Changes in Under‐Ice Primary Production in the Chukchi Sea From 1988 to 2018
Bibliographic record
Abstract
Abstract Changes in sea ice thickness and extent have corresponded with substantial changes in net primary production (NPP) in the Arctic Ocean. In recent years, observations of massive phytoplankton blooms under sea ice have upended the previous paradigm that Arctic NPP was driven largely by growth in the marginal ice zone and open water periods. Here, a new 1‐D biogeochemical model capable of simulating ice algal and phytoplankton dynamics both under the ice and in open waters is applied in the northern Chukchi Sea for the years 1988–2018. Over this period, substantial under‐ice (UI) blooms were produced in all but four years and were the primary drivers of interannual variation in total NPP. While NPP in the UI period was highly variable interannually due to fluctuations in ice thickness and the length of the UI period, UI NPP accounted for nearly half of total NPP between 1988 and 2018. Further, years with high UI NPP had reduced annual zooplankton grazing, indicating an intensification in the mismatch between phytoplankton and zooplankton populations and possibly altering the partitioning of food between benthic and pelagic ecosystems. These results demonstrate that the often‐overlooked ice covered period can be highly productive in the Arctic Ocean, and that the northern Chukchi Sea has been amenable to UIB formation since at least 1988.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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; 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".