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. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;00:1-9. © 2023 SETAC.

Moving beyond Risk Quotients: Advancing Ecological Risk Assessment to Reflect Better, More Robust and Relevant Methods.

Under standard guidance for conducting Ecological Risk Assessments (ERAs), the risks of chemical exposure to diverse organisms are most often based on deterministic point estimates evaluated against safety-factor-based levels of concern (LOCs). While the science and guidance for mechanistic effect models (e.g., demographic, population, and agent-based) have long been demonstrated to provide more ecologically relevant effect endpoints upon which risk can be evaluated, their application in ERAs has been limited, particularly in the US. This special issue highlights the state of the science in effect modeling for ERAs through demonstrated application of the recently published Population modeling Guidance, Use, Interpretation, and Development for ERA (Pop-GUIDE). We introduce this issue with a perspective on why it is critical to move past the current application of deterministic endpoints and LOCs. We demonstrate how the current, widely used approaches contain extensive uncertainty that could be reduced considerably by applying models that account for species life histories and other important endogenous and exogenous factors critical to species sustainability. We emphasize that it is long past time to incorporate better, more robust, and ecologically relevant effect models into ERAs, particularly for chronic risk determination. The papers in this special issue demonstrate how mechanistic models that follow Pop-GUIDE better inform ERAs compared to the current standard practice.

Temperature dependence of population responses to competition and metabolic stress: An agent-based model to inform ecological risk assessment in a changing climate.

Understanding the interactions among multiple stressors is a crucial issue for ecological risk assessment and ecosystem management. However, it is often impractical, or impossible, to collect empirical data concerning all the interactions at any scale because the type of interaction differs across species and levels of biological organization. We applied an agent-based model to simulate the effects of a hypothetical chemical stressor and inter-specific competition (both alone and together) on greenback cutthroat trout (GCT), a listed species under the US Endangered Species Act, in two temperature scenarios. The trout life cycle is modeled using the Dynamic Energy Budget theory. The chemical stressor is represented by a reduction in ingestion efficiency, and competition is implemented by introducing a population of brown trout. Results show that chemical exposure is the major stressor in the colder temperature scenario, whereas competition mostly affected the GCT population in the warmer environment. Moreover, the effects of the stressors at the individual level were not predictive of the type of interactions between stressors (additive, antagonistic, synergistic) at the population level, which differed between the two-temperature scenarios. We conclude that mechanistic models can help to identify generalities about interactions among environmental and stressor properties, create in-silico experiments to provide different scenarios for conservation purposes, and explore multiple-exposure consequences at higher levels of biological organization. In this way they can provide useful tools for improving ecological risk assessment and informing management decisions.

Mechanistic Effect Modeling of Earthworms in the Context of Pesticide Risk Assessment: Synthesis of the FORESEE Workshop.

Earthworms are important ecosystem engineers, and assessment of the risk of plant protection products toward them is part of the European environmental risk assessment (ERA). In the current ERA scheme, exposure and effects are represented simplistically and are not well integrated, resulting in uncertainty when the results are applied to ecosystems. Modeling offers a powerful tool to integrate the effects observed in lower tier laboratory studies with the environmental conditions under which exposure is expected in the field. This paper provides a summary of the (In)Field Organism Risk modEling by coupling Soil Exposure and Effect (FORESEE) Workshop held 28-30 January 2020 in Düsseldorf, Germany. This workshop focused on toxicokinetic-toxicodynamic (TKTD) and population modeling of earthworms in the context of ERA. The goal was to bring together scientists from different stakeholder groups to discuss the current state of soil invertebrate modeling and to explore how earthworm modeling could be applied to risk assessments, in particular how the different model outputs can be used in the tiered ERA approach. In support of these goals, the workshop aimed at addressing the requirements and concerns of the different stakeholder groups to support further model development. The modeling approach included 4 submodules to cover the most relevant processes for earthworm risk assessment: environment, behavior (feeding, vertical movement), TKTD, and population. Four workgroups examined different aspects of the model with relevance for risk assessment, earthworm ecology, uptake routes, and cross-species extrapolation and model testing. Here, we present the perspectives of each workgroup and highlight how the collaborative effort of participants from multidisciplinary backgrounds helped to establish common ground. In addition, we provide a list of recommendations for how earthworm TKTD modeling could address some of the uncertainties in current risk assessments for plant protection products. Integr Environ Assess Manag 2021;17:352-363. © 2020 SETAC.

A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent-Based Population Models for Ecological Risk Assessment.

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC.

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals.

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. Environ Toxicol Chem 2017;36:845-859. © 2017 SETAC.

Next-generation ecological risk assessment: Predicting risk from molecular initiation to ecosystem service delivery.

Ecological risk assessment is the process of evaluating how likely it is that the environment may be impacted as the result of exposure to one or more chemicals and/or other stressors. It is not playing as large a role in environmental management decisions as it should be. A core challenge is that risk assessments often do not relate directly or transparently to protection goals. There have been exciting developments in in vitro testing and high-throughput systems that measure responses to chemicals at molecular and biochemical levels of organization, but the linkage between such responses and impacts of regulatory significance - whole organisms, populations, communities, and ecosystems - are not easily predictable. This article describes some recent developments that are directed at bridging this gap and providing more predictive models that can make robust links between what we typically measure in risk assessments and what we aim to protect.

Risk communication discourse among ecological risk assessment professionals and its implications for communication with nonexperts.

Risk communication, especially to the general public and end users of plant protection products, is an important challenge. Currently, much of the risk communication the general public receives is via the popular press, and risk managers face the challenge of presenting their decisions and their scientific basis to the general public in an understandable way. Therefore, we decided to explore the obstacles in risk communication, as done by expert risk assessors and managers. Using the discourse analysis framework and readability tests, we studied perspectives of 3 stakeholder groups-regulators, industry representatives, and academics across Europe. We conducted 30 confidential interviews (10 participants in each group), with part of the interview guide focused on communication of pesticide risk to the general public and the ideas experts in the field of risk assessment and management hold of the public perception of pesticides. We used the key informant approach in recruiting our participants. They were first identified as key stakeholders in ecological risk assessment of pesticides and then sampled by means of a snowball sampling technique. In the analysis, first we identified main motifs (themes) in each group, and then we moved to studying length of the sentences and grammar and to uncovering discourses present in the text data. We also used the Flesch Reading Ease test to determine the comprehension difficulty of transcribed interviews. The test is commonly used as a standard for estimating the readability of technical documents. Our results highlight 3 main obstacles standing in the way of effective communication with wider audiences. First of all, ecological risk assessment as a highly technical procedure uses the specific language of ecological risk assessment, which is also highly specialized and might be difficult to comprehend by nonexperts. Second, the idea of existing "expert-lay discrepancy," a phenomenon described in risk perception studies is visibly present in the experts' opinions. Finally, the communication flow among stakeholders was perceived as flawed, e.g., our participants did not consider themselves fully included in the communication process, despite taking part in many networks. Interestingly, both studies on the role of trust in risk perception, and research on links between daily choices and perceived risk, show that the public is more likely to rely on experts they can trust, than the experts in our study were inclined to think.

Developing predictive systems models to address complexity and relevance for ecological risk assessment.

Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have.

Use of the ecosystem services concept in ecological risk assessment of chemicals.

The reason for expressing ecological protection goals in terms of ecosystem services is to make a connection between ecosystems and what people get out of them in terms of marketed goods and nonmarketed welfare. Here our focus will be on how the ecosystem services framework is and can be applied to the ecological risk assessment (ERA) of chemicals. We provide 2 contrasting examples of how the ecosystem services framework is currently being applied in regulatory risk assessment, and we discuss the challenges and knowledge gaps that need to be addressed if such a framework is to substantially improve ERAs and their ability to inform management decisions. We make the point that formulating protection goals in terms of ecosystem services only makes sense if they can be used in managing environmental impacts and if they are useful in informing the risk assessments behind these. Ecosystem services can make a contribution to management by connecting ecosystem structure and process to what is valued, and analyzing risk in this context is a way of making risk assessment more policy- and value-relevant. Using an ecosystem services framework to its fullest potential to support ERA will require the successful development of a suite of coupled Valuation Methods, Ecological Production Functions, and Mechanistic Effect Models that will require the establishment of strong multidisciplinary collaborations among ecologists, computer scientists, social scientists, and possibly others. In addition, buy-in from environmental decision makers and other stakeholders will be crucial. Some progress is being made on the research front, and the implementation of new legislation is providing incentives for developing risk assessment outputs that are much more directly related to environmental protection goals than those used currently.

Stakeholders' perspective on ecological modeling in environmental risk assessment of pesticides: challenges and opportunities.

The article closely examines the role of mechanistic effect models (e.g., population models) in the European environmental risk assessment (ERA) of pesticides. We studied perspectives of three stakeholder groups on population modeling in ERA of pesticides. Forty-three in-depth, semi-structured interviews were conducted with stakeholders from regulatory authorities, industry, and academia all over Europe. The key informant approach was employed in recruiting our participants. They were first identified as key stakeholders in the field and then sampled by means of a purposive sampling, where each stakeholder identified as important by others was interviewed and asked to suggest another potential participant for our study. Our results show that participants, although having different institutional backgrounds often presented similar perspectives and concerns about modeling. Analysis of repeating ideas and keywords revealed that all stakeholders had very high and often contradicting expectations from models. Still, all three groups expected effect models to become integrated in future ERA of pesticides. Main hopes associated with effect models were to reduce the amount of expensive and complex testing and field monitoring, both at the product development stage, and as an aid to develop mitigation measures. Our analysis suggests that, although the needs of stakeholders often overlapped, subtle differences and lack of trust hinder the process of introducing mechanistic effect models into ERA.

Promises and problems for the new paradigm for risk assessment and an alternative approach involving predictive systems models.

The need for cost-effective risk assessment of chemicals is leading to the development of a reductionist paradigm that tries to assess impacts on humans and ecosystems from molecular changes. However, the biggest challenge for this paradigm comes from the emergence of properties that arise out of the interactions of the parts that are not included and yet which are key for assessing likely impacts. Although identifying key events and adverse outcome pathways can shed light on the involvement of important metabolic processes in toxicity, this does not mean that particular molecular initiating events are likely to be robust or accurate predictors of impacts that matter. There are even greater challenges for the new paradigm applied to ecological systems than to human health because of the need to link across more levels of biological organization. The present study argues for a predictive systems approach that makes the linkages through systems models in a mechanistic way that allows for emergence and that also has the potential for reducing the costs and use of animals in ecological risk assessments.

Ecology in a cost-benefit society: the issues.

Is there a role for ecology in a cost-benefit society? As a theme held at Roskilde University in June 2004, this paper summarizes divergent approaches to public policy decision making. Whether based on strict cost-benefit analysis or wide-ranging discussion, we make the point that decisions need to be informed by an understanding of the causes behind environmental problems and their consequences, through impaired ecosystem services, on the economy. Taking this forward will require forums that bring ecologists, economists, and regulators into active and constructive dialogue.

The use and misuse of biomarkers in ecotoxicology.

Substantial efforts have been devoted to developing and applying biomarkers for use in ecotoxicology. These efforts have resulted partly from a desire for early warning indicators that respond before measurable effects on individuals and populations occur and partly as an aid to identifying the causes of observed population- and community-level effects. Whereas older biomarkers focused on measures of organism physiology or biochemistry, advances in molecular biology are extending the biomarker philosophy to the level of the genes (i.e., ecotoxicogenomics). However, the extent to which biomarkers are able to provide unambiguous and ecologically relevant indicators of exposure to or effects of toxicants remains highly controversial. In the present paper, we briefly discuss the application of biomarkers in ecotoxicology and ecological risk assessment, and we provide examples of how they have been applied. We conclude that although biomarkers can be helpful for gaining insight regarding the mechanisms causing observed effects of chemicals on whole-organism performance and may, in some cases, provide useful indicators of exposure, individual biomarker responses should not be expected to provide useful predictions of relevant ecological effects--and probably not even predictions of whole-organism effects. Suites of biomarkers are only likely to provide increased predictability if they can be used in a comprehensive mechanistic model that integrates them into a measure of fitness. Until this can be achieved, biomarkers may be useful for hypothesis generation in carefully controlled experiments. However, because the aims of environmental monitoring and ecological risk assessment are to detect and/or predict adverse chemical impacts on populations, communities, and ecosystems, we should be focusing our efforts on improving methods to do this directly. This will involve developing and testing models of appropriate complexity that can describe real-world systems at multiple scales.

Population growth rate as a basis for ecological risk assessment of toxic chemicals.

Assessing the ecological risks of toxic chemicals is most often based on individual-level responses such as survival, reproduction or growth. Such an approach raises the following questions with regard to translating these measured effects into likely impacts on natural populations. (i) To what extent do individual-level variables underestimate or overestimate population-level responses? (ii) How do toxicant-caused changes in individual-level variables translate into changes in population dynamics for species with different life cycles? (iii) To what extent are these relationships complicated by population-density effects? These issues go to the heart of the ecological relevance of ecotoxicology and we have addressed them using the population growth rate as an integrating concept. Our analysis indicates that although the most sensitive individual-level variables are likely to be equally or more sensitive to increasing concentrations of toxic chemicals than population growth rate, they are difficult to identify a priori and, even if they could be identified, integrating impacts on key life-cycle variables via population growth rate analysis is nevertheless a more robust approach for assessing the ecological risks of chemicals. Populations living under density-dependent control may respond differently to toxic chemicals than exponentially growing populations, and greater care needs to be given to incorporating realistic density conditions (either experimentally or by simulation) into ecotoxicological test designs. It is impractical to expect full life-table studies, which record changes in survival, fecundity and development at defined intervals through the life cycle of organisms under specified conditions, for all relevant species, so we argue that population growth rate analysis should be used to provide guidance for a more pragmatic and ecologically sound approach to ecological risk assessment.