The survival of the fittest is a common slogan in biology, and many people think it’s important to understand what it means. The propensity interpretation of fitness, which defines it as the probability that an organism will leave more descendants, is one view that has received a lot of attention in recent years. However, it faces some serious problems. This article examines those problems and argues that the propensity definition of fitness cannot be sustained.
Proponents of the propensity interpretation argue that, if we understand the concept of fitness in terms of a particular conception of probability (propensity), it will be possible to explain how evolution works. They claim that, just as a sturdier glass tends to break less often than a fragile one, an organism’s traits are likely to solve its environment’s design problems more fully, and therefore the fitter organism will survive and leave more descendants. This argument seems to have some support in empirical data, but it is problematic from a philosophical perspective. The problem is that the theory of evolutionary adaptation is not designed to provide explanations of how individual organisms succeed, let alone why some groups of organisms fail.
To avoid this problem, proponents of the propensity interpretation propose a new definition of fitness. It is a measure of an organism’s expected number of offspring, adjusted for its higher moments. This measure is very similar to the standard operational measures biologists use to evaluate traits and genetic individuals. It also happens to be mathematically simple, and thus easier to understand than the more complex probabilistic measures that evolutionary biologists usually employ.
The main problem with the propensity definition of fitness is that it does not adequately deal with the difficulties that have confronted earlier probabilistic propensity definitions of fitness. For example, the problem that Mills and Beatty encountered when attempting to define fitness as a function of reproductive rates again arises in this case. In addition, the definition only applies to asexual organisms, making it difficult to apply to sexually reproducing ones.
Another issue is that the propensity definition of fitness does not allow for variation in trait fitness in a population. To understand why, consider the following example: Suppose that one species has an overall expected number of offspring per generation equal to 1, and that another species has an overall expected number of offspring equal to 0.5. Both species have a high fitness. But, the probability that the first species will leave fewer offspring than the second is equal to 1/(1-probability of extinction)
In this case, the probabilistic propensity definition of fitness can not be applied to trait levels in populations, since the variation in these traits must be explained by other causes. Ultimately, it is not clear how to define an operational measure of fitness in this way that will work in practice. It seems that there is still a need for a probabilistic propensity definition of fitness, but this will have to be different from previous versions in ways that address the above counter-examples and other problems.
Milena Estêvão is a YouTuber passionate about sharing her experiences (challenges, successes and motivations) in the fitness activities she is involved in.
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