Phytoplankton and bacterial dynamics on the Chukchi Sea Shelf during the spring-summer transition
Bibliographic record
Abstract
Climate warming is exerting significant change on the physical properties of the Arctic Ocean, which in turn has marked consequences for the biology of the region.The Chukchi Sea is notable for its species richness as a consequence of a nutrient-rich shelf region that supports substantial primary production.However, little is known about the carbon transformations at the base of the food web in the Chukchi Sea, and in particular the relative amounts of primary production that are transferred directly to higher trophic levels or remineralized within the microbial loop.We measured microbial standing stocks (bacteria to microplankton), phytoplankton growth and mortality rates, and bacterial production and mortality rates at 10 stations in the Chukchi Sea and Bering Strait during the spring-summer transition.Our study revealed that protistan grazers consumed substantially more phytoplankton carbon than bacterial carbon.Phytoplankton growth rates were variable, but at times considerable (range: -0.06 to 0.71 d -1 ), with protistan grazers consuming an average of 46% of the daily primary production.Heterotrophic protists exerted significant grazing pressure on phytoplankton despite low environmental temperatures.Bacterial production and mortality rates were low (generally <1 µg C l -1 d -1 ) and at times in balance, but overall bacterial production exceeded mortality.This study improves our understanding of carbon cycling in the Chukchi Sea during the spring-summer transition, demonstrating a significant transfer of primary production to heterotrophic protists at that time of year.
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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 | 0.000 |
| 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".