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Record W2164517326 · doi:10.1175/jcli-d-11-00440.1

Projections of Future Soil Temperature and Water Content for Three Southern Quebec Forested Sites

2012· article· en· W2164517326 on OpenAlexaffabout
Daniel Houle, Ariane Bouffard, Louis Duchesne, Travis Logan, Richard Harvey

Bibliographic record

VenueJournal of Climate · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsOuranosEnvironment and Climate Change CanadaMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsEvapotranspirationEnvironmental scienceSnowmeltGrowing seasonWater contentClimate changeBiogeochemical cycleClimatologyHydrology (agriculture)Atmospheric sciencesSnowGeographyEcologyGeology

Abstract

fetched live from OpenAlex

The impacts of climate change on future soil temperature Ts and soil moisture Ms of northern forests are uncertain. In this study, the authors first calibrated Ts and Ms models [Forest Soil Temperature Model (ForSTeM) and Forest Hydrology Model (ForHyM), respectively] using long-term observations of Ts and Ms at different depths measured at three forest sites in eastern Canada. The two models were then used to project Ts and Ms for the period 1971–2100 using historical and future climate scenarios generated by one regional and five global climate models. Results indicate good model performance by ForSTeM and ForHyM in predicting observed Ts and Ms values at various depths for the three sites. Projected annual-mean Ts at these sites increased between 1.1° and 1.9°C and between 1.9° and 3.3°C from the present 30-yr averages (1971–2000) to the periods 2040–69 and 2070–99, respectively. Increases as high as 5.0°C were projected at the black spruce site during the growing season (June) for the period 2070–99. Changes in annual-mean Ms were relatively small; however, seasonally Ms is projected to increase in April, because of earlier snowmelt, and to decrease during the growing season, mainly because of higher evapotranspiration rates. Soil moisture in the growing season could be reduced by 20%–40% for the period 2070–99 compared to the reference period. The projected warmer and drier soil conditions in the growing season could have significant impacts on forests growth and biogeochemical cycles.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.151

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)0.0000.000

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 head0.013
GPT teacher head0.216
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.

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

Citations109
Published2012
Admission routes2
Has abstractyes

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