New York University Primatologist James Higham delivered an extraordinarily interesting talk on primate reproductive ecology at the Natural History museum this week. He pointed out that otherwise morphologically quite similar primate species can coexist sympatrically without interbreeding — some half a dozen of them in one particular rainforest. The vast bulk of the sexual signaling is carried out by facial characters. All primates know who is conspecific — a potential sex partner — and who is not through an exquisitely subtle sensitivity to facial characters. It is an extraordinary fact that no two people who aren’t identical twins look alike; that we can recognize thousands, perhaps millions, of distinct faces; that we never forget a face even if the name of the acquaintance slips us. Across the primate order, we are tuned in to extremely subtle differences in facial characters.

I asked him after the talk what is a good signal for a character to be under sexual selection. He told me something that resolved a longstanding problem for the Policy Tensor. The signal, he told me, is sexual dimorphism. If a character is dimorphic, it’s a good bet that it is under sexual selection. We have established that scale parameters of the human skeleton (pelvic bone width, femur head diameter, skull size) reflect thermoregulatory adaptation to the paleoclimate where the population spent the Upper Pleistocene. We decomposed cranial variation into that due to neutral drift and bioclimatic adaptation by projecting it onto distance from Africa (Khoi-San) and ET (or absolute latitude). If Higham is right, and I do believe he is, we can use dimorphism as the signal for sexual selection. So we can then attempt a three way decomposition. In what follows, we’ll examine a number of craniofacial shape variables or indices that control for scale. This will allow us to test the three causal vectors and identify characters that are neutrally derived, under selection for thermoregulatory control, or under sexual selection.

There are no races. There are demes or situated breeding populations that exhibit derived characters due to a combination of relative isolation (particularly among geographic isolates) and natural selection (adaptive or sexual). I have played Lewontin’s game of apportionment whereby one shows that race dummies explain a negligible portion of the phenotypic or genotypic variation. I am sure you are bored of it. So here’s another proof.

Take another so-called racial character. Racial anthropologists claimed for a century that a diagnostic character of the Australian race was their large teeth. It is true that Australian molars show larger crown diameters on average relative to other continents. But there is substantial systematic variation within Australia. Demes in southwestern Australia have massive molars; those in the central, southeast, northwest and northeast regions do not. Positing the existence of the Australian race turns out to be actively misleading in understanding morphological variation. That’s pretty much the case with every so-called racial character. 

Hanihara (2000) looked at variation in a number of craniofacial characters. We start off by looking at his shape indices. Figure 1 shows the infraglabellar index, which captures the relative size of the infraglabellar notch (GOL/NOL in Howell’s labels), the distance between the nose and the brow. We see that it is roughly proportional to distance from Africa, with the geographic isolate Sahul standing out. This suggests that this character may be neutral. As we shall see later, our intuition is right.

A different pattern emerges with the gnathic index (BPL/BNL) that measures prognathism or how much the jaws protrude. We see that this is a derived condition in demes in both Africa and Sahul (making it what’s called a homoplasy). The pattern suggests that it emerged at opposite ends of the earth for different reasons, or at least under the control of different genes (similar to loss of skin pigmentation in north Asians and Europeans which has a different genetic basis).

Figure 3 displays the frontal flatness index (NAS/FMB) that measures the flatness of the face. Again this appears to be a derived condition in Eastern Eurasians. Although there is massive variation in this character within Eastern Eurasia—more than everyone else put together! We shall see this character is under strong sexual selection in some Asian demes.

The Hanihara sample contains only male crania. In order to test our hypotheses, we must turn to the good old Howells Craniometric Dataset. Before we do that, I just want to show that distance from southern Africa (computed using the Haversine formula and known waypoints) gives us good control over the infraglabellar index. See next figure. Our estimated correlation coefficient is very large and significant (r=0.577, p<0.0001) suggesting that this trait is neutral, ie not under natural selection.

We begin by looking at sexual dimorphism in craniofacial characters.

Basically, the idea is that if we project the variation in these characters onto distance from southern Africa, absolute latitude, and our measure of dimorphism (the t-Statistic for gender equality in the character at the population level) along the cross-section, we should be able to get a handle on which of the three variables controls which character. 

Table 2. Standardized coefficients (tStat)
	Distance from Africa	Absolute latitude	Dimorphism	R-squared
Gnathic Index	0.12	-1.86	-0.29	0.15
Posterior Index	-3.86	2.26	-0.60	0.47
Transverse craniofacial Index	1.28	-1.03	-2.45	0.38
Upperfacial Index	0.09	1.43	-2.10	0.23
Nasal Index	-2.74	-2.70	-2.27	0.54
Orbital Index	1.96	-0.74	-1.42	0.19
Frontal Flatness Index	-1.38	1.04	-3.56	0.41
Orbital Flatness Index	-1.29	-0.09	-1.79	0.21
Maxillary Flatness Index	1.61	-0.29	-2.29	0.28
Nasodacryal Index	0.84	2.63	-2.71	0.38
Simotic Index	2.93	3.05	-1.82	0.63
Infraglabellar Index	2.20	-0.57	-0.07	0.21
Source: Howells Craniometric Dataset, author’s computations. Coefficients in bold are significant at the 5 percent level.

We can see from the results reported in Table 2 that the transverse craniofacial index, the upperfacial index, the frontal flatness index, and the maxillary flatness index are evidently exclusively under sexual selection since they are correlated with our measure of dimorphism but not distance from Africa or absolute latitude.

Thermoregulatory adaptations seem implicated in the shape of the back of the head (posterior craniofacial index), the relative width of the nose (nasal index), and the nasodacryal and simotic indices. Neutral drift is implicated too. It controls the infraglabellar index alone, and the simotic and the posterior indices jointly with absolute latitude. 

Recall from Table 1 that both the upperfacial index and the frontal index are dimorphic in only 5 demes each in the 30-deme Howells Craniometric Dataset. Going back to the interpretation of the Hanihara (2000) data, the “Asian” frontal flatness business is thus revealed as a derived character that owes to the definitely cultural phenomena of sexual selection (tStat=-3.56) in some populations; precisely which ones we cannot say because the Hanihara (2000) dataset contains data on only male crania so we cannot compute dimorphism metrics. Dimorphism controls half of the dozen characters examined in the present study; distance from Africa and absolute latitude control a third each. In the Venn diagram of control, the sole character in the intersection of all three is the nasal index, the relative width of the nose.

What the below plot suggests is that craniofacial flatness is under very strong sexual selection, suggesting that this is what is going on in some Asian demes as captured by Figure 2. So we have causal vectors pointing “the wrong way” (in the reductionist paradigm), from Society to Nature. Surely, sexual selection in our species is a cultural phenomena. Sexual selection is lived by situated populations. It is reenacted through the articulation and disarticulation of stable desiderata in the eye of the beholders. The disciplinary force of cultural selection acts directly on the sexual economy by structuring the eye of the beholder at the level of the situated populations. Discourse and Reality cannot but cointegrate.

Finally, Table 3 present our apportionment of craniofacial variation in terms of our three predictors. 

Table 3. Apportionment of craniofacial variation.
	Neutral drift	Bioclimatic adaptation	Sexual selection
Gnathic Index	0.1%	13.5%	0.3%
Posterior Craniofacial Index	35.2%	12.0%	0.9%
Transverse Craniofacial Index	5.3%	3.4%	19.6%
Upperfacial Index	0.0%	7.2%	15.5%
Nasal Index	17.9%	17.4%	12.3%
Orbital Index	13.5%	1.9%	7.1%
Frontal Flatness Index	5.1%	2.9%	33.7%
Orbital Flatness Index	6.2%	0.0%	11.9%
Maxillary Index	8.6%	0.3%	17.6%
Nasodacryal Index	1.9%	18.7%	19.9%
Simotic Index	19.8%	21.6%	7.6%
Infraglabellar Index	17.9%	1.2%	0.0%
Source: Howells Craniometric Dataset, author’s computations. Estimates in bold are significant at 5 percent.

What is clear from Table 3 is that sexual selection is a potent force shaping human craniofacial morphology. The upper face, the nose, and the flatness of the face are all under sexual selection in some demes. The important thing to remember is that sexual selection, like neutral drift and climatic adaptation, works at the level of the situated populations. What this means is that one cannot infer population history directly from phenotypic characters; one must control for sexual selection and climatic adaptation. To wit, if population A looks more similar to population B than C it may not be because C split from A and B first and then A split from B. For it may be that A and C split away from B first but A and B acquired the same characters as a result of adaptation to the macroclimate (as happened with skin pigmentation) or as a result of the same character coming under sexual selection in A and B but not C. Put another way, natural selection (climatic, sexual, or whatever) confounds the population history signal in phenotypic characters. So we must be careful. 

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Postscript. It seems that my A,B,C example was not clear. I am banging on this drum because this issue has been ignored for more than a century now; first, as a result of the mental rigidities associated with essentialist racial taxonomy; and later, as a result of DNA supremacism whereby scholars drank the Kool-Aid and resolved to explain the heavens and everything under them through molecular anthropology. For a century now, physical anthropologists have reasoned back from systematic variation in morphology and genetics to phylogeny (who split when from whom — the tree of descent). This approach was correctly used to infer that Americans were closer to Asians than Europeans so that the American-Asian split happened after the European-Asian split. But backing out population history from phenotypic or genotypic distance metrics does not always work, above all because the population history signal is more often than not confounded by natural selection. So if you are using phenotypic characters or genomic sequences to make inferences about population history, you better be careful. In order to make kosher inferences you have to control for stuff that is under selection. In other words, What matters is not overall genetic distance between populations but neutral distance — that’s what contains information about population history and phylogeny. We have seen that dimorphism gives us a good handle on sexual selection in craniofacial morphology.