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Applying MAR Analysis to Identify Human and Non-Human Fecal Sources in Small Kentucky Watersheds

机译:应用MAR分析识别肯塔基州小流域的人类和非人类粪便来源

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The recurrence of reports citing water quality impairments in watersheds is evidence that tools are needed to identify pollution sources and facilitate restoration efforts such as implementing total maximum daily limits (TMDLs) or best management practices (BMPs). Fecal bacteria in surface waters are one of the most commonly cited impairments to water quality. This study evaluated microbial source tracking (MST), specifically multiple antibiotic resistance (MAR) analysis, as a management tool to differentiate nonpoint source pollution into source groups. A library containing Escherichia coli (E. coli, EC) and fecal streptococci (FS) isolates from poultry (EC n = 282, FS n = 650), human (EC n = 152, FS n = 240), wildlife (EC n = 17, FS n = 43), horse (EC n = 79, FS n = 82), dairy cattle (EC n = 38, FS n = 42), and beef cattle (EC n = 49, FS n = 46) sources was created. The MAR analysis was conducted on the isolates using a profile of seven antibiotics. The antibiotic signatures of unknown source isolates from Elkhorn and Hickman Creek watersheds were evaluated against the library to determine the contributions of potential fecal inputs from the respective sources. Correct classification was >60% when analyzed at the human and non-human-level of classification. On a watershed basis, both watersheds produced similar results; inputs from non-human sources were the greatest contributors to nonpoint source pollution. The results from the multiple antibiotic resistance (MAR) analysis revealed that the information produced, coupled with knowledge of the watershed and its associated land uses, would be helpful in allocating resources to remediate impaired water quality in such watersheds.
机译:重复引用流域水质受损的报告证明,需要使用工具来识别污染源并促进恢复工作,例如实施总最大每日限量(TMDL)或最佳管理规范(BMP)。地表水中的粪便细菌是最常见的水质损害之一。这项研究评估了微生物源跟踪(MST),特别是多重抗生素抗性(MAR)分析,将其作为将非点源污染区分为源组的管理工具。一个包含大肠杆菌(E. coli,EC)和粪便链球菌(FS)分离物的文库,来自禽类(EC n = 282,FS n = 650),人(EC n = 152,FS n = 240),野生动物(EC n = 17,FS n = 43),马(EC n = 79,FS n = 82),奶牛(EC n = 38,FS n = 42)和肉牛(EC n = 49,FS n = 46)来源已创建。使用7种抗生素对这些分离株进行了MAR分析。根据库对来自Elkhorn和Hickman Creek流域的未知来源分离株的抗生素特征进行了评估,以确定来自各个来源的潜在粪便输入的贡献。在人类和非人类的分类水平上进行分析时,正确的分类> 60%。在分水岭的基础上,两个分水岭都产生了相似的结果。非人类来源的投入是非点源污染的最大贡献者。多种抗生素抗性(MAR)分析的结果表明,所产生的信息,加上对流域及其相关土地用途的了解,将有助于分配资源以补救此类流域中受损的水质。

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