Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach
Neural networks (NN) are considered well suited to modelling ecological data, especially nonlinear relationships, and were applied here to investigate which pressures best model changes in the fish community of the Grand Bank, Northwest Atlantic. Nine fishing and environmental pressures were used to...
Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
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Online Access: | http://dx.doi.org/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2018-0411 |
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crcansciencepubl:10.1139/cjfas-2018-0411 2023-12-17T10:47:36+01:00 Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach Dempsey, Danielle P. Pepin, Pierre Koen-Alonso, Mariano Gentleman, Wendy C. 2020 http://dx.doi.org/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2018-0411 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 77, issue 6, page 963-977 ISSN 0706-652X 1205-7533 Aquatic Science Ecology, Evolution, Behavior and Systematics journal-article 2020 crcansciencepubl https://doi.org/10.1139/cjfas-2018-0411 2023-11-19T13:39:09Z Neural networks (NN) are considered well suited to modelling ecological data, especially nonlinear relationships, and were applied here to investigate which pressures best model changes in the fish community of the Grand Bank, Northwest Atlantic. Nine fishing and environmental pressures were used to simultaneously model the biomasses of six fish functional groups before and after the collapse of fish biomass in the region and over the full data series. The most influential pressures were identified, and the fit and predictive power were evaluated. The analysis was repeated with different types and lengths of time delay imposed on the pressures. Results were compared with a similar analysis using a multivariate linear regression (MLR) approach. MLR generally resulted in better fit, although the ecological implications of the approaches were typically similar. Findings show that both top-down and bottom-up pressures influenced the fish community over the past several decades, over short and long time scales. NN may have useful forecast potential, although future work is required to improve the forecasts shown here before they can directly inform management. Article in Journal/Newspaper Northwest Atlantic Canadian Science Publishing (via Crossref) Canadian Journal of Fisheries and Aquatic Sciences 77 6 963 977 |
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Open Polar |
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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 Dempsey, Danielle P. Pepin, Pierre Koen-Alonso, Mariano Gentleman, Wendy C. Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
topic_facet |
Aquatic Science Ecology, Evolution, Behavior and Systematics |
description |
Neural networks (NN) are considered well suited to modelling ecological data, especially nonlinear relationships, and were applied here to investigate which pressures best model changes in the fish community of the Grand Bank, Northwest Atlantic. Nine fishing and environmental pressures were used to simultaneously model the biomasses of six fish functional groups before and after the collapse of fish biomass in the region and over the full data series. The most influential pressures were identified, and the fit and predictive power were evaluated. The analysis was repeated with different types and lengths of time delay imposed on the pressures. Results were compared with a similar analysis using a multivariate linear regression (MLR) approach. MLR generally resulted in better fit, although the ecological implications of the approaches were typically similar. Findings show that both top-down and bottom-up pressures influenced the fish community over the past several decades, over short and long time scales. NN may have useful forecast potential, although future work is required to improve the forecasts shown here before they can directly inform management. |
format |
Article in Journal/Newspaper |
author |
Dempsey, Danielle P. Pepin, Pierre Koen-Alonso, Mariano Gentleman, Wendy C. |
author_facet |
Dempsey, Danielle P. Pepin, Pierre Koen-Alonso, Mariano Gentleman, Wendy C. |
author_sort |
Dempsey, Danielle P. |
title |
Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
title_short |
Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
title_full |
Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
title_fullStr |
Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
title_full_unstemmed |
Application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
title_sort |
application of neural networks to model changes in fish community biomass in relation to pressure indicators and comparison with a linear approach |
publisher |
Canadian Science Publishing |
publishDate |
2020 |
url |
http://dx.doi.org/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2018-0411 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2018-0411 |
genre |
Northwest Atlantic |
genre_facet |
Northwest Atlantic |
op_source |
Canadian Journal of Fisheries and Aquatic Sciences volume 77, issue 6, page 963-977 ISSN 0706-652X 1205-7533 |
op_rights |
http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining |
op_doi |
https://doi.org/10.1139/cjfas-2018-0411 |
container_title |
Canadian Journal of Fisheries and Aquatic Sciences |
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77 |
container_issue |
6 |
container_start_page |
963 |
op_container_end_page |
977 |
_version_ |
1785571510991192064 |