“What Is Past Is Prologue”: Climate Change, Predictive Models, Data Challenges, and Protecting Virginia’s Archaeological Resources

Author(s): Elizabeth Moore

Year: 2024

Summary

This is an abstract from the "*SE The New Normal: Approaches to Studying, Documenting, and Mitigating Climate Change Impacts to Archaeological Sites" session, at the 89th annual meeting of the Society for American Archaeology.

Like many other areas, Virginia is becoming increasingly impacted by the effects of climate change. Over the past several years, the Virginia Department of Historic Resources has taken efforts to model these impacts to identify vulnerable areas for cultural resources planning and mitigation purposes. Testing these models requires knowledge on the distribution, density, size, and integrity of sites across the landscape. Archaeological survey varies significantly across the state and is primarily focused on the areas being impacted most by development pressures. VCRIS, the Virginia Cultural Resources Information System, contains locational and contextual information on over 50,000 archaeological sites. While many of these sites have been surveyed and have reliable integrity and boundary data, there is a significant number of older site records that include unconfirmed boundary estimates from surface observations or were map-projected with no ground-truthing. Our knowledge of the extent and conditions of submerged sites is even more limited. To begin to correct these issues, terrestrial and water-based survey is being conducted in a variety of physiographic settings across the Commonwealth. This baseline data will be used to assess and project site conditions and loss into the future and test various climate change impact models.

Cite this Record

“What Is Past Is Prologue”: Climate Change, Predictive Models, Data Challenges, and Protecting Virginia’s Archaeological Resources. Elizabeth Moore. Presented at The 89th Annual Meeting of the Society for American Archaeology. 2024 ( tDAR id: 498335)

Record Identifiers

Abstract Id(s): 38844.0