Spatial Patterns of Macromolecular Composition of Phytoplankton in the Arctic Ocean
Bibliographic record
Abstract
The macromolecular concentrations and compositions of phytoplankton are crucial for the growth or nutritional structure of higher trophic levels through the food web in the ecosystem. To understand variations in macromolecular contents of phytoplankton, we investigated the macromolecular components of phytoplankton and analyzed their spatial pattern on the Chukchi Shelf and the Canada Basin. The carbohydrate (CHO) concentrations on the Chukchi Shelf and the Canada Basin were 50.4–480.8 μg L−1 and 35.2–90.1 μg L−1, whereas the lipids (LIP) concentrations were 23.7–330.5 μg L−1 and 11.7–65.6 μg L−1, respectively. The protein (PRT) concentrations were 25.3–258.5 μg L−1 on the Chukchi Shelf and 2.4–35.1 μg L−1 in the Canada Basin. CHO were the predominant macromolecules, accounting for 42.6% on the Chukchi Shelf and 60.5% in the Canada Basin. LIP and PRT contributed to 29.7% and 27.7% of total macromolecular composition on the Chukchi Shelf and 30.8% and 8.7% in the Canada Basin, respectively. Low PRT concentration and composition in the Canada Basin might be a result from the severe nutrient-deficient conditions during phytoplankton growth. The calculated food material concentrations were 307.8 and 98.9 μg L−1, and the average calorie contents of phytoplankton were 1.9 and 0.6 kcal m−3 for the Chukchi Shelf and the Canada Basin, respectively, which indicates the phytoplankton on the Chukchi Shelf could provide the large quantity of food material and high calories to the higher trophic levels. Overall, our results highlight that the biochemical compositions of phytoplankton are considerably different in the regions of the Arctic Ocean. More studies on the changes in the biochemical compositions of phytoplankton are still required under future environmental changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 teacher head, 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".