Hello
I am trying to calculate home range area of several individual birds that I have tracked, combined as one sample rather than considering them individually, using the code:
>jj<-kernel.area(xy, id)
and I use
>hr<-kernelUD(xy, id, same4all=TRUE)  # to get a image of the predicted home range area

which works fine but it has been recommended to me that I should be using the LSCV or Brownian Bridge method of analysis

The LSCV method gives me an error message of "In .kernelUDs(SpatialPoints(x, proj4string = CRS(as.character(pfs1))),  :
The algorithm did not converge within the specified range of hlim: try to increase it"

Which I realise is a common problem so I have tried the Brownian Bridge method:

>birds<-kernelbb(tr, sig1=9.8649, sig2=2, grid=50)
> birds
> image(birds)
> plot(getverticeshr(birds, 95), add=TRUE, lwd=2)
> plot(getverticeshr(birds, 50), add=TRUE, lwd=2)
> plot(tr)
> jj<-kernel.area(birds, unout=c("km2"))
> jj

But the problem here is that I have removed the nesting site GPS locations of my birds, as do not want the island where they breed to be considered in my analysis. So there are large gaps in time between two successive foraging trips made by an individual but I believe the Brownian Bridge method still takes into account the space between two successive foraging trips (i.e. the area on land) which is not what I want! Does anyone have any ideas about how to overcome this?

Many thanks
Louise Soanes


School of Environmental Sciences
University of Liverpool
Brownlow Hill
L69 3GP

www.puffinisland.org.uk


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