Spatial Variability of Dissolved Organic Carbon, Solutes, and Suspended Sediment in Disturbed Low Arctic Coastal Watersheds
Bibliographic record
Abstract
Abstract Climate change in the Arctic leads to permafrost degradation and to associated changes in freshwater geochemistry. There is a limited understanding of how disturbances such as active layer detachments or retrogressive thaw slumps impact water quality on a catchment scale. This study investigates how permafrost degradation affects concentrations of dissolved organic carbon (DOC), total dissolved solids (TDS), suspended sediment, and stable water isotopes in adjacent Low Arctic watersheds. We incorporated data on disturbance between 1952 and 2015, as well as sporadic runoff and geochemistry data of streams nearby. Our results show that the total disturbed area decreased by 41% between 1952 and 2015, whereas the total number of disturbances increased by 66% in all six catchments. The spatial variability of hydrochemical parameters is linked to catchment properties and not necessarily reflected at the outflow. Degrading ice‐wedge polygons were found to increase DOC concentrations upstream in Ice Creek West, whereas hydrologically connected disturbances were linked to increases in TDS and suspended sediment. Although we found a great spatial variability of hydrochemical concentrations along the paired watershed, there was a linear relationship between catchment size and daily DOC, total dissolved nitrogen, and TDS fluxes for all six streams. Suspended sediment flux on the contrary did not show a clear relationship as one hydrologically connected retrogressive thaw slump impacted the overall flux in one of the streams. Understanding the spatial variability of water quality will help to model the lateral geochemical fluxes from Arctic catchments.
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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 | 0.002 |
| 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".