Direct measurement of the d13C signature of carbon respired by bacteria in lakes: Linkages to potential carbon sources, ecosystem baseline metabolism, and CO2 fluxes
Bibliographic record
Abstract
Using a novel method to measure the isotopic signature (δd 13 C) of respiratory CO 2 produced by bacterioplankton, we determined the proportion of terrigenous vs. algal‐derived organic carbon (OC) respired by bacteria in a series of eight lakes in southern Que'bec (Canada). The lakes are located within the same general basin but span a large range in trophic status, morphometry, and dissolved OC (DOC) concentrations. Isotopic δ 13 C values of respired CO 2 ranged from ‐28.4‰ to ‐32.5‰ across a gradient of lakes and streams. These values were compared with those of potential OC sources within the lakes (terrigenous and algal) using a mass balance model. The proportion of terrigenous OC respired varied from 3% to >70% and was strongly negatively correlated to lake chlorophyll a (Chl a ) concentrations and weakly positively correlated to DOC: Chl a concentrations. While both total plankton and bacterial respiration (BR) increase with lake Chl a concentration, the component of BR that is supported by terrigenous OC, which ranges from 0.7 to 1.7 mg C L ‐1 h ‐1 , stays essentially constant along the trophic gradient, increasing only slightly with DOC concentration. There is a relatively constant baseline BR supported by terrigenous OC, which becomes diluted by the BR of algal OC as the lakes become more productive. The estimated production of CO 2 through BR of terrigenous OC in the epilimnion explains on average 60% of the estimated air‐water CO 2 flux calculated for these lakes, suggesting that the processing of allochthonous OC by bacteria is a major component of this flux.
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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 | 0.000 | 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) | 0.000 | 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".