DOI: 10.1126/science.1170165
, 1298 (2009); 324Science
et al.Adam Powell,
of Modern Human Behavior
Late Pleistocene Demography and the Appearance
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46. Thanks to I. Levina and A. Verashchagina for translating
the Russian and Ukrainian archaeological materials;
P. Lambert and K. Kennedy for assistance with the
Californian and Indian archaeological evidence;
M. Alexander, K. Ames, B. Bertram, L. Luigi Cavalli-Sforza,
T. Clutton-Brock, W. Cote, E. Einhorn, D. Wood Gordon,
H. Kaplan, K. Hill, K. Howard, S.-H. Hwang,
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valuable contributions; and the Behavioral Sciences
Program of the Santa Fe Institute, the U.S. National
Science Foundation, the European Science Foundation,
and the University of Siena for support of this work.
The author declares no competing interests.
Supporting Online Material
www.sciencemag.org/cgi/content/full/324/5932/1293/DC1
Materials and Methods
Tables S1 to S5
References and Notes
5 November 2008; accepted 10 April 2009
10.1126/science.1168112
REPORTS
Late Pleistocene Demography and
the Appearance of Modern
Human Behavior
Adam Powell,
1,3
Stephen Shennan,
2,3
Mark G. Thomas
1,3
*
The origins of modern human behavior are marked by increased symbolic and technological
complexity in the archaeological record. In western Eurasia this transition, the Upper Paleolithic,
occurred about 45,000 years ago, but many of its features appear transiently in southern Africa
about 45,000 years earlier. We show that demography is a major determinant in the maintenance
of cultural complexity and that variation in regional subpopulation density and/or migratory
activity results in spatial structuring of cultural skill accumulation. Genetic estimates of regional
population size over time show that densities in early Upper Paleolithic Europe were similar to
those in sub-Saharan Africa when modern behavior first appeared. Demographic factors can thus
explain geographic variation in the timing of the first appearance of modern behavior without
invoking increased cognitive capacity.
T
he Upper Paleolithic (UP) transition,
which occurred in Europe and western
Asia about 45 thousand years ago (ka)
(1, 2), and later in southern and eastern Asia
(3, 4), Australia (5, 6), and Africa (7), is seen
by many as marking the origins of modern hu-
man behavior. UP material culture, usually
referred to as the Late Stone Age (LSA) in
Africa, is characterized by a substantial increase
in technological and cultural complexity, includ-
ing the first consistent presence of symbolic be-
havior , such as abstract and realistic art and body
decoration (e.g., threaded shell beads, teeth, ivory,
ostrich egg shells, ochre, and tattoo kits); system-
atically produced microlithic stone tools (espe-
cially blades and burins); functional and ritual
bone, antler, and ivory artifacts; grinding and
pounding stone tools; improved hunting and trap-
ping technology (e.g., spear throwers, bows, boo-
merangs, and nets); an i ncrease in the long-distance
transfer of raw materials; and musical instruments,
in the form of bone pipes (1, 2, 5, 7–9).
In Europe and western Asia, the UP transition
happened relatively rapidly, with most of the
characteristic features listed above appearing (the
“full package”), and is thought to coincide with
the appearance of anatomically modern humans
(AMH) in a region previously occupied by
Neandertals (10). In southern Siberia and north-
east Asia, microlithic technology appears be-
tween 43 and 27 ka (11), but a fuller UP package
is not evident until ~22 ka (12). The evidence
from south and southeast Asia and Australia also
points to a more gradual accumulation of modern
behavioral traits (ornamentation, use of ochre,
and possibly rock art) (3–6). These ar e thought to
first appear soon after the initial expansions o f
AMH into the regions but only become wide-
spread later on, ~30 ka (4) and ~20 ka, if not later
(5), in south Asia and Australia, respectively. In
Africa, the idea of a single transition has been
1
Research Department of Genetics, Evolution, and Environment,
University College London, Wolfson House, 4 Stephenson Way,
London NW1 2HE, UK.
2
Institute of Archaeology, University
College London, 31–34 Gordon Square, London WC1H 0PY, UK.
3
Arts and Humanities Research Council (AHRC) Centre for the
Evolution of Cultural Diversity, Institute of Archaeology,
University College London, 31–34 Gordon Square, London
WC1H 0PY, UK.
*To whom correspondence should be addressed. E-mail:
m.thomas@ucl. ac.uk
5 JUNE 2009 VOL 324 SCIENCE www.sciencemag.org1298
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contested (9) because there is strong evidence for
the sporadic appearance of many markers of mod-
ern behavior at multiple sites as early as 70 to 90 ka
(2, 9, 13), and possibly as far back as 160 ka (14).
The African Middle Stone Age (MSA) sites of
Ka t a n da, Dem o cr a t i c Rep u b l i c of Congo (~ 90 ka)
(9); Klasies River mouth (Howieson’s Poort and
Still Bay industries), South Africa (~65 to 70 ka)
(9, 15); and, in particular, Blombos Cave, South
Africa (~75 ka) (10, 13) present a striking array
of modern traits, including the earliest evidence
of abstract art (8, 13), as well as geometric blades,
barbed bone harpoon points (9), bone awls, and
marine shell personal ornaments (10). However,
these markers are intermittent and disappear be-
tween ~ 75 and 60 ka bef ore making a more stable
and widespread reappearance in the LSA start-
ing ~ 40 ka (7, 10, 13).
Notwithstanding the oversimplifications made
in the above outline, any adequate account of the
emergence of modern behavior would need to ex-
plain not only the transition itself but also its
heterogeneous spatial and temporal structuring (2)
and earlier transient appearance in sub-Saharan
Africa (9, 10, 13). It is now widely accepted that
AMH evolved in Africa ~160 to 200 ka (9, 16–18)
and expanded into most habitable parts of the Old
W or ld between 90 and 40 ka (19–21). If, as some
have suggested (22–24), the main cause of be-
havioral modernity is heritable biological change
just before the UP/LSA, then any such mutation(s)
would have had to rise to substantial frequencies
after human populations had dispersed out of Africa;
implying either their rapid spread around the world
in the past 45,000 years or , potentially , geographic
structuring of cognitive capacity . Furthermore, it is
difficult to account for the southern African evi-
dence with a late, biologically determined cognitive
advance. Many authors have argued that AMH
(1, 9, 10, 17, 20), and possibly even Neandertals
(8, 10), possessed the requisite capacities long
before the UP/LSA. This raises the further ques-
tion of why there was a delay of some 100,000 years
between anatomical modernity and perceived be-
havioral modernity (1, 17). A number of mecha-
nisms triggering the expression of modern behavior
have been proposed, many of which invoke demo-
graphic change as a causal factor . These include
expansion into new environments necessitating the
invention of new technologies (25), increased
subpopulation density escalating intergroup resource
competition (1, 25) or social organization (1), in-
creased intergroup interaction requiring various cul-
tural signaling mechanisms (6, 25, 26), and increased
stimulus for exoteric language (23, 27, 28). T wo
recent cultural evolutionary models (29, 30), which
explicitly demonstrate the positive effect of increas-
ing population size on the accumulation of beneficial
culturally inherited skills, have been proposed as an
integral explanatory component of the appearance of
modern behavior [see also (17)]. Here, we adapt and
extend Henrich’s tra n s missi on model (30)intoa
more realistic structured metapopulation, which
reflects plausible late Pleistocene conditions, to
investigate the effects of demographic factors on
the accumulation (or loss) of cultural complexity .
Henrich’s model (30) demonstrates that und er
certain critical conditions, directly biased transmission
can lead to cumulative adaptation of a culturally in-
herited skill, even when the transmission process is
inaccurate. Each individual in a population of size N
has a z value, z
i
, that measures their level of ability at
Fig. 1. Mean z values in the final (100th) generation,
averaged over 100 iterations, for a range of values of
skill complexity a and subpopulation density D.
Fig. 2. Regional mean z values (averaged over 100
iterations) over 100 generations in a heterogeneous
subpopulation density world. The 95% confidence
intervals for each region are given as dotted lines.
Fig. 3. An illustration, from a single iteration and shown at 25-generation intervals, of the spatial
structuring of skill accumulation in a heterogeneous subpopulation density world. The left side of each
subplot is populated at density D
high
(0.02) and the right side at density D
low
(0.002). Each subpopulation
is marked by a circle, centered on the spatial location of the group and with diameter proportional to its
mean z value. Regional mean z values are also given at the top of each subplot.
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some cultural skill or in some cultural domain.
Members of this population attempt to learn from
the maximally skilled individual (i.e., direct bias),
but an imperfect learning process leads on average
to a loss of skill (a reduction in z value), determined
by the parameter a. However, individual errors or
“inaccurate inferences” during transmission (the
extent of which are governed by a parameter b)
occasionally allow some learners to acquire a z
value greater than that of their model. Henrich
shows that as population size, N, increases, the
more likely it is th at the positive combined effect of
these occasional inaccurate inferences and the
selective choice of cultural model to copy will out-
weigh the degrading effect of low-fidelity transmis-
sion. This results in an increase in the mean level of
skill in the population,
z.Hetermsthis“cumulative
adaptive evolution” and derives the critical popula-
tion size necessary , N*, for this to occur for
specific ratios of a and b (30, 31).
W e introduce a stochastic transmission model
analogous to the one presented by Henrich that
incorporates both vertical and skill-level dependent
oblique learning processes. We place individuals in
G subpopulations, each of size N, in a simulated
world at density D. These subpopulations are
connected by Gaussian random-walk migratory
activity , with standard deviation M
SD
, such that the
mean global migration rate approximates the
subpopulation density D (31). Where possible, we
use parameter values from ethnographic and
comparative behavioral studies that approximate
presumed late Pleistocene demography (31). We
initialize simulations by giving all adults in all
subpopulations a z value of 10.0 and run forward for
100 generations. The mean level of cultural skill
accumulation,
z, is measured by averaging z values
across all individuals in all subpopulations. If the
mean z value in the final generation is greater than
10.0 (i.e., D
z > 0), then the result was deemed
“cumulatively adaptive.” To account for stochastic
variation in simulation outcomes, we performed
100 iterations and averaged the results across these.
W e first explored the effects of varying the num-
ber of subpopulations in our simulated world, G,on
the mean level of cultural skill accumulated,
z.For
values of G > ~50, the
z value did not increase much
further across the entire range of subpopulation den-
sities D and skill complexities a (fig. S1). Figure 1
illustrates that the degree of skill accumulation in-
creased with increasing subpopulation density and
decreasing skill complexity . These results indicate
that the accumulation, or maintenance, of culturally
inherited skill is not dependent on the absolute meta-
population size, but rather on the degree of interaction
of the constituent subpopulations, given population
substructure and that G > ~50. However , when G <
~50, skill accumulation will, to an extent, be depen-
dent on G, and thus the size of the metapopulation.
This result may have some bearing on debate concern-
ing the erosion of cultural complexity in Holoc e ne
Tasmania (30, 32, 33). As a conservative measure, we
fixed G at 100 in all subsequent simulations.
A key feature of the UP is the geographic het-
erogeneity in apparent onset times, despite different
regions being mutually accessible with modest mi-
gration activity. To investigate whether skill accu-
mulation can be spatiall y structured as a result of
different subpopulation densities, we partitioned our
simulated world into two regions differing in density
by an order of magnitude, D
high
and D
low
.Were-
tained M
SD
at 1. 0 , but as a proportion of the mean
nearest neighbor distance,
r
E
, in the lower density
region (31). This ensured that sufficient subpopu-
lations were conne ct ed by migr at ory acti vi ty —
including across the partition—for the migration
rate to approximate the density in each region. W e
set D
high
=0.02andD
low
= 0.002 and simulated a
range of a values (2.0 to 4.0). For all a values, we
found that skill accumulation is consistently high-
er in the D
high
region even though the two regions
were contiguous. As an example, when we fixed a =
3.0, this difference in mean regional z values, aver-
aged over 100 iterations, was maintained over
the entire duration of the simulation (Fig. 2).
Figure 3 and movie S1 provide an illustration
from a single iteration of the spatial stru cturing of
skill accumulation.
We would also expect heterogeneity in migra-
tory range during the late Pleistocene due to, for
example, differing terrains, vegetation, or subsistence
strategies (4). T o investigate whether this could result
in spatial structuring of skill accumulation, we pop-
ulated the simulated world at a constant subpop-
ulation density D = 0.01 and partitioned it into two
regions with differing M
SD
values (31); M
SD,high
=
1.0 and M
SD,low
= 0.1, allowing migratory activity
across the partition. Similarly to the heterogeneous
density world, we find that skill accumulation was
consistently higher in the well-connected M
SD,high
region across all a values simulated (2.0 to 4.0). An
example, with D =0.01anda = 2.9, is given in fig.
S2,withmeanregionalz values averaged over 100
iterations. Fig. S3 and movie S2 provide a spatial
illustration from a single iteration.
From the above results, it is clear that migratory
activity among a set of subpopulations can have the
same effect on skill accumulation as increasing the
size of a single population (30). This is because it
increases the within-group variance in skill levels,
z
i
, which feeds the selective directly biased trans-
mission process and offsets the eroding effect of
low-fidelity transmission. W e therefore sought to
quantify the effect of increasing migration activity
in ter ms of the effective number of adult indi-
viduals available as transmission models within
each subpopulation. To achieve this, we inverted
the previous simulation process; for given values
of a and D, we simulated widely over N to find
the minimum number of adults, N
min
, needed in
each subpopulation for adaptive cumulative evolu-
tion to occur (Fig. 4). W e repeated this process for
thesamerangeofa, but with no migratory process
operating, to obtain the minimum number of adults
required for skill accumulation in an isolated sub-
population, N
0
, for each value of a (Fig. 4) [this is
directly equivalent to Henrich’s analytical result (30)
but uses the extended transmission process pre-
sented in our study]. W e then calculated the ef fective
increase in N due to migratory activity by finding
the difference between the N
min
we expect for given
values of a and D,andtheN
0
we expect for the
same value of a.AscanbeseenfromFig.4,not
only does increasing migratory activity have the
same effect as increasing the size of an isolated
population (30), but also this effect is greater for
higher skill complexities, a.
Our simulation results demonstrate that the
influence of demography on cultural transmission
Fig. 4. The effective increase in adult subpopulation size due to migratory activity. (A) The minimum
number of adults required for adaptive cumulative evolution to occur, N
min
, for a range of values for
subpopulation density D and skill complexity a.(B) The minimum number of adults needed in a single
isolated population N
0
for the same range of a values. (C) The effective increase in adult subpopulation
size N due to migratory activity for this range of D and a, calculated by subtracting surface (A) from curve
(B) extended along the D axis. The axes of (C) have been rotated for display purposes.
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processes provides a mechanism to explain three
key features of the emergence of modern behavior
in the archaeological record: the early appearance,
and subsequent disappearance, of many modern
traits in Southern Africa 90 to 70 ka; geographical
heterogeneity in the timing o f the UP outside Africa;
and the delay between the emergence of AMH as a
species and the material expression of modern be-
havioral traits. If, as proposed here, demographic
factors are fundamental in shaping the evolution of
human behavior , then well-supported estimates of
late Pleistocene regional populatio n densities will be
crucial to understanding the UP/LSA. Recent esti-
mates of population size changes in the late
Pleistocene—based on a Bayesian coalescent infer-
ence method with a global data set of coding-region
mitochondrial DNA (mtDNA) sequences (34)—
permit some comparisons of relative effective pop-
ulation densities in different regions of the world and
at different times.
By setting the UP transition in Europe at 45 ka
(1, 2), we can in f e r the cr i t ic a l effect i ve population
size, and therefore density , necessary for the accu-
mulation of markers of modern behavior . Although
this transition is closely associated with the initial
colonization by AMH, the rapid rise in skill levels
under favorable demographic conditions that we
observe in our simulations indicates that cultural
intensification would be largely insensitive to the
time since first occupation. We assume that the
habitable area of Europe would not have included
most of Scandinavia, resulting in an estimated area
of 8.883 million km
2
. T he median effective pop-
ulation size estimate in Europe at ~ 45 ka is 2905
[with 95% highest posterior density interval of
280.4 to 15,933.9], giving an effective population
density of ~3.2714 × 10
−4
km
−2
. The time at which
this density would have been reached in sub-Saharan
Africa (estimated area ~2 4.270 m illion km
2
)is
~101 ka. Although this is a relatively crude date
estimate, and ignores the importance of t he likely
large heterogeneity in population densities at the
local level, it does correspond well with the first
appearance of modern behavioral traits in th e region
(9, 13). Furthermore, applying this estimation
method to the Middle East and North Africa region
(estimated area ~13.588 million km
2
)givesadate
of ~ 40 ka at which the critical density is reached,
relatively consistent with the first evidence of modern
behavior in the Levant and northeast Africa (2, 7).
In southern Asia, our predicted time for the UP
transition (~52 ka) considerably predates the first
archaeological evidence for modern behavio r at ~30
ka (3). Similarly , the date estimate for northern and
central Asia (~40 ka) predates that of the first full
UP site found at ~22 ka (12). One possible ex-
planation lies in t he choice of the regions used in the
analysis presented by Atkinson et al.(34). An im-
portant assumption of the ancestral population size
estimation method used is that samples are taken
from unstructured (i.e., rand omly mating) popula-
tions. Although multiple loci clustering analysis
(35, 36) broadly supports this assumption for
most of the other regions, it clearly does not for
either the southern Asian or the north and central
Asian geographic regions (34). Performing Bayes-
ian coalescent inference (34)onsuchstructureddata
sets is likely to have resulted in an overestimation of
theeffectivepopulationsizeandthetimeatwhich
population expansion took place. In addition, co-
alescence date estimates for major mtDNA haplo-
groups in southern Asia have been interpreted as
reflecting an initial phase of population growth
somewhat later (37). A second possible explanation
for this anomalous result is that, although population
density may have been sufficiently high for be-
haviorally modern traits to otherwise accumulate,
the migratory range may have been insuffi cient to
allow wide-scale interaction between subpopula-
tions. This may have been the case in southern Asia
during the later Pleistocene (4).
Although the inferred population densities
(34) could account for the early appearance of
behaviorally modern traits in sub-Saharan Africa
and the Middle East—given our demographic
model of cultural skill accumulation—they can-
not explain the subsequent absence of these
features between 70 and ~ 40 ka because no
population size reduction during this period
is inferred [see figure 1 in (34)]. However, the
method of coalescent inference used (Bayesian
skyline analysis) may be unable to accurately
reconstruct more complex demographic histories
when using sequences sampled from a single
locus (38), so repeated bottlenecks and/or ex-
pansions, which would have an important bear-
ing on the accumulation of culturally inherited
skills (17), may not be recaptured. Paleoclimatic
data does indicate worsening conditions during
oxygen isotope stage 4 (~75 to 60 ka) (21)—
possibly leading to population decline, fragmen-
tation, and range contractions—during this peri-
od (20, 21). Lahr and Foley (20) suggest that
continent-wide secondary population bottlenecks
may have occurred ~70 ka, and there is some
evidence that the sites of the South African
Howieson’s Poort industries became effectively
depopulated by ~60 ka (15, 20).
We would expect a degree of positive feed-
back on population density after the accumu-
lation of culturally inherited skills; the development
of more advanced technologies, and possibly social
organization, would likely lead to population
growth. Furthermore, we would expect to see more
artifactual evidence of behavioral modernity in
higher population density contexts through
increased deposition. Although the model we have
presented does not accommodate these processes or
explain the necessary cognitive developments that
make possible the invention or improvement of
complex behavioral traits, it does provide a
demographic mechanism for limiting the degree to
which early human populations would have
accumulated these culturally inherited skills over
time. Our model provides a plausible explanation
for the spatial and temporal structuring of the
markers of modern behavior in the paleoanthropo-
logical record, even if all AMH had the requisite
biologically determined cognitive capacities from
the time of origin some 160 to 200 ka.
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Supporting Online Material
www.sciencemag.org/cgi/content/full/324/5932/1298/DC1
Materials and Methods
Figs. S1 to S3
Movies S1 and S2
References
23 December 2008; accepted 21 April 2009
10.1126/science.1170165
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