Hi everyone,

I'm using the adehabitatHR package to analyze home range overlap amongst an estuarine population of bottlenose dolphins.  The study area is a large (250 km), mainly linear system, which is likely to greatly affect the dolphins' home ranges.  However, despite being mainly linear, the coastline is too complex for the "boundary" argument within the kernelUD() function (i.e. the segment lengths and angles violate the rules of Benhamou and Cornelis 2010).

I'm fairly new to using R for spatial analysis, so I'm not sure what other options are available for excluding the land as non-habitat.  Since the estuary system gets extremely narrow (0.5 km) in some areas, it is essential to exclude land as it will alter the home ranges.  I've found an old R-sig-geo posting discussing a similar problem with walrus data and they mentioned the raster exclusion approach (http://r-sig-geo.2731867.n2.nabble.com/Walruses-and-adehabitatHR-class-estUDm-exclusion-of-non-habitat-pixels-and-summary-over-all-animals-td6497315.html); however, I'm having trouble with this method as well.

So on to my real question.  I have an ArcGIS shapefile outlining the estuary system (aka, a polygon of my study area).  I am able to read the file into R using the readShapePoly() function.  For the method described with the previously mentioned walrus data, the habitat file needs to be class SpatialPixelsDataFrame.  Is there a way to convert my file from SpatialPolygonDataFrame into SpatialPixelsDataFrame?  Or, alternatively, is there another method for excluding land from the kernel density that is compatible with either the original shapefile or the SpatialPolygon class?

Thanks so much,
Liz

Liz Hartel
Biological Scientist
Population Biology and Behavioral Ecology
Harbor Branch Oceanographic Institute - FAU
5600 US 1 North, Fort Pierce, FL 34946
work: (772) 242-2238
cell: (772) 216-4363
www.hboi.fau.edu


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