The projects below were funded through the Interdisciplinary, Scalable Solutions for a Sustainable Future Project for the 2020-21 academic year. ISSSF grants provide seed funding for the development of major external grant proposals in the environmental and sustainability sciences. The project is supported by the Office of the Provost, Provost Investment Fund and administered by the Office of Sustainability and the Environment.

Sustainable Food Systems and COVID-19: A Mixed-Methods Assessment of Innovations and Strategies

Principal Investigators: Dr. Carly Nichols Assistant Professor, Department of Geographical and Sustainability Science and Global Health Studies College of Liberal Arts and Science; Dr. Brandi Janssen Clinical Assistant Professor, Department of Occupational and Environmental Health Director, Iowa’s Center for Agricultural Safety and Health (I-CASH)

Project Summary: In the wake of the COVID-19 pandemic and resultant social distancing restrictions, the food system has seen unprecedented shifts in consumer demand alongside supply chain bottlenecks that resulted in empty store shelves and consumer fear around the resiliency of the conventional food system (Stephens et al. 2020). The meat and vegetable/fruit supply chains have proven particularly vulnerable due to COVID-19 outbreaks in processing facilities and a lack of farmworker labor due to increased visa restrictions. At the same time, record unemployment claims and school closures have led to sudden economic stress and food insecurity for millions (Bauer 2020). The implications of these bottlenecks within the conventional food system and shifts in consumer demand will slowly become clear throughout the next year and beyond (Ker and Cardwell 2020). Amidst this unprecedented uncertainty, there is reinvigorated interest in local and regional foods as a reliable and sustainable alternative to the conventional food system (Blay-Palmer et al. 2020, Kolodinsky et al. 2020). Local and regional food systems confer multiple sustainability benefits in terms of shorter supply chains, increased local economic benefits, and an increased community accountability that reduces exploitative labor or environmental practices. However, the unique changing structure of demand (e.g. decreased institutional purchases, household buying surges, and increased economic vulnerability) alongside social distancing restrictions has presented novel challenges to local food systems’ normal modus operandi. This offers a unique opportunity to better understand regional food system actors’ responses to COVID-related challenges in order to gain knowledge about food system resilience that will inform both conventional and regional food systems and enhance social, ecological, and economic sustainability as well as crisis preparedness.

A hard rain’s gonna fall: Responses of Iowa’s bur oak to increased precipitation variability

Principal Investigator: Matthew Dannenberg (Geographical and Sustainability Sciences, GSS) Co-PIs: Susan Meerdink (GSS), Mary Skopec (Iowa Lakeside Laboratory), Adam Skibbe (GSS)

Project Summary: Anthropogenic CO2 emissions have warmed the Earth by about 1°C, with further warming a virtual certainty over the next century. Warming accelerates the hydrologic cycle due to higher water vapor holding capacity of a warmer atmosphere, likely leading to increases in precipitation variability across the globe, as vividly seen in the extreme precipitation and flooding of the Midwest in spring 2019. How Earth’s forests, including those in the Midwest, will respond to increasingly volatile precipitation remains largely unknown. Given that forests provide numerous ecosystem services to humanity, understanding how and why forests will respond to changes in the amount and timing of precipitation is a necessary step for sustainable forest management in the face of global change. Here, we propose to examine bur oak responses to a combination of drought and high precipitation variability using precipitation manipulation experiments at Iowa’s Lakeside Laboratory. We will test the hypothesis that increased precipitation variability decreases photosynthetic capacity and growth, including quantification of the physical and physiological drivers of these responses.

Algal Blooms Detection and Forecasting through Smart an AI-Powered UAV System

Principal Investigator: Xun Zhou (UI Business Analytics) Co-PIs: Corey Markfort (UI Civil & Environmental Engineering) Ali Jannesari (ISU, Computer Science), Charles Stanier (UI Chemical & Biochemical Engineering)

Project Summary: Harmful algal blooms (HABs), those caused by toxin-producing blue-green algae (cyanobacteria), significantly reduce water quality as well as recreational and ecological value of lakes. HABs degrade fisheries, are a direct health concern for humans through drinking water and contact recreation, and can be lethal for pets, livestock, and waterfowl. HABs may form in large and smaller lakes, wetlands, and farm ponds. HAB events have increased in occurrence in recent years. Yet, little information is available on what factors trigger an outbreak or why a HAB may occur at one lake and not at another. To address these challenges, we propose to develop a novel solution that integrates the latest artificial intelligence (AI) techniques, UAV systems, and dynamical simulation models to jointly and smartly plan, sample, and predict HABs for more accurate and timely decision making.