Anticipating wildfire impacts to the archaeological record of the Jemez Mountains

Fire weather, fuel condition, and topography influence the presence and severity of archaeological fire impacts. Wildfires of uncharacteristic severity, a consequence of climate changes and accumulated fuels, can cause amplified or novel impacts to archaeological resources. The archaeological record includes physical features associated with human activity; these exist within ecological landscapes and provide a unique long-term perspective on human–environment interactions. The potential for fire-caused damage to archaeological materials is of major concern because these resources are irreplaceable and non-renewable, have social or religious significance for living peoples, and are protected by an extensive body of legislation. Although previous studies have modeled ecological burn severity as a function of environmental setting and climate, none have assessed the use of these variables as predictors of archaeological fire effects.

The archaeological record includes physical features (such as structures, remnants of agricultural fields, and stone or ceramic artifacts) associated with human activity that exist within ecological landscapes and provide a unique and irreplaceable long-term perspective on human–environment interactions.

Archaeological resources are vulnerable to the impacts of wildfires, which can cause physical or chemical changes in materials or addition of residues that temporarily or permanently alter attributes important for determining artifact origin, age, cultural affiliation, or technology of production. Uncharacteristically severe fires are increasing in the U.S. Southwest and often expose archaeological materials to new—and potentially more damaging—fire environments than historically occurred in the region. In this study, we analyzed relationships among environmental predictors and observed fire impacts to archaeological sites, features, and artifacts in the Jemez Mountains of New Mexico. We used models based on machine learning algorithms to detect the environmental conditions under which wildfires result in observable impacts to archaeological sites, artifacts, and features.

Topographic predictors were highly important for distinguishing unburned, moderate, and high site burn severity within archaeological sites. High-severity impacts were more likely at archaeological sites with southern orientation or on warmer, steeper slopes with less accumulated surface moisture, likely associated with lower fuel moistures and high potential for spreading fire. Models for predicting where and when fires may negatively affect the archaeological record can be used to prioritize fuel treatments, inform fire management plans, and guide post-fire rehabilitation efforts, thus aiding in cultural resource preservation.