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

Population Growth00:57

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...
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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...
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)...
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...

You might also read

Related Articles

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

Sort by
Same author

Trimming to coexistence: how dispersal strategies should be accounted for in resource management.

Journal of mathematical biology·2025
Same author

On the interplay of harvesting and various diffusion strategies for spatially heterogeneous populations.

Journal of theoretical biology·2019
Same author

Stabilization of Structured Populations via Vector Target-Oriented Control.

Bulletin of mathematical biology·2017
Same author

Effect of treatment on the global dynamics of delayed pathological angiogenesis models.

Journal of theoretical biology·2014
Same author

Velocity-dependent cost function for the prediction of force sharing among synergistic muscles in a one degree of freedom model.

Journal of biomechanics·2009
Same author

On linear perturbations of the Ricker model.

Mathematical biosciences·2006

Related Experiment Video

Updated: Jul 6, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Continuous versus pulse harvesting for population models in constant and variable environment.

Elena Braverman1, Reneeta Mamdani

  • 1Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada. maelena@math.ucalgary.ca

Journal of Mathematical Biology
|March 19, 2008
PubMed
Summary

Impulsive harvesting strategies in population models can be as effective as continuous harvesting but not superior. However, when harm is included in harvesting, impulsive methods become optimal and necessary for logistic and Gompertz growth models.

Related Experiment Videos

Last Updated: Jul 6, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Area of Science:

  • Population dynamics
  • Mathematical biology
  • Ecological modeling

Background:

  • Population models are crucial for understanding species dynamics.
  • Harvesting strategies significantly impact population sustainability.
  • Both autonomous and nonautonomous models are used to study population dynamics.

Purpose of the Study:

  • To compare impulsive and continuous harvesting strategies in population models.
  • To introduce and analyze a model incorporating harm within harvesting events.
  • To determine the optimality and necessity of impulsive harvesting under specific conditions.

Main Methods:

  • Analysis of autonomous and nonautonomous population models.
  • Mathematical modeling of impulsive and continuous harvesting.
  • Inclusion of population harm in harvesting events.
  • Study of logistic and Gompertz growth laws.

Main Results:

  • Impulsive harvesting is found to be as effective as continuous harvesting, but not superior, in standard models.
  • When harm is integrated into harvesting, impulsive strategies become not only optimal but the sole viable option.
  • The study highlights the critical role of harm in determining harvesting strategy effectiveness.

Conclusions:

  • The effectiveness of impulsive harvesting is context-dependent.
  • Incorporating harm into harvesting models fundamentally changes optimal strategy selection.
  • Impulsive harvesting can be the only feasible approach when population harm is a factor.