User: | Open Learning Faculty Member:
Systematic sampling (area):
Sampling time= 12 hrs 7 min
Hemlock= 637.5….Percentage error= (35.67%)
Red Maple= 116.7…Percentage error= (1.85%)
White Pine= 8.3…Percentage error= (1.19%)
Striped Maple= 12.5…Percentage error= (28.57%)
I was surprised when I found that the most abundant species was represented so inaccurately while the least abundant was very accurate. I believe this may have occurred because the quadrats followed a very specific gradient going south to north, therefore we miss out on the other species that may be more present to the east or to the west of our selected quadrats.
Random sampling (area):
Sampling time= 12 hrs 42 mins
Hemlock= 420.8….Percentage error= (10.45%)
Red Maple= 100…Percentage error= (15.91%)
White Pine= 16.7…Percentage error= (98.81%)
Striped Maple= 20.8…Percentage error= (18.96%)
Overall this was even more inaccurate than the systematic sampling, especially with the rarest species- White Pine. By chance, the program sampled double the proportions of White Pine than are actually in the forest which is surprising. The more abundant species were more accurately represented.
Haphazard sampling (area):
Sampling time= 12 hrs 46 mins
Hemlock= 420.8….Percentage error= (10.45%)
Red Maple= 104.2…Percentage error= (12.4%)
White Pine= 0…Percentage error= (100%)
Striped Maple= 12.5…Percentage error= (28.60%)
This was the most inaccurate of the sampling techniques with not a single White Pine being sampled. This does not surprise me as their actual representation is quite low and haphazardly choosing quadrats without attention to the different gradients could easily lead to this result. The species in abundance were more accurately represented which is what I would expect.
Conclusion:
The systematic sampling technique had the fastest sampling time and was the most accurate. As long as the entire sampling area had similar environmental factors such as sunlight exposure, space, soil type/quality, etc then I feel this would be the best technique to use. If the environment was more diverse, more sampling points would be necessary in order to correctly represent the gradients. Either way, an increase in sample points would have been beneficial as I think would always be the case, but then that is more time consuming.
