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Darwinian fitness.
Lloyd Demetrius1, Martin Ziehe
1Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. ldemetr@oeb.harvard.edu
Theoretical Population Biology
|September 7, 2007
Summary
Darwinian fitness in finite populations is stochastic, not deterministic. Evolutionary entropy, measuring population stability, accurately predicts invasion success, unlike the Malthusian parameter.
Area of Science:
- Evolutionary biology
- Population dynamics
- Theoretical ecology
Background:
- Classical models define Darwinian fitness by population growth rate (Malthusian parameter).
- These models assume deterministic outcomes in competitive dynamics.
- Recent studies suggest finite populations introduce stochasticity.
Purpose of the Study:
- To contrast the predictive power of Malthusian and entropic principles for Darwinian fitness.
- To investigate the role of population size in competitive dynamics.
- To validate evolutionary entropy as a measure of fitness.
Main Methods:
- Computational and numerical analysis of competition models.
- Examination of population return rates to steady state after perturbations.
- Characterization of evolutionary entropy as a measure of demographic uncertainty.
Main Results:
- Malthusian parameter fails to predict invasion success in finite populations.
- Evolutionary entropy accurately predicts competitive outcomes in finite populations.
- Computational analysis supports the entropic principle over the Malthusian model.
Conclusions:
- Darwinian fitness in finite populations is a stochastic process.
- Evolutionary entropy is a robust measure of population stability and invasion success.
- Entropy provides a powerful evolutionary parameter with broad predictive capabilities.
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