Illuminating microbial species‐specific effects on organic matter remineralization in marine sediments
Bibliographic record
Abstract
Summary Marine microorganisms play a fundamental role in the global carbon cycle by mediating the sequestration of organic matter in ocean waters and sediments. A better understanding of how biological factors, such as microbial community composition, influence the lability and fate of organic matter is needed. Here, we explored the extent to which organic matter remineralization is influenced by species‐specific metabolic capabilities. We carried out aerobic time‐series incubations of Guaymas Basin sediments to quantify the dynamics of carbon utilization by two different heterotrophic marine isolates ( Vibrio splendidus 1A01; Pseudoalteromonas sp. 3D05). Continuous measurement of respiratory CO 2 production and its carbon isotopic compositions ( 13 C and 14 C) shows species‐specific differences in the rate, quantity and type of organic matter remineralized. Each species was incubated with hydrothermally‐influenced versus unimpacted sediments, resulting in a ~2‐fold difference in respiratory CO 2 yield across the experiments. Genomic analysis indicated that the observed carbon utilization patterns may be attributed in part to the number of gene copies encoding for extracellular hydrolytic enzymes. Our results demonstrate that the lability and remineralization of organic matter in marine environments is not only a function of chemical composition and/or environmental conditions, but also a function of the microorganisms that are present and active.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".