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

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

995
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
995
Stability01:28

Stability

433
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
433
Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

1.0K
In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
1.0K
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

1.1K
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
1.1K
Pole and System Stability01:24

Pole and System Stability

1.1K
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
1.1K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

885
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
885

You might also read

Related Articles

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

Sort by
Same author

Intraspecific interference among larvae in a semivoltine dragonfly population.

Oecologia·2017
Same author

Avoiding erroneously high levels of detection in combinations of semi-independent tests : An application to testing for density dependence.

Oecologia·2017
Same author

Variability and stability of a dragonfly assemblage.

Oecologia·2017
Same author

Hawks, doves, and mixed-symmetry games.

Journal of theoretical biology·2000
Same author

Solving the complementarity dilemma: evolving strategies for simultaneous hermaphroditism.

Journal of theoretical biology·1998
Same author

Evolving cooperation: the role of individual recognition.

Bio Systems·1996

Related Experiment Video

Updated: Mar 6, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

651

Density dependence, boundedness, and attraction: detecting stability in stochastic systems.

P H Crowley1

  • 1Evolutionary Ecology Research Group, T. H. Morgan School of Biological Sciences, University of Kentucky, 40506, Lexington, KY, USA.

Oecologia
|March 18, 2017
PubMed
Summary

This study introduces new statistical tests to analyze population density changes in ecological systems. The methods successfully predict population dynamics and detect stability patterns in both single and multiple species populations.

Keywords:
Population and community dynamicsRandom walkRandomizationResilienceStatistical tests

More Related Videos

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K
Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.5K

Related Experiment Videos

Last Updated: Mar 6, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

651
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K
Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.5K

Area of Science:

  • Ecology
  • Population Dynamics
  • Statistical Ecology

Background:

  • Ecological system stability can be understood through boundedness (avoiding dynamic boundaries) and attraction (approaching a dynamic attractor).
  • These concepts align with density dependence at the population level.
  • Existing methods for testing these stability concepts in stochastic ecological systems are limited.

Purpose of the Study:

  • To develop and validate new statistical tests for assessing attraction and boundedness in ecological populations.
  • To apply these tests to analyze density dependence in published population data.
  • To evaluate the performance and statistical power of the developed tests.

Main Methods:

  • Devised two single-species statistical tests of attraction: the random-walk attraction test and the randomized attraction test.
  • Employed randomization techniques for boundedness detection and autocorrelation methods for analyzing population density sequences.
  • Developed multispecies versions of the attraction and boundedness tests.

Main Results:

  • The new attraction tests successfully identified apparent attractors, predicting density changes with approximately 80% accuracy in a dragonfly assemblage.
  • Multispecies tests detected both attraction and boundedness in the dragonfly assemblage and attraction in laboratory fruitfly populations.
  • Statistical power of the tests increases with sequence length (n) and number of populations (m).

Conclusions:

  • The developed statistical tests provide robust tools for analyzing stability and density dependence in ecological systems.
  • Multispecies analyses significantly enhance the power to detect attraction and boundedness.
  • Detecting attraction is more likely with longer time series or multispecies data, even with strong density dependence.