Modeling the contribution of toxicokinetic and toxicodynamic processes to the recovery of Gammarus pulex populations after exposure to pesticides

Extrapolation of Metal Toxicity Data for the Rotifer Brachionus calyciflorus Using an Individual-Based Population Model

Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data from which are then extrapolated to derive safe concentrations for the envisioned protection goals. Because such extrapolation in conventional ERA lacks ecological realism, ecological modeling is considered as a promising new approach for extrapolation. Many published population models are complex, that is, they include many processes and parameters, and thus require an extensive dataset to calibrate. In the present study, we investigated how individual-based models based on a reduced version of the Dynamic Energy Budget theory (DEBkiss IBM) could be applied for metal effects on the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions were used to calibrate and evaluate the model for copper effects. While population growth and decline were well predicted, the underprediction of population density and the mismatch in the onset of copper effects were attributed to the simplicity of the approach. The DEBkiss IBM was applied to toxicity datasets for copper, nickel, and zinc. Predicted effect concentrations for these metals based on the maximum population growth rate were between 0.7 and 3 times higher in all but one case (10 times higher) than effect concentrations based on the toxicity data. The size of the difference depended on certain characteristics of the toxicity data: both the steepness of the concentration-effect curve and the relative sensitivity of lethal and sublethal effects played a role. Overall, the present study is an example of how a population model with reduced complexity can be useful for metal ERA. Environ Toxicol Chem 2024;43:324-337. © 2023 SETAC.

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).

High Tolerance and Delayed Responses of Daphnia magna to Neonicotinoid Insecticide Imidacloprid: Toxicokinetic and Toxicodynamic Modeling

Species sensitivity to neonicotinoids has been shown to be highly variable among aquatic invertebrates. Toxicokinetic and toxicodynamic (TKTD) models were constructed to mechanistically elucidate the susceptibility of Daphnia magna to imidacloprid. D. magna was highly tolerant to single short-term exposure to imidacloprid (96-h LC50 of 8.47 μg/mL), but delayed and carry-over toxicity occurred under repeated pulse exposures. Kinetic distribution of imidacloprid between exoskeleton and soft tissues of D. magna was evaluated using a newly developed method. Approximately 84% imidacloprid was distributed to soft tissues but was rapidly depurated from the tissue (t_1/2 of 1.2 h), resulting in low bioaccumulation and high tolerance. TKTD modeling also successfully simulated the survival of D. magna after pulsed exposures. The calculated recovery time was 45 d, indicating significant delayed and carry-over toxicity of the insecticide. While complete elimination of imidacloprid only took about 5 h (TK), slow damage recovery (45 d) caused slow organism recovery (TD). Consequently, although D. magna was tolerant to imidacloprid due to fast depuration from soft tissue, long damage recovery time significantly enhanced the toxicity under repeated pulse exposures. Our study highlights the necessity of integrating delayed and carry-over toxicity quantification in assessing the risk of neonicotinoids to aquatic invertebrates.

Sampling rates for passive samplers exposed to a field-relevant peak of 42 organic pesticides

Pesticide concentrations in agricultural streams are often characterised by a low level of baseline exposure and episodic peak concentrations associated with heavy rainfall events. Traditional sampling methods such as grab sampling, which are still largely used in governmental monitoring, typically miss peak concentrations. Passive sampling represents a cost-efficient alternative but requires the additional determination of sampling rates to calculate time-weighted average (TWA) water concentrations from the accumulated pesticide mass in the sampler. To date, sampling rates have largely been determined in experiments with constant exposure, which does not necessarily reflect field situations. Using Empore styrene-divinylbenzene (SDB) passive sampler disks mounted in metal holders, we determined sampling rates for 42 organic pesticides, of which 27 sampling rates were lacking before. The SDB disks were in an artificial channel system exposed to a field-relevant pesticide peak. We used an open-source algorithm to estimate coefficients of equations for the accumulated pesticide mass in disks and to determine exposure time-dependent sampling rates. These sampling rates ranged from 0.02 to 0.98 L d^-1 and corresponded to those from previous studies determined with constant exposure. The prediction of sampling rates using compound properties was unreliable. Hence, experiments are required to determine reliable sampling rates. We discuss the use of passive sampling to estimate peak concentrations. Overall, our study provides sampling rates and computer code to determine these under peak exposure designs and suggests that passive sampling is suitable to estimate peak pesticide concentrations in field studies.

Drivers of pesticide resistance in freshwater amphipods

Aquatic invertebrates exposed to pesticides may develop pesticide resistance. Based on a meta-analysis we revealed environmental factors driving the magnitude of resistance in the freshwater amphipod Gammarus pulex in the field. We showed that (i) insecticide tolerance of G. pulex increased with pesticide contamination in agricultural streams generally by a factor of up to 4. Tolerance increased even at concentrations lower than what is considered safe in regulatory risk assessment (ii) The increase in insecticide tolerance was pronounced at high test concentrations; comparing the LC50 of populations therefore potentially underestimates the development of resistance. (iii) Insecticide resistance in agricultural streams diminished during the spraying season, suggesting that adverse effects of sublethal concentrations in the short term contrast long-term adaptation to insecticide exposure. (iv) We found that resistance was especially high in populations characterized not only by high pesticide exposure, but also by large distance (>3.3 km) from non-polluted stream sections and by low species diversity within the invertebrate community. We conclude that the test concentration, the timing of measurement, distance to refuge areas and species diversity mediate the observed response of aquatic communities to pesticide pollution and need to be considered for the sustainable management of agricultural practices.

Insecticides in agricultural streams exert pressure for adaptation but impair performance in Gammarus pulex at regulatory acceptable concentrations

Pesticide exposure in agricultural streams requires non-target species to adapt. However, pesticides may reduce performance in between exposure events due to long-term effects and physiological fitness costs of adaptation. Here, we investigated the long-term consequences of pesticide exposure to low concentrations in the widespread crustacean Gammarus pulex. We collected populations from six German streams covering no to moderate agricultural pesticide exposure. Peak concentrations ranged up to 1/400 of their acute median lethal concentration (Toxic Unit = -2.6), resulting in significant changes in the macroinvertebrate community composition (SPEAR_pesticides = up to 0.12). Acute toxicity tests revealed up to 2.5-fold increased tolerance towards the most frequently found insecticide clothianidin compared to populations from non-contaminated streams. However, populations showing increased insecticide tolerance were characterized by reduced survival, per capita growth and mating when cultured under pesticide-free conditions in the laboratory for three months. We conclude that pesticide pollution triggers adaptation both at the species and the community level even at concentrations considered to be safe according to the European pesticide legislation. In G. pulex, exposure and adaptation are associated with impaired performance which potentially affects ecosystem functions such as leaf litter degradation. These long-term impairments need to be considered in deriving safe concentrations.

A 3-Species Aquatic Community Model for Ecological Risk Assessment Using Basic Ecotoxicity Data

A simplified ecosystem model, the Aquatic Tritrophic Ecological Risk Assessment Model (A-TERAM), for the ecological risk assessment of chemicals is presented. The A-TERAM comprises a linear grazer food chain with 3 trophic levels (the algae-Daphnia-fish system). The model simulates the seasonal patterns of abundance at each level observed in the field, and it translates the direct toxic effects of chemicals on algae or Daphnia to implications for fish via ecological interactions; thus, the A-TERAM evaluates ecological risk in terms of the annual population growth rate of fish. The model also incorporates toxicokinetics for fish. The minimum input data required for the A-TERAM are basic ecotoxicity endpoints (algal growth inhibition median effect concentration [EC50] or no-observed effect concentration, Daphnia immobility EC50, and fish acute mortality median lethal concentration); however, additional ecotoxicity data (Daphnia reproduction test, fish early life test, and fish reproduction test) are also relevant for improving simulations. Comparisons made across 496 chemicals (255 nonagricultural chemicals and 241 agrochemicals) indicated that the A-TERAM, in comparison with the conventional predicted-effect concentration/predicted-no-effect concentration method, tended to evaluate higher risk to chemicals that are highly bioaccumulative and toxic to fish by 2 orders of magnitude at the largest but lower or comparable risk to chemicals that are toxic only to algae or Daphnia. Environ Toxicol Chem 2020;39:1086-1100. © 2020 SETAC.

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

Population modeling evaluations of pesticide exposure time series were compared with aspects of a currently used risk assessment process. The US Environmental Protection Agency's Office of Pesticide Programs models daily aquatic 30-yr pesticide exposure distributions in its risk assessments, but does not routinely make full use of the information in such time series. We used mysid shrimp Americamysis bahia toxicity and demographic data to demonstrate the value of a toxicokinetic-toxicodynamic model coupled with a series of matrix population models in risk assessment refinements. This species is a small epibenthic marine crustacean routinely used in regulatory toxicity tests. We demonstrate how the model coupling can refine current risk assessments using only existing standard regulatory toxicity test results. Several exposure scenarios (each with the same initial risk characterization as determined by a more traditional organism-based approach) were created within which population modeling documented risks different from those of assessments based on the traditional approach. We also present different acute and chronic toxicity data scenarios by which toxicokinetic-toxicodynamic coupled with population modeling can distinguish responses that traditional risk evaluations are not designed to detect. Our results reinforce the benefits of this type of modeling in risk evaluations, especially related to time-varying exposure concentrations. Environ Toxicol Chem 2018;37:2633-2644. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Comparison of the behavioural effects of pharmaceuticals and pesticides on Diamesa zernyi larvae (Chironomidae)

Several studies have indicated the presence of contaminants in Alpine aquatic ecosystems. Even if measured concentrations are far below those that cause acute effects, continuous exposure to sub-lethal concentrations may have detrimental effects on the aquatic species present in these remote environments. This may lead to a cascade of indirect effects at higher levels of the ecological hierarchy (i.e., the community). To improve the determination of ecologically relevant risk endpoints, behavioural alterations in organisms due to pollutants are increasingly studied in ecotoxicology. In fact, behaviour links physiological function with ecological processes, and can be very sensitive to environmental stimuli and chemical exposure. This is the first study on behavioural alteration in a wild population of an Alpine species. In the present study, a video tracking system was standardized and subsequently used to identify contaminant-induced behavioural alterations in Diamesa zernyi larvae (Diptera, Chironomidae). Diamesa zernyi larvae, collected in an Italian Alpine stream (Rio Presena, Trentino Region), were acclimated for 24 h and successively exposed to several aquatic contaminants (pesticides: chlorpyrifos, metolachlor, boscalid, captan; pharmaceuticals: ibuprofen, furosemide, trimethoprim) at concentrations corresponding to their Lowest Observed Effect Concentration (LOEC). After 24, 48, 72, and 96 h of exposure, changes in the distance moved, the average speed, and the frequency of body bends were taken to reflect contaminant- and time-dependent effects on larval behaviour. In general, metolachlor, captan, and trimethoprim tended to reduce all the endpoints under consideration, whereas chlorpyrifos, boscalid, ibuprofen, and furosemide seemed to increase the distances moved by the larvae. This could be related to the different mechanisms of action of the investigated chemicals. Independently of the contaminant, after 72 h a general slowing down of all the behavioural activities occurred. Finally, we propose a behavioural stress indicator to compare the overall behavioural effects induced by the various contaminants.

Impaired ecosystem process despite little effects on populations: modeling combined effects of warming and toxicants

Freshwater ecosystems are exposed to many stressors, including toxic chemicals and global warming, which can impair, separately or in combination, important processes in organisms and hence higher levels of organization. Investigating combined effects of warming and toxicants has been a topic of little research, but neglecting their combined effects may seriously misguide management efforts. To explore how toxic chemicals and warming, alone and in combination, propagate across levels of biological organization, including a key ecosystem process, we developed an individual-based model (IBM) of a freshwater amphipod detritivore, Gammarus pseudolimnaeus, feeding on leaf litter. In this IBM, life history emerges from the individuals' energy budgets. We quantified, in different warming scenarios (+1-+4 °C), the effects of hypothetical toxicants on suborganismal processes, including feeding, somatic and maturity maintenance, growth, and reproduction. Warming reduced mean adult body sizes and population abundance and biomass, but only in the warmest scenarios. Leaf litter processing, a key contributor to ecosystem functioning and service delivery in streams, was consistently enhanced by warming, through strengthened interaction between the detritivorous consumer and its resource. Toxicant effects on feeding and maintenance resulted in initially small adverse effects on consumers, but ultimately led to population extinction and loss of ecosystem process. Warming in combination with toxicants had little effect at the individual and population levels, but ecosystem process was impaired in the warmer scenarios. Our results suggest that exposure to the same amount of toxicants can disproportionately compromise ecosystem processing depending on global warming scenarios; for example, reducing organismal feeding rates by 50% will reduce resource processing by 50% in current temperature conditions, but by up to 200% with warming of 4 °C. Our study has implications for assessing and monitoring impacts of chemicals on ecosystems facing global warming. We advise complementing existing monitoring approaches with directly quantifying ecosystem processes and services.

Aquatic ecotoxicological models and their applicability in Arctic regions

Dose-response modeling is one of the most important steps of ecological risk assessment. It requires concentration-effects relationships for the species under consideration. There are very limited studies and experimental data available for the Arctic aquatic species. Lack of toxicity data hinders obtaining dose-response relationships for lethal (LC50 values), sub-lethal and carcinogenic effects. Gaps in toxicity data could be filled using a variety of in-silico ecotoxicological methods. This paper reviews the suitability of such methods for the Arctic scenario. Mechanistic approaches like toxicokinetic and toxicodynamic analysis are found to be better suited for interspecies extrapolation than statistical methods, such as Quantitative Structure-Activity Relationships/Quantitative Structure Activity-Activity Relationship, ICE, and other empirical models, such as Haber's law and Ostwald's equation. A novel approach is proposed where the effects of the toxicant exposure are quantified based on the probability of cellular damage and metabolites interactions. This approach recommends modeling cellular damage using a toxicodynamic model and physiology or metabolites interactions using a toxicokinetic model. Together, these models provide more reliable estimates of toxicity in the Arctic aquatic species, which will assist in conducting ecological risk assessment of Arctic environment.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

Is the chronic Tier-1 effect assessment approach for insecticides protective for aquatic ecosystems?

We investigated the appropriateness of several methods, including those recommended in the Aquatic Guidance Document of the European Food Safety Authority (EFSA), for the derivation of chronic Tier-1 regulatory acceptable concentrations (RACs) for insecticides and aquatic organisms. The insecticides represented different chemical classes (organophosphates, pyrethroids, benzoylureas, insect growth regulators, biopesticides, carbamates, neonicotinoids, and miscellaneous). Chronic Tier-1 RACs derived using toxicity data for the standard species Daphnia magna, Chironomus spp., and/or Americamysis bahia, were compared with Tier-3 RACs derived from micro- and mesocosm studies on basis of the ecological threshold option (ETO-RACs). ETO-RACs could be derived for 31 insecticides applied to micro- and mesocosms in single or multiple applications, yielding a total number of 36 cases for comparison. The chronic Tier-1 RACs calculated according to the EFSA approach resulted in a sufficient protection level, except for 1 neonicotinoid (slightly underprotective) and for several pyrethroids if toxicity data for A. bahia were not included. This latter observation can be explained by 1) the fact that A. bahia is the most sensitive standard test species for pyrethroids, 2) the hydrophobic properties of pyrethroids, and 3) the fact that long-term effects observed in (epi) benthic arthropods may be better explained by exposure via the sediment than via overlying water. Besides including toxicity data for A. bahia, the protection level for pyrethroids can be improved by selecting both D. magna and Chironomus spp. as standard test species for chronic Tier-1 derivation. Although protective in the majority of cases, the conservativeness of the recommended chronic Tier-1 RACs appears to be less than an order of magnitude for a relatively large proportion of insecticides when compared with their Tier-3 ETO-RACs. This may leave limited options for refinement of the chronic effect assessment using laboratory toxicity data for additional species. Integr Environ Assess Manag 2016;12:747-758. © 2015 SETAC.

Developing ecological scenarios for the prospective aquatic risk assessment of pesticides

The prospective aquatic environmental risk assessment (ERA) of pesticides is generally based on the comparison of predicted environmental concentrations in edge-of-field surface waters with regulatory acceptable concentrations derived from laboratory and/or model ecosystem experiments with aquatic organisms. New improvements in mechanistic effect modeling have allowed a better characterization of the ecological risks of pesticides through the incorporation of biological trait information and landscape parameters to assess individual, population and/or community-level effects and recovery. Similarly to exposure models, ecological models require scenarios that describe the environmental context in which they are applied. In this article, we propose a conceptual framework for the development of ecological scenarios that, when merged with exposure scenarios, will constitute environmental scenarios for prospective aquatic ERA. These "unified" environmental scenarios are defined as the combination of the biotic and abiotic parameters that are required to characterize exposure, (direct and indirect) effects, and recovery of aquatic nontarget species under realistic worst-case conditions. Ideally, environmental scenarios aim to avoid a potential mismatch between the parameter values and the spatial-temporal scales currently used in aquatic exposure and effect modeling. This requires a deeper understanding of the ecological entities we intend to protect, which can be preliminarily addressed by the formulation of ecological scenarios. In this article we present a methodological approach for the development of ecological scenarios and illustrate this approach by a case-study for Dutch agricultural ditches and the example focal species Sialis lutaria. Finally, we discuss the applicability of ecological scenarios in ERA and propose research needs and recommendations for their development and integration with exposure scenarios. Integr Environ Assess Manag 2016;12:510-521. © 2015 SETAC.

Trait Characteristics Determine Pyrethroid Sensitivity in Nonstandard Test Species of Freshwater Macroinvertebrates: A Reality Check

We exposed 34 species of stream macroinvertebrates, representing 29 families, to a 90 min pulse of the pyrethroid λ-cyhalothrin. For 28 of these species, no pyrethroid ecotoxicity data exist. We recorded mortality rates 6 days post-exposure, and the behavioral response to pyrethroid exposure was recorded using automated video tracking. Most arthropod species showed mortality responses to the exposure concentrations (0.01-10 μg L(-1)), whereas nonarthropod species remained unaffected. LC50 varied by at least a factor of 1000 among arthropod species, even within the same family. This variation could not be predicted using ecotoxicity data from closely related species, nor using species-specific indicator values from traditional ecological quality indices. Moreover, LC50 was not significantly correlated to effect thresholds for behavioral responses. Importantly, however, the measured surface area-weight ratio and the preference for coarse substrates significantly influenced the LC50 for arthropod species, with the combination of small individuals and strong preference for coarse substrates indicating higher pyrethroid sensitivity. Our study highlights that existing pesticide ecotoxicity data should be extrapolated to untested species with caution and that actual body size (not maximum potential body size, as is usually available in traits databases) and habitat preference are central parameters determining species sensitivities to pyrethroids.

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.

Population-level effects and recovery of aquatic invertebrates after multiple applications of an insecticide

Standard risk assessment of plant protection products (PPP) combines "worst-case" exposure scenarios with effect thresholds using assessment (safety) factors to account for uncertainties. If needed, risks can be addressed applying more realistic conditions at higher tiers, which refine exposure and/or effect assessments using additional data. However, it is not possible to investigate the wide range of potential scenarios experimentally. In contrast, ecotoxicological mechanistic effect models do allow for addressing a multitude of scenarios. Furthermore, they may aid the interpretation of experiments such as mesocosm studies, allowing extrapolation to conditions not covered in experiments. Here, we explore how to use mechanistic effect models in the aquatic risk assessment of a model insecticide (Modelmethrin), applied several times per season but rapidly dissipating between applications. The case study focuses on potential effects on aquatic arthropods, the most sensitive group for this substance. The models provide information on the impact of a number of short exposure pulses on sensitive and/or vulnerable populations and, when impacted, assess recovery. The species to model were selected based on their sensitivity in laboratory and field (mesocosm) studies. The general unified threshold model for survival (GUTS) model, which describes the toxicokinetics and toxicodynamics of chemicals in individuals, was linked to 3 individual-based models (IBM), translating individual survival of sensitive organisms into population-level effects. The impact of pulsed insecticide exposures on populations were modeled using the spatially explicit IBM metapopulation model for assessing spatial and temporal effects of pesticides (MASTEP) for Gammarus pulex, the Chaoborus IBM for populations of Chaoborus crystallinus, and the "IdamP" model for populations of Daphnia magna. The different models were able to predict the potential effects of Modelmethrin applications to key arthropod species inhabiting different aquatic ecosystems; the most sensitive species were significantly impacted unless respective mitigation measures were implemented (buffer zones resulting in reduced exposure). As expected the impact was stronger in shallow ditches as compared to deeper pond scenarios. Furthermore, as expected, recovery depended on factors such as temperature (affecting population growth rate and number of generations) and the occurence of nonimpacted aquatic ecosystems (their frequency and connectivity). These model predictions were largely in line with field observations and/or the results of a mesocosm study, providing additional evidence on the suitability and reliability of the models for risk assessment purposes. Because of their flexibility, models may predict the likelihood of unacceptable effects-based on previously defined protection goals-for a range of insecticide exposure scenarios and freshwater habitats.

Ecological modelling and toxicity data coupled to assess population recovery of marine amphipod Gammarus locusta: Application to disturbance by chronic exposure to aniline

A population agent-based model of marine amphipod Gammarus locusta was designed and implemented as a basis for ecological risk assessment of chemical pollutants impairing life-history traits at the individual level. We further used the model to assess the toxic effects of aniline (a priority hazardous and noxious substance, HNS) on amphipod populations using empirically-built dose-response functions derived from a chronic bioassay that we previously performed with this species. We observed a significant toxicant-induced mortality and adverse effects in reproductive performance (reduction of newborn production) in G. locusta at the individual level. Coupling the population model with the toxicological data from the chronic bioassay allowed the projection of the ecological costs associated with exposure to aniline that might occur in wild populations. Model simulations with different scenarios indicated that even low level prolonged exposure to the HNS aniline can have significant long-term impacts on G. locusta population abundance, until the impacted population returns to undisturbed levels. This approach may be a useful complement in ecotoxicological studies of chemical pollution to transfer individual-collected data to ecological-relevant levels.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

A simulation study on effects of exposure to a combination of pesticides used in an orchard and tuber crop on the recovery time of a vulnerable aquatic invertebrate

The aim of the present study was to assess whether population effects and recovery times increase when a population of a vulnerable aquatic invertebrate is exposed to concentrations of 1 or multiple pesticides. The 2 sets of pesticide combinations tested are typical for orchard and tuber crops in The Netherlands. Exposure concentrations were predicted using the FOCUS step 3 modeling framework and the Dutch drainage ditch scenario. Recovery times were assessed using the MASTEP population model. We simulated the population dynamics and pesticide effects in a Monte Carlo style by using median effective concentration values drawn from an arthropod species sensitivity distribution. In the tuber scenario, exposure to λ-cyhalothrin resulted in long-term effects, whereas exposure to the co-occurring compound fluazinam hardly resulted in (additional) effects. In the orchard scenario, 3 pesticides resulted in large effects just after exposure, but pulse exposures to these compounds did not coincide. The probabilities of effects for the single compounds added up for the combination; in contrast, the recovery times were not higher for the combination compared to those associated with exposure to the individual compounds. The conclusion from the present study's simulations is that exposure to the evaluated pesticide packages may lead to increased mortality probabilities and effect sizes of the combination, but does not lead to longer recovery times for populations with synchronized reproduction than when exposed to the individual compounds.

Comparing population recovery after insecticide exposure for four aquatic invertebrate species using models of different complexity

Population models, in particular individual-based models (IBMs), are becoming increasingly important in chemical risk assessment. They can be used to assess recovery of spatially structured populations after chemical exposure that varies in time and space. The authors used an IBM coupled to a toxicokinetic-toxicodynamic model, the threshold damage model (TDM), to assess recovery times for 4 aquatic organisms, after insecticide application, in a nonseasonal environment and in 3 spatial settings (pond, stream, and ditch). The species had different life histories (e.g., voltinism, reproductive capacity, mobility). Exposure was derived from a pesticide fate model, following standard European Union scenarios. The results of the IBM-TDM were compared with results from simpler models: one in which exposure was linked to effects by means of concentration-effect relationships (IBM-CE) and one in which the IBM was replaced by a nonspatial, logistic growth model (logistic). For the first, exposure was based on peak concentrations only; for the second, exposure was spatially averaged as well. By using comparisons between models of different complexity and species with different life histories, the authors obtained an understanding of the role spatial processes play in recovery and the conditions under which the full time-varying exposure needs to be considered. The logistic model, which is amenable to an analytic approach, provided additional insights into the sensitivity of recovery times to density dependence and spatial dimensions.