Effects of Sunlight Coverage and Soil Moisture Levels on Abundance of Plant Species
Bibliographic record
Abstract
The purpose of the experiment was to determine the amount of plant species within each quadrat that was placed within grassland and relate them to the amount of sunlight and soil quality via moisture level. The data was collected on Monday October 19th 2015 from 3:00pm to 5:00pm at York Universities Danby Woodlot grassland (behind the forested part) located at 4700 Keele St in Toronto Ontario. It was 14 degrees outside and Sunny, the sun varied in position due to timing of experiment because it started to set off into the west. 2 quadrats were used to conduct the experiment; a quadrat is a tool used to calculate local abundance of individuals in a given area and works very well for stationary individuals such as plants. The quadrat was a 1 metre by 1 metre measurement of area. 120 quadrat replicates were used. The individuals that conducted the experiment were Sumera, Mustafa, Krystal and Savannah (me). Mustafa and I took one quadrat and conducted 60 replicates, 30 in open grassland near no trees and 30 on the edge of the grassland where trees were present. Sumera and Krystal took the other quadrat and did the same procedure. 6 steps were taken between each quadrat as per what the random number generator produced. A table was set up in a notebook with columns labelled # of Quadrat Replicates, Number of Plant Species, Soil Moisture Level, and Sunlight Coverage. This table was then transferred and duplicated into excel after the experiment was complete. All the variables used in table were Numerical, discrete. Number of plant species was interpreted through observation, a new species is determined if it looks nothing like the last species found within the quadrat, as in it had different colour or/and leaf shape or size. Only the number of recognizable taxonomic units was noted, not the actual names of each species of plant or number of how many individuals of that species were present. A scale was used to determine sunlight levels for the plants within each quadrat, 0 = 0%, 1 = 25%, 2 = 50%, 3 = 75%, and 4 = 100% coverage within the quadrat. This variable depended on the time of day, weather, and where the quadrat was situated in the grassland (by trees vs. in open). Estimations were given in this case to the quadrats that would normally get full sunlight, such as those found in the middle with no trees around them but because of the time of day (4pm sun is starting to set) was not getting as much as usual. Soil moisture levels were also determined by a scale, 0 equals completely dry, 1 is semi-dry, 2 is semi-wet and 3 is moist. The soil moisture level depended on rain and sunlight coverage. It had rained 24 hours before the data was collected and it was a sunny and fairly warm day. To determine what number on the scale each quadrat sample should be given, a sample of the soil was tested with our hands from the both the edges of the quadrat and the middle for consistency. This same procedure and definition of variables was used for all 120 quadrat replicates and data was noted in the table.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".