Biofouling growth risk assessment on Atlantic Salmon (Salmo salar) farm nets: exploring links to environmental factors
Bibliographic record
Abstract
Recently, salmon aquaculture companies in British Columbia, Canada, have experienced significant fish losses resulting in tens to hundreds of millions of dollars in damages due to gill disorders and mouth lesions. Hydroids, the colonial stage of some cnidarians, are the most likely problematic species. Field studies were conducted to examine biofoulant composition, gill health, and the interactions between water parameters, biofoulants, and gill health. In 2020, biofouling was observed at two fish farm sites in the Broughton Archipelago from April 20 to October 30 by suspending 30x30 cm net patches at five depths (1, 5, 10, 15, and 20 m). Net patches remained in the water for 1-3 weeks between pen cleanings (via power washing). After collection, the biofoulants were identified and counted, with hydroids removed and weighed separately. In addition, tow samples were collected weekly to identify any free-swimming stinging-capable species. Biofoulant compositions were mainly composed of Mollusca (mostly Mytilus sp.) and Arthropods (mostly Harpacticoids), hydroids were mostly composed of Obelia sp., and tow samples were composed of mostly medusa-form Obelia sp. GLMMs were built to examine the relationships between the water parameters and the biofoulant species counts, hydroid biomass, and tow sample counts. Both sites saw nearly every parameter significantly associated with biofoulant counts, with the effects stronger at Wicklow Point. Similarly, nearly all parameters were associated with hydroid biomass, however the effects were stronger at Doctor Islets. Only two (ammonia and nitrate levels) and one (ammonia) parameters were associated with the counts of sting-capable species in the tow samples from Doctor Islets and Wicklow Point, respectively. CLMMs were built to examine the relationships between gill health, biofoulant counts and biomass, and water parameters. Iron, nitrate levels, and pH were significantly associated with gill health at Doctor Islets, and temperature, pH, and dissolved oxygen were significant at Wicklow Point. No biofoulant species counts or hydroid biomass from the net patches were associated with gill health, however, when the gill health scores were sampled after a net patch collection gill scores were significantly higher at both sites. At Doctor Islets, no stinging-capable species counts were associated with gill health and at Wicklow Point, counts of Sarsia sp., Bourgainvilla sp., Clytia gregaria, and Diphydae spp. were significantly associated with gill scores. Like the net patch samples, when gill scores were recorded after a tow collection, gill scores were significantly higher.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".