Summertime Biogenic Silica Production and Silicon Limitation in the Pacific Arctic Region From 2006 to 2016
Bibliographic record
Abstract
Abstract We present a decade of dissolved and particulate silica concentrations within five biological “hot spots” in the Pacific Arctic Region (PAR) and the first measurements of both biogenic silica production rates ( ρ Si) and the kinetics of silicon utilization from a period of four years at the same sites. The “hot spots” were located within the Bering and Chukchi Seas and identified as part of the Distributed Biological Observatory (DBO). Across all hot spots, the highest concentrations of silicic acid (Si(OH) 4 ) and biogenic silica were found near the bottom of the euphotic zone and often correlated with increased ρ Si. For the entire region, the average ρ Si was 19 mmol m −2 day −1 and siliceous microplankton (i.e., diatoms) contributed an average of 62% to primary productivity and 82% to nitrate utilization. Irradiance and [Si(OH) 4 ] had separate and interactive effects on ρ Si. Irradiance modulated both the magnitude of ρ Si and the response of diatoms to changes in Si(OH) 4 . Availability of Si(OH) 4 limited ρ Si in all hot spots in at least one of the four years. Kinetic experiments conducted in all hot spots demonstrated that the half‐saturation constant ( K s ) for ρ Si was 4–8 times higher than ever reported in the literature. In the southeastern Chukchi Sea, an east to west gradient in [bSiO 2 ] and ρ Si may have been driven by differences in the availability of NO 3 − rather than Si(OH) 4 . Despite strong interannual variability, we suggest that phytoplankton phenology responds to short‐term climatic changes, which can have far‐reaching effects on Arctic regions influenced by the Pacific‐origin waters flowing through the PAR.
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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) | 0.000 | 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".