g-rppl / movetrack

Estimate flight tracks from radio-telemetry data using a Hidden Markov Model.

movetrack

movetrack is an R package that provides simple functionality to estimate individual flight tracks from radio-telemetry data such as Motus using random walk models written in Stan.

Installation

You can install movetrack from the R Universe with

install.packages("movetrack", repos = c("https://g-rppl.r-universe.dev", getOption("repos")))

To instead install the latest development version of the package from GitHub use

devtools::install_github("g-rppl/movetrack@dev")

During the initial installation, make sure that the C++ toolchain required for CmdStan is set up properly. You can find more information here.

library(cmdstanr)
check_cmdstan_toolchain(fix = TRUE)

If not, go to https://mc-stan.org/docs/cmdstan-guide/cmdstan-installation.html#cpp-toolchain and follow the instructions for your platform. Once your toolchain is configured correctly CmdStan can be installed:

install_cmdstan(cores = 2)

Details

This package provides two main functions: locate() and track(). The first function calculates location estimates based on antenna bearing and signal strength. The second function estimates individual flight paths based on the estimated locations using a Hidden Markov Model written in Stan.

Getting started

You can find a quickstart example in the vignette movetrack_example.

References

Auger‐Méthé, M., Newman, K., Cole, D., Empacher, F., Gryba, R., King, A. A., ... & Thomas, L. (2021). A guide to state–space modeling of ecological time series. Ecological Monographs, 91(4), e01470. doi:10.1002/ecm.1470

Baldwin, J. W., Leap, K., Finn, J. T., & Smetzer, J. R. (2018). Bayesian state-space models reveal unobserved off-shore nocturnal migration from Motus data. Ecological Modelling, 386, 38-46. doi:10.1016/j.ecolmodel.2018.08.006

Jonsen, I. D., Flemming, J. M., & Myers, R. A. (2005). Robust state–space modeling of animal movement data. Ecology, 86(11), 2874-2880. doi:10.1890/04-1852

movetrack's Issues

Negative weights

Calculate weighted means from normalised signal strength.

include omnidirectional antennas

Include and handle omnidirectional antennas using the receiver position as mean location.

`locate()` returns NaN

If in a time interval the only signal equals the minimum signal strength (sig = 0), the weighted mean returns NaN.

Add map and plot functions

Add functionality to generate quick plots and maps