Harbour porpoise hydrophone array data recorded on a gill net
Macaulay, Jamie et al. (2022), Harbour porpoise hydrophone array data recorded on a gill net , Dryad, Dataset, https://doi.org/10.5061/dryad.v9s4mw6xv
Entanglement in net fisheries (static and drift) is the largest known cause of direct anthropogenic mortality to many small cetacean species, including harbour porpoise (Phocoena phocoena), in UK waters. Despite this, little is known about the behaviour of small cetaceans in proximity to nets.
We have developed a passive acoustic monitoring (PAM) system for tracking the fine scale three-dimensional (3D) movements of echolocating cetaceans around actively fishing nets by localising their acoustic clicks. The system consists of two compact four-channel acoustic recorders with sample-synchronised sensor packages that use 3D motion tracking technology to accurately log orientation, depth, water temperature and ambient light level. Two recorders were used in tandem, with each one attached to and floating above the net float-line. The system can be deployed during normal fishing operations by a trained researcher or experienced fisheries observer. Recordings were analysed in PAMGuard software and the 3D positions of echolocating animals in the vicinity of the system were calculated using an acoustic particle filter-based localisation method.
We present findings from four deployments in UK waters (each 1-2 days in duration) in which 12 distinct harbour porpoise encounters yielded a sufficient number of detected clicks to track their movements around the net. The tracks show a variety of behaviours, including multiple instances of animals actively foraging in close proximity to the fishing net.
We show that a relatively inexpensive PAM system, which is practical to deploy from active fishing vessels, is capable of providing highly detailed data on harbour porpoise behaviour around nets. As harbour porpoises are the one of the most difficult species to localise, this methodology is likely to be suitable for elucidating the behaviour of many other toothed whale species in a variety of situations.
These data are processed acoustic recordings from two acoustic devices recording on an actively fishing gill net. The aim of the study was to try and acquire detailed 3D behavioural information on harbour porpoises around gill nets via acoustic localisation.
Each recorder contained a micro-aperture 4 element hydrophone array and accurate depth and orientation sensors. The 4-channel array within each device allowed for a relative 3D vector to a received harbour porpoise echolocation click to be calculated. Depth and orientation sensor then allowed the vector to be geo-referenced (i.e., relative to north). The two recorders were separated by 15- 40m along the headline of the gill net – if two devices detected the same click then the location of the harbour porpoise was the point at which the two resulting vectors crossed. As porpoises (and dolphins) echolocate regularly, localising successive clicks allowed a 3D track of an animal to be constructed over time, providing detailed information on animal movements around the gill net.
Each deployment results in terabytes of raw acoustic data- the dataset here are acoustic recordings which has been processed in PAMGuard; PAMGuard was configured to detect any transient sounds in the 80-150kHz frequency band. Most of these sounds are false positive detections but a subset will be the echolocation clicks of dolphins and harbour porpoises. An automated classifier was then used to detect which transients likely correspond to harbour porpoises. There are two datasets, one for each recording device. Each consists of a .sqlite database and folder of PAMGaurd binary files. To open the dataset simply download PAMGuard (www.pamguard.org), start PAMGuard viewer mode and select the database and binary file folder in the file browsers which appear. Data can also be imported into MATLAB or R (see http://www.pamguard.org/48_MATLABRcode.html).
The dataset also contains GPS logs of the fishing vessel used to deploy the nets. Note that these have been altered to comply with GDPR so that the relative co-ordinates are correct but they are not in the original location. The GPS data is used to determine the location of the devices on the seabed – details are available in the paper that accompanies this dataset.
Coding libraries can be found at https://github.com/macster110/soundnet/.
Defra, Award: ME6052
University of St Andrews, Award: -