Simple rules for inclusive fitness

By Razib Khan | September 23, 2010 5:05 pm

ResearchBlogging.orgWith the recent huge furor over the utility of kin selection I’ve been keeping a closer eye on the literature on inclusive fitness. The reason W. D. Hamilton’s original papers in The Journal of Theoretical Biology are highly cited is not some conspiracy, rather, they’re a powerful framework in which one can understand the evolution of social behavior. They are a logic whose basis is firmly rooted in the world of how inheritance and behavior play out concretely. But because of their formality and spareness inclusiveness fitness has also given rise to a large literature derived from simulations “in silico,” that is, evolutionary experiments in the digital domain.

375px-Green_Beard_GeneOne can elucidate inclusive fitness through Hamilton’s Rule, but it is also rather easy to exposit verbally via a “gene’s eye view.” Imagine for example a dominant mutation in a diploid organism which produces the behavior of altruism toward near kin. Initially the altruist will have offspring whose probability of carrying the dominant mutation is 50%, because there is also the probability that they will carry the ancestral non-altruistic variant. Imagine an altruistic behavior which incurs a small, but not trivial, cost to the individual performing the behavior, and a large gain to the individual who is on the receiving end of the altruism. The logic of favoring near kin is such that in the initial generation the parent which behaves altruistically toward near kin is increasing their own “inclusive fitness” because their offspring share 50% of their genes identical-by-descent (in the case of a diploid sexually reproducing organism). But from a gene’s eye perspective what is really occurring is that there is a 50% chance that the gene which fosters altruism is promoting the fitness of a copy of itself. So inclusive fitness operates by modulating the parameters of costs and gains to focal individuals as a function of their relatedness, but it is the genes, the “replicators,” which persist immortally across the generations. We “vehicles” are just the ocean through which genes sail.

But like Darwin’s theory of evolution through natural selection the fruit of these logics are in the details. A new paper in The Proceedings of the Royal Society puts the focus on different means by which inclusive fitness may be maximized. In particular, the paper offers up a reason for why what Richard Dawkins termed the “green-beard effect” is not more common. Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory:

Inclusive fitness theory predicts that natural selection will favour altruist genes that are more accurate in targeting altruism only to copies of themselves. In this paper, we provide evidence from digital evolution in support of this prediction by competing multiple altruist-targeting mechanisms that vary in their accuracy in determining whether a potential target for altruism carries a copy of the altruist gene. We compete altruism-targeting mechanisms based on (i) kinship (kin targeting), (ii) genetic similarity at a level greater than that expected of kin (similarity targeting), and (iii) perfect knowledge of the presence of an altruist gene (green beard targeting). Natural selection always favoured the most accurate targeting mechanism available. Our investigations also revealed that evolution did not increase the altruism level when all green beard altruists used the same phenotypic marker. The green beard altruism levels stably increased only when mutations that changed the altruism level also changed the marker (e.g. beard colour), such that beard colour reliably indicated the altruism level. For kin- and similarity-targeting mechanisms, we found that evolution was able to stably adjust altruism levels. Our results confirm that natural selection favours altruist genes that are increasingly accurate in targeting altruism to only their copies. Our work also emphasizes that the concept of targeting accuracy must include both the presence of an altruist gene and the level of altruism it produces.

Using the Avida software platform the researchers ran trials of the evolution of populations of artificial life which varied in fitness, coefficient of relatedness, as well as their phenotypes. In one set of trials the organisms operated through conventional means of kin selection, whereby the heuristic was to favor those to whom an individual was closely related. This will result in a fair amount of “false positives,” as everyone knows that near kin can be selfish and “cheat.” Remember that in the toy example above 50% of the offspring who will gain from altruism will themselves lack the altruism gene. A second set of organisms look to total genetic similarity. This is the sort of thing which humans could engage in if they had immediate knowledge of the genomic sequences of those around them. Even among near relatives genetic similarity is only correlated with, not perfectly correspondent with, coefficients of relatedness. Some full siblings may share more identity-by-descent than others. This is trivially obvious in the initial illustration, as there will be a great deal of intra-familial variance on the gene which produces altruism. To focus on the dynamics of the specific gene, the authors also looked at a green-beard effect, whereby a there is a correlation between altruism, a gene, and a visible phenotype. In other words, you know altruists by a correlated physical trait. If the correlation between a phenotype and a genotype is close enough you don’t need do a typing of their genome because you know the state of their genotype, and so have expectations as to whether they’re truly altruists or not. Presumably using the green-beard effect one could side-step the usage of kinship or relatedness as a proxy. In many cases those more distantly related could be more phenotypically similar on the traits of interest than those who are genetically closer.

What did they find? Figure 1 shows the outcomes of various sets of trials:

gb1

Their expectations were that in regards to the evolution of altruism kin selection should be inferior to genetic similarity which should be inferior to the green-beard effect. The reasoning is straightforward, as you progress across these sequence of dynamics the false positive rate of aiding those without the altruism conferring gene should decrease. That is not what they found, at least not initially.

What was happening is that they were focusing on the wrong parameters in framing their expectations. That’s why you run the model: human intuition often fails. Green-bearding is very precise as a dichotomous indicator of whether an individual carries a particular gene identical-by-descent, but mutation could produce variation in levels of altruism. What they found was that when green-bearding was dichotomous the levels of altruism tended to converge upon a lower equilibrium as individuals were focused on being just altruistic enough to count as real altruists and so gain advantages from those who were more generous. A concrete example of this would be an “affinity con”. An individual is a member of a group, and they leverage the trust which comes from being a member of the group to exploit the group. Baked into the cake of the original model is that altruists who also had a green-beard had to have donated at least once, and that is the target which green-beards converged upon. In contrast the strategy of genetic similarity resulted in greater donations, and because the model had non-zero sum dynamics (altruism increased everyone’s fitness greatly, though cheaters could exploit this to “free-ride”) the strategy which maximized donations was more successful. The researchers made green-bearding more competitive by simply increasing the donation threshold to match the equilibrium which emerged with the other strategies. So making all things equal the intuition about green-bearding was then vindicated.

Instead of setting a specific threshold there was another way that green-bearding could beat the other strategies to maximize inclusive fitness: vary the green-bearding trait and altruism continuously in a correlated fashion. In other words, the greener the beard, the more altruistic. This is a classic way that one could beat the cheaters: develop detection and discernment mechanisms. Why doesn’t this matter for the two other more “primitive” techniques? Kin selection and genetic similarity are more robust because they’re not fine-tuned, organisms with similar genome content are likely to have similar altruism levels. The genetic relatedness of altruists in green-bearding populations is going to be lower because they’re looking for a very specific genotype and its correlation with a phenotype. Green-bearding is more precise, but it’s also somewhat more complicated, and as a more precisely engineered solution it may not always be as robust.

And that necessity of fine-tuned intelligence in design may be why green-bearding is not more common. The authors note that in theory one could imagine mutations leading to concomitant variations of the magnitude of green-bearding and altruism in the same direction, but in a real evolutionary genetic context with normal parameters of mutation and effective population sizes this may not be plausible. Many people would argue that evolution is littered with kludges because natural selection makes recourse to “quick and dirty” solutions which are simple but effective, and kin selection and genetic similarity are closer to that than green-bearding. In theory selection may lead to a world of green-beards with infinite population sizes and generations, and persistent and consistent selection, but the world may be too protean for this optimal equilibrium to ever arise. So until then, we’ll make do with social evolution’s duct-tape: “I against my brother; my brother and I against my cousin; I, my brother, and my cousin against the stranger.”

Citation: Clune J, Goldsby HJ, Ofria C, & Pennock RT (2010). Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory. Proceedings. Biological sciences / The Royal Society PMID: 20843843

Image Credit: Burningrey

CATEGORIZED UNDER: Evolution, Genetics, Genomics
  • http://primatediariesinexile.blogspot.com EMJ

    In the past I haven’t had a problem with the elegant logic of kin selection and I’ve written about it on multiple occasions, such as my post Punishing Cheaters Promotes the Evolution of Cooperation. But I do have a problem in how it’s often discussed in terms of a hypothetical “gene” for altruism. Quite obviously no one really thinks such a complex trait is associated with a single gene. But the discussion is always in the abstract because we don’t know anything about the genetics of altruism or cooperative behavior more generally.

    There would likely be many (dozens?) of different alleles contributing to such a complex behavior in mammals. This would make the mathematics extremely difficult to sort out. And what if genetics has no direct role at all and such behaviors are the result of epigenetic influences or because selection is happening on a different, but related, trait like hormonal response? If so, altruistic behavior may not be undergoing selection since the behavior would be context dependent and selection was occurring on the related trait facing different selection pressures. We simply don’t know enough about the mechanisms involved to form definite conclusions.

    But, of course, I don’t have my mind made up on any of this. I’m merely raising a question. Perhaps Hamilton’s equation is so simple and elegant because the real details of what’s happening are entirely unknown? It seems there’s room for skepticism here.

  • http://blogs.discovermagazine.com/gnxp Razib Khan

    But the discussion is always in the abstract because we don’t know anything about the genetics of altruism or cooperative behavior more generally.

    well, we know it’s heritable according to behavioral economists. the main issue is if the gen. architecture is like IQ, or perhaps there are major modulator genes (e.g., one of the dopamine loci).

    If so, altruistic behavior may not be undergoing selection since the behavior would be context dependent and selection was occurring on the related trait facing different selection pressures. The mathematics become increasingly fuzzy once these sorts of complications arise.

    well, i don’t know if they get “fuzzy,” just complicated, since you’re talking about a g-matrix. i’d be skeptical that social behavior though is primarily a byproduct, though is gonna be a philosophical issue, because even if you think it emerged as a byproduct i think it would be hard to deny its fitness implications in a positive sense.

  • Tom Bri

    Since for most of human history we lived in small family bands, an ‘altruism’ gene would have had an easy time replicating itself. Everyone you met was a relative.

    Now, not so much. Nearly everyone you meet is NOT a close relative, so your acts of altruism don’t do your own genes any good.

    I’d guess altruism is declining.

  • http://blogs.discovermagazine.com/gnxp Razib Khan

    tom, sounds plausible. but be careful of being too confident about this. e.g., Now, not so much. Nearly everyone you meet is NOT a close relative, so your acts of altruism don’t do your own genes any good. so wouldn’t that predict that societies which aren’t characterized by tight kin networks would be less altruistic? and yet the quote was from arab societies. it’s complicated.

  • Tom Bri

    An off-the-cuff remark, trying to follow the logic of the article.

    As to modern societies, some with tight kinship networks and some not, these are too recent for much selection against altruism to have taken place. It has only been in the last century or two at most that many people lived far from relatives. In the US, a notably mobile society from the beginning, until the proliferation of modern transportation most people still lived near kin for their entire lives.

    In about 1850 my great-great grandfather moved to the US from England with his brother. They settled side-by-side on farms, and both farms stayed in the family until a decade ago. I grew up a mile from there on another farm. I now live just a few miles away, and some of my second and third cousins live in nearby communities. I meet people I never knew and discover that we share great-great grandparents. I went to high school with kids I didn’t know were relatives and could easily have married one of them…

    Now of course most of the family is scattered and outbred. I have relatives married to a Laotian, a Thai, a Pakistani, a Latino, and a Black American. I married a Japanese.

    If selection pressure for altruism is relaxing, it would still be generations before much change was seen. How often after all is someone killed for an altruistic act?

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This blog is about evolution, genetics, genomics and their interstices. Please beware that comments are aggressively moderated. Uncivil or churlish comments will likely get you banned immediately, so make any contribution count!

About Razib Khan

I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. In relation to nationality I'm a American Northwesterner, in politics I'm a reactionary, and as for religion I have none (I'm an atheist). If you want to know more, see the links at http://www.razib.com

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