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Root ammonium transport efficiency as a determinant in forest colonization patterns: an hypothesis

2003· article· en· W2042817589 on OpenAlexaff
Herbert J. Kronzucker, M. Yaeesh Siddiqi, Anthony D. M. Glass, Dev T. Britto

Bibliographic record

VenuePhysiologia Plantarum · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsEcological successionSeral communityAmmoniumBiologyColonizationBotanyNitrateSalicaceaeEcologyChemistryWoody plant

Abstract

fetched live from OpenAlex

Ratios of ammonium (NH 4 + ) to nitrate (NO 3 – ) in soils are known to increase during forest succession. Using evidence from several previous studies, we hypothesize that a malfunction in NH 4 + transport at the membrane level might limit the persistence of early successional tree species in later seral stages. In those studies, 13 N radiotracing was used to determine unidirectional fluxes and pool sizes of NH 4 + and NO 3 – in seedlings of the late‐successional species white spruce ( Picea glauca ) and in the early successional species Douglas‐fir ( Pseudotsuga menziesii var. glauca ) and trembling aspen ( Populus tremuloides ). At high external NH 4 + , the two early successional species accumulated excessive NH 4 + in the root cytosol, and exhibited high‐velocity, low‐efficiency (15% to 22%), membrane fluxes of NH 4 + . In sharp contrast, white spruce had low cytosolic NH 4 + accumulation, and lower‐velocity but much higher‐efficiency (65%), NH 4 + fluxes. Because these divergent responses parallel known differences in tolerance and toxicity to NH 4 + amongst these species, we propose that they constitute a significant driving force in forest succession, complementing the discrimination against NO 3 – documented in white spruce (Kronzucker et al. 1997).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.342

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 head0.019
GPT teacher head0.207
Teacher spread0.189 · 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

Citations111
Published2003
Admission routes1
Has abstractyes

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