Sequential bioavailability of sedimentary organic matter to heterotrophic bacteria
Bibliographic record
Abstract
Summary Aquatic sediments harbour diverse microbial communities that mediate organic matter degradation and influence biogeochemical cycles. The pool of bioavailable carbon continuously changes as a result of abiotic processes and microbial activity. It remains unclear how microbial communities respond to heterogeneous organic matrices and how this ultimately affects heterotrophic respiration. To explore the relationships between the degradation of mixed carbon substrates and microbial activity, we incubated batches of organic‐rich sediments in a novel bioreactor (IsoCaRB) that permitted continuous observations of CO 2 production rates, as well as sequential sampling of isotopic signatures (δ 13 C, Δ 14 C), microbial community structure and diversity, and extracellular enzyme activity. Our results indicated that lower molecular weight (MW), labile, phytoplankton‐derived compounds were degraded first, followed by petroleum‐derived exogenous pollutants, and finally by higher MW polymeric plant material. This shift in utilization coincided with a community succession and increased extracellular enzyme activities. Thus, sequential utilization of different carbon pools induced changes at both the community and cellular level, shifting community composition, enzyme activity, respiration rates, and residual organic matter reactivity. Our results provide novel insight into the accessibility of sedimentary organic matter and demonstrate how bioavailability of natural organic substrates may affect the function and composition of heterotrophic bacterial populations.
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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 | 0.000 |
| 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".