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Ecology 2050- Field data- Late Purple Aster- Dataset 2- Transect

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Mendeley Data2024-06-27 更新2024-06-28 收录
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https://figshare.com/articles/dataset/Ecology_2050_Field_data_Late_Purple_Aster_Dataset_2_Transect/1561335/2
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This lab was conducted on September 24th 2015 from 2.30 PM to 5.30 PM, at York University and the dataset was collected from Grasslands located next to Danby woodlot. The weather was cloudy and partially sunny with a temperature of 21 degrees Celsius. There was hardly any wind to interfere with field training. The purpose of this lab was to teach how to collect field data for a very first time and familiarize us with sampling tools, such as traits, transects and quadrats. These tools make it easier to understand the relation between several variables and their effects on each other. All group members contributed to collecting data for all of four datasets, but each member only submits one. Late Purple Aster (Aster prenathoides) was selected as the target species for Grassland data set 2 because it was easily recognizable in the field. Each group was provided with two transect tapes, one of which was used for measuring distances and the other one was used for measuring the length of each target plant. To begin with, the transect tape was tied to a tree branch, which was chosen randomly. Since the measuring tape started at 3in because of the tied knot, we subtracted it from every measured distance to record the actual value. From the starting point, we chose a random direction and walked in a straight line. Every time the line touched the target plant we observed, read, and recorded the distance shown on the transect tape. Then with our second transect tape, we measured the length of the plant. If the plant was bent we held it up (without pulling it) and measured its length from its highest point to the ground level. For every Late Purple Aster, three other data were recorded: the number of leaves, the number of flowers, and the level of crowding (0-3). We first started to count each flower and leaf, but as we got used to it we could estimate their number by observing the plant. Crowding level refers to the number of plants which surround the target plant. There are three levels to it: 0= no plants, 1= one plant, 2= two to three plants, 3= more than three plants. We limited the last observation only within a 30 centimeters radius of the target plant (an estimation made by vision). These assumptions are specific to this dataset only. Finally, we repeated this process until we gathered those data for 20 individuals.
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2023-06-28
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