CYCLING AND EXPORT OF PARTICULATE ORGANIC CARBON IN THE OCEAN
Bibliographic record
Abstract
Constraining the processes that control the distribution of carbon in the ocean is critical for understanding how the ocean’s role in the carbon cycle will evolve as global temperatures rise. However, these processes are difficult to measure directly. In this dissertation, computational methods are used to estimate the rates at which particulate organic carbon (POC) aggregates, disaggregates, remineralizes, and is exported down the water column through gravitational settling and zooplankton mediated transport. First, an inverse model is built to estimate rates of particle cycling from POC concentration data collected near Station P in the North Pacific as part of the EXPORTS program. While the model is able to obtain posterior estimates of particle cycling rates that are consistent with the POC concentration data, these estimates were sensitive to the choice of prior estimates. A revised version of this model is then applied to data from the GEOTRACES Pacific meridional transect GP15, which spans a variety of biogeochemical regimes from the south Alaskan gyre to the south Pacific subtropical gyres. Inverse estimates suggest that along GP15, settling speeds of large particles increased with depth below the euphotic zone, but there was no dependence of settling speed on seawater viscosity. The magnitude of POC settling flux out of the euphotic zone was directly related to primary production such that the highest flux occurred in the mesotrophic subarctic gyre and the lowest flux occurred in the oligotrophic subtropical gyres, but the export efficiency was generally low (< 5%) regardless of trophic status. POC appeared to be more cohesive in oligotrophic regions dominated by picoplankton, and, contrary to previous studies, no effect of temperature on remineralization was observed. Finally, a computer vision-based method is demonstrated for estimating carbon settling fluxes from particles visible in camera images with high spatiotemporal resolution while greatly decreasing the amount of human labor required for producing these flux estimates. Overall, this work contributes to a better understanding of how carbon is cycled and exported to depth in the present ocean, and provides insights into how these processes may change in the future.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".