ExMove

This toolkit is meant as an accessible introduction to analysing tracking data using R. We make use of the tidyverse collection and simple features (sf) packages to read, clean and process multiple data files, ready for a range of analyses. Go to the workflow script by clicking here, and view a fully worked example by clicking here.

Authors:

• Liam Langley 💃
• Stephen Lang
• Luke Ozsanlav-Harris 😵
• Alice Trevail 🏃

Don't want to use GitHub?

1. Download the entire repo as a zipped file here, or by using Code ▾ > Download ZIP above
2. Unzip the folder to the desired location on your machine (ExMove folder name can be changed to whatever you want)
3. Initiate the project opening the ExMove.Rproj file (which will open a new named instance of R Studio — which needs to be installed)
4. Open the Workflow.R file, and start by running on one of our three example datasets (currently RFB, but can be changed to RFB_IMM,TRPE, or GWFG)
5. To run analyses on your own data, start by copying a folder of data and metadata files into the Data folder (process described in User guide)
6. All outputs of this workflow (such as figures, summaries and processed data) are saved into folders of DataOutputs
7. If you run into issues when using your own data, the Documentation folder provides a User Guide and FAQ's for additional guidance

Do want to use GitHub?

1. Clone or fork this repo (for additional GitHub guidance see: setting up GitHub | cloning a repo | forking a repo | using GitHub with RStudio)
2. Start by opening the ExMove.Rproj file (which will open a new instance of R studio)
3. Open the Workflow.R file, and start by running on one of our three example datasets (currently RFB, but can be changed to RFB_IMM, TRPE, or GWFG)
4. If you want to run analyses on your own data, start by copying a folder of datafiles and metadata into Data (described in the Documentation/User guide.html file)
5. All outputs of this workflow (such as figures, summaries and processed data) are saved into separate folders of DataOutputs
6. If you run into issues when using your own data, the Documentation folder provides a User Guide and FAQ's for additional guidance

Repository overview

Main workflow

• R/Workflow.R - WIP file for cleaning tracking data
• app/Tracking data diagnostic app.R - Shiny app for exploring how data filters/cleaning/re-sampling influences the data and derived stats

Optional/troubleshooting scripts

• R/Optional_Processing_CP_trips.R - Code to process trips for central place data
• R/Optional_Processing_Resampling.R - Code to resample high-resolution data
• R/Optional_Processing_Segmentation.R - Code for segmenting gappy data
• R/Optional_Processing_gganimate.R - Code for animating tracking data
• R/Troubleshoot_Multiple_ID_columns.R - Code for troubleshooting data with multiple ID columns

Data Description

We provide four diffferent types of tracking data from three different species:

                     

Tracking data files

• Data/RFB - folder containing GPS tracking data files from three adult Red-footed boobies (Sula sula), from two populations
• Data/RFB_IMM - folder containing ARGOS tracking data files from two immature Red-footed boobies, from two populations
• Data/TRPE - folder containing GLS data from one Trindade petrel (Pteradroma arminjoniana)
• Data/GWFG - folder containing GPS tracking data files from four migrating Greenland White-fronted Geese (Anser albifrons flavirostris)

Metadata files

• Data/RFB_Metadata.csv - metadata file containing information on the adult Red-footed boobies dataset
• Data/RFB_IMM_Metadata.csv - metadata file containing information on the immature Red-footed boobies
• Data/TRPE_Metadata.csv - metadata file containing information on the Trindade petrel dataset
• Data/GWfG_Metadata.csv - metadata file containing information on the Greenland White-fronted Goose dataset
• Data/RFB_CPshape - folder containing shape files for central place of RFB data

Data and Code Archive

All data and code for this manuscript has been archived in a Zenodo digital repository and should be referenced using the following citation:

Langley, L.P., Lang, S.D.J., Ozsanlav-Harris, L., Trevail, A.M. (2024). Data and code from: ExMove: An open-source toolkit for processing and exploring animal tracking data in R. Zenodo digital repository. https://doi.org/10.5281/zenodo.10993581.