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Updated: Jun 11, 2025

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Willow traits outperform taxonomy in predicting phytoremediation services.

Béatrice Gervais-Bergeron1, Pierre-Luc Chagnon2, Michel Labrecque3

  • 1Institut de recherche en biologie végétale, Département de sciences biologiques, Université de Montréal, 4101 Sherbrooke Est, Montréal, QC H1X 2B2, Canada.

The Science of the Total Environment
|October 7, 2024
PubMed
Summary

Trait-based models effectively predict phytoremediation services, outperforming species composition. Community-level plant traits, not just individual species, are key for successful phytomanagement of contaminated sites.

Keywords:
ContaminationFunctional traitsPhytomanagementSalix spp.Trace elements

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Area of Science:

  • Environmental Science
  • Plant Ecology
  • Bioremediation

Background:

  • Phytomanagement uses plants to clean contaminated sites, offering ecological benefits.
  • Trait-based models are proposed for selecting plants, assuming traits predict services.
  • The predictability of community-level traits and services needs critical evaluation.

Purpose of the Study:

  • To assess if plant traits predict phytoremediation services (phytoextraction, phytostabilization, translocation).
  • To compare the predictive power of species composition versus community-level traits.
  • To validate trait-based models for plant selection in phytomanagement.

Main Methods:

  • A mesocosm study with three willow species in monocultures and mixed combinations (1-3 species).
  • Measured ten functional traits and three phytoremediation services over 110 days.
  • Compared observed community traits with monoculture expectations and analyzed trait-service relationships.

Main Results:

  • Willow species exhibited distinct, predictable traits within assemblages.
  • Community-level traits, not species composition, significantly predicted phytoremediation services (R²adj = 0.52 vs. 0.05).
  • Specific traits correlated with phytoextraction (growth strategies), translocation (root growth), and phytostabilization (root/shoot traits).

Conclusions:

  • Trait-based models incorporating functional information are superior for predicting phytoremediation services.
  • Community-level traits are more reliable than species composition for guiding plant selection in phytomanagement.
  • Findings support the broad potential of trait-based models in phytoremediation and phytotechnologies.