Application of GSM/GPRS technologies and accelerometry to the spatial ecology of the Canarian houbara bustard

Abstract

Data loggers, which incorporate Global Positioning System (GPS) and accelerometer (ACC) technologies, have enabled an important progress in the study of animal ecology. Using data from 53 Canarian houbara bustards (Chlamydotis undulata fuertaventurae) tagged with GSM/GPRS transmitters during the period 2017-2022 on the island of Lanzarote, Fuerteventura and La Graciosa, we describe how different behavioural patterns can be identified and classified using AcceleRater software and used to interpret their spatial ecology. Using AcceleRater we found that the best model to classify houbara bustards' behaviours is the one known as Radial Basis Function Kernel for Support Vector Machine (RBF SVM), which in our case offered an accuracy rate of 92.95 %, allowing the identification of seven types of behaviour (display run, vocalization, precopulatory movement, flight, foraging, resting and vigilance) of the ten behaviours assessed. In addition, the association of the ACC pattern with GPS locations allowed the identification of specific display and nesting sites, as well as the places where marked individuals foraged and rested. The present study shows how technological advances can offer clear advantages in understanding the spatial ecology of a species using detailed data from individuals, particularly in those with limited direct observation possibilities. This represents a great advance with respect to spatial ecology based on population results. We conclude that the data obtained are of great value in research, and may be key to improving the management and conservation of threatened species.