movetrack: Model flight paths from radio-telemetry data

movetrack movetrack is an R package that provides simple functionality to estimate individual flight tracks from radio-telemetry data such as Motus using a hidden Markov model 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 Codeberg use devtools::install_git("https://codeberg.org/g-rppl/movetrack.git", ref = "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 Automated radio-telemetry provides a scalable, lightweight tracking solution for mobile animals, but existing localisation methods rely solely on receiver locations or offer only small-scale, site-specific estimates, limiting their ability to reconstruct full flight paths.movetrack estimates full flight paths by combining coarse geometric position estimates – based on antenna bearing and signal strength – with an hidden Markov model that accounts for measurement error, temporal gaps, and movement dynamics. This two-step process is implemented in the main function track(): 1. It first calculates point estimates based on antenna bearing and signal strength as described in Baldwin et al. (2018).2. The results are then passed to Stan and individual flights paths are estimated using a hidden Markov model Citing movetrack and related software When using movetrack, please cite the following publication: Rüppel, G., Karwinkel, T., Brust, V., Schmaljohann, H. (2026). movetrack: An R package to model flight paths from radio-telemetry networks. Methods in Ecology and Evolution, 17(4), 1069–1081. doi: 10.1111/2041-210x.70273 As movetrack is a high-level interface to Stan, please additionally cite Stan (see https://mc-stan.org/users/citations). 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