Annual Net Community Production of Particulate and Dissolved Organic Carbon From a Decade of Biogeochemical Profiling Float Observations in the Northeast Pacific
Bibliographic record
Abstract
Abstract Carbon export out of the surface ocean via the biological pump is a critical sink for atmospheric carbon dioxide. This process transports organic carbon to the deep ocean through sinking particulate organic carbon (POC) and the downward transport of suspended POC and dissolved organic carbon (DOC). Changes in the relative contribution of each pathway can significantly affect the magnitude and efficiency of carbon export to depth. Net community production (NCP), an analog of carbon export under steady state assumptions, is typically estimated using budgets of biologically important chemical tracers in the upper ocean constrained by ship‐board or autonomous platform observations. In this study, we use measurements from biogeochemical profiling floats, the Ocean Station Papa mooring, and recently developed algorithms for carbonate system parameters to constrain budgets for three tracers (nitrate, dissolved inorganic carbon, and total alkalinity) and estimate NCP in the Northeast Pacific from 2009 to 2017. Using our multiple‐tracer approach, and constraining end‐member nutrient ratios of the POC and DOC produced, we not only calculate regional NCP throughout the annual cycle and across multiple depth horizons, but also partition this quantity into particulate and dissolved portions. We also use a particle backscatter‐based approach to estimate POC attenuation with depth and present a new method to constrain particle export across deeper horizons and estimate in situ export efficiency. Our results agree well with previously published estimates of regional carbon export annually and suggest that the approaches presented here could be used to assess the magnitude and efficiency of carbon export in other regions of the world's oceans.
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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".