Doctoral Dissertation Research: Fluvial Wood Presence and Dynamics Over a Thirty-Year Interval in Forested Watersheds

博士论文研究：森林流域三十年间隔内河流木材的存在和动态

• 批准号: 1028909
• 负责人: Mark Fonstad
• 金额: $ 0.79万
• 依托单位: Texas State University - San Marcos
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028909&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Fluvial; Wood

This doctoral dissertation research project seeks to examine both the presence and transport of wood since logging ceased in the early 1980s by analyzing changes in fluvial wood and accompanying parameters within multiple Oregon Coast Range watersheds through the recreation of a field dataset first collected in 1978 by Marston.The cessation is attributed to increased forest conservation and management due to the designation of the Northern Spotted Owl as an endangered species and the implementation of Northwest Forest Plan regulations. The effects of this forest conservation and subsequent afforestation on the river systems are currently unclear. Thirty years later, the researcher expects that some of this fluvial wood has moved, some has remained, and some new wood has been imported. This study seeks to answer three research questions based on the comparison of the two field datasets. (1) How have the volume, size, and type of fluvial wood changed in Oregon Coast Range watersheds between 1978 and 2010? (2) What stream channel morphology changes have occurred due to fluvial wood in these watersheds since 1978? (3) How have the effects of afforestation changed the landscape of fluvial wood since 1978? The fourth research question regards the use of remotely sensed data to determine the presence of fluvial wood in forested watersheds as an alternative to the current labor intensive field collection methods. (4) Can fluvial wood be detected through airborne LiDAR data analysis coupled with ground-reference data, and how can these techniques be used to better monitor fluvial wood changes and better test fluvial theory?The results of this project will provide insight into fluvial wood characteristics in the Oregon Coast Range on a basin and inter-basin scale. This is a distinctive opportunity to examine the dynamics of wood in rivers over a thirty year interval to reveal the process of afforestation that has occurred in the study area. The results will also provide understanding into some less obvious impacts of clear cut harvesting, such as changes in tree species that significantly alter the types and volumes of wood in the rivers. There is an urgent need for research in watershed-scale river restoration efforts globally. Researchers worldwide might very well embrace the key component of restoration which this work renders which is, quantifying stream health through inventory of river complexity. An important contribution to achieving watershed-scale fluvial wood research is the examination of using LiDAR data for wood identification. Success of this technique in such an extremely wooded environment will determine the extents that LiDAR imagery may be used for wood detection. The support of this research through a Doctoral Dissertation Research Improvement award will enable a promising student to establish a strong environmental research career.

本博士论文研究项目旨在通过重新利用Marston于1978年首次收集的现场数据集，分析俄勒冈海岸多个流域内河流木材和相关参数的变化，以检查自20世纪80年代初伐木停止以来木材的存在和运输。由于北斑猫头鹰被指定为濒危物种，以及西北森林计划条例的实施，森林保护和管理得到了加强。这种森林保护和随后的植树造林对河流系统的影响目前尚不清楚。三十年后，研究人员预计，这些河流木材中的一些已经移动，一些保留下来，一些新的木材已经进口。本研究试图在两个野外数据集比较的基础上回答三个研究问题。(1) 1978年至2010年间，俄勒冈海岸山脉流域河流木材的体积、大小和类型发生了怎样的变化？(2)自1978年以来，这些流域的河道形态发生了哪些变化？(3)自1978年以来，造林对河流林地景观的影响是如何变化的？第四个研究问题涉及使用遥感数据来确定森林流域中河流木材的存在，作为当前劳动密集型现场收集方法的替代方法。(4)通过机载激光雷达数据分析与地面参考数据相结合，能否检测河流木材，如何更好地监测河流木材的变化，更好地验证河流理论？这个项目的结果将在盆地和盆地间尺度上深入了解俄勒冈海岸山脉的河流木材特征。这是一个独特的机会，可以在30年的时间间隔内检查河流中木材的动态，以揭示研究区域发生的造林过程。研究结果还将帮助人们了解一些不太明显的采伐影响，比如树种的变化会显著改变河流中木材的类型和体积。目前迫切需要在全球范围内开展流域尺度的河流修复研究。世界各地的研究人员可能会很好地接受这项工作所呈现的恢复的关键组成部分，即通过河流复杂性的清单来量化河流的健康。对实现流域尺度河流木材研究的一个重要贡献是检查使用激光雷达数据进行木材识别。在这样一个树木繁茂的环境中，这项技术的成功将决定激光雷达图像在多大程度上可以用于木材检测。本研究通过博士论文研究进步奖的支持，将使有前途的学生建立一个强大的环境研究事业。