Linking pesticide exposure and spatial dynamics: An individual-based model of wood mouse (Apodemus sylvaticus) populations in agricultural landscapes

Should I Stay or Should I Go? Seasonal Fluctuations of Wood Mouse Populations in Fields Surrounded by Woodlands

The wood mouse Apodemus sylvaticus is common in woodlands and open areas of the Western Palearctic. Despite extensive research, little is known about its population ecology in fields in the Mediterranean area, where the climate involves great seasonal changes in environmental features. Here, we investigated wood mice seasonal fluctuations in the number of captures and population structure by sampling long-fallow fields and woodlands, i.e., oak forest and conifer plantation, in a heterogeneous landscape of central Italy. Mice were live-trapped every two months for three years (23.814 trap-days). The number of captures, mice body weight, and proportion of adult, residents and breeding individuals were analyzed. Mice dynamics changed across seasons and habitats. In fields, we recorded more captures, more reproductive individuals, and fewer non-adults and resident individuals in the warmer months compared to the colder months; mice were heavier in warmer months. During the cold season, the captures and adult proportion in fields were lower than in resource-rich woodlands. Breeding and non-resident mice were more abundant in fields than in woodlands in warmer months. Overall, the seasonal demographic variations we recorded provide evidence that fields can represent a suboptimal habitat in Mediterranean heterogeneous landscapes, acting nonetheless as a source of food resources, cover, and mates for mice in spring-summer.

From theory to practice in pattern-oriented modelling: identifying and using empirical patterns in predictive models

To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern-oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent-based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM-ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM-ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.

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.

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

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation). We propose a coherent and unifying naming scheme for all current major DEB variants, explore the implications of each model's underlying assumptions in terms of its capability and complexity and analyse differences between the models (endpoints, mathematical differences, physiological modes of action). The results imply a hierarchy of model complexity which could be used to guide the implementation of simplified model variants. We provide a decision tree to support matching the simplest suitable model to a given research or regulatory question. We detail which new insights can be gained by using DEB in toxicokinetic-toxicodynamic modelling, both generally and for the specific example of ERA, and highlight open questions. Specifically, we outline a moving time window approach to assess time-variable exposure concentrations and discuss how to account for cross-generational exposure. Where possible, we suggest valuable topics for experimental and theoretical research.

European hares do not avoid newly pesticide-sprayed fields: Overspray as unnoticed pathway of pesticide exposure

Although risk assessments for pesticides involve quantifying exposure routes for animals, little empirical evidence exists on how individuals use areas where pesticides were used. Further, the European Food Safety Authority guidelines for the risk assessment of birds and mammals currently only include direct dietary uptake from exposed plants as important pathway for pesticides, arguing that dermal exposure is generally negligible. Here, we use the European hare (Lepus europaeus) as a model of a farmland specialist to investigate if (1) hares adjust habitat use in response to pesticide spraying, using GPS data, and (2) calculate the pesticide exposure and uptake over different pathways, i.e. foraging uptake versus overspray and subsequent oral grooming, using an agent-based modelling approach. Apart from avoidance of sprayed fields on the spraying day by inactive hares, which was likely caused by the mechanical disturbance rather than the pesticide itself, we found no evidence that hares reduced the use of pesticide-sprayed fields compared to control observations where no pesticides were applied. Our simulation showed that both the proportion of exposed individuals and the pesticide uptake were related to the pathway of exposure (foraging versus overspray/oral grooming), and depended on the age class and the vegetation type. We found that pesticide uptake via overspray/oral grooming might be 7-fold higher compared to foraging and might thus be an important pathway of pesticide exposure in hares. Our findings emphasize that policy makers, specifically the European Food Safety Authority, should incorporate alternative pathways of pesticide exposure for birds and mammals, such as overspray and oral grooming, when conducting environmental risk assessments and take variation in vegetation structure and age-related animal behavior into account, because these factors might affect pesticide exposure. Interactions between pesticide application and vegetation structure may both increase or decrease exposure but can be predicted using a simulation approach.

Using Ecological Modelling to Assess the Long-Term Survival of the West-Indian Manatee (Trichechus manatus) in the Panama Canal

There is evidence of a thriving population of West-Indian manatee (Trichechus manatus) in the Panama Canal, although it is not clear if they are descendants of a small group of introduced manatees or if manatees have entered the Canal from the Caribbean through the Canal locks. This study describes the development and application of an individual-based model to assess the survival of a population of West-Indian manatees in the Panama Canal. In addition, we seek to determine the effects of isolation, predation, and mortality on long term survival. The model was parameterized using empirical data collected from the literature to every extent possible. A sensitivity analysis was performed to evaluate the model’s sensitivity to changes in the used parameters. Four scenarios were modeled to understand under which conditions the original population could have been maintained over time. Our results show that the manatee population would have collapsed quite quickly after its initial introduction and that only through the addition of several individuals into the lake over the years could the population have survived until the present day. Our results have important implications for the long-term conservation of this endangered species.

Predicting population responses to environmental change from individual-level mechanisms: towards a standardized mechanistic approach

Animal populations will mediate the response of global biodiversity to environmental changes. Population models are thus important tools for both understanding and predicting animal responses to uncertain future conditions. Most approaches, however, are correlative and ignore the individual-level mechanisms that give rise to population dynamics. Here, we assess several existing population modelling approaches and find limitations to both 'correlative' and 'mechanistic' models. We advocate the need for a standardized mechanistic approach for linking individual mechanisms (physiology, behaviour, and evolution) to population dynamics in spatially explicit landscapes. Such an approach is potentially more flexible and informative than current population models. Key to realizing this goal, however, is overcoming current data limitations, the development and testing of eco-evolutionary theory to represent interactions between individual mechanisms, and standardized multi-dimensional environmental change scenarios which incorporate multiple stressors. Such progress is essential in supporting environmental decisions in uncertain future conditions.

Assessing the population relevance of endocrine-disrupting effects for nontarget vertebrates exposed to plant protection products

The European Commission intends to protect vertebrate wildlife populations by regulating plant protection product (PPP) active substances that have endocrine-disrupting properties with a hazard-based approach. In this paper we consider how the Commission's hazard-based regulation and accompanying guidance can be operationalized to ensure that a technically robust process is used to distinguish between substances with adverse population-level effects and those for which it can be demonstrated that adverse effects observed (typically in the laboratory) do not translate into adverse effects at the population level. Our approach is to use population models within the adverse outcome pathway framework to link the nonlinear relationship between adverse effects at the individual and population levels in the following way: (1) use specific protection goals for focal wildlife populations within an ecosystem services framework; (2) model the effects of changes in population-related inputs on focal species populations with individual-based population models to determine thresholds between negligible and nonnegligible (i.e., adverse) population-level effects; (3) compare these thresholds with the relevant endpoints from laboratory toxicity tests to determine whether they are likely to be exceeded at hazard-based limits or the maximum tolerated dose/concentration from the experimental studies. If the population threshold is not exceeded, then the substance should not be classified as an endocrine disruptor with population-relevant adversity unless there are other lines of evidence within a weight-of-evidence approach to challenge this. We believe this approach is scientifically robust and still addresses the political and legal requirement for a hazard-based assessment. Integr Environ Assess Manag 2019;15:278-291. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913. © 2016 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.

A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

Landscape structure and management alter the outcome of a pesticide ERA: Evaluating impacts of endocrine disruption using the ALMaSS European Brown Hare model

There is a gradual change towards explicitly considering landscapes in regulatory risk assessment. To realise the objective of developing representative scenarios for risk assessment it is necessary to know how detailed a landscape representation is needed to generate a realistic risk assessment, and indeed how to generate such landscapes. This paper evaluates the contribution of landscape and farming components to a model based risk assessment of a fictitious endocrine disruptor on hares. In addition, we present methods and code examples for generation of landscape structures and farming simulation from data collected primarily for EU agricultural subsidy support and GIS map data. Ten different Danish landscapes were generated and the ERA carried out for each landscape using two different assumed toxicities. The results showed negative impacts in all cases, but the extent and form in terms of impacts on abundance or occupancy differed greatly between landscapes. A meta-model was created, predicting impact from landscape and farming characteristics. Scenarios based on all combinations of farming and landscape for five landscapes representing extreme and middle impacts were created. The meta-models developed from the 10 real landscapes failed to predict impacts for these 25 scenarios. Landscape, farming, and the emergent density of hares all influenced the results of the risk assessment considerably. The study indicates that prediction of a reasonable worst case scenario is difficult from structural, farming or population metrics; rather the emergent properties generated from interactions between landscape, management and ecology are needed. Meta-modelling may also fail to predict impacts, even when restricting inputs to combinations of those used to create the model. Future ERA may therefore need to make use of multiple scenarios representing a wide range of conditions to avoid locally unacceptable risks. This approach could now be feasible Europe wide given the landscape generation methods presented.

An example of population-level risk assessments for small mammals using individual-based population models

This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios.

An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops

Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus) population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape) was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to simulate how farming practices affect pest population dynamics, and the consequent impact of different control strategies on the risk and speed of resistance development.

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.

Common vole (Microtus arvalis) ecology and management: implications for risk assessment of plant protection products

Common voles (Microtus arvalis) are common small mammals in some European landscapes. They can be a major rodent pest in European agriculture and they are also a representative generic focal small herbivorous mammal species used in risk assessment for plant protection products. In this paper, common vole population dynamics, habitat and food preferences, pest potential and use of the common vole as a model small wild mammal species in the risk assessment process are reviewed. Common voles are a component of agroecosystems in many parts of Europe, inhabiting agricultural areas (secondary habitats) when the carrying capacity of primary grassland habitats is exceeded. Colonisation of secondary habitats occurs during multiannual outbreaks, when population sizes can exceed 1000 individuals ha(-1) . In such cases, in-crop common vole population control management has been practised to avoid significant crop damage. The species' status as a crop pest, high fecundity, resilience to disturbance and intermittent colonisation of crop habitats are important characteristics that should be reflected in risk assessment. Based on the information provided in the scientific literature, it seems justified to modify elements of the current risk assessment scheme for plant protection products, including the use of realistic food intake rates, reduced assessment factors or the use of alternativee focal rodent species in particular European regions. Some of these adjustments are already being applied in some EU member states. Therefore, it seems reasonable consistently to apply such pragmatic and realistic approaches in risk assessments for plant protection products across the EU.

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.

More ecological ERA: incorporating natural environmental factors and animal behavior

We discuss the importance of selected natural abiotic and biotic factors in ecological risk assessment based on simplistic laboratory bioassays. Although it is impossible to include all possible natural factors in standard lower-tier ecotoxicological testing, neglecting them is not an option. Therefore, we try to identify the most important factors and advocate redesigning standard testing procedures to include theoretically most potent interactions. We also point out a few potentially important factors that have not been studied enough so far. The available data allowed us to identify temperature and O2 depletion as the most critical factors that should be included in ecotoxicity testing as soon as possible. Temporal limitations and fluctuations in food availability also appear important, but at this point more fundamental research in this area is necessary before making decisions on their inclusion in risk assessment procedures. We propose using specific experimental designs, such as Box-Behnken or Central Composite, which allow for simultaneous testing of 3 or more factors for their individual and interactive effects with greater precision and without increasing the effort and costs of tests dramatically. Factorial design can lead to more powerful tests and help to extend the validity of conclusions. Finally, ecological risk assessment procedures should include information on animal behavior, especially feeding patterns. This requires more basic studies, but already at this point adequate mechanistic effect models can be developed for some species.

The use of traits-based approaches and eco(toxico)logical models to advance the ecological risk assessment framework for chemicals

This article presents a framework to diagnose and predict the effects of chemicals, integrating 2 promising tools to incorporate more ecology into ecological risk assessment, namely traits-based approaches and ecological modeling. Traits-based approaches are used increasingly to derive correlations between the occurrence of species traits and chemical exposure from biological and chemical monitoring data. This assessment can also be used in a diagnostic way, i.e., to identify the chemicals probably posing the highest risks to the aquatic ecosystems. The article also describes how ecological models can be used to explore how traits govern the species-substance interactions and to predict effects at the individual, population, and community and ecosystem level, i.e., from the receptor to the landscape level. This can be done by developing models describing the toxicokinetics and toxicodynamics of the chemical in the individual, the life-history of species and the connectivity of populations, determining their recovery, and the food web relations at the community and ecosystem level that determine the indirect effects. Special attention is given on how spatial aspects can be included in the ecological risk assessments using ecological models. The components of the framework are introduced and critically discussed. We describe how the different tools and data generated through experimentation (laboratory and semifield) and biomonitoring can be integrated. The article uses examples from the aquatic compartment, but the concepts that are used, and their integration within the framework, can be generalized to other environmental compartments.