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Dimensions: Collaborative Research: Anthropogenic nutrient input drives genetic, functional and taxonomic biodiversity in hypereutrophic Lake Taihu, China

维度：合作研究：人为养分输入驱动中国超富营养化太湖的遗传、功能和分类生物多样性

基本信息

批准号：
1240870
负责人：
Steven Wilhelm
金额：
$ 56.3万
依托单位：
University of Tennessee Knoxville
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2013
资助国家：
美国
起止时间：
2013-01-01 至 2018-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1240870&HistoricalAwards=false
关键词：
Dimensions Collaborative Research Anthropogenic nutrient

项目摘要

Human activities have dramatically increased nitrogen inputs into many rivers and lakes, causing algal blooms that threaten economic and recreational uses of those waters. Lake Taihu, the third largest lake in China, experiences damaging blooms of toxic cyanobacteria as a result of excessive nutrient inputs. The identities, nitrogen processing capabilities, and activities of microbial communities in Lake Taihu will be examined to determine if nitrogen processing can be predicted from knowledge of the identity and genetic makeup of those communities. Various components of the nitrogen cycle will be measured and linked to representative molecular markers which, coupled with high throughput genetic sequencing, will provide a genetic database of nitrogen-cycling processes in freshwater ecosystems. A goal of the project will be to link microbial taxonomic, genetic, and functional data in a model that can predict how reduction of nutrient inputs will affect toxic cyanobacterial blooms.This project will have broad applicability to the management of aquatic systems that are threatened by excessive nutrient inputs, a problem that is increasing worldwide. Additional broader impacts will include training of high school, undergraduate, and graduate students, international student exchanges, training of a postdoctoral researcher, and incorporation of science journalism students into field studies to promote adult scientific literacy.

人类活动极大地增加了对许多河流和湖泊的氮输入，导致藻类大量繁殖，威胁到这些水域的经济和娱乐用途。太湖是中国的第三大湖，由于过度的营养投入，有毒蓝藻的大量繁殖造成了破坏。将检查太湖微生物群落的身份、氮处理能力和活动，以确定是否可以根据这些群落的身份和遗传组成的知识来预测氮的处理。将测量氮循环的各种组成部分，并将其与典型的分子标记相联系，这些标记与高通量基因测序相结合，将提供淡水生态系统中氮循环过程的遗传数据库。该项目的一个目标是将微生物分类、遗传和功能数据连接到一个模型中，该模型可以预测营养输入的减少将如何影响有毒的蓝藻水华。该项目将对受到过量营养输入威胁的水生系统的管理具有广泛的适用性，这是一个在世界范围内日益严重的问题。其他更广泛的影响将包括培训高中生、本科生和研究生，国际学生交流，培训博士后研究员，以及将科学新闻专业的学生纳入实地研究，以促进成人科学素养。