Diversity and spatial variability of shallow benthic macrofaunal assemblages in a high-Arctic fjord (Young Sound, North-East Greenland)
Bibliographic record
Abstract
Although knowledge of Arctic benthic biodiversity has increased considerably in recent decades, some regions, such as Northeast Greenland, remain poorly studied. The aim of this study was to complement a previous macrofaunal inventory carried out in Young Sound, a High-Arctic fjord in this region (74°N). We sampled shallow benthic assemblages along a small inner/outer fjord gradient, including one station previously prospected two decades ago and three new stations. This sampling strategy revealed highly diversified benthic assemblages (166 species identified on a total sampling area of 1.32 m 2 ), which considerably increases the number of species recorded for the fjord (i.e. 225 species vs 100 previously recorded). The outermost station was dominated in abundance by various assemblages of bivalves, while the middle stations showed greater species evenness, including numerous species of polychaetes, bivalves and crustaceans. The innermost station was dominated by ostracods, gammarid amphipods and tube-dwelling polychaetes. Overall, benthic assemblages varied little between the four stations and the transect as a whole exhibited characteristics typical of outer fjord habitats, reflecting the rather moderate impact of meltwater inputs in this part of the fjord. Finally, trophic plasticity and omnivory were observed in most of the recorded macrobenthic species, highlighting the adaptability of these species to low trophic availability in the ecosystem. Future biodiversity studies will need to explore the innermost and deepest areas to provide a more comprehensive inventory and understanding of the influence of environmental conditions on the structure and functioning of Young Sound benthic habitats.
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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 | 0.001 | 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".