Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation
Abstract Salmon populations are highly variable in both space and time. Accurate forecasting of the productivity of salmon stocks makes effective management and conservation of the resource extremely challenging. Furthermore, widespread and consistent data on the productivity of species‐specific and...
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crwiley:10.1002/esp.2044 2024-09-15T18:15:56+00:00 Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation Luck, Matthew Maumenee, Niels Whited, Diane Lucotch, John Chilcote, Samantha Lorang, Mark Goodman, Daniel McDonald, Kyle Kimball, John Stanford, Jack 2010 http://dx.doi.org/10.1002/esp.2044 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.2044 https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.2044 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Earth Surface Processes and Landforms volume 35, issue 11, page 1330-1343 ISSN 0197-9337 1096-9837 journal-article 2010 crwiley https://doi.org/10.1002/esp.2044 2024-08-09T04:30:53Z Abstract Salmon populations are highly variable in both space and time. Accurate forecasting of the productivity of salmon stocks makes effective management and conservation of the resource extremely challenging. Furthermore, widespread and consistent data on the productivity of species‐specific and total salmon stocks in a river are almost nonexistent. Ranking rivers based on physical complexity derived from remote sensing allows rivers to be objectively compared. Our approach considered rivers with great geomorphic complexity (e.g. having expansive, multichanneled floodplains and/or on‐channel lakes) as likely to have greater productivity of salmon than rivers flowing in constrained or canyon‐bound channels. Our objective was to develop a database of landscape metrics that could be used to rank the rivers in relation to potential salmon productivity. We then examined the rankings in relation to existing empirical (monitoring) data describing productivity of salmon stocks. To extract the metrics for each river basin we used a digital elevation model and multispectral satellite imagery. We developed procedures to extract channel networks, floodplains, on‐channel lakes and other catchment features; variables such as catchment area, channel elevation, main channel length, floodplain area, and density of hydrojunctions (nodes) were measured. We processed 1509 catchments in the North Pacific Rim including the Kamchatka Peninsula in Russia and western North America. Overall, catchments were most physically complex in western Kamchatka and western Alaska, and particularly on the Arctic North Slope of Alaska. We could not directly examine coherence between potential and measured productivity except for a few rivers, but the expected relationship generally held. The resulting database and systematic ranking are objective tools that can be used to address questions about landscape structure and biological productivity at regional to continental extents, and provide a way to begin to efficiently prioritize the allocation ... Article in Journal/Newspaper Kamchatka Kamchatka Peninsula north slope Alaska Wiley Online Library Earth Surface Processes and Landforms 35 11 1330 1343 |
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Wiley Online Library |
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crwiley |
language |
English |
description |
Abstract Salmon populations are highly variable in both space and time. Accurate forecasting of the productivity of salmon stocks makes effective management and conservation of the resource extremely challenging. Furthermore, widespread and consistent data on the productivity of species‐specific and total salmon stocks in a river are almost nonexistent. Ranking rivers based on physical complexity derived from remote sensing allows rivers to be objectively compared. Our approach considered rivers with great geomorphic complexity (e.g. having expansive, multichanneled floodplains and/or on‐channel lakes) as likely to have greater productivity of salmon than rivers flowing in constrained or canyon‐bound channels. Our objective was to develop a database of landscape metrics that could be used to rank the rivers in relation to potential salmon productivity. We then examined the rankings in relation to existing empirical (monitoring) data describing productivity of salmon stocks. To extract the metrics for each river basin we used a digital elevation model and multispectral satellite imagery. We developed procedures to extract channel networks, floodplains, on‐channel lakes and other catchment features; variables such as catchment area, channel elevation, main channel length, floodplain area, and density of hydrojunctions (nodes) were measured. We processed 1509 catchments in the North Pacific Rim including the Kamchatka Peninsula in Russia and western North America. Overall, catchments were most physically complex in western Kamchatka and western Alaska, and particularly on the Arctic North Slope of Alaska. We could not directly examine coherence between potential and measured productivity except for a few rivers, but the expected relationship generally held. The resulting database and systematic ranking are objective tools that can be used to address questions about landscape structure and biological productivity at regional to continental extents, and provide a way to begin to efficiently prioritize the allocation ... |
format |
Article in Journal/Newspaper |
author |
Luck, Matthew Maumenee, Niels Whited, Diane Lucotch, John Chilcote, Samantha Lorang, Mark Goodman, Daniel McDonald, Kyle Kimball, John Stanford, Jack |
spellingShingle |
Luck, Matthew Maumenee, Niels Whited, Diane Lucotch, John Chilcote, Samantha Lorang, Mark Goodman, Daniel McDonald, Kyle Kimball, John Stanford, Jack Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
author_facet |
Luck, Matthew Maumenee, Niels Whited, Diane Lucotch, John Chilcote, Samantha Lorang, Mark Goodman, Daniel McDonald, Kyle Kimball, John Stanford, Jack |
author_sort |
Luck, Matthew |
title |
Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
title_short |
Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
title_full |
Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
title_fullStr |
Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
title_full_unstemmed |
Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation |
title_sort |
remote sensing analysis of physical complexity of north pacific rim rivers to assist wild salmon conservation |
publisher |
Wiley |
publishDate |
2010 |
url |
http://dx.doi.org/10.1002/esp.2044 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fesp.2044 https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.2044 |
genre |
Kamchatka Kamchatka Peninsula north slope Alaska |
genre_facet |
Kamchatka Kamchatka Peninsula north slope Alaska |
op_source |
Earth Surface Processes and Landforms volume 35, issue 11, page 1330-1343 ISSN 0197-9337 1096-9837 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/esp.2044 |
container_title |
Earth Surface Processes and Landforms |
container_volume |
35 |
container_issue |
11 |
container_start_page |
1330 |
op_container_end_page |
1343 |
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1810453899931287552 |