Fjords Are Potential Hotspots of Refractory Dissolved Organic Matter Production: Insights From 1 Year of Weekly Time‐Series Observations of Fluorescent Dissolved Organic Matter in the Bedford Basin, a Northwestern Atlantic Fjord
Bibliographic record
Abstract
Abstract Fjords are representative marine ecosystems that play an important role in regulating coastal carbon cycling. As fingerprints of the dissolved organic matter (DOM) pool, fluorescent DOM (FDOM) is widely used to study the ocean carbon cycle. Here, we report on 1‐year of weekly observations of FDOM (from May 2018 to May 2019) in the Bedford Basin, a well‐studied northwestern Atlantic fjord. Results showed that differences in FDOM indices (biological index, fluorescence index, and humification indices) between the euphotic and aphotic layers changed during the investigation period, suggesting that classical definitions of these indices may not apply consistently. Spearman rank correlations showed that the surface FDOM was affected by physical and biological factors, while water mass renewal was the major control for the deeper layer. Humic‐like FDOM (FDOM H ) changed following the Atlantic deep‐water intrusion, indicating that FDOM H may be used to trace water mass movements in this region. FDOM H shows a significantly positive linear correlation with apparent oxygen utilization (AOU). Their slopes were higher than those from the open ocean, suggesting that the Bedford Basin is a hotspot of RDOM production. Hence, we proposed a possible carbon sequestration mechanism that fjords play as “RDOM producing hot spots” and that the produced RDOM is then transported to the open ocean via water mass movement and finally stored in the ocean for extended periods of time. The proposed biogeochemical processes may also occur, more generally, in the global coastal ocean.
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 | 0.001 | 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) | 0.000 | 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".