TY  - INPR
A1  - Gottwald, Jannis
A1  - Royauté, Raphaël
A1  - Becker, Marcel
A1  - Geitz, Tobias
A1  - Höchst, Jonas
A1  - Lampe, Patrick
A1  - Leister, Lea
A1  - Lindner, Kim
A1  - Maier, Julia
A1  - Rösner, Sascha
A1  - Schabo, Dana G.
A1  - Freisleben, Bernd
A1  - Brandl, Roland
A1  - Mueller, Thomas
A1  - Farwig, Nina
A1  - Nauss, Thomas
T1  - Classifying the activity states of small vertebrates using automated VHF telemetry
T2  - bioRxiv
N2  - The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/73037
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-730378
IS  - 2022.03.22.485147
ER  -