Effects of light and temperature fluctuations on the growth of Myriophyllum spicatum in toxicity tests--a model-based analysis

Seasonal dynamics of the macrophyte test species Myriophyllum spicatum over two years in experimental ditches for population modeling application in risk assessment

Myriophyllum spicatum is a sediment-rooted, aquatic macrophyte growing submerged, with a wide geographical distribution and high ecological relevance in freshwater ecosystems. It is used in testing and risk assessment for pesticides in water and sediment. Population models enable effects measured under laboratory conditions to be extrapolated to effects expected in the field with time-variable environmental factors including exposure. These models are a promising tool in higher-tier risk assessments. However, there is a lack of data on the seasonal dynamics of M. spicatum, which is needed to test model predictions of typical population dynamics in the field. To generate such data, a two-year study was set up in outdoor experimental systems from May 2017 to May 2019. The growth of M. spicatum was monitored in 0.2025 m² plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh weight [FW] and dry weight [DW]), shoot length, seasonal short-term growth rates of shoots, relevant environmental parameters, and weather data. The results showed a clear seasonal pattern of biomass and shoot length and their variability. M. spicatum reached a maximum total shoot length (TSL) of 279 m m^-2 and a maximum standing crop above-ground DW of 262 g m^-2 . Periodical growth rates reached up to 0.072, 0.095, and 0.085 day^-1 for total length, FW, and DW, respectively. Multivariate regression revealed that pH (as a surrogate for the availability of carbon species) and water temperature could explain a significant proportion of the variability in M. spicatum growth rates (p < 0.05). This study has provided an ecologically relevant data set on seasonal population dynamics representative of shallow freshwater ecosystems, which can be used to test and refine population models for use in chemical risk assessment and ecosystem management. Integr Environ Assess Manag 2022;18:1375-1386. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms

Following a request from EFSA, the Panel on Plant Protection Products and their Residues (PPR) developed an opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) models and their use in prospective environmental risk assessment (ERA) for pesticides and aquatic organisms. TKTD models are species‐ and compound‐specific and can be used to predict (sub)lethal effects of pesticides under untested (time‐variable) exposure conditions. Three different types of TKTD models are described, viz., (i) the ‘General Unified Threshold models of Survival’ (GUTS), (ii) those based on the Dynamic Energy Budget theory (DEBtox models), and (iii) models for primary producers. All these TKTD models follow the principle that the processes influencing internal exposure of an organism, (TK), are separated from the processes that lead to damage and effects/mortality (TD). GUTS models can be used to predict survival rate under untested exposure conditions. DEBtox models explore the effects on growth and reproduction of toxicants over time, even over the entire life cycle. TKTD model for primary producers and pesticides have been developed for algae, Lemna and Myriophyllum. For all TKTD model calibration, both toxicity data on standard test species and/or additional species can be used. For validation, substance and species‐specific data sets from independent refined‐exposure experiments are required. Based on the current state of the art (e.g. lack of documented and evaluated examples), the DEBtox modelling approach is currently limited to research applications. However, its great potential for future use in prospective ERA for pesticides is recognised. The GUTS model and the Lemna model are considered ready to be used in risk assessment.

A toxicokinetic and toxicodynamic modeling approach using Myriophyllum spicatum to predict effects caused by short-term exposure to a sulfonylurea

Toxicokinetic and toxicodynamic models are a promising tool to address the effects of time-variable chemical exposure. Standard toxicity tests usually rely on static concentrations, but these chemical exposure patterns are unlikely to appear in the field, where time-variable exposure of chemicals is typical. In the present study, toxicodynamic processes were integrated into an existing model that includes the toxicokinetics and growth of the aquatic plant Myriophyllum spicatum, to predict the impact on plant growth of 2 iofensulfuron short-term exposure patterns. To establish a method that can be used with standard data from risk assessments, the toxicodynamics of iofensulfuron were based on effect data from a 14-d standard toxicity test using static concentrations. Modeling showed that the toxicokinetic and toxicodynamic growth model of M. spicatum can be successfully used to predict effects of short-term iofensulfuron exposure by using effect data from a standard toxicity test. A general approach is presented, in which time-variable chemical exposures can be evaluated more realistically without conducting additional toxicity studies.

How TK-TD and population models for aquatic macrophytes could support the risk assessment for plant protection products

This case study of the Society of Environmental Toxicology and Chemistry (SETAC) workshop MODELINK demonstrates the potential use of mechanistic effects models for macrophytes to extrapolate from effects of a plant protection product observed in laboratory tests to effects resulting from dynamic exposure on macrophyte populations in edge-of-field water bodies. A standard European Union (EU) risk assessment for an example herbicide based on macrophyte laboratory tests indicated risks for several exposure scenarios. Three of these scenarios are further analyzed using effect models for 2 aquatic macrophytes, the free-floating standard test species Lemna sp., and the sediment-rooted submerged additional standard test species Myriophyllum spicatum. Both models include a toxicokinetic (TK) part, describing uptake and elimination of the toxicant, a toxicodynamic (TD) part, describing the internal concentration-response function for growth inhibition, and a description of biomass growth as a function of environmental factors to allow simulating seasonal dynamics. The TK-TD models are calibrated and tested using laboratory tests, whereas the growth models were assumed to be fit for purpose based on comparisons of predictions with typical growth patterns observed in the field. For the risk assessment, biomass dynamics are predicted for the control situation and for several exposure levels. Based on specific protection goals for macrophytes, preliminary example decision criteria are suggested for evaluating the model outputs. The models refined the risk indicated by lower tier testing for 2 exposure scenarios, while confirming the risk associated for the third. Uncertainties related to the experimental and the modeling approaches and their application in the risk assessment are discussed. Based on this case study and the assumption that the models prove suitable for risk assessment once fully evaluated, we recommend that 1) ecological scenarios be developed that are also linked to the exposure scenarios, and 2) quantitative protection goals be set to facilitate the interpretation of model results for risk assessment.