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

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)...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...

Mechanistic Models: Overview of Compartment Models

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...

Pharmacodynamic Models: Emax Drug–Concentration Effect Model

Pharmacodynamic Models: E_max Drug–Concentration Effect Model

The Emax drug-concentration effect model is central to pharmacodynamics in drug discovery and development. This model is predicated on the receptor occupancy theory, which posits that the effect of a drug is directly related to the number of receptors occupied by the drug and the resultant complex formation.The model describes the reversible interaction between a drug (C) and a receptor (R) to form a drug-receptor complex (RC). The kinetics of this interaction are quantified by an equation that...

Impact of Individuals on Individuals

Impact of Individuals on Individuals

Human behavior is intricately shaped by social influences that arise from interactions with others in diverse contexts. These influences not only mold beliefs and attitudes but also drive the regulation of behaviors through both direct communication and observational learning. The study of these processes falls within the domain of social psychology, which seeks to understand how individuals are affected by and affect those around them.Mechanisms of Social InfluenceDirect social influence...

You might also read

Related Articles

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

Sort by

Same author

Evolution of dispersal in a spatially heterogeneous population with finite patch sizes and catastrophes.

Journal of theoretical biology·2026

Same author

Evolution of dispersal under spatio-temporal heterogeneity.

Journal of theoretical biology·2023

Same author

Tumor microenvironment as a metapopulation model: The effects of angiogenesis, emigration and treatment modalities.

Journal of theoretical biology·2022

Same author

Evolution of Reproduction Periods in Seasonal Environments.

The American naturalist·2020

Same author

The components of directional and disruptive selection in heterogeneous group-structured populations.

Journal of theoretical biology·2020

Same author

Environmental dimensionality determines species coexistence.

Journal of theoretical biology·2020

Search research articles

Related Experiment Video

Updated: Jun 21, 2026

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

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

Published on: July 3, 2020

The Allee effect in mechanistic models based on inter-individual interaction processes.

Hanna T M Eskola¹, Kalle Parvinen

¹Department of Mathematics, University of Turku, 20014 Turku, Finland. hanna.eskola@utu.fi

Bulletin of Mathematical Biology

|July 30, 2009

Summary

This study introduces new population models incorporating the Allee effect by modifying existing ecological frameworks with mate-finding processes. These models offer a more realistic understanding of population dynamics, crucial for ecological research.

More Related Videos

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

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: Jun 21, 2026

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

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

Published on: July 3, 2020

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

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:

Population dynamics
Mathematical biology
Ecological modeling

Background:

Existing discrete-time population models lack the Allee effect.
Previous work by Eskola and Geritz (2007) established a unified ecological framework for population models.
Variations in reproduction and aggression patterns were key in the prior framework.

Purpose of the Study:

To mechanistically derive population models that include the Allee effect.
To extend the existing ecological framework by incorporating mate-finding processes.
To provide a more comprehensive understanding of population dynamics under varying conditions.

Main Methods:

Modification of the existing discrete-time population modeling framework.
Introduction of different mate-finding processes into the ecological model.
Mechanistic derivation of new population models based on these modifications.

Main Results:

Successfully derived several discrete-time population models incorporating the Allee effect.
Demonstrated that mate-finding processes are key to introducing the Allee effect mechanistically.
The modified framework provides a unified approach to models with and without the Allee effect.

Conclusions:

The Allee effect can be mechanistically derived within a unified ecological framework by including mate-finding processes.
This research expands the applicability of the Eskola and Geritz (2007) framework.
The new models offer enhanced realism for studying population dynamics.