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 Concept Videos

Conservation of Declining Populations02:07

Conservation of Declining Populations

Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
Modeling with Differential Equations01:25

Modeling with Differential Equations

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...
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.However, realistic environmental conditions limit the number of...
Exponential Equations for Modeling Growth01:26

Exponential Equations for Modeling Growth

Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is the relative...
Genetic Drift03:33

Genetic Drift

Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.Life is not fair. A deer grazing contentedly in a field can have her meal cut tragically short by a bolt of lightning. If the doomed doe is one of only three in the population, 1/3 of the population’s gene pool is lost. Random events like this can...
Speciation Rates01:07

Speciation Rates

Speciation can proceed at markedly different rates, and evolutionary biologists commonly describe these differences through the models of gradualism and punctuated equilibrium. Both patterns explain how new species arise, but they differ in the tempo and continuity of evolutionary change. In both cases, evolutionary change arises from heritable variation within populations, with natural selection often shaping traits that improve survival and reproduction under specific environmental conditions.

You might also read

Related Articles

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

Sort by
Same author

Short-time statistics of extinction and blowup in reaction kinetics.

Physical review. E·2026
Same author

A root-soil association index reveals life-history strategies of arbuscular mycorrhizal fungi.

The New phytologist·2026
Same author

Scalable and robust regression models for continuous proportional data.

Journal of the American Statistical Association·2026
Same author

Fish and Zooplankton Co-Responses to Environmental Gradients Under Different Climate Change Scenarios.

Global change biology·2026
Same author

A digital twin for real-time biodiversity forecasting with citizen science data.

Nature ecology & evolution·2026
Same author

Short-time blowup statistics of a Brownian particle in repulsive potentials.

Physical review. E·2026

Related Experiment Video

Updated: Jun 9, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Stochastic models of population extinction.

Otso Ovaskainen1, Baruch Meerson

  • 1Metapopulation Research Group, Department of Biosciences, University of Helsinki, FI-00014, Finland. otso.ovaskainen@helsinki.fi

Trends in Ecology & Evolution
|September 3, 2010
PubMed
Summary

Population persistence relies on environmental factors. Recent theoretical physics research offers new tools to analyze population dynamics and predict extinction risks.

Area of Science:

  • Theoretical Ecology
  • Population Dynamics
  • Mathematical Biology

Background:

  • Population persistence is influenced by biotic and abiotic factors.
  • Demographic stochasticity and environmental variation impact extinction times.
  • Environmental noise autocorrelation ('color') is a key area of recent focus.

Purpose of the Study:

  • To explore the application of theoretical physics tools to stochastic population dynamics.
  • To enhance understanding of population extinction processes.
  • To investigate the role of environmental noise in population persistence.

Main Methods:

  • Analysis of large fluctuations in stochastic population dynamics.
  • Application of theoretical physics methodologies.

More Related Videos

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Resurrection of Dormant Daphnia magna: Protocol and Applications
07:37

Resurrection of Dormant Daphnia magna: Protocol and Applications

Published on: January 19, 2018

Related Experiment Videos

Last Updated: Jun 9, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Resurrection of Dormant Daphnia magna: Protocol and Applications
07:37

Resurrection of Dormant Daphnia magna: Protocol and Applications

Published on: January 19, 2018

  • Characterization of extinction pathways.
  • Main Results:

    • Theoretical physics tools provide powerful methods for analyzing population dynamics.
    • Insights into extinction times and pathways are gained through fluctuation analysis.
    • Understanding of environmental noise effects on population persistence is advanced.

    Conclusions:

    • Recent theoretical physics research offers novel approaches to studying population dynamics.
    • These methods yield sharp insights into extinction processes.
    • Significant potential exists for applying these tools in theoretical biology and conservation.