The difficulties I had with my data collection was mostly weather related. The days where I went out it started snowing a lot and didn’t stop. I had to walk in knee deep snow through the forest, which is to be expected at this time of year. I had also planned on looked at the soil in my research, but there was so much snow that I wasn’t able to get to it. I also found it difficult to get started on the data, to figure out where I was going to go and how I was going to do my research, but once I started it got easier. I also came across 3 beavers who were not happy to see me.
I didn’t find the data I collected surprising much. As I started on the flood plain, I found there was only poplar trees that were young. Then as I moved inwards towards the forest, more diverse species would show up, and less of the poplar trees would be there, which is what I expected.
I am not sure if I need to change my data collection. I found as I was going I started to change my approach to be more efficient and make more notes. at first I was measuring all the trees, which is impossible in some areas. So instead I measured the bigger ones and took note on the different sizes.
Constructive Feedback on paulso’s Hypothesis:
Hey paulso! First off, kudos for navigating the challenges of snow-covered fieldwork and encountering the beavers – field research always brings unexpected surprises!
Now, let’s dive into your hypothesis, “The presence of snow impacts the foraging behavior of local wildlife.”
Strengths:
Clear Topic: Your focus on the impact of snow on wildlife foraging is relevant and interesting.
Observable Prediction: The prediction is implicit – the presence of snow will cause a change in wildlife foraging behavior. However, consider making it more explicit and measurable. What specific changes are you expecting? This clarity will enhance the hypothesis’s testability.
Constructive Feedback:
Falsifiability: Consider making the prediction more explicit to enable easier falsifiability. For example, you could predict a quantifiable change like a decrease in foraging time or a shift in the types of food sources chosen by wildlife in the presence of snow.
Measurability: Specify the variables you’ll use to measure foraging behavior. Are you observing feeding time, types of food consumed, or the frequency of foraging events? The more specific you are, the better you can quantify the impact.
Confounding Variables: Given the weather-related challenges you’ve faced, it’s essential to consider potential confounding variables. For instance, variations in snow depth, temperature, or wildlife species might influence foraging behavior independently of snow presence. Addressing these potential confounders will strengthen your study’s conclusions.
Clarity on Patterns: While you mentioned encountering a pattern in tree distribution, it would be helpful to elaborate on the patterns you’re specifically investigating in wildlife foraging. What are the expected pieces and patterns?
Remember, refining these aspects will not only strengthen your hypothesis but also guide your data collection and analysis. Keep up the great work in the snowy wilderness!
Hi, make sure you have a sample unit of some sort, you mention sampling all the trees. You should have a quadrat size which is usually 3-5 m diameter at least for trees.