Seasonality and interannual variability of an Arctic marine time series, IsA
Bibliographic record
Abstract
The Arctic is warming twice as fast as anywhere else on the planet, in the European Arctic mainly driven by exalted Atlantic Water inflow. Microbial eukaryotes are diverse and essential to the functioning of marine ecosystems, thus environmental perturbations altering their communities influence the entire ecosystem. To study seasonal and interannual variation and the potential effects of Atlantification, a long-term marine time series has been established in Isfjorden-Adventfjorden, West Spitsbergen. We here present 3 years of high-resolution data including hydrography, nutrients, photosynthetic biomass, flow cytometry and community composition of microbial eukaryotes (0.45–10 µm, based on Illumina metabarcoding of 18S rDNA and rRNA). The timing, magnitude and species composition of the spring bloom varied interannually, with the more Atlantic spring 2014 being distinctly different from the two other years. A strong recurring seasonal pattern was evident in biodiversity, cell abundances and community composition. Winter communities were characterized by high alpha diversity and very low cell numbers with a dominance of heterotrophic and parasitic taxa. Despite large intra- and interannual differences in communities during the productive time of the year, winter communities were always highly similar, suggesting that the polar night represents a strong environmental forcing that resets the microbial communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".