Bacterial metabolism and growth efficiency in lakes: The importance of phosphorus availability
Bibliographic record
Abstract
We investigated bacterial responses to variations in dissolved organic carbon (DOC) and nutrient availability by a comparative analysis of bacterial metabolism in lakes ranging from oligotrophic to eutrophic. Bacterial growth, respiration, and growth efficiency were quantified in lake water dilution cultures performed in 20 lakes located in eastern Quebec, Canada, which varied with respect to both DOC and nutrient concentrations. Intrinsic growth rates of the bacteria ranged from 0.1 to 1.4 d−, bacterial cell‐specific respiration rates ranged from 0.4 to 7.2 fg C cell−1 h−1, and growth efficiencies ranged from 6.7% to 51.6%. These variations were unrelated to bulk DOC concentrations. Instead, growth rate and efficiency were positively related to total phosphorus concentrations. Specific respiration rate, on the other hand, decreased with increasing phosphorus concentrations, and the magnitude of respiration, on a per‐cell basis, strongly influenced observed growth efficiencies. In a series of substrate enrichment experiments, additions of glucose alone failed to stimulate a response in growth rate, mean cell biovolume, or the potential biomass yield in dilution cultures, but all responded positively to phosphorus additions. Our results show that bacterial metabolism and the fate of DOC input to lake microbial communities are strongly dependent on phosphorus availability, rather than total carbon availability. Extreme oligotrophy appears to place high respiratory demands on the bacterioplankton, resulting in very low bacterial growth efficiencies and consequently greater DOC flow to CO2 than to biomass available for transfer to higher trophic levels.
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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 | 0.000 | 0.000 |
| 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".