Lakes are important places in the landscape for capturing, transforming, emitting, and storing carbon given their small surface area. Human activities in watersheds are causing many lakes and reservoirs to become over-enriched in nutrients. This is called hypereutrophication. Over-enrichment can cause a variety of problems in ecosystems, including changes in carbon cycling. While substantial progress has been made in understanding the processes that control carbon cycling in lakes and reservoirs, relatively little is known about how those processes operate in water bodies with extremely high nutrient concentrations, a condition which is becoming increasingly common. This research is aimed at identifying the key controls on carbon cycling in lakes and reservoirs under extreme nutrient loading. This will help predict how these ecosystems will respond to future environmental stresses. In addition to carbon cycling, lakes and reservoirs also provide important ecosystem services that are threatened by eutrophication. Managing freshwater resources to protect ecosystem services is vital for societal well-being. Yet, decisions about freshwater resources require educated water stewards working at the local level. This project will provide extensive training in aquatic ecosystem management to local water stewards, empowering their communities to make informed, data-driven decisions about lake and watershed management.
In order to identify when and where the important drivers of carbon cycling are operating in lakes under extreme nutrient enrichment, high frequency sensors will be deployed in high-nutrient lakes to capture carbon cycling dynamics throughout the entire year. One of the focal study lakes is located on the Iowa State University campus. The live-streaming data and monitoring activities will be incorporated into educational opportunities across campus. An additional 20 lake-years of high frequency data will be collected through a lake management education and volunteer training program for local water stewards. All of the sensor-based measurements will be paired with less frequent synoptic sampling to quantify the pools of carbon and nutrients entering and cycling in the lakes. These time series will be used to quantify the aerobic, anaerobic, and physical transport processes controlling carbon cycling dynamics and to determine the environmental drivers of carbon cycling rates. This information, combined with long term water quality monitoring data from 130 lakes embedded in a nutrient-rich landscape, will be used to estimate aquatic carbon cycling rates at a regional scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
