track2KBA (version 1.1.2)

tripSummary: Summary of trip movements

Description

tripSummary provides a simple summary of foraging trip distances, durations, and directions performed by central place foraging animals.

Usage

tripSummary(trips, colony = NULL, nests = FALSE, extraDist = FALSE)

Value

Returns a tibble data.frame grouped by ID. Trip characteristics included are trip duration (in hours), maximum distance and cumulative distance travelled (in kilometers), direction (in degrees, measured from origin to furthest point of track), start and end times as well as a unique trip identifier ('tripID') for each trip performed by each individual in the data set. Distances are calculated on a great circle.

If the beginning of a track is starts out on a trip which is followed by only one point within InnerBuff, this is considered an 'incomplete' trip and will have an NA for duration. If an animal leaves on a trip but does not return within the ReturnBuff this will be also classified an 'incomplete trip'.

Arguments

trips

SpatialPointsDataFrame, as produced by tripSplit.

colony

data.frame with 'Latitude' and 'Longitude' columns specifying the locations of the central place (e.g. breeding colony). If nests=TRUE, colony should have a third column, 'ID' with corresponding character values in the 'ID' field in trips.

nests

logical scalar (TRUE/FALSE). Were central place (e.g. deployment) locations used in tripSplit specific to each unique 'ID'? If so, each place must be matched with an 'ID' value in both trips and colony objects.

extraDist

logical scalar (TRUE/FALSE). If TRUE, the distance between the first and last points of each trip and the colony will be added to the 'total_dist' (total distance travelled) for each trip.

Details

nests=T may be used if it is desired, for example, to use specific nest locations instead of one central location for all individuals/tracks.

See Also

tripSplit

Examples

## make some play data
dataGroup <- data.frame(Longitude = rep(c(1:10, 10:1), 2), 
               Latitude =  rep(c(1:10, 10:1), 2),
               ID = c(rep("A", 20), rep("B", 20)),
               DateTime = format(
               lubridate::ymd_hms("2021-01-01 00:00:00") + 
               lubridate::hours(0:19))
)

colony <- data.frame(
Longitude = dataGroup$Longitude[1], Latitude = dataGroup$Latitude[1]
)
## split tracks into trips
trips <- tripSplit(dataGroup, colony=colony, 
                innerBuff = 1, 
                returnBuff = 1, 
                duration = 0.5,
                rmNonTrip = FALSE
)
## summarise trip characteristics
sumTrips <- tripSummary(trips, colony)