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

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

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)...
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...
Naturalistic Observations02:30

Naturalistic Observations

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
Ecological Niches02:02

Ecological Niches

All organisms have a position within an ecosystem. The complete set of living and nonliving factors—including food resources, climate, and terrain—that define the position of a given organism are collectively referred to as the organism’s ecological niche.Multiple species cannot occupy the exact same niche within their habitat. If the niches of two or more species overlap to a large extent, the competitive exclusion principle dictates that one species will outcompete the other, forcing it to...
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.
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

You might also read

Related Articles

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

Sort by
Same author

The distribution of mycotoxins in a heterogeneous wheat field in relation to microclimate, fungal and bacterial abundance.

Journal of applied microbiology·2018
Same author

Babel, or the ecological stability discussions: an inventory and analysis of terminology and a guide for avoiding confusion.

Oecologia·2017
Same author

BEESCOUT: A model of bee scouting behaviour and a software tool for characterizing nectar/pollen landscapes for BEEHAVE.

Ecological modelling·2016
Same author

Individual-based modelling: what is the diffrence? Reply from J. Uchmamański and V. Grimm.

Trends in ecology & evolution·2011
Same author

To be, or to be essentially the same: the `self-identity of ecological units'.

Trends in ecology & evolution·2011
Same author

Reconciling classical and individual-based approaches in theoretical population ecology: a protocol for extracting population parameters from individual-based models.

The American naturalist·2008

Related Experiment Video

Updated: Jun 5, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Individual-based modelling in ecology: what makes the difference?

J Uchmański1, V Grimm

  • 1Janusz Uchmátiski is at the Institute of Ecology, Polish Academy of Sciences, 05092 ŁLomianki, Poland.

Trends in Ecology & Evolution
|January 18, 2011
PubMed
Summary

Individual-based modeling (IBM) is a distinct ecological approach that models populations by tracking individual differences and resource dynamics, differing from classical methods. IBM does not assume stable ecological systems with simple equilibrium states.

More Related Videos

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
07:41

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Published on: July 30, 2019

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

Related Experiment Videos

Last Updated: Jun 5, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
07:41

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Published on: July 30, 2019

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

Area of Science:

  • Ecology
  • Ecological Modeling

Background:

  • Distinguishing between classical and individual-based modeling (IBM) in ecology is challenging due to unclear boundaries.
  • Classical models often focus on population density and assume system stability.

Purpose of the Study:

  • To clarify the definition and characteristics of genuine individual-based models in ecology.
  • To differentiate IBM from traditional ecological modeling approaches.

Main Methods:

  • Defining genuine individual-based models based on specific criteria.
  • Comparing the assumptions and outputs of IBM with classical ecological models.

Main Results:

  • Genuine IBMs explicitly model populations composed of unique individuals.
  • These models track changes in individual numbers, not just population density.
  • Resource dynamics are integral to IBM, and they do not represent ecological systems as inherently stable with point equilibria.

Conclusions:

  • Individual-based modeling represents a distinct paradigm in ecological research.
  • Clearer definitions are needed to understand the unique contributions of IBM.
  • IBM offers a more nuanced view of ecological systems by accounting for individual heterogeneity and dynamic resource interactions.