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Record W2028532775 · doi:10.5539/jps.v2n2p28

Effects of Litter and Seed Position on Seedling Establishment of Gentiana dahirica Fischer

2013· article· en· W2028532775 on OpenAlexvenueno aff
Guixia Liu, Hejing Zhao, Euan K. James, Xiaoyun Liu

Bibliographic record

VenueJournal of Plant Studies · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
FundersNatural Science Foundation of Hebei ProvinceNational Natural Science Foundation of China
KeywordsSeedlingLitterThreatened speciesBiologyAgronomyPopulationHorticultureFencingEcologyHabitatMedicine

Abstract

fetched live from OpenAlex

In recent three decades the medicinal plant Gentiana dahurica Fischer has been threatened by large scale exploitation for trade and land-use practices, such as over-grazing and reclamation. However, research into the population ecology and sustainable use of this highly-threatened medicinal plant is lacking, and so we analyzed the effects of different litter applications and seed positioning (surface-sown or buried) as part of a program to rehabilitate it. The results indicated that although litter and seed position per se had no significant effects on the seedling emergence of G. dahurica, interestingly, litter application did show positive effects on seedling survival, e.g. 100 g m-2 and 200 g m-2 litter increased it by 9.7% and 16.4%, respectively, compared to control. Moreover, the seedling leaf area increased with the quantity of applied litter when seeds were surface-sown, with the highest leaf area occurring in the 200 g m-2 treatment (9.7-fold of the control), and litter-covered treatments also significantly improved seedling root length and root diameter of G. dahurica compared to controls. Taken together, these data indicated that seedling establishment of G. dahurica benefited from accumulated litter, and it is thus suggested that fencing to exclude grazing for a period is the best method to protect and rehabilitate the threatened wild G. dahurica populations.

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 score0.312
Threshold uncertainty score0.177

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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