Partitioning the Export of Distinct Biogenic Carbon Pools in the Northeast Pacific Ocean Using a Biogeochemical Profiling Float
Bibliographic record
Abstract
Abstract We leverage observations from chemical and bio‐optical sensors mounted on a biogeochemical profiling float in the Northeast Pacific Ocean to quantify the cycling and export potential of distinct biogenic carbon pools, including particulate inorganic carbon (PIC), particulate organic carbon (POC), and dissolved organic carbon (DOC). Year‐round observations reveal complex carbon cycle dynamics among these carbon pools. Net DOC production peaked during bloom initiation, about 3 months prior to the summer peak in POC production. We validate the float estimates of DOC cycling with seasonal accumulation and removal rates derived from ship‐board DOC observations over the same period. By combining chemical and bio‐optical tracers of POC cycling, we estimate the instantaneous POC sinking flux ( ). The cooccurrence of DOC consumption and POC production and sinking during fall and winter resolves the regional conundrum of a persistent particle sinking flux observed by sediment traps during a season that is known to be heterotrophic. PIC production is small, and uncertainties are large. By combining float‐based estimates of instantaneous net primary production (NPP) and , we quantify a real‐time carbon export ratio ([ /NPP] × 100%) for the euphotic zone. Elevated export ratios during summer are associated with an increase in the fraction of particles larger than 100 μm in size. Elevated export ratios during winter are associated with the physical redistribution of particles through seasonal deep mixing. Our study demonstrates how the combined use of multiple sensors on biogeochemical profiling floats can provide more nuanced information about upper ocean carbon cycle dynamics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".