Exposing the Distributions and Elemental Associations of Scavenged Particulate Phases in the Ocean Using Basin‐Scale Multi‐Element Data Sets
Bibliographic record
Abstract
Abstract The GEOTRACES program has greatly increased basin‐scale concentration measurements for a large number of elements in the ocean, both constraining external sources and internal sinks and exposing complex internal cycles of trace elements. Our conceptual frameworks for marine trace element cycling, however, often remain simplified as the production and remineralization of phytoplankton biomass. Despite their complexity, or perhaps because of it, trace element cycles are often predominantly considered as an extension of traditional Redfield macronutrient ratios to C or P. Here we utilize extensive data sets of particulate trace element concentrations from GEOTRACES section cruises in the South Pacific and North Atlantic Oceans to look for evidence of the internal cycles of multiple trace elements without requiring normalization to phytoplankton biomass. Using both traditional and expanded power law regression analyses and multi‐element factor analysis, we expose the internal distributions of six authigenic, biogenic, and lithogenic particulate phases and their multi‐element associations. Critically, no particulate trace element is observed to behave identically to P. Observations include a scavenged Fe phase with a slight surface maximum, which increases linearly with depth below ~ 300 m and which appears to co‐scavenge Cu, V, and La. Particulate Co is found to be associated with phytoplankton, Mn‐biooxides just below the mixed layer, and with a putative heterotrophic phase observed in the surface and at depth. We present an expanded conceptual framework for particulate trace element cycling that has explicit roles for these multiple particulate phases.
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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".