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Related Concept Videos

Limits to Natural Selection01:38

Limits to Natural Selection

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.
Genetics of Speciation02:16

Genetics of Speciation

Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
Genetic Drift03:33

Genetic Drift

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.
Mutation, Gene Flow, and Genetic Drift01:09

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).
What is Natural Selection?01:32

What is Natural Selection?

Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.

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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
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Simulating natural selection in landscape genetics.

E L Landguth1, S A Cushman, N A Johnson

  • 1Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA. erin.landguth@mso.umt.edu

Molecular Ecology Resources
|September 29, 2011
PubMed
Summary
This summary is machine-generated.

Evolutionary landscape genetics uses individual-based models to study how landscapes affect evolution. This new program links gene flow and selection, revealing deviations from classic models in allele frequency changes.

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Landscape genetics

Background:

  • Understanding how landscape features influence evolutionary processes is crucial.
  • Classic models often assume idealized, panmictic populations, which may not reflect real-world complexities.
  • Spatially-explicit, individual-based models offer a more realistic approach to evolutionary landscape genetics.

Purpose of the Study:

  • To introduce and explore applications of a new spatially-explicit, individual-based program for evolutionary landscape genetics.
  • To compare predictions of individual-based models with classic population genetics models.
  • To investigate the interplay of mutation, gene flow, genetic drift, and spatially-varying selection.

Main Methods:

  • Development and application of a spatially-explicit, individual-based evolutionary landscape genetics program (cdpop v1.0).
  • Incorporation of mutation, gene flow (resistance surfaces), genetic drift, and selection (selection surfaces) with spatially variable fitness.
  • Validation of simulations against Wright-Fisher assumptions and isolation-by-distance processes.

Main Results:

  • The program successfully couples gene flow and spatially-explicit natural selection.
  • Individual-based simulations show deviations in allele frequency change rates and equilibrium values compared to classic models under isolation-by-distance.
  • Demonstrated the impact of landscape heterogeneity on evolutionary trajectories.

Conclusions:

  • The developed program is a valuable tool for studying evolutionary landscape genetics.
  • It allows for explicit evaluation of gene flow and selection interactions in complex landscapes.
  • Highlights the importance of spatially-explicit, individual-based approaches for understanding evolutionary processes.