Introduction

Understanding the temporal and spatial use of habitats by wildlife is crucial to apprehend ecological relationships in nature. Tracking small birds and bats requires tags of less than 2g, therefore lightweight geolocators are currently the most affordable and widespread option. Recent multi-sensor geolocators now capture accelerometer and pressure data in addition to light, offering new potential to refine the accuracy of bird positioning. In particular, as atmospheric pressure varies with space and time, pressure timeseries at a single location have a unique signature which can be used for global positioning independent of light recordings.

0.1 What can you do with GeoPressureR?

This package can be broken down in two parts:

  1. Convert a pressure timeserie into probability map(s) of positions. The corresponding steps are described in the chapter Pressure map of this manual, and the corresponding publication is Raphaël Nussbaumer et al.1
  2. Produce a trajectory model integrating pressure, light, movement and wind data. The methodology to achieve this is covered in chapters Basic graph and Wind graph and the corresponding publication is Raphaël Nussbaumer et al.2

For a quick overview, here is a 10 min presentation which presents the motivation, provides an overview of the method and illustrates possible results.

0.2 What do you need to use GeoPressureR?

In order to be able to use GeoPressureR, you will need at minimum a timeserie of pressure measurements with a minimal temporal resolution of 1hr. Accelerometer and light data are optional.

GeoPressureR works best for species with a clear separation of stationary and migratory periods, as opposed to birds moving continuously and gradually over large distances (10-50km) or altitude (>10m). As such, areal 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 if your bird flies at low altitude or if pressure data is measured on a coarse temporal resolution (>5min).

Light data can also be helpful to speed-up the building of the trajectory modeling by allowing to quickly narrow down possible locations during short stationary periods.

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

0.3 The GeoPressure suite

The GeoPressure suite includes several tools:

0.4 Installation

To start, install the GeoPressureR package from Github using the following line:

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

We will be needing some additional packages which can be installed from DESCRIPTION with

devtools::install()

Finally, we can load them with

library(GeoPressureR)

# Only used for some visualization. The code to compute the light position is included in `GeoPressureR`
library(GeoLocTools)
setupGeolocation()

# ERA5 data download library
library(ecmwfr)

# Graph library 
library(igraph)

# Plotting library
library(ggplot2)
library(gridExtra)
library(plotly)
library(RColorBrewer)

# Interactif figure library
library(leaflet)
library(leaflet.extras)
library(moveVis)