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Here is a description of my sampling method:

A simple, random and distance based sampling technique was used, incorporating plots along a transect and transects along a path.

Each transect consists of three plots, one immediately adjacent to the pathway, another 10 m away from the path, and another 20 m away from the path. Each location for a transect was selected by entering the range of the number of metres of the trail length, from 0 to 3100 metres, for the trail along which data was to be collected. The first 5 numbers were selected, representing the number of metres from the beginning of the trail at which a transect would be located.

Each proceeding transect alternated from being on the left for the first to the right for the second, etc. The second plot was found by moving in the exact same direction, 10m away from the first plot centre, further into the forest. The third plot was found by moving in the exact same direction, 10m away from the second plot centre, further into the forest.

Upon finding the location along the trail, plot centre was found by moving into the forest 3m to the left (3m is the plot radius ) so that the plot is touching but not overlapping with the path edge. Each 3m plot encompasses 28.27 square meters and was selected based on silviculture survey practices. At each centre a stake was driven into the ground and a plot cord with a mark 3m away from the stake, marked the edge. If the mark touched the bark, a tree or shrub was included in the count.

The first plot represented the site with the most disturbance, the second plot represented the site with an intermediate level of disturbance, and the third plot represented a site with the least disturbance.

Here is my reflection on the sampling method:

I did not have much trouble with my sampling strategy. This was largely due to experience having conducted silviculture surveys over the past summer. I was nervous before and during the first number of plots as I had my fingers crossed that my predictions weren’t not true and I believe the data verified that. To find distance markers, indicating the placement of transects and distances between plots, I used my cell phone’s GPS technology and this probably introduced inaccuracies in distances as it is not as accurate as using an actual GPS with a low degree of error.

Some of the data collected did not seem to make sense. For instance, the number of large trees was often greater closer to the path. Though, my basic hypothesis is that they would be more plentiful further away from the path. When looking at the trees, the largest ones with a circumference of over 1m were most often found furthest away whereas trees considered ‘large’, more than 2m, may have been more plentiful but had a much smaller circumference. With this adjustment to sampling, adding another ‘class’ of tree size, I was able to reconcile the data on the ground and my hypothesis.

The collection of my initial data for my research project did prove to be a little challenging and I quickly realized some of the mistakes that I made. I was using a point count sample method in my location to count bird presence with ambient temperature as the predictor variable. However the sampling area was too large and therefore not the most effective way to sample. I used a grassed backyard area around 24 feet x 30 feet as the location which proved to be too confusing as I didn’t know whether to include birds on the fence. Also with birds flying in and through the area I wasn’t sure if I was double counting them. Therefore sometimes I counted them and sometimes I didn’t as I wasn’t sure if I had already. It was difficult to know whether the birds I was counting were ones that had already been counted. In hindsight I should have used a bird feeder on one of the trees and counted bird activity at the feeder.
Secondly, I also realized that my hypothesis was not detailed enough. My focus initially was hypothesizing that bird activity would be increased with warmer spring temperatures above 12.5 degrees C but I should have used a temperature range of 10 – 15 degrees C to hypothesize that temperatures outside of these ranges would have decreased bird activity because I needed to include temperatures both above and below the range as bird activity may be diminished in extreme temperatures on either end. I also should have done my testing in the morning when temperatures were cooler but due to time constraints I tested in the afternoon when temperatures were warmer and therefore I mostly had temperatures above my hypothesis. In hindsight I should have tested early in the morning when the temperatures weren’t as hot.
The results that surprised me were that the bird activity was strongest on the coolest day. I had hypothesized that birds prefer warmer weather but in fact based on the initial results they seem to prefer cooler weather.
When I test again, I plan to adjust my point count method by using the bird feeder. This will make it easier to count the birds, eliminate confusion and I feel it will be a more effective method. I also plan to conduct the research in the morning when temperatures will be cooler and slightly more variable (before the temperatures are at the height of the day). This will ensure I get enough days both above, below and within the range of my hypothesis. I also need to clarify my hypothesis before I complete the research project as it is too vague and doesn’t account for hot weather.