A User Manual for GeoPressureR

Learn how to use GeoPressureR with a Swainson’s Warbler and a Great Reed Warbler.

Introduction

Determining the positions, and over time trajectories, of wildlife is crucial to apprehend ecological relationships in nature. Since satellite devices (e.g. GPS) are too heavy for most bird species, lightweight geolocators remain an essential tool to track bird movement.

Geolocation by pressure provides an exciting opportunity to determine the position of birds with high precision using small tracking devices.

Indeed, as atmospheric pressure varies in space and time, a timeseries of pressure measurement recorded at a single location constitutes a unique signature which can be used for global positioning.

The GeoPressure suite helps users tackle the challenges of geolocation by pressure and provides a toolkit to implement two methods published in the following two papers:

• Nussbaumer, Gravey, Briedis, and Liechti (2023) presents the method to estimate a map of likely positions from a pressure timeseries,
• Nussbaumer, Gravey, Briedis, Liechti, and Sheldon (2023) describes a new approach to reconstruct the full trajectory of a bird quickly and accurately, using pressure and wind data.

For a quick overview of the method, here is a 10 min presentation:

Data requirements

The only strict requirement is that your geolocator provides a continuous timeseries of pressure (<1hr resolution). Beyond this, here are a few things that can help:

• GeoPressureR works best for species with a clear separation between stationary and migratory periods, as opposed to birds moving continuously over time and/or gradually over large distances (10-50km) or altitude (>10m). As such, aerial feeders such as swifts or bee-eaters or mountainous species do not lend themselves well to this method.
• Acceleration data can be helpful to define the periods of flight, especially if your bird flies at low altitude or if pressure data is measured on a coarse temporal resolution (>15min).
• Light data can accelerate building the trajectory model by allowing to quickly narrow down possible locations during short stationary periods. Generally, for species with few long stopover, light data brings limited benefit, but it can be quite helpful for species with multiple short stopovers, and particularly if migrating on a east/west trajectory.
• Knowing the equipment and retrieval sites can also be helpful, but it also works well without it.

GeoPressureR can currently read Swiss Ornithological Institute (SOI) files (*.pressure, *.lux, *.acceleration), Migrate Technology files ("*.deg" and "*.lux") and Lund CAnMove ("*.xlsx").

Feel free to contact me to discuss your data and study species.

The GeoPressure suite

The GeoPressure suite includes several tools:

• GeoPressureR is the main R package with functions to run the analysis.
• GeoPressureManual is the official user guide developed to help you learn to use GeoPressureR.
• GeoPressureTemplate is a template Github repository to help kickstart your project.
• GeoPressureAPI is the JSON API used by GeoPressureR under the hood to query the ERA5 reanalysis data with Google Earth Engine.
• GeoPressureViz is a shiny app included in GeoPressureR to visualize the trajectory of your bird. See the [GeoPressureViz] chapter for an introduction and the demo for 18LX.

Structure of the manual

This manual provides an easy entry point into pressure positioning. It includes three parts:

• The basic tutorial runs through the entire workflow using a simple track of pressure only, with the example of a Swainson’s Warbler.
• The advanced tutorial explores additional functionalities of the package using light, acceleration, and wind data, through the example of a Great Reed Warbler.
• Labelling tools introduces labelling, a critical step in the workflow. This is a complex procedure requiring a comprehensive understanding of the method and tools of the package, which is why it is described in more depth after the basic and advanced tutorials. We strongly recommended reading this section attentively for optimal results.

Feel free to read through the manual, or to fork the repository to run the examples at your own pace.

Code structure

GeoPressureTemplate defines a standard folder structure to improve readability, sharability, and reproducibility. The structure follows the standard recommendation of separating data and analysis (see Cookiecutter Data Science , rrrpkg or rrtools for the rationale behind this). This manual follows this same standard directory and file name.

Installation

The best way to install the GeoPressureR package is through Github:

install.packages("devtools")
devtools::install_github("Rafnuss/GeoPressureR")

We can then load the package:

library(GeoPressureR)

Nussbaumer, Raphaël, Mathieu Gravey, Martins Briedis, and Felix Liechti. 2023. “Global positioning with animal‐borne pressure sensors.” Methods in Ecology and Evolution, January. https://doi.org/10.1111/2041-210X.14043.

Nussbaumer, Raphaël, Mathieu Gravey, Martins Briedis, Felix Liechti, and Daniel Sheldon. 2023. “Reconstructing bird trajectories from pressure and wind data using a highly optimized hidden Markov model.” Methods in Ecology and Evolution 2023 (February): 1–12. https://doi.org/10.1111/2041-210X.14082.