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My project involves looking at the surface density of springtails (Collembola) in response to the presence or absence of cover. The data collection consisted of counting individual arthropods on the snow surface within 10 quadrats in two treatments (5 each), three times a day, over the course of five days. So though I had 150 data points, I organized them into 10 rows (corresponding with the quadrats) and divided the data up into columns according to their respective categories (date, time of day, treatment) in Excel and found this visually easy to manage. However, trying to analyze these data points in Excel was not as straightforward, partly because I’m no expert at Excel as a data management tool, and partly because “visually easy to manage” seems to be more of an endpoint of data analysis (the table or graph) rather than a starting point of data management. My “data whiz” friend informed me that data input is easiest to manage when each data point has its own row (in my case that meant 150 rows) and is only located in one column, and to try to ensure that the rest of the data (treatment, date, time-of-day) is specific to its own column – even though that means that the values within these cells would get repeated. This information allowed me to at least partially understand the way a program like Excel reads data, and I began to see how powerful a tool it can be to process, analyze, and display data, especially when datasets are large.
The graph I produced with Excel showed me that there definitely was a trend in my data, possibly a significant one. Though I need to run a p-test to see if I can reject the null hypothesis (the standard error bars between treatments appear to almost overlap), there certainly appeared to be a springtail preference for full sunlight rather than cover. This is the opposite to my prediction of a preference for shade based on observation, as well as the shade preference seen in the results of certain experiments done in the literature (Salmon and Ponge 1998). However, upon further researching this fascinating order of arthropods, I’ve come to understand that there are over 5000 species, some of whom live their lives totally subterranean, some of whom live in surface layers of soil and organic matter, and some of whom live above ground and with a multitude of life strategies and abiotic tolerances (Hopkin 1997).
The small graph I was able to generate from my data reveals to me that my experiment would most certainly be improved with more replicates done over a greater time span and in different habitats. Having more expertise at species identification and sampling in different habitats would also provide more robust scientific knowledge to the ecology of Collembola, as different species likely have different preferences for light and darkness depending on life events that may be occurring at different times throughout the winter (rearing, migration, reproduction etc.).
References:
Hopkin, S.P., 1997. Biology of the Springtails (Insecta: Collembola). Oxford University Press, Oxford.
Salmon, S., Ponge, J.F. Responses to light in a soil-dwelling springtail. European Journal of Soil Biology 34: 199-201.
