Taking movement data to new depths: Inferring prey availability and patch profitability from seabird foraging behavior.

ABSTRACT: Detailed information acquired using tracking technology has the potential to provide accurate pictures of the types of movements and behaviors performed by animals. To date, such data have not been widely exploited to provide inferred information about the foraging habitat. We collected data using multiple sensors (GPS, time depth recorders, and accelerometers) from two species of diving seabirds, razorbills (Alca torda, N = 5, from Fair Isle, UK) and common guillemots (Uria aalge, N = 2 from Fair Isle and N = 2 from Colonsay, UK). We used a clustering algorithm to identify pursuit and catching events and the time spent pursuing and catching underwater, which we then used as indicators for inferring prey encounters throughout the water column and response

SUBMITTER: Chimienti M 

PROVIDER: S-EPMC5723613 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature