I have data containing locations of 100+ pheasants during 3 seasons. I am looking to estimate kernel home ranges for each of the seasons for each individual. I run the kernelUD() function with no errors or warnings, but am receiving an error message when I attempt to use the getverticeshr() and kernel.area() functions to extract 95% polygons and area estimates from the kernel UD's.
Here is the structure of the input data set: Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 2376 obs. of 1 variable: .. ..$ ID: Factor w/ 122 levels "150.002_2013_KOR",..: 1 1 1 1 1 1 2 2 2 2 ... ..@ coords.nrs : num(0) ..@ coords : num [1:2376, 1:2] 347887 347862 347948 347964 348200 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : NULL .. .. ..$ : chr [1:2] "X_Estimate" "Y_Estimate" ..@ bbox : num [1:2, 1:2] 315869 4442294 349590 4472129 .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:2] "X_Estimate" "Y_Estimate" .. .. ..$ : chr [1:2] "min" "max" ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slots .. .. ..@ projargs: chr NA The following code works without errors or warnings for my "pre" season data: kud.pre<-kernelUD(pre.hr.id[,1],h="href",extent=1) pre.hr.poly<-getverticeshr(kud.pre, percent=95) pre.kud.area<-kernel.area(kud.pre,percent=95) However, when I repeat my other 2 seasons, kernelUD() runs with no errors or warnings: kud.early<-kernelUD(early.hr.id[,1],h="href",extent=1) but I get the following error when running the getverticeshr() function: early.hr.poly<-getverticeshr(kud.early, percent=95) Error in getverticeshr.estUD(x[[i]], percent, ida = names(x)[i], unin, : The grid is too small to allow the estimation of home-range. You should rerun kernelUD with a larger extent parameter I have adjusted the extent parameter as requested, using values of 0.5,1,5,10,25,100 and all produce the same error. I am able to generate mcp's using the same data without a problem and like I said, kernelUD() works with no errors or warnings for all 3 seasons and I am able to see each UD when I look at the image. What I find particularly strange is that I am able to run kernel.area() and even with warnings that say: 1: In kernel.area(j, percent, unin, unout) : The grid is too small to allow the estimation of home-range for the following value of percent: 95. You should rerun kernelUD with a larger extent parameter I still get a data frame with area values for each individual. It seems as if an area is estimated regardless of the error warning of small extent size. Has anyone experienced a similar issue or have a suggestion as to how I should proceed? Thanks, Lindsey -- View this message in context: http://r-sig-ecology.471788.n2.nabble.com/problem-with-kernel-UD-estimation-using-adehabitatHR-tp7578930.html Sent from the r-sig-ecology mailing list archive at Nabble.com. _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
