Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat.
The field of water resource management, including fisheries, is facing new challenges associated with climate change. This study sheds light on the modeling of water temperature indices (metrics) that describe critical thermal maxima of the Atlantic salmon (salmo salar). These thermal metrics includ...
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Online Access: | https://espace.inrs.ca/id/eprint/12628/ https://espace.inrs.ca/id/eprint/12628/1/P4131.pdf https://doi.org/10.1016/j.ecoinf.2022.101692 |
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ftinrsquebec:oai:espace.inrs.ca:12628 2024-06-23T07:51:25+00:00 Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. Abidi, Olfa St-Hilaire, André Ouarda, Taha B. M. J. Charron, Christian Boyer, Claudine Daigle, Anik 2022 application/pdf https://espace.inrs.ca/id/eprint/12628/ https://espace.inrs.ca/id/eprint/12628/1/P4131.pdf https://doi.org/10.1016/j.ecoinf.2022.101692 en eng https://espace.inrs.ca/id/eprint/12628/1/P4131.pdf Abidi, Olfa; St-Hilaire, André ORCID logoorcid:0000-0001-8443-5885 Ouarda, Taha B. M. J. ORCID logoorcid:0000-0002-0969-063X Charron, Christian; Boyer, Claudine et Daigle, Anik (2022). Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. Ecological Informatics , vol. 70 . p. 101692. DOI:10.1016/j.ecoinf.2022.101692 <https://doi.org/10.1016/j.ecoinf.2022.101692>. doi:10.1016/j.ecoinf.2022.101692 cc_by_nc_nd_4 river water temperature regional thermal analysis multiple linear regression model MLR generalized additive model GAM thermal homogeneous regions HCA Article Évalué par les pairs 2022 ftinrsquebec https://doi.org/10.1016/j.ecoinf.2022.101692 2024-06-04T14:16:26Z The field of water resource management, including fisheries, is facing new challenges associated with climate change. This study sheds light on the modeling of water temperature indices (metrics) that describe critical thermal maxima of the Atlantic salmon (salmo salar). These thermal metrics include MaxWaterTmax (interannual mean of maximum summer temperature), MaxNumDay (interannual mean of the number of consecutive days with maximum water temperature > 25 °C and minimum water temperature > 20 °C). The latter is an important indicator to evaluate thermal variability. Three other parameters of a Gaussian function fitted to the interannual daily mean temperatures characterizing the thermal regime of 146 stations located in Eastern Canada were estimated. These three parameters are Gaussian_a (maximum of interannual daily mean temperature), Gaussian_b (mean duration of the warm period), and Gaussian_c (date of occurrence of the interannual maximum temperature). The classical Multiple linear regression model (MLR) and the non-linear Generalized additive model (GAM) were tested and compared to estimate the five thermal metrics. The regression-based approaches involve the identification of thermally homogeneous regions based on three approaches: hierarchical clustering analysis (HCA), regions of influence (ROI) as well as canonical correlation analysis (CCA). Then, the regional MLR and GAM models were applied within the delineated homogenous regions. Also, the regional models were compared to models encompassing all stations (i.e., one region). For each regional estimation model and each thermal metric, a set of optimal explanatory variables were selected using a forward stepwise procedure. The database consisted of 22 environmental predictors related to physiography, topography, climate, land cover and surface deposits. To assess performance of the models, the following statistical metrics were used: coefficient of determination R², root mean square error (RMSE), bias, relative root mean square error (RRMSE) ... Article in Journal/Newspaper Atlantic salmon Salmo salar Institut national de la recherche scientifique, Québec: Espace INRS Canada Gam ENVELOPE(-57.955,-57.955,-61.923,-61.923) Ecological Informatics 70 101692 |
institution |
Open Polar |
collection |
Institut national de la recherche scientifique, Québec: Espace INRS |
op_collection_id |
ftinrsquebec |
language |
English |
topic |
river water temperature regional thermal analysis multiple linear regression model MLR generalized additive model GAM thermal homogeneous regions HCA |
spellingShingle |
river water temperature regional thermal analysis multiple linear regression model MLR generalized additive model GAM thermal homogeneous regions HCA Abidi, Olfa St-Hilaire, André Ouarda, Taha B. M. J. Charron, Christian Boyer, Claudine Daigle, Anik Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
topic_facet |
river water temperature regional thermal analysis multiple linear regression model MLR generalized additive model GAM thermal homogeneous regions HCA |
description |
The field of water resource management, including fisheries, is facing new challenges associated with climate change. This study sheds light on the modeling of water temperature indices (metrics) that describe critical thermal maxima of the Atlantic salmon (salmo salar). These thermal metrics include MaxWaterTmax (interannual mean of maximum summer temperature), MaxNumDay (interannual mean of the number of consecutive days with maximum water temperature > 25 °C and minimum water temperature > 20 °C). The latter is an important indicator to evaluate thermal variability. Three other parameters of a Gaussian function fitted to the interannual daily mean temperatures characterizing the thermal regime of 146 stations located in Eastern Canada were estimated. These three parameters are Gaussian_a (maximum of interannual daily mean temperature), Gaussian_b (mean duration of the warm period), and Gaussian_c (date of occurrence of the interannual maximum temperature). The classical Multiple linear regression model (MLR) and the non-linear Generalized additive model (GAM) were tested and compared to estimate the five thermal metrics. The regression-based approaches involve the identification of thermally homogeneous regions based on three approaches: hierarchical clustering analysis (HCA), regions of influence (ROI) as well as canonical correlation analysis (CCA). Then, the regional MLR and GAM models were applied within the delineated homogenous regions. Also, the regional models were compared to models encompassing all stations (i.e., one region). For each regional estimation model and each thermal metric, a set of optimal explanatory variables were selected using a forward stepwise procedure. The database consisted of 22 environmental predictors related to physiography, topography, climate, land cover and surface deposits. To assess performance of the models, the following statistical metrics were used: coefficient of determination R², root mean square error (RMSE), bias, relative root mean square error (RRMSE) ... |
format |
Article in Journal/Newspaper |
author |
Abidi, Olfa St-Hilaire, André Ouarda, Taha B. M. J. Charron, Christian Boyer, Claudine Daigle, Anik |
author_facet |
Abidi, Olfa St-Hilaire, André Ouarda, Taha B. M. J. Charron, Christian Boyer, Claudine Daigle, Anik |
author_sort |
Abidi, Olfa |
title |
Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
title_short |
Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
title_full |
Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
title_fullStr |
Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
title_full_unstemmed |
Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. |
title_sort |
regional thermal analysis approach: a management tool for predicting water temperature metrics relevant for thermal fish habitat. |
publishDate |
2022 |
url |
https://espace.inrs.ca/id/eprint/12628/ https://espace.inrs.ca/id/eprint/12628/1/P4131.pdf https://doi.org/10.1016/j.ecoinf.2022.101692 |
long_lat |
ENVELOPE(-57.955,-57.955,-61.923,-61.923) |
geographic |
Canada Gam |
geographic_facet |
Canada Gam |
genre |
Atlantic salmon Salmo salar |
genre_facet |
Atlantic salmon Salmo salar |
op_relation |
https://espace.inrs.ca/id/eprint/12628/1/P4131.pdf Abidi, Olfa; St-Hilaire, André ORCID logoorcid:0000-0001-8443-5885 Ouarda, Taha B. M. J. ORCID logoorcid:0000-0002-0969-063X Charron, Christian; Boyer, Claudine et Daigle, Anik (2022). Regional thermal analysis approach: A management tool for predicting water temperature metrics relevant for thermal fish habitat. Ecological Informatics , vol. 70 . p. 101692. DOI:10.1016/j.ecoinf.2022.101692 <https://doi.org/10.1016/j.ecoinf.2022.101692>. doi:10.1016/j.ecoinf.2022.101692 |
op_rights |
cc_by_nc_nd_4 |
op_doi |
https://doi.org/10.1016/j.ecoinf.2022.101692 |
container_title |
Ecological Informatics |
container_volume |
70 |
container_start_page |
101692 |
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1802642522823983104 |