User: | Open Learning Faculty Member:
The table I created clearly displays the data collected at each site for my research. The number of alive and dead spruce trees are presented, as well as fallen spruce trees and other vegetation that was present. The most important column in the table is the percent dead trees that I calculated for each site because this is what either confirms or denies my hypothesis. I had no difficulties organizing the data since it was very simple data that was collected. The outcome was not what I expected since I expected Site 4 to have the highest percent of dead trees but instead Site 2, which has sparse tree density, actually had the highest percentage of dead trees present. I believe I got the results I did because site 2 had fewer trees than site 3 and 4, so the ratio between dead and alive trees to the total amount were close together, whereas when you have more trees your percentage is going to be lower. In order to further confirm my hypothesis, I think I need to study more sites in the area to gather more data.
Table 1. Recorded field data from Spruce Beetle Research in Kluane, Yukon. The count of dead and alive trees are stated as well as the percent of dead trees calculated for each research site.
| Site – Tree Density | Alive Spruce Tree | Dead Standing Spruce Tree | Fallen Spruce Tree | Other vegetation | Percent Dead Trees |
| 1 – Low Density | 17 | 1 | 5 | 13 | 35.2 |
| 2 – Sparse | 16 | 6 | 10 | 5 | 50.00 |
| 3 – Cluster | 32 | 3 | 4 | 8 | 21.8 |
| 4 – High Density | 91 | 10 | 26 | 2 | 39.5 |
clear presentation with labels
be sure to use the text in the Table part to explain all variables – so for example, what constitutes low vs sparse density, or a cluster? etc
How does other vegetation fit into analysis?
note round up eg 35.29 = 35.3; check others
percent for sparse? 16 / 16 = 100% – I see what was attempted here but it doesn’t match other examples – check this ; )