Secular trends in Arctic Ocean net primary production
Bibliographic record
Abstract
[1] A satellite-based study was conducted to document daily changes in net primary production (NPP) by phytoplankton in the Arctic Ocean from 1998 to 2009 using fields of sea ice extent, sea surface temperature, and chlorophyll a concentrations. Total annual NPP over the Arctic Ocean exhibited a statistically significant 20% increase between 1998 and 2009 (range = 441–585 Tg C yr−1), due mainly to secular increases in both the extent of open water (+27%) and the duration of the open water season (+45 days). Increases in NPP over the 12 year study period were largest in the eastern Arctic Ocean, most notably in the Kara (+70%) and Siberian (+135%) sectors. NPP per unit area for the Arctic Ocean averaged 101 g C m−2 yr−1 with no significant change over the study period. In the western sectors, NPP ranged from 71.3 ± 11.0 g C m−2 yr−1 in the Beaufort to 96.9 ± 7.4 g C m−2 yr−1 in the Chukchi, while in the more productive eastern Arctic, annual NPP between 1998 and 2009 ranged from 101 ± 15.8 in the Siberian sector to 121 ± 20.2 in the Laptev. Results of a statistical analysis suggest that between 1979 and 1998 (prior to the launch of SeaWiFS and MODIS), total Arctic NPP likely averaged 438 ± 21.5 Tg C yr−1. Moreover, when summer minimum ice cover drops to zero sometime during the first half of this century, annual NPP in the Arctic Ocean could reach ∼730 Tg C yr−1. Nutrient fluxes into Arctic surface waters need to be better understood to determine if these projected increases are sustainable.
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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 | 0.001 | 0.001 |
| 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".