Aquatic animals rely on sound to communicate, navigate, prey, or avoid predation in turbid waters. The acoustic environment of their habitats plays an important role in their life, i.e. the fishes understand the environment using sound. Documented studies provide data indicating that marine habitats can be altered by anthropogenic noise, due to which marine life can be affected. The nearshore and the areas of harbours are usually predominated by the high sound pressure levels of anthropogenic origin resulting from frequent passages of pleasure vessels and other kind of ships nearby. These high levels no doubt can cause the risk of negative effects on marine life inhabited or migrating through nearshore and harbour areas. With the aim to assess the underwater sound levels at Klaipėda harbour area, underwater acoustic measurements were implemented. The obtained results indicate that the Klaipeda harbour is affected by the anthropogenic underwater noise and long-term noise monitoring may be useful to assess the trends of prevailing underwater noise in this area. In this paper, the results of the continuous underwater sound level measurements along with the analysis of the influence of anthropogenic sources and environmental factors on prevailing soundscape are presented; the risks of negative effects of elevated underwater noise levels on fish species and possible underwater noise measures are shortly discussed.
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http://dx.doi.org/10.1016/j.marpolbul.2022.114335 | DOI Listing |
Mar Pollut Bull
December 2024
LARSys, Universidade do Algarve, Estr. da Penha, Faro 8005-139, Portugal.
Ocean noise generated by human activities at sea has been increasing over the decades, affecting marine ecosystems. Ship traffic flow between the Mediterranean or South Atlantic and northern Europe makes the coast of Portugal one of the most intense shipping highways on a global scale. Among the cetaceans of the coast of Portugal, the common dolphin (Delphinus delphis) was selected as a target species.
View Article and Find Full Text PDFJ Acoust Soc Am
December 2024
Engineering Department, Jacksonville University, Jacksonville, Florida 32211, USA.
Underwater noise data were collected from 84 pile drives during bridge construction at various sites in Florida. These data were used to develop an empirically based model for underwater transmission loss associated with root mean squared, peak, and sound exposure level values. The model was verified using readings from other datasets as well as data from this study, and it appeared to reproduce reported transmission loss coefficient values well when data were curated to match data used in the empirical model's development and limited to situations where robust data were used in model development.
View Article and Find Full Text PDFSensors (Basel)
November 2024
College of Fisheries, Guangdong Ocean University, Zhanjiang 524088, China.
Underwater simultaneous localization and mapping (SLAM) has significant challenges due to the complexities of underwater environments, marked by limited visibility, variable conditions, and restricted global positioning system (GPS) availability. This study provides a comprehensive analysis of sensor fusion techniques in underwater SLAM, highlighting the amalgamation of proprioceptive and exteroceptive sensors to improve UUV navigational accuracy and system resilience. Essential sensor applications, including inertial measurement units (IMUs), Doppler velocity logs (DVLs), cameras, sonar, and LiDAR (light detection and ranging), are examined for their contributions to navigation and perception.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
The underwater imaging process is often hindered by high noise levels, blurring, and color distortion due to light scattering, absorption, and suspended particles in the water. To address the challenges of image enhancement in complex underwater environments, this paper proposes an underwater image color correction and detail enhancement model based on an improved Cycle-consistent Generative Adversarial Network (CycleGAN), named LPIPS-MAFA CycleGAN (LM-CycleGAN). The model integrates a Multi-scale Adaptive Fusion Attention (MAFA) mechanism into the generator architecture to enhance its ability to perceive image details.
View Article and Find Full Text PDFInt J Mol Sci
November 2024
Zhejiang Key Laboratory of Coastal Biological Germplasm Resources Conservation and Utilization, Institute of Hydrobiology, Zhejiang Academy of Agricultural Sciences, Hangzhou 310000, China.
The problem of marine noise pollution has a long history. Strong noise (>120 dB re 1 µPa) will affects the growth, development, physiological responses, and behaviors of fish, and also can induce the stress response, posing a mortal threat. Although many studies have reported that underwater noise may affect the survival of fish by disturbing their nervous system and endocrine system, the underlying causes of death due to noise stimulation remain unknown.
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