|Primary Contact(s)||Created||Required Software||Example Datafile|
|Justen Whittall||12 March 2009||Mesquite, pdap||Aquilegia.nex|
Herein, you'll be comparing the evolutionary change in a continuous character (spur length) with a discrete character (i.e. pollinator shifts). We will examine the amount of spur length evolution during speciation within a pollination syndrome vs. during shifts between pollination syndromes.
In 1863, Darwin predicted the existence of a hawkmoth with an exceedingly long tongue based on the spur length of the Malagasy orchid, Angraecum sesquipedale. The eventual discovery of this hawkmoth, "Xanthopan morgani ssp. praedicta" is considered one of the most convincing demonstrations of the predictive ability of evolution by natural selection. Yet, the mechanism by which these traits grow to exceptional lengths remains highly contentious. Darwin's model suggests that the majority of spur length evolution occurs during antagonistic coevolution between the pollinator and the plant "within" a lineage. Alternatively, Wasserthaal suggested that spur lengths may change in a punctuated manner during shifts between distinct pollinators (i.e. "during" speciation).
Part One: The Data
To compare contrasts in spur length evolution (continuous trait) with contrasts in pollination syndrome (discrete trait), I have coded pollination syndromes as 0, 1, and 2 for bee, hummingbird and hawkmoth as the last character in the Aquilegia.nex Character Matrix. This implies an ordered transition between the three states which is only justified through independent analysis of pollination syndromes (in this case using BayesTraits).
Part Two: The Contrasts
To do the contrasts analysis, have the ultrametric tree showing in the tree window (Tree #1), then in the pdap chart window showing contrasts between two characters, toggle the x-axis to pollination syndrome (#14) and the y-axis to log transformed spur length (#3). The large number of points on the y-axis are spur length contrasts when there is no pollination syndrome contrast. To test the hypothesis that most spur length occurs during pollinator shifts, we will compare the average spur length contrast within a syndrome vs. between syndromes. First, go to the Text tab, copy and paste the data into Excel (it pastes everything, so you’ll have to delete all but the x,y data points from the graph). In Excel, select the first column, then use Data, Text to Columns, Delimited, select “Space” and “Other” and put a colon in the box, click OK. Now label the first column “Pollination Syndrome Contrast” and the second column “Spur Length Contrast” and sort by Pollination Syndrome Contrast. Since we’re only interested in the relative magnitudes of the spur length contrasts, take the absolute value of the spur length contrast column (use =abs() command). Now calculate the average Spur Length Contrast when there is zero pollinator shifts and compare it to the spur length contrast when there is a non-zero contrast in pollination syndrome (use =avg() command). You can do a quick ttest in Excel between these two categories of contrasts (use =ttest(array1, array2, 1-tailed, type 3)). How much more spur length evolution is there during pollinator shifts than within pollination syndromes? Is the difference significant?
Part Three: Niche-Filling Adaptive Radiation
Another interesting analysis within the PDAP.CHART menu is the plot of the Abs. Value of Contrast vs. Node Height. A recent paper by Freckleton and Harvey (2006) suggests that a significant negative slope in this plot is consistent with a niche-filling model of adaptive radiation – as a lineage diversifies the ecological divergence decreases through time as the original niches become filled. This is an alternative to the default Brownian Motion model. Which floral traits have significantly negative slopes consistent with this “adaptive radiation” hypothesis?
Testing for Correlated Evolution in Anthocyanin Gene Expression: Identifying Correlated Gene Expression in the Anthocyanin Biosynthetic Pathway