Dear Julia,
Many thanks to those who create and maintain AniMov software!
After a steep learing curve with adehabitat I'm finding it very useful.
However with kernels for short periods, I sometimes get an error.
It seems this is caused by a set of locations that don't change.
### adehabitatHR_0.1 R 2.12.1 Windows XP
#demo: error with animal at same location during period of interest
X<- rep(699889, 10)
Y<- rep(3161559, 10)
Name<- rep("Brock", 10)
test<- data.frame (Name, X, Y)
coordinates(test)<- c("X", "Y")
ud<- kernelUD(test)
#Error in points2grid(points, tolerance, round, fuzz.tol) :
# cannot determine cell size from constant coordinate 1
Yes, this error is expected: the UD is a continuous probability density
function estimated for each pixel of a grid. The function uses the X and
Y range of the relocations to determine the extent of the grid. When
this range is equal to zero, the function cannot identify this range.
From a *purely technical* point of view, this can be fixed by first
building a grid with the desired extent, and then use it as the
parameter grid in the function kernelUD. However, you will have another
problem when the function will have to calculate the smoothing
parameter: whatever the method you choose, it depends on the variability
of the X and Y coordinates. So that the only *technical* way to have a
result from kernelUD in such a case is also to specify the smoothing
parameter "manually". For example:
## Prepares the data
X<- rep(699889, 10)
Y<- rep(3161559, 10)
Name<- rep("Brock", 10)
test<- data.frame (Name, X, Y)
coordinates(test)<- c("X", "Y")
## Prepares the grid
fakeda <- data.frame(X = c(699889-200, 699889+200), Y=c(3161559-200,
3161559+200))
coordinates(fakeda) <- c("X","Y")
grid <- ascgen(fakeda, nrcol=100)
## estimate the UD with h=100
kud <- kernelUD(test, h=100, grid=grid)
Now, you have to think about the scientific issue raised by this
problem: for example, the 95% home range is defined as the minimum area
where the probability to find the animal is equal to 95%. In your case,
the home range is not an area, but a point. What is the meaning of the
home range in this context? I do not think that any statistical method
will succeed to estimate the home-range of an animal that does not move.
HTH,
Clément
#demo: no error after small change in one location
XX<- c(rep(699889, 9), 699890)
YY<- c(rep(3161559, 9), 3161560)
Name<- rep("Brock", 10)
test2<- data.frame (Name, XX, YY)
coordinates(test2)<- c("XX", "YY")
ud2<- kernelUD(test2)
Apologies in advance if this problem arises from newbie misunderstanding.
However unchanging locations (over a limited time) are a valid occurrence in my
data so I will be very grateful for the solution.
Thanks and best wishes,
Julia
Julia Hazel Ph.D.
Adjunct Research Fellow
School of Earth and Environmental Sciences
James Cook University, Townsville
QLD 4811
Phone: 0407 431 382 (international +61 407 431 382)
Email: [email protected]
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--
Clément CALENGE
Cellule d'appui à l'analyse de données
Direction des Etudes et de la Recherche
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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