Optimising sample sizes for animal distribution analysis using tracking data
Limpus, Colin J.
Hays, Graeme C.
Wildermann, Natalie E.
Duarte, Carlos M.
Meekan, Mark G.
KAUST DepartmentRed Sea Research Center (RSRC)
Biological and Environmental Sciences and Engineering (BESE) Division
Marine Science Program
Embargo End Date2021-10-09
Permanent link to this recordhttp://hdl.handle.net/10754/665593
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Abstract1. Knowledge of the spatial distribution of populations is fundamental to management plans for any species. When tracking data are used to describe distributions, it is sometimes assumed that the reported locations of individuals delineate the spatial extent of areas used by the target population. 2. Here, we examine existing approaches to validate this assumption, highlight caveats, and propose a new method for a more informative assessment of the number of tracked animals (i.e. sample size) necessary to identify distribution patterns. We show how this assessment can be achieved by considering the heterogeneous use of habitats by a target species using the probabilistic property of a utilisation distribution. Our methods are compiled in the R package SDLfilter. 3. We illustrate and compare the protocols underlying existing and new methods using conceptual models and demonstrate an application of our approach using a large satellite tracking data-set of flatback turtles, Natator depressus, tagged with accurate Fastloc-GPS tags (n = 69). 4. Our approach has applicability for the post-hoc validation of sample sizes required for the robust estimation of distribution patterns across a wide range of taxa, populations and life history stages of animals.
CitationShimada, T., Thums, M., Hamann, M., Limpus, C. J., Hays, G. C., FitzSimmons, N., … Meekan, M. G. (2020). Optimising sample sizes for animal distribution analysis using tracking data. Methods in Ecology and Evolution. doi:10.1111/2041-210x.13506
SponsorsWe thank staff and field team leaders of the Queensland Turtle Conservation Project within Queensland Parks and Wildlife Service, Hector Barrios Garrido, Miles Yeates, Rebecca Hide, Renee Whitchurch and numerous volunteers for their support of research.
This research was funded by Gladstone Port Corporation (partially funded by the Ecosystem Research and Monitoring Program), Shell’s QGC Business, Australia Pacific LNG, Santos GLNG, James Cook University and DES.
JournalMethods in Ecology and Evolution