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...
| Main Authors: | , , , , , |
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| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Published: |
figshare
2022
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.6084/m9.figshare.c.6142230.v1 https://springernature.figshare.com/collections/Wearable_reproductive_trackers_quantifying_a_key_life_history_event_remotely/6142230/1 |
| Summary: | 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 ... |
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