Characterization and classification of acoustically detected fish spatial distributions
High-resolution, two-dimensional measurements of aquatic-organism density are collected routinely during echo integration trawl surveys. School-detection algorithms are commonly used to describe and analyse spatial distributions of pelagic and semi-pelagic organisms observed in echograms. This appro...
Main Authors: | , |
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Other Authors: | |
Format: | Text |
Language: | English |
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2008
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Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.597.3245 http://icesjms.oxfordjournals.org/content/65/7/1235.full.pdf |
Summary: | High-resolution, two-dimensional measurements of aquatic-organism density are collected routinely during echo integration trawl surveys. School-detection algorithms are commonly used to describe and analyse spatial distributions of pelagic and semi-pelagic organisms observed in echograms. This approach is appropriate for species that form well-defined schools, but is limited when used for species that form demersal layers or diffuse pelagic shoals. As an alternative to metrics obtained from school-detection algor-ithms, we used landscape indices to quantify and characterize spatial heterogeneity in density distributions of walleye pollock (Theragra chalcogramma). Survey transects were divided into segments of equal length and echo integrated at a resolution of 20 m (horizontal) and 1 m (vertical). A series of 20 landscape metrics was calculated in each segment to measure occupancy, patchi-ness, size distribution of patches, distances among patches, acoustic density, and vertical location and dispersion. Factor analysis indi-cated that the metric set could be reduced to four factors: spatial occupancy, aggregation, packing density, and vertical distribution. Cluster analysis was used to develop a 12-category classification typology for distribution patterns. Visual inspection revealed that spatial patterns of segments assigned to each type were consistent, but that there was considerable overlap among types. |
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