Statistical relationships between the distributions of groundfish and crabs in the eastern Bering Sea and processed returns from a single-beam echosounder
<qd> McConnaughey, R. A., and Syrjala, S. E. 2009. Statistical relationships between the distributions of groundfish and crabs in the eastern Bering Sea and processed returns from a single-beam echosounder. – ICES Journal of Marine Science, 66: 1425–1432. </qd>Groundfish and benthic inve...
Published in: | ICES Journal of Marine Science |
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Main Authors: | , |
Format: | Text |
Language: | English |
Published: |
Oxford University Press
2009
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Subjects: | |
Online Access: | http://icesjms.oxfordjournals.org/cgi/content/short/66/6/1425 https://doi.org/10.1093/icesjms/fsp147 |
Summary: | <qd> McConnaughey, R. A., and Syrjala, S. E. 2009. Statistical relationships between the distributions of groundfish and crabs in the eastern Bering Sea and processed returns from a single-beam echosounder. – ICES Journal of Marine Science, 66: 1425–1432. </qd>Groundfish and benthic invertebrates are not randomly distributed over the continental shelf of the eastern Bering Sea (EBS). Annual trawl surveys reveal distributional patterns that vary according to species, and substantial interannual variation in these patterns suggests some degree of environmental control. Quantitative habitat models are developed to explain the distribution and abundance of species in the EBS. Simple models based on readily available data (temperature and depth) are somewhat informative, but offer limited practical value. Earlier research in the EBS indicated that surficial sediments affect the distribution and abundance of groundfish. However, traditional sampling with grabs and cores is impractical over large areas, and an efficient sampling strategy is needed. Echosounders allow surveys of large areas, but it is unknown if they measure the relevant properties of sediments. Seabed echoes from a calibrated, single-beam echosounder were recorded over 17 000 km of trackline covering the EBS shelf. Generalized additive models were used to fit acoustic and other variables to abundance data for ten species. The final models explained 28–77% of the variability in abundances, including a marginal contribution of 2–13% by the acoustic predictors. |
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