These selected research projects highlight new water-related research projects just beginning at U-M, as well as new applied research products emerging from existing work. Have a new research project or new applied products? Contact Dieter Bouma (email@example.com) to include in the next round-up.
Enhancing sustainability in coastal communities threatened by harmful algal blooms by advancing and integrating environmental and socio-economic modeling
Two overarching questions are at the heart of this multi-disciplinary project: 1) How does climate influence the biophysical dynamics of freshwater ecosystems and ecosystem services, and 2) How can scientist and stakeholder co-production of information enhance coastal decision-making and sustainability?
Project PIs: Allison Steiner (UM-CLaSP), Christine Kirchhoff (UConn), Maria Carmen Lemos (UM-SNRE), Frank Lupi (MSU), Daniel Obenour (NC State), Donald Scavia (UM-SNRE/CoE).
Funding: National Science Foundation – Science, Engineering, and Education for Sustainability
Importance of bacterial phenotypic plasticity relative to changes in community composition as responses to disturbance
The objective of this project is to determine the role of bacterial physiological and ecological responses during short and medium-term biological disturbances, using invasion by dreissenid mussels in freshwater lakes through a combination of laboratory and field experiments. The project relies on a recently developed method based on flow cytometric analysis of bacterial diversity, and when combined with sequencing-based analyses, should be able to decompose phenotypic, versus genotypic responses of bacterial communities.
Project PIs: Vincent Denef (UM-EEB)
Funding: National Science Foundation – Early-concept Grants for Exploratory Research
WaterBeta for Asset Risk Pricing
This project team is focusing on connecting water risk from watersheds to capital markets. The premise is that when water quantity, water quality, regulatory and reputational risks in watersheds impact corporate operations, long-term opportunity cost and risk management are affected. The project takes a big data approach to express business water risk exposures in the context of capital markets risk signaling. By using mainly trading, geographic water risk exposure, and corporate operations data, researchers can extract volatility signals that can be correlated to risk events. Project collaborators include Equarius Risk Analytics, Ceres’ Invester Water Hub, and MSCI, Inc.
Project PI: Peter Adriaens
Relevant Link: WaterBeta for Asset Risk Pricing
Two new publications from the applied research project team, “Informing Lake Erie Agriculture Nutrient Management via Scenario Evaluation,” include:
- Multiple models guide strategies for agricultural nutrient reductions, Frontiers in Ecology (2017)
- A multi-model approach to evaluating target phosphorus loads for Lake Erie, Journal of Great Lakes Research (2016)
This project brought together watershed modeling groups to use a multiple model approach to explore and evaluate potential land management options for meeting the 40% reduction in phosphorus load target for the Maumee River watershed. Agricultural, environmental, and policy stakeholders from the Lake Erie region were consulted to develop agricultural land management scenarios to test in the five SWAT models.
Project PIs: Don Scavia, College of Engineering and School of Natural Resources and Environment
Relevant Link: Informing Lake Erie Nutrient Management webpage
Michigan Radio Interview with Dr. Richard Norton
Michigan Radio’s Lester Graham interviewed Dr. Norton for Stateside about his team’s project on Great Lakes coastal planning in light of changing water levels:
The project team developed a range of scenario-based planning methods to help Great Lakes coastal communities make more prudent land use management decisions for their coastal shorelands in the face of unpredictably fluctuating water levels and increasing storminess.
Project PI: Richard Norton, Taubman College of Architecture and Urban Planning
Relevant Link: Resilient Great Lakes Coast