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

Modeling with Differential Equations01:25

Modeling with Differential Equations

227
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...
227
Population Growth00:57

Population Growth

29.5K
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.
29.5K
Microenvironments01:22

Microenvironments

32
Microorganisms inhabit highly localized spaces known as microenvironments, which are defined by distinct physical and chemical characteristics. These include oxygen concentration, pH, temperature, light availability, and nutrient levels. The conditions within a microenvironment can differ markedly from those in the surrounding area and significantly influence microbial growth, metabolism, and community structure.Microenvironments often display sharp physicochemical gradients over small spatial...
32
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

65.9K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
65.9K
Genetic Drift03:33

Genetic Drift

45.1K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
45.1K
Evolution of New Traits in Microbes01:24

Evolution of New Traits in Microbes

104
Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...
104

You might also read

Related Articles

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

Sort by
Same author

Dimension Estimate of Uniform Attractor for a Model of High Intensity Focussed Ultrasound-Induced Thermotherapy.

Bulletin of mathematical biology·2021
Same author

Rare Organism Uncommon Disease Case Vignette of Guillain-Barré Syndrome Induced by <i>Fusobacterium nucleatum</i> Infection.

Case reports in infectious diseases·2021
Same author

Modelling recurrence and second cancer risks induced by proton therapy.

Mathematical medicine and biology : a journal of the IMA·2017
Same author

Genotype by random environmental interactions gives an advantage to non-favored minor alleles.

Scientific reports·2017
Same author

Efficacy of dose escalation on TCP, recurrence and second cancer risks: a mathematical study.

The British journal of radiology·2014
Same author

Spatial invasion dynamics on random and unstructured meshes: implications for heterogeneous tumor populations.

Journal of theoretical biology·2014
Same journal

Modeling and analysis of forward and inverse kinematics for a flexible Stewart platform.

PloS one·2026
Same journal

Barriers and facilitators to healthcare utilization amongst people living with sickle cell disease in the United States: A scoping review.

PloS one·2026
Same journal

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

PloS one·2026
Same journal

Key targets and mechanisms by which gut microbiota-derived metabolites regulate Alzheimer's disease through the immune - inflammatory pathway: Based on network pharmacology and molecular docking.

PloS one·2026
Same journal

Grid-tied Transformer-less Boost Switched Capacitor Topology (TLBSCT) for PV applications.

PloS one·2026
Same journal

The load-velocity profiles and exercise-specific velocity zones for seven commonly used weightlifting exercises.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Mar 31, 2026

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.7K

Modeling Invasion Dynamics with Spatial Random-Fitness Due to Micro-Environment.

V S K Manem1, K Kaveh1, M Kohandel1

  • 1Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.

Plos One
|October 29, 2015
PubMed
Summary
This summary is machine-generated.

The microenvironment significantly impacts species invasion. Lower fitness variance generally reduces invasion, but migration can increase it, especially with higher variance. This has implications for understanding biological invasions.

More Related Videos

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.7K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

9.3K

Related Experiment Videos

Last Updated: Mar 31, 2026

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

6.7K
Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.7K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

9.3K

Area of Science:

  • Mathematical Biology
  • Ecology
  • Evolutionary Biology

Background:

  • The cellular microenvironment critically influences species' proliferation and migration.
  • Environmental disturbances create heterogeneous conditions, leading to phenotypic variation.
  • Understanding invasion dynamics is crucial for various biological systems.

Purpose of the Study:

  • To investigate the effect of microenvironmental factors on species invasion probability.
  • To analyze the role of fitness distributions and migration on invasion dynamics.
  • To model invasion on structured grids with site-dependent proliferation.

Main Methods:

  • Utilized a computational framework to simulate invasion dynamics on square lattices.
  • Examined both continuous and discrete fitness distributions for mutants and host cells.
  • Incorporated site-dependent random proliferation and migration potentials.

Main Results:

  • Invasion probability negatively correlates with mutant fitness variance when migration is absent.
  • Migration amplifies invasion probability with increasing mutant fitness variance.
  • Bimodal fitness distributions show zero invasion until a threshold of advantageous phenotypes is reached.

Conclusions:

  • Microenvironmental heterogeneity, including fitness variance and migration, significantly shapes invasion dynamics.
  • Findings are relevant to bacterial micro-habitats, epithelial dysplasia, and metastasis.
  • Results may stimulate further experimental research into heterogeneous environments and invasion.