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The abundance of animal and plant species in forest area: York University

2016· article· en· W2546009748 on OpenAlexaboutno aff
popalzay saarah, Rahmani Fatana, Rujbally Abi, Tabassum Bushrat

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbundance (ecology)Distance samplingGeographyForestryEcologyBiology

Abstract

fetched live from OpenAlex

Meta DataThe experiments were carried out on October 25th, 2016 starting at 3:00 PM to 4:00 PM. The weather was 7 degrees Celsius with windy and cloudy skies. The experiment was conducted at the forest at York University at Saywell Woods with latitude 43.769, longitude -79.5079 with elevation 126.3 These coordinates were provided by the Lab Instructors. Data column headers:Census: Refers to sampling week Calendar date: continuous variable representing the date data was collected Campus: Categorical variable that relates to the University campus the data was recorded at. Group ID: Categorical variable refers to unique group in BIOL 2050 LabsHabitat: Refers to the two places where data was recorded, grassland or disturbed open space.Rep: The number of times the experiment was repeated. Meters: The unit that was used to measure distance on the transect and to distinguish the woody plant as a tree. Experiment 1: Herbaceous Plants - Abi Rujbally Methods:A transect of 50m was used to measure several variable throughout the experiment.For experiment 1, for every two metres along the transect, a 1m by 1m quadrat was randomly placed alternating from left to right. The abundance of native, exotic plants and the total number of flower heads within the quadrat were recorded. Grass was categorized as an exotic species, and surveyed over the quadrat, which was then multiplied by four to get a total estimate of colonies in the entire quadrat. This variable is quantitative and discrete. Twenty-five trials were performed at the forest area. Variables: abundance.native.plants: The abundance of native plants refer to plants that have developed or naturally occurred in Canada for many years. They were recorded by placing a quadrat every 2m on a 50m tape. Grass was categorized as an native species, and surveyed over the quadrat. The variable is discrete and continuous. Abundance.exotic.plants: The abundance of exotic plants refer to plants that are introduced from another country or originally from another location. The variable is discrete and continuous. Total.number.flowers: Refers to the total number of flower heads and average grass in the quadrat. The variable is discrete and continuous.Experiment 2: Woody Plants - Fatana Rahmani Methods:Data collected was continuous data. Meters were used to determine distance. Two 25 meter transects were used for this data set. The first transect was placed 25 meters from the edge of the curb where the grass started and the second transect was placed right joining the two to make it a continuous transect of 50 meters in total. Every 2 meters was walked along the transect and the total number of trees also known as abundance that was about 0.5 meters on either side of the transect was recorded. What was defined as a tree was any tree that had a height greater or equal to 1.5 meters. The canopy coverage of that tree was then estimated by both hands making a square using fingers and estimating the coverage of vegetation on that tree. The ground coverage was done the same way but instead of the vegetation on the actual tree, the vegetation of the ground around the tree was observed and recorded. Once that was done, the total number of flower heads within that 1m was observed and calculated using the naked eye. The transect was carried out and repeated (walked, did not move the transect) 25 times to make sure this data was accurate for the Forest habitat.Variables:Data Type: The data is categorical because each tree is considered as a full individual. Abundance woody plants: Recorded by counting all the trees that was observed when the 50 metres transect data was walked once. The tree was identified if it was 1.5 metres or greater in height.Canopy cover: Was the amount of vegetation on each tree, averaged up and measured in percentage. This describes the amount of leaves and vegetation that was visible on the tree when a square was made using fingers.Ground cover: Was done the same way as the canopy coverage, but on the ground and the amount of vegetation (including grass) was observed and recorded as a percentage. This was then all totalled up for the total number of trees and the mean was recorded for abundance. Total flower numbers: The average of all the flower heads found around 1 meter of the transect, around the tree, and was averaged for all the trees and recorded. Experiment 3: Vertebrates & Invertebrates - Bushrat TabassumMethods:The purpose of this dataset was to measure the abundance of living species (vertebrae, invertebrate and humans) in the Saywell Woods at York University. This experiment was performed by using the point survey method. The data was collected over two 15-minute intervals. A transect was used to create a 50-meter radius from any location. One individual was then responsible to observe and record any vertebrae within the radius. The total number of individual vertebrae was calculated and labeled as the abundance of vertebrae. At the same time, the total number of humans (not a part of the lab group) was counted and recorded as the abundance of humans. On the second 15-minute interval, the total number of invertebrate was observed and labelled as the abundance of invertebrate observes. Variables:Data type: Categorical Data because the values fall within the data fall into limited groups.Individual: a single body of each species.Vertebrates species: species that have a backboneInvertebrates: species that do not have a backboneSpecies: living organisms that live in the same area and are able to interact and interbreed with each other.Abundance of humans: total number of humans which are not a part of our lab group, in a given area.Experiment 4: Invertebrates - Saarah Popalzay Meta-Data:The abundance of invertebrates in the Saywell Woods at York university was measured. The abundance refers to the number of insects collected along the 50 meter transect. The two methods used to measure the abundance of the invertebrates observed, was the pan trap method and the sweeping method. In the pan trap method 6 pan traps (one for each trial) was laid out 3 meters apart in alternating colors of yellow, white and blue along a 50 meter transect. Roughly 20 ml of soap water was added to the pan traps. The traps were laid out for a period of roughly 45 min from 3:00 pm to 3:45 pm. The number of species collected in each pan trap was observed and recorded. In the sweeping method a butterfly net was used in a sweeping motion to collect insects along the 50 meter transect. At reaching the end of the transect, the number of insects collected was observed and recorded. The sweeping method was repeated for a total of 10 times and at the end of each trial the number abundance of insects observed was recorded. The data collected for both methods are continuous as they are numerical and measurable sets of data in which each outcome may change for each trial. The study was conducted twice, at a forest habitat located at York university. Null HypothesisThe is no correlation between the proximity from the disturbed area and the abundance of vegetation.Alternative Hypothesis: There is an indirect correlation between the proximity from the disturbed area and the abundance of vegetation.Prediction: There is an indirect correlation between the abundance of vegetation and the distance from disturbed area, where the abundance of vegetation increases as the proximity between the forest and disturbed area increases.Equipment used:2 Transects 6 plastic bowls; two blue, two white and two yellow 1 sweep net 1 quadrat (1m by 1m)

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.080
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0530.009

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 head0.045
GPT teacher head0.171
Teacher spread0.126 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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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