Multi-decadal increases in dissolved organic carbon and alkalinity flux from the Mackenzie drainage basin to the Arctic Ocean
Bibliographic record
Abstract
Riverine exports of organic and inorganic carbon (OC, IC) to oceans are intricately linked to processes occurring on land. Across high latitudes, thawing permafrost, alteration of hydrologic flow paths, and changes in vegetation may all affect this flux, with subsequent implications for regional and global carbon (C) budgets. Using a unique, multi-decadal dataset of continuous discharge coupled with water chemistry measurements for the Mackenzie River, we show major increases in dissolved OC (DOC) and IC (as alkalinity) fluxes since the early 1970s, for a watershed that covers 1.8 M km 2 of northwestern Canada, and provides substantial inputs of freshwater and biogeochemical constituents to the Arctic Ocean. Over a 39-year period of record, DOC flux at the Mackenzie mouth increased by 39.3% (44.5 ± 22.6 Gmol), while alkalinity flux increased by 12.5% (61.5 ± 60.1 Gmol). Isotopic analyses and substantial increases in sulfate flux indicate that increases in alkalinity are driven by accelerating sulfide oxidation, a process that liberates IC from rock and soils in the absence of CO 2 consumption. Seasonal and sub-catchment trends suggest that permafrost thaw plays an important role in the observed increases in DOC and alkalinity: sub-catchment increases for all constituents are confined to northern, permafrost-affected regions, while observed increases in autumn to winter are consistent with documented landscape-scale changes that have resulted from changing thaw dynamics. This increase in DOC and sulfide-derived alkalinity represents a substantial intensification of land-to-ocean C mobilization, at a level that is significant within the regional C budget. The change we observe, for example, is similar to current and projected future rates of CO 2 consumption by weathering in the Mackenzie basin.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".