Dear Angela, this question has different answers depending on the location of the quadrats. If some quadrats are nearer to each other than other quadrats the relationships between the species are a function of their presence and absence in the same quadrat as well as some distance fuinction taken over the quadrats. This distance function may depend on purely geographic distance and some other terrain variables (micro climatic conditions: for instance, proximity of water). Your question requires a complex answer and provides an interesting challenge!

Rudo

 Hi Angela, 

Long time, no see. I've just now started getting into similar analyses, so I don't know what methods have been vetted properly in the literature. I did come across the co-occurrence analysis in EcoSimR:

https://cran.r-project.org/web/packages/EcoSimR/vignettes/CoOccurrenceVignette.html

Of course, it would be nice--as Rudo points out--to have some ability to account for similarity due to distance. But this may be less of an issue if quadrats were placed randomly. Anyway, not sure if this resource will work for you. Maybe it could be extended a bit to provide something more useful to your question.

P

Exactly, a similarity analysis (Jaccard, among others methos) is a good idea for this question. I have a paper that discusses that issue: "Detecting plant spatial patterns, using multidimensional scaling and cluster analysis, in rural landscapes in Central Iberian Peninsula". Landscape and urban planning (2010), 95: 138-150.  I recommend reading.

Salud

Javier

J. Patrick, I have the same problem that Angela. But I am meeting EcoSimR. Do you know to interpret the graphics ("hist" and "burn_in") ecause on the package's page is not clear! ???

Thank you.