Longline and mesocosm cultivation of serrated wrack <i>Fucus serratus</i> (Phaeophyceae)
Bibliographic record
Abstract
Seaweed aquaculture is becoming increasingly important as the global seaweed market is set to exceed £20 billion by 2030, leaving natural populations at risk of overexploitation. Fucoids, such as Fucus serratus, are intertidal seaweeds hand-harvested for their use in agricultural, pharmaceutical, and biomedical industries. Despite many aspects of the biology of fucoids being well researched, there have been very few studies on their aquaculture. In this study, we grew F. serratus biomass from gamete life stages in the Queen’s University Marine Laboratory for 8 months and monitored their growth, amino acid and phenolic contents in a subtidal field trial. Gametes of F. serratus were successfully fertilized in vitro and attached to substrata: Tiles (mesocosm) and Dyneema Twine (subtidal). The growth of F. serratus on each substrate was monitored for 6 months in the laboratory facility with juveniles reaching 2–4 mm in length. The juveniles on twine were then deployed at the Strangford Lough test site and growth was compared against the juveniles on tiles after an additional two months. Prior to field deployment, individuals grown on tiles were significantly longer (~17%) than those on twine growing to ~3 cm, however, after the two-month deployment, the twine thalli grew significantly longer than those on the tiles (~33%) reaching ~6 cm in length. Subtidal F. serratus grown on twine had significantly higher amino acid content, whereas the phenolic content was significantly lower (~62 mg PGE g−1) than seaweed grown on the tiles (~128 mgPGE g−1). Growing F. serratus successfully in subtidal areas is highly important for providing sustainably sourced biomass to reduce reliance on wild harvesting. Further, cultivating in the subtidal zone will help to avoid competition for space from other aquaculture industries operating in the intertidal zone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".