Package 'move'

Description

move is a package that contains functions to access movement data stored on Movebank as well as tools to visualize and statistically analyse animal movement data. Move addresses ecological questions regarding movement.

Details

The package implements classes for movement data and supports

• Creation of Move objects (see Move-class) representing animals and their track

• Calculation of utilization distributions using the dynamic Brownian bridge Movement Model

• Plotting tracks, utilization distributions and contours

• Access to raster, n.col, projection and coordinates

• Different CRS projection methods such as longlat or aeqd

I. Creating Move objects

Move objects can be created from files with the function:

move To create an object containing one animal track
moveStack To create an object containing multiple move objects
getMovebankData To create a Move or a MoveStack object with data from Movebank

II. Calculation of the utilization distribution

The dynamic Brownian Bridge Movement Model calculates the occurrences distribution of a given track

III. Accessing values

IV. Plotting data

The track or the utilization distribution can be plotted with the following functions:

Author(s)

Bart Kranstauber, Marco Smolla, Anne Scharf

Maintainer: Bart Kranstauber, Marco Smolla, Anne Scharf

References

move on CRAN

Description

The .UD, .UDStack and .UDBurstStack class represent a raster of a simple abstraction of the utilization distribution (UD) where all probabilities necessarily sum to one. A .UDStack object can be obtained with the function UDStack.

Slots

crs

part of the Raster-class

data

part of the Raster-class

extent

part of the Raster-class

file

part of the Raster-class

history

part of the Raster-class

names

part of the Raster-class

legend

part of the Raster-class

method

stores the method that was used to calculate the utilization distribution (UD), e.g. dynamic Brownian Bridge

ncols

part of the Raster-class

nrows

part of the Raster-class

rotated

part of the Raster-class

rotation

part of the Raster-class

title

part of the Raster-class

z

part of the Raster-class

Methods

contour

signature(object = ".UD"): adds a contour line to a plot, also for .UDStack

emd

signature(object = ".UD"): quantifies similarity between utilization distributions, also for .UDStack

getVolumeUD

signature(object = ".UD"): modifies the .UD/.UDStack raster

outerProbability

signature(object = ".UD"): calculates the animal occurrence probabilities at the border of the raster (only for .UD class)

plot

signature(object = ".UD"): plots the raster from a .UD/.UDStack object with re-size insensitive proportions

raster2contour

signature(object = ".UD"): converts a raster to contour lines, also for .UDStack

show

signature(object = ".UD"): displays summary the .UD/.UDStack object

summary

signature(object = ".UD"): summarizes the information of the raster from a .UD/.UDStack object

subset

signature(object = ".UD"): subsets the .UD/.UDStack object

split

signature(object = ".UDStack"): splits a .UDStack into a list of .UD objects

Note

A DBBMM and dynBGB object contains a .UD.
A DBBMMStack contains a .UDStack.
A DBBMMBurstStack contains a .UDBurstStack.
These objects can be used to program against.

Author(s)

Bart Kranstauber & Anne Scharf

Description

The .unUsedRecords and .unUsedRecordsStack object stores unused records in Move, MoveBurst and MoveStack objects and can be obtained with the function unUsedRecords.

Slots

trackIdUnUsedRecords

Object of class "factor": vector that indicates, which data, coordinates and timestamps of the unused records belong to each individual in a .unUsedRecordsStack object

timestampsUnUsedRecords

Object of class "POSIXct": timestamps associated to the unused records.

sensorUnUsedRecords

Object of class "factor": sensors used to record the unused records

dataUnUsedRecords

Object of class "data.frame": data associated to the unused records

Methods

Methods defined with class "MoveStack" in the signature:

as.data.frame

signature(object = ".unUsedRecords"): extracts the spatial data frame

sensor

signature(object = ".unUsedRecords"): extracts the sensor(s) used to record the data

timestamps

signature(object = ".unUsedRecords"): extracts returns or sets the timestamps

trackId

signature(object = ".unUsedRecordsStack"): returning the Id of the individual per data point

Author(s)

Marco Smolla & Anne Scharf

Description

This function calculates the heading/azimuth/direction of movement of each segment between consecutive locations of a track.

Usage

## S4 method for signature '.MoveTrackSingle'
angle(x)
  ## S4 method for signature '.MoveTrackStack'
angle(x)

Arguments

Details

Other terms for this measurment are azimuth or direction of travel/movement. The angles are relative to the North pole. The headings are calculated using the functions bearing of the geosphere package.

Value

Angles in degrees (between -180 and 180). North is represented by 0.

If a move object is provided, a numeric vector one element shorter than the number of locations is obtained.
If a moveStack object is provided, a list with one element per individual containing a numeric vector one element shorter than the number of locations is obtained.

Author(s)

Marco Smolla & Anne Scharf

See Also

turnAngleGc

Examples

## angles from a Move object 
data(leroy)
head(angle(leroy))
# to add this information to the move object, a "NA" has to be assigened
# e.g. to the last location (it also could be assigend to the first location).
leroy$angles <- c(angle(leroy), NA)

## angles from a MoveStack object
data(fishers)
str(angle(fishers))
# to add this information to the moveStack object, a "NA" has to be assigened
# e.g. to the last location of each individual
fishers$angles <- unlist(lapply(angle(fishers), c, NA))

Description

Function to create a data.frame of a Move, dBMvariance, dBGBvariance, .unUsedRecords object.

Usage

## S4 method for signature 'Move'
as.data.frame(x)
  ## S4 method for signature 'MoveStack'
as.data.frame(x)
  ## S4 method for signature 'MoveBurst'
as.data.frame(x)
  
  ## S4 method for signature 'dBMvariance'
as.data.frame(x)
 
  ## S4 method for signature '.unUsedRecords'
as.data.frame(x)
  ## S4 method for signature '.unUsedRecordsStack'
as.data.frame(x)

Arguments

Details

Depending on the class of the object provided, the obtained data.frame contains the information contained in the slots:

• if class move: "timestamps", "idData", "sensor", "data", "coords".

• if class moveStack: "timestamps", "idData", "sensor", "data", "coords", "trackId".

• if class moveBurst: "timestamps", "idData", "sensor", "data", "coords", "burstId".

• if class dBMvariance: "timestamps", "sensor", "data", "coords", "window.size", "margin", "means", "in.windows", "interest".

• if class dBMvarianceStack: "timestamps", "sensor", "data", "coords", "window.size", "margin", "means", "in.windows", "interest","trackId".

• if class dBMvarianceBurst: "timestamps", "sensor", "data", "coords", "window.size", "margin", "means", "in.windows", "interest", "burstId".

• if class dBGBvariance: "timestamps", "sensor", "data", "coords", "paraSd", "orthSd", "margin", "windowSize".

• if class .unUsedRecords: "dataUnUsedRecords", "timestampsUnUsedRecords", "sensorUnUsedRecords".

• if class .unUsedRecordsStack: "trackIdUnUsedRecords", "dataUnUsedRecords", "timestampsUnUsedRecords", "sensorUnUsedRecords".

Value

'data.frame'

Author(s)

Marco Smolla & Anne Scharf

Examples

## obtain data.frame from move object
data(leroy)
head(as.data.frame(leroy))

## obtain data.frame from moveStack object
data(fishers)
head(as.data.frame(fishers))

## obtain data.frame from .unUsedRecordsStack object
unUsedFishers <- unUsedRecords(fishers)
head(as.data.frame(unUsedFishers))

Description

This function uses a Move or MoveStack object to calculate the utilization distribution (UD) of the given track. It uses the dynamic Brownian Bridge Movement Model (dBBMM) to do so, having the advantage over the other Brownian Bridge Movement Model that changes in behavior are accounted for. It does so by using the behavioral change point analysis in a sliding window. For details see 'References'.

Usage

brownian.bridge.dyn(object, raster=1, dimSize=10, location.error, 
                    margin=11, window.size=31, ext=.3, bbox=NA,...)

Arguments

Details

There are four ways to launch the brownian.bridge.dyn function:

1. Use a raster:
A RasterLayer object is set for the raster argument which is then used to calculate the UD.
(needed arguments: object, raster(=RasterLayer), location.error, margin, window.size; optional arguments: time.step, verbose, burstType)

2. Set the cell size
To set the cell size, set a numeric value for the raster argument without providing dimSize. The numeric raster argument is used as the cell sizes of the raster.
(needed arguments: object, raster(=numeric), location.error, margin, window.size; optional arguments: ext, bbox, time.step, verbose, burstType)

3. Set the number of cells (col/row)
To set the number of cells along the largest dimension a numeric dimSize argument can be set.
(needed arguments: object, dimSize, location.error, margin, window.size; optional arguments: ext, bbox, time.step, verbose, burstType)

4. Using default raster
When there are no values set, the default raster value is used to calculate and create a RasterLayer object, which is returned to the same function. Note: depending on the size of the area of interest, the default cell size value can result in a large number of cells which may take a very long time to calculate!

The function prints an estimate of the size of the computational task ahead. This can give an indication of how long the computation is going to take. It should scale roughly linearly with the duration of the computations although changes in the setup mean the computational complexity still is calculated base on the extent but this is not informative any more on the computation time. It is only useful as a rough indication of calculation duration.

time.step. The default value is the shortest time interval divided by 15. This means, if there is a location recorded e.g. every 30 mins, the function divides each segment into 2 mins chunks upon which it does the calculation. If for some reason there is one time interval of 15 secs in the track, each segment of the track will be divided into 1secs chunks, increasing the calculation time immensely. Before calculating the DBBMM, use e.g. min(timeLag(x=myMoveObject, units="mins")) to check which is the duration of the shortest time interval of the track. If the track contains time intervals much shorter than the scheduled on the tag, set the time.step e.g. to the scheduled time interval at which the tag was set, divided by 15.

Value

'DBBMM' object, if move or dBMvariance object is provided
'DBBMMStack' object, if moveStack or dBMvarianceStack object is provided
'DBBMMBurstStack' object, if moveBurst object is provided

Note

Note that the first few and last few segments of the trajectory are omitted in the calculation of the UD since a lower number of estimates for the Brownian motion variance are obtained for those segments.

Thanks to Ryan Nielson for making the BBMM package that served as an example for early versions of this code.

Author(s)

Bart Kranstauber, Marco Smolla & Anne Scharf

References

Kranstauber, B., Kays, R., LaPoint, S. D., Wikelski, M. and Safi, K. (2012), A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement. Journal of Animal Ecology. doi: 10.1111/j.1365-2656.2012.01955.x

See Also

brownian.motion.variance.dyn, getMotionVariance, getVolumeUD, contour, outerProbability, raster, raster2contour, dynBGB, dynBGBvariance

Examples

## create a move object
data(leroy)
## change projection method to aeqd and center the coordinate system to the track
data2 <- spTransform(leroy[30:90,], CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)

## create a DBBMM object
dbbmm <- brownian.bridge.dyn(object=data2, location.error=12, dimSize=125, ext=1.2, 
			     time.step=2, margin=15)

plot(dbbmm)

Description

A function to calculate the dynamic brownian motion variance for a movement track. It can be also used by advanced programmers to program against.

Usage

## S4 method for signature '.MoveTrackSingle,numeric,numeric,numeric'
brownian.motion.variance.dyn(object, location.error, window.size, margin)

Arguments

Value

'dBMvariance' object, if move object is provided
'dBMvarianceStack' object, if moveStack object is provided
'dBMvarianceBurst' object, if moveBurst object is provided

Author(s)

Bart Kranstauber & Anne Scharf

References

Kranstauber, B., Kays, R., LaPoint, S. D., Wikelski, M. and Safi, K. (2012), A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement. Journal of Animal Ecology. doi: 10.1111/j.1365-2656.2012.01955.x

See Also

brownian.bridge.dyn, dynBGBvariance

Examples

data(leroy)
data2 <- spTransform(leroy[1:80,], CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)
err<-rep(23.5,n.locs(data2))
dBMvar <- brownian.motion.variance.dyn(data2, location.error=err, margin=13, window.siz=31)
dBMvar

Description

Bursting a track by a specified variable

Usage

## S4 method for signature 'Move,factor'
burst(x, f, ...)

Arguments

Details

The burst function bursts (divides) a track into segments that are specified by the burstIDs (e.g. behavioral annotations). It allows to investigate different parts of a track according to supplied variables like day and night, movement and rest, and so on.

Value

a 'moveBurst' object

Author(s)

Marco Smolla

See Also

burstId, split, plotBursts

Examples

data(leroy)
behav <- c(rep(c("B1","B2","B3","B2"),each=200), rep("B1", 118))
testb <- burst(x=leroy, f=behav)
plot(testb, type="l")

Description

Obtain or set the ids of the behavioral categorization per segment of a MoveBurst object.

Usage

## S4 method for signature 'MoveBurst'
burstId(x)
  ## S4 replacement method for signature '.MoveTrackSingleBurst,factor'
burstId(x) <- value

Arguments

Value

Returns a factor indicating the category of each segment.

Author(s)

Bart Kranstauber & Anne Scharf

See Also

burst

Examples

data(leroy)
burstTrack <- burst(x=leroy,f=months(timestamps(leroy))[-1])
burstId(burstTrack)

Description

The citations method returns or sets the citation of a track from a Move or MoveStack object.

Usage

## S4 method for signature '.MoveGeneral'
citations(obj)
  ## S4 replacement method for signature '.MoveGeneral'
citations(obj) <- value

Arguments

Value

character string of the citation

Author(s)

Marco Smolla & Anne Scharf

See Also

licenseTerms

Examples

data(leroy)
  citations(leroy) #get the citation from a Move object
  citations(leroy) <- "No paper available" #change the citation and set it for a Move object
 
  data(fishers)
  citations(fishers) #get the citation from a MoveStack object
  citations(fishers) <- "Nothing to cite" #change the citation and set it for a MoveStack object

Description

Contour plot of a RasterLayer from a DBBMM or dynBGB object.

Usage

## S4 method for signature '.UD'
contour(x, ...)
  ## S4 method for signature '.UDStack'
contour(x, ...)

Arguments

Details

The contour function creates a shape of the area in which the animal can be found by a certain probability (i.e. the 90% contour describes the area in which the animal can be found with the 90% probability).
One or several probabilities can be set with levels (numeric or vector of values between 0 and 1). If no value is set all contour lines are returned.
You can also use nlevel to set a number of fixed distance levels.
To change parameters of the contour or line plotting use the usual parameters of the plot function (like lwd, lty, and so on).
You can also add the contour lines to a plot of a DBBMM, dynBGB or .UD object by adding add = TRUE.

Author(s)

Marco Smolla & Anne Scharf

Examples

data(leroydbbmm)
## to add a 50% and 95% contour to a plot from DBBMM object dbbmm
plot(leroydbbmm)
contour(leroydbbmm, levels=c(.5,.95), add=TRUE)
contour(leroydbbmm, levels=c(.5,.95))

Description

The coordinates method extracts the coordinates of a track.

Usage

## S4 method for signature 'Move'
coordinates(obj,...)

Arguments

Value

Returns a matrix with the coordinates of the track

Author(s)

Marco Smolla & Anne Scharf

Examples

## create a move object
data(leroy)
## extract the coordinates
head(coordinates(leroy))

Description

This function identifies movement track segments whose attributes suggest corridor use behavior

Usage

## S4 method for signature '.MoveTrackSingle'
corridor(x,speedProp=.75, circProp=.25, minNBsegments = 2, plot=FALSE, ...)
  ## S4 method for signature '.MoveTrackStack'
corridor(x,speedProp=.75, circProp=.25, minNBsegments = 2, plot=FALSE, ...)

Arguments

Details

The corridor function uses the attributes of a movement step (segment) to identify movement steps that exhibit corridor use behavior. For each segment, the speed and the azimuth are calculated and assigned to the segment midpoint.
A circular buffer is created around the midpoint of each segment whose radius is equal to half the segment length. The segment azimuth (180 >= azimuth > -180) is converted into a new unit, the 'pseudo-azimuth' (0 <= 360), removing the directional information.
Subsequent, the circular variance of the pseudo-azimuths of all segment midpoints that fall within the circular buffer is calculated. Low values of the circular variance indicate that the segments are (near) parallel.
Next, it is determined whether a segment's speed is higher than speedProp (by default the upper 25% speeds) and its circular variance is lower than circProp (by default the lower 25% of all variances).
Segment midpoints that meet both of these requirements are considered as a 'corridor' point, all others are considered 'non-corridor' points. Finally, a corridor point is determined to be within a true corridor if within its circular buffer there are more 'corridor' points than 'non-corridor' points. The argument minNBsegments can be used to establish the minimum number of 'corridor' points that each circular buffer needs for the focal segment to be defined as a corridor. It is useful to exclude wrongly (visual inspection) identified corridors with only a few segments by increasing the value of minNBsegments. Note that when increasing the value of minNBsegments, only segments with enough corridor neighbors are classified as corridors and not all segments that visually seem to fit to be classified as corridors. To remove the wrongly classified corridors, a value of 3 or 4 is usually sufficient.

Value

The function returns a moveBurst object or a list of moveBurst objects (if a MoveStack is supplied). The MoveBurst date.frame stores the following information:
- segment midpoint
- speed
- azimuth
- pseudo-azimuth
- circular variance

The object is bursted by the factor that indicates whether the segment belongs to a corridor segment or not, and is specified in the "burstId" slot.

Note

The default values for the speedProp and circProp can be changed by the users discretion using the according argument.

Author(s)

Marco Smolla & Anne Scharf

References

LaPoint, S., Gallery, P., Wikelski, M. and Kays, R. (2013), Animal Behavior, Cost-based Corridor Models, and Real Corridors. Landscape Ecology. doi:10.1007/s10980-013-9910-0.

Examples

if(requireNamespace("circular") ){
## with a move object 
  data(leroy)  
  tmp <- corridor(leroy, plot=TRUE)
  plot(tmp, type="l", col=c("red","black")[c(tmp@burstId,NA)])
  
## with a moveStack object   
  data(fishers)
  stacktmp <- corridor(fishers[c(1:400,sum(n.locs(fishers))-(400:1)),])
  plot(stacktmp[[2]], col=c("red","black")[stacktmp[[2]]@burstId])
  lines(stacktmp[[2]], col=c("red","black")[c(stacktmp[[2]]@burstId,NA)])
}

Description

The DBBMM object is created within the brownian.bridge.dyn function from a Move or dBMvariance object. It contains a dBMvariance object and a raster with probabilities.

Slots

crs

part of the Raster-class

data

part of the Raster-class

DBMvar

Object of class "dBMvariance": includes the window.size, margin, means, in.windows, break.list, and points of interest

ext

the extension factor set by the user

extent

part of the Raster-class

file

part of the Raster-class

history

part of the Raster-class

legend

part of the Raster-class

method

stores the method that was used to calculate the utilization distribution (UD), e.g. dynamic Brownian Bridge

ncols

part of the Raster-class

nrows

part of the Raster-class

rotated

part of the Raster-class

rotation

part of the Raster-class

title

part of the Raster-class

z

part of the Raster-class

Methods

contour

signature(object = "DBBMM"): adds a contour line to a plot

emd

signature(object = "DBBMM"): quantifies similarity between utilization distributions

equalProj

signature(object = "DBBMM"): checks whether all objects of a list are in the same projection

getMotionVariance

signature(object = "DBBMM"): extracts the estimated motion variance

getVolumeUD

signature(object = "DBBMM"): modifies the UD raster

outerProbability

signature(object = "DBBMM"): calculates the animal occurrence probabilities at the border of the raster

plot

signature(object = "DBBMM"): plots the raster from a DBBMM object with re-size insensitive proportions

raster2contour

signature(object = "DBBMM"): converts a raster to contour lines

show

signature(object = "DBBMM"): displays summary the DBBMM object

summary

signature(object = "DBBMM"): summarizes the information of the raster from a DBBMM object

subset

signature(object = "DBBMM"): subsets the DBBMM object

Note

The DBBMM object contains a dBMvariance and a .UD object which can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

The DBBMMBurstStack object is created within the brownian.bridge.dyn function from a MoveBurst or dBMvarianceBurst object. It contains a dBMvarianceBurst object and a raster with probabilities.

Slots

crs

part of the Raster-class

DBMvar

Object of class "dBMvarianceBurst": includes the window.size, margin, means, in.windows, break.list, and points of interest

ext

the extension factor set by the user

extent

part of the Raster-class

filename

part of the Raster-class

layers

part of the Raster-class

method

the method that was used to calculate the utilization distribution, e.g. dynamic Brwonian Bridge

ncols

part of the Raster-class

nrows

part of the Raster-class

rotated

part of the Raster-class

rotation

part of the Raster-class

title

part of the Raster-class

z

part of the Raster-class

Methods

getMotionVariance

signature(object = "DBBMMBurstStack"): extracts the estimated motion variance

plot

signature(object = "DBBMMBurstStack"): plots the raster from a DBBMMBurstStack object with re-size insensitive proportions

show

signature(object = "DBBMMBurstStack"): displays summary the DBBMMBurstStack object

subset

signature(object = "DBBMMBurstStack"): subsets the DBBMMBurstStack object

UDStack

signature(object = "DBBMMBurstStack"): creates UDStack objects

Note

The DBBMMBurstStack object contains a dBMvarianceBurst and a .UDStack object which can be used to program against.

Author(s)

Anne Scharf

Description

The DBBMMStack object is created within the brownian.bridge.dyn function from a MoveStack or dBMvarianceStack object. It contains a dBMvarianceStack object and a raster with probabilities.

Slots

crs

part of the Raster-class

DBMvar

Object of class "dBMvarianceStack": includes the window.size, margin, means, in.windows, break.list, and points of interest

ext

the extension factor set by the user

extent

part of the Raster-class

filename

part of the Raster-class

layers

part of the Raster-class

method

the method that was used to calculate the utilization distribution, e.g. dynamic Brwonian Bridge

ncols

part of the Raster-class

nrows

part of the Raster-class

rotated

part of the Raster-class

rotation

part of the Raster-class

title

part of the Raster-class

z

part of the Raster-class

Methods

contour

signature(object = "DBBMMStack"): adds a contour line to a plot

emd

signature(object = "DBBMMStack"): quantifies similarity between utilization distributions

equalProj

signature(object = "DBBMMStack"): checks whether all objects of a list are in the same projection

getMotionVariance

signature(object = "DBBMMStack"): extracts the estimated motion variance

getVolumeUD

signature(object = "DBBMMStack"): modifies the UD raster

outerProbability

signature(object = "DBBMMStack"): calculates the animal occurrence probabilities at the border of the raster

plot

signature(object = "DBBMMStack"): plots the raster from a DBBMMStack object with re-size insensitive proportions

raster2contour

signature(object = "DBBMMStack"): converts a raster to contour lines

show

signature(object = "DBBMMStack"): displays summary the DBBMMStack object

split

signature(object = "DBBMMStack"): splits a DBBMMStack into a list of DBBMM objects

summary

signature(object = "DBBMMStack"): summarizes the information of the raster from a DBBMMStack object

subset

signature(object = "DBBMMStack"): subsets the DBBMMStack object

Note

The DBBMMStack object contains a dBMvarianceStack and a .UDStack object which can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

The dynBGBvariance object stores the orthogonal and parallel variances calculated by the dynamic Bivariate Gaussian Bridge model, and is created within the dynBGBvariance function from a Move object.

Slots

windowSize

The window size used for dynBGBvariance calculation

margin

The margin used for dynBGB calculation

paraSd

The standard deviation values of the parallel variance values

orthSd

The standard deviation values of the orthogonal variance values

nEstim

The number of windows each location was included in

segInterest

Logical string, FALSE: segments have been omitted in the calculation since a lower number of estimates for variance are obtained for these segments. TRUE: segments included in the calculation

Methods

as.data.frame

signature(object = "dBGBvarianceTmp"): extracts the spatial data frame

coordinates

signature(object = "dBGBvarianceTmp"): extracts the coordinates from the Move object contained in the dBGBvarianceTmp

dynBGB

signature(object = "dBGBvarianceTmp"): calculates the utilization distribution (UD) of the given track using the dynamic Bivariate Gaussian Bridge model

getMotionVariance

signature(object = "dBGBvarianceTmp"): extracts the estimated motion variance

lines

signature(object = "dBGBvarianceTmp"): add lines of the track of the animal to a plot

points

signature(object = "dBGBvarianceTmp"): add points of the track of the animal to a plot

plot

signature(object = "dBGBvarianceTmp"): plots the track of the animal

show

signature(object = "dBGBvarianceTmp"): displays summary the dBGBvarianceTmp object

summary

signature(object = "dBGBvarianceTmp"): summarizes the information of the raster from a dBGBvarianceTmp object

subset

signature(object = "dBGBvarianceTmp"): subsets the dBGBvarianceTmp object

Note

The dynBGBvariance object contains a .MoveTrackSingle and a dBGBvarianceTmp object which can be used to program against.

Author(s)

Bart Kranstauber & Anne Scharf

Description

The dBMvariance object is created within the brownian.motion.variance.dyn function from a Move object.
The dBMvarianceStack object is created when a MoveStack is the input object.
The dBMvarianceBurst object when the input is a MoveBurst object.
These objects contain the motion variance calculated by the dynamic Brownian Bridge Movement Model.

Slots

window.size

The window size used for dbbmm calculation

margin

The margin used for dbbmm calculation

means

The variance values

in.windows

The number of windows each location was included in

interest

Logical string, FALSE: segments have been omitted in the calculation since a lower number of estimates for variance are obtained for these segments. TRUE: segments included in the calculation

break.list

list of the locations of breaks found

Methods

as.data.frame

signature(object = "dBMvarianceTmp"): extracts the spatial data frame

brownian.bridge.dyn

signature(object = "dBMvarianceTmp"): calculates the utilization distribution (UD) of the given track using the dynamic Brownian Bridge Movement Model

coordinates

signature(object = "dBMvarianceTmp"): extracts the coordinates from the Move object contained in the dBMvarianceTmp

getMotionVariance

signature(object = "dBMvarianceTmp"): extracts the estimated motion variance

lines

signature(object = "dBMvarianceTmp"): add lines of the track of the animal to a plot

points

signature(object = "dBMvarianceTmp"): add points of the track of the animal to a plot

plot

signature(object = "dBMvarianceTmp"): plots the track of the animal

show

signature(object = "dBMvarianceTmp"): displays summary the dBMvarianceTmp object

summary

signature(object = "dBMvarianceTmp"): summarizes the information of the raster from a dBMvarianceTmp object

subset

signature(object = "dBMvarianceTmp"): subsets the dBMvarianceTmp object

Note

The dBMvariance object contains a .MoveTrackSingle and a dBMvarianceTmp object.
The dBMvarianceStack object contains a .MoveTrackStack and a dBMvarianceTmp object.
The dBMvarianceBurst object contains a .MoveTrackSingleBurst and a dBMvarianceTmp object.
The class dBMvarianceTmp is mostly an internal class that is made public to make inheritance easier. These objects can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

Calculates the distance between the consecutive locations of a Move or MoveStack object.

Usage

## S4 method for signature '.MoveTrackSingle,missing'
distance(x)
  ## S4 method for signature '.MoveTrackStack,missing'
distance(x)

Arguments

Details

pointDistance is used to calculate the distances.

Value

Distance in map units.
If the projection of the coordinates is long/lat all values are returned in meters, otherwise in the map units of the projection of the move object. For long/lat distance is calculated on a sphere using the ellipsoid, for other projections the calculation is done on a plane using Pythagoras. Check and set the projection of your Move, MoveStack or MoveBurst object using the proj4string() function.

If a move or moveBurst object is provided, a numeric vector one element shorter than the number of locations is obtained.
If a moveStack object is provided, a list with one element per individual containing a numeric vector one element shorter than the number of locations is obtained

Author(s)

Marco Smolla & Anne Scharf

Examples

## distance from a Move object 
data(leroy)
head(distance(leroy))
# to add this information to the move object, a "NA" has to be assigened
# e.g. distance is assigned to the first location of a segment
leroy$distance <- c(distance(leroy), NA)

## distance from a MoveStack object
data(fishers)
str(distance(fishers))
# to add this information to the moveStack object, a "NA" has to be assigened
# e.g. distance is assigned to the first location of a segment
fishers$distance <- unlist(lapply(distance(fishers), c, NA))

Description

This file contains a data frame with fictional tracking data of two individuals, including duplicated timestamps. These data are used in the example of the function getDuplicatedTimestamps.

Examples

data(duplicatedDataExample)

Description

This function creates a utilization distribution according to the Bivariate Gaussian Bridge model.

Usage

## S4 method for signature 'dBGBvariance,RasterLayer,numeric'
dynBGB(move, raster, locErr, timeStep, ...)
## S4 method for signature '.MoveTrackSingle,RasterLayer,numeric'
dynBGB(move, raster, locErr, margin, windowSize, ...)
## S4 method for signature '.MoveTrackSingle,numeric,ANY'
dynBGB(move, raster, locErr, ext, ...)
## S4 method for signature '.MoveTrackSingle,missing,ANY'
dynBGB(move, raster, locErr, dimSize, ext, ...)

Arguments

Details

There are three ways to launch the dynBGB function:

1. Use a raster:
A RasterLayer object is set for the raster argument which is then used to calculate the UD.
(needed arguments: move, raster(=RasterLayer), locErr, margin, windowSize; optional arguments: timeStep)

2. Set the cell size
To set the cell size, set a numeric value for the raster argument which is used as the cell sizes of the raster.
(needed arguments: move, raster(=numeric), locErr, margin, windowSize, ext; optional arguments: timeStep)

3. Set the number of cells (col/row)
To set the number of cells along the largest dimension a numeric dimSize argument can be set.
(needed arguments: move, dimSize, locErr, margin, windowSize, ext; optional arguments: timeStep)

timeStep. The default value is the shortest time interval divided by 20.1. This means, if there is a location recorded e.g. every 40 mins, the function divides each segment into 1.99 mins chunks upon which it does the calculation. If for some reason there is one time interval of 20 secs in the track, each segment of the track will be divided into 1secs chunks, increasing the calculation time immensely. Before calculating the DBBMM, use e.g. min(timeLag(x=myMoveObject, units="mins")) to check which is the duration of the shortest time interval of the track. If the track contains time intervals much shorter than the scheduled on the tag, set the timeStep e.g. to the scheduled time interval at which the tag was set, divided by 20.1.

Value

It returns an object of the class dynBGB-class.

Author(s)

Bart Kranstauber & Anne Scharf

References

Kranstauber, B., Safi, K., Bartumeus, F.. (2014), Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models. Movement Ecology 2:5. doi:10.1186/2051-3933-2-5.

See Also

dynBGBvariance, getMotionVariance, getVolumeUD, contour, outerProbability, raster, raster2contour, brownian.bridge.dyn, brownian.motion.variance.dyn

Examples

data(leroy)
leroy <- leroy[230:265,]

## change projection method to aeqd and center the coordinate system to the track
dataAeqd <- spTransform(leroy, CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)

dBGB <- dynBGB(dataAeqd, locErr=9, raster=10, ext=0.5, windowSize=31, margin=15, timeStep=15/20.1)
plot(dBGB, col=hsv(sqrt(1:700/1000)))
lines(dataAeqd)

Description

The dynBGB object is created within the dynBGB function from a Move object. It contains a dBGBvariance object and a raster with probabilities.

Slots

crs

part of the Raster-class

data

part of the Raster-class

var

Object of class "dBGBvariance": includes the windowSize, margin, paraSd,orthSd, nEstim, segInterest

extent

part of the Raster-class

file

part of the Raster-class

history

part of the Raster-class

legend

part of the Raster-class

method

stores the method that was used to calculate the utilization distribution (UD), e.g. dynBGB

ncols

part of the Raster-class

nrows

part of the Raster-class

rotated

part of the Raster-class

rotation

part of the Raster-class

title

part of the Raster-class

z

part of the Raster-class

Methods

contour

signature(object = "dynBGB"): adds a contour line to a plot

equalProj

signature(object = "dynBGB"): checks whether all objects of a list are in the same projection

getMotionVariance

signature(object = "dynBGB"): extracts the estimated motion variance

getVolumeUD

signature(object = "dynBGB"): modifies the UD raster

outerProbability

signature(object = "dynBGB"): calculates the animal occurrence probabilities at the border of the raster

plot

signature(object = "dynBGB"): plots the raster from a dynBGB object with re-size insensitive proportions

raster2contour

signature(object = "dynBGB"): converts a raster to contour lines

show

signature(object = "dynBGB"): displays summary the dynBGB object

summary

signature(object = "dynBGB"): summarizes the information of the raster from a dynBGB object

subset

signature(object = "dynBGB"): subsets the dynBGB object

Note

The dynBGB object contains a dBGBvariance and a .UD object which can be used to program against.

Author(s)

Bart Kranstauber & Anne Scharf

See Also

.UD

Description

A function to calculate the dynamic Bivariate Gaussian Bridge orthogonal and parallel variance for a movement track

Usage

dynBGBvariance(move, locErr, margin, windowSize,...)

Arguments

Details

The function uses windowApply with the BGBvarbreak function in order to implement a dynamic calculation of the variance

Value

a dBGBvariance-class object

Author(s)

Bart Kranstauber & Anne Scharf

References

Kranstauber, B., Safi, K., Bartumeus, F.. (2014), Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models. Movement Ecology 2:5. doi:10.1186/2051-3933-2-5.

See Also

dynBGB, brownian.motion.variance.dyn

Examples

data(leroy)
leroy <- leroy[230:265,]

## change projection method to aeqd and center the coordinate system to the track
dataAeqd <- spTransform(leroy, CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)

dBGBvar <- dynBGBvariance(dataAeqd, locErr=9, windowSize=31, margin=15)
dBGBvar

Description

The earth mover's distance (EMD) quantifies similarity between utilization distributions by calculating the effort it takes to shape one utilization distribution landscape into another

Usage

## S4 method for signature 'SpatialPoints,SpatialPoints'
emd(x,y, gc = FALSE, threshold = NULL,...)
  ## S4 method for signature 'RasterLayer,RasterLayer'
emd(x,y, ...)

Arguments

Details

For easy interpretation of the results the utilization distributions objects compared should represent a probability surface, i.e. the sum of their values is equal to 1. Nevertheless there is also the possibility to provide utilization distributions objects with the same volume, i.e. the sum of their values is equal to the same number. In the later case interpretation of the results is probably less intuitive.

Euclidean distances are suitable for most planar spatial projections, while great circle distances, calculated using the Haversine function, could be used to compare probability distributions stretching over larger geographical distances taking into account the spherical surface of the Earth.

The function can be optimized by omitting locations that have negligible contribution to the utilization density; for example, EMD can be calculated only for the cells within the 99.99% contour of the UD. This will maximally introduce a very small error in the EMD because only small amounts of probability were omitted, but often, given the long tail of most UDs, many cells are omitted, which greatly reduces the complexity. See 'Examples'.

For more details of the method see 'References'.

Value

An matrix of distances of the class 'dist'

Author(s)

Bart Kranstauber & Anne Scharf

References

Kranstauber, B., Smolla, M. and Safi, K. (2017), Similarity in spatial utilization distributions measured by the earth mover's distance. Methods Ecol Evol, 8: 155-160. doi:10.1111/2041-210X.12649

Examples

## with a DBBMMStack object
  data(dbbmmstack)
  ## to optimize the calculation, the cells outside of the 99.99% UD contour 
  # are removed by setting them to zero.
  values(dbbmmstack)[values(getVolumeUD(dbbmmstack))>.999999]<-0
  ## transform each layer to a probability surface (i.e. sum of their values is 1)
  stk<-(dbbmmstack/cellStats(dbbmmstack,sum))
  emd(stk[[1]],stk[[2]])
  emd(stk)
  emd(stk, threshold=10000)
  
## with a SpatiaPointsDataFrame 
  x<-SpatialPointsDataFrame(cbind(c(1:3,5),2), data=data.frame(rep(.25,4)))
  y<-SpatialPointsDataFrame(coordinates(x), data.frame(c(0,.5,.5,0)))
  emd(x,y)
  emd(x,y,threshold=.1)

## with a DBBMMBurstStack object, to compare the utilization 
# distributions of e.g. different behaviors
  data(leroy)
  leroyB <- burst(x=leroy,f=c(rep(c("Behav.1","Behav.2"),each=400),rep("Behav.1", 118)))
  leroyBp <- spTransform(leroyB, CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)
  leroyBdbb <- brownian.bridge.dyn(object=leroyBp[750:850], location.error=12, raster=600, 
                                   ext=.45, time.step=15/15, margin=15)
  
  ## transform the DBBMMBurstStack into a UDStack
  leoryBud <- UDStack(leroyBdbb)
  ## to optimize the calculation, the cells outside of the 99.99% UD contour 
  # are removed by setting them to zero.
  values(leoryBud)[values(getVolumeUD(leoryBud))>.999999]<-0
  ## transform each layer to a probability surface (i.e. sum of their values is 1)
  stk2<-(leoryBud/cellStats(leoryBud,sum))
  emd(stk2)

Description

Checks whether all objects of a list are in the same projection.

Usage

## S4 method for signature 'list'
equalProj(x)

Arguments

Details

equalProj checks for equal projections using the function of identicalCRS from the package sp. It returns TRUE if none of the objects have a proj4string.

Value

TRUE or FALSE
It returns TRUE if none of the objects have a proj4string.

Author(s)

Bart Kranstauber & Anne Scharf

Examples

data(fishers)
ricky<-fishers[['Ricky.T']]
data(leroy)
data(leroydbbmm)

equalProj(list(leroydbbmm,leroydbbmm))
equalProj(list(leroy,leroydbbmm))
equalProj(list(leroy,ricky))

Description

An MoveStack consisting of two animals, Leroy and Ricky.T

Usage

data(fishers)

Format

An object of the class MoveStack

Source

https://www.datarepository.movebank.org/handle/10255/move.330

References

LaPoint, Scott, Paul Gallery, Martin Wikelski, and Roland Kays (2013) Animal Behavior, Cost-Based Corridor Models, and Real Corridors. Landscape Ecology 28, 8: 1615-1630. doi:10.1007/s10980-013-9910-0.

Examples

data(fishers)

Description

Download data from the Movebank Data Repository via DOI

Usage

getDataRepositoryData(x, ...)

Arguments

Details

This function downloads data stored in the Movebank Data Repository via the DOI. The output is MoveStack object containing the location data from all available sensors in the study. The non-location senor data are stored in the UnUsedRecords slots. Datasets without location data are excluded.

If duplicated timestamps are present in the data, the first one is chosen by default. To use a more informed approach you can download the data of interest from the Movebank Data Repository, read it in with read.csv and use the function getDuplicatedTimestamps to located the duplicated timestamps and then decide which one to keep. And then use the function move to create a Move or MoveStack object from the cleaned .csv file.

Value

move or moveStack object

Note

Visit the dataset's repository page at http://dx.doi.org/<doi> for citations and a readme that might contain additional details needed to understand the data. If analyzing these published datasets, always consult the related papers and cite the paper and dataset. If preparing analysis for publication, also contact the data owner if possible for their contribution.

Author(s)

Anne Scharf

See Also

getMovebankData, getMovebankNonLocationData, getMovebank, move

Examples

## Not run: 
getDataRepositoryData("doi:10.5441/001/1.2k536j54")

## End(Not run)

Description

Identifies all pairs of duplicated timestamps within an individual and sensor type from data downloaded from Movebank or own data.

Usage

## S4 method for signature 'character'
getDuplicatedTimestamps(x, ..., onlyVisible = TRUE)
 
  ## S4 method for signature 'factor'
getDuplicatedTimestamps(x, timestamps, sensorType, visible=NULL, ...)

Arguments

Details

If own data (non-Movebank) are used, the vectors specified in "x", "timestamps" and optionally "visible" have to have the same length.

Value

This function returns a list. The name of the list elements contains the individual's name, the timestamp that is duplicated and the sensor type (if provided). Each list element contains a vector with the corresponding row numbers where the duplicated timestamps are located in the table. If no duplicated timestamps are found NULL is returned.

Author(s)

Anne Scharf

Examples

data(duplicatedDataExample)
getDuplicatedTimestamps(x=as.factor(duplicatedDataExample$individual.id), 
                        timestamps=as.POSIXct(duplicatedDataExample$timestamps, 
					      format="%Y-%m-%d %H:%M:%S", tz="UTC"),
                        sensorType=duplicatedDataExample$sensor.type)

filePath<-system.file("extdata","leroy.csv.gz",package="move")
getDuplicatedTimestamps(filePath)

Description

This function returns the estimated motion variance calculated by the dynamic Bivariate Gaussian Bridges or dynamic Brownian Bridges

Usage

getMotionVariance(x,...)

Arguments

Value

- a numeric vector of variances if a DBBMM, DBBMMBurstStack, dBMvariance or dBMvarianceBurst object is provided
- a list of variances per individual if a DBBMMStack or dBMvarianceStack object is provided
- a matrix of the orthogonal and parallel variances if dynBGB or dBGBvariance object is provided

Author(s)

Bart Kranstauber & Anne Scharf

See Also

brownian.bridge.dyn, dynBGB, brownian.motion.variance.dyn, dynBGBvariance, dBMvariance-class, dBGBvariance-class

Examples

data(leroydbbmm)
data(dbbmmstack)
getMotionVariance(leroydbbmm)[1:50] ## with a DBBMM object
str(getMotionVariance(dbbmmstack)) ## with a DBBMMStack object

Description

An enhanced function to download information of studies, animals, deployments and tags, and sensor measurements from Movebank. Many of the options of this function have been included as separate more user friendly functions listed in the See Also section below.

Usage

## S4 method for signature 'character,MovebankLogin'
getMovebank(entity_type , login, ...)

Arguments

Details

• getMovebank("tag_type", login): returns all sensor types in Movebank and their corresponding sensor id. See also getMovebankSensors.

• getMovebank("study", login): returns all studies where the user has permission to see the data. You may have permission to see only the study details, view some or all tracks but not download data, or view and download some or all data. Also, there are studies that you do not have permission to see at all, these studies will not be included in this list. See also getMovebankStudies.

• getMovebank("study", login, i_am_owner=T): returns all studies where the user is a data manager.

• getMovebank("study", login, study_id): returns a summary of information about one or more studies. See also getMovebankStudy.

• getMovebank("tag", login, study_id): returns tag reference information from a study. See also getMovebankReferenceTable.

• getMovebank("individual", login, study_id): returns animal reference information from a study. See also getMovebankAnimals, getMovebankReferenceTable.

• getMovebank("deployment", login, study_id): returns deployment reference information from a study. See also getMovebankReferenceTable.

• getMovebank("event", login, study_id,...): returns the sensor measurements from a study. See also getMovebankData, getMovebankLocationData, getMovebankNonLocationData.

The default columns of getMovebank("event", login,study_id,...) are timestamp, location_lat, location_long, individual_id, tag_id. If the downloaded study only contains GPS data, these default columns are suitable, but for all other sensors, additional columns are required. The columns available vary among sensor type and tag manufacturer, the complete list of available attributes for a specific study can be obtained with: getMovebankSensorsAttributes(study, login=login). If attributes="all" than all attributes that are present in the study will be downloaded.

The definitions of the content of the columns is detailed in the Attribute Dictionary on Movebank

Value

'data.frame'

Note

• 'id' in getMovebank("study", login, ...) are the values required in study_id

• 'id' in getMovebank("individual", login, study_id) are the values required in individual_id

• 'id' in getMovebank("deployment", login, study_id) are the values required in deployment_id

• 'id' in getMovebank("tag_type", login) are the values required in sensor_type_id

• 'id' in getMovebank("tag", login, study_id) corresponds to 'tag_id'

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

If the data include double timestamps you can use the getDuplicatedTimestamps function to identify them and decide which one to keep.

Author(s)

Marco Smolla & Anne Scharf

See Also

movebankLogin, getMovebankData, getMovebankLocationData, getMovebankNonLocationData, getMovebankReferenceTable, getMovebankAnimals, getMovebankID, getMovebankSensors, getMovebankSensorsAttributes, getMovebankStudies, getMovebankStudy, searchMovebankStudies

Examples

## Not run: 

## first create the login object 
login <- movebankLogin()

anne## get Movebank ID from study
studyID <- getMovebankID(study="MPIAB white stork lifetime tracking data (2013-2014)", 
                         login=login)
studyID2 <- getMovebankID(study="Ocelots on Barro Colorado Island, Panama", login=login)

## get a summary of information about the two studies
getMovebank("study", login=login, study_id=c(studyID,studyID2)) 

## get tag reference information from the study
head(getMovebank("tag", login=login, study_id=studyID))

## get animal reference information from the study
head(getMovebank("individual", login=login, study_id=studyID))

## get deployments reference information from the study
head(getMovebank("deployment", login=login, study_id=studyID))

## get the sensor measurements from the study
## find out which sensors were used in this study
unique(getMovebankSensors(study=studyID,login=login)$sensor_type_id)
## get movebank ID of one individual of this study
indID <- getMovebank("individual", login=login, study_id=studyID)$id[50]
## the correspondence table between the individual ID and the 
## animal names can be obtained like this
head(getMovebank("individual", login=login, 
                 study_id=studyID)[, c("id", "local_identifier")])

## get GPS and accelerometer data within a time period
## to download all attributes for all sensors included in the study
attrib <- "all"
## get measurments for a given time period, in this case for GPS and 
## accelerometer, and between "2013-06-25 03:55:00.000" and "2013-06-26 10:25:00.000"
getMovebank("event", login=login, study_id=studyID, sensor_type_id=c(653,2365683), 
            individual_id=indID, attributes=attrib, timestamp_start="20130625035500000", 
            timestamp_end="20130626102500000 ")

## get all GPS data for 2 individuals
## get movebank ID of another individual of this study
indID2 <- getMovebank("individual", login=login, study_id=studyID)$id[35]
## get GPS measurements for these two individuals with all available attributes
head(storks <- getMovebank("event", login=login, study_id=studyID, 
                           sensor_type_id=653, individual_id=c(indID,indID2), 
                           attributes="all"))

## create moveStack
## get the names of the individuals as they appear on Movebank
(individualNames <- getMovebank("individual", login=login, 
                                study_id=studyID)[c(35,50), c("id", "local_identifier")])
head(storks2 <- merge(storks,individualNames,by.x="individual_id", by.y="id"))

myMoveStack <- move(x=storks2$location_long, y=storks2$location_lat,
                    time=as.POSIXct(storks2$timestamp, format="
                    data=storks2, 
                    proj=CRS("+proj=longlat +ellps=WGS84"), 
                    animal=storks2$local_identifier)

plot(myMoveStack, type="l")

## End(Not run)

Description

This function returns information of the animals, their tags and IDs from a Movebank study.

Usage

getMovebankAnimals(study, login)

Arguments

Details

getMovebankAnimals belongs to the Movebank browsing functions and returns a data.frame from the requested study that includes among others the individual_id, tag_id, deployment_id, sensor_type_id which are the internal ids of Movebank, the tag_local_identifier, local_identifier which are the ids uploaded to Movebank by the user and other information if available as e.g. death_comments, sex, individual_taxon_canonical_name, etc.

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

See Also

movebankLogin, getMovebankReferenceTable

Examples

## Not run: 

# obtain a login
login<-movebankLogin()
getMovebankAnimals(study=2950149, login=login)

## End(Not run)

Description

This function downloads the location data and timestamp of a study stored in Movebank as a move/moveStack object

Usage

## S4 method for signature 'numeric,character,MovebankLogin'
getMovebankData(study, animalName, login, ...)

## S4 method for signature 'numeric,numeric,MovebankLogin'
getMovebankData(study, animalName, login, 
                removeDuplicatedTimestamps=FALSE,
                includeExtraSensors=FALSE, deploymentAsIndividuals=FALSE,
                includeOutliers=FALSE,...)

Arguments

Details

getMovebankData belongs to the Movebank browsing functions and returns a Move object from studies with only one animal or a MoveStack object for studies with multiple animals.
Remember that you need an account on Movebank, see movebankLogin.

Attribute names:
The definitions of the content of the columns within the @idData, @sensor, @data slots of the move or moveStack object is detailed in the Attribute Dictionary on Movebank

includeExtraSensors:
If this includeExtraSensors=TRUE the data of all non location sensors (e.g. acceleration, magnetometer, etc) available in the study will be downloaded and stored in the unUsedRecords slot. Data from a single or a set of non location sensors can be also downloaded as a data.frame with the function getMovebankNonLocationData

deploymentAsIndividuals:
If single individuals have several deployments, and these are wished to be downloaded separately, this can be done by setting deploymentAsIndividuals=TRUE. In this case the "@trackId" will contain the names of the deployments.

idData:
The idData slot contains only the information of the animals. To obtain information on tags, deployments and sensors of the study use the function getMovebankReferenceTable.
When deploymentAsIndividuals=TRUE than the idData slot contains the information of the deployments.

Value

Object of class 'Move' or 'MoveStack'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

removeDuplicatedTimestamps:
It is possible to set removeDuplicatedTimestamps=TRUE which allows you delete the duplicated timestamps in case your data set contains them. Using this argument will retain the first of multiple records with the same animal ID and timestamp, and remove any subsequent duplicates. In case you want to control which of the duplicate timestamps are kept and which are deleted, we recommend to download the data as a .csv file from Movebank or to use the function getMovebankLocationData, find the duplicates using e.g. getDuplicatedTimestamps, decide which of the duplicated timestamp to retain, and than create a move/moveStack object with the function move. Another option is to edit the records in movebank and mark the appropriate records as outliers.

includeOutliers:
In Movebank outliers can be marked manually or using filters, including a duplicate filter that flags duplicate records based on user-selected attributes, retaining the first record of each duplicate set that was imported to the study. When includeOutliers=FALSE (default) these records are automatically placed in the UnusedRecords slots. If includeOutliers=TRUE these records are included along all other locations. This option can be useful if the user wants to e.g. implement their own filter/algorithm to identify outliers. Entries that contain NAs in the coordinate columns will always be included in the UnusedRecords slots.

Multiple sensors:
The getMovebankData function downloads the data of all location sensors available in the study. If the study contains several location sensors, the resulting move/moveStack object can be separated into a move/moveStack object per sensor type:
x[x@sensor=="z"] where "x" is a Move or a MoveStack object, and "z" is the name of the sensor e.g. "GPS", "Radio Transmitter", etc.

Downloading a study with many locations:
If the study to be downloaded has many locations (probably in the order of 10s of millions), the download may take so long that the connection breaks, and the study cannot be downloaded. We recommend to download each individual separately to ensure a successfully download. See more details and examples in the 'browseMovebank' vignette.

Author(s)

Marco Smolla & Anne Scharf

See Also

movebankLogin,getMovebankLocationData, getMovebankNonLocationData

Examples

## Not run: 
# obtain a login
login<-movebankLogin()

# returns a MoveStack object from the specified study
getMovebankData(study="Ocelots on Barro Colorado Island, Panama", login=login) 

# returns a Move object (there is only one individual in this study)
getMovebankData(study="Coatis on BCI Panama (data from Powell et al. 2017)", login=login) 

# returns a MoveStack with two individuals
getMovebankData(study=123413, animalName=c("Mancha","Yara"), login=login) 

# Get a specific timerange, eg: all positions untill "2003-05-06 19:45:10.000"
(ocelots <- getMovebankData(study=123413, animalName=c("Mancha","Yara"), 
                            login=login, timestamp_end="20030506194510000"))

timestamps(ocelots)
## End(Not run)

Description

This function returns the numeric Movebank ID of the study which corresponds to the character study name stored on Movebank

Usage

getMovebankID(study,login)

Arguments

Details

getMovebankID belongs to the Movebank browsing functions and returns the Movebank ID of a study as it is stored on Movebank. This number can also be found on the Study Details page of the study on Movebank.

Value

The function returns one 'numeric' value.

Note

The character study name on Movebank can be potentially edited and changed at any time by the Data Manager(s), whereas the Movebank ID is uniquely assigned to each study when it is uploaded to Movebank, and cannot be modified afterwards.

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

See Also

movebankLogin

Examples

## Not run: 

#obtain a login
login<-movebankLogin()
getMovebankID(study="Ocelots on Barro Colorado Island, Panama", login=login)

## End(Not run)

Description

This function downloads the location data for one or several sensors of a study stored in Movebank.

Usage

## S4 method for signature 'numeric,numeric,character,MovebankLogin'
getMovebankLocationData(study, sensorID, animalName, login, ...)

## S4 method for signature 'numeric,numeric,numeric,MovebankLogin'
getMovebankLocationData(study, sensorID, animalName, login,
                        includeOutliers=FALSE, underscoreToDots=TRUE, ...)

Arguments

Details

getMovebankLocationData belongs to the Movebank browsing functions and returns a data.frame with data from one or multiple location sensors from studies with one animal or multiple animals.
Remember that you need an account on Movebank, see movebankLogin.
Note that getMovebankData has also the option to download location data directly into a move/moveStack object.

Attribute names:
The definitions of the content of the columns of the returned data.frame is detailed in the Attribute Dictionary on Movebank. The attributes deployment_id, individual_id, tag_id, study_id correspond to the internal ids of Movebank.

sensorID:
See getMovebankSensors to obtain all available sensors of the study of interest. The valid names for this argument are those of the the columns "name" or "id" of the table returned by getMovebankSensors(login). The valid numeric Ids are also in the column "sensor_type_id" in the table returned for a specific study with getMovebankSensors(study,login). This function only accepts location sensors which are marked as "true"" in the "is_location_sensor" column of the table returned by getMovebankSensors(login).

underscoreToDots:
.csv files downloaded from the Movebank webpage contain dots in their column names, and .csv files downloaded via the API (like in the case of this function) contain instead underscores in their column names. Many of the functions in the Move package were created based on the webpage csv downloaded data and rely on the column names with dots. If you would like to use function like e.g. getDuplicatedTimestamps or read in the csv file with move by stating the path to file, among others, than the column names have to be with dots.

Downloading a study with many locations:
If the study to be downloaded has many locations (probably in the order of 10s of millions), the download may take so long that the connection breaks, and the study cannot be downloaded. We recommend to download each individual separately to ensure a successfully download. See more details and examples in the 'browseMovebank' vignette.

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Anne Scharf

See Also

movebankLogin, getMovebankData, getMovebankNonLocationData

Examples

## Not run: 
## first create the login object 
login <- movebankLogin()

## get GPS data for one individual
str(getMovebankLocationData(study=74496970, sensorID="GPS",
                               animalName="DER AR439", login=login))

## get GPS data for one individual after the "2013-07-12 06:50:07.000"
str(getMovebankLocationData(study=74496970, sensorID="GPS", animalName="DER AR439", 
                               login=login, timestamp_start="20130712065007000"))

# get GPS data for all individuals of the study between 
# the "2013-08-15 15:00:00.000" and "2013-08-15 15:01:00.000"
str(getMovebankLocationData(study=74496970, sensorID=653, 
                               login=login, timestamp_start="20130815150000000", 
                               timestamp_end="20130815150100000"))

## End(Not run)

Description

This function downloads the non location data for one or several sensors of a study stored in Movebank

Usage

## S4 method for signature 'numeric,numeric,character,MovebankLogin'
getMovebankNonLocationData(study, sensorID, animalName, login, ...)

## S4 method for signature 'numeric,numeric,numeric,MovebankLogin'
getMovebankNonLocationData(study, sensorID, animalName, login, ...)

Arguments

Details

getMovebankNonLocationData belongs to the Movebank browsing functions and returns a data.frame with data from one or multiple non-location sensors from studies with one animal or multiple animals.
Remember that you need an account on Movebank, see movebankLogin.
Note that getMovebankData has also the option to download non location alongside with the location data.

Attribute names:
The definitions of the content of the columns of the returned data.frame is detailed in the Attribute Dictionary on Movebank

sensorID:
See getMovebankSensors to obtain all available sensors of the study of interest. The valid names for this argument are those of the the columns "name" or "id" of the table returned by getMovebankSensors(login). The valid numeric Ids are also in the column "sensor_type_id" in the table returned for a specific study with getMovebankSensors(study,login). This function only accepts non-location sensors which are marked as "false"" in the "is_location_sensor" column of the table returned by getMovebankSensors(login).

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Downloading a study with a lot of data:
If the study to be downloaded has many locations (probably in the order of 10s of millions), the download may take so long that the connection breaks, and the study cannot be downloaded. We recommend to download each individual separately to ensure a successfully download. See more details and examples in the 'browseMovebank' vignette.

Author(s)

Anne Scharf

See Also

movebankLogin, getMovebankData, getMovebankLocationData

Examples

## Not run: 
## first create the login object 
login <- movebankLogin()

## get acceleration data for one individual
str(getMovebankNonLocationData(study=74496970 , sensorID="Acceleration",
                               animalName="DER AR439", login=login))

## get acceleration data for one individual after the "2013-07-12 06:50:07.000"
str(getMovebankNonLocationData(study=74496970 , sensorID="Acceleration", animalName="DER AR439", 
                               login=login, timestamp_start="20130712065007000"))

# get acceleration data for all individuals of the study between 
# the "2013-08-15 15:00:00.000" and "2013-08-15 15:01:00.000"
str(getMovebankNonLocationData(study=74496970 , sensorID=2365683, 
                               login=login, timestamp_start="20130815150000000", 
                               timestamp_end="20130815150100000"))

## End(Not run)

Description

This function returns the information of the animals, tags, deployments and sensors from a Movebank study

Usage

getMovebankReferenceTable(study, login, allAttributes = FALSE)

Arguments

Details

getMovebankReferenceTable belongs to the Movebank browsing functions and returns a data.frame from the requested study, including all data provided by the user referring to the animals, tags and deployments. It also includes animal_id, tag_id, deployment_id, sensor_type_id, study_id which are the internal ids of Movebank. This table is equivalent to the table obtained on the Movebank webpage trough the option "Download Reference Data" of the study.

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Anne Scharf

See Also

movebankLogin

Examples

## Not run: 
# obtain a login
login <- movebankLogin()
getMovebankReferenceTable(study=74496970, login=login)[1:6,]
getMovebankReferenceTable(study=74496970, login=login, allAttributes=T)[1:6,]

## End(Not run)

Description

This function returns the sensor types used in a Movebank study.

Usage

getMovebankSensors(study, login)

Arguments

Details

getMovebankSensors belongs to the Movebank browsing functions and returns the sensor type(s) used for each tag_id within the specified study.

If the study argument is missing, information about all sensor types available on Movebank and the correspondence between sensor_type_id and the sensor name is obtained.

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

See Also

movebankLogin

Examples

## Not run: 

## obtain a login
login<-movebankLogin()

## obtain sensors types of each tag in the specified study
getMovebankSensors(study=2950149, login=login)

## obtain all sensors available on Movebank
getMovebankSensors(login=login)

## End(Not run)

Description

This function returns all attributes of the sensors of the requested Movebank study.

Usage

getMovebankSensorsAttributes(study, login, ...)

Arguments

Details

getMovebankSensorAttributes belongs to the Movebank browsing functions and returns the attributes of the sensors of a study, i.e. what is the sensor id and which data types are stored for this sensor (e.g. GPS sensors store longitude and latitude locations, and timestamps and have 653 as their ID on Movebank).

The definition of each of the attributes is detailed in the Attribute Dictionary on Movebank

The correspondence between the sensor type and the sensor type id can be found with the function getMovebankSensors, leaving the study argument empty.

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla

See Also

movebankLogin

Examples

## Not run: 

# obtain a login
login<-movebankLogin()
getMovebankSensorsAttributes(study=2950149, login=login)

## End(Not run)

Description

This function returns all studies available on Movebank.

Usage

getMovebankStudies(login)

Arguments

Details

getMovebankStudies belongs to the Movebank browsing functions and returns all studies available on Movebank.

Value

returns an object of class 'factor' with the names of all studies available on Movebank.

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

Examples

## Not run: 

# obtain a login
login <- movebankLogin()
getMovebankStudies(login=login)

## End(Not run)

Description

This function returns information about the requested study as e.g. the authors of the study, licence type, citation and more.

Usage

getMovebankStudy(study, login)

Arguments

Details

getMovebankStudy belongs to the Movebank browsing functions and returns a data.frame with information about the requested study (e.g.: authors of the study, licence type, citation, etc).

Value

'data.frame'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

Examples

## Not run: 
# obtain a login
login<-movebankLogin()
getMovebankStudy(study="Coatis on BCI Panama (data from Powell et al. 2017)", login=login)

## End(Not run)

Description

The UD represents the minimum area in which an animal has some specified probability of being located (Cumulative Distribution Function).

Usage

## S4 method for signature '.UD'
getVolumeUD(x, ...)

Arguments

Value

'raster' or 'rasterStack'
If several objects are provided, a list of rasters is returned

Note

To obtain this modified UD raster from a DBBMMBurstStack object, transform the object with the UDStack function into a '.UDStack' class, and than use the getVolumeUD function upon the obtained object.

Author(s)

Marco Smolla & Anne Scharf

See Also

raster2contour, contour, UDStack

Examples

data(leroydbbmm)
data(dbbmmstack)
data(leroydbgb)
getVolumeUD(leroydbbmm) # for a DBBMM object
getVolumeUD(dbbmmstack) # for a DBBMMStack object 
getVolumeUD(leroydbgb) # for a dynBGB object 

getVolumeUD(leroydbbmm, leroydbgb) # for several objects 

plot(getVolumeUD(leroydbbmm))

## e.g. select the raster corresponding to the 95% UD
leroyUD <- getVolumeUD(leroydbbmm)
leroyUD[leroyUD>0.95] <- NA
plot(leroyUD)

Description

The hrBootstrap function calculates the 0, 25, 50, 75, 100% percentile of the Minimum Convex Polygon (MCP) area by a logarithmic step wise increase of the number of samples per calculation. For every step this calculation is repeated rep times with random coordinates from the track.

Usage

## S4 method for signature 'SpatialPoints'
hrBootstrap(x, rep=100, plot=TRUE, level=95,
            levelMax=100, unin='km', unout='m2', ...)
  
  ## S4 method for signature '.MoveTrackStack'
hrBootstrap(x, rep=100, plot=TRUE, level=95, 
            levelMax=100, unin="km", unout="m2", ...)

Arguments

Details

The function calculates the 0, 25, 50, 75, 100% percentile of the Minimum Convex Polygon (MCP) area with a logarithmic step wise increase of the number of samples per calculation. For every step this calculation is repeated rep times with random coordinates from the track. For example it calculates 100 times the MCP area from 3 random locations and stores the area. In the next step it calculates it from 5 random locations and so on. The returned graph shows the 5 percentiles of the area sizes (see 'Values'). The dot-dashed line indicates the real MCP area size of all locations.

The hrBootstrap function passes values (samples of the track) on to the function mcp that is part of the adehabitatHR package. See the help of mcp for more information about input and output units.

Value

The values are returned in a data.frame with the units indicated by unout.

Plot legend:
- 0% percentile of mcp area: blue bottom line
- 25% percentile of mcp area: red bottom line
- 50% percentile of mcp area: black middle line
- 75% percentile of mcp area: red top line
- 100% percentile of mcp area: blue top line
- Real mcp area size of all locations: horizontal dot-dashed black line

The number of locations used in each step are printed in the console.

Note

Plots for MoveStacks are plotted one after another, and not side by side.

Author(s)

Marco Smolla & Anne Scharf

Examples

if(requireNamespace("adehabitatHR")){
## for a Move object
  m <- move(x=rnorm(55), y=rnorm(55), time=as.POSIXct(1:55, origin="1970-1-1"), 
	          proj=CRS("+proj=aeqd +ellps=WGS84"), animal='a')    
  hrBootstrap(m,rep=5, level=99, unout="m2", plot=TRUE)

## for a MoveStack object
   m2 <- move(x=rnorm(30), y=rnorm(30), time=as.POSIXct(1:30, origin="1970-1-1"), 
	           proj=CRS("+proj=aeqd +ellps=WGS84"), animal='b') 
  mstack <- moveStack(list(m[30:50,],m2))
  hrBootstrap(mstack,rep=5, unout="m2", plot=FALSE) 

## for a SpatialPoints object
  hrBootstrap(as(m,"SpatialPoints"),rep=5, unout="m2", plot=TRUE) 
}

Description

This function returns or replaces the idData slot of a Move, MoveStack or MoveBurst object.

Usage

## S4 method for signature '.MoveTrack'
idData(x,i,j,...)

  ## S4 replacement method for signature '.MoveTrack,missing,missing,data.frame'
idData(x,i,j) <- value
  ## S4 replacement method for signature '.MoveTrack,ANY,ANY,ANY'
idData(x,i,j) <- value

Arguments

Value

Either the idData data.frame or the modified move object

Author(s)

Bart Kranstauber & Anne Scharf

Examples

data(fishers)
idData(fishers)

## obtain e.g. only the tag and individual identifier columns
idData(fishers, j=c(6,7))
idData(fishers, j=c("tag.local.identifier", "individual.local.identifier"))

Description

This function allows to interpolate trajectories. It does this on the basis of a simple interpolation, depending on the spaceMethod that is specified.

Usage

interpolateTime(x, time, spaceMethod=c('euclidean','greatcircle','rhumbline'),...)

Arguments

Details

In the argument time:
- number of locations: refer the total number of locations that the resulting track will have distributed equally over time. E.g. if time=200, the resulting track will have 200 points interpolated at a constant time interval.
- time interval: refers to the time interval at which a location should be interpolated. E.g. if time=as.difftime(10, units="mins") a location will be interpolated every 10 mins.
- vector of timestamps: the timestamps of this vector have to be in ascending order, and within the time range of the track.

Value

Move-class object of the interpolated locations.

Author(s)

Bart Kranstauber & Anne Scharf

Examples

data(leroy)
## providing the number of locations
plot(leroy[100:150,], col="red",pch=20)
points(mv <- interpolateTime(leroy[100:150,], time=500, spaceMethod='greatcircle'))

## providing a time interval
plot(leroy[100:150,], col="red",pch=20)
points(mv2 <- interpolateTime(leroy[100:150,], time=as.difftime(10, units="mins"), 
                              spaceMethod='greatcircle'))

## providing a vector of timestamps
plot(leroy[100:150,], col="red",pch=20)
ts <- as.POSIXct(c("2009-02-13 10:00:00", "2009-02-13 12:00:00", "2009-02-13 14:00:00",
                   "2009-02-13 16:00:00","2009-02-13 18:00:00","2009-02-13 20:00:00",
                   "2009-02-13 22:00:00","2009-02-14 00:00:00","2009-02-14 02:00:00",
                   "2009-02-14 04:00:00","2009-02-14 06:00:00", "2009-02-14 08:00:00", 
                   "2009-02-14 10:00:00"),  format="%Y-%m-%d %H:%M:%S", tz="UTC")
points(mv3 <- interpolateTime(leroy[100:150,], time=ts, spaceMethod='greatcircle'))

Description

This file includes spatial data from a fisher (Martes pennanti). It can be used to test the different functions from the move package.
These location data were collected via a 105g GPS tracking collar (manufactured by E-obs GmbH) and programmed to record the animal's location every 15 minutes, continuously. The collar was deployed from 10 February 2009 through 04 March 2009 on an adult, resident, male fisher, in New York, USA (see References). The data usage is permitted for exploratory purposes. For other purposes please get in contact.

Usage

data("leroy")

Format

An object of the class move

Author(s)

Scott LaPoint

Source

https://www.datarepository.movebank.org/handle/10255/move.330

References

For more information, contact Scott LaPoint [email protected]

Examples

## create a Move object from the data set
data <- move(system.file("extdata","leroy.csv.gz",package="move"))
plot(data)
data(leroy)

Description

Utilization densities calculated with dynBGB to exemplify functions.

Usage

data("leroydbgb")

Details

see createRDataFile.R in inst/extdata for the exact calculation

Examples

data(leroydbgb)
leroydbgb

Description

The licenseTerms method returns or sets the license terms of a track from a Move or MoveStack object.

Usage

## S4 method for signature '.MoveGeneral'
licenseTerms(obj)
  ## S4 replacement method for signature '.MoveGeneral'
licenseTerms(obj) <- value

Arguments

Value

character string of the license terms

Author(s)

Anne Scharf

See Also

citations

Examples

data(leroy)
  licenseTerms(leroy) #get the license from a Move object
  
  ## change the license and set it for a Move object
  licenseTerms(leroy) <- "use of data only permitted after obtaining licence from the PI" 
 
  data(fishers)
  licenseTerms(fishers) #get the license from a MoveStack object
  
  ## change the license and set it for a MoveStack object
  licenseTerms(fishers) <- "use of data only permitted after obtaining licence from the PI"

Description

Function for plotting a track from a Move object as lines

Usage

## S4 method for signature '.MoveTrackSingle'
lines(x,...)
  ## S4 method for signature '.MoveTrackStack'
lines(x,col=NA,...)
  ## S4 method for signature '.MoveTrackSingleBurst'
lines(x,col=NA,...)

Arguments

Author(s)

Marco Smolla & Anne Scharf

See Also

points, plot

Examples

## add a track from a Move object to a plot
data(leroy)
data(leroydbbmm)
plot(leroydbbmm)
lines(spTransform(leroy, center=TRUE), col=3)

## plot the points and lines of a moveStack
data(fishers)
plot(fishers, type='p',pch=4)
lines(fishers, col=3:4)

Description

This function creates Move or MoveStack object from a .csv file with location data downloaded from a Movebank study, from a zip file downloaded from the EnvData (environmental annotation tool) of a Movebank study, from a ltraj, telemetry, track_xyt, track or binClstPath object or from own data. If you use your own data you need to set the projection method with the 'proj' argument and specify which columns of your data contain the coordinates and timestamps.

Usage

## S4 method for signature 'connection,missing,missing,missing,missing'
move(x, removeDuplicatedTimestamps=F, ...)

## S4 method for signature 'ltraj,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'telemetry,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'track_xyt,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'list,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'track,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'binClstPath,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'binClstStck,missing,missing,missing,missing'
move(x, y, time, data, proj,...)
## S4 method for signature 'data.frame,missing,missing,missing,missing'
move(x, y, time, data, proj,...)

## S4 method for signature 'numeric,numeric,POSIXct,data.frame,CRS'
move(x, y, time, data, proj, sensor='unknown',animal='unnamed',...)

Arguments

Details

The easiest way to import data is to download the study you are interested in from https://www.movebank.org and set the file path as the x argument of the move function. The function detects whether there are single or multiple individuals in this file and automatically creates either a Move, MoveStack object. See the 'browseMovebank' vignette for more information on how to directly download data from Movebank from within R.

Another way is to read in your data using read.csv. Then specify the arguments "x" and "y" the columns of your data containing the x and y coordinates, in the argument "time" the column containing the timestamp, optionally the columns containing the information of the sensor(s) used, the animal name(s) and the projection, as well as the whole data.frame of the imported data. If the argument "animal" is left empty or contains only the name of one animal the function will return a Move object. If the data contains multiple animal names the function will return a MoveStack object.

Value

returns an object of class 'move' or 'moveStack'.

If data of Movebank are used, the definitions of the content of the columns within the @idData, @sensor, @data slots of the move or moveStack object is detailed in the Attribute Dictionary on Movebank

When the move or moveStack is created providing a path to a .csv or .zip file downloaded from Movebank the coordinates in the @coords slot are named "location.long" and "location.lat". When the move or moveStack is created by providing a data.frame, the coordinates in the @coords slot are named "coords.x1" and "coords.x2".

Note

It is checked whether the imported data set (via file path) is in a Movebank format. If your data isn't in a Movebank format, you have to use the alternative import for non-Movebank data reading in your data using read.csv and specifying which columns contain the needed information (see 'Details').

Locations with "NA":
Because the SpatialPointsDataFrame function that creates the spatial data frame of the Move object can not process NA location values, all rows with NA locations are stored as unused records in the Move object.

Duplicated timestamps:
When you are importing data from movebank (via path to .csv or .zip file) you can also set the argument "removeDuplicatedTimestamps=TRUE", which allows you delete the duplicated timestamps in case your data set contains them. Using this argument will retain the first of multiple records with the same animal ID and timestamp, and remove any subsequent duplicates. In case you want to control which of the duplicate timestamps are kept and which are deleted, we recommend to download the data as a .csv file from Movebank or to use the function getMovebankLocationData, find the duplicates using e.g. getDuplicatedTimestamps, decide which of the duplicated timestamp to retain, and than create a move/moveStack object with the function move. Another option is to edit the records in movebank and mark the appropriate records as outliers.

Naming:
Due to convention all names are turned into 'good names' which means, without spaces ('Ricky T' becomes 'Ricky.T'), if names are numbers a "X" will be prepended ('12345' becomes 'X12345') and most symbols will be replaced by "." ('Ricky-T' becomes 'Ricky.T').

Outliers:
In Movebank outliers can be marked manually or using filters, including a duplicate filter that flags duplicate records based on user-selected attributes, retaining the first record of each duplicate set that was imported to the study. These outliers will be marked with 'false' in the column 'visible', if data were downloaded including outliers.
When the move object is created by providing the path to the file downloaded from Movebank, the records marked as outliers are automatically placed in the UnusedRecords slots.
If these marked outliers want to be included in the move object, read in the data from the downloaded csv file from movebank with read.csv, set the marked outliers to 'true' in the column 'visible', or remove the column 'visible' from the data frame, save the table as a csv file and create the move object.

Multiple sensors:
If a move/moveStack object contains multiple sensors, this object can be separated into a move/moveStack object per sensor type:
x[x@sensor=="z"] where "x" is a Move or a MoveStack object, and "z" is the name of the sensor e.g. "GPS", "Radio Transmitter", etc.

Telemetry object with error calibration:
If the telemetry object (from ctmm) contains calibrated data, i.e. the GPS error has been calculated using the available tools in the ctmm package, the move object will contain an extra column in the data slot called error.loc.mts that will contain the error in meters for each location. This information can be used e.g. in the location.error argumet of the dynamic Brownian Bridge functions or the locErr argument of the Bivariate Gaussian Bridge functions.

Providing a data.frame object:
To read in a data.frame as a move/movestack object without specifying which arguments correspond to each argument, the data.frame is assumed to be downloaded from Movebank via the webpage or the getMovebankLocationData function. The function assumes a movebank format with the coordinates under the columns "location long" and "location lat" and projection lat/long; the timestamp under the column "timestamps" in the movebank format "%Y-%m-%d %H:%M:%S" and in timezone UTC; individual Id under the column "individual local identifier" and the sensor type under the column "sensor type".

Author(s)

Marco Smolla, Bart Kranstauber & Anne Scharf

Examples

## create a move object from a Movebank csv file
filePath<-system.file("extdata","leroy.csv.gz",package="move")
data <- move(filePath)

## create a move object from non-Movebank data
file <- read.table(filePath, header=TRUE, sep=",", dec=".")
data <- move(x=file$location.long, y=file$location.lat, 
	     time=as.POSIXct(file$timestamp, format="%Y-%m-%d %H:%M:%S", tz="UTC"), 
	     data=file, proj=CRS("+proj=longlat +ellps=WGS84"), 
	     animal="Leroy", sensor="GPS")
plot(data, type="b", pch=20)

## if the data contain multiple individuals a moveStack will be created
fishersPath<-system.file("extdata","fishersSubset.csv.gz",package="move")
fishersSubset <- read.table(fishersPath, header=TRUE, sep=",", dec=".")
data2 <- move(x=fishersSubset$location.long, y=fishersSubset$location.lat, 
             time=as.POSIXct(fishersSubset$timestamp,format="%Y-%m-%d %H:%M:%S", tz="UTC"), 
             data=fishersSubset, proj=CRS("+proj=longlat +ellps=WGS84"),
             animal=fishersSubset$individual.local.identifier,
             sensor=fishersSubset$sensor)
plot(data2, type="b", pch=20, col=c("green","blue")[data2@idData$individual.local.identifier])
plot(data2[[2]], type="l")

Description

The Move object contains at least time and coordinate information of an animal. It can contain further data that are specific to the animal, e.g. the sex or age, which are stored in the idData slot data.frame. Any data associated to the coordinates are stored in the data slot data.frame. If the object was created with the Movebank browsing functions it also contains the study name, licence and citation information.
A Move object can be created with the functions move, getMovebankData or getDataRepositoryData.

Slots

bbox

belongs to the SpatialPointsDataFrame

citation

Object of class "character": how to cite the study, when Movebank data are used

coords

coordinates of the track, belongs to the SpatialPointsDataFrame

coords.nrs

belongs to the SpatialPointsDataFrame

data

Object of class "data.frame": additional data associated to the coordinates

dataUnUsedRecords

Object of class "data.frame": data associated to the unused records

dateCreation

Object of class "POSIXct": timestamp when the Move object was created

idData

Object of class "data.frame": additional (one row) data. These data contain information associated to the animal

license

Object of class "character": the license under which the data were published, when Movebank data are used

proj4string

Object of class "CRS": projection of the coordinates

sensor

Object of class "factor": sensors used to record the coordinates

sensorUnUsedRecords

Object of class "factor": sensors used to record the unused records

study

Object of class "character": name of the study, when Movebank data are used

timestamps

Object of class "POSIXct": timestamps associated to the coordinates

timestampsUnUsedRecords

Object of class "POSIXct": timestamps associated to the unused records, i.e. lines of the data that were removed because they included NA locations

Methods

angle

signature(object = "Move"): calculates angles between consecutive locations

as.data.frame

signature(object = "Move"): extracts the spatial data frame

brownian.bridge.dyn

signature(object = "Move"): calculates the utilization distribution (UD) of the given track using the dynamic Brownian Bridge Movement Model

brownian.motion.variance.dyn

signature(object = "Move"): calculates the motion variance of the dynamic Brownian Bridge Movement Model

burst

signature(object = "Move"): bursts a track by a specified variable

citations

signature(object = "Move"): extracts or sets the citation

coordinates

signature(object = "Move"): extracts the coordinates from the track

corridor

signature(object = "Move"): identifies track segments whose attributes suggest corridor use behavior

distance

signature(object = "Move"): calculates distances between consecutive locations

dynBGB

signature(object = "Move"): calculates the utilization distribution (UD) of the given track using the dynamic Bivariate Gaussian Bridge model

dynBGBvariance

signature(object = "Move"): calculates the orthogonal and parallel motion variance of the dynamic Brownian Bridge Movement Model

equalProj

signature(object = "Move"): checks whether all objects of a list are in the same projection

hrBootstrap

signature(object = "Move"): calculates and plots the area of the Minimum Convex Polygon of a track

idData

signature(object = "Move"): returns or replaces the idData slot

interpolateTime

signature(object = "Move"): interpolates trajectories based on time

lines

signature(object = "Move"): add lines of the track of the animal to a plot

move2ade

signature(object = "Move"): converts to a adehabitat compatible object

moveStack

signature(object = "Move"): stacks a list of Move objects

n.locs

signature(object = "Move"): calculates number of locations

plot

signature(object = "Move"): plots the track of the animal

points

signature(object = "Move"): add points of the track of the animal to a plot

seglength

signature(object = "Move"): calculates the length of each segment of a track

sensor

signature(object = "Move"): extracts the sensor(s) used to record the coordinates

show

signature(object = "Move"): displays summary the Move object

speed

signature(object = "Move"): calculates speed between consecutive locations

spTransform

signature(object = "Move"): transforms coordinates to a different projection method

summary

signature(object = "Move"): summarizes the information of Move object

subset

signature(object = "Move"): subsets the Move object

timeLag

signature(object = "Move"): calculates time lag between consecutive locations

timestamps

signature(object = "Move"): gets the timestamps associated to the coordinates

turnAngleGc

signature(object = "Move"): calculates angles between consecutive locations

unUsedRecords

signature(object = "Move"): returns the unUsedRecords object containing the data of the unused records

Note

The Move object contains a .MoveGeneral, .MoveTrack, .MoveTrackSingle and .unUsedRecords object which can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

Convert a Move or MoveStack object to adehabitat compatible object. This is necessary because Move and MoveStack objects are not inherited by the object class that is typically used by the adehabitat package. Therefore, the move2ade function allows to use functions of the adehabitatHR package with objects that were originally created with the Move package.

Usage

## S4 method for signature '.MoveTrackSingle'
move2ade(x)
  ## S4 method for signature '.MoveTrackStack'
move2ade(x)

Arguments

Details

There is also the possibility to convert between a ltraj object and a Move or MoveStack:
as(x,"ltraj") where "x" is a Move or MoveStack object
as(x,"Move") or as(x,"MoveStack") where "x" is a ltraj object

Value

The returned object is from SpatialPointsDataFrame with the animal name (or 'unnamed') stored in the data slot of the SpatialPointsDataFrame.

Author(s)

Marco Smolla & Anne Scharf

Examples

data(fishers)
  data(leroy)
  move2ade(leroy) ## for a Move object  
  move2ade(fishers) ## for a MoveStack object

Description

Creates an object that can be used with all Movebank browsing functions.

Usage

## S4 method for signature 'character,character'
movebankLogin(username,password)

Arguments

Details

Use this function to login to Movebank. After you logged in, you can use the Movebank browsing functions from the move package.

If the function is left empty, you'll be requested to enter your username and password. This option is useful to keep Movebank login data confidential when R-code is shared.

Value

'MovebankLogin'

Note

See the 'browseMovebank' vignette for more information about security and how to use Movebank from within R.

Author(s)

Marco Smolla & Anne Scharf

Examples

## Not run: 
## First create the login object 
login <- movebankLogin(username="xxx", password="zzz")
## or
login <- movebankLogin()

## and than use it with Movebank browsing functions, e.g.
getMovebankStudies(login)

## End(Not run)

Description

The MovebankLogin object is needed for every Movebank browsing function. It is created with the function movebankLogin. Alternatively, one can also chose to enter the username and password every time one uses one of the browsing functions. The object is inherited from an httr request object.

Methods

getMovebank

signature(object = "MovebankLogin"): download data from Movebank

getMovebankAnimals

signature(object = "MovebankLogin"): get animals, tags and IDs of a Movebank study

getMovebankData

signature(object = "MovebankLogin"): download data from Movebank as a Move* object

getMovebankLocationData

signature(object = "MovebankLogin"): download location data from Movebank as a table

getMovebankNonLocationData

signature(object = "MovebankLogin"): download non-location data from Movebank as a table

getMovebankID

signature(object = "MovebankLogin"): get study ID from Movebank

getMovebankSensors

signature(object = "MovebankLogin"): get information about Movebank sensors

getMovebankSensorsAttributes

signature(object = "MovebankLogin"): get available sensor attributes of a Movebank Study

getMovebankStudies

signature(object = "MovebankLogin"): get all studies available on Movebank

getMovebankStudy

signature(object = "MovebankLogin"): get information of a Movebank study

searchMovebankStudies

signature(object = "MovebankLogin"): search for a Movebank study by key words

getMovebankReferenceTable

signature(object = "MovebankLogin"): get all reference data of a Movebank study

show

signature(object = "MovebankLogin"): shows user name and password contained in the MovebankLogin object

Author(s)

Bart Kranstauber, Marco Smolla & Anne Scharf

Description

The class MoveBurst is used to store the track of one individual with a categorical assignment to each segment. Every segment between two locations has a class of for example a behavioral category. A MoveBurst object is created with the functions burst and corridor.

Slots

bbox

See Move-class

burstId

Id of the behavioral categorization assigned to each segment, one shorter then the number of locations.

citation

See Move-class

coords

See Move-class

coords.nrs

See Move-class

data

See Move-class

dataUnUsedRecords

See Move-class

dateCreation

See Move-class

idData

See Move-class

license

See Move-class

proj4string

See Move-class

sensor

See Move-class

sensorUnUsedRecords

See Move-class

study

See Move-class

timestamps

See Move-class

timestampsUnUsedRecords

See Move-class

Methods

angle

signature(object = "MoveBurst"): calculates angles between consecutive locations

as.data.frame

signature(object = "MoveBurst"): extracts the spatial data frame

brownian.bridge.dyn

signature(object = "MoveBurst"): calculates the utilization distribution (UD) of the given track using the dynamic Brownian Bridge Movement Model

brownian.motion.variance.dyn

signature(object = "MoveBurst"): calculates the motion variance of the dynamic Brownian Bridge Movement Model

burstId

signature(object = "MoveBurst"): returns the Id of the behavioral categorization assigned to each segment

citations

signature(object = "MoveBurst"): extracts or sets the citation

coordinates

signature(object = "MoveBurst"): extracts the coordinates from the track

corridor

signature(object = "MoveBurst"): identifies track segments whose attributes suggest corridor use behavior

distance

signature(object = "MoveBurst"): calculates distances between consecutive locations

dynBGB

signature(object = "MoveBurst"): calculates the utilization distribution (UD) of the given track using the dynamic Bivariate Gaussian Bridge model

dynBGBvariance

signature(object = "MoveBurst"): calculates the orthogonal and parallel motion variance of the dynamic Brownian Bridge Movement Model

equalProj

signature(object = "MoveBurst"): checks whether all objects of a list are in the same projection

hrBootstrap

signature(object = "MoveBurst"): calculates and plots the area of the Minimum Convex Polygon of a track

idData

signature(object = "MoveBurst"): returns or replaces the idData slot

interpolateTime

signature(object = "MoveBurst"): interpolates trajectories based on time

lines

signature(object = "MoveBurst"): add lines of the track of the animal to a plot

move2ade

signature(object = "MoveBurst"): converts to a adehabitat compatible object

n.locs

signature(object = "MoveBurst"): calculates number of locations

plot

signature(object = "MoveBurst"): plots the track of the animal

plotBursts

signature(object = "MoveBurst"): plots the centroids of a bursted track

points

signature(object = "MoveBurst"): add points of the track of the animal to a plot

seglength

signature(object = "MoveBurst"): calculates the length of each segment of a track

sensor

signature(object = "MoveBurst"): extracts the sensor(s) used to record the coordinates

show

signature(object = "MoveBurst"): displays summary the MoveBurst object

speed

signature(object = "MoveBurst"): calculates speed between consecutive locations

split

signature(object = "MoveBurst"): splits a MoveBurst into a list of Move objects

spTransform

signature(object = "MoveBurst"): transforms coordinates to a different projection method

summary

signature(object = "MoveBurst"): summarizes the information of MoveBurst object

subset

signature(object = "MoveBurst"): subsets the MoveBurst object

timeLag

signature(object = "MoveBurst"): calculates time lag between consecutive locations

timestamps

signature(object = "MoveBurst"): gets the timestamps associated to the coordinates

turnAngleGc

signature(object = "MoveBurst"): calculates angles between consecutive locations

unUsedRecords

signature(object = "MoveBurst"): returns the unUsedRecords object containing the data of the unused records

Note

The MoveBurst object contains a .MoveGeneral, .MoveTrackSingleBurst and .unUsedRecords object which can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

Stacks a list of Move objects

Usage

## S4 method for signature 'list'
moveStack(x, forceTz=NULL, ...)
  
  ## S4 method for signature 'Move'
moveStack(x, ..., forceTz=NULL)
  
  ## S4 method for signature 'MoveStack'
moveStack(x, ..., forceTz=NULL)

Arguments

Details

This function stacks single Move or Movestacks objects to a MoveStack object.

Value

a 'MoveStack' object

Note

All animal names are converted into 'good names' which means, that spaces are replaced with points and duplicated names get an individual number added. For example:
'Leroy, Leroy' -> adding number to duplicated names ->'Leroy, Leroy.1'
'Ricky T' -> replacing spaces -> 'Ricky.T'

Author(s)

Marco Smolla, Bart Kranstauber & Anne Scharf

See Also

split

Examples

data(leroy)
ricky<-move(system.file("extdata","ricky.csv.gz", package="move"))
leroy<-spTransform(leroy, crs(ricky))

## creating a moveStack from a list of move objects
l <- list(ricky[200:270,], leroy[200:270,])
moveStack(l)

## creating a moveStack from several move objects
moveStack(ricky[200:270,], leroy[200:270,], forceTz="UTC")

## creating a moveStack with the same time zone as input move objects
moveStack(ricky[200:270,], leroy[200:270,], forceTz=attr(timestamps(ricky),"tzone"))

Description

The MoveStack object is a stack of move objects. A MoveStack object can be created with the functions move, moveStack, getMovebankData or getDataRepositoryData

Slots

bbox

belongs to the SpatialPointsDataFrame

citation

Object of class "character": how to cite the study, when Movebank data are used

coords

coordinates of the track, belongs to the SpatialPointsDataFrame

coords.nrs

belongs to the SpatialPointsDataFrame

data

Object of class "data.frame": additional data associated to the coordinates

dataUnUsedRecords

Object of class "data.frame": data associated to the unused records

dateCreation

Object of class "POSIXct": timestamp when the MoveStack object was created

idData

Object of class "data.frame": additional (one row) data. These data contain information associated to the animal

license

Object of class "character": the license under which the data were published, when Movebank data are used

proj4string

Object of class "CRS": projection of the coordinates

sensor

Object of class "factor": sensors used to record the coordinates

sensorUnUsedRecords

Object of class "factor": sensors used to record the unused records

study

Object of class "character": name of the study, when Movebank data are used

timestamps

Object of class "POSIXct": timestamps associated to the coordinates

timestampsUnUsedRecords

Object of class "POSIXct": timestamps associated to the unused records, i.e. lines of the data that were removed because they included NA locations

trackId

Object of class "factor": vector that indicates, which data, coordinates and timestamps belong to each individual

trackIdUnUsedRecords

Object of class "factor": vector that indicates, which data, coordinates and timestamps of the unused records belong to each individual

Methods

angle

signature(object = "MoveStack"): calculates angles between consecutive locations

as.data.frame

signature(object = "MoveStack"): extracts the spatial data frame

brownian.bridge.dyn

signature(object = "MoveStack"): calculates the utilization distribution (UD) of the given track using the dynamic Brownian Bridge Movement Model

brownian.motion.variance.dyn

signature(object = "MoveStack"): calculates the motion variance of the dynamic Brownian Bridge Movement Model

citations

signature(object = "MoveStack"): extracts or sets the citation

coordinates

signature(object = "MoveStack"): extracts the coordinates from the track

corridor

signature(object = "MoveStack"): identifies track segments whose attributes suggest corridor use behavior

distance

signature(object = "MoveStack"): calculates distances between consecutive locations

equalProj

signature(object = "MoveStack"): checks whether all objects of a list are in the same projection

hrBootstrap

signature(object = "MoveStack"): calculates and plots the area of the Minimum Convex Polygon of a track

idData

signature(object = "MoveStack"): returns or replaces the idData slot

lines

signature(object = "MoveStack"): add lines of the track of the animals to a plot

move2ade

signature(object = "MoveStack"): converts to a adehabitat compatible object

moveStack

signature(object = "MoveStack"): stacks a list of MoveStack objects

n.indiv

signature(object = "MoveStack"): returns the number of individuals

n.locs

signature(object = "MoveStack"): calculates number of locations

plot

signature(object = "MoveStack"): plots the track of the animals

points

signature(object = "MoveStack"): add points of the track of the animals to a plot

seglength

signature(object = "MoveStack"): calculates the length of each segment of a track

sensor

signature(object = "MoveStack"): extracts the sensor(s) used to record the coordinates

show

signature(object = "MoveStack"): displays summary the MoveStack object

speed

signature(object = "MoveStack"): calculates speed between consecutive locations

split

signature(object = "MoveStack"): splits a MoveStack into a list of Move objects

spTransform

signature(object = "MoveStack"): transforms coordinates to a different projection method

summary

signature(object = "MoveStack"): summarizes the information of MoveStack object

subset

signature(object = "MoveStack"): subsets the MoveStack object

timeLag

signature(object = "MoveStack"): calculates time lag between consecutive locations

timestamps

signature(object = "MoveStack"): gets the timestamps associated to the coordinates

trackId

signature(object = "MoveStack"): returning the Id of the individual per coordinate

turnAngleGc

signature(object = "MoveStack"): calculates angles between consecutive locations

unUsedRecords

signature(object = "MoveStack"): returns the unUsedRecordsStack object containing the data of the unused records

Note

The MoveStack object contains a .MoveGeneral, .MoveTrackStack and .unUsedRecordsStack object which can be used to program against.

Author(s)

Marco Smolla & Anne Scharf

Description

This function returns the number of individuals from a MoveStack object.

Usage

## S4 method for signature 'Move'
n.indiv(obj)
  ## S4 method for signature '.MoveTrackStack'
n.indiv(obj)

Arguments

Value

Returns the number of individuals.
It will be always 1 for objects of the class Move

Author(s)

Bart Kranstauber

Examples

data(leroy)
n.indiv(leroy) 

data(fishers)
n.indiv(fishers)

Description

This function returns the number of locations of a track from a Move or MoveStack object.

Usage

## S4 method for signature 'SpatialPointsDataFrame'
n.locs(obj)
  ## S4 method for signature '.MoveTrackStack'
n.locs(obj)

Arguments

Value

number of locations.
If a MoveStack is provided, the number of locations per individual is returned.

Author(s)

Marco Smolla

Examples

data(leroy)
data(fishers)
n.locs(leroy) # of Move object
n.locs(fishers) # of MoveStack object

Description

This function returns the names of the individuals from a move or moveStack object.

Usage

namesIndiv(obj)

Arguments

Value

Returns the name as a character for a move object, and the names as a character vector from a moveStack object.
If no name has been provided when creating the move object, "unnamed" will be returned.

Author(s)

Anne Scharf

Examples

data(leroy)
namesIndiv(leroy) 

data(fishers)
namesIndiv(fishers)

Description

The outerProbability method calculates the summed probability of the cells at the border of a raster

Usage

## S4 method for signature 'RasterLayer'
outerProbability(raster,border,...)
  ## S4 method for signature 'DBBMMStack'
outerProbability(raster,border,...)

Arguments

Details

The function returns the summed probability at the border (e.g. the outer 10% of the cells) of a raster. This value can be used as an indicator whether the extent of the used raster is to small for the UD calculation and therefore too much probabilities are not calculated because they are outside the raster.

Value

numeric value for a single DBBMM or dynBGB object, or a list of numeric values for a DBBMMStack

Author(s)

Marco Smolla & Anne Scharf

Examples

data(leroydbbmm)
#calculate the probabilities of 20% of the raster at the border from a DBBMM
outerProbability(leroydbbmm, border=.2)

#calculate the probabilities of 50% of the raster at the border from a DBBMMStack
outerProbability(leroydbbmm, border=.5)

Description

Function for plotting a recorded track from a Move object or the probability values from a DBBMM object

Usage

## S4 method for signature '.MoveTrackSingle,missing'
plot(x, y,asp=1, ...)
  ## S4 method for signature '.MoveTrackStack,missing'
plot(x, y, type="p",asp=1,  ...)
  ## S4 method for signature '.MoveTrackSingleBurst,missing'
plot(x, y, type="p",asp=1,  ...)

Arguments

Details

If x is a MoveBurst object colored lines (according to the burstID) are plotted if the type is set to 'l'. By default it is 'p' which plots the coordinates of the Move object as points.
If x is a DBBMM, DBBMMStack, DBBMMBurstStack or dynBGB object its raster object is plotted with the corresponding cell values. Unlike the image function, it keeps the same cell size ratio when the plot window is re-sized.

In the argument col a vector of colors of the same length as the number of individual for a moveStack, or number of burst levels for a moveBurst object can be specified. If left empty the default 8 colors from R are used, which will be recycled if the object contains more individuals or burst levels (run palette() to obtain vector of default colors).

Note

Have a look on the proportion of the graphic device when printing a track or raster. The plot function does not use equal sized units on both axes.

Author(s)

Marco Smolla & Anne Scharf

See Also

points, lines

Examples

data(leroy)
data(fishers)
plot(leroy) # plot a Move object
plot(leroy, type="o", col=3)
plot(fishers, col=c(3,5), lwd=3) # plot a MoveStack object
plot(fishers, type="l", col=c(3,5), lwd=3)

data(dbbmmstack)
data(leroydbbmm)
plot(leroydbbmm) # plot the raster of a DBBMM object
plot(dbbmmstack) # plot the raster of a DBBMMStack object

Description

The plotBursts function plots bursted Move objects (see burst for how to create a bursted Move object). The function plots a circle at the midpoint of each burst segment (consecutive coordinates that belong to a single burst).

Usage

## S4 method for signature 'list'
plotBursts(object, add=TRUE, 
            sizeFUN=function(x){as.numeric(diff(range(timestamps(x))),units ="mins")},
            col = NA, breaks = 3, ...)
            
  ## S4 method for signature '.MoveTrackSingleBurst'
plotBursts(object, add=TRUE,
            sizeFUN=function(x){as.numeric(diff(range(timestamps(x))),units ="mins")}, 
            col = NA, breaks = 3, ...)

Arguments

Details

sizeFUN
The color of the circles correspond to the burstIDs. The size of the cycles can have different meanings, depending on what function is defined. By default the size refers to the relative time of the burst segment compared to the whole track. This argument accepts any personalized function.

Note

If a list of moveBurst objects is provided, the plots are plotted one after another, and not side by side.

Author(s)

Marco Smolla & Anne Scharf

Examples

data(leroy)
behav <- c(rep(1:4,each=200), rep(5, 118))
testb <- burst(leroy, f=behav)
plot(coordinates(leroy),type="l")
plotBursts(testb, breaks=3, add=TRUE, pch=19)
plotBursts(testb, breaks=5, add=FALSE, pch=19, col=rainbow(5))

## plotting circle size of a moveBurst track by realtive segment length
plotBursts(object=testb, breaks=3, sizeFUN=function(x){sum(distance(x))}, pch=19, add=FALSE)