Vario is an R package that I am currently developing for computing spatial community variograms, carrying out null modeling, and graphing the results in a meaningful way. Allen Hurlbert and I have recently submitted a manuscript that harnesses this code to describe spatial community structure in breeding birds of North America.
As many of you know there are currently a variety of R packages that can be used to compute variograms so what is special about this package you may ask. The answer is that our calculations focus on patterns community ecologists are interested in when they are examining multi-species spatial patterns. In this context we argue that ecologists should be interested in not only understanding intra-specific (or within-species) aggregation but also inter-specific (or between-species) aggregation. Helene Wagner (2003, 2004) laid the statistical ground work for these ideas, and Allen and I have extended them further in our recent manuscript. Our package computes both intra- and inter-specific patterns of aggregation and provides relevant null models to examine if these fractions differ from what would be expected due to chance. I should point out that this package does not contain any code to carry out kriging (a common method of geospatial interpolation based upon variograms), and I have no plans for adding this in the future.
At this date (01/2012) vario functionally contains all the relevant code but still requires help files. Until these are complete, please feel free to download the source and read each functions annotations if you wish to get feel for this package. The source code is located on Git Hub at this address:
McGlinn, D.J. and A.H. Hurlbert. submitted. Spatially disentangling within- and between-species components of community variation reveals processes driving community assembly – Oikos
Wagner, H. H. 2003. Spatial covariance in plant communities: integrating ordination, geostatistics, and variance testing. – Ecology 84: 1045-1057.
Wagner, H. H. 2004. Direct multi-scale ordination with canonical correspondence analysis. – Ecology 85: 342-351.