Photoacclimation State of an Arctic Underice Phytoplankton Bloom
Bibliographic record
Abstract
Abstract Recent reports on Arctic underice phytoplankton blooms have directed attention to primary production below the sea ice cover. Such underice blooms cannot be detected from space; thus, methods for autonomous underice measurements are critically needed to extend observations beyond ship‐based surveys. One central aspect of the ecology of these blooms is whether they were advected from open‐water areas or were able to develop below the ice cover under typically low light conditions. The photoacclimation state of the bloom can provide clues about the growth conditions and therefore its origin. Here we investigate the photoacclimation state of a Phaeocystis pouchetii‐dominated underice bloom in the Arctic Ocean using ratios of photoprotective carotenoids (PPC) to photosynthetic carotenoids (PSC) and chlorophyll a. The pigment proxies indicate local growth under the ice pack. Furthermore, a method using in situ light absorption measurements to estimate the PPC:PSC ratio was in agreement with the pigment data. The slope of in situ phytoplankton absorption between 488 and 532 nm, affected by both PPC and PSC, had a significant linear relationship to the PPC:PSC ratio, indicating that prediction of photoacclimation state can be obtained from absorption profiles. We also review, with regard to the pigment function, different ways of grouping pigments into PPC or PSC applied in previous studies. Although more validation data sets are needed to assess the impact of pigment packaging on the relationship between PPC:PSC and absorption measurement slopes, our study shows the potential for using in situ absorption measurements to collect information about phytoplankton physiology below sea ice.
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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 | 0.000 | 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".