Spatial distribution of benthic macrofauna in the Central Arctic Ocean
Bibliographic record
Abstract
Permanent sea-ice cover and low primary productivity in the mostly ice-covered Central Arctic ocean basins result in significantly lower biomass and density of macrobenthos in the abyssal plains compared to the continental slopes. However, little is known on bathymetric and regional effects on the macrobenthos diversity. This study synthesizes new and available macrobenthos data to provide a baseline for future studies of the effects of Arctic change on macrofauna community composition in the Arctic basins. Samples collected during three expeditions (in 1993, 2012 and 2015) at 37 stations on the slope of the Barents and Laptev Seas and in the abyssal of the Nansen and Amundsen Basins in the depth range from 38 m to 4381 m were used for a quantitative analysis of species composition, abundance and biomass. Benthic communities clustered in five depth ranges across the slope and basin. A parabolic pattern of species diversity change with depth was found, with the diversity maximum for macrofauna at the shelf edge at depths of 100-300 m. This deviates from the typical species richness peak at mid-slope depths of 1500-3000 m in temperate oceans. Due to the limited availability of standardized benthos data, it remains difficult to assess if and how the significant sea-ice loss observed in the past decade has affected benthic community composition. The polychaete Ymerana pteropoda and the bryozoan Nolella sp. were found for the first time in the deep Nansen and Amundsen Basins.
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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) | 0.000 | 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".