Related Experiment Video
Updated: Jan 5, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments
Aleksandra Ardaševa1, Robert A Gatenby2, Alexander R A Anderson2
1Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.
Species adapt to changing environments through spontaneous phenotypic variations. Higher variation rates benefit survival during rapid environmental shifts, while slower changes favor lower variation rates.
Area of Science:
- Ecology
- Evolutionary Biology
- Mathematical Biology
Background:
- Organisms face environmental heterogeneity requiring adaptation.
- Spontaneous phenotypic variation is an ecological strategy for surviving fluctuating environments.
Purpose of the Study:
- To investigate the adaptive role of spontaneous phenotypic variations in fluctuating environments.
- To model the evolutionary dynamics of competing populations with varying phenotypic variation rates.
Main Methods:
- Utilized a system of non-local partial differential equations.
- Analyzed the long-time behavior of solutions for evolutionary dynamics.
- Modeled phenotype-structured populations with heritable variations and oscillating nutrient levels.
Main Results:
- Low rates of phenotypic variation are advantageous under small, slow environmental oscillations.
- High rates of phenotypic variation provide a competitive edge during large, fast oscillations (e.g., nutrient abundance/starvation cycles).
Conclusions:
- The optimal rate of spontaneous phenotypic variation is dependent on the characteristics of environmental fluctuations.
- Findings have implications for understanding cancer metabolism and evolutionary strategies in dynamic ecosystems.
Related Concept Videos
Speciation Rates
Types of Selection
Competition
Population Growth
Genetic Drift
Frequency-dependent Selection

