Thermal Perturbation and Rainfall Runoff have Greater Impact on Seasonal Solute Loads than Physical Disturbance of the Active Layer
Bibliographic record
Abstract
ABSTRACT Climate warming in the Arctic will alter hydrological processes and biogeochemical exports from the landscape. Studies have reported that thermokarst disturbances and active‐layer deepening increase solute concentrations in surface waters, but neither the spatial extent nor duration of the impacts of these changes is well understood. We measured total dissolved solute (TDS) concentrations and normalised seasonal TDS fluxes (kg mm‐1) in a series of small headwater catchments in the Canadian High Arctic over three consecutive summers (2007–09) to examine the impact of thermal perturbation (increased soil temperatures) and physical disturbance (active‐layer detachment slides) on solute dynamics in permafrost catchments. We find that usually high July soil temperatures (thermal perturbation) in 2007 resulted in a near‐doubling of solute fluxes during the two subsequent summers, including in a catchment where there was no physical disturbance despite significantly cooler conditions. Solute concentrations increased with the spatial extent of physical disturbances, especially towards the end of the melt season. However, total seasonal solute fluxes did not always increase with the spatial extent of physical disturbances. The results show that the impact of the disturbance area on seasonal solute flux is limited by discharge and hydrological connectivity of the disturbed areas, and that summer rainfall allows for enhanced export of solutes from catchments subject to physical disturbance. Hence, seasonal solute export in these permafrost catchments was more sensitive to thermal perturbations and rainfall runoff than to physical disturbance of the active layer. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.001 | 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".