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

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 (NOECpop) was predicted as the lowest reported individual-level NOEC (NOECind; 9.5 µg/L) using IT. For SD, the NOECpop was predicted to be lower than the NOECind 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 NOECpop of the life-cycle study. Simulations based solely on the early-life stage effects within the life-cycle study predicted unbounded NOECpop values (≥32.5 µg/L), that is, >3.4 times higher than the NOECpop based on all life-cycle effects. For the early-life stage study, the NOECpop for both IT and SD were predicted to be >2.6 times higher than the lowest reported NOECind. 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;43:1662-1676. © 2024 SETAC.

Integrating Bioavailability of Metals in Fish Population Models.

Population models are increasingly being used to extrapolate individual-level effects of chemicals, including metals, to population-level effects. For metals, it is also important to take into account their bioavailability to correctly predict metal toxicity in natural waters. However, to our knowledge, no models exist that integrate metal bioavailability into population modeling. Therefore, our main aims were to 1) incorporate the bioavailability of copper (Cu) and zinc (Zn) into an individual-based model (IBM) of rainbow trout (Oncorhynchus mykiss), and 2) predict how survival-time concentration data translate to population-level effects. For each test water, reduced versions of the general unified threshold model of survival (GUTS-RED) were calibrated using the complete survival-time concentration data. The GUTS-RED individual tolerance (IT) showed the best fit in the different test waters. Little variation between the different test waters was found for 2 GUTS-RED-IT parameters. The GUTS-RED-IT parameter "median of distribution of thresholds" (mw ) showed a strong positive relation with the Ca2+ , Mg2+ , Na+ , and H+ ion activities. Therefore, mw formed the base of the calibrated GUTS bioavailability model (GUTS-BLM), which predicted 30-d x% lethal concentration (LCx) values within a 2-fold error. The GUTS-BLM was combined with an IBM, inSTREAM-Gen, into a GUTS-BLM-IBM. Assuming that juvenile survival was the only effect of Cu and Zn exposure, population-level effect concentrations were predicted to be 1.3 to 6.2 times higher than 30-d laboratory LCx values, with the larger differences being associated with higher interindividual variation of metal sensitivity. The proposed GUTS-BLM-IBM model can provide insight into metal bioavailability and effects at the population level and could be further improved by incorporating sublethal effects of Cu and Zn. Environ Toxicol Chem 2021;40:2764-2780. © 2021 SETAC.