For my project, I am studying the effect of competition for sunlight on the height of trees. For this study, I am looking specifically at the way competition for sunlight created by surrounding trees makes the blocked trees grow taller. The data aligned with my prediction so I was not overly surprised by it. For a while, I was stumped on how I would be able to safely and accurately measure the height of such tall trees but through some research, I found an easy way to collect it. I found an app called Globe Observer that has a tool for measuring trees. I was able to use the in-app tool to take a picture of the tree, input my distance from the tree and the height of the camera and then it would calculate the height. It seemed to be pretty accurate and was close to what I estimated for height so I think I will continue to use this same method. I will however make changes to the way I measured the predictor variable. For my initial data, I just made an estimate for the amount of sun exposure the trees are getting and roughly predicted how much their sunlight would be blocked by other trees throughout the day. Next time I will plan to stay for the entire day so I can observe the sun exposure and the shadows and more accurately measure exactly how much each tree has to compete for sun during the day. Lastly, I wish there were more clusters of trees like this (close enough together to block each other’s sun exposure and of the same age and species) that I could find to include in my study. In my study, there is only the one cluster of 8 trees. With the 8 trees being divided into 3 different treatment levels (different level of sun exposure), I am not able to have as many samples for each treatment as I would have liked.
good use of app tools
yes I think looking at patterns of sun are important, without being able to measure too closely
perhaps an app that measures canopy closure will get idea of opening/light penetration? worth investigating