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I currently have presence data on two birds, a falcon species and the grouse that it prefers to hunt. These data are in two point shapefiles, one for each species. The grouse shapefile represents all of the individuals that I've seen during observational transects, while the falcon shapefile represents all falcon nests in my study region.

I have a hypothesis that the grouse species are located in areas where they are near the fewest possible number of falcon nests (there is almost nowhere on the study site completely without falcon nests, but there are locations where nests are more concentrated). I'd like to examine this with some sort of statistical GIS analysis, but I'm not sure what steps I should take. I've been looking into kernel analysis and the near distance table.

How do I put things together into a cohesive method?

My grouse data is biased toward 3 roadways that run for miles through my study site. If possible, I'd like to also entertain method that may take this bias into account -- but only if possible!

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    Have you looked at the spatial statistics toolbox? desktop.arcgis.com/en/arcmap/10.3/tools/… – Fezter May 24 '17 at 19:39
  • I have, but it seemed like the toolbox was providing tools for examining patterns within a dataset, not between datasets. Am I wrong on that? – Adam May 24 '17 at 19:42
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    Ordinary Least Squares might be what youre after. desktop.arcgis.com/en/arcmap/10.3/tools/… – Fezter May 24 '17 at 19:52
  • You could even generate buffers around the falcon nests and distinguish how far the grouse are locating themselves from these nests – NULL.Dude May 24 '17 at 20:55
  • Would that be with multiple ring buffers, or distances to each buffer? – Adam May 24 '17 at 21:11
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I think that near analysis should do the job:

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