Quantifying the contributions of riverine vs. oceanic nitrogen to hypoxia in the East China Sea
Bibliographic record
Abstract
Abstract. In the East China Sea, hypoxia (oxygen ≤ 62.5 mmol m−3) is frequently observed off the Changjiang (or Yangtze River) estuary covering up to about 15 000 km2. The Changjiang is a major contributor to hypoxia formation because it discharges large amounts of freshwater and nutrients into the region. However, modeling and observational studies have suggested that intrusions of nutrient-rich oceanic water from the Kuroshio Current also contribute to hypoxia formation. The relative contributions of riverine vs. oceanic nutrient sources to hypoxia have not been estimated before. Here, we combine a three-dimensional physical-biogeochemical model with an element-tracing method to quantify the relative contributions of nitrogen from different riverine and oceanic sources to hypoxia formation during 2008–2013. Our results suggest that the hypoxic region north of 30∘ N is dominated by Changjiang inputs, with its nitrogen loads supporting 74 % of oxygen consumption. South of 30∘ N, oceanic nitrogen sources become more important, supporting 39 % of oxygen consumption during the hypoxic season, but the Changjiang remains the main control on hypoxia formation also in this region. Model scenarios with reduced Changjiang nitrogen loads and reduced open-ocean oxygen levels suggest that nitrogen load reductions can significantly reduce hypoxia in the East China Sea and counteract a potential future decline in oxygen supply from the open ocean into the region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.001 | 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".