The wildlifeDI package facilitates the calculation of indices of dynamic interaction for wildlife telemetry data. There are also functions for more advanced contact analysis. For more information on the methods used within see the documentation but also see:
Long, J.A., Nelson, T.A., Webb, S.L., Gee, K.L. (2014) A critical examination of indices of dynamic interaction for wildlife telemetry studies. Journal of Animal Ecology. 83(5):1216-1233.
You can install the latest (under development version) of wildlifeDI from github with:
The version that can currently be downloaded from CRAN is wildlifeDI v0.4.1:
A small dataset is provided to demonstrate the functionality of the package.
library(wildlifeDI)
data(deer)
deer
#>
#> *********** List of class ltraj ***********
#>
#> Type of the traject: Type II (time recorded)
#> * Time zone unspecified: dates printed in user time zone *
#> Irregular traject. Variable time lag between two locs
#>
#> Characteristics of the bursts:
#> id burst nb.reloc NAs date.begin date.end
#> 1 37 37 551 0 2005-03-07 19:03:00 2005-03-13 18:47:00
#> 2 38 38 567 0 2005-03-07 19:02:00 2005-03-13 18:47:00
#>
#>
#> infolocs provided. The following variables are available:
#> [1] "pkey"
Different tests of dynamic interaction can be straightforwardly computed. Most require a distance threshold (dc) to define when two animals are proximal. Similarly, most methods require a time threshold (tc) to define when two fixes are simultaneous.
Here we use dc = 50 and tc = 8 mins (8*60).
A few examples are given below:
dc <- 50
tc <- 8*60
#Proximity Analysis
Prox(deer[1],deer[2])
#> [1] 0.4293948
#Doncaster's test
Don(deer[1],deer[2],tc=tc,dc=dc,plot=F)
#> $conTable
#> below.crit above.crit Totals
#> Paired 226 320 546
#> Non-Paired 3925 293637 297570
#> Totals 4159 293957 298116
#>
#> $p.value
#> [1] 0
#Kenward's Coefficient of Sociality
Cs(deer[1],deer[2],tc=tc)
#> $Do
#> [1] 422.3163
#>
#> $De
#> [1] 873.9819
#>
#> $Cs
#> [1] 0.3484272
#>
#> $p.Attract
#> [1] 7.403068e-53
#>
#> $p.Avoid
#> [1] 1
#Shirabe's correlation coefficient
Cr(deer[1],deer[2],tc=tc)
#> [1] 0.3706059
#Dynamic Interaction index
DI(deer[1],deer[2],tc=tc)
#> $DI
#> [1] 0.1510688
#>
#> $DI.theta
#> [1] 0.1735282
#>
#> $DI.d
#> [1] 0.5910381
#>
#> $P.positive
#> [1] 0.001834862
#>
#> $P.negative
#> [1] 1
#Benhamou's interaction statistic
IAB(deer[1],deer[2],tc=tc,dc=dc)
#> $IAB.obs
#> [1] 0.3986007
#>
#> $IAB.exp
#> [1] 0.01694352
#>
#> $P.attract
#> [1] 0.001831502
#>
#> $P.avoid
#> [1] 1
For much more detailed information on the package please see the documentation and the vignette.
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