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Characterization of mobilized sediments and organic matter in retrogressive thaw slumps on the Peel Plateau, NWT, Canada

2020· article· en· W3086732869 on OpenAlexaffabout
Lisa Bröder, Kirsi Keskitalo, Scott Zolkos, Sarah Shakil, Suzanne E. Tank, Tommaso Tesi, Bart E. van Dongen, Negar Haghipour, Timothy I. Eglinton, Jorien E. Vonk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPermafrostGeologySedimentOrganic matterDebrisFluvialBiogeochemical cyclePlateau (mathematics)GeomorphologyGeochemistryOceanographyEnvironmental chemistryChemistryStructural basin

Abstract

fetched live from OpenAlex

The Peel Plateau in northwestern Canada hosts some of the fastest growing “mega slumps”, retrogressive thaw slumps exceeding 2000 m2 in area. The region is located at the former margin of the Laurentide ice sheet and its landscape is dominated by ice-rich hummocky moraines. Rapid permafrost thaw resulting from enhanced warming and increases in summer precipitation has been identified as a major driver of sediment mobilization in the area, with some of the largest slumps relocating up to 106 m3 of previously frozen sediments into fluvial networks. The biogeochemical transformation of this thawed substrate within fluvial networks may represent a source of CO2 to the atmosphere and have a large impact on downstream ecosystems, yet its fate is currently unclear. Concentrations of dissolved organic matter are lowered in slump-impacted streams, while the particle loads increase. Here, we aim to characterize the mobilized material and its sources by analyzing active layer, Holocene and Pleistocene permafrost, debris (recently thawed, still at the headwall) and slump outflow samples from four different slumps on the Peel Plateau. We use sediment properties (mineral surface area, grain size distribution), carbon isotopes (13C, 14C) and molecular markers (solvent-extractable lipids, lignin phenols, cutin acids, non-extractable compound classes analyzed by pyrolysis-GCMS) in order to assess the composition and quality of the mobilized sediment and organic matter and thereby improve our understanding of their fate and downstream effects. Preliminary results show that organic matter content and radiocarbon age in debris and outflow from all four slumps are dominantly derived from Holocene and Pleistocene permafrost soils with a smaller influence of the organic-rich active layer. Degradation proxies based on extractable lipid and lignin biomarkers suggest Holocene and Pleistocene permafrost organic matter to be more matured than the fresh plant material found in the active layer, while debris and outflow samples show a mixed signal. For the non-extractable organic matter, aromatics and phenols make up the largest fraction of all samples. Lignin markers are almost exclusively found in the active layer samples, which also contain a larger proportion of polysaccharides, while N-containing compounds and alkanes make up the remaining 2-25 % with no obvious patterns. Active layer soils also have the highest median grain sizes, whereas Pleistocene permafrost soils consist of much finer mineral grains. Samples collected at the slump outflow are significantly more homogeneous (i.e., showing a narrower grain size distribution) than any of the other samples. We thus infer that both organic matter degradation and hydrodynamic sorting during transport play a role within these slump features; determining their relative magnitudes will be crucial to better assess potential feedbacks of these increasingly abundant “mega slumps” to changing climate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.022
GPT teacher head0.195
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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