Doctoral Dissertation Research: An Integrated Spatio-Temporal Approach for Reconstructing, Analyzing, and Representing Paleo-Fire Regimes

古生态扰动的空间特征对于理解环境过程的自然变异性至关重要。然而，许多古生态研究领域，特别是那些依赖于离散点收集的数据的领域，如花粉和木炭研究，强调时间变异性，最小化或忽略空间维度。对于基于从个别树木收集的火灾伤疤数据的火灾历史研究来说，情况尤其如此。许多这样的研究得出了火灾返回间隔，以估计部分景观被烧毁的频率。这些回火间隔在空间上是模糊的，对它们计算的区域范围很敏感，这使得解释具有挑战性。此外，过去处理空间变异性的研究使用了火灾的离散表示，主要是绘制了估计火灾范围的地图轮廓。这种格式很难评价，因为分别呈现了空间和时间的可变性，而且它排除了独立的解释。本博士论文研究改进项目的目的是开发一个完整的古火时空表达系统。该项目将融合火灾历史科学、景观生态学和地理信息科学，特别是时空和空间认知理论。博士生将在地理信息系统中使用地理参考火灾伤痕树木数据。该表示将整合过去火灾的场和对象模型，并融入一种标志性的可视化语言，该语言将说明单个树木在空间和时间上的状态变化。该系统将为分析古火的新方法提供便利。将提出一种空间显式方法来估计火力回击间隔。从表示系统中提取的空间度量将用于评估自上而下的气候因素和自下而上的地形因素对过去火灾的时空变异性的影响。目前的爆炸性野火只能在其历史生态背景下才能被理解。该项目将通过提供新的分析方法和对数据表示具有认知敏感性的方法来提高对自然野火制度的基本了解。这些新的数据表示方法，包括古生态火灾地图，将供包括科学家、管理人员和相关公众在内的各种感兴趣的各方使用。这将提高对古火的理解，并提供利用复杂的古生态数据进行教育的机会。最后，该项目可以为其他类型的使用深部时间点数据的古生态研究提供借鉴。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。

The spatial characteristics of paleoecological disturbances are critical to understanding the natural variability of environmental processes. However, many areas of paleoecological inquiry, particularly those relying on data collected at discrete points, such as pollen and charcoal studies, emphasize temporal variability and minimize or neglect the spatial dimension. This is particularly true of fire history research that is based on fire-scar data collected from individual trees. Many such studies result in a fire return interval that estimates how frequently a portion of the landscape burned. These fire-return intervals are spatially ambiguous and sensitive to the extent of the area for which they are calculated, making interpretation challenging. Furthermore, past studies that have addressed spatial variability have used discrete representations of fires, principally mapped outlines of the estimated fire extent. This format is difficult to evaluate because presents spatial and temporal variability separately, and it precludes independent interpretation. The purpose of this Doctoral Dissertation Research Improvement project is to develop an integrated spatial-temporal representation system for paleo-fire. The project will incorporate fire-history science, landscape ecology, and geographic information science, particularly space-time and spatial cognition theory. The doctoral candidate will use georeferenced fire-scarred tree data in a geographic information system. The representation will integrate field and object models of past fires and incorporate an iconic visualization language that will illustrate the change in state of individual trees in space and through time. This system will facilitate novel approaches to analyzing paleo-fire. A spatially explicit approach for estimating fire return interval will be presented. Spatial metrics extracted from the representation system will be used to evaluate the influence of top-down climatic factors and bottom-up topographic factors on spatial-temporal variability of past fires.Current explosive wildfires can only be understood within their historical ecological context. This project will improve basic understanding of natural wildfire regimes by contributing new analytical methods and a cognitively sensitive approach to data representation. These new approaches to data representation, including maps of paleoecological fires, will be accessible to a wide range of interested parties, including scientists, managers, and concerned members of the public. This will improve the understanding of paleo-fire and present educational opportunities using complex paleoecological data. Finally, this project can benefit other types of paleoecological research where deep time point data are used. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.