Learn R Programming

marcher

Migration and Range Change Estimation in R

The marcher package provides functions and tools for mechanistic range shift analysis decribed in Gurarie et al. (in press). The methods are designed to estimate parameters of range shifting, including coordinates of the centroids of (2 or 3) ranges, the times of initiation and duration of each shift, ranging areas and time scales of location and velocity autocorrelation. Because the estimates are likelihood based, there are several handy inferential tools including confidence intervals around all estimates and a sequence of hypothesis tests, including: (a.) What is the appropriate (highest) level of autocorrelation in the data? (b.) Is an estimated range shift significant? (c.) Is there a stop-over during the migration? (d.) Is a return migration a strict return migration?

The vignette introduces the family of range shift models and illustrates methods to simulate, visualize, estimate and conduct the hypothesis tests.

References

Gurarie, E., Francesca, C., Peters, W., Fleming, C., Calabrese, J., Müller, T., & Fagan, W. (in press) A framework for modeling range shifts and migrations: Asking whether, whither, when, and will it return. Journal of Animal Ecology.

Copy Link

Version

Install

install.packages('marcher')

Monthly Downloads

196

Version

0.0-2

License

GPL-2

Maintainer

Eliezer Gurarie

Last Published

April 12th, 2017

Functions in marcher (0.0-2)

simulate_shift

Simulate MOUF process
test_rangeshift

Range shift hypothesis tests
Michela

Movement track of Michela, a roe deer
SimulatedTracks

Simulated range shift tracks
scan_track

scan_track
selectModel

Select residual model
getRSI

Compute Range Shift Index
getTau

Compute time scale parameters
getArea

Compute area
getCov

Estimation Helper Functions
estimate_shift

Estimating range shifts
fitNSD

Test range shift using net-squared displacement
locate_shift

Interactive locating of range shifting
marcher-package

Migration and Range Change Analysis in R
getLikelihood

Estimate likelihoods and AICs
getMu

Obtain mean vector for a range shift process
plot.shiftfit

Plot results of an range-shift fit
quickfit

Quick fit of one-step migration