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Types of Selection

Types of Selection

Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...

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Frequency-dependent Selection

Frequency-dependent Selection

When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.Positive Frequency-Dependent SelectionIn positive...

Analysis of Population Pharmacokinetic Data

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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...

Stratified Sampling Method

Stratified Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Related Experiment Video

Updated: Jun 6, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Multilevel selection in multitype populations.

Amanda de Azevedo-Lopes¹, Arne Traulsen¹

¹Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, August-Thienemann Str. 2, 24306 Plön, Schleswig-Holstein, Germany.

|June 5, 2026

Summary

This summary is machine-generated.

Multilevel selection shapes complex interactions among many microbial types in host-associated microbiomes. This process can promote microbial diversity and beneficial host-microbe interactions, impacting microbiome evolution.

Keywords:

biological interactions evolutionary game theory microbiome

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

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Last Updated: Jun 6, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

Microbial Ecology
Evolutionary Biology
Theoretical Ecology

Background:

Multilevel selection is crucial for understanding host-associated microbiomes.
Previous studies focused on interactions between only two microbial types.
Microbiomes involve complex interactions among numerous microbial types.

Purpose of the Study:

To investigate how multilevel selection influences interaction dynamics among multiple microbial types.
To determine if multilevel selection promotes microbial diversity within populations.
To assess if multilevel selection favors beneficial host-microbe and microbe-microbe interactions.

Main Methods:

Simulated a multitype microbial population structured into groups.
Utilized an evolutionary game within groups to determine individual fitness.
Classified pairwise interactions based on dynamical outcomes: dominance, coexistence, or bistability.

Main Results:

Multilevel selection significantly reshapes interaction dynamics, with outcomes dependent on population structure.
The study revealed complex patterns of interaction emerging from multilevel selection.
Specific population structures lead to distinct interaction dynamics among microbial types.

Conclusions:

Multilevel selection plays a critical role in shaping the complexity of microbiome interactions.
This selection mechanism can drive the evolution of microbial diversity and cooperation within microbiomes.
Understanding multilevel selection is key to predicting microbiome evolution and function.