unimodal data for CCA

[heatherj...@gmail.com]

Hi,

What do you regard as the best method for determining unimodality of data and therefore its suitability in CCA?  

Cheers,

Heather.

[Bruce McCune]

Heather,
Some people recommend a criterion based on first axis length in DCA. But a simple, graphical approach is to use a smoothing function (or nonparametric regression) to plot species abundance or probability of occurrence against the dominant predictors, then evaluate whether the relationships are reasonably well described by straight lines or not.

You can do this with kernel smoothers (as in the ordination overlay function in PC-ORD, or via HyperNiche), or with GAMs, or other smoothers.

-Bruce McCune

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[heatherj...@gmail.com]

Thanks the overlay function in PCORD was helpful and my data seems to be reasonably unimodal.