An Environmental Anthropology of Modeling and Management on the Chesapeake Bay Watershed

Abstract

In the last few decades, computational models have become an essential component of our understanding of complex environmental processes. In addition, they are increasingly used as tools for the management of large-scale environmental problems like climate change. As a result, understanding the role that these models play in the socioecological process of environmental management is an important area of inquiry for an environmental anthropology concerned with understanding human-environment interactions. In this dissertation, I examine these roles through an ethnographic study of computational environmental modeling in the Chesapeake Bay watershed. The Chesapeake Bay region is an excellent place to investigate modeling and management because, for over thirty years, it has been the site of a watershed-scale effort to reduce nutrient pollution (nitrogen, phosphorous, and sediment) to the Chesapeake Bay. In order to carry out this management process, the Chesapeake Bay Program (CBP) was created as a partnership between the federal government and seven watershed jurisdictions. In addition, modelers at the CBP have been developing a complex computational model of the watershed known as the Chesapeake Bay Modeling System (CBMS) in order to identify and track the sources and effects of nutrient pollution on the estuary. In this dissertation, I explore the role of the CBMS and other models in our understanding and management of nutrient pollution in the region through three articles written for publication in peer-reviewed journals, each of which addresses the question in a different way. The first discusses the ways that the process of building and implementing a computational model is affected by its inclusion in a management institution. The second describes the ways that the computational models themselves are affected by the management contexts in which they are developed and deployed. The third examines the various roles that they play in building and maintaining the relationships that underlie the management process. Together, these articles shed light on the ways that computational models mediate human-environment interactions by way of environmental management, and will help to plan more inclusive and effective modeling and management approaches in the future.