Collecting data once I decided how I was going to divide up the location proved to be a little challenging. I love birds but it can be difficult to identify them to species if you only get a quick glance. I am going to observe birds within the vicinity and distinguish the bird species morning, afternoon and evening over a 9 day time period. My prediction is that there will be variance in the bird species and abundance of each noticeably in each area depending on the time of day. I may change one location depending on a secondary evaluation of the area but I see myself starting the data collection tomorrow. I am planning on doing a grid overlay from which I randomly generate a location for each sample. Factors I am considering that are related to time of day include temperature, wind, precipitation. Each of the four sites chosen have different abundance of plants, topography all of which will be documented in my field journal along with any other relevant information for sites that will play a part in the data analysis.
Hello Angela
yes it can be difficult to ID especially when canopy is out!
if they are vocalizing, there is the Merlin ID App which may help you (about 80% accurate, I would say)
the temperature may play a part in bird activity – you can talk about that in Discussion for sure as a potential impactful difference.
Wind and precipitation levels less so – there are protocls around not collecting data when too windy or too rainy. Usually after the rain it is cooler, and so that brings temperature back in.
I had a great birding day after a rainstorm here in Kamloops last week – the temp went down to 15 degrees!
I think what you need to is keep it simple – what are the predictor variables? are they site (think to Module 4 and the different treatments along the urbanization grid)? are they temperature (maybe related to time of day)?
have fun