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Record W3044528958 · doi:10.1139/cgj-2019-0647

Effects of plant morphology on root–soil hydraulic interactions of <i>Schefflera heptaphylla</i>

2020· article· en· W3044528958 on OpenAlexvenueno aff
Charles W.W. Ng, Zhaojiang Wang, Junjun Ni

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersHong Kong Government
KeywordsSuctionSoil waterEnvironmental scienceLimitingSink (geography)Root systemSoil scienceAgronomyHorticultureBiologyGeography

Abstract

fetched live from OpenAlex

Root water uptake induces additional soil suction by soil water extraction. However, induced soil suction restricts root water uptake when beyond a threshold (s t ) and tends to stop water uptake at a limiting suction (s l ). This process is called root–soil hydraulic interactions, whose relationship with plant morphology (e.g., plant height, leaf area, and root length) is unclear. This study aims to investigate the effects of plant morphology on response of the sink term (water uptake intensity; WUI) to soil suction for Schefflera heptaphylla. Laboratory tests were conducted on 26 individuals in five different height groups. A new empirical model was derived to consider effects of plant morphology on root water uptake distribution in the full soil suction range. The locations of maximum root length density (RLD) and WUI for taller individuals were relatively deeper and farther from centreline. Before soil suction reached s t , water uptake length ability (WULA) remained at a maximum level, positively related to LR ratio (ratio between leaf area, LA, and root length, RL), but less affected by plant height. For taller plants, the decreasing rate of s t with LR ratio was larger, while the decreasing rate of WULA with soil suction beyond s t appeared smaller. s l appeared independent of height, LA, and RL.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.540

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.188
Teacher spread0.181 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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