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Convergent Evolution

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.

Speciation Rates

Speciation Rates

Genetics of Speciation

Genetics of Speciation

Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.

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Gene Flow

Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

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).

The Evidence for Evolution

The Evidence for Evolution

Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.

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Related Experiment Video

Updated: Dec 23, 2025

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

Coevolution spreading in complex networks.

Wei Wang^1,2, Quan-Hui Liu^2,3,4, Junhao Liang⁵

¹Cybersecurity Research Institute, Sichuan University, Chengdu 610065, China.

Physics Reports

|April 21, 2020

Summary

This summary is machine-generated.

This review explores coevolution spreading dynamics in complex networks, highlighting how disease, behavior, and information spread interact. Understanding these networked coevolutionary processes is crucial for controlling epidemics and predicting social behaviors.

Keywords:

Awareness diffusion Biological contagions Coevolution spreading Complex networks Critical phenomena Resource allocation Social contagions

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Last Updated: Dec 23, 2025

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Area of Science:

Complex Systems Science
Statistical Mechanics
Network Science

Background:

Real-world systems exhibit interconnected propagations of diseases, behaviors, and information.
These coevolving processes interact strongly, influencing system dynamics.
Understanding these dynamics is vital for epidemic control and social behavior prediction.

Purpose of the Study:

To review recent advancements in coevolution spreading dynamics.
To emphasize contributions from statistical mechanics and network science.
To detail four representative coevolution spreading mechanisms.

Main Methods:

Analysis from the perspectives of statistical mechanics and network science.
Examination of theoretical methods, critical phenomena, and phase transitions.
Investigation of interacting mechanisms and network topology effects.

Main Results:

Detailed presentation of four coevolution spreading mechanisms: biological contagions, social contagions, epidemic-awareness, and epidemic-resources.
Identification of key dynamical mechanisms and spatiotemporal patterns.
Discussion of critical phenomena and phase transitions in networked coevolution.

Conclusions:

Coevolution spreading dynamics in complex networks are a significant area of study.
This review consolidates recent progress and highlights challenges.
Future research directions and open issues are identified.