I used the three sampling techniques listed below in the Mohn Mill community virtual forest.
| Systematic | Random | Haphazard | |
| Most Common | Red Maple (n=44)
% of error: 8.99 |
Red Maple (n=44)
% of error: 8.99 |
Red Maple (n=46)
% of error: 13.94 |
| Witch Hazel (n=17)
% of error: 19.38 |
Eastern Hemlock (n=19)
% of error: >100.00 |
Eastern Hemlock (n=25)
% of error: >100.00 |
|
| Most Rare | Downy juneberry (n=1)
% of error: 1.01 |
Striped maple (n=1)
% of error: 26.47 |
Black Cherry (n=1)
% of error: >100.00 |
| American basswood (n=1)
% of error: >100.00 |
Hawthorn (n=1)
% of error: >100.00 |
Red/black oaks (n=5)
% of error: 7.07 |
|
| Estimated Sampling Time | 5hrs, 5 mins | 5hrs, 21 mins | 5hrs, 17 mins |
Figure 1: Number of Individuals (n) and Sampling error (%) per species using systematic, random and haphazard sampling methods in the virtual forest.
The systematic technique had the fastest sampling time, however all sampling times were relatively similar. The percentage of error was lowest using the systematic technique compared to the random and haphazard techniques. There was relatively low error for the most common species but increased error with the more rare species, therefore the abundance did affect the accuracy for this technique. The random and haphazard sampling techniques however had higher rates of sampling error both within the most common and most rare species. With each having one species at >100% sampling error, it doesn’t seem like abundance had any effect on accuracy. Overall, the systematic sampling technique seems to be the most favourable technique to use with higher rates of accuracy and lower sampling time compared to the two other techniques.
I think you tagged the wrong instructor?