Phytoplankton size-class contributions to new and regenerated production during the EXPORTS Northeast Pacific Ocean field deployment
Bibliographic record
Abstract
The NASA EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) program was established to better quantify the pathways of the biological carbon pump in order to gain a more comprehensive understanding of global carbon export efficiency. The summer 2018 field campaign in the vicinity of Ocean Station Papa (Station P; 50°N, 145°W) in the Northeast Pacific Ocean yielded evidence of low phytoplankton biomass and primary productivity dominated by small cells (<5 µm) that are reliant on recycled nutrients. Using combined 13C/15N stable isotope incubations, we calculated an average depth-integrated dissolved inorganic carbon uptake (net primary production) rate of 23.1 mmol C m–2 d–1 throughout the euphotic zone with small cells contributing 88.9% of the total daily DIC uptake. Average depth-integrated NO3– uptake rates were 1.5 mmol N m–2 d–1 with small cells contributing 73.4% of the total daily NO3– uptake. Estimates of new and regenerated production fluctuated, with small cells continuing to dominate both forms of production. The daily mixed-layer f-ratio ranged from 0.17 to 0.38 for the whole community, consistent with previous studies, which indicates a predominance of regenerated production in this region, with small and large cells (≥5 μm) having average f-ratios of 0.28 and 0.82, respectively. Peak phytoplankton biomass, total primary productivity and new production occurred between Julian Days 238 and 242 of our observation period, driven primarily by an increase in carbon and nitrate assimilation rates without apparent substantial shifts in the phytoplankton size-class structure. Our findings demonstrate the importance of small cells in performing the majority of net primary production and new production and the modest productivity fluctuations that occur in this iron-limited region of the Northeast Pacific Ocean, driven by ephemeral increases in new production, which could have significant ramifications for carbon export over broad timescales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".