Abstract
Understanding animal movement and behaviour can aid spatial planning and
inform conservation management. However, it is difficult to directly
observe behaviours in remote and hostile terrain such as the marine
environment. Behaviours can be inferred from telemetry data using hidden
Markov models (HMMs), but model predictions are not typically validated
due to difficulty obtaining ‘ground truth’ behavioural information. We
investigate the accuracy of HMM-inferred behaviours by considering a
unique dataset provided by Joint Nature Conservation Committee. The data
consist of simultaneous proxy movement tracks of the boat (defined as
visual tracks as birds are followed by eye) and seabird behaviour
obtained at the same time-frequency by observers on the boat. We use
these data to assess whether (i) visual track is a good proxy for true
bird locations in relation to HMM-inferred behaviours, and (ii) inferred
behaviours from HMMs fitted to visual tracking data accurately represent
true behaviours as identified by behavioural observations taken from the
boat. We demonstrate that visual tracking data can be regarded as a good
proxy for true movement data of birds in terms of similarity in inferred
behaviours. Accuracy of HMMs ranging from 71% to 87% during
chick-rearing and 54% to 70% during incubation was generally
insensitive to model choice, even when AIC values varied substantially
across different models. Finally, we show that for foraging, a state of
primary interest for conservation purposes, identified missed foraging
bouts lasted for only a few seconds. We conclude that HMMs fitted to
tracking data can accurately identify important conservation-relevant
behaviours, demonstrated using visual tracking data. Therefore,
confidence in using HMMs for behavioural inference should increase even
when validation data are unavailable. This has important implications
for animal conservation, where the size and location of protected areas
are often informed by behaviours identified using HMMs fitted to
movement data.