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Record W1983108071 · doi:10.1139/x02-186

Whole-seedling biomass allocation, leaf area, and tissue chemistry for Douglas-fir exposed to elevated CO<sub>2</sub> and temperature for 4 years

2003· article· en· W1983108071 on OpenAlexvenueno aff
David M. Olszyk, David T. Tingey, Paul T. Rygiewicz, Claudia Wise, Erica VanEss, Annick Benson, Marjorie J. Storm, Richard King

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsnot available
Fundersnot available
KeywordsBiomass (ecology)SugarSeedlingChemistryHorticultureDry weightBotanyCelluloseLimitingAgronomyBiology

Abstract

fetched live from OpenAlex

Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seedlings were grown under ambient or elevated ( ambient + 180 µmol·mol –1 ) CO 2 and ambient or elevated (ambient + 3.5°C) temperature in outdoor, sunlit chambers with a field soil. After 4 years, seedlings were harvested and measured for leaf area, leaf, fine root (&lt;1 mm diameter), and structural (buds, branches, stems, main root, and lateral roots &gt;1 mm in diameter) dry masses, and leaf and fine root C/N ratio, percent sugar, and percent cellulose. Elevated CO 2 did not affect biomass production or allocation for any plant organ but increased specific leaf mass, leaf C/N ratio, and percent sugar and decreased the ratio of leaf area to structural weight and leaf percent cellulose. Elevated temperature tended to reduce biomass allocation to leaves and leaf sugar concentration. Fine root percent sugar tended to increase with elevated temperature but only at elevated CO 2 . Therefore, for Douglas-fir seedlings growing under naturally limiting soil moisture and nutrition conditions, elevated CO 2 and temperature may have little impact on biomass or leaf area except for reduced specific leaf mass with elevated CO 2 and reduced biomass allocation to leaves with elevated temperature. However, both elevated CO 2 and temperature may alter leaf chemistry.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.036
GPT teacher head0.271
Teacher spread0.235 · 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 designBench or experimental
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

Citations68
Published2003
Admission routes1
Has abstractyes

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