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

Predator-Prey Interactions02:39

Predator-Prey Interactions

19.7K
Predators consume prey for energy. Predators that acquire prey and prey that avoid predation both increase their chances of survival and reproduction (i.e., fitness). Routine predator-prey interactions elicit mutual adaptations that improve predator offenses, such as claws, teeth, and speed, as well as prey defenses, including crypsis, aposematism, and mimicry. Thus, predator-prey interactions resemble an evolutionary arms race.
19.7K
Population Growth00:57

Population Growth

26.2K
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.
26.2K
Optimal Foraging00:48

Optimal Foraging

12.6K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.6K
What are Populations and Communities?00:30

What are Populations and Communities?

35.4K
Overview
35.4K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

114
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...
114
Limits to Natural Selection01:38

Limits to Natural Selection

33.0K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
33.0K

You might also read

Related Articles

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

Sort by
Same author

Heritable single-cell gene expression states shape functional variability in innate immune responses.

bioRxiv : the preprint server for biology·2026
Same author

Single-cell heterogeneity in ribosome levels and protein synthesis during nutrient starvation is driven by cAMP signaling.

Science advances·2026
Same author

The role of cell growth rate on accumulation of the mitotic cyclin Cdc13 in fission yeast.

bioRxiv : the preprint server for biology·2026
Same author

Impact of variability in cell generation times on cell-to-cell variability of protein concentrations.

bioRxiv : the preprint server for biology·2026
Same author

Enhancer placement impacts transcriptional dynamics in Drosophila embryos.

Nature communications·2026
Same author

Asymmetric histone inheritance regulates olfactory stem cell fates during regeneration.

Nature communications·2026

Related Experiment Video

Updated: Oct 24, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

776

Stochastic dynamics of predator-prey interactions.

Abhyudai Singh1

  • 1Departments of Electrical and Computer Engineering, Biomedical Engineering and Mathematical Sciences, University of Delaware, Newark, DE, United States of America.

Plos One
|August 12, 2021
PubMed
Summary

This study models predator-prey dynamics using a stochastic Lotka-Volterra approach. Prey-dependent attack rates buffer population fluctuations, while predator-dependent rates amplify them, revealing insights into ecological regulation.

More Related Videos

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter
10:20

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Published on: March 12, 2013

13.6K
Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System
09:23

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System

Published on: November 1, 2017

12.2K

Related Experiment Videos

Last Updated: Oct 24, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

776
Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter
10:20

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Published on: March 12, 2013

13.6K
Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System
09:23

Methodology for Developing Life Tables for Sessile Insects in the Field Using the Whitefly, Bemisia tabaci, in Cotton As a Model System

Published on: November 1, 2017

12.2K

Area of Science:

  • Ecology
  • Mathematical Biology
  • Population Dynamics

Background:

  • Predator-prey interactions are fundamental to ecological food webs.
  • Classical Lotka-Volterra models predict neutral stability; density-dependent attack rates can stabilize these systems.
  • Stochasticity and density dependence are crucial for realistic ecological modeling.

Purpose of the Study:

  • To investigate a stochastic Lotka-Volterra model with density-dependent predator attack rates.
  • To analyze how prey and predator population densities influence stochastic fluctuations.
  • To explore the relationship between attack rate functional forms and population dynamics.

Main Methods:

  • Developed a stochastic formulation of the Lotka-Volterra model.
  • Incorporated density-dependent predator attack rates (dependent on prey and predator densities).
  • Analyzed population density fluctuations and predator-prey correlations.

Main Results:

  • Increased sensitivity of attack rate to prey density attenuates stochastic fluctuations.
  • Fluctuations vary non-monotonically with sensitivity to predator density, showing an optimal level.
  • Predator-dependent attack rates amplify stochasticity, while prey-dependent rates buffer it.

Conclusions:

  • Stochastic Lotka-Volterra models can reveal density-dependent regulatory mechanisms in predator-prey systems.
  • The functional form of density dependence has contrasting effects on population stability.
  • Understanding these dynamics is key to predicting ecological food web stability.