Development and Calibration of a New Method of Reconstructing Fire History in Low-Severity Fire Regimes

该研究项目将解决生物地理学中的一个基本假设，即黄松等干松林的结构由低密度的大树主导，并由频繁的低强度火灾维持，这限制了树木的再生。这一假设部分建立在低严重程度火灾在历史上频繁发生的假设之上，这一假设在很大程度上依赖于使用复合火灾间隔的火灾历史方法。从分析、模拟和最初的现代校准中提出了一些证据，表明使用复合火灾间隔是有偏差和不准确的。为了克服复合火灾-区间方法的局限性，研究人员提出了一种新的方法——全树火灾-区间（ATFI）方法，并通过仿真证明了该方法的无偏性和准确性。本项目将完成基于现场的现代校准，并将ATFI方法应用于历史火灾历史重建，使ATFI方法便于使用，以帮助验证基本假设。研究人员将首先收集和分析关于瘢痕分数的现场数据，这是使用ATFI方法所需的一个中心参数，通过对亚利桑那州北部黄松森林中22起火灾的48个地块进行采样，该地区是目前了解低严重性火灾的关键地区。这种疤痕分数分析将促进空间模型的发展，以预测环境设置、树木特征（如密度和直径）以及燃料的疤痕分数。然后将利用疤痕分数模型完成ATFI方法的现代校准，并在大峡谷国家公园和福特谷实验森林的1000公顷地区使用ATFI方法完成历史火灾历史重建。研究人员将提取约640个增量岩心并进行交叉数据，以确定树木的年代，并提取约105个火灾痕迹，以计算ATFI校准和重建的火灾数量。最后，他们将完成对这两个地区现存的前欧美火疤证据的空间分析，以提高对火疤证据如何在景观中发生的基本理解。在完成这三个部分的研究过程中，研究者将检验7个关于疤痕分数的具体假设，3个关于火灾历史的假设，3个关于现存火灾疤痕证据的假设。他们希望能够大大提高对火灾留下的火疤证据的理解，以及如何利用这些证据准确地重建景观中低严重性火灾的历史。该项目将测试和验证一种准确重建森林火灾历史的新方法。火灾历史为管理国家公园、国家森林和其他公共土地上的森林提供了必要的基本信息。更具体地说，该项目将进一步开发一种新的火灾历史方法，并帮助解决黄松森林历史火灾燃烧率的不确定性。火太多或太少都会对古树、林下植物和野生动物产生不利影响，因此解决这种不确定性很重要。本项目的研究将为一名研究生和几名本科生提供实地和实验室教育机会。

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.