Nitrogen isotopes in bulk marine sediment: linking seafloor observations with subseafloor records
Bibliographic record
Abstract
Abstract. The stable isotopes of nitrogen offer a unique perspective on changes in the nitrogen cycle, past and present. However, the presence of multiple forms of nitrogen in marine sediments can complicate the interpretation of bulk nitrogen isotope measurements. Although the large-scale global patterns of seafloor δ15N have been shown to match process-based expectations, small-scale heterogeneity on the seafloor, or alterations of isotopic signals during translation into the subseafloor record, could obscure the primary signals. Here, a public database of nitrogen isotope measurements is described, including both seafloor and subseafloor sediment samples ranging in age from modern to the Pliocene, and used to assess these uncertainties. In general, good agreement is observed between neighbouring seafloor sites within a 100 km radius, with 85% showing differences of < 1‰. There is also a good correlation between the δ15N of the shallowest (< 5 ka) subseafloor sediments and neighbouring seafloor sites within a 100 km radius (R2 = 0.83), which suggests a reliable translation of sediments into the buried sediment record. Meanwhile, gradual δ15N decreases over multiple glacial–interglacial cycles appear to reflect post-depositional alteration in records from the deep sea (below 2000 m). We suggest a simple conceptual model to explain these 100-kyr-timescale changes in well-oxygenated, slowly accumulating sediments, which calls on differential loss rates for pools of organic N with different δ15N. We conclude that bulk sedimentary nitrogen isotope records are reliable monitors of past changes in the marine nitrogen cycle at most locations, and could be further improved with a better understanding of systematic post-depositional alteration. Furthermore, geochemical or environmental criteria should be developed in order to effectively identify problematic locations and to account for confounding influences where possible.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".