Dependency of Antarctic zooplankton species on ice algae‐produced carbon suggests a sea ice‐driven pelagic ecosystem during winter
Bibliographic record
Abstract
Abstract How the abundant pelagic life of the Southern Ocean survives winter darkness, when the sea is covered by pack ice and phytoplankton production is nearly zero, is poorly understood. Ice‐associated (“sympagic”) microalgae could serve as a high‐quality carbon source during winter, but their significance in the food web is so far unquantified. To better understand the importance of ice algae‐produced carbon for the overwintering of Antarctic organisms, we investigated fatty acid (FA) and stable isotope compositions of 10 zooplankton species, and their potential sympagic and pelagic carbon sources. FA‐specific carbon stable isotope compositions were used in stable isotope mixing models to quantify the contribution of ice algae‐produced carbon (αIce) to the body carbon of each species. Mean αIce estimates ranged from 4% to 67%, with large variations between species and depending on the FA used for the modelling. Integrating the αIce estimates from all models, the sympagic amphipod Eusirus laticarpus was the most dependent on ice algal carbon (αIce: 54%–67%), and the salp Salpa thompsoni showed the least dependency on ice algal carbon (αIce: 8%–40%). Differences in αIce estimates between FAs associated with short‐term vs. long‐term lipid pools suggested an increasing importance of ice algal carbon for many species as the winter season progressed. In the abundant winter‐active copepod Calanus propinquus, mean αIce reached more than 50% in late winter. The trophic carbon flux from ice algae into this copepod was between 3 and 5 mg C m−2 day−1. This indicates that copepods and other ice‐dependent zooplankton species transfer significant amounts of carbon from ice algae into the pelagic system, where it fuels the food web, the biological carbon pump and elemental cycling. Understanding the role of ice algae‐produced carbon in these processes will be the key to predictions of the impact of future sea ice decline on Antarctic ecosystem functioning.
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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) | 0.001 | 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".