This $567,340 Project Grant from the National Science Foundation Division of Environmental Biology under the Biological Sciences federal grant program (CFDA 47.074) will fund research at Virginia Polytechnic Institute and State University to advance understanding of lake water quality dynamics across spatial scales using knowledge-guided machine learning. The research aims to develop Ecology-knowledge guided Machine Learning (Eco-KGML) models to improve predictions of water clarity,...
The National Science Foundation (NSF) Division of Environmental Biology awarded a $130,123 Project Grant to the University of Wisconsin System at the University of Wisconsin - Madison, with a project period from November 1, 2023 to October 31, 2027. The funding supports collaborative research to develop a comprehensive model of year-round ecosystem function in seasonally frozen lakes, addressing the "winter knowledge gap" in understanding how changing winter conditions impact lake...
This National Science Foundation (NSF) Biological Sciences (CFDA 47.074) Project Grant in the amount of $300,000 was awarded to Michigan State University to investigate the complex interactions between human disturbances and natural features that impact U.S. lake ecosystems and harmful algal blooms. The key products and services to be delivered through this 2-year award include: Developing machine learning models to quantify the relationships between multiple human disturbances and their impacts...
The National Science Foundation Division of Environmental Biology awarded a $736,279 Project Grant to the University of Wisconsin-Madison from December 1, 2021 through December 31, 2025. The grant supports research titled "CONTROL POINTS ON NUTRIENT CYCLING IN HYPEREUTROPHIC LAKES" under the Biological Sciences program (CFDA 47.074). The University of Wisconsin-Madison will conduct research to increase scientific understanding of major problems related to nutrient cycling in...
This National Science Foundation (NSF) Project Grant award for $425,311 to the Carnegie Institution for Science supports collaborative research on how winter conditions affect the ecological function of seasonally-frozen lakes. The multi-year project (11/1/2023 - 10/31/2027) will develop a comprehensive, predictive model of year-round lake ecosystem dynamics by: Conducting detailed seasonal studies of water quality, plankton populations, food webs, and organic matter cycling in 12 lakes with...
This National Science Foundation project grant of $199,984 supports the development of model enabled machine learning approaches to predict ecosystem regime shifts through the Biological Sciences program (CFDA 47.074). The University of Hawaii at Manoa will receive funding from January 15, 2023 through December 31, 2025 to co-develop numerical methods with stakeholders that combine theoretical ecosystem models with machine learning to forecast regime shifts in coral reefs, freshwater lakes...
The National Science Foundation (NSF) awarded a $213,430 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Ohio State University to develop a novel, miniature, fiber-optic multiparameter sensor capable of simultaneously measuring critical water quality and greenhouse gas parameters in lakes. The goal is to create an easy-to-deploy, cost-effective sensor that can provide high-resolution, year-round data to better understand the carbon...
This Project Grant award of $450,000 from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) supports an international research project titled "IRES: AQUATIC BRIGHT SPOTS: ECOLOGICAL RESILIENCE IN NORTHERN LAKES AND RIVERS". The project, awarded to the University of Wisconsin-Madison, aims to investigate the factors contributing to the resilience of aquatic ecosystems in northern Mongolia despite the impacts of climate change. Over 3 years...
The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Virginia. The grant supports the development of new physics-guided graph network models to capture complex, non-stationary, and poorly observed water dynamics in freshwater ecosystems. Key innovations include new graph-based architectures, continual learning strategies, and model initialization methods that leverage...
The National Science Foundation (NSF) Division of Environmental Biology awarded a $399,132 project grant to the University of Virginia for a three-year collaborative research project titled "Whole Ecosystem Test of Restoring Resilience in Lakes". The goal of the project is to experimentally test methods for enhancing the resilience of lake ecosystems to algal blooms, which threaten drinking water, reduce tourism, and harm wildlife. The researchers will measure and evaluate the...
This $525,899 National Science Foundation project grant supports the development of Ecology-Knowledge Guided Machine Learning (Eco-KGML) models to advance understanding of lake water quality dynamics across spatial and temporal scales in the United States. Funded under the Biological Sciences program (CFDA 47.074), the University of Wisconsin-Madison will utilize hybrid process-based and machine learning techniques to predict and analyze metrics such as water clarity, phytoplankton biomass, and hypolimnetic anoxia. Novel compositional learning methods will identify dominant processes influencing water quality at individual lakes and across types. This comprehensive approach leveraging scientific knowledge and data aims to discover scale-dependent relationships between lakes and drivers while improving predictions. The period of performance is from November 1, 2022 to October 31, 2026.