Source: UNIVERSITY OF MARYLAND BALTIMORE COUNTY submitted to
A TARGETED FIELD SURVEY OF PARASITES ON OYSTER AQUACULTURE FARMS IN THE CONTEXT OF THE NATURAL ENVIRONMENT
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
NEW
Funding Source
Reporting Frequency
Annual
Accession No.
1032328
Grant No.
2024-67015-42418
Project No.
MD.W-2023-07930
Proposal No.
2023-07930
Multistate No.
(N/A)
Program Code
A1221
Project Start Date
Sep 1, 2024
Project End Date
Aug 31, 2026
Grant Year
2024
Project Director
Tracy, A. M.
Recipient Organization
UNIVERSITY OF MARYLAND BALTIMORE COUNTY
1000 HILLTOP CIRCLE
BALTIMORE,MD 21250
Performing Department
(N/A)
Non Technical Summary
Oyster aquaculture farms are often sited in the natural environment because there is a free food supply for oysters, among other benefits, but the environment also includes diseases and stressors that threaten seafood production. Eastern oysters are infected by the notorious dermo diseaseas well as bio-eroding worms that burrow into oyster shells. As in many aquaculture settings, Chesapeake Bay includesboth wild and farmed oyster reefs that may be impacting each other, but there is little information on the potential for wild-to-farm disease transmission. Additionally, although climate change makes the watermore acidic and hinders oyster shell formation and repair, there is a poor understanding of how climate change will affect oyster suseptibility tobio-eroding worms.The goal of this study is to address these knowledge gaps onhow the naturalenvironmentaffects oyster health on aquaculture farms. We will collect oysters from farms in fall and spring over two years and assess oyster health by rating body condition and diagnosing each oyster for dermo and shell bio-eroding worms. We will test how oyster body condition and shell infestations depend on the proximity of farms to wild reefs, infections with dermo, and environmental conditions likely to shift under climate change. In addition to surveys, the project will include collaborating with and disseminating information to relevant stakeholders in Chesapeake Bay and the broader region. The results of this project will fill critical knowledge gaps about wild-to-farm disease transmissionand stressors related to climate change, thus helpingresearchers design future experimentsto better understand drivers of oyster disease on aquaculture farms. Our findings will help the oyster aquaculture industry make decisions to increase production byreducingthe impact of stressors, including siting farms in less stressful locations. In the long-term, building the knowledge base on where and how stressors affect oysters cansupport industry adaptations to climate change. Safeguarding aquaculture production with science-based decisions will support an economically valuable industry that provides healthy, wild seafood choices to a growing human population.
Animal Health Component
100%
Research Effort Categories
Basic
60%
Applied
40%
Developmental
0%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
3113723107075%
3113723111015%
3113723106010%
Goals / Objectives
The goals of this project are to increase sustainability of oyster aquaculture farms using novel data on parasite transmission, to provide an improved understanding of physiological trade-offs in oysters infected with multiple parasites, and to build climate change scenarios for bio-eroding oyster parasites that will inform climate change adaptation. We will work towards these long-term goals through three objectives: (1) Test whether connectivity to wild oyster reefs is linked to bio-eroder parasite impacts on oyster farms, relative to other environmental conditions and farm practices; (2) Assess body condition trade-offs in oysters co-infected with bio-eroders and P. marinus; and (3) Determine linkages between bio-eroders and climate-relevant parameters.
Project Methods
Objective 1:We will sample oysters at nine aquaculture farms over two years to determine how the environmental context of farms influences oyster bio-eroders, and thus oyster health and production. The nine farms consist of three farms in each of three tributaries that run north to south along the west coast of the Chesapeake Bay: the South River, the Patuxent River, and the St. Mary's River. These tributaries were selected because they represent a variety of bio-eroder impacts according to our previous studies, as well as a range of salinities, oyster densities, and infection intensities with P. marinus.We have identified the farm leases that are the best candidates for the proposed research in each tributary using the Maryland Aquaculture Siting Tool and show the St. Mary's as an example. In each tributary, the three farms occur in three distinct regions of the tributary with different salinities and range from having few adjacent wild reefs to many. Taken together, the nine farms are likely to cover a range of bio-eroder infection prevalence and intensity. These 9 farms are also well suited for this study because they are in proximity to long-term Maryland Fall Survey sites, allowing us to use the state survey parasite data from relevant wild oyster populations.We will sample 25 oysters, a standard sample size, from each of the nine farms by randomly sampling adult oysters approximately 60 mm in length at four timepoints: fall 2024 and spring 2025, fall 2025 and spring 2026 (N=450 in Year 2). Sampling in multiple years and seasons will allow us to test a metric of connectivity between oyster farms and wild reefs and evaluate the consistency of the relationship. For the connectivity metric, we will calculate the percent of water area made up of wild reefs within two distances (1 km and 2 km) for each aquaculture farm, using the NOAA GIS layer of reef bottom in Chesapeake Bay. We will calculate a parasite connectivity metric using the Maryland Fall Survey results on bio-eroder presence and absence in the focal tributary to estimate bio-eroder impact from reefs within 1 km and 2 km. We will also collect data on farm practices, such as desiccation or brining.We will diagnose infection with Cliona sponge using the characteristic small circular burrows on the shell exterior and will estimate intensity as the areal coverage of burrows. For Polydora worms, we will diagnose the presence of mud blisters and quantify intensity in ImageJ as the percent area of the shell occupied by blisters. We currently use these techniques and are confident in their feasibility, accuracy, and affordability. Shells can be dried and preserved indefinitely. In addition to oyster collections, we will use a YSI meter to collect day-of environmental data, including salinity, temperature, dissolved oxygen, and pH, and characterize bottom type from the sample matrix. We will use linear and generalized linear models to assess connectivity of wild reefs, parasite connectivity, select farm practices, and environmental data as predictors of bio-eroder prevalence and intensity.Objective 2:All oysters sampled from the nine farms and four timepoints (N=900) will be diagnosed for infection with P. marinus. In brief, we will shuck oysters, score body condition using visual ratingsand dissect anal and rectal tissue for culture in Ray's fluid thioglycollate medium (RFTM) for 5 to 7 days. Tissue will then be macerated, stained with Lugol's iodine, and diagnosed for infection using light microscopy. We will rate infection intensities from rare to heavy using an eight-point scale. We currently use the RFTM method and are confident in its feasibility and effectiveness. Tissues and shells will be labeled to link P. marinus and shell infections for each oyster. We will then compare body condition scores in oysters with single and multi-parasite infections for Cliona sponge, Polydora worms, and P. marinus using ANOVA.Objective 3:We will complete Objective 3 by using generalized linear models to test environmental parameters (Objective 1) as predictors of bio-eroder prevalence and intensity. In addition, we will compare bio-eroder prevalence and intensity across the two seasons, with two sampling timepoints per season. Finally, we will test more detailed seasonal data as predictors of bio-eroder impacts using publicly available water quality monitoring data.