seal: Data for one foraging trip by a male northern fur seal (NFS).

In ctmcmove: Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains

Description

seal$locs contains xyt locations for argos fixes on the seal's location in the "datetime", "latitude", and "longitude" columns.

seal$cov.df contains a data.frame of spatial covariate values for sea surface temperature (sst), chlorophyll A levels (chA) and net primary production (npp).

seal$sim.obj is a fitted "sim.obj" obtained using the "crawl" package in R.

Usage

data("seal")

Format

The format is: List of 10 $ tripID : num 156 $ locs :'data.frame': 163 obs. of 6 variables: ..$ datetime : num [1:163] 36741 36741 36741 36742 36742 ... ..$ latitude : num [1:163] 57.2 57.3 57.3 57.2 57.5 ... ..$ longitude : num [1:163] 190 190 190 190 190 ... ..$ landseamig: int [1:163] 0 1 1 1 1 1 1 1 1 1 ... ..$ lqadjust : int [1:163] 5 1 0 -2 -2 1 -2 -2 -2 -2 ... ..$ lq : Factor w/ 8 levels "0","1","2","3",..: 5 2 1 7 7 2 7 7 7 7 ... $ year : int 2000 $ rookery : Factor w/ 2 levels "Reef","Vostochni": 2 $ sex : Factor w/ 2 levels "female","male": 2 $ start.date: Factor w/ 131 levels "10/10/1999","10/11/1999",..: 80 $ end.date : Factor w/ 131 levels "10/10/1999","10/11/1999",..: 66 $ cov.df :List of 4 ..$ X :'data.frame': 10000 obs. of 5 variables: .. ..$ x : num [1:10000] 184 184 184 184 184 ... .. ..$ y : num [1:10000] 56.7 56.7 56.7 56.7 56.7 ... .. ..$ chA: num [1:10000] 1.19 0.924 0.744 0.709 0.733 ... .. ..$ sst: num [1:10000] 9.07 10.35 10.27 10.43 9.98 ... .. ..$ pro: num [1:10000] 853 821 823 849 886 ... ..$ X.grad.x: num [1:10000, 1:5] 0.0729 0.0729 0.0729 0.0729 0.0729 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : NULL .. .. ..$ : chr [1:5] "x" "y" "chA" "sst" ... ..$ X.grad.y: num [1:10000, 1:5] 0 0 0 0 0 0 0 0 0 0 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : NULL .. .. ..$ : chr [1:5] "x" "y" "chA" "sst" ... ..$ xy : num [1:10000, 1:2] 184 184 184 184 184 ... $ sim.obj :List of 31 ..$ x : num [1:5420] 190 9999 9999 9999 9999 ... ..$ y : num [1:5420] 57.2 9999 9999 9999 9999 ... ..$ loctype : num [1:5420] 0 1 1 1 1 1 1 1 1 1 ... ..$ P1.y : num [1:2, 1:2] 1 0 0 1 ..$ P1.x : num [1:2, 1:2] 1 0 0 1 ..$ a1.x : num [1:2] 190 0 ..$ a1.y : num [1:2] 57.2 0 ..$ n.errX : int 2 ..$ n.errY : int 2 ..$ n.mov : int 1 ..$ delta : num [1:5420] 0.00417 0.00417 0.00417 0.00417 0.00417 ... ..$ lonAdj : num [1:5420] 0.545 0.545 0.545 0.545 0.545 ... ..$ driftMod : logi FALSE ..$ stopMod : logi FALSE ..$ stop.mf : NULL ..$ err.mfX : num [1:5420, 1:2] 1 1 1 1 1 1 1 1 1 1 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:5420] "1" "2" "3" "4" ... .. .. ..$ : chr [1:2] "(Intercept)" "errX" ..$ err.mfY : num [1:5420, 1:2] 1 1 1 1 1 1 1 1 1 1 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:5420] "1" "2" "3" "4" ... .. .. ..$ : chr [1:2] "(Intercept)" "errY" ..$ mov.mf : num [1:5420, 1] 1 1 1 1 1 1 1 1 1 1 ... ..$ fixPar : logi [1:6] NA NA NA NA NA NA ..$ Cmat : num [1:6, 1:6] 0.116 -0.04442 0.0079 -0.00218 -0.00964 ... ..$ predType : chr [1:5420] "p" "p" "p" "p" ... ..$ par : num [1:6] -4.8167 0.5685 -6.9152 1.2077 0.0307 ... ..$ nms : chr [1:6] "ln tau.x (Intercept)" "ln tau.x errX" "ln tau.y (Intercept)" "ln tau.y errY" ... ..$ N : int 5420 ..$ lower : num -Inf ..$ upper : num Inf ..$ loglik : num 665 ..$ datetime : num [1:5420] 36741 36741 36741 36741 36741 ... ..$ coord : chr [1:2] "longitude" "latitude" ..$ Time.name : chr "datetime" ..$ thetaSampList:List of 1 .. ..$ : num [1:100, 1:9] 0.00841 0.01441 0.02038 0.01096 0.00801 ... .. .. ..- attr(*, "dimnames")=List of 2 .. .. .. ..$ : NULL .. .. .. ..$ : chr [1:9] "w" "lik" "prop.lik" "ln tau.x (Intercept)" ... .. .. ..- attr(*, "effSamp")= num 87 .. .. ..- attr(*, "method")= chr "IS" ..- attr(*, "class")= chr "crwSimulator" $ pred.times: num [1:5258] 36741 36741 36741 36741 36741 ...

Details

CRAWL sim.obj and xyt locations from ARGOS telemetry data for one NFS near the Pribilof islands.

Source

Hanks, E.; Hooten, M.; Johnson, D. & Sterling, J. Velocity-Based Movement Modeling for Individual and Population Level Inference PLoS ONE, Public Library of Science, 2011, 6, e22795

Examples

## For example code, do
##
## > help(ctmcMove)

Example output

Loading required package: raster
Loading required package: sp
Loading required package: Matrix
Loading required package: fda
Loading required package: splines

Attaching package: 'fda'

The following object is masked from 'package:graphics':

    matplot

Loading required package: gdistance
Loading required package: igraph

Attaching package: 'igraph'

The following object is masked from 'package:raster':

    union

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union


Attaching package: 'gdistance'

The following object is masked from 'package:igraph':

    normalize

ctmcmove documentation built on May 2, 2019, 5:25 p.m.