Modeling Globalization in the Biogeosphere

Christopher Chase-Dunn and Robert Hanneman,

Sociology, University of California-Riverside

Bai-lian Li, Botany and Plant Sciences, University of California-Riverside

(v. 11-10-04)[2708 words]

http://irow.ucr.edu/research/biocomp/compendium.htm

Compendium:

Data Development,Measurement Strategies and Units of Analysis

 

This project will develop a World Historical Geographical Information System using a standardized global grid for the regions and time periods we are studying. We will establish an Internet Collaboratory web site for the use of our research project. This will enable us to share access to the joint products of our research and to update modeling and data enhancements easily. The large temporal and spatial scope of our project is necessary for capturing the dynamics of long-run globalization and for determining changes over time in the genesis of complexity. It will not be feasible to acquire complete data for this huge expanse of time and space given the resource constraints on our project. Rather we will focus primarily on model building, but this will be enhanced by a strategic improvement of existing datasets. 

The project will develop programs to directly to link the spatio-temporal database with our simulation models and statistical analyses, and to move modeling results back into the spatio-temporal format for visualization of modeling results. We will eventually produce a database that is in an interoperable format to be linked with digital gazetteers and libraries such as the Alexandria Digital Library and the Electronic Cultural Atlas Initiative.

The basic strategy is to use statistical analyses of urban growth and changes in the territorial size of empires over the last three thousand years to parameterize our models. This will involve utilizing and extending two compilations of data: Chandler's (1987) Four Thousand Years of Urban Growth and Taagepera's (1978a; 1978b; 1979; 1986; 1997) studies of the territorial sizes of empires.

 

 City Populations and Locations

     Tertius Chandler's (1987) compendium contains population estimates for the largest cities on Earth since the beginnings of urbanization in Mesopotamia. Chandler's data set is a valuable resource based on decades of research at the library of the University of California at Berkeley. For our purposes, however, it needs to be upgraded using more recently published studies than Chandler used and extended to cover more frequent time points and better coverage of South Asian cities. The time points used by Chandler are too far apart before 900 BP (e.g. 3200 BP, 2650 BP, 2430 BP, 2200 BP, etc.). We propose to upgrade and extend Chandler's data set by:

Extending the data set to include more South Asian cities and assembling data on East, Central and West Asian/Mediterranean cities for more frequent temporal estimates, and

Adding new estimations based on recent studies that have come out since Chandler completed his published data set.

             We will do library and web searches for all the literature that was not available to Chandler for his 1984 compilation. This will involve thorough investigation of the resources accessible at the home universities at which our collaborators are located and easily accessible other libraries and interlibrary loan programs. We will also have access to documentary and archaeological evidence on the sizes of East Asian cities obtainable by our collaborator Dr. Wang Jun at the Beijing Institute of GIS and Cartography. For the city sizes project the newly published six volume History of Chinese Population will be a helpful source. As a final step we will send either a Graduate Research Assistant or a Project Post-Doctoral Research Assistant to the Library of Congress in Washington DC to acquire data not already obtained.  In addition to library research our project will develop a specialized search engine for the Internet to examine digital databases such as JSTOR for information about city and empire sizes. And of course we will make full use of existing comprehensive online spatial and spatio-temporal data resources such as the Alexandria Digital Library and the Electronic Cultural Atlas Initiative.  A fuller consideration of methods for estimating the population sizes of preindusrial cities is presented in Pasciuti and Chase-Dunn (http://irows.ucr.edu/research/citemp/estcit/estcit.htm).

Territorial Sizes of States and Empires

      The second data set we will upgrade is the territorial sizes of states and empires compiled by Rein Taagepera (1978a; 1978b; 1979; 1986, 1997). Taagepera used maps from atlases to estimate the territorial sizes of empires over the past four millennia. His data set has unfortunate gaps because he was only concerned with the very largest empires on Earth. Thus he excluded important regional empires that are needed when we are using PMNs as the unit of analysis and for the purposes of constructing size distributions of empires to measure power concentration/dispersion within regions.

      Estimating the territorial sizes of empires is also problematic. Taagepera used atlases and maps to produce his estimates of the spatial sizes of empires from 3000 BCE to the present. But the boundaries of empires are not usually formally specified, but are rather a matter of degrees of control that fall off with distance from the central region. Archaeological evidence of the presence of a core culture in a peripheral region does not prove the existence of control, because many core polities have established colonial enclaves in distant peripheries to facilitate trade (e.g. Stein 1999). So the estimation of empire sizes is also fraught with difficulties. But, as with city sizes, a significant improvement of accuracy, temporal resolution and coverage would result from a renewed effort to code empire sizes using recently published materials.

      Taagepera's data on the territorial sizes of empires will be upgraded by using more recent sources than those that were available when he compiled his data set. And coverage will be extended to empires that Taagepera excluded because they were not among the largest on Earth at a particular period in time.  Our spatiotemporal database will also include information about the spatial location of empire boundaries. These data will be useful for time mapping and for examining the relationships between city locations and empire boundaries. The spatially fuzzy boundaries of empires will be an important opportunity for our effort to represent and analyze uncertainty.

      Dating is also a major problem in studying the temporal dimension of empires in the ancient world-systems. In this project we utilize the years originally supplied by Taagepera and Chandler. But the dating of conquest events and city size estimations for the years before the first millennium is a matter of continuing disputes among scholars of ancient history. For ancient Western Asia the Egyptian dates are used, but these have been repeatedly revised with an error margin of around 25 years. This is a threat to any study of temporal correlations.

      Dr. Wang Jun of the Chinese Academy of Surveying and Mapping will also assist us with the upgrading of territorial size and the location of boundaries of states in East Asia. This effort will make full use of the eight-volume Chinese Historical Atlas compiled by Professor Tan Qixiang of Fudan University, which is currently being digitized by the China Historic GIS Project team at Fudan and Harvard Universities.

 

Power Configurations of Interstate Systems

      David Wilkinson has coded the power configurations of interstate systems for some of the regions we are studying. The configurations he uses are: universal state (one superpower, no great powers, no more than two local powers); hegemony (either one superpower, no great powers, three or more local powers; or no superpowers, one great power, no more than one local power); unipolar (all other configurations with one superpower); bipolar (two great powers); tripolar (three great powers);  multipolar (more than three great powers); nonpolar (no great powers). Wilkinson will join our project as a subcontractor to code power configurations for the times and regions we are studying and to assist with endogenous and exogenous modeling of system dynamics for the polarity variable. For recent centuries more quantitative estimates of power configurations are available (e.g. Modelski and Thompson 1988, 1994).

 

Climate Change

      An important component of our project is incorporation of the spatial patterns and time histories of climate change in our targeted study regions throughout the Late Holocene.  We plan to utilize proxy data from a number of existing databases to reconstruct gridded networks of paleoclimate conditions from distinct time slices.  These reconstructed paleoclimate time slices will allow for examination of the impacts and effects of climatic variation on the evolution of societies--such as the governing influences of drought frequencies and the pervasiveness and mechanisms of “abrupt” change.  Our aim is to examine the interactions between regional elements (including temperature and precipitation variability, flood and drought “events”, monsoon dynamics) human related events (agricultural practices, economics, social conditions) and urban growth and empire size. For example, geochemical findings from lake sediment cores dated at 1200-1100 BP from in the Yucatan Peninsula, Mexico support a rather strong correlation between times of drought and major cultural discontinuities in classic Mayan civilization (Hodell et al. 1997).  

      Many useful paleoclimate databases currently exist and can be utilized to help characterize the nature of paleoenvironmental change.  We plan to collate data from the European Pollen database; the International Tree Ring Data Bank (ITRDB); Lake-Level Databases, the Ice Core Data Bank, the European Climate History database and other pertinent datasets all maintained by the NOAA Paleoclimatology Program and the World Data Center for Paleoclimatology.  We will also gather historical documentary evidence on weather, rainfall, temperature, storm frequency and intensity from weather diaries and other historical documentation (e.g. Pfister et al. 1994, Wang and Wang 1994; Pfister, 1992).  Documentary evidence on the frequency and location of devastating floods or droughts may indeed be helpful, but it will be desirable to locate less subjective indicators [such as the Nile flood height measurements – Quinn (1992)] whenever possible. Our Chinese colleague, Dr. Wang Jun, will be an essential component of this data collection, being familiar with the local literature and data sources. In particular, we will select data sets with the temporal resolution necessary to assess relationships between social and geophysical variables, i.e. to assess the rates and magnitudes of climate variability on human timescales.  Finally, another valued data source is paleoclimate model output (e.g. those available from the Paleoclimate Modeling Intercomparison Project from the World Data Center for Paleoclimatology) that we will use to corroborate our climate reconstructions.  A preliminary bibliography on climate change in the period and regions we are studying is at http://irows.ucr.edu/research/citemp/clichange/clichangetoc.htm

      Our proposed time mapping approach, by utilizing regional datasets from a wide variety of existing databases, will incorporate significant local climate variability where relevant, while avoiding the danger of relying on data from only a few sites or from sites that are distant from the regions of interest.  Finally, once we have characterized the surface and climatic conditions for particular times slices, we will be able to successfully examine possible causal interactions between urbanization, empire formation and climate change throughout Eurasia.

 

Wars

      Warfare is a human interaction variable that is known to affect both urban growth and the territorial size of empires. The hypothesis about processes of steppe empire formation and the migration of pastoral nomads out of Central Asia being the key to simultaneous rise and fall of agrarian empires at both ends of the Eurasian land mass could be supported if we find simultaneous increases and decreases in warfare between steppe nomads and agrarian states of Afroeurasia.  Claudio Cioffi’s LORANOW project (Cioffi-Revilla 1991; 1994) has already coded warfare for several of the regions we are studying.  See http://vdc.hmdc.harvard.edu/VDC/index.jsp

Trade

      Ideally we would like to have comparable and reliable data on cross-Eurasian trade by both the Silk Road and maritime routes over the whole period that we are studying. In practice trade data are quite piecemeal. Nevertheless we will be able to obtain enough data to make estimates of changes over time in the amount of trade flowing over the different routes linking China, India and the Near East.  Price data are also useful. Frank and Gills (1995) have recently argued the importance of the balance of payments in influencing the growth and decline of states and regions and as an indicator of core vs. peripheral status.  As demonstrated by Braudel (1979), simultaneous and corresponding changes in prices over time in different localities are themselves an important indicator of systemness.  Yearly price data from East Asia and the West Asia/Mediterranean will enable us to examine the synchronicity hypothesis on a finer time scale than the city population and empire size data. This will also be helpful in evaluating the relationship between economic activities and climate change.

 

Migrations and Incursions

      Migrations and incursions were important aspects of East/West connections because Eastern conflict pushed Central Asia steppe nomads west all the way to Eastern Europe and Rome (Teggart 1939; McNeill 1964). We will code migrations and incursions from documentary evidence, though only rough indicators of the numbers of migrants or the size of incursions will be possible for the earlier time periods we are studying.

 

Measures

      A general problem with long-term data series is that earlier cruder indicators need to be spliced with later, more accurate indicators. These splices must be accomplished carefully so as not to introduce additional measurement errors.      

      The basic data on empire and city sizes will be used to produce four different measures for each of our regions. With the city data we will construct three measures of different aspects of change in city systems. The first measure will be the estimated population size of the largest city.  The second measure will examine the shape of the city size distribution -- the relative sizes of the five largest cities. For this we will use the Standardized Primacy Index (SPI) developed by Pamela Walters (1985).  City systems vary with regard to the steepness or flatness of the city size hierarchy. A very flat city size distribution is one in which the largest cities are all about the same size. A steep city size distribution corresponds to what is referred to in the settlement system literature as "urban primacy." This means that the largest city is much larger than the other cities in the system. The SPI compares the actual distribution of city population sizes with a hypothetical rank-size hierarchy in which the largest city is twice the size of the second largest; the third largest is one third the size of the largest, and so forth. Deviations toward flatness from the rank-size norm are assigned negative scores, while deviations toward steepness are assigned positive values that increase with the steepness of the city size distribution. 

        Two measures will be computed using the territorial sizes of empires. The simplest is the size of the largest empire in each region. We will also compute a size distribution of empires using our territorial size data on the three largest polities. We will use the SPI to compute this measure. This will provide an additional indicator of the relative degree of centralization of power in regional state systems.

 

Units of Analysis

Our Spatio-temporal Information System database will code the locations of events, settlements, polity boundaries, wars, epidemics and climate change indicators. We will use three different approaches to the problem of units of comparison for our statistical analyses:

  1. single states;
  2. political/military networks (which change their sizes over time because of expansion),
  3. and constant regions (East Asia; South Asia, Central Asia; West Asia/Mediterranean; and (after 500 BP) North and South America..

Using both political/military networks (2) and constant regions (3) will allow us to crosscheck our results to see if our way of bounding “cases” affects inferences about causal relations.

 

Ideally we would like to have decennial data estimates for city population sizes but realistically we may need to settle for estimates every twenty-five years. The temporal resolution we are able to achieve will be an outcome of our research, as we will code information relevant for estimating city sizes for the closest year. Converting different dating schemes to a single temporal dimension is a complicated problem that is under constant revision by historians. E.g. Hittite dates are translated into Egyptian dates in several competing ways. We will use the most recent consensus by expert historians for particular regions, and will employ techniques for displaying degrees of uncertainty (fuzzy boundaries) in our database and graphic presentations.

Though Tertius Chandler died in May 2000 we were able to obtain his corrections to his 1987 manuscript from his literary executor, Fred Foldvary.