Wearable reproductive trackers: quantifying a key life history event remotely ...
Abstract Advancements in biologging technology allow terabytes of data to be collected that record the location of individuals but also their direction, speed and acceleration. These multi-stream data sets allow researchers to infer movement and behavioural patterns at high spatiotemporal resolution...
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Online Access: | https://dx.doi.org/10.6084/m9.figshare.c.6142230 https://springernature.figshare.com/collections/Wearable_reproductive_trackers_quantifying_a_key_life_history_event_remotely/6142230 |
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ftdatacite:10.6084/m9.figshare.c.6142230 2024-04-28T08:10:24+00:00 Wearable reproductive trackers: quantifying a key life history event remotely ... Ozsanlav-Harris, Luke Griffin, Larry R. Weegman, Mitch D. Cao, Lei Hilton, Geoff M. Bearhop, Stuart 2022 https://dx.doi.org/10.6084/m9.figshare.c.6142230 https://springernature.figshare.com/collections/Wearable_reproductive_trackers_quantifying_a_key_life_history_event_remotely/6142230 unknown figshare Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Genetics FOS Biological sciences Biotechnology Evolutionary Biology Ecology Biological Sciences not elsewhere classified Science Policy Plant Biology Collection article 2022 ftdatacite https://doi.org/10.6084/m9.figshare.c.6142230 2024-04-02T12:06:10Z Abstract Advancements in biologging technology allow terabytes of data to be collected that record the location of individuals but also their direction, speed and acceleration. These multi-stream data sets allow researchers to infer movement and behavioural patterns at high spatiotemporal resolutions and in turn quantify fine-scale changes in state along with likely ecological causes and consequences. The scope offered by such data sets is increasing and there is potential to gain unique insights into a suite of ecological and life history phenomena. We use multi-stream data from global positioning system (GPS) and accelerometer (ACC) devices to quantify breeding events remotely in an Arctic breeding goose. From a training set of known breeders we determine the movement and overall dynamic body acceleration patterns indicative of incubation and use these to classify breeding events in individuals with unknown reproductive status. Given that researchers are often constrained by the amount of biologging data ... Article in Journal/Newspaper Arctic DataCite Metadata Store (German National Library of Science and Technology) |
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DataCite Metadata Store (German National Library of Science and Technology) |
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topic |
Genetics FOS Biological sciences Biotechnology Evolutionary Biology Ecology Biological Sciences not elsewhere classified Science Policy Plant Biology |
spellingShingle |
Genetics FOS Biological sciences Biotechnology Evolutionary Biology Ecology Biological Sciences not elsewhere classified Science Policy Plant Biology Ozsanlav-Harris, Luke Griffin, Larry R. Weegman, Mitch D. Cao, Lei Hilton, Geoff M. Bearhop, Stuart Wearable reproductive trackers: quantifying a key life history event remotely ... |
topic_facet |
Genetics FOS Biological sciences Biotechnology Evolutionary Biology Ecology Biological Sciences not elsewhere classified Science Policy Plant Biology |
description |
Abstract Advancements in biologging technology allow terabytes of data to be collected that record the location of individuals but also their direction, speed and acceleration. These multi-stream data sets allow researchers to infer movement and behavioural patterns at high spatiotemporal resolutions and in turn quantify fine-scale changes in state along with likely ecological causes and consequences. The scope offered by such data sets is increasing and there is potential to gain unique insights into a suite of ecological and life history phenomena. We use multi-stream data from global positioning system (GPS) and accelerometer (ACC) devices to quantify breeding events remotely in an Arctic breeding goose. From a training set of known breeders we determine the movement and overall dynamic body acceleration patterns indicative of incubation and use these to classify breeding events in individuals with unknown reproductive status. Given that researchers are often constrained by the amount of biologging data ... |
format |
Article in Journal/Newspaper |
author |
Ozsanlav-Harris, Luke Griffin, Larry R. Weegman, Mitch D. Cao, Lei Hilton, Geoff M. Bearhop, Stuart |
author_facet |
Ozsanlav-Harris, Luke Griffin, Larry R. Weegman, Mitch D. Cao, Lei Hilton, Geoff M. Bearhop, Stuart |
author_sort |
Ozsanlav-Harris, Luke |
title |
Wearable reproductive trackers: quantifying a key life history event remotely ... |
title_short |
Wearable reproductive trackers: quantifying a key life history event remotely ... |
title_full |
Wearable reproductive trackers: quantifying a key life history event remotely ... |
title_fullStr |
Wearable reproductive trackers: quantifying a key life history event remotely ... |
title_full_unstemmed |
Wearable reproductive trackers: quantifying a key life history event remotely ... |
title_sort |
wearable reproductive trackers: quantifying a key life history event remotely ... |
publisher |
figshare |
publishDate |
2022 |
url |
https://dx.doi.org/10.6084/m9.figshare.c.6142230 https://springernature.figshare.com/collections/Wearable_reproductive_trackers_quantifying_a_key_life_history_event_remotely/6142230 |
genre |
Arctic |
genre_facet |
Arctic |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.6084/m9.figshare.c.6142230 |
_version_ |
1797578292776140800 |