Individual-based tracking systems in Ornithology: welcome to the era of big data
Authors: Pascual LÓPEZ-LÓPEZ
Published: Volume 63.1, June 2016. Pages 103-136.
Technological innovations have led to exciting fast-moving developments in science. Today, we are living in a technology-driven era of biological discovery. Consequently, tracking technologies have facilitated dramatic advances in the fundamental understanding of ecology and animal behaviour. Major technological improvements, such as the development of GPS dataloggers, geolocators and other bio-logging technologies, provide a volume of data that were hitherto unconceivable. Hence we can claim that ornithology has entered the era of big data. In this paper, which is particularly addressed to undergraduate students and starting researchers in the emerging field of movement ecology, I summarise the current state of the art of individual-based tracking methods for birds as well as the most important challenges that, as a personal user, I consider we should address in future. To this end, I first provide a brief overview of individual tracking systems for birds. I then discuss current challenges for tracking birds with remote telemetry, including technological challenges (i.e., tag miniaturisation, incorporation of more bio-logging sensors, better efficiency in data archiving and data processing), as well as scientific challenges (i.e., development of new computational tools, investigation of spatial and temporal autocorrelation of data, improvement in environmental data annotation processes, the need for novel behavioural segmentation algorithms, the change from two to three, and even four, dimensions in the scale of analysis, and the inclusion of animal interactions). I also highlight future prospects of this research field including a set of scientific questions that have been answered by means of telemetry technologies or are expected to be answered in the future. Finally, I discuss some ethical aspects of bird tracking, putting special emphases on getting the most out of data and enhancing a culture of multidisciplinary collaboration among research groups.