Brain size, latitude, and ambient light

An Inuk wearing snow goggles. Is ambient light at its lowest in Inuit territory?

The logjam seems to have broken. On the heels of Lewis et al. (2011), we now have another paper on variation in brain size among human populations, this time by Pearce and Dunbar (2011).

Brains vary in size by latitude, being bigger at higher latitudes and smaller at lower ones. This variation seems to reflect an adaptation to climate. But just how, exactly, does climate relate to brain size? How direct or indirect is the relationship?

Pearce and Dunbar (2011) argue that bigger brains are an adaptation to lower levels of ambient light. Specifically, dimmer light requires larger eyes, which in turn require larger visual cortices in the brain. Using 73 adult crania from populations located at different latitudes, the two authors found that both eyeball size and brain size correlate positively with latitude. The correlation was stronger with eyeball size, an indication that this factor was driving the increase in brain size.

How credible is this explanation? First of all, visual cortex size was not directly measured. The authors inferred that this brain area was responsible for the increase in total cranial capacity. Obviously, they couldn’t have done otherwise. They were measuring skulls, not intact brains.

But there’s another problem—one in the realm of logic. A lot of things correlate with latitude: pigmentation, mating systems, rules of descent, degree of paternal investment, and so on. If one of them correlates more strongly with latitude than the others, does it therefore cause the others? Not at all. It may be closer than the others to this shared cause, but it doesn’t necessarily lie on the same causal chain as the others.

In other words, the level of ambient light does not produce a single cascade of consequences, with eyeball size being the first consequence. There are probably many different cascades.

To date, the best map of human variation in brain size is the one by Beals et al. (1984) (see previous post). If dimness of light is the main determinant, brain size should be highest in northwestern Europe, northern British Columbia, the Alaskan panhandle, and western Greenland. These regions combine high latitudes with generally overcast skies. Yet they are not the regions where humans have the biggest brains. Instead, brain size is at its highest among humans from the northern fringe of Arctic Asia and from northeastern Arctic Canada. These regions are, if anything, less overcast than average. They often have high levels of ambient light because of reflection from snow and ice.

The jury is still out on this question. I suspect, however, that the following three factors probably explain variation in brain size with latitude.

1. Among hunter-gatherers, hunting distance increases with latitude because there are fewer game animals per square kilometer (Hoffecker, 2002, pp. 8-9). Hunters must therefore store larger amounts of spatiotemporal information (landmarks, previous hunting itineraries, mental simulations of possible movements by game animals over space and time). This factor might explain why brains have grown smaller since the advent of agriculture.

2. The seasonal cycle matters more at higher latitudes. As a result, northern hunter-gatherers, and northern agriculturalists even more so, must plan ahead for the next season (or even for the season after the next one).

3. Women gather less food at higher latitudes and almost none in the Arctic. They are thus free to specialize in other tasks, such as garment making, food processing, and shelter building. This “family workshop” creates opportunities for greater technological complexity, which in turn increases selection for greater cognitive performance.

I suspect bigger brains provide not so much greater intelligence as greater ability to store information. As such, they nonetheless pre-adapted northern hunter-gatherers for later advances in cultural evolution.

References

Beals, K.L., C.L. Smith, and S.M. Dodd (1984). Brain size, cranial morphology, climate, and time machines, Current Anthropology, 25, 301–330.

Hoffecker, J.F. (2002). Desolate Landscapes. Ice-Age Settlement in Eastern Europe. New Brunswick: Rutgers University Press.

Lewis, J.E., D. DeGusta, M.R. Meyer, J.M. Monge, A.E. Mann, R.L. Holloway. (2011). The Mismeasure of Science: Stephen Jay Gould versus Samuel George Morton on Skulls and Bias, PLoS Biology, 9(6) e1001071

Pearce, E. and R. Dunbar. (2011). Latitudinal variation in light levels drives human visual system size, Biology Letters, doi: 10.1098/rsbl.2011.0570

Latitude and sex ratio at birth

Does closeness to the equator make a woman likelier to have daughters? So says Kristen Navara (2009) in a recent article in Biology Letters:

Here, data collected from 202 countries over a decade show that latitude is a primary factor influencing the ratio of males and females produced at birth; countries at tropical latitudes produced significantly fewer boys (51.1% males) annually than those at temperate and subarctic latitudes (51.3%). This pattern remained strong despite enormous continental variation in lifestyle and socio-economic status, suggesting that latitudinal variables may act as overarching cues on which sex ratio variation in humans is based.

The article notes that this pattern results largely from low sex ratios at birth in sub-Saharan Africa. This is no surprise. Many other authors have noted relatively low numbers of male births in sub-Saharan Africa (Romaniuk 1968:278-281, 334; van de Walle 1968:38-43). The same observation has been made for African diaspora populations in the West Indies (Visaria 1967), Britain (James 1984), Latin America (Feitosa & Krieger 1993), and the United States (Ciocco 1938; Erickson 1976; Strandskov 1945; Teitelbaum 1970; Teitelbaum 1972). Sex ratios at birth are significantly lower in Black Americans than in White Americans even when birth order, socioeconomic status, paternal age, and paternal education are controlled (Erickson 1976; Teitelbaum 1972). In a review of the literature, Garenne (2008) states:

Much less work has been done in sub-Saharan Africa, primarily because of a lack of vital registration, the main source of information for studying sex ratios at birth. Ciocco (1938) noted that in 1917–1934 African Americans had a lower sex ratio (average 1.033) than Americans of European descent. Visaria (1967) also noted that the West Indies, where populations of African descent were in the majority, had low sex ratios (0.90–1.036). James (1984) concluded that the sex ratio of African populations was lower than the sex ratio of European populations, with an average value of 1.030.

Why are sex ratios at birth so low in populations of sub-Saharan descent? Most explanations point to polygyny, which reaches high levels (>20% of all sexual unions) in 85% of sub-Saharan African societies (Goody 1973, pp. 177-178). A study of seven different Kenyan ethnic groups found that polygynous relationships produce proportionately more daughters than monogamous ones (Whiting 1995). Whiting (1995) and Martin (1994) suggest that a woman will bear more daughters if she experiences sexual intercourse less frequently, as seems likely if her husband has other wives.

This facultative mechanism reduces the number of excess males later in life. In short, a low sex ratio at birth helps compensate for a higher operational sex ratio at reproductive ages. Over time, in a population with consistently high levels of polygyny, selection will tend to hardwire this adaptation by favoring alleles that decrease the sex ratio at birth.

Navara (2009), however, prefers to explain this phenomenon in terms of “climatic variables.”

… while genetic and artificial influences on the human sex ratio cannot be discounted, studies show that natal sex ratios among African countries are as diverse as in other parts of the world (Gerenne 2002) and show a positive correlation with latitude and its associated climatic variables just as we see globally (p>

The problem here is that polygyny likewise varies with latitude (Frost 2006; Frost 2008). Polygyny is more common among tropical hunter-gatherers and even more so in tropical agricultural societies. When women can gather or grow food year-round, they depend much less on men for food provisioning. It is thus much less costly for a man to take a second or third wife.

Navara (2009) cites Garenne (2002) to show that sex ratios at birth vary in sub-Saharan Africa in a way that cannot be explained by genetic factors. This is not quite Garenne’s conclusion:

The range of variation seems to go from below 1.00 to above 1.08, with possible values lower than 1 in some countries of Southern Africa. In particular, Bantu populations seem to have lower sex ratios (possibly around or below 1.00), whereas West African populations seem to have average sex ratios (close to 1.04). Some other populations, such as Nigeria and Ethiopia, could have sex ratios as high as 1.08 or higher.

The low values for Bantu populations are consistent with a genetic explanation, as are the high values for Ethiopians. But why do West Africans generally have average values and Nigerians high values? This is all the more puzzling because black diaspora populations in the United States and the West Indies have low sex ratios at birth and yet are largely descended from West Africans.

This issue is addressed by Garenne (2008) in a later article:

Further investigations in Africa showed that the sex ratio also varied within population groups. For instance, in Nigeria the sex ratios were higher than elsewhere in Africa (>1.050) and were higher in northern Nigeria than in southern Nigeria (Ayeni 1975; Egwuatu 1984; Rehan 1982).

The difference between northern Nigeria (Muslim) and southern Nigeria (Christian/Muslim/animist) suggests that religion may be a factor. Muslims tend to have higher sex ratios at birth because of the patriarchal nature of their societies (less complete birth registration and/or higher infant mortality of daughters, tendency to postpone birth control until a son has been born, some cases of female infanticide).

Garenne (2008) did not directly study the relationship between polygyny and sex ratios at birth. He suggests that polygyny may depress sex ratio at birth in part through lower coital frequency (the husband has to satisfy more than one woman and also tends to be an older man):

Higher levels of male hormones (e.g., testosterone) seem to favor male births, and the higher levels also affect coital frequency, which indirectly affects the sex ratio. In fact, coital frequency was found repeatedly to have an effect on sex ratios, with higher frequency associated with higher sex ratios; coital frequency tends to decline with age, birth order, and marital duration (James 1996).

Polygyny may also depress sex ratios at birth through a maternal age effect, i.e., young brides are likelier to have daughters than older brides:

The effect of polygyny on sex ratios is controversial (Whiting 1993). It could be due to maternal and paternal ages, once genetic differences are controlled for. Indeed, the main consequences of polygyny are the low age at first marriage for women and the high age difference between the spouses, which is likely to increase the mean paternal age.

So if you want to have a daughter, would your chances be improved by moving to the equator? I doubt it. You’d have more luck being polygynous.

References

Ayeni, O. 1975. Sex ratio of live births in southwestern Nigeria. Annals of Human Biology, 2(2), 137–141.

Ciocco, A. (1938). Variation in the sex ratio at birth in the U.S. Human Biology, 10, 36-64.

Clark, S., E. Colson, J. Lee et al. 1995. Ten thousand Tonga: A longitudinal anthropological study from southern Zambia, 1956–1991. Population Studies, 49(1), 91–109.

Egwuatu, V. E. 1984. The sex ratio of Igbo births. International Journal of Gynecology and Obstetrics, 22(5), 399–402.

Erickson, D. (1976). The secondary sex ratio in the United States 1969-71: Association with race, parental ages, birth order, paternal education and legitimacy. Annals of Human Genetics, 40, 205-212.

Feitosa, M.F., Krieger, H. (1993). Some factors affecting the secondary sex ratio in a Latin American sample. Human Biology, 65, 273-278.

Frost, P. (2008). Sexual selection and human geographic variation, Special Issue: Proceedings of the 2nd Annual Meeting of the NorthEastern Evolutionary Psychology Society. Journal of Social, Evolutionary, and Cultural Psychology, 2(4), pp. 169-191.
http://www.jsecjournal.com/articles/volume2/issue4/NEEPSfrost.pdf

Frost, P. (2006). European hair and eye color - A case of frequency-dependent sexual selection? Evolution and Human Behavior, 27, 85-103.

Garenne, M. (2008). Poisson Variations of the Sex Ratio at Birth in African Demographic Surveys, Human Biology, 80 (5), October 2008, E-ISSN: 1534-6617 Print ISSN: 0018-7143 DOI: 10.1353/hub.0.0021

Garenne, M. (2002). Sex ratios at birth in African populations: A review of survey data, Human Biology, 74, 889-900.

Goody, J. (1973). The Character of Kinship. Cambridge: Cambridge University Press.

James, W.H. (1984). The sex ratio of black births. Annals of Human Biology, 11, 39-44.

Martin, J.F. (1994). Changing sex ratios. The history of Havasupai fertility and its implications for human sex ratio variation. Current Anthropology, 35, 255-280.

Navara, K.J. (2009). Humans at tropical latitudes produce more females, Biology Letters, published online 1 April 2009, doi: 10.1098/rsbl.2009.0069

Rehan, N. E. 1982. Sex ratio of live-born Hausa infants. British Journal of Obstetrics and Gynecology, 89(2), 136–141.

Romaniuk, A. (1968). The demography of the Democratic Republic of the Congo. In W. Brass, A.J. Coale, P. Demeny, D.F. Heisel, F. Lorimer, A. Romaniuk & E. van de Walle (Eds.) The Demography of Tropical Africa (pp. 241-341). Princeton: Princeton University Press.

Strandskov, H.H. (1945). Birth sex ratios in the total, the 'white' and the 'coloured' U.S. populations. American Journal of Physical Anthropology, 3,165-175.

Teitelbaum, M.S. (1970). Factors affecting the sex ratio in large populations. Journal of Biosocial Science (suppl.), 2, 61-71.

Teitelbaum, M.S. (1972). Factors associated with the sex ratio in human populations. In G.A. Harrison & A.J. Boyce (Eds.) The Structure of Human Populations (pp. 90-109). Oxford: Clarendon Press.

Van de Walle, E. (1968). Characteristics of African Demographic Data. In W. Brass, A.J. Coale, P. Demeny, D.F. Heisel, F. Lorimer, A. Romaniuk & E. van de Walle (Eds.) The Demography of Tropical Africa (pp. 12-87). Princeton: Princeton University Press.

Visaria, P.M. (1967). Sex ratio at birth in territories with a relatively complete registration. Eugenics Quarterly, 14, 132-142.

Whiting, J.W.M. (1993). The effect of polygyny on sex ratio at birth. American Anthropologist, 95, 435-442.