Literature DB >> 31846788

Genotypes of the aquatic plant Myriophyllum spicatum with different growth strategies show contrasting sensitivities to copper contamination.

Eva Roubeau Dumont1, Camille Larue2, Hiram Castillo Michel3, Hervé Gryta4, Clarisse Liné5, David Baqué2, Elisabeth Maria Gross6, Arnaud Elger2.   

Abstract

Genotypic variability has been considered for years as a key attribute in species adaptation to new environments. It has been extensively studied in a context of chemical resistance, but remains poorly studied in response to chemical exposure in a context of global change. As aquatic ecosystems are particularly affected by environmental changes, we aimed to study how genotypic variability could inflect the sensitivity of aquatic plants to chemicals. Seven genotypes of Myriophyllum spicatum were exposed to three copper concentrations at 0, 0.15 and 0.5 mg/L. The sensitivity of the different genotypes was assessed through several endpoints such as relative growth rate (RGR) and morphological traits, as well as physiological markers, such as plant biomacromolecular composition. Our results showed that genotypes exhibited significant differences in their life-history traits in absence of chemical contamination. Some trait syndromes were observed, and three growth strategies were identified: (1) biomass production and main shoot elongation, (2) dry matter storage with denser whorls to promote resource conservation and (3) lateral shoot production. An up to eightfold difference in sensitivity for growth-related endpoints was observed among genotypes. Differences in sensitivity were partly attributed to morphological life-history traits. Our results confirm that genotypic variability can significantly affect M. spicatum sensitivity to Cu, and may influence the outcomes of laboratory testing based on the study of one single genotype. We recommend including genotypic variation as an assessment factor in ecological risk assessment and to study this source of variability more in depth as a possible driver of ecosystem resilience.
Copyright © 2019 Elsevier Ltd. All rights reserved.

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Year:  2019        PMID: 31846788     DOI: 10.1016/j.chemosphere.2019.125552

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  1 in total

1.  Mapping leaf metal content over industrial brownfields using airborne hyperspectral imaging and optimized vegetation indices.

Authors:  Guillaume Lassalle; Sophie Fabre; Anthony Credoz; Rémy Hédacq; Dominique Dubucq; Arnaud Elger
Journal:  Sci Rep       Date:  2021-01-07       Impact factor: 4.379

  1 in total

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