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Record W2466154958 · doi:10.1002/eco.1750

Hydroclimatic influences on peatland CO<sub>2</sub> exchange following upland forest harvesting on the Boreal Plains

2016· article· en· W2466154958 on OpenAlexaffabout
Janina M. Plach, Richard M. Petrone, J. M. Waddington, Nicholas Kettridge, K. J. Devito

Bibliographic record

VenueEcohydrology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of AlbertaMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsPeatEnvironmental scienceBorealEvapotranspirationDeforestation (computer science)Growing seasonLoggingMicroclimateHydrology (agriculture)Water contentEcosystemForestryEcologyGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Abstract A comparative study of forest clear‐cut logging effects on daily growing season (May to October) net ecosystem CO 2 exchange (NEE) of adjacent peatlands was conducted in two neighbouring forest upland‐peatland complexes over 4 years (2005 to 2008) on the Boreal Plains (BP) of Alberta, Canada. Higher vapour pressure deficit at the harvested‐upland (H‐U) peatland, reflecting increased turbulent mixing after adjacent upland forest removal (2007 and 2008), resulted in increased peatland evapotranspiration rates that contributed to a seasonal decline in soil moisture (volumetric moisture content) influencing NEE. Overall, a significant change in mid‐season NEE occurred at the H‐U peatland 1 year post‐harvesting, greater than NEE changes at the neighbouring intact‐upland peatland. However, 2 years post‐harvesting, mid‐season NEE returned to within range of pre‐harvesting variability (−0.54 to 1.34 g CO 2 ‐C m −2 day −1 ). Results of this study demonstrate that BP peatland NEE is largely regulated by site‐specific water availability, which, in turn, may be influenced in the short term by shifting microclimate and soil moisture patterns because of clear‐cut logging. As such, predicting long‐term carbon storage function of BP peatlands will require careful consideration of changing hydroclimatic conditions because of rapid expansion of BP deforestation, given that these ecosystems already exist in a state of hydrologic risk in this moisture deficit eco‐region. Copyright © 2016 John Wiley &amp; 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)0.001
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 score0.037
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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