Global Spatial and Temporal Variation of Cd:P in Euphotic Zone Particulates
Bibliographic record
Abstract
Abstract Concentrations of Cd and P were determined in particle samples collected using the multiple unit large volume in situ filtration system (MULVFS) from 50 profiles at 34 different locations throughout the Atlantic, Pacific, and Southern Oceans since 1991. Consistent methodology has been used. This data set of Cd:P in size fractionated particles gives insight into the processes that lead to differences in regional Cd:P particle values as well as how the formation and remineralization of these particles lead to dissolved deep water ratios that increase from the North Atlantic to the North Pacific. With large spatial and temporal variation, this data set allows us to study the effects of an El Niño, upwelling, large‐scale in situ Fe fertilization, low‐oxygen conditions, and seasonal variation on the Cd:P in particles. Overall, Cd:P tends to be higher (~1–2 mmol/mol) in particles gathered in biologically dynamic waters and is much lower (typically ~0.1 mmol/mol) in oligotrophic regions. Using multiple linear regression analysis, we investigate how euphotic zone parameters important to photosynthesis including nitrate, phosphate, silicate, temperature, and euphotic zone depth affect the Cd:P ratio in particles. Using the results of the analysis, we create global seasonal maps of predicted particulate Cd:P distributions. We find that three factors—local dissolved nitrate, silicate concentrations, and euphotic zone depth—can predict 59% of the variation in particulate Cd:P. We verified our projections using in situ filtration samples collected during GEOTRACES expeditions GA03 (North Atlantic) and GP16 (South Pacific).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".