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Broadband Acoustic Network

 

Scientific background

Humans rely mainly on light to detect and understand their environment. But what do animals do in environments where little light is arriving? This is the case in marine ecosystems. Through fluids like water, sound propagates much more efficiently than light. Consequently, most of the species living underwater presumably do not rely on their vision to interact with their environment but on sound. At relatively low cost, marine soundscapes can be recorded over long periods of time in order to observe long term trends. They provide information on geophysical events and weather, on human activities and on the animals living in the environment—entirely non-invasively by passively listening at a distance. Soundscapes are often compared to identify good versus bad habitats, or changes of an environment over time. The broadband acoustic network will be recording continuously from 10 Hz to 50 kHz, covering most of geophonic sounds, anthropogenic noise (except sonar and technologies used to map the sea floor such as multibeam) and biophonic events. Higher frequency sound such as harbor porpoises clicks (120 - 145 kHz, mode 132 kHz) will be monitored by the Cetacean Passive Acoustic Network.

Infrastructure

The broadband acoustic network is functional since spring 2020. Four long-term acoustic recorders will be deployed on tripod frames on the sea bottom. These tripods are attached to a buoy with an acoustic release (Vemco VR2AR), allowing the recovery of the equipment. In some cases, C-PODs (see Cetacean Passive Acoustic Network) will also be attached to the same tripod. Two of the recorders will be deployed in fixed locations and the data is going to be downloaded every 5 months. The other two will be changed of location every 2 or 3 months. This strategy allows to compare spatial and temporal patterns.

 

Left: “Multi-mooring designed within the framework of LifeWatch to host a variety of stand-alone autonomous sensors. For the broadband acoustic network, it hosts 1-4 hydrophones, an acoustic recorder, battery case, a C-POD (marine mammal echolocation detector) and a receiver, also working as an acoustic release (©VLIZ).” Right: "Two permanent fixed stations (Grafton & Faulbaums) and two other alternating stations are equipped with the acoustic recorder to produce long term underwater sound data."

Data

The metadata can be assessed via the IMIS records.

 

Useful links:

  • pyhydrophone on GitHub: pyhydrophone is an open-source Python package that has been developed to ease the import of underwater sound data recorded with a hydrophone to python, so postprocessing and AI can be easily performed on the data afterwards. Different recorders can be added with their different way of reading metadata, so the scientists do not have to worry about he format but just about the outcome. It is still in constant development and improvement.
  • pyporcc on GitHub: pyporcc is an open-source Python package developed to detect and classify harbor porpoise’s clicks in audio files using the PorCC algorithm and offering the possibility to create new clicks classifiers. It provides a framework to train different models such Support Vector Machines, Linear Support Vector Machines, Random Forest and K-Nearest Neighbor that classify sound clips in Noise, and Low-Quality and High-Quality Harbor Porpoises’ clicks. The algorithm from PAMGuard to detect possible clicks clips is also implemented.

  • Pypam: is a python tool which pretends to facilitate the acoustic processing of acoustic files resulting from underwater acoustic deployments. It is a combination of some existing tools for acoustic processing, and it allows the processing of several deployments with one line of code, so it is easy to create datasets to work with. pypam is oriented to extracting features that can be used for Machine Learning algorithms or to the extraction of broad acoustic information in time-series. Pypam further depends on pyhydrophone for hydrophone metadata management and calibration, and it provides an output in netCDF format, which can be used from multiple platforms (more info).

  • Bpnsdata:  bpnsdata is a python package to add environmental data to a geopandas DataFrame. There is no support for multiindex columns, so one level has to be selected or dropped out before using it. Right now only Belgian Part of the North Sea data is available for all the classes. However, some classes are not restricted to the bpns and can be used to add environmental data to other parts of the world. It is made to be used with pypam to be able to compare environmental data with acoustic features.

Media & outreach

Most recent publications

  • Parcerisas, C., Botteldooren, D., Devos, P., Hamard, Q., Debusschere, E. (2023). Studying the Soundscape of Shallow and Heavy Used Marine Areas: Belgian Part of the North Sea. In: Popper, A.N., Sisneros, J., Hawkins, A.D., Thomsen, F. (eds) The Effects of Noise on Aquatic Life. Springer, Cham. https://doi.org/10.1007/978-3-031-10417-6_122-1. [link to IMIS record]

  • Rubbens, P.; Brodie, S.; Cordier, T.; Barcellos, D.D.; Devos, P.; Fernandes-Salvador, J.A.; Fincham, J.I.; Gomes, A.; Handegard, N.O.; Howell, K.; Jamet, C.; Kartveit, K.H.; Moustahfid, H.; Parcerisas, C.; Politikos, D.; Sauzède, R.; Sokolova, M.; Uusitalo, L.; Van den Bulcke, L.; van Helmond, A.T.M.; Watson, J.T.; Welch, H.; Beltran-Perez, O.; Chaffron, S.; Greenberg, D.S.; Kühn, B.; Kiko, R.; Lo, M.; Lopes, R.M.; Möller, K.O.; Michaels, W.; Pala, A.; Romagnan, J.-B.; Schuchert, P.; Seydi, V.; Villasante, S.; Malde, K.; Irisson, J.-O. (2023). Machine learning in marine ecology: an overview of techniques and applications. ICES J. Mar. Sci./J. Cons. int. Explor. Mer Accepted. https://dx.doi.org/10.1093/icesjms/fsad100 [link to IMIS record]

  • Parcerisas, C.; Roca, I.T.; Botteldooren, D.; Devos, P.; Debusschere, E. (2023). Categorizing shallow marine soundscapes using explained clusters. J. Mar. Sci. Eng. 11(3): 550. https://dx.doi.org/10.3390/jmse11030550 [link to IMIS record]

  • Rey Baquero, M.P.; Parcerisas, C.; Seger, K.; Perazio, C.; Botero-Acosta, N.; Mesa, F.; Acosta, A.L.; Botteldooren, D.; Debusschere, E. (2021). Comparison of two soundscapes: An opportunity to assess the dominance of biophony versus anthropophony, in: Kappel, E.S. et al. Frontiers in ocean observing: Documenting ecosystems, understanding environmental changes, forecasting hazards. Oceanography, Suppl. 34(4): pp. 62-65. https://dx.doi.org/10.5670/oceanog.2021.supplement.02-24 [link to IMIS record]

  • Thomsen, F.; Mendes, S.; Bertucci, F.; Breitzke, M.; Ciappi, E.; Cresci, A.; Debusschere, E.; Ducatel, C.; Folegot, T.; Juretzek, C.; Lam, F.-P.; O’Brien, J.; dos Santos, M.E.; Kellett, P.; van den Brand, R.; Alexander, B.; Muñiz Piniella, A.; Rodriguez-Perez, A.; van Elslander, J.; Heymans, J.J. (2021). Addressing underwater noise in Europe: Current state of knowledge and future priorities. Marine Board Future Science Brief, 7. European Marine Board: Ostend. ISBN 9789464206104. 54 pp. https://dx.doi.org/10.5281/zenodo.5534224 [link to IMIS record]

  • Rogers, P.; Debusschere, E.; de Haan, D.; Martin, B.; Slabbekoorn, H. (2021). North Sea soundscapes from a fish perspective: Directional patterns in particle motion and masking potential from anthropogenic noise. J. Acoust. Soc. Am. 150(3): 2174-2188. [link to IMIS record]

  • Kok, A.C.M.; Bruil, L.; Berges, B.; Sakinan, S.; Debusschere, E.; Reubens, J.; de Haan, D.; Norro, A.; Slabbekoorn, H. (2021). An echosounder view on the potential effects of impulsive noise pollution on pelagic fish around windfarms in the North Sea. Environ. Pollut. 290: 118063. [link to IMIS record]