14  Resources

14.1 Mailing list

If you are actively using the package, we recommand subscribing to the mailing list to be aware of bugs, issue and improvements.

14.2 Projects using GeoPressureR

You can find below the list of all research projects using GeoPressureR with links to the code used to analyse and create figures. This might be helpful to get an idea of how to analyse your data and borrow some code sections for your own project. Feel free to contact me if you’d like to add your project to this list.

Data & code

  • Mongolian Nightjar DOI
  • Northern Wheatear DOI
  • Woodland Kingfisher
  • Swainson’s Warbler
  • Siberian Rubythroat
  • Red-capped Robin-chat and Mangrove Kingfisher

Data only

  • Lesser Grey Shrike DOI
  • Barred Warbler DOI

Data (not using GeoPressureR)

  • European Starling DOI
  • Tawny Pipit DOI
  • Great Reed Warbler DOI

14.3 Main Publications

Nussbaumer, R., Gravey, M., Briedis, M., & Liechti, F. (2023). Global positioning with animal-borne pressure sensors. Methods in Ecology and Evolution, 14, 1104–1117. https://doi.org/10.1111/2041-210X.14043

Nussbaumer, R., Gravey, M., Briedis, M., Liechti, F. & Sheldon, D. (2023) Reconstructing bird trajectories from pressure and wind data using a highly optimised hidden Markov model. Methods in Ecology and Evolution, 14, 1118–1129. https://doi.org/10.1111/2041-210X.14082

Rhyne, G. S., Stouffer P. C., Briedis, M., Nussbaumer, R. (2024). Barometric geolocators can reveal unprecedented details about the migratory ecology of small birds. Ornithology. https://doi.org/10.1093/ornithology/ukae010

14.4 Presentations

Raphaël Nussbaumer. GeoPressureR: Introduction and case studies. August 2023. 14th European Ornithologicals’ Union Congress. PRESENTATION available as PDF.

Raphaël Nussbaumer, Colin Jackson, Lennox Kirao, Felix Liechti. The potential of multi-sensor geolocators to study short-distance Afrotropical migrants. November 2022. 15th Pan-African Ornithological Congress. PRESENTATION available as PDF.

Raphaël Nussbaumer, Mathieu Gravey, Martins Briedis, Felix Liechti. Leveraging light, pressure, activity, and wind data to improve geolocator positioning. August 2022. 28th International Ornithological Congress. PRESENTATION available at Youtube and as PDF.

Raphaël Nussbaumer, Mathieu Gravey, Felix Liechti. Improving the spatial accuracy of multi-sensor geolocators’ position using atmospheric surface pressure. October 2021. 7th International Bio-logging Science Symposium. PRESENTATION available at Youtube and as PDF.

14.5 References

Allard, Denis, A. Comunian, and Philippe Renard. 2012. “Probability Aggregation Methods in Geoscience.” Mathematical Geosciences 44 (July): 545–81. https://doi.org/10.1007/s11004-012-9396-3.
Basson, Marinelle, Mark V. Bravington, Jason R. Hartog, and Toby A. Patterson. 2016. “Experimentally Derived Likelihoods for Light-Based Geolocation.” Methods in Ecology and Evolution 7 (August): 980–89. https://doi.org/10.1111/2041-210X.12555.
Bindoff, Aidan D., Simon J. Wotherspoon, Christophe Guinet, and Mark A. Hindell. 2018. “Twilight‐free Geolocation from Noisy Light Data.” Edited by David Orme. Methods in Ecology and Evolution 9 (May): 1190–98. https://doi.org/10.1111/2041-210X.12953.
Copernicus Climate Change Service. 2018. “ERA5 Hourly Data on Pressure Levels from 1940 to Present.” Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/CDS.BD0915C6.
———. 2019. “ERA5-Land Hourly Data from 1950 to Present.” Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/CDS.E2161BAC.
Lisovski, Simeon, Silke Bauer, Martins Briedis, Sarah C. Davidson, Kiran L. Dhanjal‐Adams, Michael T. Hallworth, Julia Karagicheva, et al. 2020. “Light‐level Geolocator Analyses: A User’s Guide.” Edited by Garrett Street. Journal of Animal Ecology 89 (January): 221–36. https://doi.org/10.1111/1365-2656.13036.
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.
Patterson, Toby A., Len Thomas, Chris Wilcox, Otso Ovaskainen, and Jason Matthiopoulos. 2008. “State-space models of individual animal movement.” Trends in Ecology and Evolution 23 (2): 87–94. https://doi.org/10.1016/j.tree.2007.10.009.
Tobias, Joseph A., Catherine Sheard, Alex L. Pigot, Adam J. M. Devenish, Jingyi Yang, Ferran Sayol, Montague H. C. Neate-Clegg, et al. 2022. “AVONET: Morphological, Ecological and Geographical Data for All Birds.” Edited by Tim Coulson. Ecology Letters 25 (3): 581–97. https://doi.org/10.1111/ele.13898.