A phenotypic view of evolution Evolution in Structured Populations

Introduction to Contextual Analysis

First off, I have been told that you can’t talk about social evolution without mentioning kin selection:  “kin selection”.  With that done, lets now talk about contextual analysis.  (Ok, lets be honest, in future posts I will more fully diss kin selection.  Suffice it to say, as presently constructed it simply makes no sense from a phenotypic, or for that matter, a reality based perspective.)

The basic idea with contextual analysis is that we do a standard Arnold/Wade selection analysis almost exactly like I described it last week, thus the first thing of which to remind you is that we are talking about phenotypic selection and, at least as originally formulated and as typically used in experimental situations, we are talking about the selection vector, S, and the selection gradient b = P-1S.

R = G P-1S = Gβ

The difference is that the S vector will include traits measured on more than one level of organization.  For example, in a standard group selection setting, both traits measured on the organism and on the group would be included in the selection analysis.  These group level traits could potentially be summary traits for organismal level traits, or they could be traits that only can be measured on the group. As an example, an individual trait might be the leaf area of a plant, then a group summary could be the group mean leaf area, and group size might be a contextual trait.

CA S vector

In this S vector the  ΔZ1 through ΔZN are observed changes in N organismal level traits, the  ΔZ1 through ΔZN are observed changes in the group mean of the N organismal level traits, and the green ΔC1 through ΔCK are observed changes in the group mean of K “contextual” traits that can only be measured on the group.

As with any selection analysis selection of the traits is critical.  From a practical perspective the total number of traits needs to be kept small.  As anybody who has worked with real data knows multivariate methods eat degrees of freedom for lunch.


In addition, it is important to thoughtfully select the traits based on the biology of the organism.  One major issue with selection analyses in general is that the outcome of the analysis may qualitatively change depending on the selection of the traits.  For this reason people are beginning to advocate for using path analysis as in preference to a standard multivariate regression (e.g., Scheiner, Mitchell & Callahan J. Evol. Biol. 13:423-433.  I believe that Michael Morrissey is working on a paper on the topic, but I can’t find it right now)

The problem of thoughtfully choosing the correct trait becomes a bit more complicated when you move to contextual or group summary traits.  Consider that in the above I defined the summary trait as the group mean of the organismal traits.  In fact, you can immediately ask the question whether it should be the group mean, or some jackknifed version of the group mean that leaves out the focal individual.  Also, there may be times when the group mean isn’t important, rather it is some trait of the most extreme individual.  For example, in lions usurping males often kill the cubs, and for cubs the probability of survival is influenced by the ability of the dominant male to fend off other males.  In this case, the group mean could be very misleading.

lions fighting - carole white_medium

The survival of the cubs may depend on the outcome of this fight. (http://www.governorscamp.com/blog/migration-wildlife-update-masai-mara)

In any case, once the traits are identified it is then possible to do a regression of fitness on phenotype, giving the multilevel selection gradient.   This raises the interesting point that there is only a single dependent variable (relative fitness), thus, fitness can only be assigned at one level.  Thus, in our classic group selection example, we assign fitness at the level of the organism, and measure traits on the organism and on the group to which they belong.  In essence, using a perhaps bizarre perspective, we are treating the group level traits as if they were individual traits, thus we are treating, say, population size as the population size that an individual experiences.

This, then, gives us a very nice definition of group selection:  Group selection is occurring when there is significant selection on a contextual trait.  Or in more general terms, group selection is occurring when the fitness of an individual is a function of the characteristics of the group to which they belong.

I will not lie:  When I started out I did not believe that contextual analysis would work.  It was a HUGE paradigm shift for me (Kuhn, forgive me! I really try to avoid that term! ).  First, as a graduate student I had always used individual fitness and group mean fitness, and group selection to me was the differential survival and reproduction of groups.  Contextual analysis does neither of these things.  Nevertheless, it does work – Next week I will talk about how I tried, and failed, to prove that contextual analysis would not work – and for the moment I will ask you to believe it works.

In any case this change in perspective significantly broadens the concept of group selection.  When Maynard-Smith (1964. Nature 201: 1145-1147) first imposed himself on the group selection debate he basically defined a group as something with clear boundaries; metaphorically speaking, something you can walk around.  Contextual analysis makes it clear that the phenomenon of what Maynard-Smith called group selection is part of a much larger phenomenon.  Contextual analysis works equally well with “continuous” groups.  In a continuous plant population a contextual trait might be the mean leaf area of all plants within a 30 cm radius of the focal plant.  Notice that in this case every individual is at the center of their own “group”, so unlike classic group selection every individual will have a unique value for their contextual traits.  Another point is that the groups need not be physical at all.  For species with kin recognition selection on kin groups makes perfect sense.  Finally, it quickly becomes clear that many forms of frequency dependent and density dependent selection are indeed forms of multilevel selection.

Basically, what contextual analysis shows is that classic group selection is part of some sort of multivariate continuum that at one end has Maynard-Smith’s clearly delineated groups and at the other end(s) has frequency dependent selection, continuous groups and “virtual” groups.  If you want to say that there are some things that are group selection and others that are frequency dependent selection you can do that, but since they are on a continuum, there can be no objective criterion for drawing that line and where you draw it will inevitably be arbitrary.



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  1. “First off, I have been told that you can’t talk about social evolution without mentioning kin selection: “kin selection”. ”

    I’m an avid kin selectionist…but I disagree with this! Social traits obviously have evolved between non-relatives :-)!

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