Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks

Abstract Background Fine-scale data on animal position are increasingly enabling us to understand the details of movement ecology and dead-reckoning, a technique integrating motion sensor-derived information heading speed, can be used reconstruct fine-scale paths at sub-second resolution, irrespective environment. On its own however, dead-reckoning process is prone cumulative errors, so that estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location (e.g., global positioning technology) correct for this drift between Verified Positions (VPs). We present step-by-step instructions implementing Position Correction (VPC) in R using tilt-compensated compass method, accompanied by mathematical protocols underlying code improvements extensions reduce trade-off VPC rate accuracy. These all built into user-friendly, fully annotated function; Gundog.Tracks , multi-functionality across terrestrial, aquatic, aerial systems, provided within Additional file 4 as well online (GitHub). Results The function demonstrated three contrasting model species (the African lion Panthera leo Magellanic penguin Spheniscus magellanicus Imperial cormorant Leucocarbo atriceps ) moving land, water air. show effect uncorrected errors speed estimations, inaccuracies infrequent demonstrate how these issues addressed. Conclusions will allow anyone familiar dead-reckon tracks readily accurately, key complex dealt . This help community consider implement valuable, but often overlooked method reconstructing high-resolution diverse systems without requiring bespoke application.