Scale‐dependent carbon:nitrogen:phosphorus seston stoichiometry in marine and freshwaters
Bibliographic record
Abstract
The classical Redfield ratio of carbon106 : nitrogen16 : phosphorus1 is a cornerstone of biogeochemistry. With the use of >2,000 observations of the chemistry of particulate matter from small and large lakes, as well as near and off‐shore marine environments, we found that the best model to describe seston stoichiometry depended on the scale of analysis. We also found that there were better estimates for seston chemistry than the classical ratio for all habitats, whether freshwater or marine. Across the entire data set, a constant proportionality of C166:N20 : P1 (±error) described the data, which implies higher C sequestration per unit of N and P in surface waters than given in the classical ratio. At a regional scale, however, C: P and C:N often declined with increasing seston abundance, rejecting a constant ratio model. Within both freshwater and marine habitats, higher seston abundance is often associated with lower C: P and C:N ratios (higher nutrient content). The difference in appropriateness of the constant ratio model with respect to the entire data compared with subsets of the data indicates a scale dependence in stoichiometric relationships in seston C:N: P ratios. Given these consistent shifts in seston chemistry with particle abundance, the narrower variation in seston chemistry associated with marine seston chemistry could occur because of a reduced range of particulate nutrient concentration. For all but the largest scales, the classical Redfield model of biogeochemical cycling should be replaced with a more general power function model.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".