Pelagic fishes are a major source of protein and unsaturated fatty acids, and robust management is critical to avoid overfishing. Fisheries management is often supported by indices from scientific acoustic-trawl surveys, where vertically aligned echo sounders and trawl samples are used to provide an estimate of abundance. Survey biases may be introduced when fish are located near the sea surface or if they avoid the survey vessel. Horizontally scanning acoustic equipment, such as fish-detection sonars, have been proposed as a method to quantify such biases; however, manual interpretation of the data hamper further development. An automated method for identifying fish aggregations within large volumes of sonar data has been developed. It exploits the fact that near-stationary targets, i.e. a fish school, have distinct patterns through the data. The algorithm is not instrument specific, and was tested on data collected from several acoustic-trawl surveys in the Norwegian Sea. The automatic algorithm had a similar performance to manual interpretation, and the main cause of discrepancies was aggregations overlooked in the manual work. These discrepancies were substantially reduced in a second round of manual interpretation. We envision that this method will facilitate a labour efficient and more objective analysis of sonar data and provide information to support fisheries management for pelagic fish.
Density-dependent growth, which might influence the effects of fisheries on a population, is often ignored when management strategies are evaluated, mainly due to a lack of appropriate models readily available to be implemented. To improve on this, we investigated if somatic growth in Norwegian spring-spawning herring (Clupea harengus) depends on cohort density using a formulation of the von Bertalanffy growth function on cohorts from 1921 to 2014 and found a significant negative correlation between estimated asymptotic length and density. This clearly indicates density-dependent effects on growth, and we propose a model that can be used to predict the size-at-age of Norwegian spring-spawning herring as a function of herring density (the abundance of two successive cohorts) in short-term predictions of catch advice, and in Management strategy evaluations, including estimation of their reference points such as FMSY.
The equivalent beam angle is a key parameter in echo integration, where it is assumed that targets are uniformly distributed within the sampling volume of the transducer beam. For a horizontally oriented sonar, this assumption is violated if the vertical distribution of fish is non-uniform throughout a sample, potentially causing a substantial bias in estimates of fish abundance or biomass. This paper investigates the magnitude of this bias using observations and simulated data, where in each case the vertical distribution of fish within a limited geographical area is estimated.
Multi-beam sonar is commonly used in purse seine fishing to visually evaluate school size and biomass. However, quantitative analyses of the across-beam school dimensions may provide more accurate estimates of school volumes. These may help fishers improve their estimates of fish biomass prior to setting a purse seine set; and assist scientists to more accurately assess the distributions and abundances of pelagic schooling fishes. Fish-school volumes are evaluated using data from a simulated Simrad SX90 sonar. The accuracy of the estimates is dependent on the number of ensonifying beams, and therefore dependent on the school size and range from transducer. We present two models, derived through simulations, to correct for distortions of the target dimensions, both horizontally and vertically. The corrected school heights and widths have precisions of 8.5–10.5% vertically and 6.6–8.7% horizontally.
Economic profitability and responsible fisheries are objectives of fishermen and fisheries managers. In purse seine fisheries, an accurate biomass estimate of the targeted school is crucial to accomplish this. For this study, omnidirectional fisheries sonar was used to estimate individual school biomass of Norwegian spring spawning herring (Clupea harengus) and Atlantic mackerel (Scomber scombrus). A sonar sampling design based on professional skipper’s experience provided detailed information on school dimensions and acoustic backscattering. Using calibrated digital sonar data, school volume and fish densities were obtained, and school biomass computed. A positive linear relation was found between the estimated sonar school biomass and purse seine catches for both species (r2 = 0.92; residual standard error, RSE = 4.7 t). Large variability in volume backscattering coefficient and uncertainty in side-aspect target strength (TS) are the main sources of discrepancy between the estimates and the catch. Using a 4 dB (39%) weaker mean TS for mean side-aspect TS than the normal mean dorsal aspect TS was needed for optimizing the 1:1 relationship between sonar biomass estimate and catch. Accurate estimation of single school biomass can reduce the catch of unexpectedly large schools, leading to improvements in economic efficiency and reduced release of dead or dying fish.
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