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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.
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).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Conservation of Small Populations02:04

Conservation of Small Populations

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 likely to...
Conservation of Declining Populations02:07

Conservation of Declining Populations

Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
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.Life is not fair. A deer grazing contentedly in a field can have her meal cut tragically short by a bolt of lightning. If the doomed doe is one of only three in the population, 1/3 of the population’s gene pool is lost. Random events like this can...
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...

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Related Experiment Video

Updated: Jul 15, 2026

Extinction Training During the Reconsolidation Window Prevents Recovery of Fear
11:17

Extinction Training During the Reconsolidation Window Prevents Recovery of Fear

Published on: August 24, 2012

Extinction times in experimental populations.

John M Drake1

  • 1National Center for Ecological Analysis and Synthesis, 735 State Street, Ste. 300, Santa Barbara, California 93101, USA. drake.biosci@gmail.com

Ecology
|September 26, 2006
PubMed
Summary

Predicting population extinctions is crucial. This study analyzed water flea (Daphnia magna) extinction times, finding the distribution was unexpectedly peaked, challenging current ecological theories.

Area of Science:

  • Ecology
  • Conservation Biology
  • Population Dynamics

Background:

  • Predicting population extinctions is vital for conservation biology and population ecology.
  • Stochastic population theories offer theoretical extinction time distributions, but empirical testing is rare.

Purpose of the Study:

  • To quantitatively analyze the distribution of population extinction times in experimental populations.
  • To test theoretical predictions of extinction time distributions against empirical data.

Main Methods:

  • Analysis of extinction time data from 281 experimental populations of water fleas (Daphnia magna).
  • Quantitative estimation of the shape of the extinction time distribution.

Main Results:

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Extinction Training During the Reconsolidation Window Prevents Recovery of Fear
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  • The distribution of population extinction times was found to be extraordinarily peaked.
  • This finding aligns with theoretical predictions for density-independent populations.
  • The tail of the extinction time distribution was not exponential, deviating from some theoretical models.

    • Conclusions:

    • Current theories of population extinction appear inadequate to fully explain empirical observations.
    • Future research should investigate demographic stochasticity's scaling with population size.
    • The impact of nonrandom variable environments on population dynamics requires further study.