U.S. Joint Fire Science Program


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US government work.


Datasets from on-going and previous fire studies in the Coastal Plain, Piedmont, and Southern Appalachian regions in the southeastern U.S. dating back over the past 50 years were compiled and publically made available to other interested persons. The projects included for this data archival have helped to advanced fire science and provided much needed information about fire effects on ecosystem components. The research from these projects has demonstrated how returning fire to once fire-adapted communities is an on-going process that needs to be repeated frequently. They also have given some insight into alternative treatments that may be used for fuel reduction, depending on land managers’ objectives, and the ecological effects that may be associated with alternative treatment. The commonalities between these studies both in variables measured and site locations provide data that allow a more complete view of these ecosystems providing a unique opportunity for meta-analysis of multiple fires and other fuel reduction treatments at regional levels.

Datasets from 7 different studies were selected to provide information pertaining to fire and/or fuel treatment effects on vegetation, fuels, and soils: 1) prescribed burning for stand replacement in Table Mountain pine stands in the southern Appalachian Mountains; 2) consequences of fire and fuel reduction treatments in the Piedmont and Coastal Plain; 3) fuel classification by landscape position in the southern Appalachians; 4) fuel decomposition rates by landscape position in the Southern Appalachians; 5) prescribed burning and release of mercury; 6) long-term winter-burning effects on vegetation and soils in the Coastal Plain; and 7) season of burn and fire return interval effects on vegetation and soils in the Piedmont. Five of these studies can be considered as long-term projects with sampling occurring over 8-24 years (with one study encompassing 50+ years), whereas the other 2 studies were 2-5 year projects. Each dataset and its variables are found in Table 1.