Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
Hydroacoustic data commonly contain a large number of observations that are correlated in space and time. Such data are complicated to analyze, and a good estimate of the error in abundance is often difficult to obtain. Hydroacoustic data collected on Shelikof Strait walleye pollock (Theragra chalco...
| Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
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Canadian Science Publishing
1991
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1139/f91-201 http://www.nrcresearchpress.com/doi/pdf/10.1139/f91-201 |
| Summary: | Hydroacoustic data commonly contain a large number of observations that are correlated in space and time. Such data are complicated to analyze, and a good estimate of the error in abundance is often difficult to obtain. Hydroacoustic data collected on Shelikof Strait walleye pollock (Theragra chalcogramma) are used to develop statistical techniques for analyzing survey data containing spatial trends and spatial correlations. The data show a trend in fish density with depth, while detrended observations exhibit spatial correlation. Spatial means and variances of fish density, and total abundance and its variance, are determined using the geostatistical theory of kriging. The total abundance estimate is the same order of magnitude as estimates arrived at using a stratified estimation approach. Detrending the data with respect to depth through depth stratification decreased the estimated variance by nearly a factor of 10. Detrending the data with respect to depth and kriging the residual variation over space reduced the variance by an additional factor of 2. Modeling trends and making more efficient use of the data contribute to the gain in information |
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