Mobilization of Geochemical Elements to Surface Water in the Active Layer of Permafrost in the Russian Arctic
Bibliographic record
Abstract
Abstract The predicted increase of ground temperatures in the Arctic results in the deepening of the active layer and intensification of geochemical processes. Determining the responses of riparian soil systems to surrounding hydrological flows is important for understanding seasonal changes in hydrological processes. In this study, one soil core from a polygon rim (close to the Taz River, TA) and two soil cores from a riverine terrace (close to the Syoyakha River, SY and Murtyyakha River, MU) in Western Siberia, Russia, and their suprapermafrost water, adjacent surface flows, and river water were sampled for analysis of geochemical elements. Results showed that most elements above their respective detection limits began accumulating in the underlying gleyed layer during September‐October in response to the deepest thaw in the active layer. This study focused on the highly mobile elements in the deepest layer; and found that the transport of organic matter in the upper layer carried these elements to both surface water ponds/flows and suprapermafrost water, and further, to the rivers. The efflux of released elements from surface soil to surrounding surface water appeared to be low. The best linear correlation for both surface flows and river water was with Mn; therefore, Mn may be a proxy for predicting the processes occurring within the active layer during the annual summer‐autumn thaw. Moreover, landscapes with different ice contents may experience changes in the elements transported to surface waters. A general conceptual model for the response of elements to the thawing‐freezing process of the active layer is established.
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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 | 0.000 | 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".