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Record W2126388575 · doi:10.1093/jxb/ers241

Effects of Combined Drought and Heavy Metal Stresses on Xylem Structure and Hydraulic Conductivity in Red Maple (Acer rubrum L.)

2012· article· en· W2126388575 on OpenAlexaff
Nayana D. G. de Silva, Ewa Cholewa, Peter Ryser

Bibliographic record

VenueJournal of Experimental Botany · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsNipissing UniversityLaurentian University
FundersNational Institutes of Health
KeywordsXylemMapleHydraulic conductivityBotanyAceraceaeMaterials scienceBiologyEnvironmental scienceSoil scienceSoil water

Abstract

fetched live from OpenAlex

The effects of heavy metal stress, drought stress, and their combination on xylem structure in red maple (Acer rubrum) seedlings were investigated in an outdoor pot experiment. As metal-contaminated substrate, a mixture of 1.5% slag with sand was used, with Ni, Cu, Co, and Cr as the main contaminants. Plants grown on contaminated substrate had increased leaf metal concentrations. The two stresses reduced plant growth in an additive manner. The effects of metal and drought stresses on xylem characteristics were similar to each other, with a reduced proportion of xylem tissue, reduced conduit density in stems, and reduced conduit size in the roots. This resulted, in both stems and roots, in reductions in hydraulic conductance, xylem-specific conductivity, and leaf-specific conductivity. The similarity of the responses to the two stresses suggests that the plants' response to metals was actually a drought response, probably due to the reduced water uptake capacity of the metal-exposed roots. The only plant responses specific to metal stress were decreasing trends of stomatal density and chlorophyll content. In conclusion, the exposure to metals aggravates water stress in an additive manner, making the plants more vulnerable to drought.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.378

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 integrity0.0000.000
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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

Citations156
Published2012
Admission routes1
Has abstractyes

Explore more

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