Contents:
As a conceptual example, Fig. For comparison, the audiograms of Pacific white-sided dolphins, elephant seals and humpback whales are plotted as well. Only energy above the audiogram is assumed audible in the following audibility assessment. In the above example, even the loudest ships are no longer audible to Pacific white-sided dolphins at 30 km range and beyond.
Energy around Hz remains audible over the longest ranges in the case of elephant seals. For baleen whales, the low-frequency peak of the ship spectrum at 50 Hz remains audible over the longest ranges. This plot illustrates how the audiogram weighting determines which frequencies will be audible over the farthest ranges, and how these spectral characteristics differ amongst species.
Bathymetry was obtained from the Canadian Hydrographic Service. Frequency-dependent, volumetric absorption was also accounted for [57] , [58] , and results in the faster loss of energy at higher frequencies than at lower frequencies. Hence the noise map does not show any source levels; even in source cells, the level plotted is the sum of all contributions from neighboring cells plus the contribution from ships within this cell propagated over 2 km.
Up to this point, the methods have been described in more detail elsewhere [2]. The ship spectrum received at each receiver cell was filtered by the animal audiogram. The audible energy in each receiver cell was integrated over all ship positions within km radius, over all vessel classes, over frequency and over time. The result was a map representing audible acoustic energy from shipping over the summer June-September of for each species. As a first-order validation exercise, we compared our predicted cumulative sound exposure levels without audiogram-filtering to measured underwater noise reported recently for 12 sites in our study area [59].
The modeled unweighted cumulative noise from shipping over the year of was read off Fig.
The modeled cumulative sound exposure levels were ranked from noisiest 1 to quietest The median noise level measured at each site over 20— days between and was extracted from Table S1 in reference [59] in each of three frequency bands 17—28 Hz; 71— Hz; and — Hz , and also ranked from 1— A Spearman rank-order correlation i. The audibility maps were limited to the area that had previously been surveyed for marine mammals [36] , [37] , i. The audibility maps were scaled to range from 0 to 1 by subtracting the minimum received energy over all cells from the entire map, and by dividing the audibility map by the maximum received energy.
This was done for each species.
The density maps were normalized to 0—1 the same way. The normalized noise audibility map and the normalized density map were multiplied for each species. In areas where the audible energy was high i. In areas where either the audible energy or the animal density was high and the other one was low, the product was low i. The product of the two maps was normalized to 0—1 as well, to yield a risk index for each species. Risk indices computed this way are not comparable among species as the map for each species was normalized to 0—1 , but can be used to rank habitat for each species.
There was a significant correlation between the rankings, from noisy to quiet, of the modeled noise levels and the empirical measurements of underwater noise. In the lowest frequency band corresponding to fin whale calls 17—28 Hz , the Spearman's rank correlation coefficient r s was 0.
In the 71— Hz band, r s was 0. In the — Hz band, r s was 0. Note that noise statistics were available for 12 sites in the highest frequency band, but only 10 in the lower and mid- frequency bands [39]. We are therefore confident that our predicted noise surface provides a reliable proxy for scoring habitat from noisy to quiet sites. A measure of total acoustic energy from all ships over the summer of is shown for six of the seven audiograms in Fig.
Given the similarity of the elephant and harbor seal audiograms, only the latter is shown. Animals with the least hearing sensitivity below 20 kHz Steller sea lions and Pacific white-sided dolphins are expected to perceive the least amount of acoustic energy. Animals with better hearing sensitivity at low-to-mid frequencies 50— Hz experience the most ship noise baleen whales and true phocid seals.
To illustrate the process we used to map risk i. In terms of results, Fig. For species that exist in Juan de Fuca and Haro Strait, these regions are hotspots due to the large amount of ship traffic and hence ship noise. For populations that do not range this far south, Johnstone Strait and the waters off Prince Rupert tend to have the highest risk index. Secondary hotspots were identified somewhat removed from the major shipping lanes, e.
Ship noise does not propagate well into the narrow and winding fjords, which represent important habitats to some species; however, with increasing onshore development, ship noise in fjords is likely to increase. We compared modeled ship noise in British Columbia with measured and modeled animal density data.
The geometric sound propagation model ignored spatiotemporal differences in the acoustic environment of the water column and the seafloor. The spatiotemporal variability of the sound propagation model and its uncertainty were discussed elsewhere [2]. Shipping routes did not change, and as the noise maps are normalized, we expect the geographic hotspots to be unaffected. Our approach differentiates among species by applying an audiogram-weighted metric corresponding to our best estimate of received acoustic energy.
As a result, the geographic areas and the extent of the areas in which ship noise might impact marine mammals differ from species to species. Hearing sensitivity varies amongst individuals of the same species [60] ; the audiograms of 14 3—15 year-old bottlenose dolphins varied by up to 10 dB [61]. Life history and sound exposure history of captive animals, whose audiograms have been measured, are often unknown. We also note the scarcity of hearing data for some species, with the Pacific white-sided dolphin and elephant seal audiograms being based on one animal. M-weighting has been recommended to group marine mammal species into functional groups for bioacoustic impact assessments of strong sounds [7].
For the assessment of lower-level responses such as behavioral changes and masking, audiogram weighting has been preferred [64].
Correlating the resulting ship-audibility maps with density surface maps for each species yielded patterns of hotspots for each species. In other words, the same noise surface carries quite different consequences for conservation and management of different marine mammal species, because different distribution patterns cause the species to differ widely in their vulnerability exposure to noise , whereas different hearing abilities cause the species to differ widely in their sensitivity in this case, ability to perceive anthropogenic noise.
We suggest this audiogram-weighted approach for chronic ship noise as a means of differentiating between species based on the received acoustic energy, which might correlate with audibility-dependent impacts such as behavioral responses or masking. We do not advocate this approach for impact assessments of acute, intense exposures as from seismic surveying or pile driving.
Based solely on the physical properties of sound in the ocean, we postulate that marine mammals that hear best in the frequency bands dominated by ship noise should be most affected by high levels of ship noise, but this may not be true. It is conceivable that natural selection is particularly active at the edge of audibility where the acoustic arms-race between predator and prey is taking place [65] , and that the ability to detect signals in noise at the edge of audibility is a key determinant of survival and reproduction. We consider the various ways of weighting received level by hearing sensitivity as hypotheses to be tested with new behavioral response data.
Our maps showing areas where these different species are and are not currently experiencing high levels of anthropogenic noise would be useful in choosing experimental control and treatment sites for future experiments to understand the responsiveness of different species to noise.
The Second International Conference on the Effects of Noise on Aquatic Life will take place in Ireland August Advances in Experimental Medicine and Biology. Editorial Reviews. From the Back Cover. About the Author. Arthur N. Popper is Professor in the Buy The Effects of Noise on Aquatic Life: (Advances in Experimental Medicine and Biology): Read Books Reviews - www.farmersmarketmusic.com
These risk maps can inform marine spatial planning efforts, but they are only one input into a systematic conservation planning process [32]. Future tasks require managers and policy makers to set explicit conservation targets, which may vary according to the conservation status of each population.
In this case, a passing acoustic wave excites the resonator into a volumetric oscillation. They are intended to be fastened to a framework to form a stationary array surrounding an underwater noise source, such as the ones previously mentioned, or to protect a receiving area from outside noise. Oral Presentation Patricio, S. At Kobo, we try to ensure that published reviews do not contain rude or profane language, spoilers, or any of our reviewer's personal information. Invited speaker, Renewable energy session Nimak-Wood.
Future iterations could incorporate additional data, as long as other datasets can be modeled to account for spatial bias in opportunistic sightings, photo-ID locations, or data from non-randomized surveys. Otherwise, managers may end up inadvertently protecting sites where it is convenient to collect data, rather than sites that are most important to at-risk species. The percentage of any species' habitat that is affected by noise can be read off a map. The areas where noise is high and animal density is high can also be identified in our risk maps, indicating where marine spatial planning efforts have the most impact.
It is worth noting that the critical habitats for northern resident killer whales in Johnstone Strait, for example, are quite noisy Figure 6 , although there is a legal obligation in Canada to manage acoustic elements of the critical habitats of these whales [3]. In contrast, species that rely on Hecate Strait waters e. Although we have outlined one defensible way to combine information on chronic ocean noise and marine mammal habitat use, there are a number of technical issues for us to resolve before these predictions are ready for use in real-world management.
First, many sound sources are simply missing from this estimate of cumulative ship noise energy. The most important of these missing sources in our noise maps is small boat traffic. For instance, loud sounds can affect the migratory or other behavioral patterns of marine mammals [1] and fish [2]. Additionally, if the noise is loud enough, it could potentially have physically damaging effects on these animals as well. Examples of human activities that that can generate such noise are offshore wind farm installation and operation; bridge and dock construction near rivers, lakes, or ports; offshore seismic surveying for oil and gas exploration, as well as oil and gas production; and noise in busy commercial shipping lanes near environmentally sensitive areas, among others.
All of these activities can generate noise over a broad range of frequencies, but the loudest components of the noise are typically at low frequencies, between 10 Hz and about Hz, and these frequencies overlap with the hearing ranges of many aquatic life forms. We seek to reduce the level of sound radiated by these noise sources to minimize their impact on the underwater environment where needed. A traditional noise control approach is to place some type of barrier around the noise source. To be effective at low frequencies, the barrier would have to be significantly larger than the noise source itself and more dense than the water, making it impractical in most cases.
In underwater noise abatement, curtains of small freely rising bubbles are often used in an attempt to reduce the noise; however, these bubbles are often ineffective at the low frequencies at which the loudest components of the noise occur. We developed a new type of underwater air-filled acoustic resonator that is very effective at attenuating underwater noise at low frequencies.
The resonators consist of underwater inverted air-filled cavities with combinations of rigid and elastic wall members.
They are intended to be fastened to a framework to form a stationary array surrounding an underwater noise source, such as the ones previously mentioned, or to protect a receiving area from outside noise. The key idea behind our approach is that our air-filled resonator in water behaves like a mass on a spring, and hence it vibrates in response to an excitation. A good example of this occurring in the real world is when you blow over the top of an empty bottle and it makes a tone. The specific tone it makes is related to three things: In this case, a passing acoustic wave excites the resonator into a volumetric oscillation.
The air inside the resonator acts as a spring and the water the air displaces when it is resonating acts as a mass. Bestsellers in Effects of Contaminants. The UK Pesticide Guide Methods and Techniques for Cleaning-up Contaminated Sites. Carbofuran and Wildlife Poisoning. Water Pollution Incidents in England and Wales, Atmospheric Chemistry and Physics. Other titles from Springer. Bats in the Anthropocene. Background Science and the Inner Solar System. Flora and Vegetation of the Czech Republic. Browse titles from Springer.