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Anthropogenic contaminants shape the fitness of the endangered European eel: a machine learning approach
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 7(5): 274. https://dx.doi.org/10.3390/fishes7050274
In: Fishes. MDPI: Basel. e-ISSN 2410-3888
Peer reviewed article  
Available in  Authors 
    Vlaams Instituut voor de Zee: Open access 387319 [ download pdf ]
Keywords
    Anguilla Schrank, 1798 [WoRMS]; Anguillicoloides crassus (Kuwahara, Niimi & Itagaki, 1974) Moravec & Taraschewski, 1988 [WoRMS]
Author keywords
    life history traits; global change; biogeography; Anguilla
Authors  Top 
  • Bourillon, B.
  • Feunteun, E.
  • Acou, A.
  • Trancart, T.
  • Teichert, N.
  • Belpaire, C.
  • Dufour, S.
  • Bustamante, P.
  • Aarestrup, K.
  • Walker, A.
  • Righton, D.
Abstract
    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 current situation. Discussion: Remediation of contamination could represent a viable management option for increasing the resilience of eel populations, with much more effects than solely reducing fishing mortality. More broadly, our work provides an innovative way for quantitative assessment of the reaction norms of species’ biological traits and related fecundity to contamination by organic and inorganic pollutions thus opening new management and conservation pathways to revert the erosion of biodiversity.
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