Literature DB >> 2794800

A nonautonomous model of population growth.

R R Vance1, E A Coddington.   

Abstract

With x = population size, the nonautonomous equation x = xf(t, x) provides a very general description of population growth in which any of the many factors that influence the growth rate may vary through time. If there is some fixed length of time (usually long) such that during any interval of this length the population experiences environmental variability representative of the variation that occurs in all time, then definite conclusions about the population's long-term behavior apply. Specifically, conditions that produce population persistence can be distinguished from conditions that cause extinction, and the difference between any pair of solutions eventually converges to zero. These attributes resemble corresponding features of the related autonomous population growth model x = xf(x).

Mesh:

Year:  1989        PMID: 2794800     DOI: 10.1007/bf00288430

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  10 in total

1.  Density-dependent selection in a random environment: An evolutionary process that can maintain stable population dynamics.

Authors:  M Turelli; D Petry
Journal:  Proc Natl Acad Sci U S A       Date:  1980-12       Impact factor: 11.205

2.  Random environments and stochastic calculus.

Authors:  M Turelli
Journal:  Theor Popul Biol       Date:  1977-10       Impact factor: 1.570

3.  Persistence in population models with demographic fluctuations.

Authors:  T G Hallam; M Zhien
Journal:  J Math Biol       Date:  1986       Impact factor: 2.259

4.  Logistic population growth under random dispersal.

Authors:  H C Tuckwell; J A Koziol
Journal:  Bull Math Biol       Date:  1987       Impact factor: 1.758

5.  On density and extinction in continuous population models.

Authors:  T G Hallam; M Zhien
Journal:  J Math Biol       Date:  1987       Impact factor: 2.259

6.  The average lifetime of a population in a varying environment.

Authors:  E G Leigh
Journal:  J Theor Biol       Date:  1981-05-21       Impact factor: 2.691

7.  Logistic growth in the presence of non-white environmental noise.

Authors:  D E Strebel
Journal:  J Theor Biol       Date:  1980-08-21       Impact factor: 2.691

8.  Conditions for the existence of stationary densities for some two-dimensional diffusion processes with applications in population biology.

Authors:  M Turelli; J H Gillespie
Journal:  Theor Popul Biol       Date:  1980-04       Impact factor: 1.570

9.  Persistence times of populations with large random fluctuations.

Authors:  F B Hanson
Journal:  Theor Popul Biol       Date:  1978-08       Impact factor: 1.570

10.  Periodic solutions of some ecological models.

Authors:  F Brauer
Journal:  J Theor Biol       Date:  1977-11-07       Impact factor: 2.691

  10 in total
  4 in total

1.  Stochastic models for toxicant-stressed populations.

Authors:  T C Gard
Journal:  Bull Math Biol       Date:  1992-09       Impact factor: 1.758

2.  Plant population growth and competition in a light gradient: a mathematical model of canopy partitioning.

Authors:  Richard R Vance; Andrew L Nevai
Journal:  J Theor Biol       Date:  2006-10-21       Impact factor: 2.691

3.  Robust permanence for ecological equations with internal and external feedbacks.

Authors:  Swati Patel; Sebastian J Schreiber
Journal:  J Math Biol       Date:  2017-10-26       Impact factor: 2.259

4.  Incorporating prior knowledge improves detection of differences in bacterial growth rate.

Authors:  Lydia M Rickett; Nick Pullen; Matthew Hartley; Cyril Zipfel; Sophien Kamoun; József Baranyi; Richard J Morris
Journal:  BMC Syst Biol       Date:  2015-09-21
  4 in total

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