Growth and specific P-uptake rates of bacterial and phytoplanktonic communities in the Southeast Pacific (BIOSOPE cruise)
Bibliographic record
Abstract
Abstract. Predicting heterotrophic bacteria and phytoplankton specific growth rates (μ ) is of great scientific interest. Many methods have been developed in order to assess bacterial or phytoplankton μ. One widely used method is to estimate μ from data obtained on biomass or cell abundance and rates of biomass or cell production. According to Kirchman (2002), the most appropriate approach for estimating μ is simply to divide the production rate by the biomass or cell abundance estimate. Most methods using this approach to estimate μ are based on carbon (C) incorporation rates and C biomass measurements. Nevertheless it is also possible to estimate μ using phosphate (P) data. We showed that particulate phosphate (PartP) can be used to estimate biomass and that the P uptake rate to PartP ratio can be employed to assess μ. Contrary to other methods using C, this estimator does not need conversion factors and provides an evaluation of μ for both autotrophic and heterotrophic organisms. We report values of P-based μ in three size fractions (0.2–0.6; 0.6–2 and >2 μm) along a Southeast Pacific transect, over a wide range of P-replete trophic status. P-based μ values were higher in the 0.6–2 μm fraction than in the >2 μm fraction, suggesting that picoplankton-sized cells grew faster than the larger cells, whatever the trophic regime encountered. Picoplankton-sized cells grew significantly faster in the deep chlorophyll maximum layer than in the upper part of the photic zone in the oligotrophic gyre area, suggesting that picoplankton might outcompete >2 μm cells in this particular high-nutrient, low-light environment. P-based μ attributed to free-living bacteria (0.2-0.6 μm) and picoplankton (0.6–2 μm) size-fractions were relatively low (0.11±0.07 d−1 and 0.14±0.04 d−1, respectively) in the Southeast Pacific gyre, suggesting that the microbial community turns over very slowly.
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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 | 0.001 | 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 | 0.001 |
| 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".