This research project will address a basic hypothesis in biogeography -- that the structure of dry pine forests like ponderosa pine is dominated by a low density of large trees and is maintained by frequent low-severity fires that limited tree regeneration. This hypothesis rests in part on the assumption that low-severity fires were historically frequent, an assumption largely dependent on a fire-history method that uses composite fire intervals. Some evidence has been presented from analysis, simulation, and an initial modern calibration that the use of composite fire intervals is biased and inaccurate. To overcome limitations of the composite-fire-interval method, the investigators have developed a new approach, the all-tree-fire-interval (ATFI) method, and showed by simulation that the use of is new method is unbiased and accurate. This project will complete a field-based modern calibration and apply the ATFI method in a historical fire-history reconstruction to bring the ATFI method to facilitate use of this method to help test the basic hypothesis. The investigators will first gather and analyze field data on scarring fraction, a central parameter needed for using the ATFI method, by sampling about 48 plots in 22 fires that burned in ponderosa pine forests in northern Arizona, a key area for current understanding of low-severity fire. This scarring-fraction analysis will facilitate development of a spatial model to predict scarring fraction from environmental setting, tree characteristics like density and diameter, and fuels. The scarring-fraction model then will be used to complete a modern calibration of the ATFI method and historical fire-history reconstructions using the ATFI method in 1000-ha areas in Grand Canyon National Park and Fort Valley Experimental Forest. The investigators will extract and cross-date about 640 increment cores to date trees and about 105 fire scars to count fires for the ATFI calibration and reconstruction. Finally, they will complete a spatial analysis of extant pre-EuroAmerican fire-scar evidence in these two areas to improve basic understanding of how fire-scar evidence occurs across landscapes. In the process of completing these three parts of the research, the investigators will test seven specific hypotheses about scarring fraction, three about fire history, and three about extant fire-scar evidence. They expect to be able to greatly improve understanding of how fire-scar evidence is left by fires and how to use this evidence to accurately reconstruct the history of low-severity fire across landscapes.
This project will test and validate a new method for accurately reconstructing fire history in forests. Fire histories provide fundamental information needed in managing forests in national parks, national forests, and on other public lands. More specifically, this project will further develop a new fire-history method and help to resolve uncertainties about the rate that historical fires burned in ponderosa pine forests. Too much fire or too little fire can have adverse effects on old-growth trees, understory plants, and wildlife, so it is important to resolve this uncertainty. The research undertaken in this project will provide both field and laboratory educational opportunities for a graduate student and several undergraduate students.
Low-intensity fires are thought to have played a significant historical role in structuring dry forests (e.g., ponderosa pine forests) in the western United States, yet there is currently no scientifically valid method for accurately reconstructing the historical rate at which these fires burned. Accurate reconstructions are needed to guide prescribed-burning programs and other fire-management programs that are essential to maintain biological diversity and ecosystem services. Past reconstructions typically used composite fire intervals (CFIs) reconstructed from fire scars left on trees; these scars can be dated to determine when fires burned over the last few centuries and the mean interval between these fires can then be calculated. Unfortunately, the CFI method, as it has been applied, has been shown to often underestimate the actual length of intervals between fires. When applied in fire management, this can lead to too much burning, with potentially adverse impacts on biological diversity. In this research, we tested and calibrated a promising new fire-history method, the all-tree-fire-interval (ATFI) method, which has been developed through computer simulation, and shown to be accurate, but has not yet been tested in a field trial. We first studied fire scarring in recent fires in northern Arizona, essential to understand how fire-scar evidence is left by fires, then completed testing of the ATFI method on the South Rim of Grand Canyon National Park. We found that fire scarring is significantly related to the intensity and duration of the fire, which means that hotter and longer-burning fires may leave more scar evidence. We also found that scars from an individual fire are typically clustered in groups, perhaps where the fire flared up. Also, the direction the fire scar faces does seem to indicate the direction the fire was moving. Perhaps most significant from this scarring research is the finding that scarred trees can regrow around the scar and seal up the scar on average in about 38 years. Thus, fire-scar evidence may disappear as scars are sealed up inside trees by regrowth around the scar. These findings suggest that fire-history methods are needed that can accommodate how fire-scar evidence is left in landscapes and disappears as scars heal. The ATFI method can address many of these concerns. In the modern testing of ATFI and CFI methods at Grand Canyon, we compared the fire history we obtained from scars using the ATFI method and the CFI method with the fire history in mapped records of fires from the park. We confirmed that the CFI method does not accurately estimate mean fire intervals from agency records, while the ATFI method did almost perfectly reconstruct mean fire intervals from these records. In related historical tests, we found that the ATFI method also generally worked well and was the most reliable and accurate fire-history reconstruction method for fires over the last few centuries. In contrast, the traditional CFI method generally failed, although one version of CFI did reasonably well in historical testing. For use in individual small plots, the ATFI method appears to be the most reliable method. We suggest that use of the ATFI method can improve the ability of fire-management programs that seek to manage wildland fires and prescribed fires within their historical range of variability. This is likely to help maintain native biological diversity and essential ecosystem services.
