Movement Coordination Index (MCI)

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Description

Computes the Movement Coordination Index as described in Mueller, T., et al. (2011).

Usage

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mci(x)

Arguments

x

data frame of synchronized relocations of a set of individuals. The data frame must containing the following columns:

syncID: numeric (integer), ID marking the synchronization event. For each synchronization event every individual must have a record. Therefore each ID must appear as often as every other ID (e.g. not c(1,1,1,2,2,3,3,3) but c(1,1,1,2,2,2,3,3,3)).

utm.easting: numeric, planar x coordinate. Although the name indicates UTM coordinates other planar coordinate systems are also allowed.

utm.northing: analogue to utm.easting

(Further columns are allowed, but will be ignored. Usually a column naming the individual is present in the data frame.)

Such a data frame is returned by the function syncSubsample in package SyncMove (<output>$data[[i]]) with the argument ‘completeSyncsOnly’ set to TRUE.

Value

Returns a numeric vector of MCI values, one for each pair of subsequent synchronization events.

Author(s)

Martin Rimmler (maintainer, martin.rimmler[AT]gmail.com), Thomas Mueller

References

Mueller, T., et al. (2011) How landscape dynamics link individual- to population-level movement patterns: a multispecies comparison of ungulate relocation data, Global Ecology and Biogeography, 20, pages 683–694.

Examples

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    # load example data
    data(gazelleRelocations) 

    # create input data frame
    syncRelocs <- syncSubsample(x = gazelleRelocations,
                                startSearch = "2007-09-05 00:00:00",
                                syncIntervalSecs = 3600*24*16,
                                syncAccuracySecs = 3600*24) 

    # calculate MCI
    mci(syncRelocs$data[[1]])