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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Canadian Science Publishing
1991
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Online Access: | http://dx.doi.org/10.1139/f91-201 http://www.nrcresearchpress.com/doi/pdf/10.1139/f91-201 |
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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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1785576216439291904 |