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Related Concept Videos

Speciation Rates01:07

Speciation Rates

Speciation can proceed at markedly different rates, and evolutionary biologists commonly describe these differences through the models of gradualism and punctuated equilibrium. Both patterns explain how new species arise, but they differ in the tempo and continuity of evolutionary change. In both cases, evolutionary change arises from heritable variation within populations, with natural selection often shaping traits that improve survival and reproduction under specific environmental conditions.
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.However, realistic environmental conditions limit the number of...
Estimating Population Standard Deviation01:26

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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

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Estimating Population Mean with Unknown Standard Deviation01:22

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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the Guinness...

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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
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Estimating a geographically explicit model of population divergence.

L Lacey Knowles1, Bryan C Carstens

  • 1Department of Ecology and Evolutionary Biology, 1109 Geddes Ave., Museum of Zoology, University of Michigan, Ann Arbor, Michigan 48109-1079, USA. knowlesl@umich.edu <knowlesl@umich.edu>

Evolution; International Journal of Organic Evolution
|March 14, 2007
PubMed
Summary

Researchers developed a new population-divergence model to study species differentiation in geographically structured populations. This model, applied to Rocky Mountain grasshoppers, reveals population structuring due to glacial refugia and emphasizes multi-individual sampling for accurate evolutionary history.

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Area of Science:

  • Population genetics and evolutionary biology.
  • Investigating species differentiation in geographically structured populations.

Background:

  • Existing population-genetic models often lack the capacity to study divergence in geographically structured species.
  • This limitation can bias generalizations about evolutionary processes driving species divergence, particularly in regions shaped by events like Pleistocene glaciation.
  • Understanding divergence in such settings is crucial for accurately inferring evolutionary histories.

Purpose of the Study:

  • To estimate a robust population-divergence model for geographically structured species.
  • To quantitatively assess population relationships and historical associations using gene genealogies.
  • To evaluate the influence of methodological assumptions on estimated divergence histories.

Main Methods:

  • Utilized gene trees from five anonymous nuclear loci and one mitochondrial locus in Melanoplus oregonensis.
  • Employed a population-divergence model incorporating gene-lineage sorting and multi-individual sampling.
  • Compared three different approaches to estimate population divergence, evaluating model fit using per-site likelihood scores.

Main Results:

  • A population-divergence model considering multi-individual gene lineage coalescence provided the best fit to the data.
  • Results indicate significant latitudinal and regional population structuring, consistent with displacements into glacial refugia during the Pleistocene.
  • Accurate divergence history estimation requires sampling multiple individuals per population to distinguish common ancestry from gene flow.

Conclusions:

  • The developed population-divergence model offers a framework for studying differentiation in geographically structured species.
  • The study highlights the importance of considering historical associations and contemporary distributions in divergence models.
  • This approach overcomes limitations of simplified models and provides a more accurate understanding of evolutionary processes in complex landscapes.