Patterns of prokaryotic activity along the marine planktonic matter continuum
Bibliographic record
Abstract
Prokaryotic abundance and activity are commonly assessed by dividing them into two size-fractions: free-living and attached to particles. Nevertheless, organic matter, essential for the growth of heterotrophic prokaryotes, is present in the environment in a continuum of sizes, from purely dissolved to large particles. Therefore, defining the activity of the prokaryotic community would be more accurate by considering all the distinct size fractions. To achieve this, we measured prokaryotic abundance (PA), heterotrophic prokaryotic activity (as leucine incorporation) and extracellular enzyme activities at a coastal site in the NW Mediterranean Sea. We conducted measurements in both bulk seawater and size fractionated samples sequentially passing through 5 different filter types: 0.2-0.8-3-5-10 μm pore size. Our results indicate that the fraction <0.8 μm contained the highest percentage of cells (91.6 ± 1.1 %) and leucine incorporation rates (72.2 ± 3.5 %). Most of the extracellular enzyme activity appeared in the dissolved fraction (<0.2 μm; 19.8-79.4 %), yet the specific activity of the enzymes (per cell activity) was 100-1000 times higher in the particulate (>0.8 μm) than in the free-living (0.2-0.8 μm) fraction. The size fraction with highest specific activities for leucine incorporation and most of the enzyme activities (β-glucosidase, esterase, Leu-aminopeptidase and alkaline phosphatase) was the 5-10 μm fraction. In contrast, the higher specific chitobiase activity in the >10 μm fraction, suggests that the prokaryotic community colonizing large particles might be more specialized in the hydrolysis of organic matter of zooplanktonic origin than the community colonizing smaller particles.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".