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Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

van der Wal, René; Zeng, Cheng; Heptinstall, Danny; Ponnamperuma, Kapila; Mellish, Chris; Ben, Stuart and Siddharthan, Advaith (2015). Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites. Ambio, 44(Suppl 4) pp. 612–623.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1007/s13280-015-0711-3
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Abstract

Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Such delayed reporting does reduce the usefulness of such data for nature conservation when timely information about animal movements is required. To counter this problem we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (comprising speed of movement and turning angle calculated from fixes), allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data Automating the detection of both excursions and home range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal to inform conservationists and wider audiences. We recommend automated analysis, interpretation and communication of satellite tag and other ecological data to advance nature conservation research and practice.

Item Type: Journal Item
Copyright Holders: 2015 The Authors
ISSN: 1654-7209
Project Funding Details:
Funded Project NameProject IDFunding Body
Digital Economy Research HubEP/G066051/1RCUK
Keywords: Automated home-range calculation; Red kite reintroduction; Satellite-tag data; Science communication
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 51048
Depositing User: Advaith Siddharthan
Date Deposited: 21 Sep 2017 08:24
Last Modified: 08 Dec 2018 01:54
URI: http://oro.open.ac.uk/id/eprint/51048
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