Picoheterotroph ( <i>Bacteria</i> and <i>Archaea</i> ) biomass distribution in the global ocean
Bibliographic record
Abstract
Abstract. We compiled a database of 39 766 data points consisting of flow cytometric and microscopical measurements of picoheterotroph abundance, including both Bacteria and Archaea. After gridding with 1° spacing, the database covers 1.3% of the ocean surface. There are data covering all ocean basins and depths except the Southern Hemisphere below 350 m or from April until June. The average picoheterotroph biomass is 3.9 ± 3.6 μg C l−1 with a 20-fold decrease between the surface and the deep sea. We estimate a total ocean inventory of about 1.3 × 1029 picoheterotroph cells. Surprisingly, the abundance in the coastal regions is the same as at the same depths in the open ocean. Using an average of published open ocean measurements for the conversion from abundance to carbon biomass of 9.1 fg cell−1, we calculate a picoheterotroph carbon inventory of about 1.2 Pg C. The main source of uncertainty in this inventory is the conversion factor from abundance to biomass. Picoheterotroph biomass is ~2 times higher in the tropics than in the polar oceans. doi:10.1594/PANGAEA.779142
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".