

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  • Utilizing the generalized Gompertz-Makeham law to describe mortality trajectories.
  • Main Results:

    • Mortality kinetics in biology shifts focus from temperature (T) to disintegration barrier energy (E).
    • Declining E with age leads to exponential mortality rise and characteristic survivorship curves.
    • Model supports antagonistic pleiotropy: functional decline enhances progeny investment.

    Conclusions:

    • Biological aging and mortality are explained by evolved chemical decomposition kinetics.
    • The model elucidates mid-age functional decline and its deceleration.
    • Initial vitality correlates positively with the rate of aging, consistent with evolutionary trade-offs.