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A simulation approach to assessing environmental risk of sound exposure to marine mammals

View Article: PubMed Central - PubMed

ABSTRACT

Intense underwater sounds caused by military sonar, seismic surveys, and pile driving can harm acoustically sensitive marine mammals. Many jurisdictions require such activities to undergo marine mammal impact assessments to guide mitigation. However, the ability to assess impacts in a rigorous, quantitative way is hindered by large knowledge gaps concerning hearing ability, sensitivity, and behavioral responses to noise exposure. We describe a simulation‐based framework, called SAFESIMM (Statistical Algorithms For Estimating the Sonar Influence on Marine Megafauna), that can be used to calculate the numbers of agents (animals) likely to be affected by intense underwater sounds. We illustrate the simulation framework using two species that are likely to be affected by marine renewable energy developments in UK waters: gray seal (Halichoerus grypus) and harbor porpoise (Phocoena phocoena). We investigate three sources of uncertainty: How sound energy is perceived by agents with differing hearing abilities; how agents move in response to noise (i.e., the strength and directionality of their evasive movements); and the way in which these responses may interact with longer term constraints on agent movement. The estimate of received sound exposure level (SEL) is influenced most strongly by the weighting function used to account for the specie's presumed hearing ability. Strongly directional movement away from the sound source can cause modest reductions (~5 dB) in SEL over the short term (periods of less than 10 days). Beyond 10 days, the way in which agents respond to noise exposure has little or no effect on SEL, unless their movements are constrained by natural boundaries. Most experimental studies of noise impacts have been short‐term. However, data are needed on long‐term effects because uncertainty about predicted SELs accumulates over time. Synthesis and applications. Simulation frameworks offer a powerful way to explore, understand, and estimate effects of cumulative sound exposure on marine mammals and to quantify associated levels of uncertainty. However, they can often require subjective decisions that have important consequences for management recommendations, and the basis for these decisions must be clearly described.

No MeSH data available.


The effect of different degrees of responsive movement by gray seals on SEL. A standard deviation of 10 results in directionless movement; a standard deviation of 0.05 results in marked avoidance of the source. The horizontal line is the threshold (203 dB) for PTS suggested by Southall et al. (2007) for pinnipeds exposed to nonpulsed sound. Gray shading gives a 95% prediction interval, that is, the central 95% of SELs calculated for simulated animals. Note nonlinear x‐axis for display, and sound levels are dB re 1 μPa2/s
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ece32699-fig-0004: The effect of different degrees of responsive movement by gray seals on SEL. A standard deviation of 10 results in directionless movement; a standard deviation of 0.05 results in marked avoidance of the source. The horizontal line is the threshold (203 dB) for PTS suggested by Southall et al. (2007) for pinnipeds exposed to nonpulsed sound. Gray shading gives a 95% prediction interval, that is, the central 95% of SELs calculated for simulated animals. Note nonlinear x‐axis for display, and sound levels are dB re 1 μPa2/s

Mentions: The magnitude and directionality of the avoidance responses also affected the estimated SEL (Figure 4). The effect depended on the duration of the scenario. The interval is widest when SD = 10, which represents a situation in which there is effectively no response to sound. After 1 day of exposure, the average difference in the SEL for agents that showed a directionless response was about 5 dB higher than for agents that showed very directed movement. After 10 days, the difference was in the order of 10 dB.


A simulation approach to assessing environmental risk of sound exposure to marine mammals
The effect of different degrees of responsive movement by gray seals on SEL. A standard deviation of 10 results in directionless movement; a standard deviation of 0.05 results in marked avoidance of the source. The horizontal line is the threshold (203 dB) for PTS suggested by Southall et al. (2007) for pinnipeds exposed to nonpulsed sound. Gray shading gives a 95% prediction interval, that is, the central 95% of SELs calculated for simulated animals. Note nonlinear x‐axis for display, and sound levels are dB re 1 μPa2/s
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383472&req=5

ece32699-fig-0004: The effect of different degrees of responsive movement by gray seals on SEL. A standard deviation of 10 results in directionless movement; a standard deviation of 0.05 results in marked avoidance of the source. The horizontal line is the threshold (203 dB) for PTS suggested by Southall et al. (2007) for pinnipeds exposed to nonpulsed sound. Gray shading gives a 95% prediction interval, that is, the central 95% of SELs calculated for simulated animals. Note nonlinear x‐axis for display, and sound levels are dB re 1 μPa2/s
Mentions: The magnitude and directionality of the avoidance responses also affected the estimated SEL (Figure 4). The effect depended on the duration of the scenario. The interval is widest when SD = 10, which represents a situation in which there is effectively no response to sound. After 1 day of exposure, the average difference in the SEL for agents that showed a directionless response was about 5 dB higher than for agents that showed very directed movement. After 10 days, the difference was in the order of 10 dB.

View Article: PubMed Central - PubMed

ABSTRACT

Intense underwater sounds caused by military sonar, seismic surveys, and pile driving can harm acoustically sensitive marine mammals. Many jurisdictions require such activities to undergo marine mammal impact assessments to guide mitigation. However, the ability to assess impacts in a rigorous, quantitative way is hindered by large knowledge gaps concerning hearing ability, sensitivity, and behavioral responses to noise exposure. We describe a simulation‐based framework, called SAFESIMM (Statistical Algorithms For Estimating the Sonar Influence on Marine Megafauna), that can be used to calculate the numbers of agents (animals) likely to be affected by intense underwater sounds. We illustrate the simulation framework using two species that are likely to be affected by marine renewable energy developments in UK waters: gray seal (Halichoerus grypus) and harbor porpoise (Phocoena phocoena). We investigate three sources of uncertainty: How sound energy is perceived by agents with differing hearing abilities; how agents move in response to noise (i.e., the strength and directionality of their evasive movements); and the way in which these responses may interact with longer term constraints on agent movement. The estimate of received sound exposure level (SEL) is influenced most strongly by the weighting function used to account for the specie's presumed hearing ability. Strongly directional movement away from the sound source can cause modest reductions (~5 dB) in SEL over the short term (periods of less than 10 days). Beyond 10 days, the way in which agents respond to noise exposure has little or no effect on SEL, unless their movements are constrained by natural boundaries. Most experimental studies of noise impacts have been short‐term. However, data are needed on long‐term effects because uncertainty about predicted SELs accumulates over time. Synthesis and applications. Simulation frameworks offer a powerful way to explore, understand, and estimate effects of cumulative sound exposure on marine mammals and to quantify associated levels of uncertainty. However, they can often require subjective decisions that have important consequences for management recommendations, and the basis for these decisions must be clearly described.

No MeSH data available.