Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach
European eel is thought to be a symbol of the effects of global change on aquatic biodiversity. The species has persisted for millions of years and faced drastic environmental fluctuations thanks to its phenotypic plasticity. However, the species has recently declined to historically low levels unde...
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2022
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Online Access: | https://orbit.dtu.dk/en/publications/804a3220-5595-4267-974e-a5a2b78a3384 https://doi.org/10.3390/fishes7050274 https://backend.orbit.dtu.dk/ws/files/294107614/fishes_07_00274_v2.pdf |
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ftdtupubl:oai:pure.atira.dk:publications/804a3220-5595-4267-974e-a5a2b78a3384 2024-09-15T18:05:14+00:00 Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach Bourillon, Bastien Feunteun, Eric Acou, Anthony Trancart, Thomas Teichert, Nils Belpaire, Claude Dufour, Sylvie Bustamante, Paco Aarestrup, Kim Walker, Alan Righton, David 2022 application/pdf https://orbit.dtu.dk/en/publications/804a3220-5595-4267-974e-a5a2b78a3384 https://doi.org/10.3390/fishes7050274 https://backend.orbit.dtu.dk/ws/files/294107614/fishes_07_00274_v2.pdf eng eng https://orbit.dtu.dk/en/publications/804a3220-5595-4267-974e-a5a2b78a3384 info:eu-repo/semantics/openAccess Bourillon , B , Feunteun , E , Acou , A , Trancart , T , Teichert , N , Belpaire , C , Dufour , S , Bustamante , P , Aarestrup , K , Walker , A & Righton , D 2022 , ' Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach ' , Fishes , vol. 7 , no. 5 , 274 . https://doi.org/10.3390/fishes7050274 Anguilla Biogeography Global change Life history traits /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being name=SDG 3 - Good Health and Well-being article 2022 ftdtupubl https://doi.org/10.3390/fishes7050274 2024-08-13T00:03:06Z European eel is thought to be a symbol of the effects of global change on aquatic biodiversity. The species has persisted for millions of years and faced drastic environmental fluctuations thanks to its phenotypic plasticity. However, the species has recently declined to historically low levels under synergistic human pressures. Sublethal chemical contamination has been shown to alter reproductive capacity, but the impacts and required actions are not fully addressed by conservation plans. This paper proposes a modelling approach to quantify the effects of sublethal contamination by anthropogenic pollutants on the expression of life history traits and related fitness of the critically endangered European eel. Material and Methods: We sampled female silver eels from eight different catchments across Europe previously shown to be representative of the spectrum of environmental variability and contamination. We measured 11 fitness-related life history traits within four main categories: fecundity, adaptability and plasticity, migratory readiness, and spawning potential. We used machine learning in models to explore the phenotypic reaction (expression of these life history traits) according to geographical parameters, parasite burdens (the introduced nematode Anguillicoloides crassus ) and anthropogenic contaminants (persistent organic pollutants (POPs) in muscular tissue and trace elements (TEs) in gonads, livers and muscles). Finally, we simulated, the effects of two management scenarios—contamination reduction and contamination increase—on the fecundity and recruitment. Results: Contamination in our sampling was shown to have a stronger control on life history traits than do geographic and environmental factors that are currently described in the literature. We modelled different contamination scenarios to assess the benefit of mitigation: these scenarios suggest that reducing pollutants concentrations to the lowest values that occurred in our sampling design would double the fecundity of eels compared to the ... Article in Journal/Newspaper European eel Technical University of Denmark: DTU Orbit Fishes 7 5 274 |
institution |
Open Polar |
collection |
Technical University of Denmark: DTU Orbit |
op_collection_id |
ftdtupubl |
language |
English |
topic |
Anguilla Biogeography Global change Life history traits /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being name=SDG 3 - Good Health and Well-being |
spellingShingle |
Anguilla Biogeography Global change Life history traits /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being name=SDG 3 - Good Health and Well-being Bourillon, Bastien Feunteun, Eric Acou, Anthony Trancart, Thomas Teichert, Nils Belpaire, Claude Dufour, Sylvie Bustamante, Paco Aarestrup, Kim Walker, Alan Righton, David Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
topic_facet |
Anguilla Biogeography Global change Life history traits /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being name=SDG 3 - Good Health and Well-being |
description |
European eel is thought to be a symbol of the effects of global change on aquatic biodiversity. The species has persisted for millions of years and faced drastic environmental fluctuations thanks to its phenotypic plasticity. However, the species has recently declined to historically low levels under synergistic human pressures. Sublethal chemical contamination has been shown to alter reproductive capacity, but the impacts and required actions are not fully addressed by conservation plans. This paper proposes a modelling approach to quantify the effects of sublethal contamination by anthropogenic pollutants on the expression of life history traits and related fitness of the critically endangered European eel. Material and Methods: We sampled female silver eels from eight different catchments across Europe previously shown to be representative of the spectrum of environmental variability and contamination. We measured 11 fitness-related life history traits within four main categories: fecundity, adaptability and plasticity, migratory readiness, and spawning potential. We used machine learning in models to explore the phenotypic reaction (expression of these life history traits) according to geographical parameters, parasite burdens (the introduced nematode Anguillicoloides crassus ) and anthropogenic contaminants (persistent organic pollutants (POPs) in muscular tissue and trace elements (TEs) in gonads, livers and muscles). Finally, we simulated, the effects of two management scenarios—contamination reduction and contamination increase—on the fecundity and recruitment. Results: Contamination in our sampling was shown to have a stronger control on life history traits than do geographic and environmental factors that are currently described in the literature. We modelled different contamination scenarios to assess the benefit of mitigation: these scenarios suggest that reducing pollutants concentrations to the lowest values that occurred in our sampling design would double the fecundity of eels compared to the ... |
format |
Article in Journal/Newspaper |
author |
Bourillon, Bastien Feunteun, Eric Acou, Anthony Trancart, Thomas Teichert, Nils Belpaire, Claude Dufour, Sylvie Bustamante, Paco Aarestrup, Kim Walker, Alan Righton, David |
author_facet |
Bourillon, Bastien Feunteun, Eric Acou, Anthony Trancart, Thomas Teichert, Nils Belpaire, Claude Dufour, Sylvie Bustamante, Paco Aarestrup, Kim Walker, Alan Righton, David |
author_sort |
Bourillon, Bastien |
title |
Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
title_short |
Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
title_full |
Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
title_fullStr |
Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
title_full_unstemmed |
Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach |
title_sort |
anthropogenic contaminants shape the fitness of the endangered european eel: a machine learning approach |
publishDate |
2022 |
url |
https://orbit.dtu.dk/en/publications/804a3220-5595-4267-974e-a5a2b78a3384 https://doi.org/10.3390/fishes7050274 https://backend.orbit.dtu.dk/ws/files/294107614/fishes_07_00274_v2.pdf |
genre |
European eel |
genre_facet |
European eel |
op_source |
Bourillon , B , Feunteun , E , Acou , A , Trancart , T , Teichert , N , Belpaire , C , Dufour , S , Bustamante , P , Aarestrup , K , Walker , A & Righton , D 2022 , ' Anthropogenic Contaminants Shape the Fitness of the Endangered European Eel: A Machine Learning Approach ' , Fishes , vol. 7 , no. 5 , 274 . https://doi.org/10.3390/fishes7050274 |
op_relation |
https://orbit.dtu.dk/en/publications/804a3220-5595-4267-974e-a5a2b78a3384 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/fishes7050274 |
container_title |
Fishes |
container_volume |
7 |
container_issue |
5 |
container_start_page |
274 |
_version_ |
1810442819978919936 |