Sustainable Seafood Approaches for New Hampshire
Bibliographic record
Abstract
Abstract In 2023, the U.S. seafood trade deficit was $20.3 billion, importing both capture fishery and aquaculture products mostly from Canada, Chile, India, Indonesia and Vietnam. With U.S. capture fishery production of $5.6 billion, responsible aquaculture has the potential to close this difference. The University of New Hampshire (UNH) is addressing this issue through the Center of Sustainable Seafood Systems (CSSS) by developing innovative production technologies and practices through interdisciplinary research. This presentation will provide a scientific and engineering overview of these practices at four permitted aquaculture sites along the NH coast. The most extensive effort is being conducted at a nearshore site off New Castle with the operation of a community-scale, integrated multitrophic aquaculture (IMTA) system. The concept of IMTA is to employ the culture of high valued fed species, alongside non-fed, extractive species at biomass levels to offset the input of nutrients while enhancing the growth. The IMTA approach is to produce and harvest steelhead trout (Oncorhynchus mykiss), together with blue mussels (Mytilus edulis) and sugar kelp (Saccharina latissima) to remove nutrients. With such field operations, detailed datasets are being collected to examine the biological, chemical and physical processes associated with the IMTA method. The datasets include steelhead trout feed input trout, growth, harvest and sales from our present operational cycle. A moored, oceanographic buoy has also been deployed in this last year to acquire water quality information to include temperature, salinity, dissolved oxygen, chlorophyl, pH, nitrate, fluorescent dissolved organic matter, and current velocities. Part of the assessment is to analyze the total ammonia nitrogen entering the system by feeding the fish. With proximate analysis results, the amount of particulate organic nitrogen removed by mussels, and dissolved nitrogen removed by kelp, can be calculated. This information is being utilized to size the IMTA farm to match the biomass of extractive species with that of the fed species. Waves and current velocity profiles are also being measured at the site and are being used with loadcell datasets to validate numerical models of the IMTA structure for more accurate future design efforts. Research is also being done at the other three permitted aquaculture sites. One of these aquaculture permits was obtained with the Seacoast Science Center in Rye to provide community education and outreach. At another one of the sites, adjacent to Appledore Island, whale safe gear for kelp farming is being field tested. The fourth site is 130 acres, 2.5 miles offshore of Jenness Beach, in a depth of 35 m. At this fully exposed location, novel aquaculture systems for mussels, scallops and seaweed are being designed to withstand the rigors of extreme storms and to minimize risk to whales that frequent the area. Presenter Bio David W. Fredriksson joined the School of Marine Science and Ocean Engineering and the faculty of Mechanical Engineering at the University of New Hampshire in August 2022. He is also the Director of the Center for Sustainable Seafood Systems. Dr. Fredriksson brings over two decades of experience developing ocean engineering methodologies for the farming of finfish, shellfish and macroalgae, with the goal of supporting seafood security for both the United States and abroad. His underlying passion is to grow new sustainable production methods and educational programs that will enhance both local maritime communities and the ocean environment. Professor Fredriksson has been the Principal Investigator for numerous research efforts, with projects most recently funded by the Department of Energy, World Wildlife Fund, National Oceanic and Atmospheric Administration and Atlantic States Marine Fisheries Commission.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".