Wilson Kenady, Littnan Charles, Halpin Patrick, Read Andrew
Duke University Marine Lab , 135 Duke Marine Lab Rd, Beaufort, NC 28516 , USA.
Pacific Island Fisheries Science Center , 1845 WASP Blvd., Building 176, Honolulu, HI 96818 , USA.
R Soc Open Sci. 2017 Mar 8;4(3):160703. doi: 10.1098/rsos.160703. eCollection 2017 Mar.
The objective of this research was to investigate and describe the foraging behaviour of monk seals in the main Hawaiian Islands. Specifically, our goal was to identify a metric to classify foraging behaviour from telemetry instruments. We deployed accelerometers, seal-mounted cameras and GPS tags on six monk seals during 2012-2014 on the islands of Molokai, Kauai and Oahu. We used pitch, calculated from the accelerometer, to identify search events and thus classify foraging dives. A search event and consequent 'foraging dive' occurred when the pitch was greater than or equal to 70° at a depth less than or equal to -3 m. By integrating data from the accelerometers with video and GPS, we were able to ground-truth this classification method and identify environmental variables associated with each foraging dive. We used Bayesian logistic regression to identify the variables that influenced search events. Dive depth, body motion (mean overall dynamic body acceleration during the dive) and proximity to the sea floor were the best predictors of search events for these seals. Search events typically occurred on long, deep dives, with more time spent at the bottom (more than 50% bottom time). We can now identify where monk seals are foraging in the main Hawaiian Islands (MHI) and what covariates influence foraging behaviour in this region. This increased understanding will inform management strategies and supplement outreach and recovery efforts.
本研究的目的是调查和描述夏威夷主要岛屿上僧海豹的觅食行为。具体而言,我们的目标是确定一种指标,用于根据遥测仪器对觅食行为进行分类。2012年至2014年期间,我们在莫洛凯岛、考艾岛和瓦胡岛上的六只僧海豹身上部署了加速度计、海豹佩戴式摄像头和GPS标签。我们利用从加速度计计算得出的俯仰角来识别搜索事件,从而对觅食潜水进行分类。当俯仰角在深度小于或等于-3米时大于或等于70°时,就会发生一次搜索事件以及随之而来的“觅食潜水”。通过将加速度计的数据与视频和GPS数据相结合,我们能够验证这种分类方法,并识别与每次觅食潜水相关的环境变量。我们使用贝叶斯逻辑回归来识别影响搜索事件的变量。潜水深度、身体运动(潜水期间的平均总体动态身体加速度)以及与海底的接近程度是这些海豹搜索事件的最佳预测指标。搜索事件通常发生在长时间的深潜过程中,在海底停留的时间更长(底部停留时间超过50%)。我们现在能够确定僧海豹在夏威夷主要岛屿(MHI)的觅食地点,以及哪些协变量会影响该地区的觅食行为。这种进一步的了解将为管理策略提供信息,并补充宣传和恢复工作。