User: | Open Learning Faculty Member:
My field data collection began when I revised my plots to include 2 separate plots of wet and dry soil. I created a field data table similar to the activity in Module 3. I set up the table to include the 6 replicates I have chosen; Hydrocotyle Heteromeria, Trifolium repens, Glechoma hederacea, Bellis perennis, Poa pratensis and Elymus repens.
My design is a Logistical Regression experiment as I am determining a categorical predictor variable. The predictor variable for the hypothesis is soil moisture. I have determined areas which contain high levels of soil moisture and areas of less soil moisture using a ‘soil moisture meter.’ According to Gotelli and Ellison (2004), am hoping to determine the “effects of X on Variable Y.” My experiment will help me determine if the effects of moisture variable ‘X’ limits the abundance of Hydrocotyle plant ‘Y’.
I have not had any trouble implementing the Logistical Regression sampling design, on the systematically placed transects. My data table has a categorical predictor of ‘absence or presence” of the replicates in each quadrate in the two sample plots. The only issue that I had not accounted for was the fact that it was so time consuming. Looking at 16 quadrates in two 5x5m sections to determine each species took me hours.
To decrease the chances that the experimental data results may not be a representation of the actual patterns occurring, I will have a large scale area to sample, greater than 1m2 (Gotelli 2004, Englund 2003).
I am performing a natural experiment in which the two plots are in natural settings and have not been manipulated. I am performing a snapshot survey of the plots (in the month of September) instead of a trajectory experiment which would be done over time and years (Gotelli 2004). Snapshots work well because the replicates are more likely to be independent of one another as compared to the trajectory experiments (Gotelli 2004).
I will be using 6 replicates which are the 6 most common species found in my lawn experiment. Using the “Rule of 10” I have systematically set up 4 transects in a North/South and East/West direction to give me 16 study plots in each of my 2 designated “high moisture content” and “low moisture content” areas. The quadrate size is 17x17cm, which will ensure that the samples are far enough apart to be independent. Both of the plots are homogeneous in climatic conditions. I don’t not need a control group as I am not manipulating the experiment, I am surveying the natural landscape.
Grain: Smallest unit of study = the absence or presence of the replicate in the 17x17cm quadrate
Extent: Total area encompassed by all sampling units = 2.7m2 of sampling area
Citation
Gotelli and Ellison. 2004. A primer of Ecological statistics. Chapter 6; Designing a Successful Field Study. Web. Accessed TRU.
Englund, G. and S.D. Cooper. 2003. Scale effects and extrapolation in ecological experiments. Advances in Ecological Research 33: 161-213. Accessed TRU.
