# [R-sig-Geo] AdehabitatHR: interpreting biased random bridge RD and ID output

Rowena Hamer rowena.hamer at utas.edu.au
Mon Oct 23 05:01:17 CEST 2017

```Hi,

I am using the biased random bridges function within the adehabitatHR package to analyse home ranges, and am interested in breaking the utilisation distribution down into recursion and intensity of use, as outlined in the vignette. I have successfully run the analyses as per the vignette example (code below), and can happily plot the UD, ID and RD and pull out areas of high visitation using the isopleths etc.

What I can't understand is how the output of the BRB function relates to 'real' values of the number of visits per site, and the average length of time spent in these areas. The raw pixel values range between 0 and ~0.0000006 (as in example below): I can't find any explanation of the units used in these outputs, and whether there is a way to translate them into more readily interpreted values.

For example, in Benhamou and Riotte-Lambert 2012, they describe further analyses of the distributions:
"For instance, the minimum area accounting for 20% of the visits (red and orange area in the bottom right panel of Fig. 2) was visited 36 times (ignoring numerous short (<1 h) movement bouts inside or outside the area due to movements close to the area edges). The mean visit duration was about 5 h (this area thus was exploited for 27% of the total period whereas it encompassed only about 5% of the home range area), and the mean duration spent outside the area between one exit and the consecutive entry was about 13 h."

Is there a built in way to translate the ID and RD outputs into this kind of data, or do you have to calculate it separately (e.g. by overlaying the ID/ RD over the original data and summarising the number of visits manually?).

Thanks for any help you can give!

Rowena

Buffalo example from adehabitatHR vignette:

> data(buffalo)
> id <- BRB(buffalo\$traj, D = 440/60, Tmax = 3*3600, Lmin = 50, type = "ID",
+           hmin=100, radius = 300, maxt = 2*3600, activity="act", filtershort=FALSE,
+           grid = 200, extent=0.1)
> rd <- BRB(buffalo\$traj, D = 440/60, Tmax = 3*3600, Lmin = 50, type = "RD",
+           hmin=100, radius = 300, maxt = 2*3600, activity="act", filtershort=FALSE,
+           grid = 200, extent=0.1)
> ud <- BRB(buffalo\$traj, D = 440/60, Tmax = 3*3600, Lmin = 50,
+           hmin=100, radius = 300, maxt = 2*3600, activity="act", filtershort=FALSE,
+           grid = 200, extent=0.1)
> range(ud at data)
[1] 0.000000e+00 5.660811e-07
> range(id at data)
[1] 0.000000e+00 6.552115e-07
> range(rd at data)
[1] 0.000000e+00 3.774331e-07

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