Absolute fitness (W) is calculated by multiplying an organism’s survival rate by its reproductive rate. The result tells you, on average, how many surviving offspring a single individual of that genotype contributes to the next generation. A genotype with an absolute fitness of 1.0, for example, replaces itself exactly: one parent produces one viable offspring on average.
The Core Formula
The calculation has two components:
- Survival rate: the proportion of individuals with a given genotype that survive to reproductive age
- Reproductive rate: the average number of viable offspring produced by those survivors
You multiply the two together:
Absolute fitness (W) = survival rate × reproductive rate
This integrates both staying alive and actually reproducing into a single number that reflects a genotype’s total contribution to the next generation. An organism that survives reliably but barely reproduces can have the same fitness as one that reproduces prolifically but rarely survives. The product of both factors is what matters.
A Worked Example With Three Genotypes
Suppose you’re studying a population with three genotypes (DD, Dd, and dd) and you’ve collected survival and reproduction data:
- DD: 10% survival rate, 10 offspring per survivor → 0.10 × 10 = 1.0
- Dd: 10% survival rate, 8 offspring per survivor → 0.10 × 8 = 0.8
- dd: 20% survival rate, 6 offspring per survivor → 0.20 × 6 = 1.2
These products are the absolute fitness values. On average, every DD individual born produces 1.0 viable offspring over its lifetime, every Dd produces 0.8, and every dd produces 1.2. Notice that dd has the highest absolute fitness despite producing fewer offspring per survivor. Its higher survival rate more than compensates for lower reproduction.
What the Number Tells You
The absolute fitness value has a straightforward biological meaning. When W is greater than 1.0, the genotype is increasing in the population because each individual more than replaces itself. When W equals exactly 1.0, the genotype holds steady. When W falls below 1.0, the genotype is declining over time because individuals fail to fully replace themselves.
This makes absolute fitness useful for predicting whether a population (or a genotype within it) will grow, shrink, or stay stable across generations. It’s a raw count of generational output, not a comparison between genotypes.
Converting to Relative Fitness
In practice, evolutionary geneticists almost always convert absolute fitness into relative fitness. The conversion is simple: divide each genotype’s absolute fitness by the highest absolute fitness in the group.
Using the example above, dd has the highest absolute fitness at 1.2, so:
- DD: 1.0 / 1.2 = 0.83
- Dd: 0.8 / 1.2 = 0.67
- dd: 1.2 / 1.2 = 1.0
The fittest genotype always gets a relative fitness of 1.0, and every other genotype falls somewhere between 0 and 1. This normalization makes it easier to compare genotypes directly and to calculate selection coefficients. The selection coefficient (s) for any genotype is simply 1 minus its relative fitness, so DD has a selection coefficient of 0.17 and Dd has one of 0.33.
How Fitness Data Is Gathered
Unlike a trait such as color, fitness can’t be observed at a single moment. It has to be measured across the entire lifespan of the organisms you’re studying and then combined. Researchers typically collect fitness components (survival counts and offspring counts) separately and use the multiplication formula to combine them.
In field studies with plants or animals, this might involve tracking marked individuals from birth to death, recording how many survive to maturity and how many offspring each survivor produces. For organisms with short generation times like bacteria, researchers often use competition assays. Two strains are mixed together in the same environment, allowed to grow for a set period (often 24 hours), and then counted at the start and end. The ratio of each strain’s final population to its initial population gives a direct measure of fitness. Researchers distinguish the two strains by giving them different visible markers, like colonies that grow different colors on special plates, so they can count each strain separately.
A simpler lab approach measures the maximum growth rate of a single strain growing alone, typically by tracking how dense the culture becomes over time. This captures growth ability but misses the competitive dynamics that shape real evolutionary outcomes, so competition assays are considered closer to the true evolutionary meaning of fitness.
When the Simple Formula Gets Complicated
The survival × reproduction formula works cleanly when generations don’t overlap, meaning parents reproduce and then are gone before their offspring reproduce. Many textbook examples assume this structure because it keeps the math straightforward.
In species with overlapping generations (most mammals, many plants), fitness calculations become more complex. An individual that reproduces early may contribute more to population growth than one that produces the same total number of offspring later in life, because those early offspring start reproducing sooner. In these cases, fitness is better captured by more sophisticated measures that account for the timing of reproduction, not just the total count.
Environmental variation adds another layer. A genotype’s survival and reproductive rates can shift across seasons, years, or habitats. A single absolute fitness value assumes relatively stable conditions, so researchers sometimes calculate fitness across multiple environments or generations to get a more realistic picture.