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Using Adehabitat in R to Analyze Animal Space Use Joey Hinton ([email protected]) 12/04/09 This self-tutorial goes step-by-step to help you develop an animal’s homerange and movement path using the adehabitat package in R. Adehabitat is a package developed by Clement Calenge for the analysis of animal space use that creates an interface with geographic information systems. The package has four primary parts. First, it allows for the management of raster maps. It provides functions that allows for the import and export of raster maps to/from geographic information systems and subsequent analyses. Second, adehabitat provides numerous functions for several home range estimators. Third, there are basic statistics to analyze animal movements such as speed, distance, and turning angles. Finally, users are provided a platform to common analyses of habitat selection. There are many functions that I am not covering in this document. Here, I just provide some elementary use of the adehabitat package as a teaser. I would recommend downloading the package and explore the potential use of the package via built-in tutorials (i.e., demos). References used: Calenge, Clement. 2006. The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecological Modelling 197: 516-519. Calenge, Clement. 2007. Exploring habitat selection by wildlife with adehabitat. Journal of Statistical Software 22: 1-19. Install and load the package “adehabitat” In order to analyze animal space use in R, you will need a few of R libraries. These libraries are: gpclib, ade4, adehabitat, and shapefiles. Luckily, you can do a batch install for these. To install them, just enter the following: >install.packages(c("gpclib","ade4","adehabitat","shapefiles")) ##select a CRAN mirror To initialize the adehabitat package, use the command: >library(adehabitat) >######Loading the data########## >data=read.table("c:/20488F.txt", header=T) > xy=data[,c("X","Y")] #### Relocation coordinates in UTMs > id=data[,c("ID")] -1- >######Create the Minimum Convex Polygon######## > cp=mcp(xy, id) > #####Plot the MCP######### > opar=par(mar=c(0,0,0,0)) > area.plot(cp) >######Plot the relocations####### > points(xy, pch=16, col=id) > par(opar) >######Computation of the home-range size###### > area=mcp.area(xy, id) > plot(area) > area 20488F 20 408.0593 25 455.6455 30 462.9556 35 477.0643 40 559.5436 45 617.2927 50 667.5865 55 735.6050 60 736.6449 65 778.2089 70 783.6998 75 889.5542 80 1000.0232 85 1072.8038 90 1325.9270 95 1443.3882 100 1541.7186 -2- >#####Create the Kernel Home Range ad hoc######## >ud=kernelUD(xy, id) >image(ud) ####Creates contours >udvol=getvolumeUD(ud) >image(udvol) ####Creates contours with estimated ranges of probability >ver=getverticeshr(ud, 95) ####Calculates the 95 percent home range >ver50= getverticeshr(ud, 50) ####Calculates the 50 percent home range >plot(ver) >plot(ver50) >udarea=kernel.area(xy, id) 20488F 20 167.3835 25 225.0074 30 293.6072 35 375.9269 40 480.1986 45 600.9343 50 732.6459 55 880.8215 60 1042.7171 65 1215.5886 70 1404.9240 75 1610.7235 80 1841.2188 85 2101.8981 90 2428.4331 95 2938.8157 >plot(udarea) ########Nearest Neighbor Convex Hulls Home Range######### > nn=NNCH(xy, k=c(50:55)) > summary(nn) ##### Prints home range analysis summary -3- >plot(nn, k=53) ##### A graphical exploration ########################Plotting Animal Movements############################### >data=read.table("c:/20508F.txt", header=T) > xy=data[,c("X","Y")] #### Relocation coordinates in UTMs > id=data[,c("ID")] > path=as.ltraj(xy, date, id, typeII=FALSE) > path >plot(path) -4-