Relationship between surface dissolved iron inventories and net community production during a marine heatwave in the subarctic northeast Pacific
Bibliographic record
Abstract
From winter 2013-14 to the end of 2015-16, a high pressure atmospheric system induced elevated sea surface temperatures in the offshore subarctic northeast Pacific, resulting in a marine heatwave. Increased stratification due to the heatwave resulted in shoaling of the winter mixed layer and a decrease in nutrient re-supply to the euphotic zone. Here, we investigate relationships between dissolved iron (dFe) and macronutrients, net community production (NCP), (micro)nutrient uptake ratios, and phytoplankton community composition in the winter and summer from 2012 to 2015 to gain insight into coupled biogeochemical responses to the heatwave. Our investigation highlights the importance of external dFe supply during marine heatwave events, as a more shallow mixed layer reduces the transport of essential (micro)macronutrients to the surface layer. We conclude that recycled dFe did not contribute to NCP in 2014, but rather the vertical displacement of dFe rich water unrelated to mixed layer deepening played a major role. In 2015, such transport was not detected, resulting in abnormally low dFe and shift toward higher biomass of pico- and nano-phytoplankton size-classes.
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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 | 0.001 |
| 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 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".