five

Ecology Lab Four

收藏
DataCite Commons2020-09-04 更新2024-07-25 收录
下载链接:
https://figshare.com/articles/dataset/Ecology_Lab_Four/1591865/1
下载链接
链接失效反馈
官方服务:
资源简介:
Authors: Kamil Adamczewski, Joelle Brooker, Brittney Jorisch, and Karin Yosefi On October 15, 2015 between 3:00 and 4:30 p.m. and October 22, 2015 between 3:09 and 3:55 p.m., fifty random, separate adult maple trees were studied. Trees were determined as adult if their height was greater than our tallest group member, i.e. over 5 feet and 10 inches tall. First, the diameter of the target tree was determined by using a transect to measure the diameter at breast hight, and this was recorded in cm. Abundance was the second variable measured. Two transects, each measuring 3 m long, were laid out to form a quadrat. One was laid out vertically and one horizontally, to form an L shape. They were placed strategically so that the target tree was in the middle of the transects. The quantity of vegetation was then determined by manually counting the plants that were contained in the quadrat. Plants were only included in the count if their roots were still in the earth. The percent canopy cover was then determined by making a square with the thumbs and index fingers of both hands, holding the square up to the top of the target tree, and looking through it and estimating the percentage of area that the parts of the tree took up (i.e. the leaves and branches). The purpose of this observation was to determine if there is a relationship between growth of a tree (measured in terms of diameter of the trunk), the density surrounding the tree (measured in terms of abundance of vegetation), and how much sunlight the tree had access to (measured in terms of % canopy cover). On October 15, it was -11 degrees Celcius, and was cloudy, rainy and very windy. On October 22, it was 13 degrees Celcius, sunny and slightly windy, with a few clouds. Trees were studied in the Danby Woodlots, on the north-east side of York University, Keele Campus.
提供机构:
figshare
创建时间:
2016-01-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作