Emergence and Collapse of Early Villages : Models of Central Mesa Verde Archaeology
Ancestral Pueblo farmers encountered the deep, well watered, and productive soils of the central Mesa Verde region of Southwest Colorado around A.D. 600, and within two centuries built some of the largest villages known up to that time in the U.S. Southwest. But one hundred years later, those villages were empty, and most people had gone. This cycle repeated itself from the mid-A.D. 1000s until 1280, when Puebloan farmers permanently abandoned the entire northern Southwest. Taking an interdisciplinary approach, this book examines how climate change, population size, interpersonal conflict, resource depression, and changing social organization contribute to explaining these dramatic shifts. Comparing the simulations from agent-based models with the precisely dated archaeological record from this area, this text will interest archaeologists working in the Southwest and in Neolithic societies around the world as well as anyone applying modeling techniques to understanding how human societies shape, and are shaped by the environments we inhabit.
There are no customer reviews available at this time. Would you like to write a review?
University of California Press
March 10, 2012
Number of Print Pages*
Adobe DRM EPUB
* Number of eBook pages may differ. Click here for more information.
Excerpt from Emergence and Collapse of Early Villages by Timothy A. Kohler
Two hundred and forty years after the last Pueblo people had left Colorado, Hernen Cortes de Monroy y Pizarro-or maybe it was Quetzalcoatl-stepped onto the shores of Veracruz. Arriving at the Aztec capital of Tenochtitlan less than seven months later, the Spanish had no trouble recognizing kings and slaves, temples and markets, gods and warriors, and all manners of artifacts and other institutions, none of which existed when the ancestors of these two societies last lived together in Eurasia. What accounts for the surprising mutual intelligibility of social forms between two societies who shared their last common biological and cultural ancestors tens of thousands of years agoe Undoubtedly the shared biology (proximate by the standards of biological evolution) and perhaps the shared culture (which however was very distant, by that more rapidly changing standard) had some effect in channeling development in certain directions rather than others. But another possibility that needs to be considered is that winnowing of less-efficient forms by selection through competition among groups may have shaped these otherwise independent historical trajectories. Some solutions to the puzzle of how to induce people to cooperate with large numbers of other unrelated people probably work better than others, and if invented independently, might be maintained. This logic helps us understand, for example, why markets appeared alongside older reciprocal exchange systems as Pueblo peoples began to concentrate in the northern Rio Grande region of New Mexico in the A.D. 1300s (Kohler, Van Pelt, and Yap 2000). Markedly less-workable solutions tend to be supplanted, whether through lethal intergroup competition, non-lethal cultural group selection, selective migration, or related processes (see review in Salomonsson 2010). But such arguments are only plausible if we can show that adaptation, a concept we are borrowing from biology, has some relevance for understanding cultural behavior. This might seem a modest claim-we are not for example proposing that natural selection is a "universal acid" explaining all aspects of culture and its contents, as Dennett (1995) sometimes seems to do. But as we shall see, even this modest claim would be dismissed by some. Societies are likewise in constant interaction with the environments they inhabit. They modify those environments by accident and on purpose, affecting their short- and long-term productivity. How could it not be the case that this also affects the success of the societiese One common characteristic of Neolithic societies is the rapid population growth they experience. If per capita use of resources remains constant as population grows, resources that regenerate slowly will be drawn down. This may soon require societies to move to previously uninhabited areas if they are available-but eventually, this option will be impossible and new patterns of resource usage must be developed. Societies unable to innovate these patterns will be displaced by those which could. The general growth of Neolithic populations also favors those groups who can effectively coordinate the largest numbers of people, since large cohesive groups can displace smaller or less cohesive groups, or resist displacement by others. These two pressures-building larger sedentary groups without depleting the environment-are at odds with each other. This contributes to the dynamic character of the Neolithic record in most areas; in finding an effective compromise between these two opposing forces societies are driven to a position on a metaphorical fitness landscape where they become extremely vulnerable to external perturbations such as climate change. Eventually we would like to examine how these processes play out in Neolithic societies all over the world. (We suspect that they are completely general!) Unfortunately, there are few places where the Neolithic sequences are well-enough known to make this possible in any convincing detail. In this volume we analyze these social and "socionatural" processes through an extended case study set in southwestern Colorado between A.D. 600 and 1300. This is a fascinating 700 years that takes us, in the first 200 years, from the arrival of small groups of maize farmers into an almost uninhabited mesa and canyon country, to the emergence of some of the Southwest's earliest and largest villages. But around a hundred years later, by A.D. 900, most of the villages in our study area disband and their inhabitants depart for the south or west. The remaining households once again lived mostly in small hamlets until about A.D. 1080 when a new wave of colonists arrived from the south bringing a differently organized village lifeway backed by a novel, powerful political and religious system that united most of the eastern Southwest. Within 200 years this wave, too, receded, again to the south, leaving behind the famous ruins of Mesa Verde National Park and the less-well-known, but more populous district that includes Canyons of the Ancients National Monument, where our work centers (Plate 1.1). Even before the project we report here began in 2001, archaeologists knew more about the development of societies in this area than we did for almost any other comparable Neolithic society anywhere in the world. For that we thank generations of researchers, recently including Hayes (1964), Kane (1986), Lipe et al. (1999), Rohn (1977), Varien (1999a), and Varien and Wilshusen (2002), among many others. Why, then, another volumee The answer lies in an exciting opportunity that the National Science Foundation (NSF) presented in 2001 for a "Biocomplexity in the Environment Special Competition" in "coupled natural and human systems." NSF recognized that understanding how humans interacted with ecosystems over long periods of time required both deep interdisciplinary collaboration and modeling. They also saw that such research was not being generated by their existing programs. When the authors of this chapter saw this call for proposals, we recognized it as providing precisely the sort of research program we had been trying to put together. We also saw that we needed help to carry out the kind and scope of research that NSF was requesting, and we assembled a team to create a research proposal that came to be known as the "Village Ecodynamics Project" or VEP. Fortunately we weren't starting from a blank slate. Kohler, an external professor at the Santa Fe Institute, had recently hosted a conference there on agent-based modeling (Kohler and Gumerman, editors, 2000) where Bob Reynolds presented a paper on his research with Joyce Marcus and Kent Flannery on the role of conflict in the prehispanic emergence of chiefdoms and states in the Valley of Oaxaca (Reynolds 2000). Bob is nearly unique among computer scientists in having a long history of collaboration with archaeologists-complexity pioneer John Holland and archaeologist Flannery had co-chaired Bob's dissertation committee at the University of Michigan. By then a computer scientist at Wayne State University, Bob agreed to join our team as a principal investigator on the proposal, and among the many assets he brought to the collaboration was Ziad Kobti, then Bob's Ph.D. student. Ziad reports on VEP efforts to model local exchange among households in our simulations in chapter 13. Given NSF's charge to understand how societies were shaped by their changing environments, and how those societies in turned altered their environments, we also needed a partner who could bring a broad understanding of humans in their landscapes. A second acquaintance from an SFI workshop, hydrologist Ken Kolm, agreed to take a leading role in this research to help us understand the interactions through time between people and water, which we thought would be especially important to model on this semi-arid landscape. Ken, then of the Colorado School of Mines, brought along his Ph.D. student, Schaun Smith. In late 2001 this team drafted a successful proposal to fund what we came to call the "VEP I" (NSF BCS-0119981). Kohler also brought a group of graduate students at Washington State University (WSU) to the team, and Varien involved the staff at the Crow Canyon Archaeological Center, especially Scott Ortman, who assembled the database of archaeological sites discussed in chapters 2 and 14.
We have been at it ever since! As we write this in 2011, our research is now supported by a grant program at NSF called "Dynamics of Coupled Natural and Human Systems" that grew out of the special competition that funded the first phase of the VEP. VEP II is organically connected to the project reported in this volume by continuity of many personnel and most research interests to our work during the initial phase of the VEP reported in this volume. Many students from the first team however now work for a living: Fumi Arakawa is embarking on an assistant professorship at New Mexico State University; Sarah Cole is President of Red River Archaeology in Dallas; Jason Cowan works as an archaeologist for CRC in Washington state; Donna Glowacki is an assistant professor of anthropology at the University of Notre Dame; Dave Johnson is now an archaeologist and tribal liaison for the Bureau of Land Management in Arcata, California; Scott Ortman holds a dual position as the Lightfoot Fellow at Crow Canyon and the Omidyar Fellow at the Santa Fe Institute; Schaun Smith is now a staff scientist in the Environmental Unit of Chevron Energy Technology Company in Houston; and Ziad Kobti is an associate professor of computer science at the University of Windsor.
Over the years we have seen the stream of research undertaken in 2001 lead to some fundamentally new ways of thinking about and seeing the past. Part of this is due to the interdisciplinary nature of our research, part is due to modeling the past using computer simulation, and part is due to amassing synthetic databases on all known archaeological sites in our study area. Together these allow us to develop "model-based approaches" (Kohler and van der Leeuw 2007) to generate and test expectations about what the past might have looked like if certain processes were dominant. For the VEP, it was a case of being in the right place at the right time. There are few areas in the world where the past environment can be reconstructed in such detail and linked so precisely to ancient subsistence practices; this reconstruction of ancient environments and subsistence practices was a fundamental aspect of the computer simulation. Further, there are few places where we could assemble so much previous archaeological research and analyze it in productive ways, though we had to develop new approaches to make that possible (Ortman et al. 2007). As a result, the VEP can use the computer simulation to generate models and evaluate them through quantitative comparisons to the archaeological data.