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Record W2107685744 · doi:10.1139/x07-231

Above- and below-ground biomass accumulation, production, and distribution of sweetgum and loblolly pine grown with irrigation and fertilization

2008· article· en· W2107685744 on OpenAlexvenueno aff
David R. Coyle, Mark D. Coleman, Doug P. Aubrey

Bibliographic record

VenueCanadian Journal of Forest Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersOak Ridge National LaboratoryU.S. Forest ServiceU.S. Department of AgricultureU.S. Department of Energy
KeywordsLiquidambar styracifluaHuman fertilizationBiomass (ecology)IrrigationAgronomyShootPerennial plantNutrientBiologyCoastal plainLoblolly pineBotanyEnvironmental sciencePinus <genus>Ecology

Abstract

fetched live from OpenAlex

Increased forest productivity has been obtained by improving resource availability through water and nutrient amendments. However, more stress-tolerant species that have robust site requirements do not respond consistently to irrigation. An important factor contributing to robust site requirements may be the distribution of biomass belowground, yet available information is limited. We examined the accumulation and distribution of above- and below-ground biomass in sweetgum ( Liquidambar styraciflua L.) and loblolly pine ( Pinus taeda L.) stands receiving irrigation and fertilization. Mean annual aboveground production after 4 years ranged from 2.4 to 5.1 Mg·ha –1 ·year –1 for sweetgum and from 5.0 to 6.9 Mg·ha –1 ·year –1 for pine. Sweetgum responded positively to irrigation and fertilization with an additive response to irrigation + fertilization. Pine only responded to fertilization. Sweetgum root mass fraction (RMF) increased with fertilization at 2 years and decreased with fertilization at 4 years. There were no detectable treatment differences in loblolly pine RMF. Development explained from 67% to 98% of variation in shoot versus root allometry for ephemeral and perennial tissues, fertilization explained no more than 5% of the variation in for either species, and irrigation did not explain any. We conclude that shifts in allocation from roots to shoots do not explain nutrient-induced growth stimulations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.273
Teacher spread0.241 · 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

Citations97
Published2008
Admission routes1
Has abstractyes

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