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...

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Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Author: Sullivan, Patrick J.
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 1991
Subjects:
Online Access:http://dx.doi.org/10.1139/f91-201
http://www.nrcresearchpress.com/doi/pdf/10.1139/f91-201
id crcansciencepubl:10.1139/f91-201
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spelling crcansciencepubl:10.1139/f91-201 2023-12-17T10:51:04+01:00 Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation Sullivan, Patrick J. 1991 http://dx.doi.org/10.1139/f91-201 http://www.nrcresearchpress.com/doi/pdf/10.1139/f91-201 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 48, issue 9, page 1691-1703 ISSN 0706-652X 1205-7533 Aquatic Science Ecology, Evolution, Behavior and Systematics journal-article 1991 crcansciencepubl https://doi.org/10.1139/f91-201 2023-11-19T13:38:57Z 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 Article in Journal/Newspaper Theragra chalcogramma Canadian Science Publishing (via Crossref) Canadian Journal of Fisheries and Aquatic Sciences 48 9 1691 1703
institution Open Polar
collection Canadian Science Publishing (via Crossref)
op_collection_id crcansciencepubl
language English
topic Aquatic Science
Ecology, Evolution, Behavior and Systematics
spellingShingle Aquatic Science
Ecology, Evolution, Behavior and Systematics
Sullivan, Patrick J.
Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
topic_facet Aquatic Science
Ecology, Evolution, Behavior and Systematics
description 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
format Article in Journal/Newspaper
author Sullivan, Patrick J.
author_facet Sullivan, Patrick J.
author_sort Sullivan, Patrick J.
title Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
title_short Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
title_full Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
title_fullStr Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
title_full_unstemmed Stock Abundance Estimation Using Depth-Dependent Trends and Spatially Correlated Variation
title_sort stock abundance estimation using depth-dependent trends and spatially correlated variation
publisher Canadian Science Publishing
publishDate 1991
url http://dx.doi.org/10.1139/f91-201
http://www.nrcresearchpress.com/doi/pdf/10.1139/f91-201
genre Theragra chalcogramma
genre_facet Theragra chalcogramma
op_source Canadian Journal of Fisheries and Aquatic Sciences
volume 48, issue 9, page 1691-1703
ISSN 0706-652X 1205-7533
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/f91-201
container_title Canadian Journal of Fisheries and Aquatic Sciences
container_volume 48
container_issue 9
container_start_page 1691
op_container_end_page 1703
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