Simultaneous estimation of the temporal and spatial extent of animal migration using step lengths and turning angles.

Autor: Thompson PR; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada. pt1@ualberta.ca., Harrington PD; Department of Mathematics, University of British Columbia, Vancouver, BC, Canada.; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada., Mallory CD; Inuit Tapiriit Kanatami, Ottawa, ON, Canada., Lele SR; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada., Bayne EM; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada., Derocher AE; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada., Edwards MA; Office of the Chief Scientist, Environment and Protected Areas, Government of Alberta, Edmonton, AB, Canada.; Department of Renewable Resources, University of Alberta, Edmonton, AB, Canada., Campbell M; Government of Nunavut, Iqaluit, NU, Canada., Lewis MA; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada.; Department of Biology, University of Victoria, Victoria, BC, Canada.; Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada.
Jazyk: angličtina
Zdroj: Movement ecology [Mov Ecol] 2024 Jan 08; Vol. 12 (1), pp. 1. Date of Electronic Publication: 2024 Jan 08.
DOI: 10.1186/s40462-023-00444-8
Abstrakt: Background: Animals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements.
Methods: We designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by change-points in step length and turning angle distributions. To this end, we can also use the model to estimate how an animal's movement changes when it begins migrating. In addition to a thorough simulation analysis, we tested our model on three datasets: migratory ferruginous hawks (Buteo regalis) in the Great Plains, barren-ground caribou (Rangifer tarandus groenlandicus) in northern Canada, and non-migratory brown bears (Ursus arctos) from the Canadian Arctic.
Results: Our simulation analysis suggests that our model is most useful for datasets where an increase in movement speed or directional autocorrelation is clearly detectable. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bears. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how they migrated; ferruginous hawks achieved efficient migrations by drastically increasing their movement rates while caribou migration was achieved through significant increases in directional persistence.
Conclusions: Our approach is applicable to many animal movement studies and includes parameters that can facilitate comparison between different species or datasets. We hope that rigorous assessment of migration metrics will aid understanding of both how and why animals move.
(© 2024. The Author(s).)
Databáze: MEDLINE
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