fbtgUD: Field-based Time Geography Utilization Distribution

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

Description

Calculate the utilization distribution of an animal using the field-based time geographic model.

Usage

fbtgUD(traj, tl, timefun = "inverse", c2 = 1, sigma = 0, k = 100,
  clipPPS = TRUE, d.min = 0, dt.max = Inf)

Arguments

traj	animal movement trajectory in the form of an ltraj object, see package adehabitatLT
tl	a TransitionLayer object
timefun	method for convertingtime into probability; one of: – 'inverse' = \frac{1}{c_2 * t}, – 'inverse2' = \frac{1}{(c_2 * t)^2}, – 'exp' = \exp{-c_2 * t}, – 'norm' = \exp{-c_2 * t^2}, – 'rootexp' = \exp{-c_2 * √{t}}, – 'pareto' = \exp{-c_2 * \log{t}}, – 'lognorm'= \exp{-c_2 * \log{t^2}}.
c2	Parameter input into timefun (see likec2) default=1.
sigma	locational uncertainty parameter for Guassian error kernel, default=0.
k	number of time slices between fixes upon which to estimate the UD, default=100.
clipPPS	(logical) whether or not the output probabilities should be clipped to the potential path space, default=TRUE.
d.min	minimum distance, below which the segment is removed from analysis. Can be used to focus the UD on only longer movement segments. Default is the pixel size of surf.
dt.max	maximum time, above which the segment is removed from analysis. Can be used to remove segments with missing data from analysis, as segments with a very long time between fixes can be problematic in time geographic analysis.

Details

Calculates the field-based time geography utilization distribution (UD) for an animal. Field-based time geography is based on an underlying resistance surface, which constratins potential movement by the animal between two location fixes. This model is applied recursively over an entire trajectory in order to compute a UD for an animal. The UD inherently considers the movement limitations described by the underlying resistance surface, and thus is considered a landscape-based model for a UD. The landscape-based approach deviates from current models building upon random walks and diffusion processes.
The model requires that the resistance surface be directly related to an animals speed of passing through that environment.
The timefun parameter is used to choose the model for converting time into a probability based on the described function. The c2 parameter can be used to tune these functions based on some fine-scale movement data if available, but defaults to a value of 1. The sigma parameter represents the locational uncertainty, which can be interpreted as the standard deviation of the location error in a similar fashion to what is done in Brownian bridge models. The parameter k, which defines how many 'time slices' are to be computed, has the most significant influence on computational time. Lower values for k will speed up computations, but result in less-smooth output UD surfaces.

Value

This function returns a RasterLayer which can be used to estimate the UD of an animal.

See Also

dynppa, estc2, fbtgTS, volras

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