Oyster Aquaculture

Oyster Aquaculture Research

High-precision research on environmental stressors, genetics, and the microbiome to improve Maryland oyster aquaculture yields

PI: Dr. Allison Tracy (Institute of Marine and Environmental Technology, University of Maryland Baltimore County/ University of Maryland Baltimore)

Co-PIs: Dr.  Jillian Bible (Washington College) and Dr. Emily Rivest (Virginia Institute of Marine Science)

Duration: June 2024 to January 2026

Cost: $124,555

Description: Oyster aquaculture is a rapidly growing industry globally and in the Chesapeake Bay. Oyster farms benefit from the natural environment, including a free food supply and many other features that are production costs for on-land aquaculture operations. However, some aspects of that natural environment threaten production, like poor water quality and disease. This project aims to support aquaculture in the state of Maryland by improving knowledge of how oysters respond to variable environmental conditions.

This study aims to characterize environmental impacts on oysters by comparing oyster performance across sites with co-located water quality data. We will outplant juvenile oysters at four sites in Maryland and four sites in Virginia from June 2024 to May 2025. All oysters come from the LOLA genetic line, popular in Maryland for improving disease resistance at low salinity sites. The study includes both diploid and triploid LOLA oysters to test the effect of ploidy on performance. The first objective is to compare the survival and growth of oysters at sites with co-located water quality data on temperature, salinity, pH, dissolved oxygen, water clarity, and carbonate chemistry. 

With the assistance of high school students and teachers, and undergraduate researchers, survival, growth, and water quality metrics will be collected at all eight sites every two weeks over the 11-month deployment. In addition to assessing water quality, we will assess how differential survival and growth at the eight sites relate to the community of bacteria living in oyster guts. Researchers will collect the oysters in May 2025 to sample gut bacteria and collect additional metrics of oyster health, including size, body condition, and infection with the damaging parasite that causes Dermo disease. They will use bacterial DNA in oyster guts to identify types of bacteria associated with high survival and growth necessary for positive production outcomes.

The project could benefit the aquaculture industry and the state of Maryland. An improved understanding of environmental impacts on oyster production could help reduce the risk of mortality events by informing oyster breeding, farm practices, and regulatory decisions. PI Allison Tracy notes, “We’re collecting data that will give us more information on the causes of slow growth and mortality events, paying attention to both detailed water quality data and features of the oysters themselves.” In addition to the economic benefits that aquaculture could bring to Maryland in the future, oysters improve the ecosystem around them by filtering water and reducing nutrients, for example. Given the relevance to many stakeholders, this study includes an engagement plan to interact with the aquaculture communities in Maryland and Virginia and to inform diverse audiences.

Optimizing Oyster Setting for Maximum Results

PIs: Dr. Louis Plough (University of Maryland Center for Environmental Science Horn Point Laboratory) and Alex Golding (Ferry Cove Shellfish)

Co-PIs: Kelly Barnes (Maryland Seafood Cooperative)

Duration: April 2024 to Dec. 2025

Cost: $35,000

Description: The State and commercial businesses spend millions of dollars annually to plant billions of oyster spat-on-shells in Maryland’s portion of the Chesapeake Bay to support public fishery, aquaculture, and restoration projects. Yet the actual process of creating the spat on shell (SOS) is far from being optimized and fully understood. Growers see a wide variability in setting distribution, resulting in increased production costs and lower long-term oyster survival. Due to the extreme variation in setting, this project hopes to identify and reduce the major variability that occurs in the current oyster setting processes. The proposal will look at a multitude of factors that could impact setting distribution to determine the preferred process to achieve a variance of five to 15 oysters per shell.

“This proposal will examine primarily how light and aeration play a role in the setting process,” said Alex Golding, who will lead the research at Ferry Cove Oyster Hatchery located in Sherwood, Md. “Growers produce millions of spat each season, yet no one really knows the most effective setting process to yield the maximum results. We hope to improve that.” Working with the University of Maryland Center for Environmental Science researchers and in partnership with the Maryland Seafood Cooperative’s setting facility, Ferry Cove Shellfish will be conducting numerous setting trials over the summer and will be publishing its findings.

Improving oyster aquaculture site selection: Getting rid of the guesswork


PI: Matt Parker (University of Maryland Extension)

Co-PIs: Don Webster (UMD Extension), Jeremy Testa (University of Maryland Center for Environmental Sciences), Suzanne Bricker (NOAA Cooperative Oxford Lab)

Duration: June 2023 to May 2025

Grant: $99,792

This project will use an oyster bioenergetics model to determine optimum growing conditions for Maryland oysters based on water quality at potential lease sites. It gets “rid of the guesswork” when it comes to finding suitable locations for aquaculturists seeking a place to grow oysters.

This study is being led by Dr. Matt Parker of the University of Maryland Extension, along with Don Webster of the University of Maryland Extension, Dr. Jeremy Testa of the University of Maryland Center for Environmental Sciences, and Dr. Suzanne Bricker of the NOAA National Centers for Coastal Ocean Science.

Users of the tool this study creates will be able to get information from publicly available data sources such as Maryland’s Eyes on the Bay. Along with variables such as temperature and salinity ranges, users will be able to enter values to estimate food abundance in proposed leases. To evaluate sites, the tool will include other variables, such as bottom type and distance from land-based facilities. Based on user inputs, potential leases will receive a numerical score that can be compared between sites to estimate which is better to grow oysters. 

The team will start the project in the summer of 2023. Orchard Point Oyster Company and Ferry Cove Shellfish have agreed to be industry partners to field test the tool and provide user feedback.

Advanced machine learning of factors for improving oyster hatchery production

PI: Vyacheslav Lyubchich (University of Maryland Center for Environmental Sciences)

Duration: July 2022 to June 2024

Grant: $99,033

Description: The demand for reliable spat production from oyster hatcheries has risen in recent years with the onset of Chesapeake Bay oyster restoration and the rise of the Bay’s oyster aquaculture industry.

Oyster hatcheries are facilities where adult oysters are spawned, and spat is grown and later sold for use in the aquaculture industry, fisheries augmentation, or restoration efforts. Despite highly skilled and experienced staff running hatcheries, there are periods of poor larval growth and uneven production levels (also termed ‘crashes’). These crashes affect hatchery profitability and become a bottleneck in the supply chain for private oyster growers, consumers, and state entities that manage natural resources. In most cases, the causes of crashes and their potential remedies are unidentified.

This project is being performed by the University of Maryland Center for Environmental Sciences researchers Drs. Vyacheslav Lyubchich, Matthew Grey and Greg Silsbe. It aims to process large amounts of hatchery and environmental data to identify conditions leading to hatchery inefficiencies and strategies for mitigating their impacts on production. The hatcheries are heavily influenced by environmental conditions in the coastal zones where they are located. The water is taken from the environment and, after more or less thorough processing (such as filtering, heating, or cooling), is used for growing oyster larvae. This project proposes to use machine learning techniques to identify patterns in the data; between hatchery production outcomes and factors such as water quality, atmospheric conditions, and implementation of agricultural fertilizers and herbicides upstream from the hatchery. This extensive data analysis will help in finding the causes of the crashes and will allow managers to stay informed about the potential success of the production. With this knowledge, the managers will be able to focus on manipulating specific variables to improve production outcomes.