Elemental and isotopic characterization of dissolved and particulate organic matter in a unique California upwelling system: Importance of size and composition in the export of labile material
Bibliographic record
Abstract
We report the interseasonal variation in bulk elemental and stable isotopic (δ13C, δ15N) composition of dissolved and particulate organic matter (DOM, POM) during a high‐resolution time series (2007–2009) on the Big Sur coast. In addition to interseasonal variations, we explore the relationships between physical size and reactivity (i.e., composition) of exportable organic matter (OM) pools, and characterize the elemental and isotopic composition of size‐fractionated POM and DOM pools within this potentially high‐nutrient, low‐chlorophyll (HNLC) California upwelling region. Average POM concentrations were low (< 5.2 µmol C L−1 and < 0.7 µmol N L−1), and all OM pools had low C : N ratios (DOM average = 15.0 and POM < 7.8)—indicating that this upwelling center may represent an important source of N‐rich material to offshore environments. Seasonal “excess” dissolved organic carbon (DOC) production was significant (~ 30–80 µmol L−1 DOC); however, dissolved organic nitrogen (DON) production and cycling was largely decoupled from both DOC and physical processes. Overall, our results are consistent with this region representing an “HNLC upwelling system.” The distinct bulk elemental and isotopic OM composition and seasonality vs. that of high‐productivity upwelling regions highlights the need to better understand the biogeochemical diversity of upwelling systems. Finally, we observed a quantifiable size–composition relationship across both POM and DOM size classes, perhaps representing a powerful new tool for modeling N vs. C fluxes in ocean biogeochemical cycles.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".