Links this week:
Links this week:
Links this week:
In my last post, I discussed the framework for cultural evolution laid out by Claire El Mouden and colleagues in a new article in the Journal of Evolutionary Biology (ungated pdf and supporting information). By setting out clear definitions for the analysis of cultural evolution, such as cultural relatedness and fitness, a workable framework using evolutionary biology’s Price equation can be developed.
As I noted in that post, it is when the biological and genetic frameworks are laid on top of each other, as is the focus of the dual-inheritance literature, that things get interesting. With their framework, El Mouden and friends tackle a couple of the prominent gene-culture evolution questions.
The first question is to what extent cultural evolution increases or decreases genetic fitness. The authors note that a theme of the gene-culture evolution literature is that cultural evolution made the scale and distribution of today’s human population possible. How does this work?
For there to be a positive correlation between cultural and genetic fitness, those who have the most cultural influence must also leave the most offspring. It is easy to see circumstances where this holds, with those of high social status tending to have both cultural influence and more offspring (look at the number of partners of rock stars).
An example to the contrary is low fertility in developed countries. El Mouden and colleagues reference work by Richerson and Boyd, who suggest that high status is given to professions with high investment in education, which would allow the behaviour to spread despite the negative relationship between education and fertility.
However, El Mouden and friends show that this mismatch between cultural and genetic fitness is evolutionarily unstable as genetic natural selection acts to align genetic and cultural fitness. They suggest two reasons for this, one involving transmission and the other selection.
Their transmission explanation relies on the already evolved propensity for people to avoid behaviours that are harmful to their genetic interests. For example, the nausea produced when consuming toxins would fight against any cultural pressure to eat toxic food. However, it is an interesting question as to how general this transmission effect would be, as many cultural forces are novel and without precedent in our evolutionary history. Transmission may be unlikely to constrain our desire for high status professions that require large investments in education any time soon.
The genetic selection explanation would seem to have broader power. In the supplementary information, the authors ask us to consider a population where cultural and genetic fitness were not aligned. Now, imagine a mutant in that population that causes people to pay attention to a cultural trait that is more highly correlated with genetic fitness. As these mutants have higher genetic fitness, they increase in proportion of the population, and cultural and genetic fitness are now more correlated. Cultural fitness now promotes genetic fitness. In the long-run, the two will be perfectly correlated (the exception being where cultural traits are neutral to genetic fitness).
The catch in that last sentence is the “long-run”. As cultural evolution can be so much faster than genetic evolution, systems can be far from genetic equilibrium until the genetic response evolves. Fertility in developed countries would be an example of this. There may also be some constraints that prevent perfect alignment, such as the presence of appropriate learning mechanisms.
This interaction of genetic and cultural evolution gets most interesting is when we turn to the evolution of altruism. In examining this question we must remember that genetic and cultural fitness are distinct. Cultural altruism reduces the altruist’s cultural fitness; that is, their influence. As a result, the claim that cultural evolution increases genetic altruism (the more common claim in the gene-culture evolution literature) needs to be made carefully.
As an illustration, consider this interesting example from the paper. A stranger is being attacked, so a good Samaritan steps in to defend them and dies as a result. Whether this is culturally altruistic would depend on whether the Samaritan’s deed was copied. If so, then the Samaritan’s act would actually have been increase cultural fitness as it would have increased their influence in respect of that cultural trait.
Conversely, their death is genetically altruistic. As a result, genetic selection would tend to act against it. Those who ignore this cultural trait will have higher genetic fitness, grow in proportion of the population and eventually bring cultural and genetic fitness into alignment.
So what of behaviours that are both culturally and genetically altruistic? Whether the behaviour spreads will depend on the degree of cultural and genetic relatedness.
Evidence suggests that cultural relatedness within ethnic groups is higher than genetic relatedness (although it is still not high in absolute terms, with more within group than between group variation). This means that there are a wider range of circumstances for which cultural altruism can emerge than for genetic altruism. However, that domain in which cultural but not genetic altruism is likely to emerge will be subject to the forces described above to align cultural and genetic fitness.
Another important point is that each cultural trait should be considered separately. Even though a group may have the same language, giving them high relatedness for this cultural trait, this does not mean that they have the same views on giving their lives for strangers, for which they may have low cultural relatedness. Consideration of the conditions for altruism need to consider the specific cultural trait.
There are many other interesting points in the article – I recommend reading the whole thing – but I will close with a point on the practicality of modelling cultural evolution in this way. El Mouden and friends note that there is a host of complications not present in the genetic case. Cultural relatedness can vary wildly across cultural traits, whereas the nature of genetic transmission means that relatedness is similar across most of the genome. Recognising the pattern of inheritance is also a challenge, as ancestor numbers can vary in number and be of vastly different biological ages. In that context, there is no such thing as a standard length of generation.
So although this paper presents a nice approach to cultural evolution, it does not present an approach that is easily applied to empirical observation. However, given the lack of clarity across much of the gene-culture evolution literature, particularly when examined across authors and papers, it is nice to see an attempt to achieve some conceptual coherence.
A sojourn into the literature on cultural evolution can be confusing. Authors use the same terms in different ways. Unique models are used to reach opposite conclusions. And each author seems to find their own way to intertwine genetic evolution into the analysis.
In that light, a new article in the Journal of Evolutionary Biology (ungated pdf and supporting information) by Claire El Mouden and friends seeks to nail down some of the concepts of cultural evolution and to set up a general framework (thank you!). The paper is at a more basic level than that of Geoffrey Hodgson and Thorbjørn Knudsen’s book Darwin’s Conjecture, which also sought to define and generalise concepts in this area.
El Mouden and her colleagues’ paper covers a lot of interesting terrain, so I will cover it in two posts. In the first, I’ll cover the basics of a cultural evolution framework. In the second, I will look at how cultural and genetic evolution interact in this framework.
The authors set up their framework using the Price equation from evolutionary biology. The Price equation divides evolutionary change of a trait into two components. The first is a natural selection component resulting from the covariance between a trait and relative fitness. Where there is large covariance, evolution will be fast. Second is a transmission component, which is the fitness-weighted change in trait value between generations (for example, increasing height with improved nutrition across the population would be considered transmission). The Price equation has the neat property that it can be decomposed into within-group and between-group components, allowing analysis in a multilevel selection framework (although not everyone is happy with this decomposition).
But to use this framework, it is important to clarify some terms (which is one of my bugbears about the cultural evolution literature). First, relatedness. As the units of inheritance are cultural traits, the measure of relatedness is similarity in cultural traits. In a simple model where we have one cultural trait, anyone with that same cultural trait has a relatedness of one. In effect, when passing on a cultural trait to another person, they become kin.
The use of the term relatedness is often confusing in the cultural evolution literature as the relatedness of interest is typically genetic relatedness. That is fine, but we need to distinguish the two types of relatedness. Cultural kin are not necessarily genetic kin.
Second, fitness. Cultural fitness reflects the number of people who learn from an individual, plus the degree of influence that they have on those people. Degree of influence is important because, unlike genetic evolution where you have a known and fixed number of ancestors (one parent in the case of asexually reproducing species, two parents for sexually reproducing species such as humans) who contribute a specific amount of genetic material, the number of cultural ancestors may vary by trait and between people. How many people have influenced your cooking? Who was more influential?
Further, for each cultural trait, people will have different fitness. The authors offer the example of Beethoven, whose influence in cookery did not match his influence in music. This necessitates different measurements of cultural fitness for different traits.
Third, generation. The ancestor-descendent relationship is defined by influence, and can have weak relation to biological age. Plato is still spawning direct cultural descendants today, whereas ideas can also spread through a population in days. However, it is only possible to influence people in the next cultural generation, as that is how generation is defined. If I influence someone, they are the next cultural generation in respect of that cultural trait.
Having defined these concepts, they are relatively easy to slot into a cultural Price equation (the maths is in the supplementary information to the paper). While there is extra complexity from considering the degree of influence rather than just the number of descendants, the form of the Price equation is effectively the same for both the genetic and cultural forms. It is just that each deals distinctly with genetic or cultural fitness.
It is also possible to derive a Cultural Hamilton’s Rule. In biology, Hamilton’s rule states that a gene will spread if the cost of the act to the altruist is less than the benefit accrued by the beneficiaries adjusted by the degree of relatedness. A gene can spread if you help kin who also have that gene, even if it comes to a cost to yourself.
Similarly, the Cultural Hamilton’s Rule states that “a behaviour that reduces the actor’s lifetime cultural influence can only be culturally selected for if the cost to him is less than the product of the cultural benefit to his interaction partners and their cultural relatedness to him”. On this point, the authors give an example of two philosophers with the same cultural views. If one chooses to farm to feed the other, allowing the other to focus on spreading the philosophy, the cultural trait may spread despite one of the philosophers effectively sacrificing his own influence.
Under this definition, cultural kin selection becomes a relatively parsimonious explanation for the spread of many cultural traits, such as altruism (and as noted above, this could also be converted into a multilevel selection framework). If people believe in altruism and help others who also do (who are their kin), then helping each other could assist in the further spread of the cultural trait of altruism.
However, this story of spreading cultural altruism falls somewhat short of covering the examples in much of the gene-culture evolution literature. The issue is that, while culture is a part of the model and analysis, people are typically interested in genetic altruism.
Thus, the question of interest is how cultural evolution affects the evolution of genetic altruism? That will be the subject of my next post.
Links this week:
And to close, my twitter and blog feeds contain an inordinate amount of baseball content. I don’t understand why economists are so interested in baseball, despite the fact they can use their statistical skills to re-live the jock versus nerd battles of their childhood (In the same way, I don’t understand my countrymen’s infatuation with cricket – adults chasing balls?). Surely there are more interesting statistics.
So, to get some real sport into your feeds (this being the only sport in which I can bring myself to watch), I’m introducing a semi-regular surf link or clip to my week of links posts. Today, some awesome Pipeline footage (using drones, another area that economists seem to be infatuated with). I love how you can see the reef, the holes in it, and how the water depth changes so suddenly at its edge. Other highlights – Kelly Slater at 1:05 catching the wave that won him the recent Pipe Masters, and the crowd all paddling for the horizon at 2:54 when they see some sets starting to rear up on third reef. (As an aside, surfing could use some numerate economists – from the almost award of the Eddie Aikau to Tony Ray to the premature crowning of Kelly Slater as world champion, the surfing hierarchy could benefit from the ability to add.)
When low-status males have no chance of accessing females via traditional routes such as fighting or signalling their prowess, they may attempt more deceptive means of getting a mate.
As an example, some male fish take advantage of the external fertilisation of eggs by hiding on the periphery of the courting male’s territory, including in some cases disguising themselves as females. When the eggs are released, they rush in and attempt to fertilise them. This strategy can be dangerous, but for males that simply aren’t in the game, it may be their only option.
The technical term for this behaviour is kleptogamy, but it is better known as the “sneaky fucker” strategy. I’ve often heard and read in the blogosphere that John Maynard Smith coined the phrase, but I haven’t been able to turn up anything authoritative.
The earliest use of the term I have been able to find is by Richard Dawkins and John Krebs in their chapter Animal Signals: Information or Manipulation in the 1978 first edition of Krebs and Nicholas Davies Behavioural Ecology: An Evolutionary Approach (HT: Rob Brooks). The relevant passage is as follows:
It is especially interesting that the movements of the eventual loser of a contest closely parallel those of the winner until a few moments before giving up, just as one would expect if the contest involves both bluff and assessment. A similar effect was observed in red deer stags (Cervus elephus) by Clutton-Brock (in prep.); the stags compete for hinds to add to their harems, and contests consist of prolonged roaring duels. Escalated contests are rare, and they are costly because of the high risk of injury and because subordinate males, known as sneaky fuckers, may steal matings during a prolonged fight. Contests are settled by roaring: the two males roar at each other with a gradually increasing tempo until one suddenly gives up …
Interestingly, the mention of sneaky fuckers is an aside and not the point of the paragraph. Also, the phrase “known as sneaky fuckers” suggests the term was already established.
So, does anyone know of an earlier reference to the sneaky fucker strategy?
UPDATE: In the comments, Alex Sutherland notes an earlier reference from New Scientist in 1977 (Vol 75, p673). In an article The games animals play, Jeremy Cherfas writes (also on the subject of Clutton-Brock’s work on stags):
A stag can gain females by successfully challenging other stags. Fights start with a session of roaring, which may be followed by parallel walking and perhaps a tussle with locked antlers. If the challenger had a harem, the winner takes control of both sets of hinds. The benefits of a larger harem in terms of increased reproductive potential, are clear, but what of the costs? Clutton-Brock estimates that during the average reproductive life of four years, 20 per cent of the stags are permanently injured in fights. The costs are considerable. For a bachelor without a harem the benefits outweigh the costs, and one finds that harem owners initiate fights less often than bachelors. The costs are also increased when both stags hold harems, largely because young stags take advantage of the fight to steal hinds from the harems. (This is known as kleptogyny, but Clutton-Brock and most others prefer “the sneaky fucker strategy”.) Fights, and injuries, are more frequent in mid rut, when most conceptions occur.
This passage confirms the phrase was already established by 1977. And again, the mention is an aside and not a discussion of the sneaky fucker strategy itself.
Links this week (or two):
As has been the case since I started blogging, I have almost no ability to predict in advance which posts will be popular or not. Here are the most read posts in 2013:
As is my habit, each year I give a list of the best books I have read during the year. I tend not to focus on the newest releases, so most of the list was not published this year. In no particular order:
Books I read that didn’t make the list but are worth a mention include Nate Silver’s The Signal and the Noise: Why So Many Predictions Fail but Some Don’t (I thought a couple of chapters were great, but just wasn’t that excited by a lot of it) and Victor Hwang and Greg Horowitt’s The Rainforest: The Secret to Building the Next Silicon Valley.
