In the virtual forest tutorial, I examined 3 sampling techniques: area haphazard, area random and area systematic. All sampling techniques collected data from Mohn Mill Natural Area, which was sectioned into 750 quadrats (25x 30 quadrats).
For area haphazard, I selected 50 areas for data collection. Using this method, 13 of the 16 tree species were sampled and would take an estimated time of 19 hours and 24 minutes to collect, which was the fastest of the 3 sampling strategies.
For area random, 50 X and Y coordinates were randomly generated which correlated to 50 quadrats. Using this method, 12 of the 16 tree species were sampled and would take an estimated time of 29 hours and 55 minutes.
For area systematic, I sampled every 15th quadrat to get a total of 50 samples. Using this method, 10 of the 16 tree species were sampled and would take an estimated time of 25 hours and 30 minutes.
The 2 most common tree species were Red Maple and White Oak; whereas Yellow Birch and White Ash were the 2 rarest. Using area haphazard sampling, Red Maple and White Oak had an error percentage of 1.8% and 8.9% respectively. Area random sampling had an error percentage of 1.8% and 5.9%, and area systematic had an error percentage of 0.6% and 10.0% respectively. In contrast, the 2 rare tree species, Yellow Birch and White Ash, had an error percentage of 100% across the 3 different sampling methods. Therefore, trees with a higher density or abundance have a lower percentage error, indicating superior accuracy. Area random appears to be the more accurate sampling strategy. This method had a lower percentage error total when Red Maple and White Oak were added together (7.7%). In contrast, area haphazard and area systematic totalled 10.7% and 10.6% respectively.