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Record W1612065363 · doi:10.1002/hyp.9898

Towards quantifying the negative feedback regulation of peatland evaporation to drought

2013· article· en· W1612065363 on OpenAlexafffund
Nicholas Kettridge, J. M. Waddington

Bibliographic record

VenueHydrological Processes · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeatEnvironmental scienceSphagnumBorealWater tableEvaporationHumidityMoistureHydrology (agriculture)Atmospheric sciencesWater contentSoil scienceGeologyEcologyChemistryMeteorologyGroundwater

Abstract

fetched live from OpenAlex

Abstract The frequency and intensity of drought is projected to increase within the boreal region under future climatic conditions. Peatlands are widely considered to regulate water loss under drought conditions, increasing surface resistance ( r s ) and reducing evaporative losses. This maintains peat moisture content, increasing the resilience of these globally important carbon stores. However, the magnitude and form of this important negative feedback response remains uncertain. To address this, we monitored the response of r s to drought within four peat cores under controlled meteorological conditions. When the water‐table was dropped to a depth of 0.30 m and the humidity reduced to ≤40%, a step shift in r s from ~50 s m ‐1 up to 1000 s m ‐1 was observed within burned and unburned peat, which virtually shuts down evaporation, limiting water loss. We show that measured near‐surface tension cannot be used to directly calculate this transition in peat surface resistance. However, empirical relationships that account for strong vertical variations in tension through the near‐surface and/or disequilibrium between pore air and near‐surface pore water pressure provide the potential to incorporate this negative feedback response into peatland ecohydrological models. Further observations are necessary to examine this response under dynamic atmospheric conditions. We suggest that the link between surface temperature and evaporation provides potential to further examine this feedback in either burned peatlands or peatlands with a low vascular vegetation cover. Copyright © 2013 John Wiley & Sons, Ltd.

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 score0.142
Threshold uncertainty score0.998

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)0.0020.000

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 head0.030
GPT teacher head0.259
Teacher spread0.229 · 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

Citations60
Published2013
Admission routes2
Has abstractyes

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