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Record W2780345951 · doi:10.1021/acs.est.7b04979

Changes in Methane Flux along a Permafrost Thaw Sequence on the Tibetan Plateau

2017· article· en· W2780345951 on OpenAlexaff
Guibiao Yang, Yunfeng Peng, David Olefeldt, Yongliang Chen, Guanqin Wang, Fei Li, Dianye Zhang, Jun Wang, Jianchun Yu, Li Liu, Shuqi Qin, Tianyang Sun, Yuanhe Yang

Bibliographic record

VenueEnvironmental Science & Technology · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Alberta
FundersPeking UniversityMinistry of Science and Technology of the People's Republic of ChinaChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsThermokarstPermafrostMethaneEnvironmental scienceWetlandHydrology (agriculture)SwampAtmospheric methaneSoil scienceEnvironmental chemistryGeologyChemistryEcologyGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

Permafrost thaw alters the physical and environmental conditions of soil and may thus cause a positive feedback to climate warming through increased methane emissions. However, the current knowledge of methane emissions following thermokarst development is primarily based on expanding lakes and wetlands, with upland thermokarst being studied less often. In this study, we monitored the methane emissions during the peak growing seasons of two consecutive years along a thaw sequence within a thermo-erosion gully in a Tibetan swamp meadow. Both years had consistent results, with the early and midthaw stages (3 to 12 years since thaw) exhibiting low methane emissions that were similar to those in the undisturbed meadow, while the emissions from the late thaw stage (20 years since thaw) were 3.5 times higher. Our results also showed that the soil water-filled pore space, rather than the soil moisture per se, in combination with the sand content, were the main factors that caused increased methane emissions. These findings differ from the traditional view that upland thermokarst could reduce methane emissions owing to the improvement of drainage conditions, suggesting that upland thermokarst development does not always result in a decrease in methane emissions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.040
GPT teacher head0.257
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations72
Published2017
Admission routes1
Has abstractyes

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