Estimating stocking weights for Atlantic salmon to grow to market size at novel aquaculture sites with extreme temperatures
Bibliographic record
Abstract
Land-based hatcheries are now capable of growing large Atlantic salmon ( Salmo salar ) post-smolts (approximately 150 – 1000 g), which means that marine net-pens can be stocked with substantially larger fish compared to traditional stocking sizes (< 150 g). This stocking strategy typically aims to reduce the time required for fish to grow to market size in the marine environment and limit risks (e.g., exposure to pathogens and diseases, opportunities for escapes). This study investigates another potential application of this strategy: the use of novel sites in areas previously considered unsuitable for aquaculture due to seasonally cold temperatures. The thermal-unit growth coefficient (TGC) model was applied to estimate the stocking weight needed to reach a harvest size of 5.5 kg, based on observed degree days for three sites. High resolution, depth-partitioned temperature time series from coastal locations in Atlantic Canada were used to represent a short, medium, and long growing season, as constrained by seasonal temperature extremes. Growing days for model inputs were defined as temperatures > 4 °C and trending up for stocking, < 18 °C to account for heat stress, and > -0.7 °C to avoid superchill conditions. Different TGC values were applied to simulate remedial, average, and elite growth performance. There was a range of model stocking weight estimates for each site (1.5 – 2.5 kg, 0.94 – 2.8 kg, and < 0.1 – 0.52 kg, for the short, medium, and long season sites, respectively). Results were sensitive to the number of degree days, heat stress threshold, and TGC value. At the two sites where season length was constrained by superchill, fish with a stocking weight of approximately 1.5 kg could grow to market size in shallow water depths (< 15 m), assuming elite growth performance. This investigation suggests that with appropriate growth performance assumptions and high-resolution temperature data, large post-smolt stocking strategies could enable the use of novel sites in coastal areas previously considered unsuitable for aquaculture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 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".