...a problem where one could cite many, many great studies.
- Google "locational analysis" will be helpful
- check the work (PhDs) of Martijn van Leusen (http://scholar.google.com/citations?user=H6OP3MUAAAAJ) and Philipp Verhagen (http://vu-nl.academia.edu/PhilipVerhagen) for basics regarding theory and method in general.
- tutorials and guides regarding the application in R and GIS can be found, e.g, in the books/manuals of Roger Bivand (see link for a book) or Adrian Baddeley (--> http://www.spatstat.org/) [they cover the practice part and you have to adapt your question to it...but it will work!]
...finally after checking all this you are ready to also check current papers/books covering this topic and attending mailing lists of R and e.g GRASS GIS.
In general, the methodological approach that your are looking for is "predictive modelling"
I am not sure whether there is a point-and-click tutorial. It always depends on the context of the research question.
...some techniques from this link will be useful for analyzing the data: http://cran.r-project.org/web/packages/dismo/vignettes/sdm.pdf
In general you shall follow a procedure like this (what will take some time - but this is unavoidable):
1) understand the method, so that you can divide it in smaller parts for your data analysis
2) find tutorials for R and GIS that explain how to solve the "small step question" defined in 1 --> e.g. one question would be "what is the environmental feature, where most of my hitherto known sites are located" ... the R-course of Baddely explains in detail how to answer these kind of questions (link: http://www.csiro.au/Portals/Publications/Research--Reports/Spatial-Point-Patterns-in-R.aspx)
3) combine the data...
not the answer you looked for, right? ;) But in my opinion there is no quicker way.