Dynamics of bacteria–substrate stable isotope separation: dependence on substrate availability and implications for aquatic food web studies
Bibliographic record
Abstract
Heterotrophic bacteria growing without substrate limitation discriminate against the heavier stable isotopes of C and N, which is reflected in the isotopic signatures of consumers of bacteria. We measured bacteria and substrate isotopic separation (C and N) during glucose and ammonium uptake by three strains of bacteria ( Pseudomonas putida , Bacillus megaterium , and Enterobacter aerogenes ) grown in batch culture at 4 and 30 °C. Isotopic separation between bacteria and substrate was dependent on substrate availability. Higher discrimination against the heavier isotopes, and therefore more depleted δ 13 C and δ 15 N values of bacterial biomass, were observed during the exponential growth phase when the nutrient supply was in excess of the demand. We also compared the isotopic ratios of Chironomus tentans grown on aged macrophyte detritus and commercial fish food. Isotopic signatures of Chironomus larvae grown on fish food were within the ranges typical of one trophic step, whereas larvae grown on detritus were strongly depleted in 13 C, suggesting assimilation of bacteria that had grown on the C-rich detritus. Our results are consistent with the very few other studies of bacterial fractionation of nonlimiting nutrients and may also explain the frequent observation of unexpectedly depleted isotopic signatures in aquatic food web studies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".