Exploring Biofouling Control by the California Sea Cucumber (Apostichopus californicus) in Integrated Multi-Trophic Aquaculture (IMTA) with Organic Chinook Salmon (Oncorhynchus tshawytscha)
Bibliographic record
Abstract
The growth of biofouling on aquaculture infrastructure is a universal challenge. Standard industry practices to remove biofouling in finfish aquaculture typically include in situ net cleaning via power washing. Since those cleaning practices can be potentially harmful to fish-gill health and expensive, development of other non-toxic biofouling controls is an industry priority. Deposit-feeding sea cucumbers are potentially well suited for biofouling control due to their feeding mechanism, but remain relatively untested in this capacity. We examined the use of California sea cucumbers (Apostichopus californicus) to control biofouling on cages containing adult Chinook salmon (Oncorhynchus tshawytscha) at a commercial farming operation. Four cage types were established: cages with salmon and sea cucumbers, cages with salmon only, cages with sea cucumbers only, and cages without either species. Results showed that the sea cucumbers actively fed on biofouling when salmon were absent (~16% cleaner on average) but preferred to consume uneaten feed/faeces at the bottom of the cages, neglecting the biofouling, when the salmon were present. It is hypothesized that biofouling control in cages with salmon may be possible with an increased density of sea cucumbers. This is the first study to examine the use of sea cucumbers as a direct net biofouling control agent with adult fish. Our results will be beneficial for industry to develop standard operating procedures for using California sea cucumbers as a biofouling control and could contribute to the development of a management framework for sea cucumber/salmon integrated multi-tropic aquaculture.
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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 | 0.000 | 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) | 0.000 | 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 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".