Upsweep Inventory:
Scale Shifts of Settlements and Polities in World-Systems Since the Stone Age
Christopher Chase-Dunn, Alexis Alvarez, Oswin Chan,
Ben Fierro and Hiroko Inoue
Institute for Research on World-Systems
University of California-Riverside
Riverside, CA. 92521-0419 USA
v. 3-10-08, 9722 words
Rome
National Science Foundation Grant #: NSF-HSD SES-0527720 Award type: HSD-AOC
PI: Christopher Chase-Dunn, Institute for Research on World-Systems, University of California-Riverside; Co-PIs: Peter Turchin, University of Connecticut and E.N. Anderson, University of California-Riverside
To be presented at the annual meeting of the International Studies Association, 10:30 am Wednesday March 26, 2008, San Francisco, Session WB37 “Theory and History in World-Systems Research” organized by Richard Niemeyer. Discussant: Heikki Patomaki.
This paper is IROWS Working Paper #39 available at http://irows.ucr.edu/papers/irows39/irows39.htm
This paper reports the most recent results of a research project that studies the growth/decline phases of settlements and polities since the Stone Age. The project uses quantitative estimates of population sizes of the largest settlements in regions and estimates of the territorial size of polities to study changes in the scale of human institutions. It is part of a larger effort to construct non-linear dynamical models of human socio-cultural evolution and future global state formation (See Chase-Dunn, Anderson and Turchin 2005).[1] Here we report the results of an inventory of upward sweeps. Upward sweeps are defined as instances in which the largest settlements and/or polities significantly increase in size for the first time in a given region. Our comparative project is theoretically global in scope and would like to include both nomadic and sedentary world-systems, though in practice we are limited by the availability of estimates of largest polity and settlements sizes.
Cycles, Upward Sweeps, Collapses and Ceilings
Our project compares relative small regional world-systems with larger continental and global systems, thus we must abstract from scale in order to examine changes in the structural patterns of small, medium and large human interaction networks. We mainly focus on medium term change in the scale of polities and settlements. In the long run settlements and polities have tended to get larger, but our research focuses on medium-term sequences of growth and decline in order to identify those upward sweeps in which the scale significantly changes. Identification of these events will facilitate testing models of socio-cultural evolution because these are the events that account for the long-run trend toward larger and more complex human social institutions.
When we use world-systems --an interacting set of polities and/or settlements-- as the unit of analysis nearly all systems oscillate in what we may term a normal cycle of rise and fall – the largest city or polity reaches a peak and then declines and then this or another city or polity returns to the peak again. Note that this cycle is usually not observed by looking at a single polity or settlement in isolation, but rather by looking at the largest settlements and polities within a region of interaction. We call this a normal cycle of rise and fall. It roughly approximates a sine wave, although few cycles that involve the behavior of groups of humans actually display the perfect regularity of amplitude and period found in the pure sine wave.
In Figure 1 the normal cycle of rise and fall is half way down the figure and is labeled “normal rise and fall.” At the top of Figure 1 is a depiction of an upward sweep in which the size of the largest entity (state or city) increases by a factor of 2. Such a sweep may be relatively rapid or may be slow, and Rein Taagepera (1978a) observes that the speed of the rise is often related to the sustainability of the upsweep, at least in the case of empires. Taagepera notices that empires that rise more slowly tend to last longer than those that rise abruptly. When an upward movement is sustained and a new higher level of scale becomes the norm we call this an upward sweep. When it is temporary and returns to the old lower norm we call it a “surge” (see the 2nd line from the top in Figure 1). We also distinguish between three types of decline, a “normal” decline which is part of the normal rise and fall cycle, a short-term collapse in which a decline goes significantly below what had been established as the normal trough, and a sustained collapse in which the new lower scale becomes the norm for some extended period of time.
Jared Diamond (2005) has discussed the factors that cause collapses, though he does not employ quantitative indicators of collapse and he often focuses on particular societies or settlements that collapsed while ignoring neighboring societies or settlements that rose. If intersocietal interaction networks (world-systems) had been his unit of comparison instead of single societies some of the cases he studied would be seen to have been instances of what we are calling normal rise and fall cycles rather than instances of system-wide collapse. A genuine collapse is when all the societies in a region go down and stay down for at least two average cyclical periods.
Figure 1: Types of medium-term scale change in the largest settlement or polity in an interacting region
This paper reports the results of an inventory of all the instances of the types of scale change of city population sizes and the territorial sizes of polities (chiefdoms, states and empires) for the regional networks for which we currently have quantitative data. We will use this inventory to identify instances of each type of change, and will use these as cases for testing our models. This paper reports results for all regions for which we have adequate data except for the U.S. Southwest.[2]
Figure 2 is a stylized depiction of the rise and fall of large polities and occasional upward sweeps that portrays, not the history of a single world region, but rather the general evolution of what has happened over the past 12,000 years as many small polities (bands, tribes and chiefdoms) have been consolidated into a much smaller number of larger polities (states, empires and a possible future world state).
Figure 2: Rise, Fall and Upward Sweeps of Polity Size
George Modelski’s (2003) recent study of the growth of cities over the past 5000 years points to a phenomenon also noticed and theorized by Roland Fletcher (1995) – cities grow and decline in size, but occasionally a single new city will attain a size that is much larger than any earlier city, and then other cities catch up with that new scale, but do not much exceed it. It is as if cities reach a size ceiling that it is not possible to exceed until new conditions are met that allow for that ceiling to be breached. This notion of size ceiling will also be useful for studying changes in the sizes of polities.
Theories of Rise, Fall and Upward Sweeps
There are many theories about why systems of interacting polities experience cycles of rise and fall. A thorough overview of the anthropological literature on “cycling” – the rise and fall of large chiefdoms-- is presented in David G. Anderson’s (1995) The Savannah River Chiefdoms. Chase-Dunn (2005) presents an overview of earlier theories and a new theoretical synthesis based on Peter Turchin's (2003) model of the dynamics of agrarian state growth and decline, a population pressure iteration model and explanations of the rise and fall of modern hegemons. This approach is further modified below to reincorporate the operation of trade networks. Explaining the upsweeps requires adding a discussion of emergent properties and the increasing geographical scale of interaction networks to the theories of rise and fall. Explaining collapses requires taking account of environmental fragility and resilience, cultural and technological flexibility and the other factors identified by Jared Diamond (2005)
Explaining Upsweeps
Earlier work on socio-cultural evolution has produced a synthesized “iteration model” of the processes by which hierarchies and new technologies have emerged in regional world-systems since the Paleolithic (Chase-Dunn and Hall 1997: Chapter 6). The iteration model assumes a system of societies that are interacting with one another in ways that are important for the reproduction and transformation of social structures and institutions. This comparative world-systems theory uses interaction networks rather than spatially homogenous characteristics to bound regional systems (Chase-Dunn and Jorgenson 2003). Bulk goods exchanges are an important network in all systems, and so are alliances and conflicts among polities (the so-called political/military network – PMN). Some systems are also importantly linked by the long-distance exchanges of prestige goods.
While Chase-Dunn and Hall used trade networks to spatially bound world-systems, they left trade out of the iteration model that explains why world-systems evolve. More recent works by McNeill and McNeill (2003) and Christian (2004) have stressed the importance of trade and communications networks in the processes of human socio-cultural evolution. Both of these recent works employ a network node theory of innovation and collective learning that is similar to the human ecology approach developed earlier by Amos Hawley (1971). Innovations are said to be unusually likely to occur at transportation and communications nodes where information from many different sources can be easily combined and recombined.
One advantage of using world-systems as the explicit unit of analysis and of examining the possibility that world-systems may be organized by core/periphery structures is that it allows us to see that there are important and repeated exceptions to the network node theory of innovation. It is often societies out on the edge of a system rather than at the center that either innovate or that successfully implement new strategies and technologies of power, production and trade. Chase-Dunn and Hall (1997: Chapter 5) synthesize earlier formulations into a theory of semiperipheral development in which a few of the societies that are in between the core and the periphery of a system are the ones that are most likely to come forth with strategies and behaviors that produce evolutionary transformations and upward mobility. This phenomenon takes various forms in different kinds of systems: semiperipheral marcher chiefdoms, semiperipheral marcher states, semiperipheral capitalist city states, the semiperipheral position of Europe in the larger Afroeurasian world-system, modern semiperipheral nations that rise to hegemony, and contemporary semiperipheral societies that engage in and support novel and potentially transformative economic and political activities.
The network node theory does not well account for the spatially uneven nature of evolutionary change. The cutting edge of evolution moves. Old centers are often transcended by societies out on the edge that are able to rewire network nodes in a way that expands the spatial scale of networks.
There are several possible processes that might account for the phenomenon of semiperipheral development. Randall Collins (1999) has argued that the phenomenon of marcher states conquering other states to make larger empires is due to the marcher state advantage. Being out on the edge of a core region of competing states allows more maneuverability because it is not necessary to defend the rear. This geopolitical advantage allows military resources to be concentrated on vulnerable neighbors. Peter Turchin (2005) argues that the relevant process is one in which group solidarity is enhanced by being on a “metaethnic frontier” in which the clash of contending cultures produces strong cohesion and cooperation within a frontier society, allowing it to perform great feats. Carroll Quigley (1961) distilled a somewhat similar theory from the works of Arnold Toynbee.
But Toynbee also suggested another way in which semiperipheral regions might be motivated to take risks with new ideas, technologies and strategies. Semiperipheral societies are often located in ecologically marginal regions that have poor soil and little water or other disadvantages. Patrick Kirch (1984) relies on this idea of ecological marginality in his depiction of the process by which semiperipheral marcher chiefs are most often the conquerors that create island-wide paramount chiefdoms in the Pacific. It is quite possible that all these features combine to produce what Alexander Gershenkron (1962) called “the advantages of backwardness” that allow some semiperipheral societies to transform and to dominate regional world-systems.
Iteration Revised
The first version of the iteration model of world-systems evolution was presented in Chapter 6 of Chase-Dunn and Hall (1997). It is called an iteration model because its overall structure is a positive feedback loop that explains the growing scale of human societies and world-systems since the Stone Age. But within the overall positive feedback loop there is a smaller negative feedback loop, the “nasty bottom” that comprises the human demographic regulator.[3] A revised version of the overall iteration model is depicted in Figure 3.
Figure 3: Revised Iteration Model of World-Systems Evolution
This version relabels some of the processes depicted in the original model and it adds trade, epidemics and non-anthropogenic climate worsening. Trade was put in because, after reading the world historians who emphasize a network node theory of innovation (e.g McNeill and McNeill 2003; Christian 2003), we realized that we had used interaction networks to bound world-systems but had mistakenly left them out of the causal model that explains socio-cultural evolution. So we put trade back in. Thompson (2008), and the large and persuasive literature that he reviews, convinced us that epidemics and non-anthropogenic climate change should also be included in the model as well. We note that anthropogenic climate change (e.g. due to deforestation, etc.) should be understood as part of “Environmental Degradation.”
In state-based systems periods of intensified conflict within and between societies lower the resistance to empire formation. A semiperipheral marcher state can “roll up the system” under such circumstances. Thus did the Neo-Assyrians, the Achaemenid Persians, Alexander, the Romans, the Islamic Caliphates and the Aztecs produce the core-wide empires that constitute the great upward sweeps of state size in the age of state-based systems.
During the Bronze and Iron Age expansions of the tributary empires a new niche emerged for states that specialized in the carrying trade among the empires and adjacent regions. These semiperipheral capitalist city states were usually “thalassocratic” entities that used naval power to protect sea-going trade (e.g. the Phoenician city-states, Venice, Genoa, Malacca), but Assur on the Tigris, the “Old Assyrian city-state and its colonies,” was a land-based example of this phenomenon that relied mainly upon donkey caravans for transportation (Larsen 1976). The semiperipheral capitalist city-states did not typically conquer other states to construct large empires, but their trading and production activities promoted regional commerce and the emergence of markets within and between the tributary states.
The expansion of trading and communication networks facilitated the growth of empires and vice versa. The emergence of agriculture, mining and manufacturing production of surpluses for trade gave conquerors an incentive to expand state control into distant areas. And the apparatus of the empire was itself often a boon to trade. The specialized trading states promoted the production of trade surpluses, bringing peoples into commerce over wide regions, and thus they helped to create the conditions for the emergence of larger empires.
Capitalist city-states and ports of trade
Sabloff and Rathje (1975) contend that the same settlement can oscillate back and forth between being a “port of trade” (neutral territory that is used for administered trade between different competing states and empires – see Polanyi et al 1957) and a “trading port” (an autonomous and sovereign polity that actively pursues policies that facilitate profitable trade). This latter corresponds to what Chase-Dunn and Hall (1997) mean by a semiperipheral capitalist city-state. Sabloff and Rathje also contend that a trading port is more likely to emerge during a period in which other states within the same region are weak, whereas a port of trade is more likely during a period in which there are large strong states.
The archaeological investigation of Cozumel carried out by Sabloff and Rathje was designed to try to test the hypothesis that Cozumel had been a trading state with a cosmopolitan and tolerant elite during the so-called Decadent period of the Mayan state system just before the arrival of the Spanish in the sixteenth century. If Sabloff and Rathje are right, trading ports (semiperipheral capitalist city-states) may more likely to be autonomous and to prosper during the fall part of the cycle of rise and fall when tributary states and empires are relatively weak.
Several analysts have contended that world-systems oscillate between periods in which they are more integrated by horizontal networks of exchange versus periods in which corporate and hierarchical organization is more predominant (Ekholm and Friedman 1982; Blanton et al 1996; White, Kejzar and Tambayong 2006). Arrighi (1994, 2006) contends that modern “systemic cycles of accumulation” display a somewhat similar alternation, with the Genoese-Portuguese network-based cycle followed by a more corporate Dutch organized cycle and that by a more network-based British cycle and then a more corporate U.S. cycle. These oscillations may be composed by the alternative successes and failures of tributary marcher states and capitalist city-states, but in the long run it was the capitalist city-states that transformed the state-based systems into the global capitalist system of today. The long-term trend toward commercialization and the integration of large regions into networks of market exchange may have made greater gains during periods in which tributary states were relatively weak. But Arrighi contends that the deepening of commodity production made gains under both network and corporate forms of hegemony.
So what does this have to do with upward sweeps of empires and upward sweeps of city sizes? Regarding upward sweeps of empires, if semiperipheral capitalist city states were major agents of the spread of commodified exchange and the expansion and intensification of trade, then upward sweeps in which larger states emerged to encompass regions that had already been unified by trade should have occurred after a period in which semiperipheral capitalist city-states had been flourishing.
Regarding upward sweeps of city sizes, these should have followed upward sweeps of empire sizes because it was empires that created the largest cities as their capitals. The settlements of semiperipheral capitalist city-states were typically smaller than the capital cities of empires. It was not until the rise of London that a capitalist city became the largest city in a world-system.
The question of the timing of upward sweeps to new levels is entirely germane to the problem of modeling global state formation. So also is the issue of how unusually large states have been formed in the past. Upward sweeps have mainly been instances of a semiperipheral marcher state conquering and unifying adjacent older core states and nearby peripheral areas. Conquest of adjacent territories has been the main mechanism of large-scale political integration in the past. But the pattern of hegemonic rise and fall in the modern world-system has been different. The most powerful states, the hegemons (the Dutch, the British and the United States), have fought semiperipheral challengers (e.g. Napoleonic France and Germany) to prevent the emergence of core-wide empires. We contend that this is because the modern hegemons are the most capitalist states in the system, the ones for whom economic success is most closely tied to the ability to make superprofits on the technological rents that return from new lead technologies.
Only during hegemonic decline have the modern capitalist hegemons shown a tendency toward “imperial overreach” in which their military power is employed in a last ditch effort to prop up a declining economic hegemony.[4] These efforts have not been successful, and a new hegemon only emerges after a period of hegemonic rivalry and world war. This is a primitive method of choosing “global leadership” that we can no longer afford to employ because of the existence of weapons of mass destruction. This is analogous to the succession problem within states. The further construction and strengthening of institutions that can peacefully resolve the struggle for hegemony is of the first importance for our very survival as a species.
Our approach is to model the main causes of state formation and upward sweeps taking into account the ways in which the basic processes have been altered by the emergence of new institutions. We elaborate and improve upon the recent work of Robert Bates Graber (2004). Graber develops both an ahistorical and an historical population pressure model of political integration. His ahistorical model is a very simplified version of the iteration model that includes population growth rates and the number of independent polities. Graber’s historical model takes account of the emergence of the League of Nations and the United Nations. But we will add the rise and fall cycle, the emergence of markets and capitalism, and the growth of other international political organizations and non-governmental organizations to our model of the evolution of global governance.
Measurement Issues:
The Population Sizes of Largest Settlements and the Territorial Sizes of Largest Polities
We use two features of human social organization that can be quantitatively estimated to study upward sweeps. Determining scale shifts requires real interval-level estimates, not just periodizations of growth and decline. The two quantitative features that we use are the population sizes of settlements and the territorial sizes of polities. These can be estimated over very long periods of time in several regions of the world. The populations sizes of settlements (cities) can be estimated even in the absence of any written documents based on the dating of the built-up area of the settlement. Of course such estimates contain a good deal of error because population densities within settlements can vary greatly (Pasciuti and Chase-Dunn 2003; Pasciuti 2003). But such estimates are probably good enough to see the scale changes that are the focus of this study. Most of the city population size estimates used in this paper are taken from George Modelski (2003).
The territorial sizes of polities cannot be estimated from archaeological evidence alone. What we want to know is the territorial size of the area over which a central power exercises a degree of control that allows for the appropriation of important resources. Control falls off with distance from the center in all states and empires, and controlling larger and larger territories requires the invention of new transportation, communications technologies and techniques of power (Mann 1986). Military technologies and bureaucracies are key, but so are new ideologies and new technologies for communication.
Estimating the territorial sizes of states and empires is done from historical atlases and for the ancient and classical words these are based primarily on knowledge about who conquered which city when, and whether or not tribute continued to be paid. Sometimes it is difficult to tell whether or not tribute is assymetrical or symetrical exchange. It is assymetrical exchange that signifies a tributary imperial relationship.
Most of the large ancient and classical empires involved conquest of territory that that was contiguous with the home territory. But once naval power was taken up by tributary states an empire could encompass a client state that was far from its contiguously controlled territory, such as Rome’s control of areas on the south shore of the Mediterranean and the relationship between China and Melakka. If these distant non-contiguous tribute-payers were small trading states, not including them in the estimate of the territorial size of empire does not constitute a large error. But with the coming of capitalism the thallasocratic form of empire – control over distant overseas territories – became the norm. The modern colonial empires require estimating the territorial sizes of colonies that are spread across the seas. The increasing institutionalization of state territorial boundaries makes this much easier than it was in the ancient worlds.
Not all maps in atlases show the boundaries of territorial control. They may represent linguistic groups or other cultural distinctions that have little to do with state power. And maps may not have good time resolution. Our data on the territorial sizes of polities are mostly taken from the published articles of Rein Taagepera (1978a, 1978b, 1979, 1997), except that some estimates for South Asia are added based on Schwartzberg (1992).
Ideally we would like to have a minimum temporal resolution of about every 50 years because we are trying to study middle-run growth/decline phases of polities and settlements. Archaeological evidence of the areal sizes of settlements can be used to estimate settlement sizes, but the limitation here is temporal resolution. Studies that rely on carbon 14 dating or related methods are not able to achieve a level of temporal resolution that can make the settlement growth/decline phases that we wish to study visible. They typically have an error margin of around 200 years. In some regions, such as the Southwest of the United States, finer temporal resolution of settlement sizes is possible based on the dating of settlement construction with dendrochronology (tree rings). Thus our examination of upward sweeps of settlement size can, in principle, be extended to regions in which there are no written records.[5] When temporal resolution is less than 100 years we suspect that we may be missing cycles of growth/deline phases.
The Areal Units of Analysis
We want to know the territorial size of the largest polity in a region and the population size of the largest city. This requires that we bound regions in some systematic way. We do this in two ways in this research. We use constant regions such as Mesopotamia, Egypt, Central Asia, East Asia and South Asia. But we also use the criterion of political-military interaction – the so-called PMN. This is a network of polities that are making war and allying with one another. This is the criterion we use to bound what we call the Central PMN,[6] which was born when the Mesopotamian and Egyptian state systems merge around 1500 BCE. That system continued to expand until it encompassed the whole globe in the 19th century CE. Each region was originally a separate PMN, and all these local systems were eventually incorporated into the Central PMN. In practice our areal cases are the constant regions listed above and the Central PMN, a network that expands as time passes. The question we ask is: how big is the largest city and the largest state in each region? So we are not really studying individual cities and states, but are rather studying the largest of these entities in each region, which is a temporally variable characteristic of the region.
Upward Sweeps
What follows is a set of fourteen figures that show our counts of urban and empire upward sweeps in five constant regions and in the Central PMN. The five regions are done in such a way so as to minimize double counting, except that we include Central Asia, a region from which three empires emerged that conquered territories in East Asia and the Central System and appear in those figures as well. We not only want to identify cases in which upward sweeps occur, but we want to count how many occur over time so that we can compare frequencies across regions. And we want to try to determine how many of the empire upsweeps were instances of semiperipheral marcher conquest.
Figure 4: Largest empires in Mesopotamia
Figure 4 shows two upsweeps between the earliest point at which we have estimates of the territorial sizes of polities (3200 BCE) and 1500 BCE when the Mesopotamian PMN merged with the Egyptian PMN. The units on the vertical axis are square megameters[7] of territorial size.
The Akkadian empire was huge, but brief. It might be termed a surge rather than and upward sweep, though the equilibrium size of polities revealed by subsequent peaks was significantly larger than the earlier high peak represented by Lagash. So the Akkadian empire should be designated as a combination of a surge and an upward sweep. The Babylon-Mitanni peaks are .25 and .30 so not quite a big enough change to qualify as an upward sweep. Thus we have two empire upsweeps in Mesopotamia during this period out of a total of 6 and ½ cycles.
Whereas Chase-Dunn and Hall (1996:85-89) first identified the Akkadian Empire as an instance of a semiperipheral marcher conquest (a recently formed state out on the edge of an old core region rolls up the system) we later came to understand that it was more likely to have been an internal ethnic revolt that was the spur to the upward sweep (Chase-Dunn et al 2006a).
Figure 5: Largest cities in Mesopotamia
Figure 5 shows the largest known cities in Mesopotamia from 3500 BCE to 1500 BCE when the Mesopotamian and Egyptian PMNs merged to become the Central PMN.[8] The units on the vertical axis are thousands of city residents. The Uruk upsweep was followed by a normal cycle in which Girsu attained the same size that Uruk had been, and then an upsweep to Ur, followed by a collapse and a partial recovery.[9] So there were two urban upsweeps and 4 cycles.
Figure 6: Largest states and empires in Egypt
Figure 6 shows the largest states and empires in Egypt from 3200 BCE to 1250 BCE, but we stop counting at 1500 BCE when the Mesopotamian and Egyptian PMNs merged into the Central PMN, which is depicted below. Figure 6 includes the years between 1500 BCE and 1250 BCE so that we can see what happened with the upsweep that had occurred just before 1500 BCE. There were three upsweeps out of five cycles in this region and period. The first upsweep in Figure 6 was probably not a semiperipheral marcher conquest, and neither was the third. The second was either a semiperipheral or a peripheral marcher conquest. Not much is known about the origins of the chariot-using Hyksos who invaded Egypt from the east except that their names were Semitic.
Figure 7: Egyptian Largest Cities
Figure 7 shows the sizes of the largest cities in Egypt from 2500 BCE to 1500 BCE. Obviously there had to be an earlier upward sweep that led to Memphis’s 30,000 population but we do not have estimates of the earlier settlement sizes and so we cannot figure out the timing of that upsweep. What we see here is a decline, then a recovery, and then upsweep that corresponds with the founding of the Hyksos capital, Avaris. So the count is one upsweep and 2 ½ cycles.
Figure 8: Largest Empires in the Early Central System
We divide the Central System, the expanding political-military networks into early and late periods so that the large-scale changes of recent centuries do not obscure the earlier cycles and upsweeps. Figure 8 shows the empire cycles and upsweeps from 1500 BCE to 390 CE. Again, the units on the vertical axis are square megameters of territorial size. There are four upsweeps, though Rome turns out to be a long-term recovery because the earlier Persian Empire was so large. But we will still call Rome an upsweep because, though it is part of the same political/military network, it is a substantially different part. The rise of Rome constituted a shift of the core of old West Asian/Eastern Mediterranean system toward the west, with a new center emerging on the Italian peninsula. There are 12 cycles visible in this network over this time period. All of these upsweeps except the first in Eqypt were the result of semiperipheral marcher conquests. The Neo-Assyrians radically changed the commercial strategy of the Old Assyrian City-State into a very successful semiperipheral marcher strategy. The Achaemenid Persians were originally pastoralist nomads from Iran who conquered the entire core region of West Asia and the some of the Eastern Mediterranean [from Bactria (Afghanistan) to Egypt]. Alexander was from Macedonia. And the Romans were Latin hill-billies living in the shadow of Etruscan cities.[10]
Figure 9: Early Central System Largest Cities
Figure 9 shows the sizes of the largest cities in the early Central PMN from 1500 BCE to 300 CE. There are three city size upsweeps and really only three visible cycles.
Figure 10: Largest Empires in the Late Central PMN
Figure 10 shows the largest empires in the late Central PMN from the birth of Christ until 1991 CE when Taagepera’s estimates end. We already counted the Roman upsweep in Figure 9. So there are four upsweeps shown here that have not already been counted. And we wont count Rome as a cycle either. So there are fourteen cycles. We may be seeing more cycles because the temporal resolution is now much better. We include the Mongol Empire even though it emerged in Central Asia, more on the edge of the East Asian PMN than on the edge of the Central PMN. Central Asia played an important role in the development of connections between east and west both because of the Silk Roads trade routes and because Central Asian steppe nomads repeatedly formed huge military confederacies that attacked and sometimes conquered the agrarian civilizations of both the east and the west.
All the upsweeps in Figure 10 were the accomplishments of either semiperipheral or peripheral marcher states, or in the case of the British Empire, a modern semiperipheral capitalist nation-state rising to hegemony.[11] A peripheral marcher state is usually one in which in nomadic peoples from adjacent regions invade an agrarian region and quickly put together a territorial empire that encompasses most of the old core region. A semiperipheral marcher state is one in which peripheral people settle on the edge of an old core region, go through state formation and class formation, and then conquer the older core states.
Figure 11: Largest Cities in the Late Central PMN
Figure 11 shows the sizes of the largest cities in the Central PMN from 600 BCE to 1900 CE. We already counted the Babylonian and Roman upsweeps in Figure 9. Perhaps Baghdad should not be termed an upward sweep. In 1000 CE it had a population of around 1,200,000 people, about the same number that Rome had had in 200 CE, 800 years earlier. We called Rome an upward sweep because it was in a region within the Central PMN that had never had such a large city before. Islamic Baghdad grew up in the old heartland of cities on the Mesopotamian flood plain, but it was far larger than any city in that area had been before. For this reason we are willing to include the rise of Baghdad in our count of city upsweeps. Thus Figure 11 contains two upsweeps and 4 ½ cycles that have not been previously counted.
The
meteoric rise of London was followed by another meteoric rise, that of New York. We do not include the 20th century in Figure 10 because the scale of New York makes it very hard to see what was happening at the earlier end of this sequence.
Logging the city populations is one solution, but that makes it difficult to
see which rises were really upsweeps.
Figure 12: Largest Empires in the East Asian Region
Figure 12 shows the territorial sizes in square megameters of the largest states and empires in East Asia from 1900 BCE to 206 BCE with the sequential upsweep carried out by Chu, Qin and Western Han. There are two upsweeps in this period and 3 ½ cycles. Both of the upsweeps involved the actions of semiperipheral marcher states who roled up the regional system of states.
Figure 13: Territorial sizes of largest states and empires in East Asia
Figure 13 shows the sizes of the largest states and empires in East Asia from 1900 BCE to 1949 CE, so the part to the left side of the verticle line overlaps with Figure 12. We see that the second upsweep that started in Figure 12 was carried further by the Hsiung-Nu, a steppe nomad conqueror state that many believe was composed of the same people who were known as the Huns in the West. Using the same logic as before we will not label the impressive rise of the Turks, a rather different group from Central Asia, an upsweep because it occurred in nearly the same territory as that put together by the Hsiung-nu and was not as large. So we call that a recovery. The number of true upsweeps in East Asia in this period was four and there were 20 ½ cycles (three visible in the early part of Figure 11).
All these, including the recovery, involved semiperipheral or peripheral marcher states. The Hsiung-nu were classic horse pastoralist nomads who came out of Central Asia, very similar to the later Mongols. The Turks were also from Central Asia but they were different. They were originally hill people who specialized in mining and metallurgy. They became an important ethnicity in the Central Asian oasis states, and then led several expansive conquests toward both the east and the west. (Chase-Dunn et al 2006b).
Figure 14: Largest cities in East Asia
Figure 14 shows the largest East Asian cities from 1000 BCE to 1900 CE. The first little hump is not called an upsweep because the population of Haoqing increased from 100,000 to 125,000, not enough to be called an upsweep. So we see three upsweeps and 5 ½ cycles.
Figure 15: Largest states and empires in South Asia
Figure 15 shows the largest states and empires in South Asia from 420 BCE to 1790 CE, but not including the modern European colonies in South Asia (e.g. the British Empire). Of course the Indus River valley had contained an immense Bronze Age civilization with large cities and polities of an undetermined size. Obviously this was an earlier South Asian upward sweep, but we do not have quantifiable estimates of the settlement and polity sizes.
We extended Taagepera’s estimates back from 620 CE to 420 BCE by estimating the territorial sizes of states using maps in Schwartzberg (1992).[12] Figure 15 shows only two upsweeps. The Delhi Empire in the middle is deemed a recovery because it was centered in the Ganges River Valley, which had also been the center of the prior Mauryan Empire, and it was not as large as the Mauryan. There are 8 cycles visible in Figure 15. The South Asian sequence is rather unlike other regions because of the long period of political decentralization following the Mauryan. This long trough in the sequence of rise and fall is the main reason why South Asia is out of synchrony with the periodicity of both Eastern and Western empire cycles (Chase-Dunn, Manning and Hall 2000).
The Mauryan Empire was not itself a semiperipheral marcher state, but it was made possible by the invasion of South Asia by Alexander’s armies. The Mauryans basically reconquered South Asia and held it when the Seleucids tried to get it back. Delhi was another Ganges River valley state that eventually managed to put a large polity back together after a long period of political decentralization. Neither should the Mogul Empire be considered a semiperipheral marcher state. The Moguls were Central Asian Moslems who were descended from Ghenghis Khan and Tamerlane and who brought Persian culture to South Asia when they conquered it. This could qualify as a semiperipheral marcher conquest. If so it is the only one for which we have quantitative data in South Asia. That said, the Mauryan Empire was a nativist reconquest in response to a semiperipheral marcher invasion from a neighboring PMN. Once the Greek-led armies were expelled the South Asian and Central PMNs remained disconnected in terms of warfare and alliance until the arrival of Turkic armies in the 13th century CE.
Figure 16: South Asian Largest Cities
Figure 16 shows the sizes of the largest cities in South Asia from 500 BCE to 1850 CE. Pataliputra was the capital of the Mauryan Empire. Then a long period of smaller cities follows that corresponds with the political decentralization seen in Figure 15. Vijayanagar was the capital of a South Indian empire. In Figure 16 we see three upsweeps and 6 ½ cycles.
Figure17: Largest Central Asian Empires
Figure 17 shows the territorial sizes of the largest empires that began in Central Asia, not to be confused with the Central PMN shown in Figures 8-11 above. The time period covered is from 230 BCE to 1550 CE when the Muscovite Empire conquered the area. Central Asia played a special role in human socio-cultural evolution in the Old World, as mentioned above (see also Chase-Dunn et al 2006). Central Asia was a peripheral region of both East and West and a link between them, and some of the empires in Figure 17 have already appeared in earlier Figures, but it is still interesting to look at those empires that emerged from the Central Asia region with regard to the issue of upsweeps and cycles. Figure 17 shows two upsweeps, a recovery, and 12 cycles.
|
Region or PMN |
Time period |
# of upsweeps |
Av. Years per upsweep |
# of cycles |
Av. Years per cycle |
|
Mesopotamia |
-3500/-1500 |
2 |
1000 |
4 |
500 |
|
Egypt |
-2500/-1500 |
1 |
1000 |
2.5 |
400 |
|
Central PMN |
-1500/2000 |
5 |
700 |
7.5 |
467 |
|
East Asia (PMN) |
-1000/1900 |
3 |
967 |
5.5 |
527 |
|
South Asia |
-500/1850 |
3 |
783 |
6.5 |
362 |
|
Table average |
|
|
865 |
|
451 |
Table 1: City size upsweeps (population sizes of largest cities)
Table 1 shows the summary statistics for urban upward sweeps and the number of cycles for each of the regions that we studied in the figures above. The average number of years per upsweep varied from 700 for the Central PMN to 1000 for the Mesopotamian and Egyptian regions. This may have been partly a function of the poorer temporal resolution of city sizes in the earlier periods. The rate of upsweeps varied across regions, but less so than in the empire upsweeps shown in Table 2. The average years per cycle across all the regions was 451, and this varied from 362 for South Asia to a high of 527 for East Asia. This is good news for the issue of the necessary temporal resolution of quantitative estimates.
|
Region or PMN |
Time period |
# of upsweeps (semip or per devel) |
Av. Years per upsweep |
# of cycles |
Av. Years per cycle |
|
Mesopotamia |
-3200/-1450 |
2 (0) |
875 |
6.5 |
269 |
|
Egypt |
-3200/-1500 |
3 (1) |
567 |
5 |
340 |
|
Central PMN |
-1500/2000 |
8 (7) |
437 |
26 |
135 |
|
East Asia (PMN) |
-1000/1790 |
4 (4) |
750 |
20.5 |
146 |
|
South Asia |
-420/1800 |
3 (1) |
670 |
8 |
251 |
|
Central Asia |
-230/1550 |
2 (2) |
1105 |
12 |
167 |
|
Table average |
|
|
734 |
|
218 |
Table 2: Empires size upsweeps (territorial sizes of largest empires)
Table 2 shows the summary statistics for the empire upward sweeps and the number of rise and fall cycles for each region. The average years per upsweep across all the 6 regions was 734, a bit less than for the city upsweeps in Table 1, and the variation is from 437 for the Central PMN to a high of 1105 for Central Asia. The average number of cycles per year across these six regions was 218, with a low of 135 for the Central PMN and a high of 340 for Egypt. The relatively high years per cycle for Egypt and Mesopotamia is similar to that found for the cities in Table 1, but this time it is unlikely to be an artifact of poor temporal resolution because Taagepera’s method of reporting changes in empire sizes produces better temporal resolution than we have for cities.
The average number of years per upsweep is similar for cities and empires (865 for cities, 734 for empires), but the average number of years per cycle is twice as long for the cities as for the empires (451/218). Empire cycles are shorter than city cycles and empire upsweeps are slightly more frequent than city upsweeps.
Regarding the hypothesis that upsweeps are mainly carried out by semiperipheral or peripheral marcher states, the results are mixed. Consistent with David Wilkinson’s (1991) earlier survey, we found that some upward sweeps were carried out by older core powers or were the result of internal rebellions that established a new regime and then went on to empire. Out of 22 total upsweeps 14 of them were a direct consequence of semiperipheral or peripheral marcher states and one was a semiperipheral nation-state that rose to hegemony in the modern world-system. That is about seven out of ten. The semiperipheral development phenomenon seems to be more prevalent in East Asia and the Central PMN (and in Central Asia) than in the other regions.
Our results need to be examined more closely in order to test some of the hypotheses discussed in the theoretical section above. Although earlier investigations have examined the relations between urban and empire growth/decline phases (e.g. Chase-Dunn et al 2005) we have not done this with a specific focus on upward sweeps. Do city upward sweeps tend to follow rather than precede empire upward sweeps, as we would expect based on the notion that it is large empires that construct large capital cities? Our efforts to find explanations for city and empire upsweeps or things like the long trough of decentralization in South Asia in the writings of historians has not born fruit. Most historians are unaware of the quantitative changes we are discussing or do not see them in a comparative context. Our next step is to produce dynamic mathematical models based on the interation model depicted in Figure 3 and to use our comparative study of upsweeps to evaluate different specifications of the models.
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