“When north-south relations were east-west:
urban and empire synchrony (500 BCE-1500 CE)”
Christopher Chase-Dunn, Richard Niemeyer, Alexis Alvarez,
Hiroko Inoue, Kirk Lawrence and Anders Carlson
To be presented at the 2006 conference of the International Studies Association, San Diego, March 23, 3:45-5:30 PANEL: The Historical Long-Term. 5006 words
This paper is available at http://irows.ucr.edu/papers/irows16/irows16.htm
The growth and decline patterns of the world’s largest cities and empires and their changing locations over the past three millennia provide an important window on world history. Earlier research has repeatedly demonstrated a fascinating synchrony in the growth/decline phases of largest cities and empires in East Asia and the West Asian/Mediterranean region (e.g. Chase-Dunn and Willard 1993; Chase-Dunn, Manning and Hall 2000; Chase-Dunn and Manning 2002).
data on the population sizes of largest cities and the territorial sizes of
largest empires it has been discovered and repeatedly confirmed that
medium-term growth/decline phases in
The population and areal sizes of human settlements have increased since the emergence of sedentism around 12,000 years ago, and so have the sizes of the largest polities. But these general long-term trends have been complicated by sequential middle-term declines in the sizes of the largest cities and empires in all regions where urban and polity sizes have been studied quantitatively. The population size estimates of both modern and ancient cities are subject to large errors, and existing compilations (Chandler 1987; Modelski 2003) badly need to be improved using better methods of estimation (e.g. Pasciuti and Chase-Dunn 2002). The same can be said for existing compilations of estimates of the territorial sizes of the world’s largest empires (Taagepera 1978a, 1978b, 1979, 1997). When these upgraded estimates become available, the East/West synchrony findings discussed here will need to be reexamined with the improved data. We believe that the East/West synchrony finding will be confirmed.
This phenomenon of East/West urban and empire synchrony in middle-term growth/decline phases has been subjected to several different methods of analysis, and it holds up across all of them. Both changes in the size of the largest cities and changes in the steepness of the city-size distributions have been used. And earlier studies have used two different kinds of spatial units of analysis: constant regions and expanding political-military networks (interaction networks of fighting and allying states). The East/West synchrony has been found with both.
Detrending is important because the long-term trend for city and empires sizes to increase. Two different methods of detrending have been used: partial correlation controlling for year and decadal change scores in which the earlier year is subtracted from the later year. In the studies of empire sizes, empires that touch adjacent macro-regions such as the Mongol Empire of the thirteenth century CE have been removed from the analysis because they build in a degree of synchrony by appearing in both regions at the same time. The synchrony finding is strong even when this case has been removed from the calculations.
Teggart’s (1939) path-breaking world historical study of temporal
correlations between events on the edges of the Roman and Han Empires argued
the thesis that incursions by Central Asian steppe nomads were the key to
East/West synchrony. An early study of city-size distributions in Afroeurasia
(Chase-Dunn and Willard 1993; see also Chase-Dunn and Hall 1997: 222-223) found
an apparent synchrony between changes in city size distributions and the growth
of largest cities in
Figure 1: Sizes of Largest cities in
other instances of distant systems that came into weak contact with one another
can be found. Within the Old World, the Mesopotamian and Egyptian core
regions were interacting with one another by means of prestige goods exchange
from about 3000 BCE until their political-military networks (state systems)
merged in 1500 BCE. Chase-Dunn, Pasciuti, Alvarez and Hall (2006) have already
examined this case for synchrony and have not found it, though the data on
Bronze Age city and empire sizes are very crude with regard to temporality and
accuracy. It is also possible to study the temporality of rise and fall and
oscillations among distant regions in the
Chase-Dunn, Alvarez and Pasciuti (2005) also report detrended correlations between constant regions for total population estimates taken from McEvedy and Jones (1975). These total population estimates at 100-year intervals show rather high growth/decline synchronies for several regions, also noted and discussed by McEvedy and Jones (1975: 343-48).
East/West growth/decline synchrony seems to be rather robust, though better
estimates and finer temporal resolution of empire and city sizes might
challenge it. Interregional synchrony can be caused when two cyclical processes
get simultaneously reset, either by the same cause or by different causes. This
could be a one-shot occurrence. Or a process that is similarly cyclical can
cause synchrony. Candidates for the East/West synchrony are: climate change,
epidemic diseases, trade interruptions, or attacks by
change might affect regions by causing growth and decline of agricultural productivity
that in turn affects cities and empires. Perhaps because
climate change could also be involved in somewhat more complicated ways.
Central Asian steppe nomads (discussed below) were very susceptible to climate
change because their pastoral economy was greatly affected by changes in
temperature and rainfall. It is possible that climate change in
The above hypotheses all conceive of climate change as an exogenous variable. But it is also possible that city and empire growth change the climate. We know that population growth and the development of complex civilizations changes the environment by means of deforestation, soil erosion and the construction of large irrigation systems (Diamond 2005). These changes may have affects on climate. Modern studies show that the construction of large cities creates an “urban heat island” that changes the environment in the immediate vicinity and downwind of cities. Cities ingest and egest water, air and energy, and while industrial cities do this on a much larger scale, earlier large cities also did it to some extent. So large-scale agriculture and city-building may be causes of climate change. Thus climate change may also be an endogenous variable.
We know that Central Asian steppe nomads who raised horses and sheep periodically formed large confederacies and attacked the agrarian empires of the East and the West (Barfield 1989). Famous examples are the Huns and the Mongols. Perhaps there was a cycle of Central Asian incursions that impacted upon the agrarian civilizations of the East and the West and that accounts for the synchrony.
know that epidemic diseases spread across
We also know that the Roman and Han empires were linked by long distance trade routes across the Silk Roads and by sea. Perhaps interruptions to trade, or periods of greater and easier trade flows, affected the Eastern and Western civilizations simultaneously.
It is also possible that two systems that are cycling independently can become synchronized if they are both reset by a simultaneous accidental shock. This is the so-called “Moran Effect” known in population ecology. We have discussed this possibility in Chase-Dunn, Alvarez and Pasciuti (2006).
Figure 2 is a propositional inventory that includes most of the possible causes of East/West synchrony.
Figure 2: Possible Causes of East/West Synchrony
research is required to find out which of these possible causes was responsible
for the East/West synchrony. We have found some evidence that temperature
East Asian Climate Change and Growth/Decline Phases
have located time series data on two indicators of climate change in
first indicator we have of climate change from China is an estimate of changes in average temperature that are inferred from
measurements taken of stalagmites formed in the Shihua cave near Beijing (Tan et
al 2003). Ideally
the indicator of climate change should be geographically near the area of city
and empire growth. Recent research on El Nino and the Southern Ocean
Oscillation shows that climate dynamics on a global scale are linked by huge
inter-regional “teleconnections” in which changes in ocean temperature in one
region affect rainfall and temperature in distant other regions, but the
resulting patterns are very different from region to region (Davis 2001). This
means that we need to have information on climate change that is spatially near
to the areas where we are studying the possible impacts. Knowing what happened
in Greenland or
The estimated temperature series as well as the plots for largest city and largest polity from 650 BCE to 1800 CE are shown in Figure 3.
Figure 3: Temperature Change (
Figure 3 graphs the temperature changes inferred
Table 1 reveals a significantly steady rate of
empire growth throughout the period, when plotted against DECADE (correlation
is 0.587, p < 0.01). Similarly, the
population of the largest city in
Table 1: Bivariate
and partial correlations: largest city, largest empire, temperature estimate
Table 1 also confirms an earlier finding of a
significant bivariate and partial temporal correlation between city and empire
The results in Figure 1 and Table 1 are based on only 26 time points because of the paucity of data on city population sizes, which have been estimated at only very widely-spaced intervals, especially for the earlier time periods. When we examine the relationship between empire sizes and temperature change separately we have far better temporal resolution. Figure 4 graphs the empire sizes using ten-year interpolated values and the ten-year moving average of yearly temperature estimates. The bivariate correlation is .02.
Figure 4: Largest Empire and Temperature Change in
Figure 5 shows the same relationship, but it is easier to see what is going on because the scores have been standardized.
Figure 5: East Asian Largest Empires and Average Temperatures (standardized values)
Figure 6 depicts the relationship between
Figure 6: Largest Cities and Average Temperature with city polynomial
results so far imply that there is no regular relationship between climate
change and the growth/decline phases of cities and empires in
temperature is only one indicator of climate change. Yearly rainfall, the
distribution of rainfall throughout a year, the frequency of large and
destructive storms – all these are important aspects of climate change that may
have large effects on agriculture and irrigation systems but are not well
reflected in temperature changes. It is also possible that climate change near
We also want to examine the possibility of time lags between climate change and city and empire growth decline phases. The methods employed above presume a simultaneous causality, whereas it is likely that changes in climate take some period of time to affect the sizes of cities and empires. This can be systematically examined using the techniques employed by Turchin and Korotayev (nd) for studying lagged dynamical relations among time series variables. We plan to do this in the next version of our research.
Climate Oscillations in the
of the climate change within
the Mediterranean region is a product of the North Atlantic Oscillation (NAO),
a hemispheric meridional oscillation in atmospheric mass between the polar
Figure 7: Atmospheric regions responsible for North Atlantic Oscillation
Figure 8: Atmospheric effects and climate results of the NAO positive phase.
Figure 9: Atmospheric effects and climate results of the NAO negative phase
Climate conditions within
Figure 10. Regions affected by the Asian Monsoon
Connections between the NAO and the Asian Monsoon
Recent research has
supposedly established a synchronic connection between regions affected by the
NAO and regions affected by the Asian Monsoon (Wang et al. 2005). Generally speaking, many of the abrupt
climate change events in the paleoclimatology record of the Asian Monsoon
correlate with abrupt climate change in the Mediterranean and
Comparison of the smoothed (5-point running average) detrended China climate
proxy data (green) with the smoothed 20-year averaged Greenland climate proxy
record (5-point running average, red) over the past 9000 years. The broad
correlations between the
From Wang et al. 2005, http://www.sciencemag.org/cgi/content/full/308/5723/854
Figure 12: Geographic locations of proxy measures for climate conditions
In order to further examine the hypothesis of
East/West climate synchrony we compared proxy precipitation data from the Red
Sea (Lamey et al. 2006) with
Contrary to the previous research cited above, a
positive correlation between
Figure 13: East/West Estimated Precipitation Oscillations (Sources: Wang et al 2005 and Lamey et al 2006)
With regard to the correlation between the precipitation estimates
Figure 14: East Asian Precipitation and Temperature
The relationship between the
this point we are lacking firm conclusions. There do not appear to be big
climate events in either East or
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