Final report for FNE24-091
Project Information
Clam farming is an important sector of New Jersey’s coastal economy. Recently, farmers have observed that clam growth rates varied across the state, and they hypothesized that varying levels of food availability across sites may be driving this trend. Once planted on shallow coastal farms, aquacultured clams rely exclusively on naturally occurring food, specifically phytoplankton and other small particles. The objective of this study was to assess the relative abundance, diversity, and phenology of phytoplankton communities across four farming locations to help inform aquaculture management decisions. In 2024 and 2025, surface water samples were collected at three hard clam growout sites, Middle Island Channel (MIC), Dry Bay (DB), and Great Sounds (GS), and a three-minute tow of a 20 µm plankton net was used to collect concentrated water samples at a shellfish hatchery, the NJ Aquaculture Innovation Center (AIC). In both years, particles between 20 and 200µm were processed using FlowCam to identify and enumerate phytoplankton in the clam farm samples, while a digital compound microscope was used to analyze water samples collected at the hatchery. In 2025, a Beckman Coulter Counter was used to examine particles <20µm. Among the four aquaculture habitats examined in this study, AIC consistently exhibited the highest and most stable phytoplankton diversity, yet diversity was moderate or high (Simpson Diversity Index 0.6-0.8) at the other three sites throughout much of the sampling period. The dominant constituents of the phytoplankton community composition were diatoms that broadly co-occurred across the four sites. Diatom blooms were most pronounced at GS and MIC. GS and MIC were also the two locations that exhibited the most similar community composition. In the absence of blooms, all four sites exhibited comparable concentrations of diatom and dinoflagellate taxa. Likewise, no clear differences in small particles (2-42 µm) concentrations were observed across the three clam grow-out sites. Taken together, these findings suggest that food availability is generally similar across all four of the study sites and is unlikely to be the primary cause of the observed differences in clam performance across the NJ coast. Future projects should further examine the structure of phytoplankton communities and connect food availability with farmed bivalve performance metrics, such as growth and gut contents.
The objective of this study was to evaluate phytoplankton community trends across four New Jersey aquaculture sites. Specifically, the diversity, relative abundance, and phenology of key phytoplankton taxa were assessed. The goal of this study was to better understand bivalve food availability and determine if this could be a plausible explanation for differential hard clam (Mercenaria mercenaria) growth rates that have been observed by farmers across the state.
As a family business established in 1909, Parsons Seafood and Mariculture has over a century of practical experience devoted to the farming and harvesting of bivalves in waters local to Tuckerton, NJ. Extensive knowledge of aquaculture farming practices allows 5th generation owner, Dale Parsons, to adjust planting and harvesting routines based on a multitude of conditions including but not limited to weather, water characteristics, and tidal patterns. This ability to modify practices based on farmer knowledge and hands-on experience has allowed the Parsons business to flourish and become a multifaceted enterprise while remaining connected to the generations that came before.
Although continuing to operate a successful multigenerational aquaculture business, it is evident that the growth rate of farmed hard clams, M. mercenaria, has decreased significantly in recent years. While planted clam seed do not seem to be experiencing a noticeable reduction in juvenile development there has been a remarkable decline in growth rate once clams begin to enter the size in which they would be considered mature. Not solely limited to the farmed leases that Parsons maintains, other aquaculture businesses local to the Tuckerton area and beyond have experienced a similar decrease in the rate growth for their clams. The reduction in growth directly impacts aquaculture farm profit as restricted growth results in less harvested clams available for the wholesale and retail market. If the rate of clam growth continues to decline, aquaculture farms in New Jersey may very well be compromised with the loss of their primary harvest species.
Having already experimented with altering various aspects of the aquaculture process, the question of what is influencing the apparent decrease in the growth of clams remains unanswered. A previous study in the same region resulted in findings that indicated a significant negative linear relationship between the growth of hard clams and the presence of cyanobacteria species (Fantasia, Bricelj, & Ren, 2017). Although this study was conducted in an area with close geographic relation to Parsons there is a profound lack of current knowledge regarding phytoplankton communities in waters surrounding the aquaculture farms involved in this study. Middle Island Channel and Dry Bay are located in adjacent waterways and have both experienced a continuous decrease in growth rates for clams while Great Sound, a waterbody located roughly 50 miles south, has exhibited consistency with hard clam growth rate. Sampling conducted during this pilot study will focus on analyzing the presence and differences of phytoplankton communities between Middle Island, Dry Bay, and Great Sound. Obtaining knowledge concerning phytoplankton communities in various water bodies will provide valuable information for potential additional studies surrounding the decrease in growth rate for hard clams. As stated through research performed by Sea Grant New York, “evidence suggests that hard clams are growing slower…than they did in the past, potentially due to brown tides…or changes in the plankton community due to variable plankton size and type” (2007).
With the findings of this study and studies that will potentially follow, aquaculture farmers that have experienced a continued decrease in the growth rate of their product may be able to mitigate the compromise of their businesses through alteration of their brood stock. If, among other factors, it is a possibility that the presence of specific communities of phytoplankton are hindering clam growth, aquaculture farmers will have a recent and thoroughly assessed collection of data indicating the concentration and location of where these species may be found. Without knowledge of what phytoplankton species are present in the water column there is not enough information available with which farmers can make an educated decision on where to place their focus when attempting to mitigate the decline in growth that has been noticed. Additionally, if analysis of samples taken during this study indicates that there are different densities of harmful or beneficial phytoplankton found in certain areas of the waterbody, changing the location of the farmed leases could prove to be advantageous. There are multiple approaches that shellfish farmers could pursue in efforts to continue the success of their business, but without the knowledge that this study will aid in providing it is impossible for an informed decision to be made. In short, finding out the “where?” “what kind?” and “how much?” regarding phytoplankton communities around aquaculture farms could effectively assist in the persistence of multiple threatened businesses.
Since 1909 Parsons Seafood operates a full-time, year-round shellfish farming business. Annually, we market between six and eight million clams and more than one million oysters, generating nearly $2 million in sales. Our operation employs approximately 12 full-time employees during the summer months and 8 full-time employees throughout the winter. The business operates 52 weeks a year and never closes.
The farming process begins with the selection of broodstock shellfish that have been carefully chosen for desirable traits such as growth rate, survivorship, shell shape, and shelf life. These broodstock are maintained on our farm and exposed to a variety of field conditions before being shipped or delivered for spawning during the winter months. To maintain genetic diversity and preserve regional adaptation, wild strains are periodically incorporated into our breeding program.
The resulting offspring, known as post-set shellfish, are raised in a land-based nursery system where they receive optimal nutrition through specialized tank and filtration systems. Once they reach an appropriate size, the seed is deployed onto several commercial shellfish leases authorized by the New Jersey Department of Environmental Protection.
On average, hard clams now require three full growing seasons to reach market size, whereas not long ago they could be harvested in less than two seasons. Oysters mature much more rapidly and may reach market size within months under favorable conditions, though they typically require less than two growing seasons.
Our shellfish are distributed throughout the eastern United States, with customers ranging from Maine to Florida. Through every stage of production—from selective breeding and nursery culture to grow-out and distribution—Parsons Seafood remains committed to producing a high-quality product while maintaining the long-standing traditions of New Jersey's shellfish industry.
Cooperators
- - Technical Advisor
- (Researcher)
- (Researcher)
- (Researcher)
Research
Sampling Locations and Procedures:
Water samples were collected from four aquaculture sites located in southern New Jersey. From north to south, the sites include Middle Island Channel (MIC), Dry Bay (DB), Great Sound (GS), and the Rutgers University New Jersey Aquaculture Innovation Center (AIC). Great Sound, Middle Island Channel, and Dry Bay are back-bay estuaries and contain numerous bivalve aquaculture operations, where clams and oysters are grown from seed (i.e., juvenile stages) to market size. The AIC is a public bivalve hatchery and nursey site where bivalves are reared from larvae to seed stages. Seed are grown in flow-through conditions, supplied with seawater from the Cape May Canal. At the bivalve growout sites (MIC, DB, GS), 1 L water samples were collected from the surface and immediately preserved with Lugol's iodine solution (1% final concentration). In general, samples were collected monthly or bimonthly from March to October in 2024 and 2025. Samples were stored in the dark at room temperature until final analysis. At the AIC, a 20 µm plankton net was used to collect concentrated water samples weekly to monthly between June and August in 2024 and 2025. To collect the AIC sample, a supply hose from the flow-through seawater system was set the 1.00 L/s, and a 200 L cylindrical tank was filled with seawater. The 20 µm plankton net then suspended in tank and the supply hose was inserted into the net for exactly three minutes, resulting in a 125 mL concentrated sample. AIC samples were immediately analyzed or stored in a 4˚C refrigerator for up to 24 hour before analysis occurred.
FlowCam Methods:
Preserved samples from MIC, DB, and GS were analyzed using FlowCam, a dynamic particle imaging microscope. To concentrate samples prior to FlowCam analysis, each 1 L sample was gently inverted to resuspend particles and then sequentially sieved through a paired stack of 200 µm and 20 µm screens. Particles captured on the 20 µm screen (i.e., particles 20≤x<200 µm) were then rinsed into a 50mL Falcon tube using 1 µm filtered seawater, producing a more concentrated sample. This particle size range was selected because it includes the size range of particles that clams can capture with 100% efficiency (Riisgard, 1988), while also facilitating ease of use with the FlowCam. In both 2024 and 2025, all materials retained by the 200 µm screen were discarded. In the first sampling year (2024), effluent of 20 µm screen was discarded; however, in 2025, particles that fell through the 20 µm screen were analyzed using a Beckman Coulter Counter (see below).
FlowCam imaging was conducted using a 4x objective lens (40x magnification) and a 300 µm field of view flow cell (FC300-FV). Samples were analyzed using a 5 mL syringe at a flow rate of 0.40 mL/min with a total imaged sample volume of 1.0 mL per triplicate run. Images were captured at a rate of 10 frames per second. Image capture parameters include an equivalent spherical diameter size filter of <400µm and a nearest neighbor distance of 10 µm. Each sample was run through FlowCam in triplicate. Cross-contamination was highly monitored. The system was flushed between triplicate sample measurements and thoroughly cleansed between sampling sites. For each sample, phytoplankton analysis was conducted by visually inspecting the data, sorting the resulting images by size and morphology, and using automated FlowCam library filtering methods. Taxonomic identification was performed to the lowest taxonomic level for diatoms (N= 17 taxa), dinoflagellates (N=10 taxa), and other phytoplankton clades (Table 1.). The total number of individuals in each phytoplankton group were averaged across triplicate subsamples. A correction factor was then applied to these values to determine the relative abundance of each taxa that would be present in the original, unconcentrated samples.
Compound Microscopy Methods:
For compound microscopy, preserved or live samples taken at the AIC were gently inverted to resuspend phytoplankton cells before analysis. For each sampled, triplicate 100 µL subsamples were placed onto a gridded slide, and a 10x objective lens (100x magnification) was used to identify live phytoplankton cells. Detailed identification was conducted at a 100x objective lens (1000x magnification). Phytoplankton were identified to the lowest possible taxonomic groups, including diatoms (N= 17 taxa), dinoflagellates (N=10 taxa), raphidophytes, cyanobacteria, and other planktonic organisms, with a focus on the following list of species (Table 1). The total number of individuals in each phytoplankton group were averaged across triplicate subsamples. A correction factor was then applied to these values to determine the relative abundance of each taxa that would be present in the original, unconcentrated seawater. Representative images of observed taxa were photographed for documentation and verification.
Coulter Counter Methods:
Preserved water samples collected from MIC, DB and GS in 2025 were processed through a Beckman Coulter Counter Multisizer 4e, a type of flow cytometer that can rapidly analyze the concentration and size distribution of particles suspended in water samples. The system is set to analyze particles within a size range of 1.67 µm to 42 µm.
Before the samples were run through the Coulter Counter, the preserved samples were screened through a 20 µm screen to remove any large particles that could blocking the system’s aperture. Particles larger than 20 µm were analyzed using FlowCam (see above). Samples were gently inverted to resuspend particles before triplicate 20 mL subsamples were pipetted into 20 mL cuvette sample beakers. The electrolyte used within the system was 28 ppt treated seawater filtered through a 0.1 µm filter. Resulting cell density (concentration, particle/mL) and particle size distribution data were averaged across the triplicate subsamples to produce a value for each sample.
Analysis
Processed data from both methods were entered into Microsoft Excel for organization and cleaning, then transferred to RStudio (Version 2025.05.1+513) for statistical analysis. We utilized the Simpson Diversity Index to assess biodiversity and community structure across sampling sites. Results were visualized as time-series for the diversity and relative abundance datasets and as pie charts for the taxonomic dataset. For graphs depicting cell concentration, the y-axes are labeled as cells per liter to represent the probable composition of phytoplankton in the natural environment, accounting for sub-sampling of the original water volume.
Table 1. Target taxa enumerated in samples collected at four NJ aquaculture sites
|
Clade |
Taxon |
|
Clade |
Genus/ Taxon |
|
Diatom |
Miscellaneous Diatom |
|
Dinoflagellate |
Miscellaneous Dinoflagellate |
|
Diatom |
Actinoptychus |
|
Dinoflagellate |
Akashiwo sanguinea |
|
Diatom |
Asterionellopsis |
|
Dinoflagellate |
Alexandrium spp. |
|
Diatom |
Chaetoceros |
|
Dinoflagellate |
Dinophysis |
|
Diatom |
Coscinodiscus |
|
Dinoflagellate |
Margalefidinium |
|
Diatom |
Guinardia |
|
Dinoflagellate |
Prorocentrum spp. |
|
Diatom |
Navicula |
|
Dinoflagellate |
Prorocentrum cordatum |
|
Diatom |
Nitzschia |
|
Dinoflagellate |
Prorocentrum reticulatum |
|
Diatom |
Paralia |
|
Dinoflagellate |
Tripos furca |
|
Diatom |
Pleurosigma |
|
Dinoflagellate |
Tripos fusus |
|
Diatom |
Pseudo-nitzschia |
|
Dinoflagellate |
Tripos longipes |
|
Diatom |
Raphid Pennate Diatom |
|
|
|
|
Diatom |
Rhizosolenia |
|
Raphidophyte |
Misc_Raphidophyte |
|
Diatom |
Skeletonema |
|
Raphidophyte |
Chattonella |
|
Diatom |
Thalassionema |
|
Raphidophyte |
Heterosigma |
|
Diatom |
Thassaloria |
|
|
|
|
Diatom |
Licmophora |
|
Ciliate (microzooplankton) |
Tintinnid |
|
Diatom |
Ondetella |
|
|
|
|
|
|
|
|
|
Across the two-year study period, all sites generally exhibited phytoplankton communities with medium to high diversity (Simpson Diversity Index >0.50) throughout most months of the year. Less than 15% of samples (N=8/60) across had a Simpson Diversity Index value below 0.50, and only one sample fell below 0.25. AIC showed more consistent and higher diversity compared to the clam grow-out sites (Simpson Diversity Index X-X). The clam grow-out sites showed greater community variability within and across years, yet the directionality of fluctuations in phytoplankton community diversity were observed across the three clam grow-out sites. Although sometimes offset by a few weeks, similar cyclical trends in phytoplankton diversity were detected across the three sites.
Diatom relative abundance varied across site, month, and sampling year. Diatom blooms, as defined as exceeding the 75th percentile of the dataset for a particular site, were observed in the spring and fall of both years, yet blooms were not observed at all sites. GS and MIC exhibited the largest diatom relative abundances, with some samples nearly reaching 10,000 cells/L. At GS the largest diatoms relative abundances were observed in the spring (April 2024 and May 2025) and the fall (September 2024 and September 2025), with the fall values matching or exceeding the spring values. At MIC, the largest annual diatoms relative abundances were observed in March of 2024 and 2025. No fall peak in diatom relative abundance was detected at MIC in either year, yet a diatom bloom was observed in July 2025. Diatom relative abundance was low and stable at DB, rarely exceeding 1,500 cells/L. At AIC, diatom relative abundance was low and stable in 2024, and while the AIC exhibited greater diatom relative abundance in 2025, values in this dataset never exceeded 3,000 cells/L.
In general, dinoflagellate relative abundance was relatively low across all sites, rarely exceeding 100 cells/L. Dinoflagellate densities were consistently low at MIC and DB, with densities typically below 30 cells/L. In 2025, no dinoflagellates were observed at MIC or DB. In contrast, highest and most stable dinoflagellate relative abundances were observed at the two most southern sites, GS and AIC. Dinoflagellate blooms, where cell densities rose up to two orders of magnitude above baseline levels, were observed at both GS and AIC in July 2024, and at GS in May 2025.
Across all sites and both years, a relatively small number of diatom taxa dominated the samples, yet no single taxon ever exceeded 30% of the community composition at a site. Specifically, the diatoms Actinoptychus, Navicula, Nitzschia, and Rhizosolenia were among the most abundant taxa that were observed across all four sites. For example, Actinoptychus and Navicula ranked in the top five taxa at all four sites in 2024 and 2025, respectively. The community compositions at GS and MIC were the two most similar, especially in 2024 when these sites shared four of their top five most common taxa, with nearly identical proportions of Actinoptychus (GS: 28%, MIC: 24%), Rhizosolenia (GS: 15%, MIC: 13%), and Nitzschia (both 8%) recorded.
At AIC, the top five taxa composed 59% and 71% of the samples in 2024 and 2025, respectively. Three of the five most abundant taxa were shared across sampling years: Coscinodiscus, Asterionellopsis, and Pleurosigma. At DB, the top five taxa composed 83% and 80% of the samples in 2024 and 2025, respectively. Two taxa, Navicula and Nitzchia, were dominant in both years, with each ranging from 24-30% of the community composition. At GS, the top five taxa composed 73% and 69% of the samples in 2024 and 2025, respectively. In both years, Rhizosolenia and Navicula were stable and abundant. The proportions of Actinoptychus, Eucampia, and Nitzchia in samples decreased between 2024 to 2025, while the proportions of Coscinodiscus and Asterionellopsis increased. At MIC, the top five taxa composed 77% and 68% of the samples in 2024 and 2025, respectively. The proportions of Actinoptychus, Rhizosolenia, Pleurosigma and Navicula decreased from 2024 to 2025. In 2025, two unusual taxa were highly abundant at MIC. Licmophora, a stalked “biofouling” diatom, composed 20% of the phytoplankton community documented at MIC in 2025. Predatory ciliates known as Tintinnids were also constituted a large fraction of the plankton community at at MIC in 2025.
In 2025, the smallest size class of particles that bivalves can consume (~2-42 µm) were analyzed from samples collected at the three clam grow-out sites. Notably, data presented here represent all particles, not just phytoplankton particles. This includes inorganic particles (e.g., sediment) and other non-edible particles present in the samples. Overall, no clear seasonal trends were observed at any of the sites. At MIC, the density of particles in this size class typically ranged from 75,000-175,000 cells/mL, with particle densities falling below this level in May and September. At DB, the density of small particles was typically less than 100,000 cells/mL, although two peaks in small particle cell density, where concentrations exceeded 150,000 cells/mL, were observed in late June/early July and August. GS exhibited the lowest concentration of small particles, with concentration consistently below 125,000 cells/mL across all samples.
Among the four aquaculture habitats examined in this study, AIC consistently exhibited the highest and most stable phytoplankton diversity, yet diversity was moderate or high at the other three sites throughout much of the sampling period. Diatom blooms were most pronounced at GS and MIC. Moreover, these two locations exhibited the most similar community composition. Interestingly, both GS and MIC are heavily influenced by inlets, where significant tidal flows connect the Atlantic Ocean to their estuaries.
In the absence of blooms, all four sites exhibited comparable concentrations of diatom and dinoflagellate taxa. The dominant constituents of the phytoplankton community composition were diatoms that broadly co-occurred across the four sites. Likewise, no clear differences in small particles (2-42 µm) concentrations were observed across the three clam grow-out sites. Taken together, these findings suggest that food availability is generally similar across all four of the study sites.
However, further study is required in order to more thoroughly understand the relationship between phytoplankton availability and farmed bivalve performance. Phytoplankton quality, not just quantity, is an important element of bivalve growth and survival. Different phytoplankton species exhibit distinct nutritional profiles and microhabitats around farms can locally influence phytoplankton dynamics at timescales not captured in this study. Furthermore, although phytoplankton may be present at a site, it does not necessarily mean that they are being consumed by the bivalves there. Future studies should examine not only the phytoplankton dynamics at bivalve farms, but also the gut contents and growth of bivalves present on those farms.
Education & outreach activities and participation summary
Participation summary:
This project led to a series of education and outreach activities. Data from the project was presented by student intern, Dakarai Lindsay, at the Research Internship in Ocean Science Symposium, a capstone event of the NSF-REU funded internship at Rutgers University. D. Lindsay also presented this work at the annual conference of the Mid-Atlantic Chapter of the American Fisheries Society.
Data from this project is also being used to develop a Farmer Factsheet, that describes the characteristics of local phytoplankton species that clam and oyster farmers may encounter on their farms.
Additionally, this project inspirited the inaugural Rutgers Mini Microalgae Course, where local farmers attended a three-day workshop to learn the basics of growing microalgae. During this course, participants also learned about the wild phytoplankton that may inhabit their shellfish farms. https://acquafreddalab.rutgers.edu/courses/courses-for-shellfish-growers/
Finally, results from this project will be shared with the broader NJ bivalve farmer community through a Rutgers Aquaculture Growers Forum. At this forthcoming seminar, aquaculturists will learn about the diversity, relative abundance, and phenology of phytoplankton that were detected at the study sites. Farmers who attend this event will learn more about the types of food their clams and oysters are feeding upon.
Learning Outcomes
Historically, shellfishermen could only assess potential food availability for shellfish based on the color and density of what they perceived to be a productive bloom. Under certain circumstances, particularly during blooms of non-beneficial phytoplankton species, they could only speculate as to why clams or oysters were not performing as expected.
With a better understanding of phytoplankton composition and the ability to more closely monitor conditions within targeted aquaculture areas, farmers can make informed management decisions based on actual conditions rather than observation alone. This knowledge can improve farm efficiency, enhance production, and potentially reduce losses associated with poor growing conditions or harmful algal blooms.
Project Outcomes
Historically, shellfishermen could only assess potential food availability for shellfish based on the color and density of what they perceived to be a productive bloom. Under certain circumstances, particularly during blooms of non-beneficial phytoplankton species, they could only speculate as to why clams or oysters were not performing as expected.
With a better understanding of phytoplankton composition and the ability to more closely monitor conditions within targeted aquaculture areas, farmers can make informed management decisions based on actual conditions rather than observation alone. This knowledge can improve farm efficiency, enhance production, and potentially reduce losses associated with poor growing conditions or harmful algal blooms.
Parsons Seafood has also pioneered the recycling of shell material to enhance depleted oyster reef habitat throughout southern Barnegat Bay. This emerging understanding of phytoplankton dynamics may allow for a more targeted approach to reef restoration as a whole. With a greater understanding of phytoplankton composition and concentration, funding agencies and resource managers can better evaluate restoration opportunities throughout Barnegat Bay and prioritize sites with the highest potential for success.
In practical terms, if the available food sources within a given area can be identified and quantified, it becomes possible to strategically introduce the appropriate filter-feeding shellfish to improve both habitat quality and water conditions. This creates a more informed and adaptive approach to restoration, linking water quality, food availability, and shellfish growth in a more precise and effective way.
Overall, the methods used in this study were effective for addressing the questions set forth by the project team. FlowCam and compound light microscopy were both highly useful tools for determining the identity of phytoplankton species in water samples. The smallest size class of edible particles for bivalves (2-20µm) were only examined in 2025 samples, and the organic content and identify of particles in this size class were not assessed. Future work should ensure that both small particles (2-20µm) and larger particles (20-200µm) are thoroughly analyzed in order to elucidate the full community of phytoplankton food available to farmed bivalves.
This study provides much needed information about the types of phytoplankton present on NJ bivalve farms, as well as the phenology and relative abundance of those species. However, this study was not able to connect phytoplankton community structure to clam growth. More work is necessary to more fully understand how phytoplankton dynamics may be affecting the growth rates of hard clams and other farmed bivalves. To address this further, future studies should not only monitor phytoplankton on bivalve farms, but also monitor bivalve growth rates on farms and examine gut contents and excrement.
Project partners are actively investigating future funding opportunities to expand upon this work.
Shellfish farmers throughout the Northeast may benefit from the results of the project, by gaining a more thorough understanding of the phytoplankton community structure in estuaries and around farms. Other researchers studying productivity in estuaries, including those using satellite data to monitor phytoplankton blooms, may also find this work useful for their research efforts.