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Record W4230624122 · doi:10.1139/x99-199

Effects of elevated CO<sub>2</sub>, N-fertilization, and season on survival of ponderosa pine fine roots

2000· article· en· W4230624122 on OpenAlexvenueno aff
Mark G. Johnson, Donald L. Phillips, David T. Tingey, Marjorie J. Storm

Bibliographic record

VenueCanadian Journal of Forest Research · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsnot available
Fundersnot available
KeywordsPinus <genus>Human fertilizationLife spanAnimal scienceGrowing seasonBotanyNutrientHorticultureBiologyChemistryAgronomyEcology

Abstract

fetched live from OpenAlex

We used minirhizotrons to assess the effects of elevated CO 2 , N, and season on the life-span of ponderosa pine (Pinus ponderosa Dougl. ex Laws.) fine roots. CO 2 levels were ambient air (A), ambient air + 175 µmol·mol -1 (A + 175) and ambient air + 350 µmol·mol -1 (A + 350). N treatments were 0, 100, and 200 kg N·ha -1 per year (N0, N100, and N200, respectively). Fine root survival was strongly influenced by season and seemed to be most strongly linked to soil temperature. Roots born in the fall and winter had longer median root life-span (MRLs) than those born during the spring and summer. Elevated CO 2 increased root life-span, but N fertilization decreased it. Under A, MRL was 74 ± 12 days (mean ± SE) and was significantly different from the MRL for the A + 350 treatment (102 ± 14 days). MRL under A + 175 averaged 92 ± 10 days. MRL was 116 ± 13 days for the N0 treatment and was significantly greater than MRL for the N100 (70 ± 10 days) and N200 (62 ± 14 days) treatments. Assuming that longer lived fine roots continue their resource acquisition functions, then elevated CO 2 may have the effect of extending the resource acquisition period. In contrast, fine roots in N-rich environments have shorter life-spans than fine roots in N-poor environments.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.257
Teacher spread0.233 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

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