Mechanisms of microbial carbon sequestration in the ocean – future research directions
Bibliographic record
Abstract
Abstract. This paper reviews progress on understanding biological carbon sequestration in the ocean with special reference to the microbial formation and transformation of recalcitrant dissolved organic carbon (RDOC), the microbial carbon pump (MCP). We propose that RDOC is a concept with a wide continuum of recalcitrance. Most RDOC compounds maintain their levels of recalcitrance only in a specific environmental context (RDOCt). The ocean RDOC pool also contains compounds that may be inaccessible to microbes due to their extremely low concentration (RDOCc). This differentiation allows us to appreciate the linkage between microbial source and RDOC composition on a range of temporal and spatial scales. Analyses of biomarkers and isotopic records show intensive MCP processes in the Proterozoic oceans when the MCP could have played a significant role in regulating climate. Understanding the dynamics of the MCP in conjunction with the better constrained biological pump (BP) over geological timescales could help to predict future climate trends. Integration of the MCP and the BP will require new research approaches and opportunities. Major goals include understanding the interactions between particulate organic carbon (POC) and RDOC that contribute to sequestration efficiency, and the concurrent determination of the chemical composition of organic carbon, microbial community composition and enzymatic activity. Molecular biomarkers and isotopic tracers should be employed to link water column processes to sediment records, as well as to link present-day observations to paleo-evolution. Ecosystem models need to be developed based on empirical relationships derived from bioassay experiments and field investigations in order to predict the dynamics of carbon cycling along the stability continuum of POC and RDOC under potential global change scenarios. We propose that inorganic nutrient input to coastal waters may reduce the capacity for carbon sequestration as RDOC. The nutrient regime enabling maximum carbon storage from combined POC flux and RDOC formation should therefore be sought.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".