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Record W2120060138 · doi:10.1080/02827580310015044

Response of<i>Populus tremuloides</i>,<i>Populus balsamifera</i>,<i>Betula papyrifera</i>and<i>Picea glauca</i>Seedlings to Low Soil Temperature and Water-logged Soil Conditions

2003· article· he· W2120060138 on OpenAlexafffund
Simon M. Landhäusser, U. Silins, Victor J. Lieffers, Wei Liu

Bibliographic record

VenueScandinavian Journal of Forest Research · 2003
Typearticle
Languagehe
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Alberta
FundersAlberta-Pacific Forest Industries
KeywordsTranspirationSalicaceaeSoil waterWater tableEnvironmental scienceBetula platyphyllaBotanyAgronomyWater potentialWater contentHorticultureBiologyWoody plantPhotosynthesisGroundwaterSoil scienceGeology

Abstract

fetched live from OpenAlex

Populus balsamifera L., Betula papyrifera Marsh., Populus tremuloides Michx. and Picea glauca (Moench) Voss seedlings were grown in specialized pots that maintained a constant water-table height and allowed monitoring of water use by the tree/pot under high water-table conditions and different soil temperatures. The trees were grown at imperfectly and poorly drained water table conditions and at 5, 10 or 20°C soil temperature. In P. balsamifera, net assimilation and transpiration remained high under wet soil conditions and increased with higher soil temperatures. Populus balsamifera growth and leaf area development were severely restricted at soil temperatures of 5°C. Both B. papyrifera and P. tremuloides had low transpiration and pot level water-use rates at both water-table conditions and these did not significantly increase with increasing soil temperature. Picea glauca was negatively affected by high water tables but showed minimal response to soil temperature changes. The study suggests that P. balsamifera would be a good hydrological nurse crop to lower the water table when soils are warm, while B. papyrifera is likely to be a good nurse species in cool and imperfectly drained sites.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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

Citations45
Published2003
Admission routes2
Has abstractyes

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