During the mid-1970s, new evolutionary and ecological approaches to understanding animal
behavior were starting to be applied to human
behavior. Increasing knowledge about the sophisticated social behavior of other primates further
fueled the effort to place human behavior in a broader evolutionary and zoological context. These efforts were vigorously
contested by academics and activists opposed to any biological interpretation of contemporary human behavior.
In early 1978, the American Association for the
Advancement of Science held a meeting in Washington,
D.C., which attempted to bring together representatives from
all sides in what came to be called “the sociobiology debate.”
Two of the most prominent scientists to attend the meeting
were Edward Wilson, a proponent of the evolutionary study
of human behavior (which was then called sociobiology), and
Stephen Jay Gould, who cautioned that arguments about
the biological basis of human behavior historically had been
used to justify racist and sexist ideologies. Many of Wilson’s
critics accused him of arrogance for suggesting that evolutionary explanations of human behavior would come to dominate thinking in the traditional social sciences. In contrast,
proponents of sociobiology felt that Wilson and other workers in the field were being unfairly accused of holding political
and ideological views that they themselves found to be repugnant. Advocates on both sides of the debate were fueled
by arrogance and righteousness, a volatile combination.
Sociologist of science Ullica Segerstråle attended this
landmark meeting. She describes the extraordinary scene
when Wilson faced some of his more enthusiastic critics:
“The two-day symposium featured about twenty
speakers in all. As a member of the audience, I can say
that for those who anticipated a public showdown, it was
somewhat disappointing to sit through rather technical
talks dealing with animal sociobiology . . . . But there was
anticipation in the air, particularly in the session where both
Wilson and Gould were to speak. The ballroom was filled
to capacity. Would Gould demolish sociobiology? Would
Wilson stand up to Gould? By now, the audience wanted
some action. The result exceeded anybody’s expectation.
“What happens is a total surprise. The session has already featured Gould, among others, and Wilson is one of
the later speakers. Just as Wilson is about to begin, about
ten people rush up on the speaker podium shouting ‘Racist
Wilson you can’t hide, we charge you with genocide!’ While
some take over the microphone and denounce sociobiology,
a couple of them rush up behind Wilson (who is sitting in his
place) and pour a pitcher of ice-water over his head, shouting
‘Wilson, you are all wet!’ Then they quickly disappear again.
Great commotion ensues but things calm down when the session organizer steps up to the microphone and apologizes to
Wilson for the incident. The audience gives Wilson a standing
ovation. Now Gould steps up to the microphone saying that
this kind of activism is not the right way to fight sociobiology—
here he has a Lenin quote handy, on
‘radicalism, an infantile disorder of
socialism.’ For his valiant handling of the situation, Gould, too,
gets a standing ovation. (The
audience does not quite
know how to react to any
of this but applauding
seems somehow right.)
Wilson—still wet—gives
his talk, in spite of the
shock of the physical
attack . . . . his calmly
delivered talk is something of an anticlimax”
(Segerstråle, 2000).
We are fortunate that most debates about the evolution of human behavior do
not end (or begin) with someone being doused with water. But the incident provides an indication of just how heated these debates can become. They reflect a
basic conflict over whether human behavior is “in the genes” or is a product of our
culture and upbringing: the old nature versus nurture debate. The nurture, or cultural, side accuses the nature, or evolutionary, side of being genetic determinists, people who believe that all observed behavioral differences between individuals, the
sexes, or populations can be ascribed only to differences in genetics. The genetic
side accuses the cultural side of embracing the logic of creationism: That once culture evolved, the rules of the game changed, and we were no longer subject (at the
behavioral level) to the forces of evolution, which are so readily apparent in the
animal world.
As you might expect, neither of these two extreme positions reflects the views of
most biological anthropologists. Biological anthropologists, with their appreciation
for the biology and behavior of our closest primate relatives, understand that human
bodies and human behavior evolved. On the other hand, biological anthropologists
also recognize that human behavior is not genetically determined but is the product
of the interaction of genes and cultural environments. Although behaviors do not
fossilize, we can draw inferences about how they may have evolved by examining
contemporary human and nonhuman primate behavior and biology. Many behavioral scientists today believe that although humans are capable of a wide range of
behaviors, some patterns of behavior we observe across cultures and populations are
most directly explained by evolution and natural selection.
In this chapter, we will review the evolution of the human brain and behavior.
The human brain is a structure of great complexity, and it produces behaviors that
are of unparalleled sophistication in the animal world. Yet we need to keep in mind
that the human brain is assembled from the same basic cellular parts as found in most
other animals, and its basic structural organization is reflected in the brains of both
closely and distantly related species. At some point in hominin evolution, changes in
the brain led to the appearance of a species that behaved more like us and less like
our ape cousins. Compared with the brains of our closest relatives, the human brain
is larger, and it exhibits important differences in its functional organization.
Overview of the Brain
The brain consists of three major parts: the
brainstem, the cerebellum, and the
cerebrum (Figure 14.1). As its name suggests, the brainstem sits at the base of
the brain and connects directly to the spinal cord. The brainstem is crucial in the regulation and control of complex motor patterns, in breathing, and in the regulation of sleep and consciousness. The cerebellum, or “little brain,” sits tucked in
under the rest of the brain, behind the brainstem. It is densely packed with nerve
cells, or neurons. The cerebellum is important in the control of balance, posture,
and voluntary movements.
The cerebrum is the part of the brain that has undergone the most obvious
changes over the course of human evolution. The outer surface of the cerebrum is
crisscrossed by a complex arrangement of grooves known as sulci (singular, sulcus),
which gives the human cerebrum its characteristic wrinkled appearance. The sulci
divide the surface of the brain into a series of thick bands or ridges, which are called
gyri (singular, gyrus). Although there is individual variation, several basic sulci divide
the brain into functional regions that are common to almost everyone. If we look at
a cross-section through the cerebrum (Figure 14.2), we notice that its outer surface
is actually formed by a rim of tissue (4–6 mm thick) that follows the surface down
into the valleys formed by the sulci; this is the cerebral cortex. The cerebral cortex is
made of gray matter (which looks more brown in the living brain). Gray matter consists mostly of the cell bodies of neurons.
Neurons have a characteristic structure (Figure 14.3). From the cell body, there
emerge branchlike outgrowths through which neurons communicate with one
another: The dendrites receive inputs from other neurons, and the axon is the outgrowth through which one neuron sends a signal to another neuron. Neurons can
have many dendrites but only one axon. The rest of the cerebrum is composed of
white matter, which forms the core of the hemisphere. The white matter is made up
predominantly of the axons of neurons. Axons are sheathed in a white, fatty substance known as myelin, which facilitates the transmission of the electrical impulse
along the axon.
Different regions of the cerebrum have different
functions. It is important to keep in mind that different
regions work in concert to produce complex behaviors. The
cerebral cortex is divided into two kinds of functional areas.
Primary cortex is involved directly with either motor control
or input from the senses. Primary motor regions are concentrated in the frontal lobe, the part of the cerebrum located just
behind the eyes and forehead (Figure 14.4). Primary sensory
regions are distributed throughout the cerebrum. Most of
the human cerebral cortex is not primary cortex but rather
association cortex. We can think of the association cortex as
the regions where the processing of primary inputs or information occurs. It is generally believed that in mammals, as
brain size increases, the proportion of the brain devoted to
association rather than primary regions also increases. Some
association areas receive inputs from only one primary area,
and other regions receive inputs from multiple primary
regions. Anything that we think of as a higher-level function,
such as thought, decision-making, art, or music, originates in
association cortices
Issues in Hominin Brain Evolution
The complexity of the human brain suggests an evolutionary history that is equally
complex. Given that brains themselves are not preserved in the fossil record, evolutionary investigations have focused in particular on issues related to brain size, the
relative size of different parts of the brain, and those aspects of functional organization that can be reconstructed from fossil remains. It is important to note, however,
that advances in brain imaging and molecular neurobiology are changing the way
scientists look at brain evolution. The next few decades promise to be exciting ones
in the field of hominin brain evolution.
Humans Have “Large” Brains
One of the defining features of the genus Homo, and especially of our own species,
is large brain size (Allen, 2009). But what do we mean by “large”? In absolute terms,
the human brain weighs in at about 1,300 g, and human cranial capacities usually are
reported to be in the region of 1,300 to 1,400 cc. These are average figures, and there
is much variation in brain size. However, for purposes of cross-species comparisons,
the 1,350-cc estimate for the volume of the typical human brain is good enough.
Look at the cranial capacities of various primates listed in Table 14.1. As you
can see, humans have the largest brains among primates. The second largest brains
belong to the gorillas. Among the Old World monkeys, baboons appear to have relatively large brains. As discussed in Chapter 6, among the New World monkeys, spider
monkeys have substantially larger brains than their close relatives, howler monkeys.
To put these data in a broader zoological context, cattle have brains of about 486
cc and horses of about 609 cc—somewhat larger than that seen in a great ape (Figure 14.5). The bottle-nosed dolphin has a brain volume of about 1,118 cc, which is
nearly human-sized (Hofman, 1988).
Many scientists find absolute brain size values to be of limited usefulness in
understanding brain evolution or the relationship between brain size and behavior.
After all, it comes as no surprise that bigger animals have bigger brains than smaller
animals, but just because a big animal has a big brain does not mean that the animal
is more intelligent. For many years, scientists have tried to determine ways to measure brain size relative to body size. Researchers such as Harry Jerison (1991) and
Robert Martin (1983) have shown that the relationship between brain size and body
size is somewhat more complicated than a simple linear relationship. By looking at
large numbers of mammal species, they derived equations that allow us to calculate the expected brain size for a mammal of any size. The encephalization quotient (EQ)
is a ratio of the actual brain size to the expected size. Thus mammals that have EQs
greater than 1.00 have brains that are larger than expected for a mammal of their
size; an EQ less than 1.00 means that it is smaller than expected.
Returning to Table 14.1, we see that humans have the largest brains not only
in absolute but also in relative terms, as measured by the EQ. In general, anthropoid primates have EQs greater than 1.00,
indicating that their brains are larger than
would be expected for mammals of their size.
So even though cattle and horses have brains
that are ape-sized in absolute terms, their EQs
are smaller than those of apes because of their
larger body sizes. It is generally assumed that
the larger brain size in anthropoid primates has
evolved in conjunction with the evolution of
complex social behavior and adaptation to the
arboreal environment.
Can we say that mammals with higher
EQs are in some sense “smarter” than those
with lower EQs? Yes and no. Terrence Deacon
(1997) points out that the encephalization quotient is derived from both brain size and body
size and that there is a tendency to overlook
the fact that animals face strong selection pressures that shape body size as well as brain size.
Among dog breeds, for example, chihuahuas
are more encephalized than German shepherds; artificial selection on chihuahuas has
driven body size down at a faster rate than brain size ( Figure 14.6). But no one (except chihuahua fanciers) would argue that a chihuahua is smarter than a German shepherd. In anthropoids, small or even dwarfed
species, such as the squirrel monkey in the New World or
the talapoin monkey in the Old World, have high EQs.
Again, rather than interpreting this as a sign of large
brain size, we could also see it as an example of selection
for small body size, which is probably more correct.
Brain Size and the Fossil Record
In previous chapters, you read that increasing brain size
is a characteristic of genus Homo. A compilation of average cranial capacities of different hominin fossil taxa is
presented in Table 14.2. (Please note that the H. sapiens
values in Tables 14.1 on page 365 and 14.2 differ because
they are based on different samples.) As you can see, the
different groups can be sorted to some extent according
to their cranial capacities and EQs.
Early Hominins and Robust Australopithecus Brain size increases from the
early australopithecines (A. afarensis and A. africanus) to the “robust australopithecines,” or Paranthropus. The early australopithecines have cranial capacities in the
range of 400 to 500 cc, whereas the later A. robustus and A. boisei are in the 475 to 530
cc range. Are the robust australopithecines species more encephalized than the earlier
australopithecines? Estimating body mass of fossilized individuals is very difficult and
depends on how well sizes of available parts of the skeleton correlate to overall body
size. EQs calculated for any individual fossil specimen therefore should be taken with
a grain of salt. Henry McHenry (1992; see also Kappelman, 1996) estimates that A. afarensis, A. africanus, and A. robustus had male body sizes of 40 to 45 kg and female sizes
of 30 to 32 kg; A. boisei was about 10% larger. These estimates indicate that these hominins were smaller than contemporary great apes; given that their cranial capacities
were at least as large, we can conclude that gracile and robust australopithecines were
indeed more encephalized than the great apes. In addition, the brain size increase
seen in the robust forms relative to the earlier forms may reflect a further increase
in encephalization. However, the reworking of the robust australopithecine skull in
response to the biomechanical demands of hard object chewing could have increased
cranial capacity without changing brain size. The relationship between cranial capacity and brain size varies somewhat across species, and the relatively small increase in
cranial capacity we see in going from gracile to robust australopithecines may or may
not have resulted in (or been the result of) more brain tissue (Allen, 2009).
Early Homo and Homo erectus Hominin fossils assigned to Homo habilis or early
Homo have cranial capacities substantially larger on average (by 25–30%) than those
seen in Australopithecus or the great apes (see Chapter 11). Although the smallest
early Homo specimens (for example, KNM-ER 1813, which has a cranial capacity
of 509 cc) and the largest gorillas may overlap in cranial size, the relatively small
habiline body size, estimated by McHenry (1992) to be 52 kg for males and 32 kg
for females, combined with the larger brain size, represents a clear increase in
encephalization over earlier hominins. As you read earlier, the appearance of H.
habilis roughly coincides with the appearance of stone tools in the archaeological
record, providing evidence of at least one kind of cognitive evolution.
The average cranial capacity of fossils assigned to H. erectus shows an even more
profound jump than H. habilis in both relative and absolute size compared with
earlier hominin taxa. Although both brain and body size increased in H. erectus,
brain size may have increased relatively more quickly leading to an increase in encephalization (Kappelman, 1996). As discussed in Chapter 12, H. erectus was widely
distributed geographically and exhibited gradual change over its more than 1 million years in existence. On average, the earliest H. erectus specimens (such as KNMER 3883 and KNM-ER 3733) have smaller cranial capacities than do later specimens.
Thus the range of cranial capacities seen in H. erectus specimens is quite large (from
650–1,250 cc), which is one reason that some investigators have justified splitting the
taxon into two or more species.
Archaic Homo sapiens, Neandertals, and Modern Homo sapiens Cranial
capacities in the modern range are found in both archaic H. sapiens and Neandertal
specimens. Indeed, one of the apparent paradoxes of the later hominin fossil record
is that Neandertal cranial capacities often exceed the average cranial capacity of modern humans (see Table 14.1 on page 365 and Table 14.2). Even the archaic H. sapiens
mean is within the range of modern H. sapiens. The increase in average cranial capacity from H. erectus to the later Homo species is quite
profound and undoubtedly exceeds any increase in body size. Thus
the hominin trend for increasing brain size and encephalization continues—and even accelerates—through the appearance of archaic H.
sapiens and Neandertals.
What about the apparent decline in brain size in modern humans compared with Neandertals and even with earlier modern
humans? We should keep in mind that there may be some kind of
sampling bias (for example, toward larger males); after all, we have
only small numbers of fossils available to compare with large numbers of modern humans. More critically, John Kappelman (1996)
points out that the larger body size of archaic H. sapiens and Neandertals, relative to modern humans, often is overlooked or underemphasized (see Chapter 12). Thus modern humans are more
encephalized than Neandertals because their bodies are much
smaller but their brains are almost as large as Neandertal brains
(Figure 14.7).
Although Neandertal and modern human brains are similar in
size, their overall shapes are quite different. Modern humans have
brains that are much more globe-shaped than Neandertal archaic
Homo sapiens brains (Lieberman et al., 2002; Bruner, 2004). This
“globularization” may reflect in particular changes in the parietal
lobes and the region around the border of the temporal and parietal lobes. Studies of endocasts of very young Neandertal and human children suggest that this difference in shape emerges very
early, within the first year of life (Gunz et al., 2010). The globularization of the human brain thus appears to reflect a unique pattern
of brain growth and development within primates, which may be
distinct from changes in size.
Brain size increase and increased encephalization have characterized hominin
evolution over the past 3 to 4 million years (Figure 14.8). These trends have become
more marked over the past 2 million years, as absolute brain size has nearly tripled.
During the past 2 million years, increases in brain size have outpaced increases in
body size, thus leading to increasingly encephalized hominins. Although brain size
and encephalization are not everything, expanding brain size in the hominin lineage clearly reflects an adaptation, given how “expensive” brain tissue is (see Insights
and Advances: The Ten-Percent Myth: Evolution and Energy).
Brain Reorganization
As the brain has expanded, its functional organization has also changed. Functional
reorganization can occur in three ways. An anatomical region of the brain (linked to
some function) can become larger or smaller compared with the rest of the brain.
Functional regions of the brain can shift or change position, which may or may not
be associated with regional expansion or contraction. Finally, new behaviors may
lead to the evolution of new functional fields, which would supplant or enhance
previously existing functional associations in those areas (as occurs with the development of a new complex behavior such as language; see below).
In the human brain, an example of size reorganization can be seen in the
olfactory bulbs, which control our sense of smell; these are small, knob-like structures found on the bottom of the frontal lobes in each hemisphere (Figure 14.9).
In humans, these measure only about 0.1 cc in volume (Stephan et al., 1981),
reflecting our decreasing reliance on smell. In contrast, wolves have olfactory bulbs
that are about 6 cc in volume, a sixty-fold advantage over the human-sized olfactory
bulb. Olfactory reduction is characteristic of most haplorhine species ( although
more pronounced in humans); humans have olfactory bulbs that are about the
same size as those found in strepsirhine species whose brains are only 1%–2% the
size of human brains.
Another part of the human brain that has undergone reorganization is the primary visual region, the part of the brain where visual information from the eyes is
initially processed. Although it is present in the occipital lobes (the rear portion of the
cerebrum) in both humans and other primates, in humans the primary visual region
is located in a sulcus on the inner surface of the lobe, whereas in primates the primary visual cortex encompasses most of the lobe’s outer surface. Furthermore, the visual cortex is smaller than we would expect for a primate brain its size: It is
only about 1.5 times larger than the visual cortex of a chimpanzee or gorilla,
whereas the brain as a whole is about three times larger (Stephan et al.,
1981). The reduction and shift of the visual region in primates presumably
has allowed the expansion of the parietal association cortex, a region where
sensory information from different sources is processed and synthesized. It
may be possible to track some organizational changes in the brain by studying
brain endocasts from fossil specimens (Figure 14.10), although this is an area
of study that has prompted much debate over the years (Allen et al., 2006).
Language: Biology and Evolution
Much of what makes human behavior more complex and more sophisticated
than the behavior of other animals depends on our possession of spoken
language. Language is an adaptation. It is easy to imagine that a social group
of hominins who possess language would have an advantage over a social
group of hominins who did not. But language ability is as much an anatomical as a behavioral adaptation. As we will see, modern humans are shaped by
natural selection—in the anatomy of their throats and respiratory system and
in various aspects of the structure and function of their brains—to produce
language.
What is language? Language is the system of communication used by members
of the human species. Although linguists differ on which features are most critical
in defining language, they all tend to agree on certain critical aspects that make language a unique form of animal communication. Language is spoken, and we are anatomically specialized to produce language and to process language-oriented sounds.
Language is semantic: The words we use when speaking have meanings that represent
real-world objects, events, or actions. Language is phonemic. Words are made from
small sound elements called phonemes; there is no biological limit to the number
of words that can be formed from phonemes and there is no intrinsic association
between a word and the object or concept it represents. Finally, language is grammatical. All languages have a grammar, an implicit set of rules that governs the way word
classes are defined and used. Although there may be a limit on the number of words
a person can know, there is no limit on the ways they may be grammatically linked
together. Grammar allows recursion, the ability to string together clauses in a sentence, or to embed clauses one within another. Some cognitive scientists believe that
recursion in language reflects the unique ability of the human mind to keep track of
multiple ideas, objects, and processes all at the same time. As a child acquires its first
language, he or she assimilates the grammatical rules of language subconsciously.
Language in the Brain
We can define a language area of the brain as any part of the brain that is activated
during the production or comprehension of speech. The classical language regions
are found around the left (in the vast majority of people) Sylvian fissure, or perisylvian
language area (Figure 14.11). In the frontal lobe, there is Broca’s area. As we saw earlier,
a lesion in Broca’s area causes a disruption in speech production (an aphasia), yet
comprehension remains intact. At the posterior end of the Sylvian fissure, spanning
the top of the temporal lobe and the bottom of the parietal lobe, is another language
area that was identified by German physician Carl Wernicke in 1874. Wernicke’s area
lesions cause a person to have difficulties in speech comprehension. People with Wernicke’s area aphasia produce fluent but nonsensical speech, substituting one word for
another or producing incomprehensible strings of words. Wernicke predicted that
because it is likely that his area and Broca’s area are in communication, different
lesions in the white matter joining the two should produce aphasias with different
symptoms. These conduction aphasias have been observed; for example, a lesion in
the projection from Wernicke’s area to Broca’s area causes someone to produce fluent, nonsensical speech while retaining comprehension (Damasio & Damasio, 1989).
Wernicke’s insights about conduction aphasias taught us to think about language as
the product of interactive networks in the brain rather than of just one or two areas.
Language Lateralization When a function of the brain typically and consistently
occurs in only one of the hemispheres, we say that function is lateralized. In 95% of
people, the perisylvian language area is in the left hemisphere. Most people are also right-handed, and because motor control of one side of the body is housed in the
opposite side of the brain, it is very likely that right-handedness and language ability
evolved in tandem. The classical view that both language and right-handedness are
associated with the left hemisphere has led to the notion of left hemisphere dominance over the right hemisphere (except in about half of the left-handers—who
make up about 10% of the population—who have right hemisphere dominance).
Although it is easy to focus on the classical left perisylvian regions as the seat of
language, keep in mind that lesions in other parts of the brain also disrupt normal
speech. Lesions in the right hemisphere (of people with left hemisphere language
dominance) disrupt the musical or prosodic elements of speech. Prosody is essential
for speech to sound normal; otherwise, it would have the flat sound of computersynthesized speech.
Language in the Throat
Although there is little evidence that evolving language capabilities has cost us anything in terms of brain function—just the opposite, in fact—it is quite clear that the
rearrangement of the anatomy of our throats for language purposes has introduced
new risks in everyday life that our ancestors did not have to worry about (Laitman,
1984; Lieberman, 1991). To offset these risks, there must have been a strong selective advantage for the development of language abilities over the course of hominin
evolution.
The supralaryngeal airway is a more precise way to describe the parts of the throat
and head that have undergone changes during hominin evolution (Figure 14.12). As
the name suggests, it is that part of the airway that is above the larynx, or voice box. The
larynx sits at the top of the trachea and has vocal folds (vocal cords), which can modulate the passage of air through the trachea to produce different sounds. The cavity
above the larynx, at the back of the mouth, is known as the pharynx. The posterior part
of the tongue, the epiglottis, and the soft palate form the boundaries of the pharynx.
When we compare the supralaryngeal airway of a human with that of a more typical mammal, such as a chimpanzee, we can see several differences that have profound
functional implications (Figure 14.12). First, the larynx in humans is much lower
than in other mammals. The new position of the larynx leads to an expansion of the
pharynx. This expanded pharynx’s anterior wall is formed uniquely in humans by a
shortened and rounded tongue, is much more efficient for modifying the stream of air
passing through the larynx to generate a greater variety of sounds, leading to fully articulate speech. These changes in anatomy have a profound cost; however, they greatly
increase the risk of choking on food or liquid. There is too much distance between
the human larynx and nasal cavity for a sealed connection to form between the two,
as it does in the typical mammal. The epiglottis and soft palate are separated by the
rear part of the tongue. Everything we swallow must pass over the incompletely sealed
opening of the larynx, which greatly increases the risk of choking and suffocation.
Interestingly, human babies less than 1 year old have a supralaryngeal anatomy that
more closely resembles the mammalian norm. This allows them to drink, swallow, and breathe at the same time, which greatly enhances their suckling ability. During the
second year, the larynx begins the shift to the adult position, which increases their risk
of choking while increasing their ability to produce articulate speech. Darwin noted
in On the Origin of Species that the position of the trachea in the human throat was an
example of natural selection working with what history makes available to it.
Language Ability and the Fossil Record
The brain and supralaryngeal tract—anatomical structures that demonstrate most
clearly our adaptations associated with the production of spoken language—are
composed primarily of soft tissues that do not fossilize. However, we do have endocasts, which might preserve information about gross changes in the brain that might
be associated with the development of language. In addition the supralaryngeal tract
is connected by muscles and ligaments to bony structures at the base of the cranium
and in the neck. It is possible some insights into the evolution of the soft tissues of
the throat may be gained by examining these bony structures.
Endocasts and the Evolution of Brain Asymmetries Language in the brain is
associated with a leftward lateralization of function. Is it possible that asymmetries in
gross brain structure may be pronounced enough that they can be seen in endocasts,
indicating the possible origins of spoken language in the fossil record?
For example, researchers have looked for evidence of asymmetry in Broca’s
area. The endocast of 1470 (H. habilis) has a well-preserved left inferior frontal region (the location of Broca’s area). Anthropologists interested in hominin endocasts
tend to agree that 1470 resembles humans more than pongids in the region corresponding to Broca’s area (Holloway, 1976, 1999; Falk, 1983b; Tobias, 1987). A similar
claim has been made for a more recently discovered Indonesian H. erectus specimen,
Sambungmacan 3 (Broadfield et al., 2001). Although this specimen has protrusions
in the inferior frontal lobe on both left and right hemispheres, the total size of the
protrusion is larger in the left hemisphere, indicating the possible presence of a Broca’s area in that hemisphere. These asymmetries may indicate the development of
spoken language (or its precursors) in species ancestral to modern Homo sapiens.
Hyoid Bone According to some investigators, the bony remains—especially the
base of the cranium—of fossil hominins yield real clues to the form and position
of the supralaryngeal tract, offering insights into the vocal abilities of these earlier
hominins (Laitman and Reidenburg, 1988). However, most of these claims are
somewhat controversial and reflect the inherent difficulty of reconstructing complex
soft tissue structures from fossil remains (Arensburg et al., 1990).
A potentially more direct source of evidence about the speech abilities of extinct
hominins has come with the discovery of a Neandertal hyoid bone from Kebara
Cave, Israel, dating to about 60,000 years ago (Arensburg et al., 1990). The hyoid
is a small, free-floating bone (that is, it does not articulate with any other bones)
that sits in the throat in front of the larynx and in close association (via muscles and
ligaments) with the mandible, larynx, and other structures.
Arensburg and colleagues argue that the Kebara hyoid is
essentially human-like in its size and shape and very distinct
from that of a chimpanzee, for example (Figure 14.13).
The hyoids of chimpanzees and other apes have a box-like
body with two narrow, flaring horns, whereas the human hyoid has a much more regular horseshoe shape. According
to Arensburg and colleagues, its position was human-like
within a neck that was similar in length to human necks.
Thus, they conclude that the larynx was also in a humanlike position and that Neandertals were fully capable of
producing speech. In contrast, the recently discovered A.
afarensis juvenile skeleton from Dikika, Ethiopia, dating to
3.3 MYA, has a hyoid bone that is much more ape-like than human-like (Alemseged et al., 2006). If hyoid shape is indeed a good indicator of spoken language ability, then it would seem it is a behavior that had not evolved in
the earlier australopithecines.
Scenarios of Language Evolution
The absence of direct evidence concerning the evolution of language ability means
that there are many theories or models for how it might have occurred (Hewes,
1999). For example, it has been suggested that language “piggy-backed” on throwing
ability (improved hunting efficiency), which is another activity associated with handedness (Calvin, 1983); that it replaced grooming as a social facilitator in increasingly
large groups (Dunbar, 1997); or that it critically enhanced the formation of exclusive
reproductive relationships in the context of multimale/multifemale social groups
(Deacon, 1997). Most of these suggestions are untestable, although it is possible to
assess the plausibility of some of the claims based on contemporary data. It is safe to
say that no single model or theory of language origins is accepted by the majority
of anthropologists, psychologists, or linguists, and that we can expect many more
models to be put forth in the coming years that will incorporate new insights into the
nature of brain and language.
The Evolution of Human Behavior
Studying the evolution of the human brain and language serves as a foundation for
developing a broader understanding of the evolution of human behavior in general.
Human behavior is, of course, an enormous topic, and we can only touch on a few
aspects of its evolution in this chapter. However, let us begin by considering the ways
in which biological anthropologists analyze the evolution of human behavior.
The Evolution of Human Behavior: Four Approaches
Anthropologists and other scientists use varied approaches to study the evolution
of human behavior, depending on their particular research interests and training (Figure 14.14). Four of the most common approaches are paleontological reconstructions of behavior, biocultural approaches, evolutionary psychology, and
human evolutionary (or behavioral) ecology. The examples covered in this chapter
make use of the latter three approaches.
Paleontological Reconstructions of Behavior In Chapters 10 to 13 we discussed several reconstructions of the behavior of earlier hominins. These reconstructions were based on the anatomy of extinct hominins and, when present, the
archaeological remains with which they were associated. They were also based on
correlations among behavior, anatomy, and ecology we have observed in nonhuman
primate species and in contemporary humans, especially those living under traditional hunter–gatherer conditions. Any reconstruction of the behavior of our hominin ancestors is a synthesis of both paleontological and contemporary data.
Biocultural Approaches It is clear that human cultural behavior has influenced
human evolution. One aspect of human behavior that we have already discussed
in detail—language—is a prime example. Other examples include the adoption of
slash-and-burn agriculture, which had an indirect effect on the evolution of the sickle
cell polymorphism, and the development of dairying in some populations, which
was a direct selective factor in the evolution of lactose tolerance (Chapter 6). As we
will see below, there are instances where human biology may influence patterns of
behavior observed across different human cultures.
Evolutionary Psychology The relatively new discipline of evolutionary psychology
is characterized by an adherence to three main principles. First, human and animal behavior is not produced by minds that are general-purpose devices. Rather, the
mind is composed of cognitive modules with an underlying neuroanatomical basis
that express specific behaviors in specific situations. Language and visual processing
are prime examples of this kind of modular processing, but evolutionary psychologists believe that almost any adaptive behavior (say, a fear response to a snake moving
in the grass) could be considered in modular terms. Second, cognitive modules are
complex design features of organisms. Because natural selection is the only way to
evolve complex design features, evolutionary psychology focuses on understanding behaviors or cognitive modules as adaptations. Third, for most of our history,
humans and hominins have lived in small groups as hunter-gatherers. Evolutionary psychologists believe that our evolved behavior may reflect or should be interpreted in terms of this hypothetical environment of evolutionary adaptedness (EEA)
( Barkow et al., 1992; Tooby and Cosmides, 2000).
Human Evolutionary (or Behavioral) Ecology In contrast to evolutionary psychology, which focuses more on psychological experiments and surveys of people
living in developed countries, human evolutionary ecology focuses on the ecological
factors that influence reproductive success in the few remaining hunter–gatherer
populations. Among the groups studied most intensely have been the Yanomamö
of Amazonia (Chagnon, 1988, 1997), the Aché of Paraguay (Hill & Hurtado, 1996),
and the Hadza of Tanzania (Hawkes et al., 2001). Topics of interest to human evolutionary ecologists include the relationship between status and reproductive success,
demographic effects of tribal warfare and aggression, and the underlying social impact of hunting and food sharing. Researchers use data on contemporary hunter–
gatherer groups to refine models that purport to reconstruct the behavior of extinct
hominins (Marlowe, 2005).
Traditional Lives in Evolutionary Ecological Perspective
Over the past four decades, human evolutionary ecologists have undertaken
intensive study of traditional cultures to better understand the interplay between
biological and cultural factors in human behavior and human behavioral evolution (Figure 14.15). Studies of traditional hunter–gatherers and
traditional agricultural cultures are important because their
lifestyles reflect more closely the natural selection environments (the EEA) that shaped hominin evolution, until the
advent of agriculture and large-scale societies starting about
10,000 years ago.
Wealth, Reproductive Success, and Survival
One of the basic tenets of human evolutionary ecology is
that cultural success should be related to increased fitness
(Irons, 1979). William Irons tested this hypothesis in a study
of fertility and mortality among the tribal Turkmen of Iran.
In this culture, wealth (in terms of money, jewelry, and consumable goods) is a primary measure of cultural success.
Irons found that for men, fertility and survivorship were
higher for the wealthier half of the population than for the
poorer half (Figure 14.16); survivorship was significantly
higher for the wealthier women, but there was no difference in fertility. He also
found that reproductive success was more variable among men than among women
(that is, the difference between the richer and poorer halves was more pronounced
for men than for women), as predicted by sexual selection theory.
Monique Borgerhoff Mulder (1987, 1990) looked at the relationship between
wealth and reproductive success in a different population, the Kipsigis of Kenya (Figure 14.17 on page 378). The Kipsigis are a pastoral people who moved into Kenya
from northeastern Africa in the late eighteenth century. The wealth of a Kipsigis
man is defined in terms of his land holdings, the number of animals he has, and his
household possessions. Borgerhoff Mulder found that all these measures correlate
strongly to amount of land owned, so she used that as her primary statistic of wealth.
The Kipsigis practice polygyny, which means that a man can have more than one
wife at a time. When a man wants to marry a young woman, he approaches her parents with an offer of bridewealth, a payment that can equal up to a third of an average
man’s wealth. Borgerhoff Mulder looked at wealth and reproductive success among
Kipsigis men in a series of different age groups and found a strong correlation between wealth and number of offspring. For example, in a group of forty-four men
who were circumcised between 1922 and 1930 (circumcision marks coming of age),
there was a very high correlation between number of offspring and acres of land owned (Figure 14.18). Ownership of 30 acres correlated to
having fifteen to twenty surviving offspring, whereas men
with 90 acres had twenty-five to thirty offspring. In general,
the fertility of the wives of richer and poorer men was approximately the same. Wealthier men have more children
because they can have more wives, being able to afford
more bridewealth payments. And although larger families
may lead to increased wealth, Borgerhoff Mulder found no
evidence that this was the causal direction: Wealthier men
were able to afford large families, not the other way around.
The Turkmen and Kipsigis studies, and others done
elsewhere, support the hypothesis that one measure of cultural success—wealth—correlates with reproductive success.
However, this correlation does not generally hold for developed, urbanized, capitalist cultures, where higher socioeconomic status typically is not associated with a higher birth
rate. This is an important example of the kind of fundamental biocultural change that can occur in a society when it
transforms from an undeveloped to a developed economy
Physiology and Ecology
Another method for quantifying the relationship between cultural and ecological
factors in human behavior is to look at the way physiological measures vary across
ecological contexts. For example, Peter Ellison (1990, 1994) developed a method of
measuring levels of reproductive hormones in saliva as a noninvasive means to assess
reproductive function in women living in diverse environments.
Progesterone is a steroid hormone produced by the corpus luteum and the placenta that prepares the uterus for pregnancy and helps maintain pregnancy once
fertilization has occurred. Progesterone levels measured in saliva correlate with ovarian function. Ellison and his colleagues found that salivary progesterone levels are
strongly correlated with age over the course of a woman’s reproductive life (between
about ages 15 and 50 years). Progesterone levels increase from a baseline level at the
end of puberty, peaking between 25 and 30 years of age, and dropping off thereafter.
Ellison suggests that ovarian function matures at approximately the same age as the
pelvis becomes structurally mature (early to mid-20s).
Studies among two traditional agricultural groups, the Lese of Zaire and the
Tamang of Nepal, and women from the Boston area, showed that the basic agedependent curve of salivary progesterone production was the same in all three populations (Figure 14.19). Ellison believes that this pattern probably represents a
fundamental feature of human reproductive physiology. This discovery refines our
view of the female reproductive years as an evolved life-history stage (beginning at
menarche and ending at menopause).
Although the shapes of the progesterone-versus-age curves were the same in Boston, Lese, and Tamang women, the amount of progesterone produced varied among
the groups. Boston women, who presumably had the most nutritionally rich environment with few infectious diseases, had higher progesterone levels at every age than
were found in the other two populations. Ellison suggests that chronic stress that
delays growth and maturation, such as nutritional deficiencies, could lead to lower
levels of ovarian function throughout the lifetime. Such a stress-response relationship could be adaptive because in a stressful environment it may be better to devote
more effort and energy to body maintenance and survival rather than reproduction.
Another steroid hormone whose levels can be measured in saliva is testosterone.
Testosterone is produced primarily in the testes and ovaries; it is known as the “male hormone” since the testes produce about 10 times as much as the ovaries, and testosterone
is primarily responsible for the development of the primary male sexual characteristics
in the fetus and the secondary characteristics at puberty. It has also been hypothesized
that testosterone is an important modulator of behavior, especially in the context of male
dominance and reproductive behavior. Much evidence for this hypothesis has been gathered from studies of numerous mammal species, but what is the situation in humans?
One way to test the hypothesis claiming that testosterone influences behaviors
related to male–male competition and mate-seeking behavior is to compare testosterone levels in men who are in a committed relationship with those who are single.
T. C. Burnham (2003) and his colleagues found that in a sample of 122 American
business school students, men who were married or in a committed relationship had
21% lower salivary testosterone levels than those who were single. Peter Gray and his
colleagues (2006) looked at testosterone levels in a group of men in Beijing, China,
and they found that married non-fathers had slightly lower levels than unmarried
men but the difference did not reach statistical significance; however, they did
find that married fathers had significantly lower levels than either of the other two
groups. In a study in East Africa, Martin Muller and his colleagues (2009) compared
testosterone levels between non-fathers and fathers in Hadza foragers and in Datoga
pastoralists. Hadza fathers are much more involved in paternal care than Datoga fathers, thus Muller and his colleagues predicted that in the Hadza, testosterone levels
should be lower in fathers rather than non-fathers, while in the Datoga, there should
be no difference. This is exactly what they found: The intensive childcare given by
Hadza fathers appears to suppress testosterone production. Note that there was no
overall difference in testosterone levels between the Hadza and Datoga men
These studies demonstrate that testosterone levels vary
in human males according to their marital/parental status,
and that these patterns can be observed in a variety of biological and cultural groups. They support the hypothesis
that testosterone level is a modulator of, or reacts to, an
individual male’s reproductive situation. Burnham and colleagues (2003) point out that since testosterone may impair
immune function and encourage risk-taking, lower levels of
testosterone in married men may help explain the fact that
married men generally are healthier and have lower mortality than unmarried men.
Hunting, Gathering, and the Sexual Division of Labor
Recent research on contemporary hunter–gatherer groups
has revolutionized our knowledge of how people without
agriculture acquire the food they eat and how hunting and
gathering patterns in hominins may have evolved. It has become increasingly clear
that earlier speculations (Lee & DeVore, 1968) were based on inadequate understanding of hunter–gatherer lifeways. The concept of “man the hunter, woman the
gatherer” reflects a division of labor between the sexes in all human cultures, but it is
all too easy to turn it into a simplistic, stereotypical picture of evolved, hardwired gender roles (Bird, 1999; Panter-Brick, 2002). Furthermore, observing sex differences in
food acquisition practices is not the same as explaining why they exist.
In almost every traditional foraging culture, both men and women devote a substantial portion of their time and energy to the search for and acquisition of food.
And in almost every culture, despite the fact that they live in the same environment,
men and women exploit different aspects of that environment when acquiring food,
leading to a pronounced sexual division of labor, although not necessarily along
the simplistic division that “men hunt and women gather.” For example, among the
aboriginal peoples of Mer Island in the Coral Sea, both men and women forage for
food on the coral reef. Men concentrate on using large spears to kill large fish swimming around the edges of the reef while women walk the dry part of the reef, collecting shellfish or catching small fish or octopus with small spears (Figure 14.20). Women
almost always succeed in bringing home a reasonable amount of food, whereas the
men have much more variable success (Bird, 1999). In the Hadza of Tanzania, men
concentrate on large game hunting while women focus almost exclusively on foraging
for berries, nuts, fruits, and roots (O’Connell et al., 1992; Hawkes et al., 1997).
There are several models for the origins of the sexual division of labor. The cooperative
provisioning model, based on the study of monogamous birds, predicts that the sexual division of labor occurred as a result of the evolution of monogamous relationships, because
it would allow the pair to more fully exploit the environment if they did not compete with
each other for resources (see discussion of Lovejoy’s model in Chapter 10). An alternative
model, the conflict model, suggests that hominin males and females were already exploiting the environment in fundamentally different ways before males began contributing
energy and resources to females and their young (Bird, 1999). The “sexual division of
labor” is not really a division but reflects the fact that males and females have different
problems to overcome (conflicts) in the course of mating, reproduction, and parenting.
It is nonsensical to ask whether hunting or gathering is more important. Neither
provides more energy than the other on a regular basis. The productivity of hunting
and gathering varies by season, environment, and a host of other factors (Kaplan
et al., 2000). Women and men do vary in the package size of the food they focus on
acquiring. Women concentrate on small foodstuffs that tend to be predictable,
immobile, and obtainable while caring for infants and young children. Even though
she almost always receives assistance from others, including female relatives and
the father of her children, an individual woman is responsible primarily for feeding
herself and her children
Men concentrate on obtaining foods in large sizes that they cannot consume at
once by themselves and that they redistribute to families or the larger social group.
These foods almost always come in the form of dead animals, which may be obtained
by hunting, trapping, fishing, or even scavenging. In some Melanesian societies, however, men compete to grow the largest yams, which, although they are too fibrous
to eat, can be distributed and used for propagation of new plants (Weiner, 1988).
Big yams aside, animals provide protein and fat in quantities not available from any
other source, and animal food is almost always highly prized in human cultures. As
Hilliard Kaplan and colleagues (2000, p. 174) state, “The primary activity for adult
males is hunting to provide nutrients for others . . . . [Hunting] is a fundamental
feature of the human life-history adaptation.”
Sexual Selection and Human Behavior
The sexual division of labor sits firmly within the broader context of sexual selection. As
we discussed in Chapter 5, sexual selection was Darwin’s other great idea about mechanisms underlying evolutionary change in animals, including humans. The study of
human sexual behavior has been revolutionized over the past 25 years by investigators
who take sexual selection seriously in our species. The development of an evolutionary
perspective has informed our views on human reproductive strategies, sex and gender
differences in behavior, and cross-cultural patterns of attractiveness and mate selection
(Symons, 1979; Fisher, 1992; Buss, 2003). For example, research on human mate selection and standards of attractiveness in different cultures indicate that women tend to
value resource-providing ability in their partners, whereas men tend to value youth and
appearance (indicators of reproductive potential) in their potential partners (Buss,
2003). These observations are consistent with predictions derived from mammalian
evolutionary biology. Of course, these are statistical patterns generated from surveys of
large numbers of individuals. Obviously, different cultures define sexual attractiveness
differently, and there is much individual variation in sexual preferences. Nonetheless,
according to many evolutionary researchers, the statistical patterns of sexual behavior
that are observed across cultures are not easily explained by cultural convergence. Instead, they may reflect underlying behavioral trends that have been shaped by natural
selection. For example, it has long been noted that the behavior of young males—
more so than an other age/sex category—is frequently at odds with accepted cultural
norms. Why should this be the case?
Risk-Taking Behavior
Sex difference in risk-taking behavior has long
been recognized, and found in several different
behavioral domains. When we look across human cultures, we find that as a group young adult
males (ages 15–29) have the highest death rates
from accidents or violence (Figure 14.21). For
example, death rates in motor vehicle accidents
for 20-year-old Americans are three to four times
higher in men than women (Hill & Chow, 2002).
Young males do not die from accidents more
often because they are unlucky but because they
are more likely to put themselves in risky situations (Figure 14.22 on page 382). Beyond accidents, young, single males take greater financial
risks with their money compared to their female
counterparts (Jianakoplos & Bernasek, 1998). In
addition, laboratory studies (in which risk taking
is assessed with a simulation) suggest that men respond to an acute stress by increasing risk-taking behavior, while women become more risk-aversive. (Lighthall et al., 2009). Proclivity
toward risk-taking behavior in males may reflect a significant sex difference in human behavior, which may have a long evolutionary history (Low, 2000).
Why should males engage in risk-taking behavior more than females? Bobbi Low
(2000) argues that the reason goes back to general sex differences in mammalian biology. For a female mammal, the costs associated with risk-taking behavior are unlikely
to outweigh the benefits. She is likely to be able to find mates and fulfill her reproductive potential throughout her lifetime, so she has no particular need to engage in
risk-taking behavior to acquire mates. On the other hand, male mammals vary much
more in reproductive success. A male mammal may engage in high-risk, potentially
very costly (even life-threatening) activities because such behaviors could have a potentially high reproductive benefit. For example, aggressive behavior between male
mammals over access to females is very common; it has clearly been selected for in the
context of sexual access to mates. Females may also find risk-taking in males to be attractive because they may consider it a manifestation of ambition or “good genes” or a
proxy for the ability to provide resources for the female and her offspring.
Elizabeth Hill and Krista Chow (2002) suggest that risky or binge drinking may
also be understood in the context of sexual selection for risk-taking behavior. First,
among college-age people, risky drinking is about 50% more common in men than
women (48% versus 33%, although figures vary depending on criteria for defining a
binge), and males are more likely to engage in driving after drinking. The peak age for
alcohol abuse in males is 15 to 29 years. College men who were not married were twice
as likely to engage in binge drinking as those who were married. These aspects of risky
drinking in young men suggest to Hill and Chow that it is another manifestation of the
evolved pattern of risk-taking behavior. They argue that risk-taking behaviors are not
deviant but that we should recognize them as an evolved response to environmental
instability. With specific reference to risky drinking at the individual level, Hill and
Chow suggest that dealing with instability in the person’s family or work life may be
one avenue of therapy for the treatment for alcohol abuse.
Inbreeding Avoidance and Incest Taboos
Evolutionary factors may have played an important role in shaping not only mate
choice preferences but also mate choice aversions. Inbreeding is defined as reproduction between close relatives. Close inbreeding has several major biological costs
(Rudan & Campbell, 2004). A highly inbred population or species loses genetic variability over time. Reduced variability means that the population cannot respond
quickly via natural selection to environmental change.
The likelihood that lethal or debilitating recessive alleles will be expressed is
increased when close relatives interbreed. Because relatives share a high percentage of their alleles, there is a greater chance (compared to unrelated individuals)
that they will both possess the same lethal recessives that may be passed on to their
offspring. Inbred individuals suffer from greater mortality or loss of fitness relative to less-inbred individuals in the same species; this phenomenon is known as
inbreeding depression (Mettler et al., 1988).
Inbreeding Avoidance and Incest Rules All human cultures have rules and
traditions that regulate sexual contact and reproductive relationships. Incest is any
violation of such rules by members of a kin group. Incest rules are sometimes explicit (stated in legal or customary form) and sometimes implicit (followed but not
overtly stated or codified). Definitions of kin vary from culture to culture and do not
always closely follow biological patterns of relatedness. For example, in American
culture, sexual contact between stepparents and stepchildren, or between relatives
linked by adoption, is generally regarded as being incestuous, although from a biological standpoint a pregnancy that resulted from such a mating would not constitute inbreeding.
Both cultural and biological scientists agree on the universality of cultural rules
governing sexual relations between close kin—the incest taboo—but they differ on why it exists. For many years, Freudian ideas dominated cultural explanations of
the incest taboo: Incest rules were necessary to prevent people from acting on their
“natural” desire to commit incest. The evidence that people innately desire to commit incest is very slight, and the Freudian viewpoint, despite its historical popularity,
has little cross-cultural, empirical support (Thornhill, 1991). Biological theories of
inbreeding avoidance have focused on the fact that mechanisms that encourage outbreeding should be selected for; the cross-cultural universality of the incest taboo,
which is essentially a mechanism for outbreeding, is taken to be evidence that such
an adaptive mechanism may be present in the human species as a whole Brother–Sister Inbreeding and the Westermarck Hypothesis Finnish anthropologist Edvard Westermarck (1891) long ago suggested, in what became known as
the Westermarck hypothesis, that siblings raised together develop an aversion to seeing
each other as reproductive partners when they are adults. In order for the aversion to develop, siblings must be in proximity to one another during a critical period,
usually thought to encompass the first 5 years of life. The psychological mechanism
governing this aversion may be an adaptation because it was probably selected for as
a mechanism to promote outbreeding.
Evidence for the Westermarck hypothesis comes from a variety of sources, including some natural experiments. In the mid-twentieth century, the kibbutz movement
in Israel led to the establishment of numerous small, independent communities dedicated to socialist and egalitarian principles. Similarly aged boys and girls were raised
communally in “children’s houses” in some of these kibbutzim (Shepher, 1983)
(Figure 14.23). In his groundbreaking study, anthropologist Joseph Shepher found
that of 2,769 marriages between children raised in kibbutzim, only 14 united couples
had been reared in the same children’s house. Shepher interpreted these results as
strong evidence for the Westermarck hypothesis. The child-rearing arrangement in
the kibbutz “fooled” biology (and the psychological mechanism leading to sexual
aversion) by bringing unrelated children into close proximity with one another during the critical period. In usual circumstances, children raised in close proximity
to one another are close relatives, and there should be strong selection pressures
against them mating with one another. Thus kibbutz children raised in the same
children’s house saw each other as siblings and did not see their housemates as
potential spouses.
Similar evidence supporting the Westermarck hypothesis has been obtained
from the study of sim-pua marriages in Taiwan (Wolf, 1966, 1970). Sim-pua is a form
of arranged marriage whereby a girl is adopted into a household at a young age
and then later expected to marry a biological son of the same family when they are
older. These marriages were found to have much higher rates of divorce and lower
numbers of offspring than non–sim-pua marriages. Anthropologist Arthur Wolf,
who conducted the research, suggests that these marriages often failed because of a
sexual aversion that developed between the adopted sister and her brother/groom
who were raised in close proximity during the critical period.
The Westermarck hypothesis is supported by evidence from these diverse
natural experiments and is based on a strong theoretical foundation in the context
of the biological costs of close inbreeding (although see Shor & Simchai, 2009 for a
critique). It applies only to sibling inbreeding avoidance, of course. Clearly, different
biological or cultural mechanisms would have to regulate intergenerational inbreeding avoidance.
We have traveled a great distance in this survey of the evolution of human
behavior—from the neuron to the cultural rules governing the sexual behavior of
close kin. The goal here has not been to provide a comprehensive rendering of
how human behavior evolved, but to introduce some of the basic approaches to
understanding this important topic. We will not really know the evolution of our species until we know how and why we behave the way we do. And we cannot understand
human behavior fully until we understand the ecological and cultural contexts in
which it evolved.