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Society for American Archaeology
Heartlands and Hinterlands: Alternative Trajectories of Early Urbanization in Mesopotamiaand the Southern LevantAuthor(s): Steven E. Falconer and Stephen H. SavageReviewed work(s):Source: American Antiquity, Vol. 60, No. 1 (Jan., 1995), pp. 37-58Published by: Society for American ArchaeologyStable URL: http://www.jstor.org/stable/282075 .
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HEARTLANDS AND HINTERLANDS:
ALTERNATIVE TRAJECTORIES OF EARLY URBANIZATION IN
MESOPOTAMIA AND THE SOUTHERN LEVANT
Steven E. Falconer and Stephen H. Savage
Comparative ank-sizeanalysesrevealhighlyvariablecoursesof urbanizationn ancientMesopotamiaand the
southernLevantduring he ourth throughearlysecond millenniaB.C. Whiletraditional ank-sizemethodsdo not
consider he effectsof archaeological ampling,weproposea revisedapproachbasedon Monte Carlosimulation,which ncorporatesite-recoveryates and demonstrates he advantagesof 'full-coverage"urvey.Wehighlight he
rapiddevelopment f urbanprimacy n southernMesopotamia'sheartland Adams1981) and the more staticrural
integrationof the Diyala hinterland Adams 1965). In contrast,BronzeAge urbanizationn the southernLevantdescribesa mosaic of urbanand ruralsystems ollowing independent rajectories.We callfor greaterattentiontosmall sites, whichoften define heshapeof rank-sizedistributions.Ourapproachlluminatesmodestcasesof urban-izationin termsof structure, ather hansimply of reduced cale,and avoidsa tendency o categorize uch cases asderivative.
Los andlisiscomparativos el rangode tamaniode asentamientos evelanunagranvariabilidadn el rumbohacia
la urbanizacion n la Mesopotamiaantiguay en el sur de Levantea travesdel cuarto milenio hastaprincipiosdel
segundo milenio A.C. Los metodos de rango-tamanoempleadostradicionalmenteno consideran os efectosdelmuestreoarqueologico.Por ello proponemosuna perspectiva istinta de aquellos,basadaen la simulacionMonteCarlo la cual incorpora stimacionesde los sitios recuperados demuestra as ventajasde los reconocimientos e
superficie e "coberturaotal."Distinguimosaprimaciadelrdpidodesarrollo rbano n el nucleode la Mesopotamiasurena(Adams1981) de la integracion uralmds estdticaen la periferiadelDiyala (Adams1965).En contraste,aurbanizacion n la Edad de Bronce en el sur de Levantepresentaun mosaicode sistemas ruralesy urbanosque
siguen trayectoriasndependientes. onemosmayoratencionen los sitiospequenos, os cuales con recuenciadefinenla forma de las distribuciones e rango-tamano.Nuestroperspectiva lustra casos modestos de urbanizacion nterminosde estructura n lugarde una simpleescalareducida, evita la tendenciade categorizar stos casos comoderivativos.
T he title of Robert Adams's book Heart-
land of Cities succinctly captures a theme
that unifies many of the most influential anal-
yses of early civilizations: the evo-
lution of urbanism. Urbanized societies fea-
tured city centers that were differentiatedfrom, but integrated with, their rural periph-eries (e.g., Redman 1978:215-216). The
closely related process of "urbanization" gaverise to urban economic and political primacy,
based on the "increasingly substantial pro-
portion of the population of a settlement sys-tem [that] came either to live in a central
place or to be involved in a variety of waysin the activities of a central place" (Clarke
1979:436). A substantial literature focuses onthe diverse forms and functions of pre-in-dustrial cities (e.g., Sanders and Webster 1988;
Wheatley 1971; Adams 1966). However, we
argue that urban studies are most compelling
Steven E. Falconer * Department of Anthropology, Arizona State University, Tempe, AZ 85287-2402
Stephen H. Savage * Department of Anthropology, University of Wisconsin, Milwaukee, WI 53201
American Antiquity, 60(1), 1995, pp. 37-58.
Copyright ? 1995 by the Society for American Archaeology
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when they comprehend entire networks of
sedentary settlement and, in so doing, distin-
guish different trajectories whereby cities,
towns, villages, and hamlets became incor-
porated or disarticulated as regional systemscoalesced or broke down (e.g., Adams 1981).
Nonsedentary populations tend to leave more
ephemeral archaeological signatures that of-
ten elude effective recovery and dating byextensive regional surveys. Regrettably, this
aspect of society can only be addressed tan-
gentially (e.g., regarding Early Bronze IV pas-toralism in the Levant) with the data we as-
semble here.
This study offers a comparative perspec-tive on the initial urbanization of lowland
Mesopotamia and the southern Levant, two
regions characterized by the early appearanceof cities and broad regional survey coverage.
Using revised methods of rank-size analysisbased on Monte Carlo simulation, we high-
light a variety of urbanized settlement sys-tems in the "heartlands" and "hinterlands"
of both regions. Our approach not only high-
lights fundamental distinctions between the
courses of Mesopotamian and Levantine ur-banization, but also strikingchronological and
geographical variation within each region.Our results reveal further that the orderingof rural sites often serves to distinguish the
rank-size distribution of one settlement sys-tem from another. Thus, when attempting to
capture urbanized systems as whole entities,small places, as well as central ones, may serve
as key defining elements.
The diversity between and within Meso-
potamian and Levantine settlement systemscalls for a renewed body of interpretive par-
adigms with which the full panorama of pre-industrial urbanism may be explored. As a
case in point, the spectacular growth of met-
ropolitan Uruk in the fourth and third mil-
lennia B.C. may provide the classic textbook
example of urban nucleation, but it does not
necessarily prefigure all courses of urbaniza-
tion in Mesopotamia, let alone other regionsof the Near East. Our approach is particularly
valuable for interpreting less ostentatious ex-pressions of urbanism in terms of structure
and development, rather than simply re-
duced scale.
We begin with a discussion of rank-size
analysis, followed by a proposal for how it
might be adapted to the special nature of ar-
chaeological sampling and survey data. Our
rank-size analyses corroborate Adams's
(1981) portrait of southern Mesopotamia as
a centrally important urban "heartland" in
which the earliest cities, striking for their im-
pressive size, are accompanied by the deci-
mation of surrounding villages as they grow.In contrast, the Diyala Plain constituted a
Mesopotamian "hinterland,"distinct and well
removed from the Uruk heartland, that was
characterized by a dwindling array of small
towns and cities situated amid proliferatingrural settlement. Interestingly, Bronze Agesettlement in the southern Levant emerges as
neither an urban heartland nor a rural hin-
terland. Rather, a patchwork of urban and
rural systems followed variable trajectoriesat different times and in different subregions.Urbanism was primarily a coastal phenom-enon apparently superimposed on a resilient
network of rural settlement. Systems of smalltowns and villages in the Levantine hill coun-
try and Jordan Valley followed their own
courses of development that generally cannot
be attributed to the influences of waxing and
waning coastal urbanism.
These alternative expressions of urbaniza-
tion heighten our appreciation of early urban
diversity and signal a need for renewed at-
tention to the significance of small commu-
nities in stratified settlement systems. Ana-
lytical methods, such as those applied here,that are tailored for archaeology and accom-
modate a full spectrum of settlement typeswill inevitably enhance our insight on urban-
ism, and other issues of social complexity, in
southwestern Asia and elsewhere.
Rank-Size Analysis
Auerbach (1913) originally observed that the
cities of modern industrial nations, when
ranked according to their populations, aredistributed such that the largest city has twice
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Falconer and Savage] EARLYURBANIZATIONNMESOPOTAMIANDTHESOUTHERN EVANT
1000
,N.,.
oo
1000
100
10
1
\x
10
b
10
Rank
10100
Rank
Figure 1. Examples of primate and convex rank-size distributions (a), and a primo-convex distribution created by
combining the two distributions in a (b).
the population of the second-ranked city,three times the population of the third-ranked,and so on. Following this "rank-size rule,"the size of any nth-ranked place is predicted
by dividing the size of the largest place by n,and the rank and population of cities describe
a log-normal distribution when plotted log-
arithmically (Haggett 1971:101; see Figure1A).
Applying the Principle of Least Effort, Zipf
(1949) invoked "Economic Man" to explainthe interaction of two opposite courses of
economic action that create the rank-size rule.
The "Force of Diversification" encourages a
large number of "small, widely scattered and
largelyautarchical communities" located nearraw material sources, while the "Force of
Unification" moves raw materials to a very
limited number of massive centers of pro-duction and consumption (1949:352).
Conventional applications in archaeologyassume that the forces of diversification and
unification are equal, which provides an ex-
pedient resolution to the dilemma of assign-
ing values to Zipfs two forces. However, the
assumption also renders the formula used by
archaeologists a special case of the general
equation that is open to critical discussion(Kowalewski 1982; Richardson 1973; Dzie-
wonski 1972; Moore 1959).
Interpreting Rank-Size Curves
Log-normal distributions in accordance with
the rank-size rule "appear to be typical of
larger countries with a long tradition of ur-
banization, which are politically and eco-
nomically complex" (Berry 1961:582). Ar-
chaeologists infer that such distributionssignify regional systems in which cities are
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AMERICANANTIQUITY
well integrated with their subordinate com-
munities (e.g., Adams 1981:72-74; Johnson
1980). Observation of "log-normality" in
western industrialized nations (e.g., Vining
1955:Figure 1) inspired Auerbach's original
formulation, but pre-industrial settlement
patterns tend not to conform to the values
expected under the special case of the rank-
size rule applied in archaeology. Therefore,most archaeological inferences are derived
from the manner and degree to which rank-
size distributions depart from log-normal.These departures may be classified into "pri-
mate," "convex," and "primo-convex" forms
(Johnson 1977; Paynter 1983), which poten-
tially indicate various expressions of strongor weak integration between large and small
communities.
Primate Distributions
Primate distributions are generated by set-
tlement systems that contain fewer inter-
mediate and large places than predicted by
the rank-size rule, or in which the first-ranked
place is considerably larger than expected
(Figure 1A). Typical primate patterns, whichare somewhat concave (see Johnson 1977),
may indicate an extraordinary centralization
of political or economic functions, as ex-
emplified by several long-lived Mesoameri-
can systems in which "the primate center
provided unique services having to do with
maintenance of a regional boundary for a set
of local subsystems. The primate center's
special activities often involved a combina-
tion of high order sacred ceremonialism,
macroregional elite exchange, foreign diplo-
macy, and war" (Kowalewski 1982:65).
Primate distributions may also result from
the constraints of settlement system bound-
aries. Johnson, following Smith (1976) and
Blanton (1976), notes that the primate con-
dition is associated frequently with centers or
peripheries of former colonial empires, "in
systems which are sufficiently bounded so as
to inhibit the development of more than one
highest order central place" (1977:496-497).
Johnson also cautions that "problems in sys-
tem boundary definition. . . may produce es-
sentially artificial primate distributions in
both archaeological and modern data sets"
(1977:498). This may be particularly true
when the entire extent of a settlement systemhas not been identified. Therefore, archaeo-
logical interpretations should consider the
possibility that there may be "a role for the
primate city that extends beyond its regionalhinterland" (Skinner 1977:238).
Convex Distributions
A convex distribution contains more inter-
mediate and large places than predicted by
the rank-size rule (Figure 1A). "In these caseslarge settlements are smaller or small settle-
ments are larger than expected" (Johnson
1977:497). In contrast to many primate sys-
tems, a convex distribution indicates rela-
tively little integration of political and eco-
nomic services among communities in a
settlement system, particularly less "verti-
cal" integration between large cities and
smaller rural communities (Johnson 1980;
Paynter 1982). For example, data from the
Levantine Central Hills reveal pronouncedrank-size convexity that implies minimal ar-
ticulation between dispersed Bronze Age vil-
lages (see discussion below).
Johnson (1980) suggests further that as theybecome increasingly integrated, settlement
systems will shift from convex to log-normalto primate distributions. Adams notes this
sequence in the combined Warka and Nip-
pur-Adab survey data, and our analyses sug-
gest another example in the upper end of the
rank-size curves for the Levantine CoastalPlain (see discussion below). Alternatively, a
convex pattern may result from pooling two
or more adjacent settlement systems, or from
the exclusion of a primate center from its
subordinate settlement system (Johnson
1980; Paynter 1983).In yet another twist to rank-size interpre-
tation, some convex distributions may reflect
central place economic organization (John-son 1977; Crumley 1976). Central Place The-
ory (e.g., Christaller 1933) predicts that plac-
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Falconerand Savage] EARLYURBANIZATIONN MESOPOTAMIANDTHESOUTHERN EVANT
es of equivalent economic function will be
equivalent in size, resulting in a stepwise
ranking, rather than the more continuous dis-
tribution predicted by the rank-size rule. Such
a stair-step distribution is inherently convex,
especially when a system has multiple high-est-order central places.
Primo-convex Distributions
Primo-convex distributions incorporate ele-
ments of rank-size primacy in their upper-size range and convexity in their lower range.For example, the primo-convex curve in Fig-ure 1B was created by combining the primate
and convex curves in Figure 1A. Primo-con-vex distributions may represent a special ex-
pression of pooling: the superimposition of a
centralized or colonially derived system (ex-
pressed in a primate upper curve) on a lower-
level system that may be loosely integratedor have an element of central place organi-zation (reflected in a convex lower curve).This possibility is particularlyintriguing, since
it suggests the simultaneous operation of two
distinct settlement systems in a single region.
Toward an Accommodation of Rank-Size
Analysis and Archaeological Data
Although rank-size methods are used com-
monly in settlement pattern analysis, archae-
ological interpretations often rely simply on
judgmental appraisals of the shapes of rank-
size distributions. This approach sidesteps the
issue of how far a distribution must departfrom log-normal to merit interpretation as
primate or convex. Attempts at greater sta-
tistical rigor use the Kolmogorov-Smimov
one-tailed-goodness-of-fit test (hereaftercalled the "K- test") to determine whether an
observed rank-size plot is significantly dif-
ferent from an expected one (Sokal and Rohlf
1969; Paynter 1982, 1983). The K- test is a
distribution-free test of the null hypothesisthat a sample is drawn from a particular pop-ulation. "The Kolmogorov-Smirnov test re-
jects the null hypothesis if there are differ-
ences in the central tendency, range, or shape
of the sample and population distributions,
thus making it a very general test of noni-
dentity" (Paynter 1982:156). As it is used in
rank-size analysis, the K- test measures the
maximum deviation between cumulative
distributions of observed and expected site
sizes (Shennan 1990:55-61; Thomas 1986:
322-337). The maximum deviation (the K-
statistic) is compared to a predetermined val-
ue for a given alpha level in a statistical table
(e.g., Thomas 1986:504-506). If the devia-
tion exceeds this value, the observed distri-
bution is considered to be significantly dif-
ferent from the expected one.
Problems with Rank-Size Analysis of
Archaeological Data
There are several fundamental considera-
tions that affect the applicability of rank-size
analysis to archaeological data. First, the K-
test may not be appropriate for archaeolog-ical analyses for at least four reasons:
1. The K- test assumes that the individual
observed and expected values are indepen-dent of each other. However, none of the
expected values are selected independently,since they follow directly from the size of the
largestobserved site as prescribed by the rank-
size rule.
2. Although the test is designed for contin-
uous frequency distributions, the expectedvalues assume a step-wise distribution, againin accordance with the rank-size rule.
3. The observed frequency distributions are
assumed to be drawn from largerpopulationswith replacement. However, they are clearlynot drawn with replacement, since we count
each site only once.
4. Both frequency distributions are as-
sumed to have no upper bound. This is true
of the observed data set, but the expecteddistribution is bounded at its upper end bythe size of the largest observed site.
These characteristics of archaeologicalrank-size data call traditional archaeological
applications of the K- test into serious ques-tion. While the procedure for calculating the
maximum deviation between observed and
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expected distributions remains acceptable, we
argue that appropriate measures of statistical
confidence for archaeological data must be
derived empirically.The calculation of appropriate confidence
levels follows directly from a second majorconsideration underlying archaeological rank-
size analyses: archaeological site distribu-
tions are samples drawn from larger popu-lations according to uncertain sample pro-
portions that can only be estimated. Previous
tests of significance do not account for this.
Since the shape of any observed distribution
is affected by its sample proportion (based on
survey coverageand
intensity), quantitativeanalysis must incorporate estimated site re-
covery rates to produce meaningful results.
Thus, the issue of sampling cannot be sepa-rated from the issue of statistical confidence.
Additional issues stem from difficulties in-
herent in sensing archaeological sites and es-
timating their sizes. Archaeological site sizes
may be over- or under-estimated, particular-
ly at deeply stratified sites or those subject to
alluviation. The area of a stratified site often
reflects the extent of its largest occupation,which may inflate our estimates of smaller
habitations in other periods. In contrast, al-
luvial or colluvial blanketing of site fringesin some regions (e.g., lower Mesopotamia and
the Jordan Valley) may cause underestima-
tion of occupations at or below modern sur-
face levels.
Further, the effects of such systematic er-
rors on the analysis of any observed rank-
size distribution will be particularly acute to-
ward its lower end, since this is precisely wherethe majority of sites in an expected log-nor-mal distribution are located and where the
likelihood is greatest that sites in the target
population have been missed or obliterated.
Applying the K- Test Through Monte Carlo
Simulation
Given the limitations of the traditional K-
test, our analyses utilize the RankSize com-puter program (Savage 1993)1, which applies
Monte Carlo simulation methods and ac-
commodates the special characteristics of ar-
chaeological data and sampling. This pro-gram analyzes a set of observed site sizes based
on an estimate of the sample proportion it
represents. The simulation first sorts the ob-
served data and calculates a K- statistic (that
is, the maximum deviation between the ex-
pected and observed values), keeping it for
later reference. The program then creates a
simulated population based on the rank-size
rule starting from the largest site size in the
observed data. The number of sites in this
simulated population is determined by mul-
tiplying the number of observed sites by the
reciprocal of the sample fraction. Thus, if a
survey yields a sample of 100 sites that are
assumed to represent 90 percent of the pop-ulation, that population contains 100 / .90 =
111 sites. The largest site in the population
equals the largest site in the sample. The re-
maining 110 sites are generated according to
the rank-size rule. Clearly, this method is onlyas accurate as the estimate of the sample pro-
portion, but it forces the analyst to confront
the sampling issue explicitly.The simulated population becomes the ba-
sis for a long series of random computer runs.
Each run draws a sample of sites from the
simulated population equal to the number of
observed sites. (The user may always include
the largest observed site size or allow it to
vary; all of our analyses include it.) The sim-
ulation then calculates a K- statistic that mea-
sures the maximum deviation between this
sample and its own expected, log-normal dis-
tribution. The program repeats this proce-dure over a large number of runs, stores the
K- statistics produced by each run, and sorts
them in ascending order. Finally, the simu-
lation compares the value of the original K-
statistic for the observed data to the range of
K- values from the random runs to estimate
the probability that a K- value greater than
or equal to the observed value will be ob-
tained by random samples drawn from a log-normal population. For example, if only 3
percent of the simulated K-values are as largeor larger than the observed K- value, we may
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infer that it is unlikely that the observed sam-
ple is drawn from a log-normal population.
Whereas a traditional test categorizes an
observed K- statistic as significant or nonsig-nificant at a predetermined alpha level (typ-
ically .05), we prefer to estimate the proba-
bility that an observed distribution could have
been drawn from a log-normal population.The lower the probability, the greater our
confidence that the original settlement sys-tem may be interpreted as differing from log-normal (primate, convex, or a combination
of the two). The analyst may deem some
probability estimates as highly diagnostic and
others as more equivocal. Rather than a sim-ple pass-fail result, this approach provides a
variety of possible outcomes and interpretive
avenues (see Cowgill 1977).The potential for misestimating observed
site areas may be accommodated by random-
ly inflating or diminishing the sizes of sites
picked by the RankSize program for simu-
lated distributions. This might be done with-
in a preset percentage range, for a predeter-mined proportion of sites, for example. To
compensate for the likelihood of missing moresites at the lower end of an observed distri-
bution, it may be advantageous to incorpo-rate a "sliding probability" of site recovery
rangingfrom near certainty for extremely largecities to very modest levels for diminutive
villages and hamlets. The addition of these
two routines to the RankSize procedure would
raise a variety of questions regarding how
these potential sources of sample bias should
be measured and simulated. While we do not
attempt to address these concerns in detailhere, experimental results indicate that the
introduction of these two sources of vari-
ability into the RankSize program tends to
result in modestly higher probability figures.
Therefore, the probabilities discussed below
may tend to slightly exaggerate the departureof observed rank-size distributions from log-normal.
We apply RankSize simulations to site size
data, revealing a variety of trajectories where-
by early urbanized settlement systems arosein Mesopotamia and the southern Levant.
Each analysis poses two questions: 1) How
low is the probability that the observed dis-
tribution could be drawn from a log-normal
population? 2)In
lightof this
probabilityand
the observed rank-size plot, what is the shape
of the observed distribution (and the likely
shape of the original population)? In each case,
we assume that the largest site reported was
the largest settlement in the original system
under study. We introduce the settlement data
from each region with an assessment of sur-
vey methods and site recovery rates from
which we estimate an average sample pro-
portion. The number of settlements in each
original population is calculated by multi-plying the number of observed sites by the
reciprocal of the sample proportion. When a
probability value is very low, we argue that
our sample represents a noteworthy depar-
ture from the log-normal distribution pre-
dicted by the rank-size rule, and we address
the archaeological implications of that de-
parture.
Interestingly, the settlement patterns ana-
lyzed in this study generate very few equiv-
ocal probability figures. The majority of ob-served distributions in both Mesopotamia and
the southern Levant have probabilities of
<.01 of simply representing samples of a
larger log-normal population. The remaining
cases, with two Mesopotamian exceptions,
provide substantially larger values (ranging
between .24 and .93) more clearly indicative
of effective adherence to the rank-size rule.
Our approach begins to accommodate the
uncertainty inherent in archaeological field
and analytical procedures and illustrates thebenefits of larger sample proportions. Sim-
ulated K- statistics rarely exceed observed
values when the observed data represent a
high sample proportion, rather than a low
one. For example, when analyzed at sample
proportions ranging between .05 and .95,
Early Bronze III settlement data from the
Levantine Coastal Plain show that site re-
covery rates must be greater than 75 percentto generate an extremely low probability that
an observed sample was drawn from a log-normal population (Figure 2). This obser-
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AMERICANANTIQUITY
0
. C
CisIe
0
X IM/m,
,.6
).2 ~
n-~~~~I/:
5 10 15 20 25 30 35 40 50 55 60 65 70 75Sample Percent
vation reinforces the call for full coverage
survey (e.g., Fish and Kowalewski 1990) and
careful consideration of the factors that de-
termine site survivorship and recovery.
Mesopotamian Survey Chronology and
MethodsOur analyses of urbanization in Mesopota-
mia draw data from the Warka,Nippur-Adab,
and Diyala surveys conducted by Adams
(1981; 1965; Adams and Nissen 1972) (Fig-
ure 3). All three survey areas lie beyond the
frontiers of modern cultivation and present
only the "low, featureless relief' of sparse
vegetation, "long disused canal levees, and
the rubble strewn mounds of former settle-
ments" (Adams 1981:xvii). The Warka and
Nippur-Adab surveys encompass the heart-
land of early Mesopotamian city and state
development: the central floodplain of the
Euphrates River. The Diyala Survey assesses
early canal systems and agrarian settlement
in the lower Diyala River drainage, a region
that constituted a rather detached hinterland
of the urban developments farther to the
south. We concentrate on the explosion of
Mesopotamian urbanism centered on Uruk
during the Early-Middle Uruk, Late Uruk,
and Early Dynastic I periods (following Ad-
in80 5 90 95 Figure 2. Probability estimates
at increasing sample proportionsfor Early Bronze III data from
the Levantine Coastal Plain.
ams 1981; see Table 1). We omit data from
the enigmatic phenomenon known as "Jem-
det Nasr," which may have been a regionalceramic style or an archaeologically elusive
time period (Adams 1981:81; Finkbeiner and
Rollig 1986).2
Large-scale archaeological reconnaissance
in Mesopotamia has relied on visits to sitesidentified from maps or aerial photographs,as well as vehicular reconnaissance along par-allel transects (usually 0.5-1.0 km apart) or
across river levees (e.g., Adams 1965:120;
1981:38-39; Wright 1981:298). Perhaps the
major natural impediment to site recovery in
Mesopotamia is alluviation, which may re-
duce the apparent size of a site, or obscure it
altogether, particularly in cases of small sites
from earlier periods (e.g., Stronach 1961; Ad-
ams 1975). As a formal test of the efficiencyof jeep reconnaissance, Adams (1981:40-42)
restudied 13 sq km north and east of ancient
Nippur in which nine sites were identified
originally. More intensive coverage revealed
three additional sites and required modifi-
cation of the descriptions or dating of four
others. These results suggest that settlement
inventories for the Nippur-Adab Survey and
others like it may be deficient by one-quarterto "as much as one-third" (Adams 1981:42).
This deficiency tends to underestimate site
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Figure 3. Mesopotamian surveyareas. Approximate coverages:
Diyala Survey = 8,000 km2;Nip-
pur-Adab Survey = 3,450 km2;Warka Survey = 2,800 km2.
Adapted from Adams (1965:119,
1981:42), Adams and Nissen
(1972:4).
counts at the lower end of rank-size curves.
On the basis of Adams's systematic restudy,a rarity in Near Eastern survey archaeology,we estimate an average recovery rate of 70
percent, which we apply as the sample pro-
portion for our analyses of Mesopotamiansettlement.3
Hyperurbanization in the MesopotamianHeartland
The Uruk and EarlyDynastic I periods reveala pattern of population growth in a dwindlingnumber of communities in the combined
regions of the Warka and Nippur-Adab sur-
veys. Ancient Uruk achieved primate status
through a process of urban "agglomeration"in which it absorbed much of the rural pop-ulation immediately
surroundingit,
therebyswelling to 400 ha and "no less than 40,000
to 50,000" inhabitants by Early Dynastic I
(Adams 1981:85; Adams and Nissen 1972:
19-21). The rank-size plots in Figure 4 follow
Johnson's (1980) prescription for the devel-
opment of such a primate system.4 To beginthe sequence, our simulation of Early-Mid-dle Uruk settlement generates a probabilityof
only.03 that the observed distribution
rep-resents a random departure from log-normal(Table 2). The Early-Middle Uruk rank-size
plot shows this distribution to be convex.The Late Uruk rank-size distribution,
though also convex, has a much higher prob-
ability (p = .71) of representing a random
departure from log-normal. Therefore, this
settlement pattern is more justifiably inter-
preted as adhering to the rank-size rule, rath-er than deviating substantially from it. In this
case, verydifferent
probability estimates re-sult from rather similar data sets primarily
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AMERICANANTIQUITY
Table 1. Mesopotamian Chronology.
Period Beginning Date Ending Date
Early DynasticI ca. 2900 B.C. ca. 2600 B.C.
Jemdet Nasr ca. 3100 B.C. ca. 2900 B.C.
Late Uruk ca. 3500 B.C. ca. 3100 B.C.
Early-Middle Uruk ca. 4000 B.C. ca. 3500 B.C.
Note: Based on historical correlations and recalibrated radiocarbon dates (see Porada et al. 1992: Figures 3, 4;Adams 1981:81-82).
due to an increase in the size of the largestsite (Warka) in the Late Uruk Period.
Data from the subsequent Early DynasticI Period generate a very low probability (p <
.01)that the
primaterank-size curve in
Fig-ure 4 is a product of chance. Indeed, we es-
timate that by Early Dynastic I more than 60
percent of the sedentary populations around
Warka and Nippur lived in a total of only
five communities, each larger than 40 ha
(Falconer 1987:Figure 5; Adams 1981:Table
7).
Although our rank-size plots do not pro-
vide highly convex patterns suggestive of
pooling, separate analyses of northern and
southern settlement "enclaves" (followingAdams 1981:70-90) reveal two distinct, but
related routes by which urbanization devel-
oped more locally. In the Early-Middle Uruk
Period, the Nippur-Adab enclave to the north
was more heavily populated, particularlywith
village farmers (Adams 1981:70; Falconer
1987:Figure 7). The growth of Uruk in the
subsequent Late Uruk Period (from 70 to 100
ha) was accompanied by an apparent shift in
rural settlement from the north to the south.
Adams suggests that "if we take into account
the artificial limitations of the survey area
... literally tens of thousands of small vil-
lagers appear to have abandoned their homes
and moved southward" (1981:70). This tran-
sition is manifested in rank-size curves that
developin
very differentmanners.
The Nippur-Adab data produce probabil-
Table 2. Summary of Simulation Runs for Mesopotamian Survey Regions.
Numberof Sites Ob-
Largest Number Sample in Pop- served Proba- Curve
Region Period Sitea of Sites Percent lationb K-Value bilityc Shape
Warka/Nippur-Adab Early Dynastic I 400.0 98 70 140 .643 <.01 Primate
Late Uruk 100.0 156 70 223 .288 .71 L-norm
Early-Middle
Uruk 70.0 203 70 290 .335 .03 Convex
Nippur-Adab Early Dynastic I 50.0 34 70 49 .441 <.01 Convex
Late Uruk 50.0 49 70 70 .408 <.01 Convex
Early-MiddleUruk 50.0 144 70 206 .389 <.01 Convex
Warka Early Dynastic I 400.0 64 70 91 .688 <.01 Primate
Late Uruk 100.0 107 70 153 .336 .04 Primate
Early-MiddleUruk 70.0 59 70 84 .492 <.01 Primate
Diyala Early Dynastic I 36.0 37 70 53 .243 .93 L-norm
Early-Late Uruk 36.0 21 70 30 .286 .68 L-norm
a Size in hectares.b
Number of sites in population=
number of observed sitesx
(1/sample percent).c Probability of drawing a K- value greater than or equal to the observed value at random from a log-normal
population, based on 1,000 random runs for each row.
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_
v:5-D
t^
Rank Rank
Figure 4. Rank-size distributions for Early-Middle
Uruk and Early Dynastic I settlement within the com-
bined areas of the Warka and Nippur-Adab surveys. Datafrom Adams (1981:Table 7).
ity estimates consistently less than .01, with
rising K- statistics, and rank-size distribu-
tions that denote increasing convexity (seeAdams 1981:Figure 17). This convexity be-
comes accentuated as the system loses small-
er settlements. The Warka Survey data like-
wise produce very low probability values and
rank-size plots that start as distinctly pri-mate, then approach log-normal in the Late
Uruk Period due to the addition of medium-
and small-sized settlements (Adams 1981:
Figure 17). In Early Dynastic I, while the
Nippur-Adab enclave continued to lose vil-
lages, the city of Uruk quadrupled in size,
providing a rank-size distribution that once
again is resoundingly primate (Figure 5).In general, these trends portray a society
that became highly urbanized by relocating
and reducing its rural population. In this casethe process had two related facets. A growingsouthern populace "agglomerated" in the
quintessentially primate center of Uruk, while
settlement to the north became increasinglyurbanized only in a residual sense, as the hi-
erarchy of towns and villages below Nippurand Adab withered. Interestingly, both pat-terns strongly imply decreased agrarian pro-
ductivity and contradict the expectation that
urban authorities willencourage
rural farm-
ing communities to ensure a strong agricul-tural base and their own self-preservation
Figure 5. Separate Early Dynastic I rank-size distri-
butions for the Warka and Nippur-Adab survey areas.
Data from Adams (1981:Table 7).
(Adams 1981:88). Only late in the third mil-
lennium B.C. (i.e., the Early Dynastic II
through Isin-Larsa periods), do cities en-
courage an abundance of surrounding vil-
lages in a process of "ruralization" (Yoffee
1986; Robinson 1972) more in keeping with
this expectation (Adams 1981:130-170; Fal-
coner 1987:122-123). As we shall see, thisprocess of simultaneous urban aggregationand rural depopulation describes only one,counterintuitive and potentially maladap-
tive, expression of urbanization that does not
typify the development of early urbanism in
other time periods or regions of southwestern
Asia.
Small-scale Urbanism in the DiyalaHinterland
The long-term trajectory for settlement on
the Diyala Plain, which stands as a counter-
point to that of the Warka and Nippur-Adabregions, starts with the appearance of rela-
tively modest cities in the Uruk Period and
charts their decline and disappearance by ca.
1000 B.C. (Falconer 1987:128-133; Adams
1965:36-42). The Diyala's sparse regional
population became overwhelmingly and in-
creasingly rural over these millennia. By Ear-
ly Dynastic I,10 towns and cities measured
10 ha or larger (including Tell Asmar and
Khafajah; see Figure 3). More impressively,
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AMERICANANTIQUITY
---Uruk observed------ EDI observed-
Expectedboth)
100
Rank
Figure 6. Rank-size distributions for settlement within
the Diyala Survey area. Data from Adams (1981:Figures
8, 10; 1965:Table 10, Figure 2, Appendix C, map sections
1B-4B).
the frequency of villages (less than or equal
to 4 ha) jumped from 71 to 90 percent (Fal-coner 1987:Figure 12). These data would sug-
gest a pattern of "ruralization" like that
around Uruk following the Early DynasticPeriod. However, despite apparently convex
rank-size plots (Figure 6), very high proba-
bility estimates reveal that the observed Urukand Early Dynastic I settlement distributions
represent merely chance departures from log-
normal (Table 2). This approximation of log-
normal contrasts fundamentally with the de-
veloping primacy of Uruk's settlement sys-
tem. Adams observes that the emergence of
fortified towns in the Diyala found "little ap-
parent reflection in the disposition of the re-
maining, smaller settlements over the coun-
tryside" (1965:38). Like their much larger
counterparts to the south, the Diyala's towns
and cities emerged amid an array of poten-
tially subordinate villages, but apparentlyfailed to exert a comparable molding influ-
ence on surrounding settlement patterns.While metropolitan behemoths came to
dominate the Mesopotamian heartland, set-
tlement in the Diyala hinterland emerged as
an alternative expression of urbanism based
on a log-normal integration of small cities,
towns, and proliferating villages.
Lower Mesopotamia and the Diyala do notexhaust the range of early urban expressions
in the Near East. However, they do bear wit-
ness to two classic patterns by which urban-
ism might first appear: through the nucle-
ation of a predominating primate city or the
coalescence of a stratified, but less central-
ized, settlement system on a much smaller
scale. By virtue of their early appearance and
massive scale (at least for Uruk) these pat-terns serve as touchstones for the interpre-tation of cities and regional settlement else-
where in the Near East. The southern Levant
provides a striking case in point in which
conventional models of urbanism hinge ex-
plicitly or implicitly on reference to earlier,
larger-scale events elsewhere in southwestern
Asia, notably Mesopotamia or Syria.
Conventional Approaches to Levantine
Urbanism
A substantial and growing literature explores
the rise of Levantine cities and towns usinga variety of data and interpretive angles, but
sharing a set of common themes. With the
exception of a handful of recent works (e.g.,Joffe 1991a; Finkelstein and Gophna 1993;
Gophna and Portugali 1988), urbanism istreated as a regionwide phenomenon, with
little discussion of its variable manifestations
in the southern Levant's constituent settle-
ment zones (Esse 1989; Dever 1987; Richard
1987). Secondly, urbanism is construed as
structurally equivalent to that found else-
where; it simply occurred later, and on a re-
duced scale. For example, Kempinski (1978)attributes the appearance of EarlyBronze Agecities to a process of nucleation analogous to
that around Uruk. Third, many authors pro-
pose that antecedent forms of Bronze Agematerial culture, and the technology that pro-duced it, are found elsewhere, notably in Egypt
and Syria (Ilan and Sebbane 1989; Kempin-ski 1989). Therefore, this material evidence
and an associated tradition of urbanism must
have spread into the southern Levant, pre-
sumably from earlier, exotic sources (Dever
1987; Gerstenblith 1983). Jointly, these sup-
positions hold that the first urbanized soci-
eties in the southern Levant were secondary,derivative expressions of early urbanism. The
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southern Levant is described as a "backwa-
ter" in comparison to neighboring regions,which nonetheless featured "truly urban" so-
ciety during the Bronze Age (Dever 1976;
Kenyon 1973).Our study reverses the conventional inter-
pretive process applied to the southern Le-
vant. Instead of emphasizing foreign rela-
tions and the effects of cities on the entire
southern Levant, we break the region into
constituent units, from which analytical re-
sults are assembled to reinterpret the mosaic
of Bronze Age urbanism.
LevantineSurvey Chronology
and Methods
Settlement data from the southern Levant
derive from a variety of surveys in Israel north
of the Negev Desert, the West Bank of the
Jordan River, and the Jordan Valley (e.g., see
Joffe 199 lb:Table 1, Figures 2-4). In contrast
to Mesopotamia, this region features signif-icant variation in topographic relief, modem
vegetation, and human habitation. The
southern Levant can be divided longitudi-
nally into a series of geomorphic zones (Fig-
ure 7; see Horowitz 1979:11-19). A coastalplain up to 50 km wide extends in from the
Mediterranean shoreline. The landscape then
rises to form a north-south chain of hills
reaching 300 m asl. Major valleys separatethe northern hills of the Galilee from the cen-
tral hills that extend through the West Bank.
The eastern slope of this hilly backbone
plummets rapidly to the Jordan Valley, where
the valley floor lies between 100 and 350 m
below sea level. Relatively sparse Mediter-
ranean maquis and oak and pistachio rem-
nant forests populate the Levantine hill coun-
try, while only vestiges of natural vegetationexist amid the modem settlement and agri-culture of the Levantine Coastal Plain and
Jordan Valley (Gophna et al. 1986; al-Eisawi
1985).The success of early Levantine urbanism
oscillated dramatically through the Early and
Middle Bronze ages, which covered the third
and early second millennia B.C. (Table 3).
Early Bronze I provided a formative, village-level prelude to the fortified towns and cities
^^7 Negev Desert
Figure 7. Geomorphic/settlement zones in the southern
Levant. Hatched areas indicate survey subregions con-
sidered in this study. Approximate coverages: Total
southern Levant = 15,000 km2; Coastal Plain = 2,650km2;Central Hills = 7,500 km2;Jordan Valley = 1,700
km2.Compiled from Broshi and Gophna (1984:Table 11),
Ibrahim et al. (1976:Figure 1, 1988:192-193).
that emerged in Early Bronze II and III (Joffe1991a). This urban florescence paralleled the
rise of the Egyptian state during Dynasties I-
VI (Kemp 1983:71-116; Ben-Tor 1991; Kan-
tor 1992:17-21; Stager 1992:40-41). Subse-
quently, Egypt entered the First Intermediate
Period, during which centralized authority
collapsed and regional economic ties were at-
tenuated (Ward 1971; Stager 1992:41). The
southern Levant simultaneously experiencedwholesale abandonment of cities in favor of
village life and nonsedentary pastoralism
during Early Bronze IV (Dever 1980; 1989)5.
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AMERICANANTIQUITY
Table 3. Levantine Chronology.
Period Beginning Date Ending Date
Middle BronzeIIB-C ca. 1800 B.C. ca. 1500 B.C.
Middle BronzeIIA ca. 2000 B.C. ca. 1800 B.C.
Early Bronze
IV ca. 2300 B.C. ca. 2000 B.C.
Early BronzeIII ca. 2700 B.C. ca. 2300 B.C.
Early BronzeII ca. 3100 B.C. ca. 2700 B.C.
Early Bronze I ca. 3500 B.C. ca. 3100 B.C.
Note: Based on historic correlations and recalibrated
radiocarbon dates (see Falconer 1993, Stager 1992:40-
1, Joffe 1991b:Table 3, Richard 1987).
Unfortunately, published settlement data for
this striking period of collapse are available
only from the coastal plain.
The duration of the Middle Bronze Age
approximated that of Egypt's Middle King-dom (Weinstein 1975). While Egypt reesta-
blished state-level government and far-flung
economic influence, Levantine cities ree-
merged suddenly ca. 2000 B.C. in Middle
Bronze IIA. During Middle Bronze IIB and
C the region's cities and general population
grew to sizes unsurpassed until the Roman
and Byzantine periods (i.e., first-seventh cen-
turies A.D.; Broshi 1979). The archaeological
distinctions between Middle Bronze IIB and
C are subtle and not universally recognized
(Falconer 1987:180-181), and settlement data
commonly are analyzed jointly, as we do here.
This study draws on data compiled by sev-
eral authors for specific periods (Joffe 1991b;
Broshi and Gophna 1984; 1986) or regions
(Finkelstein and Gophna 1993; Gophna and
Portugali 1988; Ibrahim et al. 1975, 1988) in
the southern Levant. Since this literature cites
a wide variety of local and regional surveys,it offers few discussions of survey methods.
Levantine surveys typically collate data from
earlier surveys and maps, while new field-
work combines purposive vehicular recon-
naissance, intensive pedestrian tactics, and
questioning of local inhabitants (Joffe 1991 b:
34-44; Ibrahim et al. 1976:44). Most authors
presume virtually complete survey coverage
(e.g., Finkelstein and Gophna 1993:2) and
judge the likelihood of finding additional
largersites to be "practically nil" (Broshi and
Gophna 1986:88; 1984:50). Hence, as in
Mesopotamia, the vast majority of unde-
tected sites are likely to have been small.
Despite the lack of an explicit study of sur-
vey efficiency like Adams's, we may approx-
imate site recovery rates based on several
considerations. First, since Levantine sur-
veys encompass areas of substantial modern
habitation and agriculture, these factors un-
doubtedly obscure small sites to a greater ex-
tent than in Mesopotamia. On the other hand,
Levantine alluviation, which does affect somesites (e.g., Braun 1985; Rosen 1986:45), is
limited to the intermittent erosion of hill
slopes (Beaumont 1985), rather than the con-
tinuous massive silt transport of the Tigris
and Euphrates rivers. While natural factors
may affect site visibility more commonly in
Mesopotamia, cultural influences may have
a greater impact in the Levant. In sum, we
estimate Levantine site recovery rates on the
same order as those for Mesopotamia, but
nudge them slightly higher because of the pre-dominance of intensive localized surveys that
rely more heavily on pedestrian tactics (Joffe
1991b:34-44), rather than macroscopic ve-
hicular coverage.6 These considerations sug-
gest an average site recovery rate on the order
of 75 percent, only slightly lower than that
guessed by Broshi and Gophna (1984:41,
1986:73, 88).
Rank-Size Analyses of Levantine Urbanism
In light of the preeminence normally ascribed
to fortified Bronze Age cities in the southern
Levant (e.g., Dever 1987; Richard 1987), we
might anticipate accordingly primate rank-
size settlement distributions. When com-
bined for the entire region, Bronze Age sur-
vey data do produce a series of probabilities
below .01 (Table 4). However, these values
reflect convex departures from log-normal, as
exemplified for the high points of Levantine
urbanism in Early Bronze III and Middle
Bronze IIB-C (Figure 8). This consistent pat-
tern implies a series of poorly integrated re-
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gionwide systems or the pooling of many more
localized settlement networks. As we shall
see, these two interpretations are not mutu-
ally exclusive.First, let us consider the possibility of
pooled systems before returning to argu-ments for integration and disintegration be-
low. Finkelstein and Gophna (1988) note that
the Bronze Age ushered in the economic
"conquest" of the central hill country. Unlike
the coastal plain and Jordan Valley, which
were ideal for lowland agriculture, the central
hills were best suited for large-scale fruit
growing and summer pasturage. Thus, a cor-
ollary of Bronze Age urbanism was an emerg-ing potential for significant economic spe-
cialization and pastoral interplay between
6
Nd
Rank
Figure 8. Rank-size distributions for Early Bronze III
and Middle Bronze II B-C settlement in the southern
Levant. Data from Joffe (1991b), Finkelstein and Gophna
(1993), Gophna and Portugali (1988), Broshi and Gophna
(1984; 1986), Ibrahim et al. (1976, 1988).
Table 4. Summary of Simulation Runs for Southern Levant.
Numberof Sites Ob-
Sample in served
Largest Number Per- Popu- K- Proba- Curve
Region Period Sitea of Sitesb cent lationc Value bilityd Shape
Southern Levant Middle Bronze IIB-C 80.0 219 75 292 .479 <.01 ConvexMiddle Bronze IIA 80.0 96 75 128 .573 <.01 Convex
Early Bronze III 30.0 202 75 269 .406 <.01 Convex
Early Bronze II 40.0 151 75 201 .377 <.01 Convex
Early Bronze I 40.0 243 75 324 .370 <.01 Convex
Coastal Plain Middle Bronze IIB-C 64.0 59 75 79 .610 <.01 P-cnvxeMiddle Bronze IIA 65.0 51 75 68 .745 <.01 P-cnvxe
Early Bronze IV 5.0 16 75 24 .564 <.01 D-cnvxr
Early Bronze III 25.0 12 75 16 .250 .25 L-norm
Early Bronze II 25.0 24 75 32 .500 <.01 Convex
Early Bronze I 25.0 42 75 56 .595 <.01 Convex
Central Hills Middle Bronze IIB-C 15.0 91 75 121 .385 <.01 ConvexMiddle Bronze IIA 12.0 9 75 12 .444 <.01 Convex
Early Bronze III 11.0 49 75 65 .347 <.01 Convex
Early Bronze II 15.5 43 75 57 .465 <.01 Convex
Early Bronze I 15.0 81 75 108 .469 <.01 Convex
Jordan Valley Middle Bronze IIB-C 7.0 26 75 35 .308 .24 L-normMiddle Bronze IIA 7.0 13 75 17 .231 .29 L-norm
Early Bronze III 25.0 36 75 48 .444 <.01 Convex
Early Bronze II 20.0 32 75 43 .219 .69 L-norm
Early Bronze I 20.0 64 75 85 .219 .78 L-norm
a Size in hectares.b Includes only sites with unequivocal dates of occupation and known size. Some counts are underestimated (e.g.,MBIIA in the Central Hills).c Number of sites in population = number of observed sites x (1/sample percent).d Probability of drawing a K- value greater than or equal to the observed value at random from a log-normal
population, based on 1,000 random runs for each row.e P-cnvx = Primo-convex curve.f D-cnvx = "Double convex" curve.
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AMERICANANTIQUITY
100 -
_................. EB I observed--- EB ml observed
-_-- - Expected (EB I & HI)
10-
SU~:_^^-~10 100
Rankank
Figure 9. Rank-size distributions for Early Bronze I
and Early Bronze III settlement on the Coastal Plain.
Data from Joffe (1991b), Gophna and Portugali (1988),
Broshi and Gophna (1984).
highlands and lowlands (Finkelstein and
Gophna 1993). Therefore, it is not surprising
that Bronze Age society followed multiple
courses of development, which may be dis-
tinguished according to geomorphic zones of
settlement. We present analyses of settlement
in the coastal plain, the central hills, and the
Jordan Valley, which reveal these variabletrajectories, and collectively constitute the
early urbanization of the southern Levant.7
The Coastal Plain
If there was a "heartland" of Levantine ur-
banism, it was the Mediterranean coastal
plain, which contained most Bronze Age
communities 10 ha and larger (Falconer
1994). Among the best-known sites in the
coastal plain are Tell Dor, Aphek, Tell Gezer,Tell el-'Areini, and Ashkelon (see Figure 7).
During the Early Bronze Age, a growing
coastal population became increasingly con-
centrated in larger towns and cities as rural
settlement dwindled (Gophna and Portugali
1993). Coastal settlement data produce prob-
abilities below .01 for Early Bronze I and II,
and a more equivocal estimate of.25 for Ear-
ly Bronze III. Unlike any pattern found in
Mesopotamia, these data describe slightly
convex upper rank-size curves that join morepronounced lower convex curves character-
Figure 10. Rank-size distributions for Early Bronze IV
and Middle Bronze II B-C settlement on the Coastal
Plain. Data from Gophna and Portugali (1988), Broshi
and Gophna (1986).
ized by stair steps (Figure 9). These unusual
distributions bear a striking resemblance to
primo-convex curves, but since their upper
portions are convex rather than concave, we
refer to their form as "double convex."
Through the Early Bronze sequence, the
lower curves become increasingly truncated.
The relatively high probability estimate forEarly Bronze III (p = .25) reflects a particu-
larly drastic curtailment of the rural settle-
ment that defined the lower curves of Early
Bronze I and II. This trend presages the sub-
sequent abandonment of coastal sedentism
in EarlyBronze IV. Coastal population growth
resumed on a grander scale in the Middle
Bronze Age (Gophna and Portugali 1988).
Very low probabilities (p<.0O) again reflect
compound rank-size distributions that de-
part substantially from log-normal (Figure10). Unlike those of the Early Bronze Age,
these curves are primo-convex, and reflect
slightly increased numbers of medium- and
small-sized settlements.
Following the examples and general rea-
soning summarized earlier, we propose that
these primo-convex and "double convex"
rank-size distributions signify the superim-
position of multiple, contemporaneous set-
tlement systems. Coastal settlement during
the Early Bronze IV Period is particularlynoteworthy for interpreting these curves. A
CZ
._c/
Rank
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Falconer and Savage] EARLYURBANIZATIONN MESOPOTAMIANDTHESOUTHERN EVANT
modest array of very small towns (two mea-
sure 5 ha each) and diminutive villages (none
larger than 1 ha) comprised a "decapitated"
settlementsystem
that followed the aban-
donment of larger towns and cities. This con-
vex distribution has a very low probability
(p<.01) of being drawn from log-normalpopulation. Since the Early Bronze IV rank-
size distribution results from the elimination
of an upper settlement curve, this convex
curve is comparable to the lower curves of
Early Bronze I-III. This pattern provides cir-
cumstantial evidence that each compoundcurve of Early Bronze I-III may indeed be
composed of an upper distribution of townsand cities superimposed on a relatively dis-
crete lower curve of villages and hamlets.
In keeping with this interpretation, our data
suggest that an Early Bronze Age network of
loosely knit towns and cities was established
amid a dwindling and increasingly disartic-
ulated system of small villages. Statuary ex-
cavated from coastal sites and texts from
Egypt suggest that this patterning reflects the
presence of Egyptian commercial missions in
coastal towns (Ahituv 1978; Na'aman 1981).While also "compound," the Middle Bronze
rank-size plots differ in three respects: the
more concave upper curves suggest more cen-
tralized integration of towns and cities, the
more extended lower limbs reflect more pro-nounced ruralism, and the upper and lower
curves remain more closely articulated.
We must conclude that despite containingmost of the Levant's cities, the coastal plainwas neither a heartland of urban nucleation,
nor a hinterland of lower level urban-ruralintegration. Early Bronze coastal cities re-
mained relatively static in size and number
(Joffe 199 lb:Table 23), and their lack of rank-
size primacy suggests that they failed to exert
the influence of centers like Uruk, even on a
reduced scale. During the Middle Bronze Age,both urban and rural populations grew, but
only slightly (Falconer 1994). An element of
Middle Bronze Age rank-size primacy, which
became more pronounced in MB IIB-C, sug-
gests that MB cities could have had a moldinginfluence, but exercised it only to a limited
0)
rC
10
Rank
Figure 11. Rank-size distributions for Early Bronze II
and Middle Bronze II B-C settlement in the Central Hills.
Data from Finkelstein and Gophna (1993), Joffe (1991b),
Broshi and Gophna (1984; 1986).
extent. This portrait of coastal urbanism may
be clarified with reference to the Levantine
"hinterlands" of the central hills and Jordan
Valley.
The Central Hills
With the emergence of highland/lowland eco-nomic interaction (see above), we might pre-
dict that coastal settlement systems may have
incorporated rural communities in the ad-
joining central hills. Indeed, Early and Mid-
dle Bronze settlement data produce consis-
tently convex rank-size distributions (p< .01;
Figure 11), as we would expect if villages in
the hills supplemented coastal ruralism. Oth-
er analyses verify that hill country villagesbecame more abundant between EarlyBronze
I and II (Joffe 1991 b:Tables 20, 21), and pro-liferated dramatically in the Middle Bronze
Age (Broshi and Gophna 1986; Falconer
1994). However, these communities declined
drastically during the first urban climax of
Early Bronze III as part of a general popu-lation drop in the hill country (Finkelsteinand Gophna 1993). So, during Early Bronze
I and II and the Middle Bronze Age, some
settlement in the central hills may have com-
pensated for the otherwise under-represented
ruralism of the coastal plain. In contrast, Ear-ly Bronze III represents a nadir in rural set-
53
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AMERICANANTIQUITY
a
.Nu
Rank
Figure 12. Rank-size distributions for Early Bronze I,
Early Bronze III, and Middle Bronze II B-C settlement
in the Jordan Valley. Data from Joffe (1991b), Broshi
and Gophna (1984; 1986), Ibrahim et al. (1976, 1988).
tlement contemporaneous with that of the
coastal plain.
The Jordan Valley
Among the settlement zones within the
southern Levant, only the Jordan Valley dis-
plays patterns of development that resemble
any of those found in Mesopotamia. Much
as we saw for the Diyala, very high EarlyBronze I and II probability estimates suggesta similar pattern of close adherence to log-normal and low-level hinterland integration
(Figure 12). However, unlike the Diyala, the
Jordan Valley experienced a drop in popu-lation and settlement frequency (Joffe 1991 b:
Table 18). While valleywide population lev-
eled off in Early Bronze III, the settlement
system became significantly less integrated as
suggested by its convex rank-size distribution
(p<.01). In this case, rather similar EarlyBronze II and III rank-size curves generate
very different simulation results, primarilybecause the lower end of the Early Bronze III
curve consists of smaller sites, which implya shrinking population of rural farmers.
During the Middle Bronze Age, sedentarysettlement redeveloped in the Jordan Valleyon a more modest scale. The valley's popu-lation grew slightly, while the number of set-
tlements roughly doubled (Broshi and
Gophna 1986; Falconer 1994). Settlement
data produce relatively high probabilities that
the observed convex distributions are simply
samples drawn from a log-normal popula-tion. It appears that after the non-urban in-
terlude of Early Bronze IV, local inhabitants
dispersed into a renewed hinterland network
of towns and villages, which was again rough-
ly analogous to that of the Diyala.
Summary of Levantine Urbanism
Early Bronze Age urbanization in the Levant
is striking, because while urban communities
grew, primarily along the Mediterranean
coast, regional population declined as smallersettlements dwindled in number and size in
all three subregions (Joffe 1991 b:Tables 8, 11,
12, Figures 9, 10). Far from anticipating this
waning sedentary population, most conven-
tional interpretations view the Early Bronze
Age as a period of pronounced population
growth (e.g., Amiran 1970; Richard 1987).
Instead, these patterns hint that rural popu-lations may have adopted strategies of "re-
silience" (Adams 1978) based on increased
pastoralism that peaked during the urban col-lapse of Early Bronze IV. This interpretationfinds circumstantial support in the persistent
compound nature of coastal rank-size curves
and the declining ruralism of the central hills
and Jordan Valley.In contrast, Middle Bronze Age urbaniza-
tion fits conventional expectations much bet-
ter. Survey data suggest population growth,both in cities and the general countryside.While compound rank-size curves still sug-gest that cities and towns were superimposedon coastal ruralism, urban-rural integrationbecame enhanced and may have extended
into the hill country. In the Jordan Valley,settlement returned to a distinct pattern of
hinterland development similar to that of the
Diyala, but on a further reduced scale.
Interestingly, the advent of cities in the third
millennium B.C. and their rejuvenation in
the early second millennium B.C. followed
different courses of development. Further,
when dissected geographically, settlementdata from both periods reveal distinct, some-
54 [Vol. 60, No. 1, 1995
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Falconerand Savage] EARLYURBANIZATIONN MESOPOTAMIANDTHESOUTHERN EVANT
times divergent settlement trajectories within
the coastal plain, central hills, and Jordan
Valley, a composite pattern perhaps most
characteristic of Levantine urbanism. While
the southern Levant must have been affected
by the actions of foreign cities and states,
notably those of Egypt, its own expression of
urbanism was not simply derivative. Rather,
the earliest urbanism in the southern Levant
described an intriguing patchwork, in which
the largest cities were superimposed on a
much broader network of resilient towns and
villages that followed their own courses of
development.
Conclusions
Orthodox approaches to Near Eastern ur-
banism treat the rise of Near Eastern cities
as a uniform phenomenon with core and
marginal expressions. Adams recalls that
Benno Landsberger, a noted Assyriologist,
criticized his choice of the Diyala Basin for
initial survey reconnaissance because this
work defined a derivative "dialect" of early
urbanism "before the paradigm of the heart-
land [was] known" (Adams 1981 :xviii). Mosttreatments of the southern Levant follow a
similar logic in which the rise of Bronze Age
cities is interpreted as a local vernacular ex-
pression of Near Eastern urbanization. This
view holds that Levantine urbanism simply
followed and echoed that of Syria and Mes-
opotamia, but on a smaller scale. While Mes-
opotamia is justifiably renowned for its heart-
land of very early, highly nucleated cities, our
rank-size analyses also elucidate a distinct
expression of hinterland development in theDiyala based on more modest, but consis-
tently integrated town and village life. In con-
trast, we demonstrate that Early Levantine
urbanism rarely adheres to either of these
general patterns, but represents a distinct geo-
graphic and chronological mosaic that defies
simple categorization. We conclude that Near
Eastern urbanization did not include so much
a Mesopotamian core and its dialectical off-
shoots, as a polyglot arrayof alternative forms
of city life and its relations with the country-side.
Ultimately, our study implies that cities do
not, in any uniform sense, epitomize all "ur-
banized" societies. A fuller comprehension
of urbanization as a highly variable phenom-
enon requires that we expand our compre-hension of non-urban components in strati-
fied settlement systems. We suggest that small
communities are most important in this re-
gard, not simply as a supporting foundation
for urbanism. Instead, configurations of rural
settlement often define the overall contours
of rank-size distributions and, in so doing,
may reveal peculiar courses of rural devel-
opment that contribute to the variety of tra-
jectories for early urbanization in Mesopo-
tamia, the southern Levant, and elsewhere in
southwestern Asia.
Acknowledgments. We thank George Cowgill, Charles
Redman, Norman Yoffee, and especially Keith Kintigh
for their abundant commentary on preliminary versions
of this study. The mathematical assumptions underlying
the K- test were brought to our attention through lengthy
discussion with Dennis Young, Department of Mathe-
matics, Arizona State University. Carole Crumley, Keith
Kintigh, Kenneth Kvamme, and Barbara Stark made
helpful suggestions during the development of the sim-ulation program. Moawiyah Ibrahim, James Sauer, and
Khair Yassine kindly provided access to the field notes
and ceramic collections of the East Jordan Valley Survey.
Falconer derived site size estimates from these sources
with the support of a National Endowment for the Hu-
manities Travel to Collections Grant.
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Notes
' The RankSize programwas written by Savage in Turbo
Pascal 6.0 (Borland International 1990) for IBM PC or
compatible computers.2 These periods lie at the crossroads of prehistoric ra-
diocarbon-based chronologies and historic chronologies.
Radiocarbon recalibrations tend to push these horizons
earlier, often by several centuries (e.g., see Aurenche,
Evin, and Hours 1987).3 Most archaeological sites in Mesopotamia and the
southern Levant are multiphase mounded tells in which
later deposits obscure the habitation areas of earlier stra-
ta. Since site size often can only be estimated according
to the area covered by the largest occupation, some es-
timates are inflated. However, most survey reports offer
period-by-period size estimates whenever possible, pri-
marily for larger sites.
4 For the sake of graphic clarity only selected curves are
presented in our rank-size figures (Figures 4-6, 8-12).
However, simulation results for all rank-size analyses
are included in Tables 2 and 4.
5This period is referredto as "Intermediate Bronze" or"Intermediate EB-MB" in some literature (see discus-
sion in Falconer 1993).6 Schiffer (1987:340-353) provides a broader discussion
of the many factors that influence site recovery rates by
archaeological surveys.7 These zones correspond to geographic zones 4, 6, 7,
and 9 in Joffe 1991b, and Broshi and Gophna 1984 and
1986.
Received September 28, 1993; accepted August 1, 1994
58 [Vol. 60, No. 1, 1995
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