I wonder whether spatial autocorrelation could / should be moved to the distance-based methods lecture.

Also, I have some reservations about interpreting significant autocorrelations at large distances: this requires a good explanation (the example shown is ok in that respect) but also that this is not an effect of very few observations. For any distance class beyond half the maximum distance of the sample, not all observations will contribute. As you get to the largest distances, very few observations are included in the calculations. You may have 10 pairwise comparisons, but they all are between the same two patches...

While Moran's I is focused on testing for autocorrelation, variogram based methods are more directly interpretable (the y axis is a measure of genetic distance) and easily related to pairwise fst plots etc. while allowing for testing for autocorrelation. Maybe these could be mentioned too (e.g. Wagner et al. Genetics)?

Maybe in this lecture (or as part of another lecture) it would be appropriate to discuss a set of methods that are spatial, but do not include processes other than distance (Moran's I, Correlograms, NN, etc).  Was the intention of "distance based measures" to be genetic distance (and include landscape variables in modes) or more purely spatial measures ("spatial genetics" or "geographical genetics")? 

It is used in the gene flow discussion paper that I was suggesting we read for this week so I wanted to introduce the concept. 

I'm not all that knowlegdable about the spatial autocorrelation stuff or Moran's I so if it fits in a later lecture that would be great...i could drop it from here.  But it will make the discussion paper more difficult to follow or I could try to think of a different one.  What did folks think of this student activity?  With more time I could design a better activity that analyzes a dataset.  I had considered having students calculate genetic distance measures - Fst, Ds, Dsp etc and having them interpret the results. 

We also still need a good background reading on measuring gene flow....

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