The isotopic signature of particulate organic C and N in bottom ice: Key influencing factors and applications for tracing the fate of ice‐algae in the Arctic Ocean
Bibliographic record
Abstract
Abstract The isotopic, taxonomic, and nutrient dynamics of protist communities at the bottom of first‐year sea ice were studied for a wide range of ice conditions during the spring‐summer transition in the southeast Beaufort Sea. In bottom ice, total protist abundance ranged from 0.07 to 9.94 × 109 cells m–2 and chlorophyll a biomass ranged from 0.33 to 110 mg m–2. Both variables were positively related to the concentrations of nitrate, silicic acid, and phosphate at the ice‐water interface, with r2 values between 0.63 and 0.79. Results showed that the δ13C of sympagic (ice‐associated) particulate organic matter (POM) (–27.1 to –11.4‰) was mainly influenced by ice protist stocks and dissolved inorganic carbon availability. Flagellated cells maintained a low δ13C relative to diatoms. The δ15N of POM (3.9 to 9.4‰) could not be explained by any of the variables considered and showed considerable overlap with the pelagic δ15N‐POM (0.0 to 10.3‰). Detailed analyses of δ13C‐POM through size fractionation and settling experiments along with a short temporal study of the interaction between sympagic and pelagic communities confirmed or demonstrated that (1) the analysis of stable C isotopes is a valuable tool to trace the flow of ice‐derived matter, (2) sympagic POM contributes substantially to suspended pelagic biomass during release episodes, and (3) ice‐grown autotrophic flagellated cells have a strong potential to interact with the pelagic biota in the coastal Arctic Ocean. This study highlights the need to carefully evaluate stable isotope dynamics before assessing food web interactions or the fate of POM in seasonally ice‐covered waters.
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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 | 0.000 |
| 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".