Price Associates, Inc., One North Broadway Ste 406, White Plains, NY 10601, USA.
Water Res. 2010 Apr;44(8):2629-37. doi: 10.1016/j.watres.2010.01.018. Epub 2010 Jan 29.
Microbial source tracking (MST) is a procedure used to determine the relative contributions of humans and animals to fecal microbial contamination of surface waters in a given watershed. Studies of MST methodology have focused on optimizing sampling, laboratory, and statistical analysis methods in order to improve the reliability of determining which sources contributed most to surface water fecal contaminant. The usual approach for estimating a source distribution of microbial contamination is to classify water sample microbial isolates into discrete source categories and calculate the proportion of these isolates in each source category. The set of proportions is an estimate of the contaminant source distribution. In this paper we propose and compare an alternative method for estimating a source distribution-averaging posterior probabilities of source identity across isolates. We conducted a Monte Carlo simulation covering a wide variety of watershed scenarios to compare the two methods. The results show that averaging source posterior probabilities across isolates leads to more accurate source distribution estimates than proportions that follow classification.
微生物源追踪（MST）是一种用于确定人类和动物对特定流域地表水粪便微生物污染相对贡献的方法。MST 方法的研究侧重于优化采样、实验室和统计分析方法，以提高确定哪些来源对地表水粪便污染物的贡献最大的可靠性。估计微生物污染源分布的常用方法是将水样微生物分离物分类到离散的源类别中，并计算每个源类别中这些分离物的比例。这组比例是污染物源分布的估计。在本文中，我们提出并比较了一种估计源分布的替代方法——跨分离物平均源身份的后验概率。我们进行了蒙特卡罗模拟，涵盖了各种流域场景，以比较这两种方法。结果表明，跨分离物平均源后验概率比遵循分类的比例更能准确估计源分布。
