Light, ammonium, <scp>pH</scp>, and phytoplankton competition as environmental factors controlling nitrification
Bibliographic record
Abstract
Abstract The biogeochemical cycling of nitrogen (N) plays a critical role in supporting marine ecosystems and controlling primary production. Nitrification, the oxidation of ammonia (NH3) by microorganisms, is an important process in the marine N cycle, supplying nitrate (), the primary source of N that fuels new phytoplankton growth, and the primary substrate for the microbial process of denitrification. Understanding nitrification in the Chukchi Sea, the shallow sea overlying the continental shelf north of Alaska and the Bering Strait, is particularly important as phytoplankton growth there has been shown to be limited by N. However, the controls on nitrification in the water column and potential effects of climate change remain unknown. This study seeks to characterize the controls on nitrification in the Chukchi Sea. We found light to be a strong control on nitrification rates. Nitrification was undetectable at light levels above 23 μmol photons m−2 s−1. Subsequently, sea ice concentration was related to nitrification, with rates being higher at stations with high ice cover where light transmission to the water column was reduced. High ammonium () concentrations also enhanced nitrification, suggesting that nitrifying organisms were substrate‐limited, likely due to competition for from phytoplankton. Unlike previous experimental studies, we found that nitrification rates were higher under low pH conditions. As the effects of ocean acidification and warming disproportionately impact the Arctic, nitrification rates will undoubtedly be affected. Our results will help guide future studies on potential implications of climate change on the biogeochemistry of N in the Chukchi Sea.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".