Advanced Technologies for Cetacean Monitoring: A One-Health and Multidisciplinary Approach for Ocean Effective Surveillance
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Field Study Area
2.2. Data Collection
2.3. Data Analysis
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Cisneros-Montemayor, A.M.; Sumaila, U.R.; Kaschner, K.; Pauly, D. The global potential for whale watching. Mar. Policy 2010, 34, 1273–1278. [Google Scholar] [CrossRef]
- Suárez-Rojas, C.; Hernández, M.M.G.; León, C.J. Sustainability in whale-watching: A literature review and future research directions based on regenerative tourism. Tour. Manag. Perspect. 2023, 47, 101120. [Google Scholar] [CrossRef]
- Jefferson, T.A.; Webber, M.A.; Pitman, R.L. Marine Mammals of the World: A Comprehensive Guide to Their Identification, 2nd ed.; Elsevier: Amsterdam, The Netherlands, 2015. [Google Scholar]
- Evans, P.G.H.; Hammond, P.S. Monitoring cetaceans in European waters. Mamm. Rev. 2004, 34, 131–156. [Google Scholar] [CrossRef] [Green Version]
- Liu, M.; Lin, M.; Dong, L.; Caruso, F.; Li, S. An integrated strategy for monitoring cetaceans in data-poor regions. Biol. Conserv. 2022, 272, 109648. [Google Scholar] [CrossRef]
- Verfuss, U.K.; Aniceto, A.S.; Harris, D.V.; Gillespie, D.; Fielding, S.; Jiménez, G.; Johnston, P.; Sinclair, R.R.; Sivertsen, A.; Solbø, S.; et al. A review of unmanned vehicles for the detection and monitoring of marine fauna. Mar. Pollut. Bull. 2019, 140, 17–29. [Google Scholar] [CrossRef]
- Whitt, C.; Pearlman, J.; Polagye, B.; Caimi, F.; Muller-Karger, F.; Copping, A.; Spence, H.; Madhusudhana, S.; Kirkwood, W.; Grosjean, L.; et al. Future Vision for Autonomous Ocean Observations. Front. Mar. Sci. 2020, 7, 697. [Google Scholar] [CrossRef]
- Rogers, E.O.; Gunderson, J.G.; Smith, W.S.; Denny, G.F.; Farley, P.J. Underwater acoustic glider. Int. Geosci. Remote Sens. Symp. 2004, 3, 2241–2244. [Google Scholar] [CrossRef]
- Haxel, J.H.; Matsumoto, H.; Meinig, C.; Kalbach, G.; Lau, T.-K.; Dziak, R.P.; Stalin, S. Ocean sound levels in the northeast Pacific recorded from an autonomous underwater glider. PLoS ONE 2019, 14, e0225325. [Google Scholar] [CrossRef] [Green Version]
- Miksis-Olds, J.L.; Martin, B.; Tyack, P.L. Exploring the Ocean through Sound. Acoust. Today 2018, 14, 26–34. [Google Scholar]
- Miloslavich, P.; Bax, N.J.; Simmons, S.E.; Klein, E.; Appeltans, W.; Aburto-Oropeza, O.; Garcia, M.A.; Batten, S.D.; Benedetti-Cecchi, L.; Checkley, D.M.; et al. Essential ocean variables for global sustained observations of biodiversity and ecosystem changes. Glob. Chang. Biol. 2018, 24, 2416–2433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Castro, I.; De Rosa, A.; Priyadarshani, N.; Bradbury, L.; Marsland, S. Experimental test of birdcall detection by autonomous recorder units and by human observers using broadcast. Ecol. Evol. 2019, 9, 2376–2397. [Google Scholar] [CrossRef] [Green Version]
- Kułaga, K.; Budka, M. Bird species detection by an observer and an autonomous sound recorder in two different environments: Forest and farmland. PLoS ONE 2019, 14, e0211970. [Google Scholar] [CrossRef] [PubMed]
- Joshi, K.A.; Mulder, R.A.; Rowe, K.M.C. Comparing manual and automated species recognition in the detection of four common south-east Australian forest birds from digital field recordings. Emu 2017, 117, 233–246. [Google Scholar] [CrossRef]
- Digby, A.; Towsey, M.; Bell, B.D.; Teal, P.D. A practical comparison of manual and autonomous methods for acoustic monitoring. Methods Ecol. Evol. 2013, 4, 675–683. [Google Scholar] [CrossRef]
- Zwerts, J.A.; Stephenson, P.J.; Maisels, F.; Rowcliffe, M.; Astaras, C.; Jansen, P.A.; Waarde, J.; Sterck, L.E.H.M.; Verweij, P.A.; Bruce, T.; et al. Methods for wildlife monitoring in tropical forests: Comparing human observations, camera traps, and passive acoustic sensors. Conserv. Sci. Pract. 2021, 3, e568. [Google Scholar] [CrossRef]
- Richardson, W.; Greene, J.; CI, C.R.M.; Thomson, D. Marine Mammals and Noise; Academic Press: Cambridge, MA, USA, 1995. [Google Scholar]
- Solsona-Berga, A.; Frasier, K.; Baumann-Pickering, S.; Wiggins, S.; Hildebrand, J. DetEdit: A graphical user interface for annotating and editing events detected in long-term acoustic monitoring data. PLoS Comput. Biol. 2020, 16, e1007598. [Google Scholar] [CrossRef] [PubMed]
- Frasier, K.E. A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets. PLoS Comput. Biol. 2021, 17, e1009613. [Google Scholar] [CrossRef] [PubMed]
- Kowarski, K.; Moors-Murphy, H. A review of big data analysis methods for baleen whale passive acoustic monitoring. Mar. Mammal Sci. 2021, 37, 652–673. [Google Scholar] [CrossRef]
- Dataset Retrieval: 2015 DCLDE Workshop. Available online: https://www.cetus.ucsd.edu/dclde/dataset.html (accessed on 21 March 2023).
- Hildebrand, J.A.; Frasier, K.E.; Helble, T.A.; Roch, M.A. Performance metrics for marine mammal signal detection and classification. J. Acoust. Soc. Am. 2022, 151, 414–427. [Google Scholar] [CrossRef]
- One Health High-Level Expert Panel (OHHLEP); Adisasmito, W.B.; Almuhairi, S.; Behravesh, C.B.; Bilivogui, P.; Bukachi, S.A.; Casas, N.; Becerra, N.C.; Charron, D.F.; Chaudhary, A.; et al. One Health: A new definition for a sustainable and healthy future. PLoS Pathog. 2022, 18, e1010537. [Google Scholar] [CrossRef]
- Atlas, R.M. One Health: Its Origins and Future. In One Health: The Human-Animal-Environment Interfaces in Emerging Infectious Diseases: The Concept and Examples of a One Health Approach; Mackenzie, J.S., Jeggo, M., Daszak, P., Richt, J.A., Eds.; Springer: Berlin/Heidelberg, Germany, 2013; pp. 1–13. [Google Scholar]
- Carrillo, M.; Pérez-Vallazza, C.; Álvarez-Vázquez, R. Cetacean diversity and distribution off Tenerife (Canary Islands). Mar. Biodivers. Rec. 2010, 3, e97. [Google Scholar] [CrossRef] [Green Version]
- Herrera, I.; Carrillo, M.; de Esteban, M.C.; Haroun, R. Distribution of Cetaceans in the Canary Islands (Northeast Atlantic Ocean): Implications for the Natura 2000 Network and Future Conservation Measures. Front. Mar. Sci. 2021, 8, 669790. [Google Scholar] [CrossRef]
- Barton, E.D.; Arístegui, J.; Tett, P.; Cantón, M.; García-Braun, J.; Hernández-León, S.; Nykjaer, L.; Almeida, C.; Almunia, J.; Ballesteros, S.; et al. The transition zone of the Canary Current upwelling region. Prog. Oceanogr. 1998, 41, 455–504. [Google Scholar] [CrossRef]
- Pelegrí, J.L.; Peña-Izquierdo, J. Eastern boundary currents off North-West Africa. In Oceanographic and Biological Features in the Canary Current Large Marine Ecosystem; IOC-UNESCO: Paris, France, 2015; pp. 81–92. [Google Scholar]
- Suárez-Rojas, C.; Hernández, M.M.G.; León, C.J. Do tourists value responsible sustainability in whale-watching tourism? Exploring sustainability and consumption preferences. J. Sustain. Tour. 2021, 30, 2053–2072. [Google Scholar] [CrossRef]
- De la Cruz-Modino, R.; Cosentino, M. Conservation Hub: The Added Value of the Whale-Watching Industry. Sustainability 2022, 14, 13471. [Google Scholar] [CrossRef]
- Gillespie, D.; Mellinger, D.K.; Gordon, J.; McLaren, D.; Redmond, P.; McHugh, R.; Trinder, P.; Deng, X.; Thode, A. PAMGUARD: Semiautomated, open source software for real-time acoustic detection and localization of cetaceans. J. Acoust. Soc. Am. 2009, 125, 2547. [Google Scholar] [CrossRef]
- Janik, V.M.; Sayigh, L.S. Communication in bottlenose dolphins: 50 years of signature whistle research. J. Comp. Physiol. A 2013, 199, 479–489. [Google Scholar] [CrossRef] [PubMed]
- Sayigh, L.S. Cetacean acoustic communication. Biocommun. Anim. 2014, 9789400774148, 275–297. [Google Scholar]
- Wei, C. Sound production and propagation in cetaceans. In Neuroendocrine Regulation of Animal Vocalization—Mechanisms and Anthropogenic Factors in Animal Communication; Academic Press: Cambridge, MA, USA, 2021; pp. 267–295. [Google Scholar] [CrossRef]
- Davis, J.; Goadrich, M. The Relationship between PR and ROC curves. In Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, USA, 25–29 June 2006; Volume 148, pp. 233–240. Available online: http://portal.acm.org/citation.cfm?doid=1143844.1143874 (accessed on 15 April 2023).
- Hossin, M.; Sulaiman, M.N. A review on evaluation metrics for data classification evaluations. Int. J. Data Min. Knowl. Manag. Process 2015, 5, 1. [Google Scholar]
- Marques, T.A.; Thomas, L.; Ward, J.; DiMarzio, N.; Tyack, P.L. Estimating cetacean population density using fixed passive acoustic sensors: An example with Blainville’s beaked whales. J. Acoust. Soc. Am. 2009, 125, 1982–1994. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Marques, T.A.; Thomas, L.; Martin, S.W.; Mellinger, D.K.; Ward, J.A.; Moretti, D.J.; Harris, D.; Tyack, P.L. Estimating animal population density using passive acoustics. Biol. Rev. 2013, 88, 287–309. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gillespie, D.; Caillat, M.; Gordon, J.; White, P. Automatic detection and classification of odontocete whistles. J. Acoust. Soc. Am. 2013, 134, 2427–2437. [Google Scholar] [CrossRef] [PubMed]
- Barlow, J.; Griffiths, E.T.; Klinck, H.; Harris, D.V. Diving behavior of Cuvier’s beaked whales inferred from three-dimensional acoustic localization and tracking using a nested array of drifting hydrophone recorders. J. Acoust. Soc. Am. 2018, 144, 2030–2041. [Google Scholar] [CrossRef] [PubMed]
- Gillespie, D.; Oswald, M.; Hastie, G.; Sparling, C. Marine Mammal HiCUP: A High Current Underwater Platform for the Long-Term Monitoring of Fine-Scale Marine Mammal Behavior Around Tidal Turbines. Front. Mar. Sci. 2022, 9, 283. [Google Scholar] [CrossRef]
- Romagosa, M.; Boisseau, O.; Cucknell, A.-C.; Moscrop, A.; McLanaghan, R. Source level estimates for sei whale (Balaenoptera borealis) vocalizations off the Azores. J. Acoust. Soc. Am. 2015, 138, 2367–2372. [Google Scholar] [CrossRef] [PubMed]
- Palmer, K.J.; Tabbutt, S.; Gillespie, D.; Turner, J.; King, P.; Tollit, D.; Thompson, J.; Wood, J. Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring. Methods Ecol. Evol. 2022, 13, 2491–2502. [Google Scholar] [CrossRef]
- Korkmaz, B.N.; Diamant, R.; Danino, G.; Testolin, A. Automated detection of dolphin whistles with convolutional networks and transfer learning. Front. Artif. Intell. 2023, 6, 1099022. [Google Scholar] [CrossRef] [PubMed]
- Al-Badrawi, M.H.; Liang, Y.; Seger, K.D.; Foster, C.M.; Kirsch, N.J. Caller ID for Risso’s and Pacific White-sided dolphins. Sci. Rep. 2022, 12, 4510. [Google Scholar] [CrossRef]
- Baumgartner, M.; Bonnell, J.; Corkeron, P.; Van Parijs, S.; Hotchkin, C.; Hodges, B. Slocum gliders provide accurate near real-time estimates of baleen whale presence from human-reviewed passive acoustic detection information. Front. Mar. Sci. 2020, 7, 100. [Google Scholar] [CrossRef]
- Allen, A.N.; Harvey, M.; Harrell, L.; Jansen, A.; Merkens, K.P.; Wall, C.C.; Cattiau, J.; Oleson, E.M. A Convolutional Neural Network for Automated Detection of Humpback Whale Song in a Diverse, Long-Term Passive Acoustic Dataset. Front. Mar. Sci. 2021, 8, 607321. [Google Scholar] [CrossRef]
- Zhong, M.; Castellote, M.; Dodhia, R.; Ferres, J.L.; Keogh, M.; Brewer, A. Beluga whale acoustic signal classification using deep learning neural network models. J. Acoust. Soc. Am. 2020, 147, 1834–1841. [Google Scholar] [CrossRef]
- Fernandes, P.G.; Stevenson, P.; Brierley, A.S. AUVs as research vessels: The pros and cons. ICES C 2002, 2002, 2. [Google Scholar]
- Harris, D.; Fregosi, S.; Klinck, H.; Mellinger, D.K.; Barlow, J.; Thomas, L. Evaluating autonomous underwater vehicles as platforms for animal population density estimation. J. Acoust. Soc. Am. 2017, 141, 3606. [Google Scholar] [CrossRef]
- Cauchy, P.; Heywood, K.J.; Merchant, N.D.; Risch, D.; Queste, B.Y.; Testor, P. Gliders for passive acoustic monitoring of the oceanic environment. Front. Remote Sens. 2023, 4, 1106533. [Google Scholar] [CrossRef]
- Caillat, M.; Thomas, L.; Gillespie, D. The effects of acoustic misclassification on cetacean species abundance estimation. J. Acoust. Soc. Am. 2013, 134, 2469–2476. [Google Scholar] [CrossRef]
- Palacios-Díaz, M.d.P.; Mendoza-Grimón, V. Environment in Veterinary Education. Vet. Sci. 2023, 10, 146. [Google Scholar] [CrossRef] [PubMed]
Detection Outcome | Actual Condition |
---|---|
Positive Detection | Signal Present |
False Positive | No Signal Present |
Negative Detection | No Signal Present |
False Negative | Signal Present |
Descriptor | Cetaceans Click (%) | Cetaceans Whistles (%) |
---|---|---|
Accuracy | 33 | 13 |
Recall | 22 | 19 |
F-Score | 26 | 16 |
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Neves, S.; Doh, Y.; Sacchini, S.; Delory, E.; Fernández, A.; Castro-Alonso, A. Advanced Technologies for Cetacean Monitoring: A One-Health and Multidisciplinary Approach for Ocean Effective Surveillance. J. Mar. Sci. Eng. 2023, 11, 1431. https://doi.org/10.3390/jmse11071431
Neves S, Doh Y, Sacchini S, Delory E, Fernández A, Castro-Alonso A. Advanced Technologies for Cetacean Monitoring: A One-Health and Multidisciplinary Approach for Ocean Effective Surveillance. Journal of Marine Science and Engineering. 2023; 11(7):1431. https://doi.org/10.3390/jmse11071431
Chicago/Turabian StyleNeves, Silvana, Yann Doh, Simona Sacchini, Eric Delory, Antonio Fernández, and Ayoze Castro-Alonso. 2023. "Advanced Technologies for Cetacean Monitoring: A One-Health and Multidisciplinary Approach for Ocean Effective Surveillance" Journal of Marine Science and Engineering 11, no. 7: 1431. https://doi.org/10.3390/jmse11071431
APA StyleNeves, S., Doh, Y., Sacchini, S., Delory, E., Fernández, A., & Castro-Alonso, A. (2023). Advanced Technologies for Cetacean Monitoring: A One-Health and Multidisciplinary Approach for Ocean Effective Surveillance. Journal of Marine Science and Engineering, 11(7), 1431. https://doi.org/10.3390/jmse11071431