Mesopelagic Sound Scattering Layers of the High Arctic: Seasonal Variations in Biomass, Species Assemblage, and Trophic Relationships
Bibliographic record
Abstract
Mesopelagic sound scattering layers (SSL) are ubiquitous in all oceans. Pelagic organisms within the SSL play important roles as prey for higher trophic levels and in climate regulation through the biological carbon pump. Yet, the biomass and species composition of SSL in the Arctic Ocean remain poorly documented, particularly in winter. A multifrequency echosounder detected a SSL north of Svalbard, from 79.8°N to 81.4°N, in January 2016, August 2016, and January 2017. Midwater trawl sampling confirmed that the SSL comprised zooplankton and pelagic fish of boreal and Arctic origins. Juvenile beaked redfish dominated the fish assemblage in January and Arctic cod in August. The macrozooplankton community mainly comprised the medusa Cyanea capillata, the amphipod Themisto libellula, and the euphausiids Meganyctiphanes norvegica in August and Thysanoessa inermis in January. The SSL was located in the Atlantic Water mass, between 200-700 m in August and between 50-500 m in January. In January, the SSL was shallower and weaker above the deeper basin, where less Atlantic Water penetrated. The energy content available in the form of lipids within the SSL was significantly higher in summer than winter. The biomass within the SSL was >12-fold higher in summer, and the diversity of fish was slightly higher than in winter (12 vs. 9 species). We suggest that these differences are mainly related to life history and ontogenetic changes resulting in a descent towards the seafloor, outside the mesopelagic layer, in winter. In addition, some fish species of boreal origin, such as the spotted barracudina, did not seem to survive the polar night when advected from the Atlantic into the Arctic. Others, mainly juvenile beaked redfish, were abundant in both summer and winter, implying that the species can survive the polar night and possibly extend its range into the high Arctic. Fatty-acid trophic markers revealed that Arctic cod mainly fed on calanoid copepods while juvenile beaked redfish targeted krill (Thysanoessa spp.). The relatively high biomass of Arctic cod in August and of redfish in January thus suggests a shift within the SSL, from a Calanus-based food web in summer to a krill-based food web during winter.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".