Retrogressive thaw slumps temper dissolved organic carbon delivery to streams of the Peel Plateau, NWT, Canada
Bibliographic record
Abstract
Abstract. In Siberia and Alaska, permafrost thaw has been associated with significant increases in the delivery of dissolved organic carbon (DOC) to recipient stream ecosystems. Here, we examine the effect of retrogressive thaw slumps (RTS) on DOC concentration and transport, using data from eight RTS features on the Peel Plateau, NT, Canada. Like extensive regions of northwestern Canada, the Peel Plateau is comprised of thick, ice-rich tills that were deposited at the margins of the continental ice sheet. RTS features are now widespread in this region, with headwall exposures up to 30 m high, and total disturbed areas often exceeding 30 ha. We find that intensive slumping on the Peel Plateau is universally associated with decreasing DOC concentrations downstream of slumps, even though the composition of slump-derived dissolved organic matter (DOM; assessed using specific UV absorbance and slope ratios) is similar to permafrost-derived DOM from other regions. Comparisons of upstream and downstream DOC flux relative to a conservative tracer suggest that the substantial fine-grained sediments released by slumping may sequester DOC on this landscape. Runoff obtained directly from within slump features, above entry into recipient streams, indicates that the deepest RTS features, which thaw the greatest extent of buried, Pleistocene-aged glacial tills, have the lowest runoff DOC concentrations when compared to upstream, un-disturbed locations. In contrast, shallower features, with exposures that are more limited to a relict Holocene active layer, have within-slump DOC concentrations more similar to upstream sites. Finally, fine-scale work at a single RTS feature indicates that temperature and precipitation serve as primary environmental controls on above-slump and below-slump DOC flux, but that the relationship between climatic parameters and DOC flux is complex for these dynamic thermokarst features. These results demonstrate that we should expect striking variation in thermokarst-associated DOC mobilization across Arctic regions, but that within-region variation in thermokarst intensity and other landscape factors are also important for determining biogeochemical response. An understanding of landscape and climate history, permafrost genesis, soil composition, the nature and intensity of thermokarst, and the interaction of these factors, is critical for predicting changes in land-to-water carbon mobilization in a warming circumpolar world.
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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 | 0.001 | 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) | 0.001 | 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".