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Record W2035599361 · doi:10.1139/x05-176

Spring and summer hydraulic conductivity of 14 woody species of the sub-boreal forest in British Columbia

2005· article· en· W2035599361 on OpenAlexvenueaboutno aff
Jian R Wang

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEvergreenDeciduousAbies lasiocarpaShrubXylemTaigaWoody plantBotanyBorealScots pineBiologyHydraulic conductivityEcologyPinus <genus>Soil waterPinus contorta

Abstract

fetched live from OpenAlex

Four hydraulic properties of the xylem, the Huber value (HV), hydraulic conductivity (Kh), and specific (Ks) and leaf-specific hydraulic conductivity (K1) were studied during the spring before leaf-out and during the summer after full leaf-out for 14 co-occurring tree and shrub species in the sub-boreal mixedwood forests of central British Columbia. The 14 studied species were divided into deciduous and evergreen angiosperm and gymnosperm groups, including one deciduous gymnosperm species, the tamarack, Larix laricina (Du Roi) K. Koch. I tested whether species with different life forms and classification divisions have different hydraulic properties. HVs were statistically similar for all angiosperms but significantly different among gymnosperms. Long-lived, late-successional species had higher HVs than pioneer and early-successional species. Ks and K1 values for all species except one, subalpine fir, Abies lasiocarpa var. lasiocarpa (Hook.) Nutt., were significantly higher in the spring than in the summer. Conductivity was higher in angiosperms than in gymnosperms in both the spring and the summer, and was highest in deciduous species in both seasons. The results indicate that requirements for mechanical strength may account for the high HVs in conifers, and that the high HVs compensate for low Ks and K1 values. The high hydraulic conductivities observed in the spring coincide with high water availability and high water demand by trees with emerging leaves. The subsequent reduction in Ks and K1 values could be caused by drought-induced embolism and cavitation in early summer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.136
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.241
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2005
Admission routes2
Has abstractyes

Explore more

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