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Modeling Full Life-Cycle Effects of Copper on Brook Trout (Salvelinus fontinalis) Populations.

Sharon D JanssenKarel P J ViaenePatrick Van SprangKarel A C De Schamphelaere
Published in: Environmental toxicology and chemistry (2024)
Population models are increasingly used to predict population-level effects of chemicals. For trout, most toxicity data are available on early-life stages, but this may cause population models to miss true population-level effects. We predicted population-level effects of copper (Cu) on a brook trout (Salvelinus fontinalis) population based on individual-level effects observed in either a life-cycle study or an early-life stage study. We assessed the effect of Cu on predicted trout densities (both total and different age classes) and the importance of accounting for effects on the full life cycle compared with only early-life stage effects. Additionally, uncertainty about the death mechanism and growth effects was evaluated by comparing the effect of different implementation methods: individual tolerance (IT) versus stochastic death (SD) and continuous versus temporary growth effects. For the life-cycle study, the same population-level no-observed-effect concentration (NOEC pop ) was predicted as the lowest reported individual-level NOEC (NOEC ind ; 9.5 µg/L) using IT. For SD, the NOEC pop was predicted to be lower than the NOEC ind for young-of-the-year and 1-year-old trout (3.4 µg/L), but similar for older trout (9.5 µg/L). The implementation method for growth effects did not affect the NOEC pop of the life-cycle study . Simulations based solely on the early-life stage effects within the life-cycle study predicted unbounded NOEC pop values (≥32.5 µg/L), that is, >3.4 times higher than the NOEC pop based on all life-cycle effects. For the early-life stage study, the NOEC pop for both IT and SD were predicted to be >2.6 times higher than the lowest reported NOEC ind . Overall, we demonstrate that effects on trout populations can be underestimated if predictions are solely based on toxicity data with early-life stages. Environ Toxicol Chem 2024;00:1-15. © 2024 SETAC.
Keyphrases
  • early life
  • life cycle
  • primary care
  • molecular dynamics
  • electronic health record
  • middle aged
  • artificial intelligence
  • community dwelling