Earth, Oceans, and Space REU Program

Marine microbes cover a diversity of organisms that account for more than 98% of ocean biomass. They are fundamental for oceanic food webs and thus ecosystem function and services. Research within the Ocean Process Analysis Laboratory aims to understand microbial and biogeochemical processes and their role in the cycling of growth-limiting nutrients (e.g., nitrogen and phosphorus) as well as organic and inorganic carbon in marine environments. REU students will be involved with field measurements in the Gulf of Maine and its estuaries, and with laboratory research focusing on microbial growth and metabolic rates along with carbon chemistry, and how these rates and parameters are affected by anthropogenic stressors such as ocean acidification, sea surface warming, and ocean pollutants (e.g., microplastics, spilled oil). Students will gain skills in marine sensor deployment, lab incubation methods, and statistical data analysis.

Mentor: Dr. Kai Ziervogel

Acoustic waves can be a powerful tool to learn about our oceans. The Acoustic Characterization and Experimentation (ACE) Lab employs a wide range of physics-based field, laboratory, and modeling methodologies to extract useful information from underwater sound to learn more about underwater ecosystems, particularly those that live on the seabed (i.e. seagrasses). Depending on your interests, you may choose between projects that contain big data, coastal field work, or laboratory work using real acoustic sensors and statistical/machine learning signal processing techniques. 

Mentor: Dr. Gabriel R. Venegas

Eelgrass plays a pivotal role in improving water quality. Despite significant reduction in pollution, inorganic (e.g., nitrogen) and organic materials being released from wastewater treatment plants across municipalities, eelgrass coverage of the Great Bay Estuary has decreased over the last decades. Emerging floating seaweed coupled with invasive species further restricts their growth, reproduction, and survival. As a part of an ongoing project funded by Environmental Protection Agency (EPA), the main objective of this summer project is to gain key factor(s) controlling on eelgrass through comprehensive measurements and analyses using optical, physical, biological, and biogeochemical variables. Together with remote sensing data, this will guide us to improve the present eelgrass situation by enhancing our understanding of eelgrass relevant processes from a point-base to a broader spatial scale. Interns will be directly involved in various activities including boat trips, tank experiments, lab work, and data analysis.

Mentors: Atsushi Matsuoka and Lara Martin

Marine pathogens spread quickly and can decimate important coastal ecosystems like seagrass meadows and coral reefs. The loss of ecosystems impacts coastal communities and economies that rely on these marine organisms and their ecosystem services. In this project, students will explore how the flow of water can drive the spread of these diseases, either by causing plant-to-plant contact in seagrass meadows or by transporting tissue fragments or sediment between diseased corals. This project will involve synthetic physical systems and a laboratory flume, or mathematical modeling of marine epidemiology. Possible skills students will develop include 3D solid modeling or 3D printing, quantitative imaging, mathematical modeling, and data analysis.

Mentor: Dr. Tracy Mandel

Winter is the fastest warming season across most of the United States, with New England emerging as a winter warming hot spot. In this summer REU project, we will explore historical and future climate projections of winter climate indicators relevant to ecosystems and society. Data analysis will include observations from long-term sensors and comparison with gridded model output. REU students will learn how to approach big data from multi-model climate ensembles and generate data visualizations relevant to interest holders in wildlife management, outdoor recreation, forestry, or more!

Mentor: Dr. Elizabeth Burakowski

Our technology-driven society is dependent upon satellite technology for communication, navigation, and national security, as well as upon a reliable power grid for everyday needs such as money transactions, job functions, and food storage. These infrastructure systems are vulnerable to geomagnetic activity, when charged particles in the space surrounding Earth are energized and transported due to energy input from the Sun. Researchers in the Space Science Center use satellite- and ground-based sensor data to study the particles and fields in this region of space. Emerging machine-learning methods are being tested to evaluate their ability to use these datasets to model geomagnetic storms and predict when these events could cause power outages and other disruptions. REU students in the Space Science Center will conduct a project that incorporates one or more of these data sets. Skill development may include satellite and/or ground data processing, data visualization, and machine learning methods.

Mentor: Dr. Amy Keesee