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Vegetation-based metrics of biotic integrity for assessing the ecological condition of wetlands of Kentucky.

机译:基于植被的生物完整性指标,用于评估肯塔基州湿地的生态状况。

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摘要

Over the last two centuries, wetland acreage across the world has significantly declined due to human disturbances. It has been estimated that Kentucky has lost over 80% of its wetland area. In response to these losses occurring across the United States, the Clean Water Act was passed to halt this dramatic decline and to restore the ecological integrity of waters of the United States. To enforce the Clean Water Act, a number of ecological assessment techniques have been developed to quantify the ecological quality of the waters of the United States. Kentucky recently adopted a rapid method for assessing the ecological condition of wetlands, but there is no standardized means to rigorously assess the ecological quality of its wetlands. Indices of biotic integrity (IBI) represent such a rigorous method and has become one of the most common approaches for intensive ecological assessment. IBIs evaluate the ecological condition of a site based on indicator organisms that reflect current and past anthropogenic disturbances of the area. In this study I report on initial efforts to develop a vegetation-based IBI for Kentucky (KY VIBI). Ohio has a state-wide applicable vegetation-based IBI (VIBI) for wetlands that has undergone multiple iterations of testing and refinement over more than 10 years. Due to the geographic and vegetative similarities between Ohio and Kentucky, Ohio's VIBI (OH VIBI) was used as a model to begin developing a state-wide applicable vegetation-based IBI for Kentucky.;A unique approach was used to begin the process of developing the KY VIBI. I developed a set of candidate metrics that included unmodified and slightly modified OH VIBI metrics, unmodified metrics from a VIBI study conducted in Colorado, and newly hypothesized metrics based on similar studies and my own professional knowledge of the plant communities of wetlands in Kentucky. The candidate metrics were tested for their response to disturbance indices using correlation analysis with data obtained from 68 wetland sites in Kentucky. Since metric response is expected to vary along a disturbance gradient, the resultant ecological condition of a site can be evaluated based on a core set of metrics that are related to anthropogenic disturbance. Sites were distributed across wetland types (emergent, forest, and shrub), as well as across the three major river basins (Green River, Kentucky River, and Upper Cumberland River). The disturbance indices were created by combining the non-biological submetrics of a newly developed rapid assessment method, the Kentucky Wetland Rapid Assessment Method (KY-WRAM), and the landscape disturbance index (LDI). The KY-WRAM and LDI were statistically combined using Principal Components Analysis (PCA) to create new disturbances indices. Combining these two separate measures of anthropogenic disturbance in a PCA resulted in better metric correlation compared to using either the KY-WRAM or LDI individually. The first two PC axes explained 48.35% and 13.47% of the total variation, respectively, and so those two axes were retained for comparison to the candidate KY VIBI metrics. Loading scores of variables were relatively strongly weighted on just the first or second axis of the PCA, suggesting good, simple structure in the PCA.;A list of the best ten candidate metrics were selected for each wetland type (emergent, shrub, and forest) based on their correlation and apparent response to disturbance, along with using best professional judgment. Many of the best metrics are related to invasiveness, tolerance, and floristic quality scores (e.g. Mean Coefficient of Conservatism for all Species, % Non-native Species, % Intolerant). Although the OH VIBI provided a sound methodological foundation for developing a VIBI for Kentucky, the results presented here suggest that many of the metrics in the current OH VIBI do not accurately reflect the biological effects of disturbance in Kentucky's wetlands, at least for the three river basins sampled for this study. The ten best candidate metrics will need to be further tested and evaluated for performance in other basins of Kentucky to ensure complete and proper calibration. Also, the individual metrics will need to be scaled, combined, and possibly weighted to create an index. By selecting and utilizing a different set of metrics with stronger association to disturbance we can more accurately describe wetland quality in the state of Kentucky.
机译:在过去的两个世纪中,由于人为干扰,世界各地的湿地面积已大大减少。据估计,肯塔基州已经失去了超过80%的湿地面积。针对美国各地发生的这些损失,通过了《清洁水法》,以制止这种急剧下降并恢复美国水域的生态完整性。为了执行《清洁水法》,已经开发了许多生态评估技术来量化美国水域的生态质量。肯塔基州最近采用了一种快速的方法来评估湿地的生态状况,但是尚没有标准化的方法来严格评估其湿地的生态质量。生物完整性指数(IBI)代表了这种严格的方法,已成为集约化生态评估的最常见方法之一。 IBI根据反映该地区当前和过去人为干扰的指示生物评估该地点的生态状况。在这项研究中,我报告了为肯塔基州(KY VIBI)开发基于植被的IBI的初步工作。俄亥俄州在全州范围内适用于湿地的基于植被的IBI(VIBI),经过十多年的反复测试和完善。由于俄亥俄州和肯塔基州之间在地理和营养上的相似性,俄亥俄州的VIBI(OH VIBI)被用作开始为肯塔基州开发适用于全州的基于植被的IBI的模型。采用独特的方法开始了开发过程KY VIBI。我开发了一组候选指标,包括未经修改和稍作修改的OH VIBI指标,在科罗拉多州进行的VIBI研究中的未修改指标,以及基于类似研究和我自己对肯塔基州湿地植物群落的专业知识而提出的新假设指标。使用从肯塔基州68个湿地站点获得的数据进行相关分析,测试了候选指标对干扰指数的响应。由于预计度量响应会沿着干扰梯度变化,因此可以基于与人为干扰相关的一组核心度量来评估站点的最终生态状况。地点分布在湿地类型(紧急,森林和灌木)以及三个主要流域(格林河,肯塔基河和坎伯兰河)上。干扰指数是通过结合一种新开发的快速评估方法,肯塔基州湿地快速评估方法(KY-WRAM)和景观干扰指数(LDI)的非生物亚度量来创建的。使用主成分分析(PCA)对KY-WRAM和LDI进行统计组合,以创建新的干扰指数。与单独使用KY-WRAM或LDI相比,在PCA中将这两种单独的人为干扰度量结合起来可产生更好的度量相关性。前两个PC轴分别解释了总变化的48.35%和13.47%,因此保留了这两个轴以与候选KY VIBI度量进行比较。仅在PCA的第一轴或第二轴上对变量的加载分数进行了比较强的加权,这表明PCA中的结构良好,简单。;为每种湿地类型(紧急,灌木和森林)选择了最佳的十个候选指标列表)基于他们的相关性和对干扰的明显反应,并使用最佳的专业判断力。许多最佳指标与入侵性,耐受性和植物质量得分有关(例如,所有物种的平均保守性系数,非本地物种的百分比,不耐受的百分比)。尽管OH VIBI为开发肯塔基州的VIBI提供了良好的方法论基础,但此处提出的结果表明,当前的OH VIBI中的许多指标都不能准确反映出肯塔基州湿地干扰的生物影响,至少对于三河而言本研究采样的盆地。需要对十个最佳候选指标进行进一步测试和评估,以确保其在肯塔基州其他盆地的性能,以确保完整且适当的校准。同样,将需要对各个指标进行缩放,组合以及可能进行加权以创建索引。通过选择和利用与干扰相关性更强的一组不同指标,我们可以更准确地描述肯塔基州的湿地质量。

著录项

  • 作者

    Morris, Tanner Matthew.;

  • 作者单位

    Eastern Kentucky University.;

  • 授予单位 Eastern Kentucky University.;
  • 学科 Ecology.;Botany.;Natural resource management.
  • 学位 M.S.
  • 年度 2015
  • 页码 80 p.
  • 总页数 80
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:52:15

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