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Effects of sunlight and plant density on plant height in Aster prenanthoides, Cirsium vulgare and Solidago canadensis.Datasheet.

2014· article· en· W2247872255 on OpenAlexaboutno aff
Bastone Gabriella

Bibliographic record

VenueFigshare · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolidago canadensisAdvanced Spaceborne Thermal Emission and Reflection RadiometerSunlightDatasheetBotanyPlant densityHorticultureBiologyGeographyInvasive speciesEngineeringPhysicsRemote sensingSowingOptics

Abstract

fetched live from OpenAlex

To test the theory of competition and plant traits, both shadiness,plant density and the heights of three plant species were recorded in the grassland east of Stong Pond (43°46'15.5"N 79°30'26.2"W) located at York University (4700 Keele Street,Toronto, ON M3J 1P3, Canada) , on September 14th and 21st,2014 from 3:00 pm to 5:00 pm. Plant species observed in the grassland included the following : Canada Goldenrob (Solidago canadensis), white aster (Aster ericoides), zig-zag aster (Aster prenanthoides), spear thistle (Cirsium vulgare), Queen Anne's lace (Daucus carota), common dandelion (Taraxacum officinale), Graminoids ( grasses). The tools used in this dataset are : a belt transect and a measure transect tape. In total n=60 plots (denoted as “replicates”) are sampled : the firstn=30 replicates were sampled in the inner grassland (denoted as "I") and the second n=30 replicates were sampled in the outer grassland (denoted as "O"). On September 14th, the belt transect was set down on the ground along a gradient from shady to sunny. In order to do this, the belt transect departed from a random point in the middle of the grassland towards the closest tree or group of trees. From the start of the belt transect,a plot was sampled every 5 meters along the transect and the variables (listed below) were collected for each plot. The plot area to sample was defined by walking two steps in every direction from a point on the transect each 5 meters.In total, n= 10 plots were sampled along each belt transect and n=3 belt transects were performed with the same procedure in the inner grassland during the field sampling. On September 21st, the belt transect was set down on the ground departing from a random point located on the edge of the grassland towards another subsequent point on the border. The sampling procedure was repeated each 5 meters along the transect. In total, n=3 belt transects were performed in the outer grassland and n=10 plots were sampled along each belt transect. Shadiness is the shade coverage in the plot. It was visually observed looking from above to the ground. Every plot was then denoted either as "L"= lots of shade, "S"=some shade, "N"=no shade. Plant density (denoted as "crowdedness") was visually observed and estimated in each plot. It was recorded whether the target species in the plot were in a crowded patch (0 = open, 1 = some plants nearby, 2 = quite a few plants nearby, 3 = very crowded bunch of plants within 50 cm). Height is measured in meters for individuals of the target species in each plot : S.canadensis height (m) , C.vulgare height (m) , A.prenanthoides height (m) . Height was measured using a measure transect tape from the ground to the tallest point of the plant which we were sampling. The dataset is represented using a clustered bar graph with three groups (no shade,some,lots) of three bars (for each of the target species) and a scatter plot where height is dependant on crowdedness. The statistical tests run are an one-way ANOVA (Analysis of Variance) with alpha = 0.05 to test the significance between groups (species height vs. shadiness) and a correlation test to see if crowdedness has an effect/trade-off (species height vs. crowdedness).

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 score0.866
Threshold uncertainty score0.669

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)0.0010.000

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 head0.012
GPT teacher head0.170
Teacher spread0.159 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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