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Record W2165979799 · doi:10.1093/treephys/28.12.1851

Effects of above- and belowground partial harvest disturbance on growth and water status of residual sugar maple

2008· article· en· W2165979799 on OpenAlexaff
Henrik Hartmann, Christian Wirth, Christian Messier, Frank Berninger

Bibliographic record

VenueTree Physiology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMapleSugarResidualDisturbance (geology)Environmental scienceBiologyBotanyHorticultureMathematicsFood science

Abstract

fetched live from OpenAlex

Partial forest harvesting is known to modify both above- and belowground resource availability and may result in direct and indirect stress to the residual trees as a result of machinery traffic and sudden changes in irradiance. We studied sugar maple (Acer saccharum Marsh.) trees in stands that had undergone a selection harvest 11 years before sampling to verify whether sudden increases in light availability and soil disturbance caused by machinery influence growth rates and lead to water stress. We selected trees that had experienced either no disturbance from partial harvest, soil disturbance only, sudden increases in light availability only or both disturbances. We analyzed stem radial growth rates and stable carbon isotope composition (delta(13)C) of stem wood with an annual resolution from 10 years before partial harvest until 10 years after partial harvest. Disturbances from partial harvest did not negatively affect growth rates or tree water status. Although trees that experienced increased light availability had higher (less negative) delta(13)C after harvest (indicating increased water-use efficiency), they also had higher growth rates, suggesting that they experienced no pronounced water stress. Trees subjected to soil disturbance showed no sign of water stress. These results may partly be associated with favorable growth conditions (abundant precipitation and mild temperature) in the years following harvest and could differ from results that would be observed under more severe climatic conditions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.274

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 studies0.0000.001
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 head0.006
GPT teacher head0.193
Teacher spread0.188 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

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