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Record W2143067585 · doi:10.1093/forestry/cpm035

The effect of roots and litter of Calamagrostis canadensis on root sucker regeneration of Populus tremuloides

2007· article· en· W2143067585 on OpenAlexaff
Simon M. Landhäusser, Tara Mulak, Victor J. Lieffers

Bibliographic record

VenueForestry An International Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologySuckerTaigaLitterAgronomyBotanyEcology

Abstract

fetched live from OpenAlex

Marsh reed grass (Calamagrostis canadensis (Michx.) Beauv.) is a common, highly competitive grass native to the boreal mixedwood forest. This grass increases in abundance after clear-cut logging but little is known about its effects on trembling aspen (Populus tremuloides Michx.) sucker regeneration. The effects of Calamagrostis sod and its litter on aspen regeneration were studied in two separate greenhouse studies. Calamagrostis sod did not affect the initiation of suckers, but resulted in 30 per cent fewer suckers emerging above the soil that were smaller and had 40 per cent less leaf area. Calamagrostis litter had little effect on the initiation and number of emerged suckers; however, it delayed emergence by 10 days. The physical barrier by roots and litter of Calamagrostis reduced or delayed the expansion of suckers and therefore prolonged their dependence on root reserves. By the time the suckers reached the surface, they had to compete for light with Calamagrostis shoots that had emerged a week earlier. This, coupled with low soil temperatures associated with Calamagrostis in other experiments, will significantly reduce the number and growth of suckers. Any reduction and delay in sucker emergence will decrease aspen regeneration and productivity since the growing season in the boreal forest region is short.

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)0.002
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 score0.022
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.016
GPT teacher head0.326
Teacher spread0.310 · 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

Citations22
Published2007
Admission routes1
Has abstractyes

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