FYI
-------- Messaggio originale --------
Da: Conservation Ecology <[email protected]>
Inviato il: Sun Mar 03 21:41:50 CET 2013
A: [email protected]
Oggetto: [New post] Calculating average percentual Home-range overlaps in R
Post : Calculating average percentual Home-range overlaps in R
URL :
http://conservationecology.wordpress.com/2013/03/03/calculating-percentual-home-range-overlaps-in-r/
Posted : March 3, 2013 at 9:41 pm
Author : Curlew
Tags : home-range, ornithology, r-code, spatial overlaps
Categories : Biology, GIS, Statistics
If you are studying ornithology you can usually fall back on a rich basis of
knowledge accumulated over many years by volunteers, birders and professional
ornithologist. I can think of no other taxonomic group that has been studied
this intensively (well, maybe plants). Any yet it amazes me that stil
http://conservationecology.files.wordpress.com/2013/03/web_20090415_951.jpg&h=180
l we lack so much knowledge and data about why bird populations are declining
and what the reasons for these declines are. For instance since some years it
has been known that especially long-distant migrants are quite vulnerable to
multiple reasons like habitat degradation and climate change in their wintering
grounds (Berthold et al. 1998, Sanderson et al. 2006; Heldbjerg & Fox 2008).
Since so little is known (if for example compared to the American migration
route) about how those species behave, forage and migrate in the areas below
the Sahara, there is an urgent need for more information and data. Using the
newest technology such as very tiny GPS loggers we became able to track many
declining birds to their wintering grounds.
Right know i am working with relocation data from 3 warbler species, which is a
quite a new way of thinking for me (waypoints instead of occurence points) and
right now i am diving into the topic by analyzing this data to for instance
estimate the amount of overlaps between many species.
In this R-code i show you how you can easily use the package adehabitat for R
to estimate the home-range using an adhoc Kernel. In my example i have used a
point-layer containing relocation data with a Date and Time and a Species ID
(Bird_ID) of 3 warbler species in an area in southern Senegal.
require(adehabitat);library(rgdal)
# Read in your Relocation Layer
spp <- readOGR("source","layer")
# Construct an adhoc Kernel for my 3 different warbler species
k <- kernelUD(as.data.frame(coordinates(spp)),
id=spp$Bird_ID,h="href",same4all=T,grid=200)
# Calculate the area in square kilometers for a 50% Core-Zone and 95% Zone
kernel.area(data.frame(coordinates(spp)),
id=spp$Bird_ID,levels=c(50,95),unin="m",unout="km2")
# Calculate the Overlap of the kernel in Percent for all Bird species
(kov <- kerneloverlaphr(k,method="HR",lev=95)) # Percentage Overlap 95
http://conservationecology.files.wordpress.com/2013/03/overlap.png&h=142
Calculating Percentage values of overlaps usually returns a matrix containing
two different values. The percentage overlap from the smaller home-range to the
bigger and vice versa (See Picture - Area C). Therefore there could be two
different percentage values depending from which site you're looking at it.
My approach for this problem has been to simply swap the distance matrix and
average the percentage values (this is kinda inaccurate, but still used in some
newer papers), but i also would advice to use other indices, like the
Utilization distribution Overlap Index (UDOI) proposed by Fieberg and Kochanny
in 2005.
# SwapMatrix function to convert a distance matrix into a data.frame
swapMatrix <- function(m) {
ut <- upper.tri(m)
data.frame(i = rownames(m)[row(m)[ut]],
j = rownames(m)[col(m)[ut]],
x=t(m)[ut],
y=(m)[ut])
}
m <- swapMatrix(kov) # Swap your overlap
m$avg <- rowMeans(m[,3:4]) # And calculate the average of both values
Thats be it for now. I am still in the process of exploring all those
techniques to investigate species home-ranges. Any links or cool examples are
much appreciated.
References:
* Berthold, P, Fiedler, W, Schlenker, R, Querner, U, "25-year study of the
population development of Central European songbirds: a general decline, most
evident in long-distance migrants." Naturwissenschaften 85.7 (1998): 350-353.
* Sanderson, Fiona J, Donald, Paul F., Pain, Deborah J., Burfield, Ian J., van
Bommel, Frans P.J. "Long-term population declines in Afro-Palearctic migrant
birds." Biological Conservation 131.1 (2006): 93-105.
* Heldbjerg, Henning, and Fox, Tony (AD) "Long-term population declines in
Danish trans-Saharan migrant birds: Capsule Long-distance migrant birds show
less favourable trends than sedentary/short-distance species." Bird Study 55.3
(2008): 267-279.
* Fieberg, J. and Kochanny, C.O. (2005) Quantifying home-range overlap: the
importance of the utilization distribution. Journal of Wildlife Management, 69,
1346–1359.
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