A protocol for using drones to assist monitoring of large breeding bird colonies

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Authors

Mitchell Lyons, Kate Brandis, John Wilshire, Nicholas Murray, Justin McCann, Richard Kingsford, Corey Thomas Callaghan

Abstract

Drones are rapidly becoming part of environmental monitoring and management applications. They provide an opportunity to improve a number of activities related to monitoring population dynamics of aggregations of wildlife. Bird surveys using drones have attracted particular attention, with a range of potential metrics able to be derived from high resolution drone imagery. Whilst a number of papers have shown that drone-based data can be used to effectively and accurately count and monitor features in bird colonies, the use of drone-derived data in real management and monitoring applications remains rare. This is in part due to a lack of clear guidelines as to the capability of drones and how to plan and successfully execute flights, but also due to a lack of information pertaining to specific target species and related contextual and environmental considerations. In this paper we outline a protocol for using drones to assist in the monitoring of colonies of breeding colonial waterbirds. We base the protocol on experience carrying out drone-based surveys of several colonies ranging in population from ~1000 to ~250,000 individuals. These are among the largest colonies ever surveyed via drone. We provide end-to-end guidelines, including detectability, flight planning and execution, on-ground data collection, image processing and target feature counting.

DOI

https://doi.org/10.32942/osf.io/p9j3f

Subjects

Animal Sciences, Behavior and Ethology, Biology, Ecology and Evolutionary Biology, Environmental Monitoring, Environmental Sciences, Life Sciences, Ornithology, Physical Sciences and Mathematics, Research Methods in Life Sciences, Zoology

Keywords

aerial vehicle, colonial, detection, population count, waterbird, wildlife

Dates

Published: 2019-04-29 06:16

Last Updated: 2019-04-29 06:32

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License

CC-By Attribution-ShareAlike 4.0 International