Comparing freshwater mussel responses to stress using life-history and Dynamic Energy Budget theory.

Freshwater mussels are experiencing severe population declines, affecting their critical role in freshwater ecosystems. A thorough assessment of threats posed by various stressors is needed; however, the large number of species to be considered and significant data gaps, especially for listed species, hinder the process. We combined a traits-based approach to represent multiple species grouped into three life-history categories - Equilibrium, Opportunistic, and Periodic - with the Dynamic Energy Budget modeling principles to capture the physiological mechanisms driving individual-level responses.

SolBeePop: A Population Model for Pesticide Risk Assessments of Solitary Bees.

In agricultural landscapes, solitary bees occur in a large diversity of species and are important for crop and wildflower pollination. They are distinguished from honey bees and bumble bees by their solitary lifestyle as well as different nesting strategies, phenologies, and floral preferences. Their ecological traits and presence in agricultural landscapes imply potential exposure to pesticides and suggest a need to conduct ecological risk assessments for solitary bees.

Advancing ecotoxicological studies: Utilizing new approach methodologies to enable cross-species extrapolation and reduce avian testing.

Ecological risk assessments of agrochemicals have traditionally depended on in vivo guideline tests using northern bobwhite and mallard to provide relevant endpoints for avian species. However, these studies have limitations, including animal welfare concerns, the time and cost involved, limited potential for extrapolation to more realistic exposure conditions, and the lack of mechanistic understanding. The proof-of-concept work presented a case study for thiamethoxam in three avian species, demonstrating the potential of physiologically based kinetic (PBK) modeling to enable dosimetry extrapolations that inform hazard characterization in risk assessment, and reduce the use of avian testing.

Modeling temperature-dependent life-cycle toxicity of thiamethoxam in Chironomus riparius using a DEB-TKTD model.

The neonicotinoid insecticide thiamethoxam (TMX) is widely used to protect crops against insect pests. Despite some desirable properties such as its low toxicity to birds and mammals, concerns have been raised about its toxicity to non-target arthropods, including freshwater insects like chironomids. Whereas multiple studies have investigated chronic effects of neonicotinoids in chironomid larvae at standardized laboratory conditions, a better understanding of their chronic toxicity under variable temperatures and exposure is needed for coherent extrapolation from the laboratory to the field.

Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.

Practical, legal, and ethical reasons necessitate the development of methods to replace animal experiments. Computational techniques to acquire information that traditionally relied on animal testing are considered a crucial pillar among these so-called new approach methodologies. In this light, we recently introduced the Bio-QSAR concept for multispecies aquatic toxicity regression tasks.

Mechanistic population models for ecological risk assessment and decision support: The importance of good conceptual model diagrams.

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate.

Density-dependent population regulation in freshwater fishes and small mammals: A literature review and insights for Ecological Risk Assessment.

The regulation of populations through density dependence (DD) has long been a central tenet of studies of ecological systems. As an important factor in regulating populations, DD is also crucial for understanding risks to populations from stressors, including its incorporation into population models applied for this purpose. However, study of density-dependent regulation is challenging because it can occur through various mechanisms, and their identification in the field, as well as the quantification of the consequences on individuals and populations, can be difficult.

Characterization of patterns and variability in the dynamics of outdoor aquatic mesocosms: exploring the capabilities and challenges in data supporting aquatic system models.

Aquatic mesocosms are complex test systems used within regulatory risk assessment of plant protection products. These model ecosystems allow researchers to capture interactions of multiple species under realistic environmental conditions. They enable assessment of direct and indirect effects of stressors at all trophic levels (i.

Physiological variables in machine learning QSARs allow for both cross-chemical and cross-species predictions.

A major challenge in ecological risk assessment is estimating chemical-induced effects across taxa without species-specific testing. Where ecotoxicological data may be more challenging to gather, information on species physiology is more available for a broad range of taxa. Physiology is known to drive species sensitivity but understanding about the relative contribution of specific underlying processes is still elusive.

Development of a mechanistic model for analyzing avian reproduction data for pesticide risk assessment.

Mechanistic effect models are increasingly recommended as tools for refining evaluations of risk from exposure to pesticides. In the context of bird and mammal risk assessments, DEB-TKTD models have been recommended for characterizing sublethal effects at lower tiers. However, there are currently no such models.

Using life-history trait variation to inform ecological risk assessments for threatened and endangered plant species.

Developing population models for assessing risks to terrestrial plant species listed as threatened or endangered under the Endangered Species Act (ESA) is challenging given a paucity of data on their life histories. The purpose of this study was to develop a novel approach for identifying relatively data-rich nonlisted species that could serve as representatives for species listed under the ESA in the development of population models to inform risk assessments. We used the USDA PLANTS Database, which provides data on plants present in the US territories, to create a list of herbaceous plants.

Assessment of risks to listed species from the use of atrazine in the USA: a perspective.

Atrazine is a triazine herbicide used predominantly on corn, sorghum, and sugarcane in the US. Its use potentially overlaps with the ranges of listed (threatened and endangered) species. In response to registration review in the context of the Endangered Species Act, we evaluated potential direct and indirect impacts of atrazine on listed species and designated critical habitats.

Assessment of the Vulnerability to Pesticide Exposures Across Bee Species.

In many countries, the western honey bee is used as surrogate in pesticide risk assessments for bees. However, uncertainty remains in the estimation of pesticide risk to non-Apis bees because their potential routes of exposure to pesticides, life histories, and ecologies differ from those of honey bees. We applied the vulnerability concept in pesticide risk assessment to 10 bee species including the honey bee, 2 bumble bee species, and 7 solitary bee species with different nesting strategies.

Applying a Hybrid Modeling Approach to Evaluate Potential Pesticide Effects and Mitigation Effectiveness for an Endangered Fish in Simulated Oxbow Habitats.

The occurrence of some species listed under the United States' Endangered Species Act in agricultural landscapes suggests that their habitats could potentially be exposed to pesticides. However, the potential effects from such exposures on populations are difficult to estimate. Mechanistic models can provide an avenue to estimating the potential impacts on populations, considering realistic assumptions about the ecology of the species, the ecosystem it is part of, and the potential exposures within the habitat.

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.

The Comprehensive Aquatic Systems Model (CASM): Advancing Computational Capability for Ecosystem Simulation.

The comprehensive aquatic systems model (CASM), an aquatic food web-ecosystem model, was developed originally to explore relationships between food web structure and ecosystem function, and was then subsequently adapted to assess potential ecological risks posed by chemical contaminants. The present short communication presents the history of the CASM, describes the model structure, lists the outputs of the model, and introduces user-friendly versions of CASM applications that are being made publicly available. Environ Toxicol Chem 2020;39:2298-2303.

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part II: Analysis of Overwintering Outcomes.

Large-scale colony feeding studies (LSCFSs) aim to assess potential pesticide exposure to and effects on honey bees at the colony level. However, these studies are sometimes affected by high losses of control colonies, indicating that other stressors may impact colonies and confound the analysis of potential pesticide impacts. We assessed the study design and environmental conditions experienced by the untreated control colonies across 7 LSCFSs conducted in North Carolina (USA).

Simulating Honey Bee Large-Scale Colony Feeding Studies Using the BEEHAVE Model-Part I: Model Validation.

In pesticide risk assessments, semifield studies, such as large-scale colony feeding studies (LSCFSs), are conducted to assess potential risks at the honey bee colony level. However, such studies are very cost and time intensive, and high overwintering losses of untreated control hives have been observed in some studies. Honey bee colony models such as BEEHAVE may provide tools to systematically assess multiple factors influencing colony outcomes, to inform study design, and to estimate pesticide impacts under varying environmental conditions.

Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges.

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation).

Modeling Sublethal Effects of Chemicals: Application of a Simplified Dynamic Energy Budget Model to Standard Ecotoxicity Data.

To assess ecological risks from chemical exposure, we need tools to extrapolate from the sublethal effects observed in the laboratory under constant exposure to realistic time-varying exposures. Dynamic energy budget (DEB) theory offers a mechanistic modeling approach to describe the entire life history of a single organism and the effects of toxicant exposure. We use a simplified model, which can be wholly calibrated from standard chronic bioassay data.

Guidance for Developing Amphibian Population Models for Ecological Risk Assessment.

Despite widespread acceptance of the utility of population modeling and advocacy of this approach for a more ecologically relevant perspective, it is not routinely incorporated in ecological risk assessments (ERA). A systematic framework for situation-specific model development is one of the major challenges to broadly adopting population models in ERA. As risk assessors confront the multitude of species and chemicals requiring evaluation, an adaptable stepwise guide for model parameterization would facilitate this process.

Correcting for Phylogenetic Autocorrelation in Species Sensitivity Distributions.

A species sensitivity distribution (SSD) is a cumulative distribution function of toxicity endpoints for a receptor group. A key assumption when deriving an SSD is that the toxicity data points are independent and identically distributed (iid). This assumption is tenuous, however, because closely related species are more likely to have similar sensitivities than are distantly related species.

A Hybrid Individual-Based and Food Web-Ecosystem Modeling Approach for Assessing Ecological Risks to the Topeka Shiner (Notropis topeka): A Case Study with Atrazine.

A hybrid model was used to characterize potential ecological risks posed by atrazine to the endangered Topeka shiner. The model linked a Topeka shiner individual-based bioenergetics population model (TS-IBM) to a comprehensive aquatic system model (CASM ) to simulate Topeka shiner population and food web dynamics for an Iowa (USA) headwater pool. Risks were estimated for monitored concentrations in Iowa, Missouri, and Nebraska (USA), and for monitored concentrations multiplied by 2, 4, and 5.

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake.

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment endpoints with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. Here we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints.