User: | Open Learning Faculty Member:
The 3 sampling strategies learnt in the virtual forests tutorial are systematic, random, and haphazard sampling. Throughout the virtual forest tutorial I learned which were the most efficient, fastest, and most accurate. I sampled the Snyder-Middleswarth Natural Area using area sampling technique rather than the distance sampling technique.
Systematic Sampling –
A combination of both random and haphazard sampling. It is easier than random but has less of a bias than haphazard. Quadrats were chosen in a specific pattern across the location, usually a gradient. On the virtual forest tutorial, systematic was slower than haphazard, but faster than random sampling. However it did have a high percent error as follows:
Eastern Hemlock – 14.0%
Red Maple – 5.4%
Striped Maple – 138.3%
White Pine – 147.6%
Random Sampling –
Done by labelling quadrats and choosing the numbered quadrats at random, every quadrat has an equal chance at getting chosen. This takes the longest time to do to ensure everything is chosen at random. Random sampling did have the lowest percent error, making it the most accurate way of sampling.
Eastern Hemlock – 6.4%
Red Maple – 5.4%
Striped Maple – 66.8%
White Pine – 100.0%
Haphazard Sampling –
Done by choosing areas that have samples which are readily available, and taking samples from the different variations in your testing area. Haphazard samples are never random but always available, and therefore also have a high percent error.
Eastern Hemlock – 23.3%
Red Maple – 43.65%
Striped Maple – 4.6%
White Pine – 1.2%
Sampling speed:
Haphazard > Systematic > Random
Accuracy in 2 most common species:
Random > Systematic > Haphazard
Accuracy in 2 most rare species:
Haphazard > Random > Systematic
The accuracy did change with abundance of the species. Random sampling was the most accurate for common species, and haphazard was the most accurate for rare species. Overall, if time allows, random sampling would be the most accurate.
