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Record W4312199695 · doi:10.1002/lno.12288

High ebullitive, millennial‐aged greenhouse gas emissions from thermokarst expansion of peatland lakes in boreal western Canada

2022· article· en· W4312199695 on OpenAlexafffundabout
McKenzie A. Kuhn, Megan Schmidt, Liam Heffernan, Jördis Stührenberg, Klaus‐Holger Knorr, Cristian Estop‐Aragonés, Tanja Broder, Regina Gonzalez Moguel, Peter Douglas, David Olefeldt

Bibliographic record

VenueLimnology and Oceanography · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsMcGill UniversityUniversity of WaterlooUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston Foundation
KeywordsThermokarstPeatPermafrostGreenhouse gasBorealEnvironmental scienceRadiocarbon datingMethaneCarbon dioxideTaigaAtmospheric sciencesPhysical geographyHydrology (agriculture)SedimentEnvironmental chemistryClimatologyGeologyGeomorphologyOceanographyChemistryEcologyForestryGeography

Abstract

fetched live from OpenAlex

Abstract Methane (CH4) and carbon dioxide (CO2) emissions from small peatland lakes may be highly sensitive to climate warming and thermokarst expansion caused by permafrost thaw. We studied effects of thermokarst expansion on ebullitive CH4 and CO2 fluxes and diffusive CH4 fluxes from a peatland thaw lake in boreal western Canada. Ebullitive CH4 fluxes from the thaw edge (236 ± 61 mg CH4 m−2 d−1) were double and quadruple that of the stable lake edge and center, respectively. Modeled diffusive CH4 fluxes did not differ between the thawing and stable edges (~ 50 mg CH4 m−2 d−1) but were double that of the center. Radiocarbon (14C) analysis of CH4 and CO2 bubbles from the thaw edge was older (~ 1211 and 1420 14C yr BP) than from the stable edge and the center (modern to ~ 102 and 50 14C yr BP, respectively). Incubations indicated that deep, old peat sediment was more labile along the thaw edge than in the center. While our study suggested increase CH4 emissions partly derived from millennial‐aged carbon along the thaw edge, accounting for these emissions only increased the estimated total lake CH4 emissions by ~ 10%, which is a much smaller contribution than measured from thermokarst lakes in yedoma regions. Our study suggests that it is important to account for landscape history and lake types when studying the processes that govern the sensitivity of lake greenhouse gas emissions to climate change.

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 score0.118
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

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

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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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".

Quick stats

Citations9
Published2022
Admission routes3
Has abstractyes

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