[AniMov] Clipping area from home range estimates

Wayne Getz getz at nature.berkeley.edu
Thu Jul 16 06:10:58 CEST 2009


Dear Tim:

If you have any questions about trying to get a-LoCoH to run more  
efficiently, please contact Scott Fortmann-Roe at: scottfr at gmail.com.

Wayne

>
> Dear Animovers,
>
> Thank you for the many suggestions.  I have been trying to implement  
> several, but keep running into problems.
>
> 1.  The LoCoH analysis seems to be the most promising method of  
> analyzing my data, especially since I have both coastal boundaries  
> and many of the species I work on seem to have migratory corridors.   
> However, I tried analyzing my data for five different settings of  
> "a" and nine different animals.  Each animal has approximately  
> 432000 data points (once/second for 5 days).  After letting it run  
> for 48 hours I had to stop it to work on another project.  Is LoCoH  
> really that computationally difficult or did I do something wrong?   
> I am using a Dell Precision 390 running Windows XP SP3 with 2 GB  
> RAM.  Any idea how long the analysis should take?  My code was:
>
> homerange<-NNCH(xy,a=c(100,200,300,400,500),id=id)
>
> 2.  I loaded qGIS and have a semi-working version.  However, I have  
> tried to use the Home Range plugin and keep getting an error  
> message.  I posted it on the qGIS forum (http://forum.qgis.org/viewtopic.php?f=2&t=4914 
> ).  I think qGIS isn't communicating with R, but have no idea why.   
> I would appreciate any suggestions you have on how to get the  
> pluging to work correctly.
>
> 3.  I haven't had time to try Damiano or Clement's asc based methods  
> yet, but will be looking for a nice rasta map of the area we are  
> working in to try them out.  While I think the LoCoH method will  
> give a better home range estimate for a lot of our animals, I will  
> still need to produce kernel UD's for comparisons to other studies.   
> I especially appreciate the demo code and the explanation in "fishy"  
> terms.
>
> Aloha,
>
> Tim
>
> Tim Clark
> Department of Zoology
> University of Hawaii
>
>
>> Date: Wed, 15 Jul 2009 09:26:20 +0200
>> From: clement.calenge at oncfs.gouv.fr
>> Subject: Re: [AniMov] Clipping area from home range
>> estimates
>> To: Animal Movement <animov at faunalia.it>
>> Message-ID: <19037.33948.735259.593901 at localhost.localdomain>
>> Content-Type: text/plain; charset=iso-8859-1
>>
>>>
>>> I am trying to use Adehabitat to analyze the home
>> range and movement
>>> patterns of fish (manta rays, sharks, and various
>> species of reef
>>> fish) in Hawaii, but have not found a way to clip land
>> area out of
>>> the animals home range.  Most of the fish I study
>> stay fairly close
>>> to shore, moving along a sinuous coastline.  I
>> have used adehabitat
>>> to estimate their home range (I am mostly interested
>> in kernel
>>> HR's), but need to either limit the calculations to
>> only include
>>> water areas during the calculation or clip out the
>> land area after
>>> the kernel has been calculated.  Is there a way
>> to use a shapefile
>>> or other projected map file to either limit the kernel
>> or to clip
>>> out the area post-processing?  I am fairly new to
>> R and adehabitat,
>>> and am working in Windows.
>>
>>
>> Actually, the main issue with the (classical) kernel method
>> is that it
>> does not allow boundary constraints. I have heard about
>> extensions of
>> the kernel method allowing to take into account boundary
>> extensions,
>> but they are not implemented in adehabitat (and I do not
>> remember the
>> corresponding references) . If your aim is just to estimate
>> a home
>> range (i.e. if an utilization distribution is not desired),
>> and if you
>> do not want to compare your results with previous
>> home-range sizes
>> estimated in the literature, the kernel method is probably
>> not the
>> best choice (as noted by Maren, NNCH would probably be a
>> better
>> choice, as it fits more closely the relocations).
>>
>> However, if you really need to estimate a kernel home
>> range, I may
>> suggest you a tricky solution: to estimate the UD for each
>> animal,
>> then to set the UD to 0 in the pixels located outside the
>> water, to
>> standardise the modified UD so that the volume under the UD
>> is equal
>> to 1, and finally to estimate the home range from this
>> modified UD.
>>
>> mhm... Ok... not that clear. I take an example (just copy
>> and paste to
>> R):
>>
>> ## prepare the data
>> data(puechabon)
>> locs <- puechabon$locs[,c("Name","X","Y")]
>> map <- getkasc(puechabon$kasc, 1)
>>
>> ## show the data
>> image(map)
>> points(locs[,c("X","Y")], col=as.numeric(locs$Name))
>>
>>
>> This map shows the relocations of four wild boars on an
>> elevation
>> map. But imagine that they represent the location of four
>> fishes in a
>> lake (unmapped white areas - NA on this map - are
>> corresponding to the
>> land). Consider the red and black points: they are close to
>> the
>> shore. If we estimate a home range, a large proportion of
>> the home
>> range will cover the land:
>>
>>
>> ## Note here that we use the map as the grid on which the
>> UD is
>> ## estimated
>> kud <- kernelUD(locs[,c("X","Y")], locs$Name, grid=map)
>> ver <- getverticeshr(getvolumeUD(kud))
>> plot(ver, add=TRUE)
>>
>>
>> So a possible way would be to set to zero all the pixels of
>> the UD
>> located on the land, and then to standardise the result.
>> That is:
>>
>> for (i in 1:length(kud)) {
>>     kud[[i]]$UD[is.na(map)] <- 0
>>     kud[[i]]$UD <-
>> kud[[i]]$UD/(sum(kud[[i]]$UD)*(attr(map, "cellsize")^2))
>> }
>> ver2 <- getverticeshr(getvolumeUD(kud))
>>
>>
>> And the resulting home range is:
>>
>> image(map)
>> points(locs[,c("X","Y")], col=as.numeric(locs$Name))
>> plot(ver2, add=TRUE)
>>
>> the home range does not cover the land. And the point is
>> that the
>> object kud represents the UD corrected so that the land is
>> characterized by a probability of occurrence equal to zero
>> (i.e., it
>> is not the home range that is corrected, but the UD). But
>> this
>> solution implies that you are able to derive a raster map
>> from your
>> shapefile where land is represented by NA. Another
>> alternative,
>> already pointed out by Paolo would be to use a GIS (such
>> as qGIS) to clip the home-range polygons after the
>> estimation.
>>
>> Hope this helps,
>>
>>
>> Cl?ment Calenge
>> -- 
>> Cl?ment CALENGE
>> Office national de la chasse et de la faune sauvage
>> Saint Benoist - 78610 Auffargis
>> tel. (33) 01.30.46.54.14
>>
>>
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>>
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>>
>> End of AniMov Digest, Vol 46, Issue 4
>> *************************************
>>
>
>
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___________________________________________________________
___________________________________________________________

Professor Wayne M. Getz
Department Environmental Science Policy & Management
140 Mulford Hall
University of California at Berkeley
CA 94720-3112, USA

Campus Visitors: My office is in 5052 VLSB

Fax:    ( (1-510) 666-2352
Office:    (1-510) 642-8745
Lab:  (1-510) 643-1227
email:  getz at nature.berkeley.edu
http://www.CNR.Berkeley.EDU/~getz/
___________________________________________________________
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