| dc.contributor.author | Broell, Franziska | en_US |
| dc.contributor.author | Noda, Takuji | en_US |
| dc.contributor.author | Wright, Serena | en_US |
| dc.contributor.author | Domenici, Paolo | en_US |
| dc.contributor.author | Steffensen, John Fleng | en_US |
| dc.contributor.author | Auclair, Jean-Pierre | en_US |
| dc.contributor.author | Taggart, Christopher T. | en_US |
| dc.date.accessioned | 2013-06-19T18:05:00Z | |
| dc.date.available | 2013-06-19T18:05:00Z | |
| dc.date.issued | 2013-04 | en_US |
| dc.identifier.citation | Broell, Franziska, Takuji Noda, Serena Wright, Paolo Domenici, et al. 2013. "Accelerometer tags: detecting and identifying activities in fish and the effect of sampling frequency." Journal of Experimental Biology 216(7): 1255-1264. | en_US |
| dc.identifier.issn | 0022-0949 | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1242/jeb.077396 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10222/27375 | |
| dc.description.abstract | Monitoring and measuring the behaviour and movement of aquatic animals in the wild is typically challenging, though micro-accelerometer (archival or telemetry) tags now provide the means to remotely identify and quantify behavioural states and rates such as resting, swimming and migrating, and to estimate activity and energy budgets. Most studies use low-frequency (30 Hz) accelerometer sampling be used in similar laboratory and field studies. If battery and/or data storage is limited, we also recommend archiving the events via an on-board algorithm that determines the highest likelihood and subsequent archiving of the various event classes of interest. | en_US |
| dc.relation.ispartof | Journal of Experimental Biology | en_US |
| dc.title | Accelerometer tags: detecting and identifying activities in fish and the effect of sampling frequency | en_US |
| dc.type | article | en_US |
| dc.identifier.volume | 216 | en_US |
| dc.identifier.issue | 7 | en_US |
| dc.identifier.startpage | 1255 | en_US |
