Post 5: Design reflections

My initial data collection went well despite the weather factors and wildlife encounters I had to deal with. After many weeks of continuous rain, I was able to go to the site and stake out my study area. I initially was thinking of doing 250m2 based on my google earth location, however, on one side of my study location, there was an active great horned owl’s nest with nestlings that I had to keep distance to minimize stress. On the opposite side perhaps 500m away, a red-tailed hawk pair was nesting and were showing aggressive behavior when in the field. So, I decided to change my study location and study parameters.

With a 100m2, this still allowed me to transect along various zones being tallgrass, cottonwood trees, rocks and floodplain. I removed the upland slope and wetland from my study because of my constraints with the fence-line and wildlife. I added an extra sample to my transect making it 6 quadrats of 0.9144m2  in order to reach the floodplain.

I picked my transect lines at random with a random number generator. My intervals were 15m and sampling at opposite sides to increase randomization. Rather than using the x,y method to go parallel with each zone, I used the x, y method to cross each zone (perpendicular) from the fence-line to the river. I made a mistake by starting my first sampling at 80, 15 instead of sampling at 80, 0. To rectify this issue for my next transect, my options are: create my table with 80, 15 being my starting point; sample the missing quadrat point next time I go back; or select new random numbers and start over.

This will depend if the vegetation has changed and what time of the day I will transect. To improve overall uniformity and reduce bias, I am considering starting over. This wont take much time because I have created waypoints on my GPS of my x,y axis.

Overall, the systematic approach with transects and quadrats was the best method to use to increase my odds of observing absence/presence of ants along the gradient (response variable).