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.
