Behavioral classification of low-frequency acceleration and temperature data from a free-ranging small mammal.

ABSTRACT: The miniaturization and affordability of new technology is driving a biologging revolution in wildlife ecology with use of animal-borne data logging devices. Among many new biologging technologies, accelerometers are emerging as key tools for continuously recording animal behavior. Yet a critical, but under-acknowledged consideration in biologging is the trade-off between sampling rate and sampling duration, created by battery- (or memory-) related sampling constraints. This is especially acute among small animals, causing most researchers to sample at high rates for very limited durations. Here, we show that high accuracy in behavioral classification is achievable when pairing low-frequency acceleration recordings with temperature. We conducted 84 hr of direct behavioral observations on 6

SUBMITTER: Studd EK 

PROVIDER: S-EPMC6342100 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature