Defining fitness in an uncertain world

Area of Science:

• Evolutionary Biology
• Population Genetics
• Mathematical Biology

Background:

• Fisher's fundamental theorem of natural selection is crucial for understanding evolution.
• Existing models struggle with complex population dynamics like random environments and class structure.
• Reproductive value definitions require re-evaluation in fluctuating population settings.

Purpose of the Study:

• To unify Fisher's fitness definition with reproductive values in class-structured populations.
• To develop generalizable equations for natural selection under environmental and demographic uncertainty.
• To explore the axiomatic foundations of reproductive value.

Main Methods:

• Combined Fisher's definition of fitness with context-specific reproductive values.
• Developed generalized versions of the Price Equation and Fisher's fundamental theorem.
• Incorporated arbitrary population classes, including continuous variables and varying ploidy (haploid, diploid, haplodiploid).

Main Results:

• Natural selection simplifies to acting solely through the arithmetic expectation of fitness across uncertainties.
• New equations generalize the Price Equation and fundamental theorem for fluctuating demography.
• The model accommodates diverse ploidy levels and arbitrary population structures.

Conclusions:

• The study provides a significantly simplified framework for understanding natural selection in complex populations.
• Results support the individual-as-maximising-agent analogy in finite populations with environmental and distributional fluctuations.
• The model offers potential for improved empirical measurement of fitness in natural populations.