Characterization of dissolved fluvial carbon from landscape characteristics across High Arctic headwater streams
Bibliographic record
Abstract
Stream runoff is an important conduit of carbon from the terrestrial ecosystem to the Arctic Ocean, where fluvial carbon is a product of both the source and pathway of the stream network through a watershed. Small headwater streams in the High Arctic are understudied and account for a significant amount of the freshwater geochemical flux from North America. This research investigates the concentration of fluvial dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) across High Arctic streams in order to understand the role of landscape characteristics on carbon transfer from High Arctic watersheds to the Arctic Ocean. Water chemistry data were obtained from 146 streams across four regions on Axel Heiberg Island, NU and the Sabine Peninsula on Melville Island, NU. Different landscape characteristics were identified and characterized across watersheds including terrain features (watershed area, elevation, slope, aspect), hydrology (stream length, stream order), vegetation cover, permafrost disturbances, glacier presence, and geology. Landscape drivers of fluvial carbon vary based on the specific sampling location due to the heterogeneity of the High Arctic landscape, although some trends do emerge. Vegetation cover was identified as a driver of DOC; DOC concentration increases with increasing vegetation coverage. The presence of limestone rock and evaporite rock increases DIC concentration. Vegetation cover and elevation were identified as drivers of DIC; DIC concentrations increase with increasing vegetation cover or decreasing elevations. Regression analyses were conducted to develop models of DOC and DIC concentration across the heterogenous landscape of the Northern Canadian Arctic Archipelago. Vegetation cover, north-south aspects, and elevation provided the greatest significant (p < 0.05) correlations in the regression models. This study helps further the understanding of sources and drivers for fluvial carbon concentrations in the High Arctic and when coupled with stream discharge measurements will aid in the modeling of carbon flux from land to the Arctic Ocean.
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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 | 0.001 |
| 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 | 0.001 | 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".