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Blog Post 4:

For this sampling exercise, I studied the 154-ha Mohn Mill area located within Pennsylvania at elevations that range between approximately 420 to 570 m ASL. Steeply dipping slopes make up the topography of the area and sandy loams cover the slopes. During the sampling exercise, I used three techniques that included systematic, random, and haphazard sampling. The results from the three sampling methods are as follows and show percent error data from the two most common and most rare trees.

Using random sampling methods Red Maple (RM) and Witch Hazel (WH) came up as the most dominant species. After 20 quadrats were sampled percent error for each showed errors of 1.98% and 26%, and a total time of 10 hours and 33 minutes was taken to sample. The two most rare species were black cherry (BC) and American basswood each having errors of 566% and 566% respectively.

Using haphazard sampling methods RM and WH came up as the most dominant species. After 20 quadrats were sampled percent error for each showed an error of 14.14% and 49%, and a total time of 10 hours and 34 minutes was taken to sample. The two most rare species were downy juneberry (DJ) and BC each having errors of 201% and 233% respectively

Using systematic sampling methods RM and WH came up as the most dominant species. 24 quadrats were sampled and systematically spaced 50 quadrats from one another. Percent error for each showed an error of 4.21% and 37%, and a total time of 12 hours and 22 minutes was taken to sample. The two most rare species were DJ and white pine and white pine each having errors of 57% and 67% respectively

Observing the results shows that RM and WH are the most common species. Out of the three methods random sampling produced the least percent error (1.98%, 26%), and I suggest that this is the most accurate method. RM appeared to have the lowest percent error in all three methods (1.98%, 14.14%, 4.21%). This could be an artifact from the actual data and more current analysis may have to be undertaken. Another observation includes percent error increasing with diminishing abundance of species with BC (566%, 233%) and DJ (201%, 57%) having the largest error and least recorded abundance. This concludes that accuracy in all three methods increases with the availability of species to sample and random sampling was the most accurate method for sampling. Moreover, systematic sampling took the longest to complete and haphazard and random took similar amounts of time.

For this blog post, I used an online community sampling exercise to sample Mohn Mill. I used three techniques, systematic sampling, random sampling, and haphazard sampling. The most efficient sampling technique was random sampling, taking approximately 11 hours and 51 minutes in comparison to the other techniques taking over 12 hours. The two most common species were the Red Maple and the White Oak, and the two rarest species were the White Ash and Yellow Birch. The percentages are listed below for comparison. The accuracy of the tests varied widely between the common and rare species, the common species having errors as low as 1.33%, and the rare species having errors as high as 1037.5%, the accuracy declining significantly with the rare species. In general, random sampling method had the lowest percent error for both common and rare species, excluding the White Ash. The most accurate of the common species was the random sampling of the Red Maple, with percent error of 1.33%. The most accurate of the rare species was significantly worse, from all sample methods of the Yellow Birch with a percent error of 100% across the board. I think 24 sample points is enough to capture the number of species in this density, but it would not hurt to have more data to further confirm conclusions made. I think that 24 sample points is not enough to accurately estimate the abundance of these species, as the percent error for the rare species was astronomical in comparison to that of the common species and more data is needed to capture more accurate numbers for the rare species. 

RM random- 8%

ROM syst – 1.33%

RM hap – 7.12%

 

WO ran – 34.33%

WO syst – 46.44%

WO hap – 39.87%

YB ran – 100%

YB syst 

TB hap

WA ran 100%

WA syst 1037.5%

WA hap – 937.5%

In the virtual forest tutorial, a systematic sampling method, a simple randomized sampling method, and a haphazard sampling method were used to determine the frequency of seven tree species. The systematic sampling method involved randomly selecting a point along the southern margin of the study area and running a transect, straight north, through the five topographical regions (Southern Ridge Top, North Facing Slope, Bottomland, South-Facing Slope, and Northern Ridge Top). Samples were then taken from 24 quadrats (alternating between the eastern side and western side of the transect) until the northern margin was reached. The simple randomized sampling method involved generating 24 random locations to collect data. Finally, my haphazard method of sample collection involved attempting to space the quadrats in such a way that they maximized the distance between each other and the edge of the study area.

Based on the estimated sampling times, the haphazard method proved to be the fastest method (12:17 hrs) of sampling, and the simple random sampling method ended up being the slowest (12:45 hrs). However, I think it is worth noting that the systematic sampling method was, anecdotally, the fastest to conduct in the simulation and it seems logical that it should be considerably faster that either of the other two methods. This is because it covered much less walking distance than the random and haphazard method.

The two most common species in the study area were eastern hemlock and red maple. For eastern hemlock, the haphazard sampling method yielded a 6.9% error, the systematic sampling method yielded a 13.2% error, and the random sampling method yielded a 26.4% error. For red maple, the haphazard sampling method yielded a 17.0% error, the systematic sampling method yielded a 5.1% error, and the random sampling method yielded a 5.9% error.   In both cases, the systematic method was more accurate than the random method, and the haphazard varied from being the best and the worst method.

The two most rare species in the study area were striped maple and white pine. For striped maple, the haphazard sampling method yielded a 100% error, the systematic sampling method yielded a 31.4% error, and the random sampling method yielded a 42% error. For white pine, the haphazard sampling method yielded a 98% error, the systematic sampling method yielded a 185% error, and the random sampling method yielded a 49% error.   The systematic sampling method was most accurate for the striped maple; however, the random method wasn’t far off. In the case of the white pine, the systematic sampling method was extremely inaccurate and the random method was the most accurate. The haphazard method was extremely inaccurate in both cases.

Overall, the haphazard method out-performed the other methods for four out of the seven species. However, it was extremely inaccurate with determining the frequency of rare species and red maple. The inconsistent percent error values of the haphazard method lead me to believe that this method has value; however, it is a risky sampling strategy. I believe that the success from my haphazard approach is likely derived from traits that it took from a stratified method. By choosing points that were relatively far away from each other, I, incidentally, chose a similar amount of points in each region (Southern Ridge Top, North Facing Slope, Bottomland, South-Facing Slope, and Northern Ridge Top). Similarly, the systematic method performed well in most cases but had a lot of challenge with the rare species. Therefore, even though the random sampling method only outperformed both other methods in one case, it was the most consistent for determining the frequency of common and rare species.