Distribution and retention of effluent nitrogen in surface sediments of a coastal bay
Bibliographic record
Abstract
Anthropogenic nitrogen (N) often causes coastal eutrophication, yet little is known about the fate and retention of effluent N in coastal waters and, hence, about the system’s ability to assimilate excess N loads. We used the spatial distribution of stable N isotope ratios and algal pigments in sedimentary organic matter from a Baltic bay receiving tertiary‐treated effluent to evaluate the extent of effects and the role of nearshore marine environments as sinks of anthropogenic N. Surface sediments (0–2 cm and 2–4 cm) exhibited a pronounced spatial gradient of δ 15 N, with the most elevated values (~8‰) near the outfall; values decreased linearly to values of ;4‰ outside the bay. Sedimentary pigment concentrations were consistent with water‐column data and showed that phytoplankton biomass was elevated in the inner reaches of the bay. In particular, diatoms were heavily labeled (δ 15 N ~ 10‰), reached maximum abundance near the effluent outfall, and were likely the main mechanism delivering effluent N to the sediments. Sediments within the bay removed ~5–11% of wastewater N inputs, with 50% of the sequestered effluent N buried in the basin nearest to the outfall. Magnitudes of N removal by sediments (23–26 x 10 4 kg N yr −1 ) were less than those estimated for denitrification (30–60 x 10 4 kg N yr −1 ), but they were substantially greater than biological uptake by macroalgae (~2 x 10 4 kg N yr −1 ). Taken together, these patterns demonstrate the idea that coastal sediments can be effective sinks of wastewater N, even after 30 yr of effluent input.
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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".