Lower trophic level mixed fishery (LOTROMIX) - Implications for ecosystem and management
Bibliographic record
Abstract
There is an increasing interest in new marine resources for the production of aquaculture feed, to meet the increasing growth of the aquaculture industry. Marine species from lower trophic levels are a potential resource that could partly cover the increasing need for lipid and protein in aquaculture feed. The mesopelagic layer present a variety of species that is estimated to hold a vast biomass to harvest from, both globally and in the Norwegian Sea and fjords. Marine species at high latitudes are known for a high lipid content, with a potential for high concentrations of essential fatty acids and polyunsaturated fatty acids that are sought to incorporate into aquaculture feed. \nThe main objective of this present study was to quantify the species composition and assess the biomass distribution and production in the Norwegian Sea and fjords by trawling. The catch were further analysed, and the suitability catch from the mesopelagic layer would provide as a feed component was determined by analysing the total lipid content, and further assess the fatty acid and lipid class composition. \nCatches from the mesopelagic layer showed high variation in densities of species at different season and location. With jellyfish and mesopelagic fish dominating the hauls conducted in the fjords, while krill and mesopelagic fish were dominating the hauls at sea. The mesopelagic fishes Maurolicus muelleri (Gmelin, 1789) and Benthosema glaciale (Reinhardt, 1837) had the highest lipid content of the analysed species from the mesopelagic layer, with mixed layer samples containing an average of 30.6 % lipid from dry weight, equivalent to 9.1 % lipid of wet weight. Placing a mixed catch from the mesopelagic layer between some of the pelagic fish species that are the main source of fishmeal and fish oil today in regards of lipid content. The highest lipid content was found in samples collected in the fjords during spring. The fatty acid composition of the catch contained favourable amounts of both PUFA and DHA+ EPA in all samples. With higher relative content found in smaller and leaner samples. The lipid class composition was satisfying, with the mixed layer samples containing well beneath the upper limit for the potentially limiting wax ester.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".