Two versions of short-term phytoplankton ecophysiology and taxonomic assemblages in the Arctic Ocean’s North Water (Canada, Greenland)
Bibliographic record
Abstract
Abstract Photosynthetic performance in open marine waters is determined by how well phytoplankton species are adapted to their immediate environment and available light. Although there is light for 24 h a day during the Arctic summer, little is known about short-term (h) temporal variability of phytoplankton photosynthetic performance in Arctic waters. To address this, we sampled the North Water (76.5°N) every 4 h over 24 h at two stations on the East and West sides that are influenced by different water masses and current conditions. We specifically investigated phytoplankton pigments, the xanthophyll cycle (XC), which is an indication of photoprotective capacity, and photosynthesis–irradiance (PE) response curves, at the surface and 20 m depth. The photophysiological parameters on the two sides differed along with the taxonomic signal derived from accessory pigments. On both sides, surface XC pigments showed high photoprotection capacity with the dinodinoxanthin–diatoxanthin (DD) and the violaxanthin, antheraxanthin and zeaxanthin cycles correlated with incoming radiation. The PE results showed that communities dominated by small flagellates on the western side performed better compared to diatom dominated communities on the eastern side. We conclude that phytoplankton and photosynthetic capacity differed consistent with known hydrography, with implications for a changing Arctic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".