Suitability of the Coralline Alga Clathromorphum compactum as an Arctic Archive for Past Sea ice Cover
Bibliographic record
Abstract
Arctic sea ice cover has been steeply declining since the onset of satellite observations in the late 1970s. However, the available annually resolved sea ice data prior to this time are limited. Here, we evaluated the suitability of annual trace element (Mg/Ca) ratios and growth increments from the long-lived annual increment-forming benthic coralline red alga, Clathromorphum compactum, as high-resolution sea ice cover c. It has previously been shown that growth and Mg/Ca of C. compactum are strongly light controlled and therefore greatly limited during polar night and underneath sea ice cover. We compare algal data from 11 sites collected throughout the Canadian Arctic, Greenland and Svalbard, with satellite sea ice data. Our results suggested that algal growth anomalies most often produced better correlations to sea ice concentration than Mg/Ca alone or when averaging growth and Mg/Ca anomalies. High Arctic regions with persistently higher sea ice concentrations and shorter ice-free seasons showed strongest correlations between algal growth anomalies and satellite sea ice concentration over the study period (1979-2015). At sites where ice breakup took place prior to the return of sufficient solar irradiance, algal growth was most strongly tied to a combination of solar irradiance and other factors such as temperature, suspended sediments, phytoplankton blooms and cloud cover. These data are the only annually resolved in situ marine proxy data known to date and are of utmost important to gain a better understanding of the sea ice system and to project future sea ice conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".