7. General Framework
7.3. Surrogate reference tier (SRT) and the systems approach
Current practice in prospective ERA is to conduct the exposure and effect assessment for one PPP at a time. An important question is whether the chemical-by-chemical approach in the current prospective ERA for PPPs is sufficient also to prevent cumulative risks from exposure to different PPPs, as well as to predict ecological recovery. To determine this, the impact of multiple stressors on the state of the population needs to be taken into account when assessing a particular PPP impact. Thus, due to the complexity of ecological systems and the need to evaluate direct and indirect effects and recovery in spatial and temporal dimensions, a systems approach is considered appropriate by EFSA (EFSA Scientific Committee, 2016a). In this context, a systems approach is defined to mean taking into account the range of factors considered to potentially interact and affect the result of the risk assessment. For example, this would include multiple applications and non-chemical stressors as they might affect the organisms considered in the assessment. It may also include indirect effect and abiotic factors. The surrogate reference tier (SRT) for this type of assessment would thus be a fully implemented ecological model system including the important factors identified.
In many other systems (e.g. non-target arthropods, aquatic systems), the systems approach is needed owing to the impacts of both spatial and temporal drivers of population change. Spatial drivers, in particular ‘action at a distance’ are relevant for those groups of organisms (EFSA PPR Panel, 2015a; EFSA Scientific Committee, 2016a). In soil, the scales and rates of movements are smaller and thus the primary drivers considered are temporal drivers of population change, i.e. the vital rates. This means that recovery would be primarily driven by internal population growth rather than external migrations (see Section 3.2), and that the measurement endpoint in focus is the long-term population growth rate.
In order to adopt a systems approach and to integrate this into the risk assessment, several steps need to be taken:
1) Relevant taxa and focal cropping systems need to be identified to create relevant scenarios.
These species need to cover those where population impacts and recovery can be related to the SPGs;
2) The normal operating range of relevant taxa needs to be identified (bearing in mind that this may vary in time and between different ecosystems). This is used to establish baselines against which the system with the addition of the regulated pesticide can be assessed.
These baselines would need to be established for the range of scenarios needed to represent the range of conditions for which the assessment should cover (e.g. low input and high input agro-ecosystems);
3) Good mechanistic effect models, which are both manageable and realistic enough, will need to be developed. To assess effects on other species in an ecological network requires food-web modelling (De Ruiter et al., 2005a,b). However, the use of food-food-web models for assessment would require that they are predictive, and that their predictive quality has been proven in independent experiments. Hence, although food-web models are conceptually suitable and appropriate, parameterisation and uncertainty of predictions are challenges in their application in risk assessments (see e.g. De Ruiter et al., 1998, 2005a,b; Traas et al., 2004; Baird et al., 2011; De Laender et al., 2011). For community-level assessment, recourse must therefore be made to field studies (see Section 9.7). Note also that the longer time-frame for field-study assessment provides the potential to detect delayed community or life-history effects, e.g. as a result of reproductive impacts. However, in terms of understanding the case-specific results of field studies, food-web models may play an important role. In contrast, population models are relatively easy to develop and require fewer case-specific data. Hence, for assessment of long-term impacts the use of population models is proposed.
For in-soil organisms, it is advised to take the aspects that affect life span into account, rather than large-scale spatial dynamics. For some organisms, vertical movements in the soil profile might be of relevance to assess exposure to PPP. Therefore, for in-soil organisms, there are only a limited number of aspects to consider in terms of their impact and timing. These are:
•
The regulated stressor of interest and its intended use;•
Abiotic conditions, e.g. temperature and moisture, as they affect population-growth rate;•
The reproductive profile within a season of the relevant taxa;•
The mortality profile within a season of the relevant taxa;•
Individual growth and development;•
Individual vertical movement within the soil profile, if relevant;•
Individual toxicokinetics and toxicodynamics of the active substance, in combination with varying exposure in the soil profile;•
Impacts of non-regulated stressors, probably primarily impacts of agricultural management;•
Other regulated stressors, i.e. other pesticides, GMO crops and biocides, as relevant.The models to be developed do not need to take every possible management scenario into account. In edge-of-field surface waters there are typically 2–3 pesticides dominating the mixture in terms of toxic units (see e.g. Liess and Von der Ohe, 2005; Belden et al., 2007; Sch€afer et al., 2007;
Verro et al., 2009). Consequently, when addressing cumulative stress of pesticides in ERA, it seems cost-effective to focus on those pesticides that dominate the exposure in terms of toxic units in the relevant medium (e.g. > 90%). However, it is important that a range of scenarios altering potential vulnerability of populations is taken into account (e.g. highly stressed populations may be more vulnerable to further stressors).
Information on the distribution of crops in agricultural landscapes and frequently occurring pesticide combinations may be derived from existing databases (e.g. databases under the EU subsidies scheme and databases from EU pesticide usage as collected within the frame of the Sustainable Use Directive, Garthwaite et al., 2015). This information may be important input for population models to evaluate effect periods and recovery times following pesticide stress in a realistic agricultural landscape context (e.g. Focks et al., 2014; Topping et al., 2016).
7.3.1. Population modelling for lower tier assessments
The use of population modelling including all relevant environmental and ecological parameters, is designed to cover two important endpoints in the risk assessment, i.e. long-term population effects
and spatial distribution effects. These endpoints are considered over multiple years and would be expressed as a change in distribution of the population over an area modelled and a change in density of area occupied (Høye et al., 2012; EFSA PPR Panel 2015a). To use the modelling in this way, it will be necessary first to have decided exactly what criteria would be applied to the data from population model(s) in order to assess whether or not the relevant SPGs were achieved (or whether or not they were achieved to a sufficient degree). In this case, application of the models does not suffer from the same issues as field studies or TMEs, i.e. practical issues of measurement endpoints interpreted against minimum detectable differences in field data; outputs from the models can be very precise.
However, modelling involves other uncertainties (see Section 7.7.2).
One possibility would be to use the modelling to calibrate the toxicity tests for lower tiers. The outcome of the population model(s) would be dependent on parameter values used for toxicity and other chemical properties in combination with the relevant use and environmental scenarios (the regulatory scenario (EFSA PPR Panel, 2014b)). Provided that the model(s) were easy enough to run, it should in principle be possible to establish the highest toxicity input that would lead to acceptable outcomes for any particular substance. However, by doing this, there is a risk of confounding uncertainties associated with different endpoints and complicating the use of the model at higher tiers. Therefore, we recommend that the modelling and standard toxicity testing are seen as parallel and complementary activities.
7.3.1.1. Practical application of population modelling in lower tiers
Lower tiers should in principle be more conservative than higher tiers, and the tests should be easy to carry out. The use of complex population modelling in lower tiers seems contradictory to these principles, but need not necessarily be so. To use the models developed as one component of the surrogate reference tier in lower tiers, three main criteria need to be met:
1) The models must be standard, agreed models for focal vulnerable species where the behaviour is known and trusted without the option to alter model behaviour.
2) The scenarios used should be standard scenarios.
3) Inputs to the models must be simple, ideally the same data as used in, or coming from, standard lower tier tests (toxicity and use information).
4) For the lowest tier, the use of dynamic population modelling is not suggested, rather a set of look-up tables based on the results of standard population modelling of a range of standard scenarios and toxicities should be created. This look-up table can be used as a lower level screening (see Section7.3).
5) Refinement of the model in terms of specific exposure scenarios will require running the dynamic model, and is thus described as subsequent tier (see below).
If these criteria are met then the results of the models can easily be interpreted as standard outputs, to which suitable standard assessment factors can be applied. This approach is very much parallel to the idea of FOCUS scenarios in aquatic exposure assessment and would mean that the models could be run by anyone with a short training in model usage, but the outputs could be interpreted easily by anyone.
To further streamline the assessment at lower tiers and negate the running of the model as part of the assessment, a look-up table for model results could be used. This was also suggested for non-target arthropod ERA (EFSA PPR Panel, 2015a). Here, a very wide range of standard scenarios (landscapes, toxicity and intended use) would be pre-run and evaluated. These scenarios should cover the range of possible uses, toxicities and modes of action. The lowest tier assessment would then be made by matching the substance to be assessed to the one of standard inputs and using the pre-run scenario results to determine the risk. The advantage of this method would be that initial screening for long-term population impacts, both spatial and temporal, would be very fast and many products could pass this part of the lower tier assessment without the need to run models. Since standard scenarios would need to be developed as part of the ERA guidance in any case, the additional resources needed to run different toxicity profiles for each scenario to create the look-up table would not be very significant.
7.3.1.2. Refinement of population modelling
If a lower tier population modelling screening is failed, refinement of the modelling requires running the models with altered inputs. There is no expectation that the models themselves will be altered as part of this process because to do so would require further tests and agreement of the altered model
by regulators. This would be a complicated and time-consuming procedure and leads to the need for regulators to be able to assess impacts of the model changes on the ERA outputs. Hence, it is proposed that the only refinements allowed would be of toxicology and exposure, e.g. more accurate toxicity inputs, more realistic use or more realistic exposure.