DOM degradation by light and microbes along the Yukon River-coastal ocean continuum
Bibliographic record
Abstract
The Arctic is experiencing rapid warming, resulting in fundamental shifts in hydrologic connectivity and carbon cycling. Dissolved organic matter (DOM) is a significant component of the Arctic and global carbon cycle, and significant perturbations to DOM cycling are expected with Arctic warming. The impact of photochemical and microbial degradation, and their interactive effects, on DOM composition and remineralization have been documented in Arctic soils and rivers. However, the role of microbes, sunlight and their interactions on Arctic DOM alteration and remineralization in the coastal ocean has not been considered, particularly during the spring freshet when DOM loads are high, photoexposure can be quite limited and residence time within river networks is low. Here, we collected DOM samples along a salinity gradient in the Yukon River delta, plume and coastal ocean during peak river discharge immediately after spring freshet and explored the role of UV exposure, microbial transformations and interactive effects on DOM quantity and composition. Our results show: (1) photochemical alteration of DOM significantly shifts processing pathways of terrestrial DOM, including increasing relative humification of DOM by microbes by > 10%; (2) microbes produce humic-like material that is not optically distinguishable from terrestrial humics; and (3) size-fractionation of the microbial community indicates a size-dependent role for DOM remineralization and humification of DOM observed through modeled PARAFAC components of fluorescent DOM, either through direct or community effects. Field observations indicate apparent conservative mixing along the salinity gradient; however, changing photochemical and microbial alteration of DOM with increasing salinity indicate changing DOM composition likely due to microbial activity. Finally, our findings show potential for rapid transformation of DOM in the coastal ocean from photochemical and microbial alteration, with microbes responsible for the majority of dissolved organic matter remineralization.
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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 | 0.001 | 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".