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 (RTSs) on DOC concentration and transport, using data from eight RTS features on the Peel Plateau, NWT, 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 Laurentide Ice Sheet. RTS features are now widespread in this region, with headwall exposures up to 30 m high and total disturbed areas often exceeding 20 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 fluxes of total suspended solids suggest that the substantial fine-grained sediments released by RTS features may sequester DOC. Runoff obtained directly from slump rill water, above entry into recipient streams, indicates that the deepest RTS features, which thaw the greatest extent of buried, Pleistocene-aged glacial tills, release low-concentration DOC when compared to paired upstream, undisturbed locations, while 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 site indicates that temperature and precipitation serve as primary environmental controls on above-slump and below-slump DOC flux, but it also shows that the relationship between climatic parameters and DOC flux is complex for these dynamic thermokarst features. These results demonstrate that we should expect clear variation in thermokarst-associated DOC mobilization across Arctic regions. However, they also show that within-region variation in thermokarst intensity and landscape composition is critical for determining the biogeochemical response. Geological and climate legacy shape the physical and chemical composition of permafrost and thermokarst potential. As such, these factors must be considered in predictions of land-to-water carbon mobilization in a warming Arctic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".