Plankton ecosystem functioning and nitrogen fluxes in the most oligotrophic waters of the Beaufort Sea, Arctic Ocean: a modeling study
Bibliographic record
Abstract
Abstract. The Arctic Ocean (AO) undergoes profound changes of its physical and biotic environments due to climate change. The greater light exposure and stratification alter its plankton ecosystem structure, functioning and productivity promoting oligotrophy in some areas as the Beaufort Sea. A one-dimension (1-D) physical-biological coupled model based on the large multiparametric database of the Malina project in the Beaufort Sea was used (i) to infer the functioning and nitrogen fluxes within the summer plankton ecosystem and (ii) to assess the model sensitivity to key light-associated processes involved in nutrient recycling and phytoplankton growth. The coupled model suggested that ammonium photochemically produced from photosensitive dissolved organic nitrogen (i.e. photoammonification process) was a necessary nitrogen source to achieve the observed levels of microbial biomass and production. It contributed to ca. two-thirds and one-third of the simulated surface (0–10 m) and depth-integrated primary and bacterial production, respectively. The model also suggested that carbon to chlorophyll ratios for small (< 5 μm) phytoplankton (ca. 15–45 g g−1) lower than those commonly used in biogeochemical models applied to the AO were required to simulate the observed herbivorous versus microbial food web competition and realistic nitrogen fluxes in the Beaufort Sea oligotrophic waters. In face of accelerating Arctic warming, more attention should be paid in the future to the mechanistic processes involved in food webs and functional groups competition, nutrient recycling and primary production in poorly productive waters of the AO as they are expected to expand rapidly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".