Search

Myriophyllum spicatum is a sediment-rooted, aquatic macrophyte growing submerged, with a wide geographical distribution and high ecological relevance in freshwater ecosystems. It is used in testing and risk assessment for pesticides in water and sediment. Population models enable effects measured under laboratory conditions to be extrapolated to effects expected in the field with time-variable environmental factors including exposure. These models are a promising tool in higher tier risk assessments. However, there is a lack of data on the seasonal dynamics of M. spicatum, which is needed to test model predictions of typical population dynamics in the field. To generate such data, a 2-year study was set up in outdoor experimental systems from May 2017 to May 2019. The growth of M. spicatum was monitored in 0.2025 m2 plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh and dry weight), shoot length, seasonal short-term growth rates of shoots, relevant environmental parameters and weather data. The results showed a clear seasonal pattern of biomass and shoot length and their variability. Myriophyllum spicatum reached a maximum total shoot length of 125.3 m.m-2 and a maximum standing crop aboveground dry weight of 262 g.m-2. Periodical growth rates reached up to 0.072.d-1, 0.095.d-1 and 0.085.d-1 for total length, fresh weight and dry weight, respectively. Multivariate regression revealed that pH (as a surrogate for the availability of carbon species) and water temperature could explain a significant part of the variability in Myriophyllum spicatum growth rates (p-values < 0.05). This study has delivered an ecologically relevant dataset on seasonal population dynamics representative of shallow freshwater ecosystems, which can be used to test and refine population models for use in chemical risk assessment and ecosystem management.

The dataset covers biotic and abiotic data from the aquatic habitat of a population of the sediment-rooted macrophyte Myriophyllum spicatum in the temperate climate region (The Netherlands). The growth of M. spicatum was monitored in 0.2025 m2 plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh and dry weight), shoot length, seasonal short-term growth rates of shoots, relevant environmental parameters and weather data. This dataset includes the 2-year experimental biotic (macrophyte biomass and growth data) and environmental data (water quality data, sediment data). A second file includes the statistical data. A third file includes the weather data.

Mechanistic effect models (MEMs) are useful tools for ecological risk assessment of chemicals to complement experimentation. However, there are currently no recommendations for how to use them in risk assessments. Therefore, the SETAC MODELINK workshop aimed at providing guidance for when and how to apply MEMs in regulatory risk assessments. The workshop focused on risk assessment of plant protection products under Regulation (EC) No 1107/2009 using MEMs at the organism- and population levels. Realistic applications of MEMs were demonstrated in six case studies covering assessments for plants, invertebrates and vertebrates in aquatic and terrestrial habitats. From the case studies and their evaluation, 12 recommendations on the future use of MEMs were formulated, addressing the issues of how to translate specific protection goals into workable questions, how to select species and scenarios to be modelled, and where and how to fit MEMs into current and future risk assessment schemes. The most important recommendations are: protection goals should be made more quantitative; the species to be modelled must be vulnerable not only regarding toxic effects but also regarding their life history and dispersal traits; the models should be as realistic as possible for a specific risk assessment question, and the level of conservatism required for a specific risk assessment should be reached by designing appropriately conservative environmental and exposure scenarios; scenarios should include different regions of the EU and different crops; in the long run, generic MEMs covering relevant species based on representative scenarios should be developed, which will require EU-level joint initiatives of all stakeholders involved. The main conclusion from the MODELINK workshop is that the considerable effort required for making MEMs an integral part of environmental risk assessment of pesticides is worthwhile because it will make risk assessments not only more ecologically relevant an

In the European registration procedure for pesticides, microcosm and mesocosm studies are the highest aquatic experimental tier to assess their environmental effects. Evaluations of microcosm/mesocosm studies rely heavily on no observed effect concentrations (NOECs) calculated for different population-level endpoints. Ideally, a power analysis should be reported for the concentration–response relationships underlying these NOECs, as well as for measurement endpoints for which significant effects cannot be demonstrated. An indication of this statistical power can be provided a posteriori by calculated minimum detectable differences (MDDs). The MDD defines the difference between the means of a treatment and the control that must exist to detect a statistically significant effect. The aim of this paper is to expand on the Aquatic Guidance Document recently published by the European Food Safety Authority (EFSA) and to propose a procedure to report and evaluate NOECs and related MDDs in a harmonised way. In addition, decision schemes are provided on how MDDs can be used to assess the reliability of microcosm/mesocosm studies and for the derivation of effect classes used to derive regulatory acceptable concentrations. Furthermore, examples are presented to show how MDDs can be reduced by optimising experimental design and sampling techniques.

While many ecological models addressing pesticide risk assessment can be found in the academic literature, they are rarely applied in pesticide registrations. In order to determine issues with existing models as published in literature, we assess the state-of-the-art of ecological models addressing pesticide risk assessments. We focus on how toxic effects were modelled, how risk was quantified, and on the verification and validation of the models. From an extensive literature scan, 41 models were selected for review. Three main classes of models are used for pesticide risk assessment: difference and differential equations (14 out of 41 models), matrix models (17), and individual-based models (IBMs; 8). Additionally, two grid-based simulations were included. In the majority of models, toxicity was implemented as increased mortality, and risk was quantified by the effects on population dynamics. In some publications, both measures remained unclear. Apart from a subset of the IBMs, no validation was performed on the models. Another problem could be identified in the often ambiguous description of the models, and a lack of justification of the choice of model type. From this review of models as published in scientific literature, we conclude that most models do not address key issues of pesticide risk assessment sufficiently. We provide recommendations for the future use of ecological models in pesticide risk assessment.

Ecological modelling has the potential to become a standard tool in higher tier risk assessments of pesticides. However, most stakeholders involved are not familiar with the rationale and methods of ecological modelling, and as a consequence, they do not know how to assess models and when models are to be trusted. Therefore, I here give a short introduction to ecological modelling. After presenting the three main model types of population models relevant for pesticide risk assessment, I explain why choice of model type and structure should not be ad hoc, but instead be determined by a detailed specification of the model's purpose. Finally, I recommend that modellers offer short courses where non-modellers from industry and regulatory authorities are introduced to ecological modelling in more detail, and where modellers can learn more about the specific requirements of the regulatory process.

The LEMTOX workshop had the aim to bring together experts from industry, academia and regulatory authorities to discuss (1) the benefits of ecological models (EMs) for pesticide risk assessment, (2) to identify issues that so far have prevented a wider use of EMs in the regulatory context, and (3) to agree on the next steps to be taken to establish EMs as a more widely used tool for or pesticide risk assessment. During the workshop, in a series of keynote lectures the perspectives of industry, academia and regulatory authorities were summarized, and three example models were presented. In breakout group and plenary discussions, the three topics of the workshop were discussed. There was general consensus that EMs have a high potential, or might even be the only way, to achieve risk assessments that are more ecologically relevant. A major challenge in establishing EMs as a common tool is the lack of a guidance document defining Good Modelling Practice. The next steps to be taken in order to establish EMs in pesticide registration are to build a core group of stakeholders to organize a follow-up workshop where a draft guidance document on Good Modelling Practice is produced, and to perform carefully selected case studies that follow the guidance document and which clearly demonstrate the added value of risk assessments that are supported by ecological models.

no abstract

This brief communication reports on the main findings of the LEMTOX workshop, held from 9 to 12 September 2007, at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. The workshop brought together a diverse group of stakeholders from academia, regulatory authorities, contract research organizations, and industry, epresenting Europe, the United States, and Asia, to discuss the role of ecological modeling in risk assessments of pesticides, particularly under the European regulatory framework. The following questions were addressed: What are the potential benefits of using ecological models in pesticide registration and risk assessment? What obstacles prevent ecological modeling from being used routinely in regulatory submissions? What actions are needed to overcome the identified obstacles? What recommendations should be made to ensure good modeling practice in this context? The workshop focused exclusively on population models, and discussion was focused on those categories of population models that link effects on individuals (e.g., survival, growth, reproduction, behavior) to effects on population dynamics. The workshop participants concluded that the overall benefits of ecological modeling are that it could bring more ecology into ecological risk assessment, and it could provide an excellent tool for exploring the importance of, and interactions among, ecological complexities. However, there are a number of challenges that need to be overcome before such models will receive wide acceptance for pesticide risk assessment, despite having been used extensively in other contexts (e.g., conservation biology). The need for guidance on Good Modeling Practice (on model development, analysis, interpretation, evaluation, documentation, and communication), as well as the need for case studies that can be used to explore the added value of ecological models for risk assessment, were identified as top priorities. Assessing recovery potential of exposed no

no abstract