Photosynthetic processes in Antarctic sea ice during the spring melt
Bibliographic record
Abstract
Abstract High‐latitude oceans experience strong seasonality where low light limits photosynthetic activity most of the year. This limitation is pronounced for algae within and underlying sea ice, and these algae are uniquely acclimated to low light levels. During spring melt, however, light intensity and daylength increase drastically, triggering blooms of ice algae that play important roles in carbon cycling and ecosystem productivity. How the algae acclimate to this dynamic and heterogeneous environment is poorly understood. Here, we measured 14C‐carbon fixation rates, photophysiology, and ribulose 1,5‐bisphosphate carboxylase oxygenase (Rubisco) content of sea‐ice algae in coastal waters near the western Antarctic Peninsula during spring, ranging from a low‐light‐acclimated, bottom community to a light‐saturated bloom. Carbon fixation rates by sea‐ice algae were similar to other Antarctic sea‐ice measurements (2–49 mg C m−2 d−1), and there was little phytoplankton biomass in the underlying water at the time of sampling. Net‐to‐gross ratios of carbon fixation were generally high and showed no relationship with ice type. We found algal photophysiology and Rubisco concentrations varied in relation to the different types of ice, altering the balance between the photochemical and biochemical processes that constrain carbon fixation rates. For algae inhabiting the bottom layers of sea ice, rates of carbon fixation were largely constrained by light availability whereas in surface seawater, interior and rotten/brash ice, carbon fixation rates could be calculated with reasonable accuracy from measurements of Rubisco concentrations. This work provides additional insight and means to evaluate carbon fixation rates as sea ice continues to change in future.
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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 | 0.001 | 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) | 0.000 | 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".