Microbial Nitrogen Removal in South San Francisco Bay: Does It Play a Role in Eutrophication Resistance?
Bibliographic record
Abstract
Abstract The ecosystem response to anthropogenic nitrogen (N) loading in estuarine systems is determined by hydrodynamics, biogeochemical transformation rates, and other system-specific characteristics. Historically, San Francisco (SF) Bay has been an outlier from other estuaries with an unusual resistance to eutrophication, despite having extremely high rates of nitrogen loading. Recent increases in phytoplankton biomass and an unprecedented harmful algal bloom, however, have increased the urgency to understand rates and drivers of nitrogen removal in the system. To assess benthic N cycling rates, we conducted seasonal measurements across nine sites in South and Lower South SF Bay, the two sub-embayments with the highest rates of area-normalized N loading, to determine the rates and potential drivers of denitrification and dissimilatory nitrate reduction to ammonium (DNRA). Denitrification rates averaged 60.6 ± 8.1 µmol m −2 h −1 and were primarily coupled to nitrification. Denitrification rates were positively correlated with DNRA rates and % clay. DNRA rates ranged from 0 to 20 µmol m −2 h −1 and on an annual basis averaged ~ 10% of total benthic nitrate reduction, with a negative correlation to % clay content in the surface sediment. The measured denitrification rates account for the removal of, on average, 14% of N loaded annually to South SF Bay, leaving a sizeable portion for alternate fates (e.g., recycling, export, or burial) and potential for substantial temporal and spatial variability (1–79%). This identifies the relative importance of sediment denitrification in ecosystems characterized by high nutrients and low productivity.
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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".