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Record W2173832201 · doi:10.2980/i1195-6860-13-3-318.1

Effects of light and water availability on shoot dynamics of the stoloniferous plant Linnaea borealis

2006· article· en· W2173832201 on OpenAlexvenueno aff
Mikael Niva, Brita M. Svensson, P. Staffan Karlsson

Bibliographic record

VenueEcoscience · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsStolonShootBiologyBotanyEcologyEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

:Many stoloniferous plant species have the ability to exploit resource-rich patches via plastic growth responses. The most efficient responses are shortened spacers and increased branching frequency. Here we experimentally investigate the ability of the stoloniferous plant Linnaea borealis to respond to patches of increased light intensity and reduced water availability in natural systems. The significance of contrasts between patches was also investigated. A three-level factorial design was used, with light, water availability, and site as the factors. Increased light intensity was achieved through mowing of the surrounding vegetation, and reduced water availability was achieved by placing wooden ledges under the stolons. The treatments were applied at three subarctic sites that differ in light conditions. Branching frequency, number of new meristems, average internode length, leaf area, and dry weight production were studied 14 months after the manipulations. Increased light intensity increased branching frequencies; the strongest effects were obtained at the site with a closed canopy. Average internode length decreased 19% in response to increased light intensity. Root:shoot ratios decreased under increased light intensity and reduced water availability. A reduction in water availability alone did not affect any other investigated traits. We conclude that ramets of L. borealis are able to respond efficiently to small-scale variations in light intensity in natural systems, an ability of great importance for the performance of a prostrate species on shady forest floors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.510

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 head0.009
GPT teacher head0.166
Teacher spread0.157 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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