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A Performance Comparison of Metric Scoring Methods for a Multimetric Index for Mid-Atlantic Highlands Streams

机译:中大西洋高地河流多指标指标的度量标准评分方法的性能比较

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When biological metrics are combined into a multimetric index for bioassessment purposes, individual metrics must be scored as unitless numbers to be combined into a single index value. Among different multimetric indices, methods of scoring metrics may vary widely in the type of scaling used and the way in which metric expectations are established. Theses differences among scoring methods may influence the performance characteristics of the final index that is created by summing individual metric scores. The Macroinvertebrate Biotic Integrity Index (MBII), a multimetric index, was developed previously for first through third order streams in the Mid-Atlantic highlands of the United States. In this study, six metric scoring methods were evaluated for the MBII using measures related to site condition and index variability, including the degree of overlap between impaired and reference distributions, relationships to a stressor gradient, within-sample index variability, temporal variability, and the minimum detectable difference. Measures of index variability were affected to a greater degree than those of index responsiveness by both the type of scaling (discrete or continuous) and the method of setting expectations. A scoring method using continuous scaling and setting metric expectations using the 95th percentile of the entire distribution of sites performed the best overall for the MBII. These results showed that the method of scoring metrics affects the properties of the final index, particularly variability, and should be examined in developing a multimetric index because these properties can affect the number of condition classes (e.g., unimpaired, impaired) an index can distinguish.
机译:当出于生物评估目的将生物学指标合并为多指标时,必须将各个指标评分为无单位数,以合并为单个指标值。在不同的多指标索引中,对指标进行评分的方法可能会在所使用的缩放类型和建立指标预期的方式方面发生很大变化。评分方法之间的这些差异可能会影响最终指标的性能特征,而最终指标是通过汇总各个指标得分而得出的。大型无脊椎动物生物完整性指数(MBII)是一种多指标指数,以前是为美国中大西洋高地的一阶到三阶流开发的。在这项研究中,对MBII的六种指标评分方法使用了与场地条件和指数变异性相关的措施进行了评估,包括受损和参考分布之间的重叠程度,与压力源梯度的关系,样本内指数变异性,时间变异性和最小可检测差异。指标类型(离散或连续)和设定期望值的方法对指标变异性的影响都比指标响应性更大。对于MBII,使用连续缩放和设置指标期望值(使用网站的整个分布的95%)的评分方法表现最佳。这些结果表明,对指标进行评分的方法会影响最终索引的属性,尤其是可变性,因此应在开发多指标索引时进行检查,因为这些属性会影响索引可以区分的条件类别(例如,未受损,受损)的数量。 。

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