Wrapper for selecting different animal movement methods.
This version uses just turn angles and step lengths to define the correlated random walk.
move(hypothesis = "crw", ...) crw(agent, extent, stepLength, stddev, lonlat, torus = FALSE) # S4 method for SpatialPointsDataFrame crw(agent, extent, stepLength, stddev, lonlat, torus = FALSE) # S4 method for SpatialPoints crw(agent, extent, stepLength, stddev, lonlat, torus = FALSE)
Character vector, length one, indicating which movement
hypothesis/method to test/use. Currently defaults to
'crw' (correlated random walk) using
arguments passed to the function in
SpatialPointsDataFrame, 2 of the columns must
y1, indicating the previous location.
SpatialPoints object, then
y1 will be assigned randomly.
Extent object that will be used for
Numeric vector of length 1 or number of agents describing step length.
Numeric vector of length 1 or number of agents describing standard deviation of wrapped normal turn angles.
TRUE, coordinates should be in degrees.
FALSE coordinates represent planar ('Euclidean')
space (e.g. units of meters)
Logical. Should the movement be wrapped to the opposite
side of the map, as determined by the
A SpatialPointsDataFrame object with updated spatial position defined by a single occurrence of step length(s) and turn angle(s).
This simple version of a correlated random walk is largely the version that was presented in Turchin 1998, but it was also used with bias modifications in McIntire, Schultz, Crone 2007.
Turchin, P. 1998. Quantitative analysis of movement: measuring and modeling population redistribution in animals and plants. Sinauer Associates, Sunderland, MA.
McIntire, E. J. B., C. B. Schultz, and E. E. Crone. 2007. Designing a network for butterfly habitat restoration: where individuals, populations and landscapes interact. Journal of Applied Ecology 44:725-736.