Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Population Growth

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...

Genetic Drift

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...

Modeling with Differential Equations

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...

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

Conservation of Declining Populations

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.

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...

You might also read

Related Articles

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

Sort by

Same author

Increased head-turning, hyperactivity and low-penetrance circling behaviour in mice lacking ZPLD1, a protein that scaffolds the cupula to the roof of the ampulla.

Hearing research·2026

Same author

A tiger is not always a satyr: role of male mating behaviour in interspecific mating interactions between Aedes aegypti and Aedes albopictus.

Parasites & vectors·2026

Same author

A digital imagery-competing task intervention for stopping intrusive memories in trauma-exposed health-care staff during the COVID-19 pandemic in the UK: a Bayesian adaptive randomised clinical trial.

The lancet. Psychiatry·2026

Same author

The impact of structured higher-order interactions on ecological network stability.

Theoretical ecology·2026

Same author

Polygenic viral factors enable efficient mosquito-borne transmission of African Zika virus.

Nature communications·2025

Same author

A natural barrier: tick-repellent potential of a spruce-derived volatile blend against Hyalomma excavatum and Ixodes ricinus.

Pest management science·2025

Search research articles

Related Experiment Video

Updated: Jul 3, 2026

Resurrection of Dormant Daphnia magna: Protocol and Applications

Resurrection of Dormant Daphnia magna: Protocol and Applications

Published on: January 19, 2018

Overcompensatory population dynamic responses to environmental stochasticity.

James C Bull¹, Michael B Bonsall

¹Ecology & Epidemiology Group, Department of Biological Sciences, University of Warwick, Coventry, UK.

The Journal of Animal Ecology

|July 24, 2008

Summary

This study quantifies population regulation by examining insect dynamics under varying environmental noise and resource limits. Environmental conditions significantly influence population fluctuations, driven by overcompensatory dynamics and stochastic processes.

More Related Videos

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Related Experiment Videos

Last Updated: Jul 3, 2026

Resurrection of Dormant Daphnia magna: Protocol and Applications

Resurrection of Dormant Daphnia magna: Protocol and Applications

Published on: January 19, 2018

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Area of Science:

Ecology
Population Dynamics
Mathematical Biology

Background:

Population dynamics are shaped by density-dependent and density-independent factors.
Understanding these interactions is crucial for predicting population fluctuations.
Environmental noise and resource limitation are key drivers of population change.

Purpose of the Study:

To quantify the interplay between density-dependent population regulation and density-independent limitation.
To analyze time-series dynamics in experimental insect microcosms.
To develop a general stochastic population model linking abundance fluctuations to density dependence and noise.

Main Methods:

Utilized a hierarchical Bayesian state-space approach to model population dynamics.
Manipulated environmental noise and resource limitation in laboratory insect microcosms.
Employed a general stochastic population model to explore ecological interactions.

Main Results:

Population regulation in bruchid beetles is primarily driven by environmental conditions.
Fluctuations in abundance are explained by changes in overcompensatory dynamics and stochastic processes.
Incorporating time-lags in population regulation significantly amplifies predicted population fluctuations due to noise.

Conclusions:

Environmental conditions are principal regulators of bruchid beetle population dynamics.
Stochastic processes and overcompensatory dynamics are key to understanding abundance fluctuations.
Time-lags in density dependence are critical for accurate population fluctuation predictions in noisy environments.