Our overall goal is to is to is to gain insight into the basic biology of Craspedacusta in order to better predict its ecological impact in response to climate change. In particular, we are interested in the following questions:

1. What are the environmental cues for Craspedacusta jellyfish blooms and can these cues predict when and where Craspedacusta blooms will occur in southern Lake Michigan?
2. Can these conditions be replicated in a laboratory environment to induce jellyfish formation?
3. Are the genetic mechanisms that control jellyfish blooms in Craspedacusta similar to that of their marine relatives, and thus likely to have a parallel response to climate change?

To address these questions we have three primary objectives:

1. Determine environmental parameters required for jellyfish blooms through field work and citizen science approaches;
2. With the involvement of undergraduates we will design and conduct laboratory experiments utilizing environmental parameters and zooplankton composition data from objective 1, with the intention of culturing Craspedacusta medusae to their reproductive stage.
3. Conduct transcriptional analyses to document differential gene expression in the different life cycle stages to determine the genetic cues for life cycle transitions. 

We have a fourth objective to improve scientific literacy on invasive aquatic species though developing educational modules with live Craspedacusta jellyfish for the public, K-12 classrooms, focusing on underserved communities.

Aquaponics food production systems produce more food on less land, using less water than conventional food production systems. Further, they can be located near population centers, diminishing the carbon footprint of long-distance transportation of foods. Fresh food supplies in urban cities in the US takes advantage of the developing trends among consumers seeking sustainable, fresh, locally grown food supplies. Marine aquaponic systems are capable of producing fresh seafood and plant crops with high market value and strong consumer demand, but few species combinations have been developed well enough for practical applications. In this project, we propose continuing our ongoing efforts to explore marine aquaponics and provide operational guidelines for successful production.

Objective 1 – Complete our developing list of salt-tolerant plant species with a focus on seed availability, recommendations for germination, growth rates, and chemical composition data;
Objective 2 – Evaluate the long-term sustainability of a shrimp/plant marine aquaponic system, and evaluate salinity tolerance of 3-6 halophytic plant crop in marine aquaponics systems; and,
Objective 3 – Determine characteristics of the Asian markets in Chicago for products from marine aquaponic FPS and estimate total poundage of market demand.

The main project objective is to empower underserved students by directly involving them in innovative Great Lakes-based antibiotic discovery and providing exposure to careers in the environmental and biomedical sciences. Our team is uniquely suited to integrate community-based education into advanced, technology-driven problem solving in a remote or hybrid environment. Importantly, our program will allow students in afterschool programs like the Boys and Girls Club to go beyond workbook science and into real world problem solving. 

Aim 1. Supervised sample collection from the Chicago River and Lake Michigan lakefront.
Aim 2. High-throughput robotics to build a library of bacteria from their samples.
Aim 3. High-throughput robotics to test bacterial libraries against the human pathogens Pseudomonas aeruginosa and Staphylococcus aureus.

Short-term outcomes

1. Determine the capacity of bacteria derived from the Great Lakes to produce novel antibiotic leads via environmental collection, bacterial library generation, and screening against pathogens.
2. Assemble and educate up to 20 middle school students over the course of the project period (broken down into two student cohorts, ~7-10 students per year).
3. Engage the student cohorts in multiple steps of Great Lakes-based antibiotic discovery.
4. Expose the student cohorts to weekly exercises that focus on environmental problems facing the Great Lakes.
5. Expose the student cohorts to possible careers in STEM-based Great Lakes research via weekly guest career talks.

Long-term outcomes

1. Discover and develop locally sourced antibiotics via spectroscopic identification and in depth biological profiling experiments.
2. Expand our university-community partnership to other Chicago area BGC’s. 
3. Acquire NSF funding to expand to up to five additional clubs and engage large numbers of youth in a pipeline toward STEM careers based on topics important to Great Lakes health.
4. Disseminate the blueprint of our university-community partnership via detailed open-access publications, conference presentations, and other media promotions to the greater academic world and inspire the creation and improvement of similar programs nationwide.

Nitrogen contamination in groundwater of the Southern Lake Michigan region endangers both the potability of well water in the region and contributes a source of ‘legacy nitrogen’ to the surface waters of the southern Lake Michigan region. Using a data-driven approach leveraging machine learning and GIS, this graduate student scholars project will for the first time provide an estimate of how much nitrate is stored within the aquifers of the Upper Mississippi River Basin and Lake Michigan watersheds.

The overarching goal of this graduate student scholars project is to better evaluate the effects of small dams and reservoirs on changing the flow of nutrients to downstream water bodies and water quality across Lake Michigan Watersheds. There are two primary objectives associated with this goal: (1). Small reservoir identification through a combination of remote-sensing and deep-learning approaches and reservoir dataset development with associated information (reservoir location, surface area, storage volume, catchment drainage area, and residence time). 2). Using hydrologic modelling and USGS water quality data collected above and below reservoirs to quantify the spatially and temporally varying effects of small reservoirs on water quality (nutrient runoff and retention). This proposed research is of pressing concern due to increased release of legacy contaminants to surface and groundwater around Lake Michigan.

Aquatic invasive species pose a serious threat to aquatic ecosystems. In the Great Lakes, new fish species that are non-native to the environment have been introduced due to transoceanic activities. These species compete with native species causing a heavy toll on the environment and economy by shifting ecological balances and disrupting food chains. While many methods exist to sample fish, due to the increasing availability of underwater video, fish can now be sampled by crowd sourcing or using Image recognition techniques. These methods have highlighted the challenges associated with identifying fish based on their appearance against a cluttered background. This graduate student scholars project aims to identify and model fish behavior in underwater video using machine learning methods that are suited for classification of classification of time series data. Video data of round goby (Neogobius melanostomus) from literature will be used to test the approach. The methods proposed here will significantly increase the usability of existing datasets and enable the creation of life-like animations for use in virtual training environments.