Source water controls on the character and origin of dissolved organic matter in streams of the Yukon River basin, Alaska
Bibliographic record
Abstract
Climate warming and permafrost degradation at high latitudes will likely impact watershed hydrology, and consequently, alter the concentration and character of dissolved organic carbon (DOC) in northern rivers. We examined seasonal variation of DOC chemistry in 16 streams of the Yukon River basin, Alaska. Our primary objective was to evaluate the relationship between source water (shallow versus deep groundwater flow paths) and DOC chemical composition. Using base cation chemistry and principal component analysis, we observed high contributions of deep groundwater to glacial and clearwater streams, whereas blackwater streams received larger contributions from shallow groundwater sources. DOC concentration and specific ultraviolet absorbance peaked during spring snowmelt in all streams, and were consistently higher in blackwater streams than in glacial and clearwater streams. The hydrophobic acid fraction of DOC dominated across all streams and seasons, comprising between 35% and 56% of total DOC. The hydrophilic acid fraction of DOC was more prominent in glacial (23% ± 3%) and clearwater streams (19% ± 1%) than in blackwater streams (16% ± 1%), and was enriched during winter base flow (29% ± 1%) relative to snowmelt and summer base flow. We observed that an increase in the contribution of deep groundwater to streamflow resulted in decreased DOC concentration, aromaticity, and DOC‐to‐dissolved organic nitrogen ratio, and an increase in the proportion of hydrophilic acids relative to hydrophobic acids. Our findings suggest that future permafrost degradation and higher contributions of groundwater to streamflow may result in a higher fraction of labile DOM in streams of the Yukon 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 | 0.001 | 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".