Related Experiment Video
Updated: Aug 16, 2025
07:37
Resurrection of Dormant Daphnia magna: Protocol and Applications
Published on: January 19, 2018
18.5K
Universal scaling of extinction time in stochastic evolutionary dynamics
Ching-I Huang1,2,3, Chun-Chung Chen4,5, Hsiu-Hau Lin6
1Department of Physics, National Tsing Hua University, Hsinchu, 30013, Taiwan.
Scientific Reports
|December 27, 2022
Summary
Finite populations and spatial structure alter extinction dynamics in rock-paper-scissors ecosystems. Simulations reveal universal scaling in extinction times, offering new ways to classify evolutionary dynamics.
Area of Science:
- Evolutionary dynamics
- Ecological stability
- Population dynamics
Background:
- Replicator equations model evolutionary dynamics in infinite, well-mixed populations.
- Extinction dynamics differ in finite, structured populations.
- Ecological stability in non-transitive ecosystems depends on spatial structure.
Purpose of the Study:
- Investigate extinction dynamics in finite, structured rock-paper-scissors ecosystems.
- Analyze the impact of spatial structure on ecological stability and extinction.
- Identify universal scaling laws in extinction dynamics.
Main Methods:
- Agent-based Monte Carlo simulations using the Reference-Gamble-Birth algorithm.
- Modeling the rock-paper-scissors ecosystem with three bacterial populations.
- Simulations on fully-connected networks and two-dimensional grids.
Main Results:
- Extinction time follows universal functions on fully-connected networks with rescaled variables.
- Spatial structure on a 2D grid alters stability transition boundaries but not extinction trends.
- Unexpected universal scaling observed in extinction dynamics.
Conclusions:
- Spatial structure significantly impacts extinction dynamics in finite ecosystems.
- Universal scaling provides a potential framework for classifying evolutionary dynamics.
- Findings challenge traditional models and offer new insights into ecological stability.
More Related Videos
Related Concept Videos
03:33Genetic Drift
40.4K
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.
40.4K
01:14Parametric Survival Analysis: Weibull and Exponential Methods
525
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
525
01:07Speciation Rates
21.3K
Overview
21.3K
01:09Mutation, Gene Flow, and Genetic Drift
59.1K
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).
59.1K
01:38Limits to Natural Selection
31.5K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.5K
02:04Conservation of Small Populations
13.3K
Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
13.3K