Coupling toxicokinetic-toxicodynamic and population models for assessing aquatic ecological risks to time-varying pesticide exposures

Projection of Interspecific Competition (PIC) Matrices: A Conceptual Framework for Inclusion in Population Risk Assessments

Accounting for intraspecific and interspecific competition when assessing the effects of chemical and nonchemical stressors is an important uncertainty in ecological risk assessments. We developed novel projection of interspecific competition (PIC) matrices that allow for analysis of population dynamics of two or more species exposed to a given stressor(s) that compete for shared resources within a landscape. We demonstrate the application of PIC matrices to investigate the population dynamics of two hypothetical fish species that compete with one another and have differences in net reproductive rate and intrinsic rate of population increase. Population status predictions were made under scenarios that included exposure to a chemical stressor that reduced fecundity for one or both species. The results of our simulations demonstrated that measures obtained from the life table and Leslie matrix of an organism, including net reproductive rate and intrinsic rate of increase, can result in erroneous conclusions of population status and viability in the absence of a consideration of resource limitation and interspecific competition. This modeling approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects due to stressors to possible outcomes within an ecosystem. In addition, PIC matrices could be combined with adverse outcome pathways to allow for ecosystem projection based on taxonomic conservation of molecular targets of chemicals to predict the likelihood of relative cross-species susceptibility. Overall, the present study shows how PIC matrices can integrate effects across the life cycles of multiple species, provide a linkage between endpoints observed in individual and population-level responses, and project outcomes at the community level for multiple generations for multiple species that compete for limited resources. Environ Toxicol Chem 2024;43:1406-1422. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

Comparison of two modeling frameworks for unifying the toxicant-affected percentage of aquatic species, individuals, and time into a single metric

To address time-variable exposure to toxicants, this work compares simple and complex approaches to unifying the affected percentage of aquatic species, individuals, and time into a single metric. The simple approach uses only information on the probability distribution of exposure concentrations, a species sensitivity distribution (SSD) of chronic values, and the distribution of tolerance within species. The complex approach involves time-series simulation with a kinetics-based toxicity model coupled with a population model for each species in the SSD. Unlike the simple approach, this takes into account the exposure duration needed to elicit toxicity, differing sensitivities of life stages within a species, differing effects on survival versus reproduction, and species differences in their model population's response to press disturbance and recovery time from pulse disturbance. The probability distribution approach indicated that, for SSD assemblages challenged with moderately variable toxicant concentrations exceeding the aquatic life criterion a few percent of the time, most of the predicted aggregate effect is usually experienced by the most sensitive 10% of species and individuals. The kinetics-population simulation approach indicated that, for time-variable exposure (but not for constant exposure), the severity of the population effect depended on the type of effect and life stage affected. The results from both approaches suggest that moderately time-variable exposure is best viewed as a fluctuating press disturbance, not as a sporadic pulse disturbance. Integr Environ Assess Manag 2022;18:1364-1374. © 2021 SETAC.

Investigating Vernal Pool Fairy Shrimp Exposure to Organophosphate Pesticides: Implications for Population-Level Risk Assessment

Vernal pool fairy shrimp, Branchinecta lynchi, is a freshwater crustacean endemic to California and Oregon, including California's Central Valley. B. lynchi is listed as a Federally Threatened species under the US Endangered Species Act, and as a vulnerable species on the IUCN Red List. Threats that may negatively impact vernal pool fairy shrimp populations include pesticide applications to agricultural land use (e.g., agrochemicals such as organophosphate pesticides) and climate changes that impact vernal pool hydrology. Pop-GUIDE (Population model Guidance, Use, Interpretation, and Development for Ecological risk assessment) is a comprehensive tool that facilitates development and implementation of population models for ecological risk assessment and can be used to document the model derivation process. We employed Pop-GUIDE to document and facilitate the development of a population model for investigating impacts of organophosphate pesticides on vernal pool fairy shrimp populations in California's Central Valley. The resulting model could be applied in combination with field assessment and laboratory-based chemical analysis to link effects from pesticide exposure to adverse outcomes in populations across their range. B. lynchi has a unique intra-annual life cycle that is largely dependent upon environmental conditions. Future deployment of this population model should include complex scenarios consisting of multiple stressors, whereby the model is used to examine scenarios that combine chemical stress resulting from exposure to pesticides and climate changes.

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 Multidimensional Matrix Model for Predicting the Effects of Male-Biased Sex Ratios on Fish Populations

Laboratory experiments have established that exposure to certain endocrine-active substances prior to and/or during the period of sexual differentiation can lead to skewed sex ratios in fish. However, the potential long-term population impact of biased sex ratio depends on multiple factors including the life history of the species and whether the ratio is male or female-biased. In the present study, we describe a novel multidimensional, density-dependent matrix model that analyzes age class-structure of both males and females over time, allowing for the quantitative evaluation of the effects of biased sex ratio on population status. This approach can be used in conjunction with field monitoring efforts and/or laboratory testing to link effects on sex ratio due to chemical and/or nonchemical stressors to adverse outcomes in whole organisms and populations. For demonstration purposes, we applied the model to evaluate population trajectories for fathead minnow (Pimephales promelas) exposed to prochloraz, an aromatase inhibitor, during sexual differentiation. The model also was used to explore the population impact in a more realistic exposure scenario in which both adult and early life stages of fish are exposed concurrently to prochloraz, which, in addition to altering sex ratio during development, can decrease vitellogenin and egg production in adult females. For each exposure scenario, the model was used to analyze total population size, numbers of females and of males, and sex specific recruitment of the F1 generation. The present study illustrates the utility of multidimensional matrix population models for ecological risk assessment in terms of integrating effects across a population of an organism even when chemical effects on individuals are manifested via different pathways depending on life stage. Environ Toxicol Chem 2022;41:1066-1077. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.

DEVELOPING INTEGRAL PROJECTION MODELS FOR ECOTOXICOLOGY

In many ecosystems, especially aquatic ecosystems, size plays a critical role in the factors that determine an individual's ability to survive and reproduce. In aquatic ecotoxicology, size informs both realized and potential acute and chronic effects of chemical exposure. This paper demonstrates how chemical and nonchemical effects on growth, survival, and reproduction can be linked to population-level dynamics using size-structured integral projection models (IPM). The modeling approach was developed with the goals and constraints of ecological risk assessors in mind, who are tasked with estimating the effects of chemical exposures to wildlife populations in a data-limited environment. The included case study is a collection of daily time-step IPMs parameterized for the life history and annual cycle of fathead minnows (Pimephales promelas), which motivated the development of modeling techniques for seasonal, iteroparous reproduction, density dependent growth effects, and size-dependent over-winter survival. The effects of a time-variable annual chemical exposure were interpreted using a toxicokinetic-toxicodynamic model for acute survival and sub-lethal growth effects model for chronic effects and incorporated into the IPMs. This paper presents a first application of integral projection models to ecotoxicology. Our research demonstrates that size-structured IPMs provide a promising, flexible, framework for synthesizing ecotoxicologically relevant data and theory to explore the effects of chemical and nonchemical stressors and the resulting impacts on exposed populations.

A Simplified Population-Level Landscape Model Identifying Ecological Risk Drivers of Pesticide Applications, Part One: Case Study for Large Herbivorous Mammals

Environmental risk assessment is a key process for the authorization of pesticides, and is subjected to continuous challenges and updates. Current approaches are based on standard scenarios and independent substance-crop assessments. This arrangement does not address the complexity of agricultural ecosystems with mammals feeding on different crops. This work presents a simplified model for regulatory use addressing landscape variability, co-exposure to several pesticides, and predicting the effect on population abundance. The focus is on terrestrial vertebrates and the aim is the identification of the key risk drivers impacting on mid-term population dynamics. The model is parameterized for EU assessments according to the European Food Safety Authority (EFSA) Guidance Document, but can be adapted to other regulatory schemes. The conceptual approach includes two modules: (a) the species population dynamics, and (b) the population impact of pesticide exposure. Population dynamics is modelled through daily survival and seasonal reproductions rates; which are modified in case of pesticide exposure. All variables, parameters, and functions can be modified. The model has been calibrated with ecological data for wild rabbits and brown hares and tested for two herbicides, glyphosate and bromoxynil, using validated toxicity data extracted from EFSA assessments. Results demonstrate that the information available for a regulatory assessment, according to current EU information requirements, is sufficient for predicting the impact and possible consequences at population dynamic levels. The model confirms that agroecological parameters play a key role when assessing the effect of pesticide exposure on population abundance. The integration of laboratory toxicity studies with this simplified landscape model allows for the identification of conditions leading to population vulnerability or resilience. An Annex includes a detailed assessment of the model characteristics according to the EFSA scheme on Good Modelling Practice.

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.