Chapter 8 References

  • Brlík, V, Koleček, J, Burgess, M, et al. Weak effects of geolocators on small birds: A meta‐analysis controlled for phylogeny and publication bias. J Anim Ecol. 2019; 00: 1– 14. https://doi.org/10.1111/1365-2656.12962.
  • Lisovski, S, Bauer, S, Briedis, M, et al. Light‐level geolocator analyses: A user’s guide. J Anim Ecol. 2019; 00: 1– 16. https://doi.org/10.1111/1365-2656.13036.
  • Lisovski, S. and Hahn, S. (2012), GeoLight – processing and analysing light‐based geolocator data in R. Methods Ecol Evol, 3: 1055-1059. doi:10.1111/j.2041-210X.2012.00248.x.
  • Lisovski, S., Sumner, M. D., & Wotherspoon, S. J. ( 2015). TwGeos: Basic data processing for light based geolocation archival tags. Github Repository, Retrieved from https://github.com/slisovski/TwGeos.
  • Wotherspoon, S. J., Sumner, D. A., & Lisovski, S. ( 2013b). R Package BAStag: Basic data processing for light based geolocation archival tags. GitHub Repository, Retrieved from https://github.com/SWotherspoon/BAStag.
  • Kranstauber, B. , Weinzierl, R. , Wikelski, M. and Safi, K. (2015), Global aerial flyways allow efficient travelling. Ecol Lett, 18: 1338-1345. doi:10.1111/ele.12528.
  • Pettorelli, N. et al. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. - Trends Ecol. Evol. 20: 503–510.
  • R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. S