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Relationship between abundance of Woody Plants, Animal and Plant Species

2016· article· en· W2543421753 on OpenAlexaboutno aff
Raveendhran Geethanjanen, Sukhraj Singh, Carreira Pedro, Arnab Shuvo

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWoody plantAbundance (ecology)BiologyPlant speciesGeographyEcology

Abstract

fetched live from OpenAlex

<b>Meta Data:</b> 1) Abundance Native Plants: This is a discrete variable. A 50 m transect was placed along the length of the forest/woodlot. The quadrat was moved every 2 m along transect. Using a quadrat, the abundance of native plants was determined by visually distinguishing between exotic and native and then counted the amount of native plants within the quadrant. In ambiguous situation the teaching assistant was consulted for further clarification. This was repeated 25 times and took on average 15 minutes to collect and record. 2) Abundance Exotic Plants: This is a discrete variable. A 50m transect was placed along the length of the woodlot/forest. Every 2m along the transect, a quadrat was placed alternating left and right, to visually determine the number of exotic plants present within the quadrant. To estimate the abundance of exotic grass within a quadrant, an area of 0.0625 m<sup>2</sup> sample of the quadrant was counted and then multiplied by 4. This was repeated 25 times and the data was collected simultaneously with dataset 1 by individual peers. 3) Total Number of Flowers: This discrete variable. A 50 m transect was placed along the length of the woodlot/forest. Every two meters along the transect, a quadrat was placed alternating left and right to determine the total number of flowers within the quadrant. The number of total flowers was counted within the quadrat. This was repeated 25 times and the data took 15 minutes to collect 4) Abundance woody plants: This is a discrete variable. A 50 m transect was placed along the length of woodlot/forest. Then counted the number trees 0.5 m perpendicular to the transect on either side every 2m. The tree had to be 1.5 m in height or greater to be considered as a woody plants. 25 replicates were recorded and took 15 minutes to collect. 5) Canopy cover: This is a continuous variable. For each respective replicate, the percentage of sky cover not visible due to impeding canopy cover, directly above the observer was estimated. 25 replicates were recorded and took 40 minutes to complete simultaneously with dataset 2 variables. 25 recorded and took 15 minutes to collect. 6) Ground cover: This is a continuous variable. The vegetative ground cover was estimated as a percentage by the observer directly looking underneath themselves. 25 replicates were recorded and took 30 minutes to collect simultaneously along with the other variables of dataset 2. 7) Total flower numbers: This is a discrete variable. The number of flowers around the 50 m transect was measured every 2 m around the woody plant area. 25 replicates were recorded and took 15 minutes to collect simultaneously along with the other variables of dataset 2. 8) Abundance invertebrates pan traps: This is a discrete variable measured with the usage of 6 pan traps (coloured plastic bowl with approx. 20mL of soap water). The 6 replicate pan traps were placed 3 meters apart, along the transect, while alternating colours (blue, yellow, white) in the woodlot/forest. After placement of the pan traps, a period of 25 minutes was elapsed, at which point the abundance of invertebrates captured by the pan trap was counted and recorded. 9) Abundance vertebrates: This is a discrete variable, which was measured with the use of a point/observation survey while standing at the beginning of the 50m transect. Any/all vertebrates that were visually identified within a 50m radius from the original position were counted and recorded for a 15 min period. 10) Abundance Humans: This is a discrete variable, which was measured with the use of a point/observation survey while standing at the beginning of the 50m transect. Any/all humans that were visually identified (whether on-foot, in motor-vehicle or other modes of transportation) within a 50m radius from the original position were counted and recorded for a period of 15 min. 11) Abundance Invertebrates observed: This is a discrete variable, which was measured with the use of a point/observation survey while standing at the beginning of the 50m transect. Any/all invertebrates that were visually identified within a 50m radius from the original position were counted and recorded for a 15 min period. 12) Abundance invertebrates pan traps: This is a discrete variable measured with the usage of 6 pan traps (coloured plastic bowl with approx. 20mL of soap water). The 6 replicate pan traps were placed 3 meters apart, along the transect, while alternating colours (blue, yellow, white) in the forest/woodlot. After placement of the pan traps, a period of 25 minutes was elapsed, at which point the abundance of invertebrates captured by the pan trap was counted and recorded. The variables of dataset 4 were done in 25 minutes. 13) Abundance invertebrates sweeps: This is a discrete variable. Used the sweep net along the 50 m transect and swept 1 m perpendicular to the transect. After thoroughly sweeping in the forest/woodlot and counted the amount of invertebrates caught in the sweep net. <b>Hypothesis:</b> It is hypothesized that the forest/woodlot will demonstrate a vast abundance of woody plants that it will correlate with an increase in canopy coverage which in cases of disturbance will depict a decreasing abundance of animal and plant species because competition of light sources will increase. <b>Predictions:</b> 1. Increase in woody plants will correlate to an increase in canopy coverage percentile. 2. Increase in woody plants will correlate to a decrease in abundance of native plants and exotic plants. 3. Increase in woody plants will correlate to a decrease in abundance of invertebrate and vertebrate species . <b>Methods:</b> The experiment was conducted at the Danby Woodlot/forest at York university Keele campus at 2:45 p.m. E.T and lasted approximately 1 hour and 30 minutes. The GPS coordinates of the Danby Woodlot are: longitude -79.5079 and latitude 43.768756. The 50m transect was established by using two 30 tape measure and aligning it in a linear fashion. The tape was set as low as possible without disturbing the area. For Dataset 1, quadrats (1m *1m) were placed alternately left and right along the transect every 2 m. The quadrats were placed 0.5m away from the transect. The number of flowers were then within the quadrant. Then the abundance of exotic plants (i.e. grass, weed, etc.) and native plants (i.e. white and purple flowered plants) within the quadrant were counted. For calculating the abundance of grass, the number of grass in a quarter (0.5m*0.5m) was counted and then multiplied by four. This process was repeated 24 times along the 50m transect every 2m in the forest/woodlot. For dataset 2, using the same 50 m transect, the abundance of wood plants (trees) 0.5m perpendicular to the transect were surveyed. Also, the canopy coverage and vegetative ground coverage was estimated and the total number of flowers were counted around the area. This process was done every 2 m along the transect 25 times in the woodlot/forest. For data set 3, we stood at the beginning of the transect and surveyed along a 50 m radius for 15 minutes (trial 1) and observed the abundance of humans that crossed by, without including lab group members. Also, the abundance of vertebrates (crows, owl, etc.), number of vertebrate species were o and the abundance of invertebrates (snails, spiders, ants, etc.) were observed in this trail. Then in another 15 minute interval survey, the abundance invertebrates were measured for trial 2 in the forest/woodlot. For dataset 4, the pan test was conducted for 15 minutes and six pans were placed with soap water. The pans were placed 3m away from each other along the transect in the color scheme of blue, yellow, white, blue, yellow, white. Then counted the abundance of invertebrates (i.e. ants, flies, spiders, etc.) caught in pan traps for a total 6 trials. Then conducted the sweep test for 20 minutes along the 50 m transect. Then, the abundance of invertebrate was counted caught in the sweep test. A total of 10 trials were done. The data was collected across two notebooks among three group members/peer and later accumulated to be digitally recorded on a excel document and saved as a .csv file. <b>Study Site Description: </b> A field study was conducted at the Danby Woodlot/forest located on York University’s Keele campus near Keele Street and York Boulevard in Toronto, Ontario on October 24, 2016, around 2:45 pm. The temperature was around 10 degrees Celsius, gloomy skies with overcast and little to no sunshine. Danby Woodlot/forest perimeter surrounded by grassland, and contains vast abundance of somewhat barren trees. The woodlot also contains man made/artificial objects including empty glass bottles, bench, garbage, etc. The woodlot ground was covered with red, yellow, brown and orange leaves, below which soil could be found. As soon as we entered the woodlot, an owl and two crows were spotted. <br>

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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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.989

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)0.0120.000

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 head0.100
GPT teacher head0.225
Teacher spread0.125 · 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.

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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Published2016
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