Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Stochastic models for toxicant-stressed populations.

T C Gard1

  • 1Department of Mathematics, University of Georgia, Athens, 30602.

Bulletin of Mathematical Biology
|September 1, 1992
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Extinction in predator-prey models with time delay.

Mathematical biosciences·1993
Same author

Top predator persistence in differential equation models of food chains: the effects of omnivory and external forcing of lower trophic levels.

Journal of mathematical biology·1982
See all related articles

This study establishes conditions for invariant distributions in stochastic population growth models. It examines toxicant impacts on growth rates and compares findings with ordinary differential equation models.

Area of Science:

  • Ecology
  • Mathematical Biology
  • Stochastic Processes

Background:

  • Population dynamics are often modeled using differential equations.
  • Stochastic models offer a more realistic representation by incorporating randomness.
  • Understanding population persistence requires analyzing invariant distributions.

Purpose of the Study:

  • To determine conditions for the existence of an invariant distribution in stochastic population growth models of Ito type.
  • To analyze the influence of toxicants on population growth rates within these stochastic models.
  • To compare results with existing ordinary differential equation (ODE) models.

Main Methods:

  • Analysis of stochastic differential equations (SDEs) using Ito calculus.
  • Derivation of conditions for the existence of invariant measures.

Related Experiment Videos

  • Interpretation of toxicant effects on intrinsic growth rates.

    • Main Results:

    • Established criteria for the existence of a stationary distribution in stochastic growth models.
    • Demonstrated how toxicant-induced changes in growth rates affect population persistence.
    • Identified differences and similarities with ODE model predictions.

    Conclusions:

    • The study provides a framework for analyzing population stability under stochasticity and toxicant exposure.
    • Results offer insights into the long-term viability of populations in fluctuating environments.
    • Highlights the importance of stochastic interpretations in ecological modeling.