Peter M. Yaworsky portrait
  • Graduate Research Assistant, Anthropology Department
801-581-6927

Research Summary

My research uses insights from evolutionary ecology to explore the variation in both past and present human behavior. I am particularly interested in understanding the decisions people make regarding spatial distributions on regional scales. My current research focuses on the distribution of archaeological sites in the Grand Staircase-Escalante National Monument, Utah and the site placement of early agriculturalists in Nine Mile Canyon, Utah as a function of risk mitigation.

Education

  • B.S., Anthropology, University of Utah
  • M.S., Anthropology, University of Utah

Biography

Originally from Georgia, I came to the University of Utah for college and completed both my B.S. and M.S. I have experience leading cultural resource management projects in Utah, Nevada, and California. I am currently enrolled as a Ph.D. student at the University of Utah.

Current Work

Risk Mitigation in a Changing Environment: A Subsistence Farmer Perspective

Risk, or variation in outcomes, is an inherent part of the human condition and can result in the adoption of complex behavioral patterns that seemingly contradict expectations of human rationality. Thus, considering how risk constrans or encourages decisions is necessary to understand complex patterns of behavioral adaptation. However, to date there are no broadly applicable formal models of risk from which researchers can derive testable hypotheses and predictions. To overcome this limitation we develop a formal model of risk by integrating components of behavioral ecology and utility theory. Using this formal model, we then derive predictions to explain the diverse food storage strategies undertaken by Formative Period (2100-400 BP) agriculturalists on the West Tavaputs Plateau in central Utah, known as the Fremont.

Figure: Deviations from profit-maximizing behavior is a result of the non-linear relationship between profit (returns) and utility. When an individual is below the inflection point (cross) of the sigmoid (blue), subsequent increases in return result in a greater increase in profit when compared to an individual to the right of the inflection point, who experiences marginal gains in profit. As you approach the inflection point of the line, the relationship of returns and profit become more linear, and at the inflection point, the individual is expected to be profit maximizing independent of the variation. 

The Fremont employed an expensive strategy of storing agricultural products in constructed features high on the canyon walls, often placed in difficult and dangerous to access locations. A simpler and more efficient strategy is to store agricultural products centrally, either at the point of production or point of consumption, but, while common in other regions, centralized storage is rare on the West Tavaputs Plateau.  Why did the Fremont employ an exceedingly expensive strategy of storing agricultural resources? Current explanations often rely on normative differences resulting from regional variation. Here we use our formal model to derive predictions about how Formative Period agriculturalists should respond when facing risk and will test our predictions using temporal data, a paleoclimatic reconstruction, and high precision locational data of storage features. This case serves as a model system to evaluate the utility of this general model, and will offer new insights into seemingly irrational storage decisions.

Figure: Example of paleoclimatic reconstruction of the West Tavaputs Plateau from 1 to 2000 AD. Years 236 and 1350 AD are selected to show individual raster map data at high and low mean precipitation values. Each dot represents the mean annual cell value for precipitation in millimeters.

An Ecological Model of Site Distribution for the Grand Staircase-Escalante National Monument

Researchers at the University of Utah Archaeological Center (UUAC) have developed a novel predictive model of archaeological site occurrences that combines insights from the science of behavioral ecology with a powerful machine-learning program known as Maximum Entropy. The model will further our understanding of prehistoric human land use patterns and empower land managers to identify more efficient strategies for preserving archaeological resources in the Grand Staircase-Escalante National Monument.

For more, see:

Yaworsky, Vernon, and Codding (2018). Archaeological Potential of the Grand Staircase-Escalante National Monument. Poster.