Automated image-based tracking and its application in ecology
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The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.
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DELL, Anthony I., John A. BENDER, Kristin BRANSON, Iain D. COUZIN, Gonzalo G. DE POLAVIEJA, Lucas P. J. J. NOLDUS, Alfonso PÉREZ-ESCUDERO, Pietro PERONA, Andrew D. STRAW, Martin WIKELSKI, Ulrich BROSE, 2014. Automated image-based tracking and its application in ecology. In: Trends in Ecology & Evolution. 2014, 29(7), pp. 417-428. ISSN 0169-5347. eISSN 1872-8383. Available under: doi: 10.1016/j.tree.2014.05.004BibTex
@article{Dell2014Autom-29414, year={2014}, doi={10.1016/j.tree.2014.05.004}, title={Automated image-based tracking and its application in ecology}, number={7}, volume={29}, issn={0169-5347}, journal={Trends in Ecology & Evolution}, pages={417--428}, author={Dell, Anthony I. and Bender, John A. and Branson, Kristin and Couzin, Iain D. and de Polavieja, Gonzalo G. and Noldus, Lucas P. J. J. and Pérez-Escudero, Alfonso and Perona, Pietro and Straw, Andrew D. and Wikelski, Martin and Brose, Ulrich} }
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