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I did not make any changes to my stratified random sampling method from Module 3, however, I decided to increase the number of replicates from five to 10 for each stratum, as I observed variation within each stratum that could be reduced with a greater number of samples. I continued to use a distance-based sampling method with the random number generator to create two numbers, an angle and a distance in cm to determine the location of the sample unit to measure. I did not encounter any other problems since revising the data collection technique mentioned in Blog Post 5. A potential ancillary pattern I noticed was that the stratum with a high level of exposure to sunlight, which appeared to consist of the tallest plants, was also the furthest away from the creek, with the highest elevation. The moderate exposure strata was second closest, and the low exposure strata was adjacent to the creek. This prompted me to consider the effect of soil moisture and elevation as potential confounding factors affecting plant growth.
Edit:
I collected my data again following my revised hypothesis and study design outlined in Blog Post 5. I implemented the stratified random sampling method using quadrats to measure density of the Canada goldenrod. While this method was more difficult that simply measuring the height of individual plants, I believe it will provide more conclusive results of the effect of sunlight exposure on plant success. This sampling method was more time consuming, but included a larger sample size. I sampled 30 replicates in total, 10 from each strata. Potential ancillary patterns are similar to those observed with height measurements, since density and height appear to be correlated.
