The trouble with surrogates in environmental risk assessment: a daphniid case study

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

A tale of two metrics: the EPA Risk Quotient Approach versus the delay in Population Growth Index for determination of pesticide risk to aquatic species

The potential risk that two closely related insecticides, spinetoram and spinosad, posed to three Cladoceran species, Ceriodaphnia dubia, Daphnia pulex, and D. magna was determined using two approaches, the USEPA Risk Quotient method and the Delay in Population Growth Index (DPGI). Results of the RQ method showed that spinetoram posed a risk to all three species, but spinosad posed a risk only to C. dubia. The DPGI analysis showed that exposure to spinetoram resulted in populations of all three species being delayed ≥ 3 generation times. Exposure to the LC₅₀ and the lower 95% CL resulted in delayed populations while exposure to the upper 95% CL concentration of spinetoram resulted in no recovery of any of the three species over the course of the modeling exercise (88 d). Exposure to the lower and upper 95% Cl and the LC₅₀ of spinosad resulted in C. dubia populations being delayed ≥ 3 generations. D. pulex populations were not negatively affected after exposure to spinosad. D. magna populations were delayed ≥ 3 generations, but only after exposure to the upper 95% Cl of spinosad. These results illustrate that although the EPA risk quotient method indicated that spinetoram posed a risk to all three species and that spinosad only posed a risk to C. dubia, the DPGI showed that D. magna would be negatively affected by spinosad and none of the three species would reach a predetermined number of individuals after exposure to the upper 95% CL of spinetoram. Because the DPGI uses the 95% Cl as well as the LC₅₀ in its calculation and produces a measure of population growth it provides more detailed information in terms of the potential risk of pesticides to populations than the RQ method.

Pop-guide: Population modeling guidance, use, interpretation, and development for ecological risk assessment

The assimilation of population models into ecological risk assessment (ERA) has been hindered by their range of complexity, uncertainty, resource investment, and data availability. Likewise, ensuring that the models address risk assessment objectives has been challenging. Recent research efforts have begun to tackle these challenges by creating an integrated modeling framework and decision guide to aid the development of population models with respect to ERA objectives and data availability. In the framework, the trade-offs associated with the generality, realism, and precision of an assessment are used to guide the development of a population model commensurate with the protection goal. The decision guide provides risk assessors with a stepwise process to assist them in developing a conceptual model that is appropriate for the assessment objective and available data. We have merged the decision guide and modeling framework into a comprehensive approach, Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE), for the development of population models for ERA that is applicable across regulatory statutes and assessment objectives. In Phase 1 of Pop-GUIDE, assessors are guided through the trade-offs of ERA generality, realism, and precision, which are translated into model objectives. In Phase 2, available data are assimilated and characterized as general, realistic, and/or precise. Phase 3 provides a series of dichotomous questions to guide development of a conceptual model that matches the complexity and uncertainty appropriate for the assessment that is in concordance with the available data. This phase guides model developers and users to ensure consistency and transparency of the modeling process. We introduce Pop-GUIDE as the most comprehensive guidance for population model development provided to date and demonstrate its use through case studies using fish as an example taxon and the US Federal Insecticide Fungicide and Rodenticide Act and Endangered Species Act as example regulatory statutes. Integr Environ Assess Manag 2021;17:767-784. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Environmental risk assessment in agro-ecosystems: Revisiting the concept of receiving environment after the EFSA guidance document

The environmental risk assessment (ERA) for genetically modified plants (GMPs) is a prerequisite for commercial approval of these new varieties according to regulatory systems worldwide. The first country to regulate GM crops was the USA and the issue of possible environmental impacts was based on the principles used in risk assessment of pesticides. Two main pillars of this approach are the use of surrogate species for testing effects on non-target organisms using a tiered assessment with clear thresholds to indicate the need to move between tiers. The latest EFSA guidance document on ERA of Genetically Modified Organisms considers specifically the receiving environment in preparation of ERA for commercial cultivation of GMPs. According to existing guidelines in the EU, the receiving environment is defined by three mutually interacting components: the characteristics of the environmental stressor (i.e. the GM plant), the bio-geographical regions where the commercial release of the crop is expected and the agricultural systems therein. Difference in agronomic and ecological conditions (e.g. use of different varieties, vegetation of adjacent areas, non-target species assemblages, sensitivity of local species to the stressors) suggests that explicit considerations of the receiving environments are necessary. Results from field experiments indicate that differences in cultivation practices, e.g. the herbicide regime used on herbicide-tolerant GM crops, may induce direct and indirect effects on wild plant distribution and abundance, with consequent repercussions on food webs based on these plants. Moreover, ecological literature indicates that the concept of surrogate species has clear limitations if applied broadly to any ERA. Starting from case studies regarding GMPs, this paper discusses some ecological and agronomic characteristics of agro-ecosystems, which have implications in the elaboration of both hazard and exposure analyses during ERA. The species selection approach indicated in the EFSA Guidance Document and the consideration of the area(s) of the expected release of the new variety may provide the basis to an ecologically sound ERA for a range of environmental stressors. The quality of the data that become available for risk managers with this approach may support a more transparent and dependable ERA and risk management for GMPs as well as for other potential environmental stressors in agro-ecosystems.

The evolution of toxicant resistance in daphniids and its role on surrogate species

Prolonged exposure to a disturbance such as a toxicant has the potential to result in rapid evolution to toxicant resistance in many short-lived species such as daphniids. This evolution may allow a population to persist at higher levels of the toxicant than is possible without evolution. Here we apply evolutionary game theory to a Leslie matrix model for a daphniid population to obtain a Darwinian model that couples population dynamics with the dynamics of an evolving trait. We use the Darwinian model to consider how the evolution of resistance to the lethal or sublethal effects of a disturbance may change the population dynamics. In particular, we determine the conditions under which a daphniid population can persist by evolving toxicant resistance. We then consider the implications of this evolution in terms of the use of daphniids as surrogate species. We show for three species of daphniids that evolution of toxicant resistance means that one species may persist while another does not. These results suggest that toxicant studies that do not consider the potential of a species (or its surrogate) to develop toxicant resistance may not accurately predict the long term persistence of the species.