Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of endocrine disruptor effects on trout

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early-life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP key events to DEB processes through "damage" that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and DEB models to predict sublethal and lethal effects on young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters point to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern. Environ Toxicol Chem 2023;42:2040-2053. © 2023 Oak Ridge National Laboratory and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Impacts of human activities on the supply of marine ecosystem services: A conceptual model for offshore wind farms to aid quantitative assessments

Increased pressures from human activities may cause cumulative ecological effects on marine ecosystems. Increasingly, the study of ecosystem services is applied in the marine environment to assess the full effects of human activities on the ecosystem and on the benefits it provides. However, in the marine environment, such integrated studies have yet to move from qualitative and score-based to fully quantitative assessments. To bridge this gap, this study proposed a 4-tiered method for summarizing available knowledge and modelling tools to aid in quantitative assessments of ecosystem services supply. First, the ecosystem functioning mechanisms underlying the supply of services are conceptually mapped. Second, the impacts of the human activity of interest are summarized and linked to the first conceptual model in a case-specific model of ecosystem services supply. Third, indicators are selected that would best represent changes in the most important parameters of the conceptual model in a quantitative manner. Fourth, the knowledge gained in the previous steps is used to select models that are most useful to quantify changes in ecosystem services supply under the human pressure of interest. This approach was applied to the case study of offshore wind energy in the Belgian part of the North Sea, which is one of the most rapidly expanding industries in the marine environment globally. This study provides a useful tool to proceed towards quantification of marine ecosystem services, highlighting the need for a fully integrated approach to developing environmental impact assessment tools.

Extrapolating Contaminant Effects from Individuals to Populations: A Case Study on Nanoparticle Toxicity to Daphnia Fed Environmentally Relevant Food Levels

Ecological risk assessment (ERA) is charged with assessing the likelihood a chemical will have adverse environmental or ecological effects. When assessing the risk of a potential contaminant to biological organisms, ecologists are most concerned with the sustainability of populations of organisms, rather than protecting every individual. However, ERA most commonly relies on data on the effect of a potential contaminant on individuals because these experiments are more feasible than costly population-level exposures. In this work, we address the challenge of extrapolating these individual-level results to predict population-level effects. Previous per-capita population growth rate estimates calculated from individual-level exposures of Daphnia pulicaria to silver nanoparticles (AgNPs) at different food rations predict a critical daily food requirement for daphnid populations exposed to 200 μg/L AgNPs to avoid extinction. To test this, we exposed daphnid populations to the same AgNP concentration at three different food inputs, with the lowest ration close to the extinction threshold predicted from data on individuals. The two populations with the higher food inputs persisted, and the population with the lowest food input went extinct after 50 days but did persist through two generations. We demonstrate that we can extrapolate between these levels of biological organization by parameterizing an individual-level biomass model with data on individuals' response to AgNPs and using these parameters to predict the outcome for control and AgNP-exposed populations. Key to successful extrapolation is careful modeling of temporal changes in resource density, driven by both the experimental protocols and feedback from the consumer. The implication for ecotoxicology is that estimates of extinction thresholds based on studies of individuals may be reliable predictors of population outcomes, but only with careful treatment of resource dynamics.

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.

Towards a comprehensive sustainability methodology to assess anthropogenic impacts on ecosystems: Review of the integration of Life Cycle Assessment, Environmental Risk Assessment and Ecosystem Services Assessment

Nowadays, a variety of methodologies are available to assess local, regional and global impacts of human activities on ecosystems, which include Life Cycle Assessment (LCA), Environmental Risk Assessment (ERA) and Ecosystem Services Assessment (ESA). However, none can individually assess both the positive and negative impacts of human activities at different geographical scales in a comprehensive manner. In order to overcome the shortcomings of each methodology and develop more holistic assessments, the integration of these methodologies is essential. Several studies have attempted to integrate these methodologies either conceptually or through applied case studies. To understand why, how and to what extent these methodologies have been integrated, a total of 110 relevant publications were reviewed. The analysis of the case studies showed that the integration can occur at different positions along the cause-effect chain and from this, a classification scheme was proposed to characterize the different integration approaches. Three categories of integration are distinguished: post-analysis, integration through the combination of results, and integration through the complementation of a driving method. The literature review highlights that the most recurrent type of integration is the latter. While the integration through the complementation of a driving method is more realistic and accurate compared to the other two categories, its development is more complex and a higher data requirement could be needed. In addition to this, there is always the risk of double-counting for all the approaches. None of the integration approaches can be categorized as a full integration, but this is not necessarily needed to have a comprehensive assessment. The most essential aspect is to select the appropriate components from each methodology that can cover both the environmental and socioeconomic costs and benefits of human activities on the ecosystems.

Integrating Bioavailability of Metals in Fish Population Models

Population models are increasingly being used to extrapolate individual-level effects of chemicals, including metals, to population-level effects. For metals, it is also important to take into account their bioavailability to correctly predict metal toxicity in natural waters. However, to our knowledge, no models exist that integrate metal bioavailability into population modeling. Therefore, our main aims were to 1) incorporate the bioavailability of copper (Cu) and zinc (Zn) into an individual-based model (IBM) of rainbow trout (Oncorhynchus mykiss), and 2) predict how survival-time concentration data translate to population-level effects. For each test water, reduced versions of the general unified threshold model of survival (GUTS-RED) were calibrated using the complete survival-time concentration data. The GUTS-RED individual tolerance (IT) showed the best fit in the different test waters. Little variation between the different test waters was found for 2 GUTS-RED-IT parameters. The GUTS-RED-IT parameter "median of distribution of thresholds" (m_w ) showed a strong positive relation with the Ca²⁺ , Mg²⁺ , Na⁺ , and H⁺ ion activities. Therefore, m_w formed the base of the calibrated GUTS bioavailability model (GUTS-BLM), which predicted 30-d x% lethal concentration (LCx) values within a 2-fold error. The GUTS-BLM was combined with an IBM, inSTREAM-Gen, into a GUTS-BLM-IBM. Assuming that juvenile survival was the only effect of Cu and Zn exposure, population-level effect concentrations were predicted to be 1.3 to 6.2 times higher than 30-d laboratory LCx values, with the larger differences being associated with higher interindividual variation of metal sensitivity. The proposed GUTS-BLM-IBM model can provide insight into metal bioavailability and effects at the population level and could be further improved by incorporating sublethal effects of Cu and Zn. Environ Toxicol Chem 2021;40:2764-2780. © 2021 SETAC.

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.

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.

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.

Using native and invasive livebearing fishes (Poeciliidae, Teleostei) for the integrated biological assessment of pollution in urban streams

Invasive species are increasingly replacing native species, especially in anthropogenically transformed or polluted habitats. This opens the possibility to use invasive species as indicator taxa for the biological assessment of pollution. Integrated biological assessment, however, additionally relies on the application of multiple approaches to quantify physiological or cytogenetic responses to pollution within the same focal species. This is challenging when species are restricted to either polluted or unpolluted sites. Here, we make use of a small group of neotropical livebearing fishes (family Poeciliidae) for the integrated biological assessment of water quality. Comparing urban and suburban stream sections that receive varying degrees of pollution from industrial and domestic waste waters in and around the Brazilian city of Uberlândia, we demonstrate that two members of this family may indeed serve as indicators of water pollution levels. The native species Phalloceros caudimaculatus appears to be replaced by invasive guppies (Poecilia reticulata) at heavily polluted sites. Nevertheless, we demonstrate that both species could be used for the assessment of bioaccumulation of heavy metals (Pb, Cu, and Cr). Ambient (sediment) concentrations predicted concentrations in somatic tissue across species (R²-values between 0.74 and 0.96). Moreover, we used cytogenetic methods to provide an estimate of genotoxic effects of water pollution and found pollution levels (multiple variables, condensed into principal components) to predict the occurrence of nuclear abnormalities (e.g., frequencies of micro-nucleated cells) across species (R² between 0.69 and 0.83). The occurrence of poeciliid fishes in urban and polluted environments renders this family a prime group of focal organisms for biological water quality monitoring and assessment. Both species could be used interchangeably to assess genotoxic effects of water pollution, which may facilitate future comparative analyses over extensive geographic scales, as members of the family Poeciliidae have become invasive in tropical and subtropical regions worldwide.

Similar individual-level responses to stressors have different population-level consequences among closely related species of trout

In this paper, we applied an individual-based model to study the population-level impacts of sub-lethal stressors affecting the metabolic pathways of three closely related trout species: Oncorhynchus mykiss (rainbow trout, RT), Salmo trutta (brown trout, BT) and Oncorhynchus calrki stomias (greenback cutthroat trout, GCT). Both RT and BT are well-studied species, and the former is widely used as a standard cold-water test species. These species are known to outcompete GCT, which is listed as threatened under the US Endangered Species Act. Our goal was to understand the extent to which stressor effects, which are often measured at the individual level, on taxonomically-related (i.e., surrogate) species can be informative of impacts on population dynamics in species that cannot be tested (e.g., listed species). When comparing stressor effects among species, we found that individual-level responses to each stressor were qualitatively comparable. Individual lengths and number of eggs decreased by similar percentages with respect to baseline, even if small quantitative differences were present depending on the physiological mode of action of the stressor. Individual-level effects in GCT were slightly greater when ingestion efficiency decreased, whereas effects in GCT and RT were greater when maintenance costs increased, and effects in BT were slightly greater when costs of growth increased. In contrast, results at the population level differed markedly among species with GCT the most impacted by sub-lethal stress effects on individual metabolism. Our findings suggest that using non-listed species to assess the risks of stressors to listed species populations may be misleading, even if the species are closely related and show similar individual-level responses. Mechanistic population models that incorporate species life history and ecology can improve inter-species extrapolation of stressor effects.

Analysis of an Ecological Flow Regime during the Ctenopharyngodon Idella Spawning Period Based on Reservoir Operations

The study of fish habitats is important for us to better understand the impact of reservoir construction on river ecosystems. Many habitat models have been developed in the past few decades. In this study, a fuzzy logic-based habitat model, which couples fuzzy inference system, two-dimensional laterally averaged hydrodynamic model, and two-dimensional shallow water hydrodynamic model, is proposed to identify the baseline condition of suitable habitat for fish spawning activities. The proposed model considers the reservoir and the downstream river channel, and explores the comprehensive effects of water temperature, velocity, and water depth on habitat suitability. A real-world case that considers the Ctenopharyngodon idella in the Xuanwei Reservoir of Qingshui River is studied to investigate the effect of in- and outflow of reservoir on fish habitat and the best integrative management measure of the model. There were 64 simulations with different reservoir in- and outflows employed to calculate the weighted usable area and hydraulic habitat suitability. The experimental results show that the ecological flow for Ctenopharyngodon idella spawning can satisfy the basic demand when the reservoir inflow is greater than 60 m3/s and the reservoir outflow is greater than 100 m3/s. The habitat ecological suitability is the best when the reservoir outflow is 120 m3/s. A more reasonable and reliable ecological flow range can be obtained based on the habitat model in this paper, which provides the best scenario for water resources planning and management in the Qingshui River Basin.

Applying ecosystem services for pre-market environmental risk assessments of regulated stressors

Ecosystem services (ES) are the benefits that people obtain from ecosystems. Investigating the environment through an ES framework has gained wide acceptance in the international scientific community and is applied by policymakers to protect biodiversity and safeguard the sustainability of ecosystems. This approach can enhance the ecological and societal relevance of pre‐market/prospective environmental risk assessments (ERAs) of regulated stressors by: (1) informing the derivation of operational protection goals; (2) enabling the integration of environmental and human health risk assessments; (3) facilitating horizontal integration of policies and regulations; (4) leading to more comprehensive and consistent environmental protection; (5) articulating the utility of, and trade‐offs involved in, environmental decisions; and (6) enhancing the transparency of risk assessment results and the decisions based upon them. Realisation of these advantages will require challenges that impede acceptance of an ES approach to be overcome. Particularly, there is concern that, if biodiversity only matters to the extent that it benefits humans, the intrinsic value of nature is ignored. Moreover, our understanding of linkages among ecological components and the processes that ultimately deliver ES is incomplete, valuing ES is complex, and there is no standard ES lexicon and limited familiarity with the approach. To help overcome these challenges, we encourage: (1) further research to establish biodiversity–ES relationships; (2) the development of approaches that (i) quantitatively translate responses to chemical stressors by organisms and groups of organisms to ES delivery across different spatial and temporal scales, (ii) measure cultural ES and ease their integration into ES valuations, and (iii) appropriately value changes in ES delivery so that trade‐offs among different management options can be assessed; (3) the establishment of a standard ES lexicon; and (4) building capacity in ES science and how to apply ES to ERAs. These development needs should not prevent movement towards implementation of an ES approach in ERAs, as the advantages we perceive of using this approach render it more than worthwhile to tackle those challenges. Society and the environment stand to benefit from this shift in how we conduct the ERA of regulated stressors.

Environmental DNA Shaping a New Era of Ecotoxicological Research

Aquatic ecosystems, such as rivers and lakes, are exposed to multiple stressors from anthropogenic activity and changes in climate, which have resulted in a general decrease in biodiversity, alteration of community structures, and can ultimately result in reduction of resources provided by natural ecosystems. Adverse outcomes caused by pollutants to ecosystems are determined not only by toxic properties but also ecological contexts of ecosystems, including indigenous biodiversity and community composition. It is therefore important to identify key factors, such as diversity of species and traits that determine the vulnerability of structures and functions of ecosystems in response to toxic substances. Detection and quantification of biodiversity and its activities using environmental DNA (eDNA) is arguably one of the most important technical advances in ecology in recent years. A huge opportunity has appeared to allow more relevant approaches for assessments of risks posed to ecosystems by toxic substances. eDNA approaches provide effective and efficient tools to evaluate the effects of chemical pollutants on (1) the occurrences and population of wildlife, (2) communities, and (3) the function of ecosystem in the field. Here a conceptual framework of adverse outcome pathways to relate molecular initiating events to apical ecosystem-level responses is proposed to connecting laboratory-based prediction to observations under field conditions. Particularly, future research opportunities on effects on biodiversity, community structure, and ecosystem function by toxic substances will be discussed.