Environmental conditions and plant physiology modulate Cu phytotoxicity in field-contaminated soils

Pedro Mondaca, Patricio Valenzuela, Waldo Quiroz, Monika Valdenegro, Sebastián Abades, Juan L. Celis-Diez

Research output: Contribution to journalArticlepeer-review

Abstract

Foliar Cu concentration has been widely used as a biomarker of plant growth in phytotoxicity bioassays. This relation has helped find plant processes altered by Cu in dose-response experiments (a bivariate approach). However, when plants are grown in field conditions, their responses can vary in function of multiple variables, such as the environment, plant physiology, and other elements in plant (plant ionome). These sources of variability are commonly unreported, which could limit bioassays’ utility. Thus, the present study aimed to assess and integrate the mentioned sources of variability on Cu phytotoxicity. Lettuce was used as plant model. Lettuces were grown in growth chambers with contrasting light and air humidity conditions and on two different field-contaminated soils (sandy and loamy soils). Results showed that environmental conditions significantly affected foliar Cu and plant growth, but this effect differed in the two studied soils. Foliar Cu was not a good biomarker of plant growth. In contrast, integrating the potential phytotoxicity effect with the plant's nutritional status allowed a better understanding of plant growth. We remarked on using a structural equation modeling approach (SEM) to integrate plant physiology and plant ionome as moderators of plant growth. Results showed that plant growth was primarily related to plant nutritional status rather than Cu phytotoxicity. Also, the foliar Cu concentration would affect plant nutritional status due to photosynthesis-related plant processes and cation balance. Finally, this research invites to state and include sources of variability when assessing phytotoxicity. This way, it is possible to advance toward understanding complex linked processes occurring in field conditions.

Original languageEnglish
Article number114179
JournalEcotoxicology and Environmental Safety
Volume246
DOIs
StatePublished - Nov 2022
Externally publishedYes

Keywords

  • Contamination
  • Copper
  • Ionomics
  • Structural equation modeling

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