Statistics and R « The Echinacea Project

Rachael’s paper on Malo curves

Read Rachael’s final paper, in which she investigates the extent to which flowering schedules differ between plants with only one head and plants with multiple heads.

initial aphid dataset for discussion about statistics

Here it is:
aphid1.csv

Asteraceae Breeding Systems: Data Analysis!

Hi all!
I’ve been back at Grinnell for about a month now, and so far my semester’s off to a great start! Very busy, but not busy enough to prevent me from finishing up my data analysis.

It looks like Echinacea purpurea‘s breeding system is similar to Echinacea angustifolia‘s. Styles that receive compatible pollen shrivel up within a few days, whereas styles that don’t persist longer, often for more than a week. In addition, E. purpurea is self-incompatible. (This means that an individual plant can’t pollinate itself, it needs pollen from another plant of the same species.)

To complicate things a little:
Not all of the flower heads I was studying had finished flowering by the time I left Minnesota, so I do not have much data on the top several rows of styles on many of them. Since styles in higher-up rows persist somewhat shorter than in lower rows, I cannot be sure that the trends I saw in my data hold for the top rows of all flower heads.
Also, some of the statistical tests I ran showed that style persistence in the self-pollination treatment differs significantly from the control treatment, while others do not. I’m not sure why that would be.

Here are my csv file and my analysis in R:
epurpurea.csv
epurpureaAnalysis.R

If anyone has any suggestions for improvement or other things I could look at with this data, please let me know!

And I posted much of my data analysis on H. helianthoides already, but here are the “final” versions. (But, again, I’m open to suggestions for further improvement!)
hhelianthoides.csv
FinalAnalysisLeeRodman.R

Some C. palmata and H. helianthoides Results

H. helianthoides appears to be self-incompatible. Here’s the data I collected:
hhelianthoides.csv
I’ve also started my data analysis in R. It’s not done yet, but here’s what I have so far:
Data Analysis.txt
Basically, styles persist significantly longer when self-pollinated or not pollinated than when cross-pollinated. However, in the top rows of florets on each flower head, style persistence does not differ as much between the treatments (because all the styles in these rows shrivel rather quickly). Therefore, when using style persistence to study other aspects of this species’ breeding system (ex. pollinator efficiency, compatibility of specific individuals), one should use the bottom several rows of florets. In these rows, cross-pollinated styles always shrivel within three days of pollen application, whereas styles that do not receive compatible pollen never shrivel so quickly.

As I mentioned before, I was unable to collect much quantitative data about C. palmata style persistence. But I did notice some things that might be helpful to anyone interested in studying this species further. The following document gives a brief summary:
C. palmata Summary.doc

Dataset for Callin’s Compatibility Experiment

Here’s the final dataset for my compatibility experiment. The experiment is officially ended today (I collected the last bit of data). The dataset contains GPS data (column name distBetween). I missed one plant while GPS-ing, so I used the hand-measured data (for flag #6 at Nessman’s). I also corrected several errors in the datasheet.

Data for Analysis — cswitzer — 31 July 2011.csv

We spent some time GPS-ing the plants, so we could get the exact distances between them. Here is a csv file with the gps data.

I have been working on analyzing all my data. I looked at plots of each of my individual sties, as well as all the data combined. The data are almost exactly opposite of what I expected.
Here’s the script I’ve been exploring:
callinCompatRScript31july2011.R

Here’s a picture of Josh, Amber Z, and I out in the field (having a lot of fun).

Characteristics of a good CSV file for R

Edited by cswitzer. 25 July 2011

Characteristics of a good CSV file:
1. Use database format in Excel

See this example: https://echinaceaproject.org/wp-content/uploads/2011/07/preliminary-analysis-for-calli.html
2. Don’t mix text, integer, or numeric fields (you may enter NA in a numeric field to signify missing data)
3. Remove spaces from excel cells
4. No punctuation in each column name
5. Don’t start a column with a number
6. Column names should be in easily typable format — use capitals at new words and use no spaces (called camelback format)

Statistics online Textbook

Here’s a link to a useful, online statistics textbook.

http://www.statsoft.com/textbook/

Stipa and the common garden

I’ve been working with the Stipa germination data we collected from the common garden over the summer for Stuart’s R class and, among other things, have come up with a little plot of the common garden. Filled-in blue circles are where we found Stipa alive, empty circles had no seedlings. A neat thing would be some kind of heat map for longest leaf or number of leaves, but I’ll try that later.

View image