What is fitness?
1. Introduction
A central concept for the understanding of evolutionary theory and subsequent disciplines such as evolutionary game theory or psychology is that of fitness (cf. Millstein 2021, p.5; Alexander 2001, p.1). But: There are few idioms as popular and as regularly misunderstood as the survival of the fittest, which was coined by Herbert Spencer and popularized by Charles Darwin (cf. Darwin 1876 pp. 49, 62). While Darwin himself introduced it in his revised editions of The Origins of Species, as he found it be a more accurate synonym for the principle of Natural Selection (cf. ibid. p. 49) – today the idiom in many contexts is a less accurate, hollow phrase or even worse: conjures up memories of the 20th century ideology of so-called social Darwinism (cf. Wright 2010, p.12).
One could discuss the extent to which Darwin contributed to the misuse of his theories – whether he was too careless with his pathos, when writing of the Struggle for Existence (cf. Darwin 1876, pp. 48, 55, 62). But these are questions for philologists and historians and should not concern us here. Although it should be clear – by the end of this essay at the latest – that these evolutionary concepts have little to do with crude supremacist ideologies of the past nor present, and on the contrary explain and justify often the very civilized virtues these misguided and inhumane ideologies tried to dismantle (cf. Haidt 2013, pp. 36 – 38; Wright 2010, p. 19).
The goal of this essay is another: To clarify the concept of fitness in the context of evolution.
2. What is Evolution?
When discussing fitness in the context of evolution, the term has a very different meaning than in everyday language e.g. it has nothing to do with the fitness measured and quantified by physical fitness monitors or activity trackers. To approach an understanding of the term fitness in the special context of evolution, we need to clarify first what we mean by evolution. While in contemporary biology, evolution is often defined as a change of genes or alleles from one generation to the next, evolution in general can be understood as the change in the characteristics – including alleles, variants, traits, values, states – of populations over generations (cf. Millstein 2021, pp.2-3). Changes from generation to generation can be found not only on the biological level of analysis in form of genetic change, but also e.g. on the cultural level in form of memes (e.g. Dawkins 2007, pp. 486-487). Therefore, evolution can take many shapes and forms, but all of them have certain elements in common: For one, replicators (e.g. genes or memes), who replicate or are reproduced from one generation to the next and that cause traits (cf. Millstein 2021, p.7). Second, vehicles (e.g. organisms or minds) who carry the replicators and exhibit their traits (cf. ibid.). Third, a change in the frequency and quality of the replicators found in the subsequent generations due to more or less random mutations and due to a change in the ability to survive and reproduce the replicators among the vehicles, which can be caused by different modes, of which selective pressures are the most prevalent one (cf. Rosenberg & Bouchard 2015, p.1; cf. Millstein 2021, p.4). This change, which is called evolution, can therefore be loosely described as the repetition of a three-step algorithm, where: 1. Vehicles reproduce. 2. Their offspring inherits variations of their replicators. 3. Differences in the ability to survive and reproduce among the offspring due to the replicators they carry (cf. Campbell 2009, pp. 41-42). As these steps repeat over time, the frequency and quality of replicators changes, as those variations of the replicators that bestow greater reproductive success, become more frequent, while others disappear (cf. ibid. p. 42). Replicators, e.g. genes, and their resulting traits, which replicate from generation to generation most successfully, can be described as adaptations – and in the long run through evolution subsequent generations of vehicles, e.g. organisms, accumulate these adaptations (cf. ibid.).
Through evolution each new generation of vehicles represents the accumulation of replicators, which facilitated traits, which were adaptive for the previous generation, plus often a bit of additional variation due to random change e.g. mutations. This combination of variance in reproductive success due to variations of the adaptiveness of traits and random variation, can explain how over many generations the diversity and complexity of vehicles change, as different branches of descendants accumulate adaptations to different environments – and this process of change over many generations is called evolution (cf. Rosenberg & Bouchard 2015, p. 2).
3. A general definition of fitness in the context of biological evolution
In the process of evolution, the term fitness is usually used in biology to describe the ability of a vehicle ergo individual organism to reproduce more successfully, due to having traits which are adaptive for its environment. For example, an individual x can be described to have a higher fitness than individual y, if individual x is able to reproduce more successfully ergo create more offspring than y (cf. Rosenberg & Bouchhard 2015, pp. 2-5). In the long run, the genes contributing to the highest fitness survive in the gene pool, as individuals with higher fitness outcompete and outreproduce those with lower fitness. Or as Darwin himself put it: “This preservation of favourable individual differences and variations, and the destruction of those which are injurious, I have called Natural Selection, or the Survival of the Fittest” (Darwin 1876, p.63)
4. The relativity of fitness
The definition of fitness, as the ability to reproduce more successfully may initially appear very clear, but it has several glaring issues, as it is a highly relative concept.
4.1. Fitness when?
For one, fitness is can be only really attested in hindsight, as we can’t say with certainty how successful an individual will reproduce. Furthermore, if an individual’s offspring doesn’t successfully reproduce and therefore its lineage vanishes, this too, seems to indicate a lower fitness for this individual. To solve this, fitness is often also defined as a probability or expected utility of the accumulated long-term replication e.g. the expected number of descendants (cf. Rosenberg & Bouchhard 2015, pp. 8-12). But: As nothing is eternal and even the universe is expected to die (cf. Adams & Laughlin 1997, pp. 366- 370), the long term expected fitness of any replicator using a timeframe of ∞ is probably 0. So, we can ascribe the fitness of an entity only in relation to a certain timeframe or a set of generations, e.g. between one generation to the next. For example, the fitness of the mighty T-Rex might have been really high at a certain point in time, but today of the extinct dinosaur’s lineage, the probably most successful und currently fittest descendants are birds like chickens (cf. Rashid et al. 2014, pp. 4, 15, 16) – which reminds us that the survival of the fittest should not be confused with some supremacist fantasy of a survival of the strongest.
The relevance of the timeframe is especially important, when comparing the fitness-advantages of strategies e.g. when applying evolutionary game theory.
For example, in biology, species differ in reproductive strategies – which are often described with the spectrum between r- and K-selection, or High Quantity and High Quality (cf. Abhishek 2020, p. 6). While producing many offspring – and therefore investing only little resources into each individual – may look initially like a fitness-advantage, when looking at longer time frames, it may be indeed a disadvantage, as often seen in biology, as K-selected species often replace r-selected ones (cf. ibid.). Take for example humans, which are – compared to most other organisms – extreme k-selectors, as parents invest often resources for two decades or longer into a handful of children, sometimes only one or two. Nevertheless, our species was able to hunt down and eat other species faster, than they could reproduce, despite them producing more offspring per capita (cf. Petruzzello 2023). Similarly, it seems plausible, that our species due to its ability to adapt through technology and cu, may outlive many species, which today outreproduce us but rely solely on biological evolution for adaptations.
Similarly, when analysing e.g. the evolution and fitness of social norms with game theory, the evaluation if a norm is an effective strategy and fitness-enhancing, is highly sensitive to the selected timeframe. As an example, Islamic scholars in the 15th century declared the use of the printing press to be haram and punishable by death (cf. Rubin 2017, pp. 105-120). When looking only at the very narrow timeframe of the 15th century, this was maybe an effective strategy to realize the preferences of their society e.g. maintaining political stability, or at least the clergies’ preferences. But the ban on printing remained in Islamic countries like the Ottoman Empire for almost 250 years, contributing to a relative slowdown in technological and economic development, from which many Islamic countries haven’t fully recovered to this day (cf. ibid.). The cultural replicator or mem underlying a strategy, may initially enhance the fitness of its memepool, but lower it in the long run (cf. Dawkins 2007, p. 330).
4.2. Whose fitness?
Another disputed issue is if fitness should be applied to vehicles such as individuals at all, or if it would be more accurate to use it to describe groups, generations, or the replicators (cf. Millstein 2021, p.5). An illustrative example from evolutionary game theory stems from the study of morals like e.g. altruism. While certain behaviours, like indiscriminate helping or self-sacrificing, may be fitness-sacrificing for an individual, the fitness advantages to kin may be greater, leading to groups with such individuals to gain a higher fitness and becoming more frequent than other groups cf. Joyce 2007, pp. 38-41). Such an individual may have a lower fitness relative to its peers, but thanks to its behaviour, their group has a higher fitness. Looking at long timeframes, through genetic drifts or the clustering of such individuals through mechanisms like reciprocity, such individual fitness-sacrificing may lead to a higher reproductive success of vehicles carrying the underlying replicators. Especially when taking kin selection into account – ergo the effects of one vehicles behaviour on the reproduction of other vehicles carrying the same replicators – evaluating fitness solely on an individual level, fails to capture and explain the evolutionary success of certain replicators (cf. Joyce 2007, pp.19-22). Thus, depending on the level and timeframe of analysis, ascribing fitness may make only sense on the levels of replicators or groups of kin. Evolutionary processes resemble here the emergence of dominant strategies through trial-and-error in iterative games from game theory, and fitness the exercise of the dominant strategy – but which strategy is the dominant or what yields the highest fitness, is highly contingent on how many rounds (generations) the game is played and what strategies other players (other vehicles) employ (cf. Binmore 2011, pp. 1, 61, 86).
5. Conclusion
Fitness in the context of evolution describes the ability of a vehicle (e.g. an organism), to pass on its traits in the form of replicators (e.g. genes) more successfully to the next generation, due to these traits facilitating higher adaptation to its environment. The little comparative words more and higher in the previous sentence, indicate already the central problem of the term and concept: Fitness is highly relative, as the evolutionary fitness of an entity can only be defined effectively in comparison to another entity and in relation to a certain timeframe and context.
4 of 4 Essay for the course: Rational agents in social interaction
Grade: 1,3 (Very good)
Lecturer: Dr. Jurgis Karpus
LMU University of Munich
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