Quantification of Wide-Area Norwegian Spring-Spawning Herring Population Density with Ocean Acoustic Waveguide Remote Sensing (OAWRS)

Abstract

Norwegian spring-spawning herring are a critical economic resource for multiple nations in the North Atlantic and a keystone species of the Nordic Seas ecosystem. Given the wide areas that the herring occupy, it is difficult to accurately measure the population size and spatial distribution. Ocean Acoustic Waveguide Remote Sensing (OAWRS) was used to instantaneously measure the areal population density of Norwegian herring over more than one thousand square kilometers in spawning grounds near Ålesund, Norway. In the vicinity of the Ålesund trench near peak spawning, significant attenuation in signal-to-noise ratio and mean sensing range was observed after nautical sunset that had not been observed in previous OAWRS surveys in the Nordic Seas or in other regions. We show that this range-dependent decay along a given propagation path was caused by attenuation through dense herring shoals forming at sunset and persisting through the evening for transmissions near the swimbladder resonance peak. OAWRS transmissions are corrected for attenuation in a manner consistent with waveguide scattering theory and simultaneous downward directed local line-transect measurements in the region in order to produce instantaneous wide-area population density maps. Corresponding measured reductions in the median sensing range over the azimuth before ambient noise limitation are shown to be theoretically predictable from waveguide scattering theory and observed population densities. Spatial-temporal inhomogeneities in wide-area herring distributions seen synoptically in OAWRS imagery show that standard sparsely spaced line-transect surveys through this region during spawning can lead to large errors in the estimated population due to spatial and temporal undersampling.

1. Introduction

Norwegian spring-spawning herring is a critical economic resource for multiple nations in the North Atlantic. Since 2013, disagreements over the shifting spatial distribution of this herring stock have prevented these nations from negotiating quota sharing agreements, resulting in a combined catch exceeding the recommended limit by more than 30% in the past three years [1]. It is therefore important to accurately measure the population size and spatial distribution for Norwegian herring over ecosystem scales. Oceanic fish groups, however, occupy vast undersea areas that are difficult to sample without significant aliasing in space and time with conventional survey methods [2,3].

Here, we demonstrate the ability of Ocean Acoustic Waveguide Remote Sensing (OAWRS) to instantaneously image Norwegian herring shoals over more than one thousand square kilometers in spawning grounds near Ålesund, Norway. Wide-area OAWRS scattering strength maps are generated by correcting transmissions for source level and areal resolution footprint, as well as transmission losses from spreading and seafloor attenuation [4,5,6,7,8].

Previous OAWRS experiments have revealed the diel shoaling patterns of massive fish groups, including vertical migrations of shoaling herring measured from changes in the resonance frequency of the fish as they move from deep water to their spawning locations [9]. OAWRS also revealed that shoaling fish tend to rapidly congregate in massive groups spanning tens of kilometers when the fish population density reaches a species-specific critical value [4]. Shoal growth was found to propagate horizontally outward in compressional waves at speeds orders of magnitude larger than the swimming speed of a fish, indicating that shoal formation is the result of synchronous convergence of individual fish [4,5].

These massive fish groups are found to have a relatively stable mean size, and historical population surveys have shown that when a given species was overfished to the point where the total spawning population fell within a standard deviation of the group size a return to pre-industrial total spawning populations took decades [10]. OAWRS has also been used to observe ecosystem-scale interactions between fish groups and marine mammals that forage for fish, and it was shown that marine mammals will spatially converge on fish spawning grounds and divide into separate foraging areas specific to each marine mammal species [11].

Here, OAWRS is used to investigate the effects of diel shoaling behavior of fish groups on acoustic sensing in the ocean. During the day, the OAWRS system revealed small, dispersed groups of herring in the Ålesund spawning grounds with dimensions that were typically less than 1 km. After nautical sunset, the formation of numerous dense herring groups was observed, corresponding with a significant range-dependent decay in OAWRS imagery even after making typical corrections for spreading loss and seafloor attenuation.

This range-dependent decay can be explained by acoustic attenuation through the dense herring groups. Such attenuation requires exceptionally high fish population densities over significant portions of the water column and extended ranges [12] and thus was not observed previously in OAWRS fish sensing, including Mid-Atlantic Bight herring [5], Gulf of Maine herring [6] and Lofoten cod [10]. Reductions in the ambient noise level after nautical sunset can be similarly explained by attenuation from the herring groups.

The organization of this paper is as follows: wide-area OAWRS maps of herring population density are presented, and range-dependent decays in OAWRS transmissions are corrected with a theoretical formulation that was previously shown to be consistent with experimental measurements of attenuation from fish in a waveguide environment [12,13]. Formulations are then introduced for predicting ambient noise reductions and sensing range reductions due to attenuation from fish. The predicted reductions in ambient noise are shown to be theoretically consistent with the measured reductions when dense herring shoals form after nautical sunset.

Theoretical predictions of sensing range are confirmed using measurements of OAWRS sensing range in the presence of herring in Ålesund spawning grounds, capelin in Finnmark spawning grounds, and cod in Lofoten spawning spawning grounds. Spatial-temporal inhomogeneities in wide-area herring distributions observed by OAWRS indicate that significant errors are expected in sparse temporal-spatial line transect surveys through this region during spawning. Equivalent echosounder measurements of the herring population, for example, are estimated by sampling 2014 spatially continuous OAWRS wide-area population density data with the sparse line-transects of a 2001 herring survey in the same region.

2. Methods and Materials

2.1. Population Density Measurements without Significant Fish-Attenuation

Ocean Acoustic Waveguide Remote Sensing (OAWRS) is used to instantaneously monitor Norwegian herring spawning grounds over more than one thousand square kilometers off the coast of Ålesund, Norway (Figure 1). OAWRS sound pressure level maps are generated by beamforming, matched filtering and charting scattered returns [4,5,6,7,8]. Scattering strength levels are determined by correcting sound pressure level maps for source level, areal resolution footprint, spreading loss and seafloor attenuation [4,5,6,7] (Appendix A).

Approximately one hour before nautical sunset, the OAWRS system reveals small, dispersed groups of herring with dimensions that are typically less than 1 km (Figure 2A), and there are few herring groups observed in echosounder measurements from the research vessel towing the OAWRS system (Figure 2B). Scattering strength is converted to areal population density by calibration with local in situ measurements of population density obtained from vertical echosounder measurements (Appendix B), and the dispersed herring groups are found to have population densities on the order of 0.3 fish/m² (Figure 3).

During this time, the median sensing range over azimuth for the OAWRS system is approximately 20 km, where the sensing range is defined as the minimum range where scattered returns from the environment fall within the detection threshold of the ambient noise (Appendix C). Attempts to measure scattering strength beyond the sensing range limit where ambient noise dominates will not lead to an actual scattering strength but to a quantity that increases with range since transmission loss corrections are being applied to ambient noise with relatively constant mean intensity over time unless it is dominated by a particular nearby ship or sound source.

2.2. Correcting Population Density Maps for Fish-Attenuation

On the same day and in the same region as the daylight measurements of Figure 2 and Figure 3, there is a significant range-dependent decay in the intensity of OAWRS transmissions after sunset, even after making the same standard corrections as in Figure 2 for source level, areal resolution footprint, spreading loss, and seafloor attenuation (Figure 4). This range-dependent decay can be explained by acoustic attenuation from dense herring groups forming at sunset, which are observed in both OAWRS imagery and echosounder measurements from the research vessel towing the OAWRS system.

OAWRS images are corrected for attenuation from fish scattering using a theoretical formulation that has been previously shown to be consistent with experimental measurements of attenuation from fish in a waveguide (Appendix D) [12,13] (Figure 5). The theoretical decay due to attenuation depends on the average population density of fish within the sensing region ${\overline{n}}_A$, which is estimated by modeling the fish-attenuated scattering strength ($\widetilde{SS}\equiv SS-\Delta SP{L}_{2way}$) assuming a horizontally uniform distribution of fish within the OAWRS sensing region and performing a least-squares fit between the measured and modeled fish-attenuated scattering strength.

Measurements of the mean fish-attenuated scattering strength ($〈{\widetilde{SS}}_{data}〉$) with respect to range $\rho$ are calculated by correcting OAWRS sound pressure level maps for source level, areal resolution footprint, spreading loss and seafloor attenuation according to Equation (A4), and then averaging across azimuthal angle excluding beams within 25° of endfire. The modeled fish-attenuated scattering strength (${\widetilde{SS}}_{model}$) at range $\rho$ and assuming average areal density ${\overline{n}}_A$ is given by:

$${\widetilde{SS}}_{model}({\overline{n}}_A,\rho )\equiv 10{log}_{10}\left({10}^{S{S}_{fish}\left(n_A\right)/10}+{10}^{S{S}_{seafloor}/10}\right)-\Delta SP{L}_{2way,model}(n_A,\rho )$$

(1)

where $S{S}_{seafloor}=-43\mathrm{dB}$ is the measured scattering strength of seafloor in the region, and $S{S}_{fish}$ is the scattering strength of the fish groups, given [7] by:

$$S{S}_{fish}\left(n_A\right)=TS+10{log}_{10}\left(n_A\right)$$

(2)

where $TS$ is the target strength of an individual fish (Appendix E) and $\Delta SP{L}_{2way,model}$ is the predicted reduction in sound pressure level caused by attenuation from fish (Equation (A15)), which is modeled assuming the depth distribution of herring groups measured by echosounders during this time (Figure A6).

The average areal density of the herring within the sensing region of the OAWRS system is determined using a least-square estimation performed by maximizing the likelihood function. Since the acoustic field can be described as a circular complex Gaussian random variable (CCGR) and the time-bandwidth product of the acoustic measurements $\mu =\left(1\mathrm{s}\right)\left(50\mathrm{Hz}\right)\gg 1$, intensity measurements in the logarithmic domain, such as the fish-attenuated scattering strength, can be well-approximated as Gaussian random variables with variance independent of the mean [14,15]. The mean herring areal density is estimated by maximizing the log-likelihood function $\ell \left({\overline{n}}_A\right)$ assuming that fish-attenuated scattering strength $\widetilde{SS}$ is a Gaussian random variable with variance independent of the mean:

$$\ell \left({\overline{n}}_A\right)={\int }_{{\rho }_{min}}^{{\rho }_{sens}}-\frac{{\left({\widetilde{SS}}_{model}({\overline{n}}_A,\rho )-〈{\widetilde{SS}}_{data}\left(\rho \right)〉\right)}^2}{{\sigma }_{\widetilde{SS}}{\left(\rho \right)}^2}\rho d\rho$$

(3)

where ${\sigma }_{\widetilde{SS}}{\left(\rho \right)}^2$ is the variance of ${\widetilde{SS}}_{data}$ in dB at range $\rho$, and the differential $\rho d\rho$ is chosen in order to integrate over range in polar coordinates. Since the log-likelihood function is calculated by integrating the weighted difference squared across range in polar coordinates, measurements at longer ranges are weighted more heavily since they correspond to a larger area.

The minimum range ${\rho }_{min}$ = 2 km is chosen so that acoustic data is only considered at ranges well above farfield $\rho >L^2/\lambda$, where L = 47.25 is the length of the receiver array [16] and $\lambda$ = 1.57 m is the acoustic wavelength at the sensing frequency 955 Hz. The sensing range ${\rho }_{sens}$ is defined in Section 2.4. Once the average areal density ${\overline{n}}_A$ is determined for a given OAWRS transmission, a range-dependent correction can be applied to scattering strength maps at each azimuthal angle according to:

$$SS(\rho ,\theta )={\widetilde{SS}}_{data}(\rho ,\theta )+\Delta SP{L}_{2way}({\overline{n}}_A,\rho )$$

(4)

This method is used to produce herring population density maps after nautical sunset where attenuation is significant (Figure 6). Multiple large herring groups are observed after sunset with dimensions of several kilometers and population densities of up to roughly five fish/m², which is consistent with echosounder measurements during this time (Figure A5).

2.3. Predicting Ambient Noise Reductions from Fish-Attenuation

Reductions in the ambient noise level are observed after nautical sunset (Figure 7A), and they can be explained by attenuation from herring groups. Here, a formulation is introduced for predicting reductions in the ambient noise levels due to attenuation from fish. Since the dominant source of ambient noise is assumed to be surface waves, ambient noise is modeled as coming from a uniform set of uncorrelated monopoles at the surface. The intensity of the ambient noise field in a shallow water environment is then given [17] by:

$$I=\frac{8{\pi }^2{q}^2}{k^2}{\int }_0^{\infty }\xi \left|g(\xi ;z,z_0)\right|d\xi$$

(5)

where k is the wavenumber, q is the amplitude of an individual monopole at depth $z_0$ near the surface, and $g(\xi ;z,z_0)$ is the wavenumber-depth Green function for horizontal wavenumber $\xi$ and receiver depth z, which can be written in a waveguide environment in terms of normal modes [17] as follows:

$$g(\xi ;z,z_0)=\frac{d}{2\pi }\sum _n\frac{u_n\left(z\right)u_n\left(z_0\right)}{{\xi }^2-{\xi }_n^2}$$

(6)

where ${\xi }_n$ is the modal horizontal wavenumber, d is water density, and the amplitude of mode n at receiver depth z is given by $u_n\left(z\right)$.

In order for the integral in Equation (5) to converge, some attenuation must be included in the system. This is because the signal from each monopole suffers cylindrical spreading loss, but the energy radiated by the monopoles increases with the range from the receiver squared [17]. Environmental attenuation (not including attenuation from fish) is introduced by letting the wavenumber k be complex:

$$k=\frac{2\pi f}{c}+iϵ$$

(7)

where f is the frequency, c is the speed of sound in water, and $ϵ$ is a coefficient for environmental attenuation excluding fish [17,18]. The modal wavenumbers (${\xi }_n$) are also assumed to be complex, with the form:

$${\xi }_n={\kappa }_n+i{\alpha }_n$$

(8)

where the modal attenuation coefficient ${\alpha }_n$ is given [19] by

$${\alpha }_n=\frac{ϵ}{{\kappa }_n}{\int }_0^D\frac{2\pi f}{c\left(z\right)}{\left|u_n\left(z\right)\right|}^{2}dz$$

(9)

where D is the water depth. In the absence of attenuation from fish, the ambient field can then be written [17] as:

$$I=\frac{\pi q^2{d}^2}{2k^2}\sum _n\frac{u_n{\left(z\right)}^2{u}_n{\left(z_0\right)}^2}{{\kappa }_n{\alpha }_n}$$

(10)

In the presence of fish, the modal wavenumber equation is modified to include the modal coefficients for attenuation and dispersion from fish (${\nu }_n$):

$${\xi }_n={\kappa }_n+i{\alpha }_n+{\nu }_n\left(n_A\right)=({\kappa }_n+\Re \left[{\nu }_n\left(n_A\right)\right])+i({\alpha }_n+\Im \left[{\nu }_n\left(n_A\right)\right])$$

(11)

where ${\nu }_n\left(n_A\right)$ is defined in Equation (A22). Following the same derivation that led to Equation (10), the ambient noise field in the presence of attenuation from fish can be written as:

$$I_{attn}\left(n_A\right)=\frac{\pi q^2{d}^2}{2k^2}\sum _n\frac{u_n{\left(z\right)}^2{u}_n{\left(z_0\right)}^2}{({\kappa }_n+\Re \left[{\nu }_n\left(n_A\right)\right])({\alpha }_n+\Im \left[{\nu }_n\left(n_A\right)\right])}$$

(12)

The decrease in the ambient noise level from attenuation as fish density increases from $n_{A1}$ to $n_{A2}$ can then be given by:

$$\begin{array}{c}\Delta N{L}_{partial}(n_{A1},n_{A2})=10{log}_{10}\left(\frac{I_{attn}\left(n_{A1}\right)}{I_{attn}\left(n_{A2}\right)}\right)\hfill \\ =10{log}_{10}[\left(\sum _n\frac{u_n{\left(z\right)}^2{u}_n{\left(z_0\right)}^2}{({\kappa }_n+\Re \left[{\nu }_n\left(n_{A1}\right)\right])({\alpha }_n+\Im \left[{\nu }_n\left(n_{A1}\right)\right])}\right)\\ \hfill {\left(\sum _n\frac{u_n{\left(z\right)}^2{u}_n{\left(z_0\right)}^2}{({\kappa }_n+\Re \left[{\nu }_n\left(n_{A2}\right)\right])({\alpha }_n+\Im \left[{\nu }_n\left(n_{A2}\right)\right])}\right)}^{-1}]\end{array}$$

(13)

where $n_{A1}<n_{A2}$.

2.4. Predicting Sensing Range Reductions from Fish-Attenuation

The observed reductions in signal intensity and ambient noise due to attenuation from fish can contribute to fluctuations in the sensing range for long-range active acoustic sensing systems in the ocean. Here, a formulation is introduced for predicting sensing range in the presence of attenuation from fish. The sensing range (${\rho }_{sens}$) is defined as:

$${\rho }_{sens}(f,n_A)=min\left[\rho \right|SP{L}_A(\rho ,f,n_A)>NL\left(f\right)-\Delta NL(f,n_A)+DT]$$

(14)

where $SP{L}_A$ is the azimuthally intensity-averaged sound-pressure level of the received signal, $NL$ is the ambient noise level, $DT$ is the detection threshold, f is the sensing frequency, and it is assumed that fish are uniformly distributed in the horizontal within the sensing region with average areal density $n_A$. Ambient noise level $NL$ is determined from measurements before nautical sunset (17:00–18:30 on 20 February) in order to avoid attenuation effects caused by the formation of herring groups after nautical sunset (Figure 7A). The reduction in ambient noise due to attenuation from fish ($\Delta NL$) is modeled according to Section 2.3. The azimuthally intensity-averaged sound-pressure level $SP{L}_A$ is estimated by averaging the intensity of the scattered field across the azimuthal angle $\theta$:

$$SP{L}_A(\rho ,f,n_A)=10{log}_{10}\left(\frac{1}{{\theta }_{max}-{\theta }_{min}}{\int }_{{\theta }_{min}}^{{\theta }_{max}}{\left|\frac{\mathsf{\Psi }(\rho ,f,n_A,\theta )}{{\mathsf{\Psi }}_{ref}}\right|}^{2}d\theta \right)$$

(15)

where $\mathsf{\Psi }(\rho ,f,n_A,\theta )$ is the modeled scattered field, ${\mathsf{\Psi }}_{ref}=1 \mathsf{\mu }\mathrm{Pa}$ is the reference pressure for underwater sound, and the limits of integration ${\theta }_{min}$ and ${\theta }_{max}$ are chosen to exclude beams within 25° of endfire. Assuming that scattered returns from the environment are dominated by scattering from fish groups rather than seafloor scattering, the intensity of the scattered field ${\left|\frac{\mathsf{\Psi }(\rho ,f,n_A,\theta )}{{\mathsf{\Psi }}_{ref}}\right|}^2$ is modeled according [12] to

$$10{log}_{10}{\left|\frac{\mathsf{\Psi }(\rho ,f,n_A,\theta )}{{\mathsf{\Psi }}_{ref}}\right|}^2=SL+TLA(\rho ,f,\theta )+TS\left(f\right)+10{log}_{10}\left(n_A\right)-\Delta SP{L}_{2way}(\rho ,f,n_A)$$

(16)

Transmission loss area $TLA$ is calculated according to Equation (A2). The formulation for target strength $TS$ is shown in Appendix E and the formulation for the decrease in sound pressure level during two-way propagation due to the attenuation from fish ($\Delta SP{L}_{2way}$) is shown in Equation (A15).

3. Results

3.1. Ambient Noise Reductions from Fish-Attenuation

Reductions in the ambient noise level observed after nautical sunset are found to be consistent with the predicted reductions in ambient noise due to attenuation from fish (Figure 7). The decrease in ambient noise due to the formation of herring groups at nautical sunset on 20 February 2014 is predicted using Equation (13). The average areal density after nautical sunset ($n_{A1}$) is determined to be 0.08 fish/m² by taking the average of OAWRS areal density measurements between 17:00 and 18:30 (Figure 5D).

The average areal density after nautical sunset ($n_{A2}$) is determined to be 0.2 fish/m² by taking the average of OAWRS measurements of areal density between 19:30 and 21:00 (Figure 5D). The modeled coefficient for environmental attenuation excluding fish $ϵ$ is determined by maximizing the following likelihood function:

$$\ell \left(ϵ\right)=\sum _{i=1}^{N_f}\left(\frac{-(N{L}_{model}(ϵ,f_i)-〈\Delta NL\left(f_i\right)〉)}{{\sigma }_{\Delta NL}{\left(f_i\right)}^2}\right)$$

(17)

where $〈\Delta NL\left(f_i\right)〉$ is the mean reduction in ambient noise at frequency $f_i$, ${\sigma }_{\Delta NL}\left(f_i\right)$ is the standard deviation at frequency $f_i$, $N_f$ is the number of frequencies where $\Delta NL$ is measured, and the coefficient for environmental attenuation excluding fish $ϵ$ is assumed to be in units of ${\lambda }^{-1}$. The likelihood function is maximized at $ϵ=5\times {10}^{-5}{\lambda }^{-1}$, which is in the same order of magnitude as previous experimental measurements of environmental attenuation in waveguide environments [18].

3.2. Sensing Range Reductions from Fish-Attenuation

The range-dependent decay in OAWRS transmissions due to attenuation from fish leads to significant reductions in the sensing range (Figure 8). Thirty minutes before nautical sunset, the average fish population density within the sensing region is below 0.1 fish/m² and the sensing range remains approximately constant (20 km). In the two hours following nautical sunset, the fish population density increases to nearly 0.3 fish/m², corresponding with reductions in the sensing range of 20%.

Measured reductions in sensing range are found to be theoretically predictable from waveguide scattering theory and observed population densities. Sensing range predictions depend on the average density of fish within the sensing region as well as the source power of the sensing system and ambient noise level (Section 2.4). The sensing range is predicted for both Ålesund herring and Finnmark capelin, and the predictions are in agreement with OAWRS measurements in both environments (Figure 9). The sensing range predictions for Lofoten cod exceed the maximum possible range that could be recorded in the 50 s recording window that was used in this region (Figure 9C). The formulation introduced here can be used to predict the performance of active sensing systems using historical surveys of fish population density in the relevant region, as well as fluctuations in the sensing range using known diel and annual variations in population density.

3.3. Spatial Undersampling in Echosounder Surveys

Spatial inhomogeneities in wide-area herring distributions seen synoptically in OAWRS imagery can be spatially undersampled in typical echosounder surveys, which can result in significant overestimation or underestimation of the fish population in the survey region. Equivalent echosounder estimates of herring population density, for example, are made by sampling 2014 spatially continuous OAWRS wide-area population density data (Figure 3, Figure 6 and Figure 10) with the sparse line-transects of a 2001 herring survey in the same region [20]. The measured population size within the survey box for each OAWRS image shown in Figure 10 is shown in Figure 11.

The total population estimate from line-transect sampling is then calculated by multiplying the average population density along the transect with a specified survey area (Figure 12A). Resulting population estimates in this area range from 0.5 to 2.5 times the population found using the entire OAWRS population density data for the region (Figure 12B). Wide-area spatial population density maps made with OAWRS can be used in conjunction with conventional line-transect survey methods to provide better estimates of herring population and spatial distribution.

4. Discussion

It is experimentally shown that Ocean Acoustic Waveguide Remote Sensing (OAWRS) can be used to instantaneously measure wide-area fish population density, even in environments where sensing is affected by attenuation from fish. OAWRS imagery of Norwegian spring-spawning herring is corrected for attenuation in a manner consistent with waveguide scattering theory in order to produce population density maps over more than one thousand square kilometers during dense shoaling activity. We found that attenuation from dense herring groups forming after nautical sunset on February 20 resulted in reductions in sensing range of roughly 20%.

It is also shown that attenuation from fish groups forming at nautical sunset can result in ambient noise reductions. In future experiments, it may be possible to make crude inferences about diel changes in fish population density from fluctuations in ambient noise. It has been previously shown that attenuation from Norwegian herring can be significant at the sensing frequencies and typical shoaling densities in this experiment, and attenuation can be significantly reduced in this environment by choosing sensing frequencies above or below the swimbladder resonance of the herring (>2 kHz or <500 Hz) [12]. Such attenuation requires exceptionally high fish population densities over significant portions of the water column and extended ranges and, thus, was not observed previously in OAWRS sensing of swimbladder-bearing fish including Mid-Atlantic Bight herring [5], Gulf of Maine herring [6], and Lofoten cod [10].

5. Conclusions

Ocean Acoustic Waveguide Remote Sensing (OAWRS) is used to instantaneously monitor spawning Norwegian herring population densities over wide areas, spanning more than one thousand square kilometers, in the Nordic Seas near the Ålesund trench where herring are known to spawn. Larger spawning shoals often spanning a few kilometers are instantaneously imaged in their entirety. Reductions of roughly 20% in sensing range after sunset have been found due to the corresponding formation of larger and denser herring shoals after sunset for OAWRS transmissions near swimbladder resonance.

This attenuation is corrected for in a manner consistent with waveguide scattering theory, leading to instantaneous wide-area OAWRS population density maps up to the sensing range of ambient noise limitation. Sensing range reductions due to attenuation from fish are shown to be theoretically predictable from waveguide scattering theory and observed population densities. Such sensing range reductions may also limit the ability of vocalizing marine mammals to echolocate in regions with dense fish shoals [21,22].

Spatial-temporal inhomogeneities in wide-area herring distributions observed by OAWRS indicate that large errors are expected in the population density estimates made from sparse line-transect surveys through this region during spawning. This is due to the significant temporal and spatial aliasing of the non-homogeneous herring population density distributions observed by OAWRS. The population density maps provided by OAWRS can then be used in conjunction with conventional line-transect survey methods to efficiently provide more accurate estimates of herring populations and temporal-spatial distributions.