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Record W1970791523 · doi:10.2136/sssaj2004.5960

Root Development of Young Loblolly Pine in Spodosols in Southeast Georgia

2004· article· en· W1970791523 on OpenAlexaff
H. Adégbidi, N. B. Comerford, Eric J. Jokela, N. F. de Barros

Bibliographic record

VenueSoil Science Society of America Journal · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversité de Moncton
FundersU.S. Department of Energy
KeywordsShootLoblolly pineRoot systemRoot (linguistics)Environmental scienceBotanySoil horizonAgronomySoil waterBiologyHorticulturePinus <genus>Soil science

Abstract

fetched live from OpenAlex

Determining fine‐root dynamics is fundamental to forest soil nutrient management yet root development of fast‐growing loblolly pine ( Pinus taeda L.) is poorly documented. The objectives of this study were to (i) investigate the spatial and temporal root development of loblolly pine; (ii) evaluate the relationship between root length, number of roots exiting a trench face, and root mass densities; and (iii) determine if there is a relationship between fine root and foliage mass as well as root and shoot mass during the early stages of stand development. Thirteen forest sites in southeastern Georgia covering ages 1 to 4 yr old were used. Roots temporal and spatial distributions were investigated using a trench method. The value of N X (# roots cm −2 ) was measured in August/September during the first 4 yr of stand development. Root density depth distributions fit a natural logarithm relationship with soil depth. An empirical model for root development over time was developed. A two‐dimensional evaluation of root development showed that roots were present in 13 to &gt;60% of the soil volume from Year 1 to Year 4. Regressions between root length density, L V (cm root cm −3 soil), and N X were weak until root mass and soil depth were included. Lastly, it was shown that the ratio of fine root mass/foliage mass was stable after the establishment phase, as was the ratio of root to shoot.

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 score0.077
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations28
Published2004
Admission routes1
Has abstractyes

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