Towards understanding the variability between rates of biological productivity in the Beaufort Gyre of the Arctic Ocean
Bibliographic record
Abstract
Oceans account for more than 25% of anthropogenic CO2 removal from the atmosphere. Changes in our global climate have affected the Arctic Ocean in particular, resulting in increasing rates of warming and record-low sea ice extent, which for example, in the summer of 2012, was only half of the average over the previous three decades. It is unclear how these changes in the Arctic Ocean may affect biological productivity, which is one of the main drivers of the oceanic carbon cycle as CO2is consumed through photosynthesis and released through respiration. In order to investigate how these changes may influence the efficacy of the Arctic Ocean as a carbon sink, we calculated the gross oxygen production (GOP), which is the rate of total photosynthesis, and the net community production (NCP), which is the rate of photosynthesis minus community respiration and thus represents the strength of the carbon sink. The chemical gas tracers, triple oxygen isotopes and O2/Ar ratios, as measured in samples from the surface waters of the Beaufort Gyre region of the Canada Basin, were used to quantify gross oxygen production and net community production, respectively, in late summer and early fall over six years (2011-2016). We examined the effects of location, ice cover, chlorophyll-a, season, and more to better understand the collective impact of these physical conditions on biological productivity rates. Over these six years, mean GOP rates ranged from 9.1 ± 1 mmol O2 m-2 d-1 to 40 ± 4 mmol O2 m-2d-1 and mean NCP rates ranged from 1.1 ± 0.2 mmol O2 m-2 d-1 to 2.5 ± 0.2 mmol O2 m-2 d-1. Analyzing inter-annual variations in these rates can enlighten our understanding of how dramatic changes in the global climate may impact the ability of this region in the Arctic Ocean to remove carbon dioxide from the atmosphere.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".