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Record W4398243381 · doi:10.1007/s10021-024-00904-1

Wind as a Driver of Peat CO2 Dynamics in a Northern Bog

2024· article· en· W4398243381 on OpenAlexafffundabout
Audrey Campeau, Hongxing He, Joakim Riml, Elyn Humphreys, M. Dalva, Nigel T. Roulet

Bibliographic record

VenueEcosystems · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsCarleton UniversityUniversité de MontréalMcGill UniversityUniversité du Québec
FundersNatural Sciences and Engineering Research Council of CanadaSveriges LantbruksuniversitetSvenska Forskningsrådet Formas
KeywordsPeatEnvironmental scienceBogDiffusionAtmospheric sciencesWind speedDiel vertical migrationAtmosphere (unit)Soil scienceHydrology (agriculture)GeologyEcologyMeteorologyPhysics

Abstract

fetched live from OpenAlex

Abstract Excess CO 2 accumulated in soils is typically transported to the atmosphere through molecular diffusion along a concentration gradient. Because of the slow and constant nature of this process, a steady state between peat CO 2 production and emissions is often established. However, in peatland ecosystems, high peat porosity could foster additional non-diffusive transport processes, whose dynamics may become important to peat CO 2 storage, transport and emission. Based on a continuous record of in situ peat pore CO 2 concentration within the unsaturated zone of a raised bog in southern Canada, we show that changes in wind speed create large diel fluctuations in peat pore CO 2 store. Peat CO 2 builds up overnight and is regularly flushed out the following morning. Persistently high wind speed during the day maintains the peat CO 2 with concentrations close to that of the ambient air. At night, wind speed decreases and CO 2 production overtakes the transport rate leading to the accumulation of CO 2 in the peat. Our results indicate that the effective diffusion coefficient fluctuates based on wind speed and generally exceeds the estimated molecular diffusion coefficient. The balance between peat CO 2 accumulation and transport is most dynamic within the range of 0–2 m s −1 wind speeds, which occurs over 75% of the growing season and dominates night-time measurements. Wind therefore drives considerable temporal dynamics in peat CO 2 transport and storage, particularly over sub-daily timescales, such that peat CO 2 emissions can only be directly related to biological production over longer timescales.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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 teacher head, not a consensus.

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

Citations3
Published2024
Admission routes3
Has abstractyes

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