Kelps on demand: Closed‐system protocols for culturing large bull kelp sporophytes for research and restoration
Bibliographic record
Abstract
Abstract Culturing kelps for commercial, conservation, and scientific purposes is becoming increasingly widespread. However, kelp aquaculture methods are typically designed for ocean‐based farms, and these methods may not be applicable for smaller scale cultivation efforts common in research and restoration. Growing kelps in closed, recirculating culture systems may address many of these constraints, yet closed system approaches have remained largely undescribed. Extensive declines of the bull kelp (Nereocystis luetkeana), an ecologically important canopy species in the Northeast Pacific, have received widespread attention and prompted numerous research and conservation initiatives. Here, we detail two approaches for cultivating N. luetkeana sporophytes in closed recirculating systems. Nereocystis luetkeana were reared as attached thalli in custom seaweed growth flumes and also free‐floating in tumble culture tanks. Careful control of stocking density, water motion, aeration, and nutrient levels allowed for rapid growth and normal morphogenesis of laboratory‐grown kelp. Culture systems reached up to 3 kg · m−3, and individual thalli attained lengths of up to 6 m before the trials were terminated. Our results demonstrate the potential of recirculating, closed culture systems to overcome limitations associated with traditional culture methods. Recirculating systems enable the precise control of culture conditions, improving biosecurity and facilitating cultivar development and other research. Kelps can be grown away from the ocean or outside their native ranges, and seasonal or annual species can be produced year‐round without seasonal constraints.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".