The reliability of sockeye-salmon (Oncorhynchus nerka) count data collected by a dual-frequency, identification sonar (DIDSON) system is evaluated on the basis of comparisons with visual counts of unconstrained migrating salmon and visual counts of salmon constrained to passing through an enumeration fence. Regressions fitted to the DIDSON count data and the visual count data from the enumeration fence were statistically indistinguishable from a line with slope = 1.0 passing through the origin, which we interpret as agreement in both counts. In contrast, the regressions fitted to the DIDSON count data and the unconstrained visual count data had slopes that were significantly <1.0 (p < 0.001) and are consistent with an interpretation of systematic bias in these data. When counts of both unconstrained and constrained fish from the DIDSON system were ≥50 fish event−1, repeated counts of the DIDSON files were observed to produce the same counts 98–99% of the time, respectively, and based on the coefficient of variation, counts of individual passage events varied <3% on average. Therefore, the DIDSON count data exhibit high precision among different observers. As an enumeration fence provides a complete census of all fish passing through it, we conclude that fish-count data produced by the DIDSON imaging system are as accurate as visual counts of fish passing through an enumeration fence when counts range up to 932 fish event−1, the maximum count recorded during our study, regardless of the observer conducting the count. These conclusions should be applicable to typical riverine applications of the DIDSON system in which the bottom and surface boundaries are suitable for acoustic imaging, the migrating fish are adult salmon, and the transducer is carefully aimed so that the beams ensonify the area through which the salmon are migrating.

Simulations were performed to evaluate the bias and precision of stock composition estimates from the maximum-likelihood mixture model using hypothetical multilocus characters. Bias and precision were examined in relation to the number of stocks being resolved, the number of loci available, and the difference in allelic frequency among stocks at each locus, using Monte Carlo simulations with different levels of sampling error in the mixture and learning samples. Model performance improved with increasing stock separation and number of loci available. Bias was not affected by the number of stocks resolved in simulations where mixture contributions from individual stocks remained constant. These results provide guidelines for reducing the complexity of genetic stock-identification problems by summing estimated mixing proportions for individual stocks within groupings based on stock similarity. The trade-off between improved accuracy and level of grouping can be examined graphically to determine the most useful level of grouping for the problem at hand. We illustrate this procedure with a real example from mixed-stock fisheries on sockeye salmon (Oncorhynchus nerka) along the British Columbia – Alaska coast.

We observed patterns in echograms of data collected with a dual-frequency identification sonar (DIDSON) that were related to the tail beats of fish. These patterns reflect the size, shape, and swimming motion of the fish and also depend on the fish's angle relative to the axis of the beam. When the tail is large enough to reflect sound of sufficient intensity and the body is angled such that the tail beat produces periodic changes in the range extent covered by the fish image, then the tail beat becomes clearly visible on echograms that plot the intensity maximum of all beams. The analysis of DIDSON echograms of a mix of upstreammigrating Chinook salmon Oncorhynchus tshawytscha and sockeye salmon O. nerka resulted in the separation of two groups: (1) fish of sockeye salmon size that swam with a tail-beat frequency (TBF) between 2.0 and 3.5 beats/s and (2) fish of Chinook salmon size with a TBF between 1.0 and 2.0 beats/s. There was no correlation between TBF and fish size within each group, which suggests that the observed difference in TBF between the two groups was species-specific rather than an indirect effect of the groups' difference in size. The technique of extracting TBF from DIDSON echograms may also be useful for bioenergetics studies. Compared with electromyogram telemetry, it offers the advantages of being nonintrusive and faster to set up and analyze and therefore is suitable for analyzing larger sample sizes. The disadvantages are that the technique's potential is limited to relatively large fish, it can cover only relatively small areas, it cannot be used to follow individual fish over long distances, and some environments are too noisy to produce DIDSON images of sufficient quality.

Abstract.-The purpose of this study was to explore the extent to which a computer-driven process can be used to classify sonar images. The data we present come from a feasibility study for a hydroacoustic monitoring system aimed at the automatic detection of downstream-migrating adult American eels Anguilla rostrata in the intake canal of a small hydroelectric station. The images were collected by a dual-frequency identification sonar with sufficient resolution to show the distinct shape and swimming motion of eels, and thus to allow confident visual identification. The goal was to find a set of image processing, tracking, and pattern recognition techniques that would reproduce the results of the visual classification. Of the three classification methods that we tested with our example data set, neural network analysis had the lowest misclassification rate for eels (7% of the eels being misclassified as debris) and the second-lowest misclassification rate for debris (5% of the debris being misclassified as eels). Discriminant function analysis misclassified 12% of the eels as debris and 4% of the debris as eels. A K-nearest-neighbor analysis initially provided the poorest results (17% misclassified eels and 12% misclassified debris). However, after applying an algebraic correction, K-nearest-neighbor analysis yielded an accurate estimate of the number of eels in the data set. We discuss the value of flagging cases of uncertain classification, how image processing and feature selection can affect the results, and how the numeric ratio of the targets present determines what error rates are acceptable. We conclude that, depending on the application, different degrees of automation may be achieved, ranging from a relatively high degree of human supervision in the classification of all potential targets to a fully automated process that requires only periodic quality control and adjustments of the classification model.

Abstract.— Feed costs are a major portion of aqua‐culture operations. Accurate estimates of daily ration are vital to prevent overfeeding which results in wasted feed. poor water quality, underfeeding, and reduced growth. Understanding the relationship of ingestion rate and absorption efficiency of Strongylocentrotus franciscanus should improve the cost effectiveness of aquaculture of this candidate species. Adult S. franciscanus were collected from a subtidal area devoid of algae and fed two rations of an extruded diet for 62 d. Mean test diameter and whole weight of an initial sample were 91 ± 2 mm and 295 ± 18.4 g (mean ± SEM; N = 16). The two rations used were l‐g dry feed/d or 3 g/d. An unfed control group was also maintained. Eight urchins per treatment showed significant differences in food ingestion rate, total organic absorption, gonad index, gut index, and moisture content of the gonad (P < 0.001). Food intake was greatest in the high ration treatment, while total organic absorption was greatest in the low ration treatment. The gonad index of S. franciscanus in the high food ration was significantly greater than the initial gonad index and was also greater than the index of animals in the low ration and unfed treatments. The gonad index of animals in the low food ration treatment was significantly greater than the index of the initial sample and the index of animals in the unfed treatment. The gut index of urchins in the high food ration treatment was significantly greater than initially and was also greater than the gut index for animals in the low ration and unfed treatments. The gut index for urchins in the unfed treatment was significantly less than the initial index. The moisture content of the gonad of urchins fed the prepared diet was significantly greater than the gonad moisture content of the initial sample or unfed group. Test diameter. whole animal weight, and gonad production efficiency (increase in g dry gonad weight/g dry feed intake) were not significantly different (P > 0.200). Histological examination of the gonads showed S. franciscanus in the two ration treatments developed from the spent to the growing or premature stage while the unfed controls lost nutritive tissue and contained only relict gametes or remained in the spent condition. The results suggest S. franciscanus from food‐limited environments can be fed appropriate rations to control gonad production.