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Record W2107606553 · doi:10.5539/enrr.v4n2p80

The Competitive Response of Panicum virgatum Cultivars to Non-Native Invasive Species

2014· article· en· W2107606553 on OpenAlexvenueno aff
Lauren M. Schwartz, David J. Gibson

Bibliographic record

VenueEnvironment and Natural Resources Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
Fundersnot available
KeywordsPanicum virgatumCultivarAgronomyBiologyBromusBiomass (ecology)ShootPoaceaeBioenergyBiofuelEcology

Abstract

fetched live from OpenAlex

It is important to use the most appropriate plant cultivar in restoration or biofuel trials especially when plantings are likely to be invaded by undesirable species. In this study, the competitive response of two lowland and three upland cultivars of the dominant C4 grass Panicum virgatum to three invasive species (Bromus inermis, Schedonorus phoenix, and Poa pratensis) was tested using a simple pair-wise greenhouse experiment. Response variables (height, number of leaves, tiller density, and biomass of P. virgatum) and resources (soil moisture and light intensity) were measured over a seven-month period. Performance of the different P. virgatum cultivars were differentially reduced by the three invasive species, especially the performance of the Kanlow (lowland) and Blackwell (upland) cultivars. Low soil moisture reduced the performance of P. virgatum in the presence of only one invasive (Bromus inermis) irrespective of cultivar source. Root, shoot, and total biomass depended on cultivar and did not show an interaction with invasive species identity. The results of this greenhouse study suggest that the P. virgatum cultivars differentially responded to the invasive species and that the cultivar used should be considered carefully in planning prairie restorations or biofuel trials in the context of likely invasive species.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.458

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 studies0.0010.001
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 head0.023
GPT teacher head0.252
Teacher spread0.230 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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