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
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 (https://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 https://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.
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.
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:
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.