dynvmax: Dynamic Calculation of the Vmax Parameter

In jedalong/wildlifeTG: Time Geograhic Analysis of Wildlife Telemetry Data

Description

The function dynvmax computes a dynamic version of the Vmax parameter for the PPA method. It can be used to incorporate changes in animal movement behaviour into the PPA method caluculation to better model that area accessible to an individual animal given the set of known telemetry locations in space and time.

Usage

dynvmax(traj, dynamic = "NA", w = 9, class.col = "dt",
  method = "Robson", k = 5, alpha = 0.05, manualVmax = NA,
  vmaxtrunc = NA)

Arguments

traj	an object of the class ltraj which contains the time-stamped movement fixes of the first object. Note this object must be a type II ltraj object. For more information on objects of this type see help(ltraj).
dynamic	one of 'NA', 'focal', 'cumulative', or 'class'; which signifies whether or how to dynamically compute the Vmax parameter. See Details for more information on each of the choices.
w	(optional) window size (only used with dynamic = 'focal' or 'cumulative').
class.col	(optional) character indicating the name of the column in the infolocs dataframe of traj containing the categorized behavioural states of the animal (which can be stored as a character or numeric column).
method	method for computing the Vmax parameter dynamically; can be one of several options: – "Robson" for the Robson & Whitlock (1964) method, – "RobsonLL" for the R & W (1964) lower (1-α)*100\% C.I. limit, – "RobsonUL" for the R & W (1964) upper (1-α)*100\% C.I. limit, – "vanderWatt" for the van der Watt (1980) method, – "vanderWattLL" for the van der Watt (1980) lower (1-α)*100\% C.I. limit, – "vanderWattUL" for the van der Watt (1980) upper (1-α)*100\% C.I. limit.
k	(optional) value for the k parameter in the van der watt (1980) method; default is 5.
alpha	(optional) value for the α parameter if using upper or lower C.I. methods; default is 0.05.
manualVmax	(optional) Character name of column in traj storing user input column of vmax values (typically call the column dynVmax).
vmaxtrunc	(optional) due to irregular sampling intervals, or errors in GPS location, or other effects, the calculation of the vmax parameter through the statistical methods outlined above can be heavily influenced by high outliers. Thus, it may be useful to exclude those segments from calculation of the dynamic Vmax parameter. Default is NA.

Details

The function dynvmax represents an intermediary function used to extend and improve upon an existing PPA home range method (Long and Nelson, 2012) as described in the paper (Long and Nelson, 2014). Four options are available for computing the vmax parameter dynamically and are passed into the dynvmax function using dynamic option.

1) NA – if dynamic = 'NA' (the default) the function estimates the original, non-dynamic estimate of Vmax which is a global estimate, as per Long & Nelson (2012).
2) focal – a moving window approach whereby a window of size w is moved along the trajectory and vmax computed dynamically within each window and assigned to the central segment.
3) cumulative – A moving window of size w is again used, only in this case the value is assigned to the end segment. This represents the vmax calculation of the previous w segments.
4) class – A priori analysis (e.g., obtained via state-space models, or from expert knowledge) is used to identify discrete behavioural states in the telemetry data and these stored in a column which is then passed into the function.

The class method is the preferred choice, as it allows the use of more sophisticated models for identifying behavioural shifts in telemetry data where we would expect to see clear differences in the Vmax parameter based on changing movement behaviour.

The use of the 'focal' or 'cumulative' dynamic methods uses a moving window approach, which is sensitive to edge effects at the initial and ending times of the trajectory. Thus, the dynamic Vmax parameter is only computed for those segments that have a valid window and the dataset is shrunk by w-1 segments.

Value

This function returns the original traj object with a new column – dynVmax in the infolocs dataframe containing the dynamic vmax parameter for each trajectory segment.

References

Long, JA, Nelson, TA. (2012) Time geography and wildlife home range delineation. Journal of Wildlife Management. 76(2):407-413.

Long, JA, Nelson, TA. (2015) Home range and habitat analysis using dynamic time geography. Journal of - Wildlife Management. 79(3):481-490.

Robson, DS, Whitlock, JH. (1964) Estimation of a truncation point. Biometrika 51:33-39.

van der Watt, P. (1980) A note on estimation bounds of random variables. Biometrika 67(3):712-714.

See Also

dynppa

Examples

data(m3)
m3R <- dynvmax(m3,dynamic='focal',method='Robson')
m3V <- dynvmax(m3,dynamic='focal',method='vanderWatt')
m3c <- dynvmax(m3,dynamic='cumulative')

jedalong/wildlifeTG documentation built on July 17, 2019, 2:52 p.m.