My work lies at the intersection of freshwater ecosystem science and data science and I get excited about lots of different questions exploring anthropogenic effects on inland waters. I am broadly interested in nutrient and carbon cycling in freshwater ecosystems and the feedbacks that occur between aquatic biogeochemical cycles and plankton food webs. I also am interested in how local communities value and manage their water resources, which has implications for water quality. I particularly like working in interdisciplinary, collaborative teams to solve water challenges. Check out the lab’s Publications page to explore our most recent work or my Google Scholar profile.
At Virginia Tech, my research has expanded into near-term ecological forecasting. In collaboration with computer scientists, environmental engineers, decision scientists, and water utilities, my lab group integrates high-frequency sensor data and ecosystem models to generate daily water quality forecasts that predict a suite of freshwater ecosystem services for lakes and reservoirs across the U.S. I am particularly interested in studying how managers use forecasts of future conditions to control hypoxia and algal blooms, which in turn alters biogeochemical cycling and greenhouse gas dynamics. For more information, see our project website on SmartReservoirs.
Finally, a major goal of my lab is to advance undergraduate training in environmental data science. I am the lead PI of Macrosystems EDDIE (Environmental Data-Driven Inquiry & Exploration), an NSF-supported program to develop teaching modules that train undergraduates ecological modeling, forecasting, and computational literacy. By integrating messy, high-frequency sensor datasets into undergraduate curricula, students simultaneously learn the core concepts of ecology while developing the quantitative skill sets needed to conduct the next generation of environmental research.