What proportion of riverine nutrients reaches the open ocean?
Bibliographic record
Abstract
Abstract Globally, rivers deliver significant quantities of nitrogen (N) and phosphorus (P) to the coastal ocean each year. Currently, there are no viable estimates of how much of this N and P escapes biogeochemical processing on the shelf to be exported to the open ocean; most models of N and P cycling assume that either all or none of the riverine nutrients reach the open ocean. We address this problem by using a simple mechanistic model of how a low‐salinity plume behaves outside an estuary mouth. The model results in a global map of riverine water residence times on the shelf, typically a few weeks at low latitudes and up to a year at higher latitudes, which agrees well with observations. We combine the map of plume residence times on the shelf with empirical relationships that link residence time to the proportions of dissolved inorganic N (DIN) and P (DIP) exported and use a database of riverine nutrient loads to estimate the global distribution of riverine DIN and DIP supplied to the open ocean. We estimate that 75% of DIN and 80% of DIP reaches the open ocean. Ignoring processing within estuaries yields annual totals of 17 Tg DIN and 1.2 Tg DIP reaching the open ocean. For DIN this supply is about 50% of that supplied via atmospheric deposition, with significant east‐west contrasts across the main ocean basins. The main sources of uncertainty are exchange rates across the shelf break and the empirical relationships between nutrient processing and plume residence time.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".