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Protecting the structure and functioning of soil ecosystems is one of the central aims of current regulations of chemicals. This is, for instance, shown by the emphasis on the protection of key drivers and ecosystem services as proposed in the protection goal options for soil organisms by the European Food Safety Authority (EFSA). Such targets require insight into soil biodiversity, its role in the functioning of ecosystems, and the way it responds to stress. Also required are tools and methodologies for properly assessing biodiversity. To address these issues, the Society of Environmental Toxicology and Chemistry (SETAC) Europe 14th Special Science Symposium (SESSS14) was held 19 to 20 November 2019 in Brussels, Belgium. The central aim of the SESSS14 was to provide information on how to include soil biodiversity and soil functions as protection goal options in the risk assessment and quantification of the effects of chemicals and other stressors (including their respective regulations). This paper is based on the presentations and discussions at the SESSS14 and will give a brief update on the scientific state‐of‐the art on soil biodiversity, novel scientific developments, experimental and modeling approaches, as well as case studies. It will also discuss how these approaches could inform future risk assessment of chemicals and other stressors in the regulatory context of protecting soil ecosystems. Integr Environ Assess Manag 2021;17:541–551. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC), KEY POINTS The SETAC Europe 14th Special Science Symposium (SESSS14) aimed at providing information on how to include soil biodiversity and soil functions (ecosystem services) as protection goal options in the risk assessment and quantification of the effects of chemicals and other stressors.Definitions and associated terminology currently used to describe soil biodiversity are given, together with a brief but comprehensive state‐of‐the‐art overview of the current scientific knowledge on soil biodiversity and its relation to the functioning of soils.Backgrounds and current practices regarding the way protection of soil biodiversity is addressed in chemical regulations are described, including drawbacks and the possible ways forward.Novel methods for assessing biodiversity in soils are presented, as well as approaches, both experimental and modeling, for assessing effects of (chemical) stressors on soil biodiversity and the potential consequences for ecosystem services.

Pre‐market/prospective environmental risk assessments (ERAs) contribute to risk analyses performed to facilitate decisions about the market introduction of regulated stressors. Robust ERAs begin with an explicit problem formulation, which involves among other steps: (1) formally devising plausible pathways to harm that describe how the deployment of a regulated stressor could be harmful; (2) formulating risk hypotheses about the likelihood and severity of such events; (3) identifying the information that will be useful to test the risk hypotheses; and (4) developing a plan to acquire new data for hypothesis testing should tests with existing information be insufficient for decision‐making. Here, we apply problem formulation to the assessment of possible adverse effects of RNA interference‐based insecticidal genetically modified (GM) plants, GM growth hormone coho salmon, gene drive‐modified mosquitoes and classical biological weed control agents on non‐target organisms in a prospective manner, and of neonicotinoid insecticides on bees in a retrospective manner. In addition, specific considerations for the problem formulation for the ERA of nanomaterials and for landscape‐scale population‐level ERAs are given. We argue that applying problem formulation to ERA maximises the usefulness of ERA studies for decision‐making, through an iterative process, because: (1) harm is defined explicitly from the start; (2) the construction of risk hypotheses is guided by policy rather than an exhaustive attempt to address any possible differences; (3) existing information is used effectively; (4) new data are collected with a clear purpose; (5) risk is characterised against well‐defined criteria of hypothesis corroboration or falsification; and (6) risk assessment conclusions can be communicated clearly. However, problem formulation is still often hindered by the absence of clear policy goals and decision‐making criteria (e.g. definition of protection goals and what constitutes harm) that are needed to guide the interpretation of scientific information. We therefore advocate further dialogue between risk assessors and risk managers to clarify how ERAs can address policy goals and decision‐making criteria. Ideally, this dialogue should take place for all classes of regulated stressors, as this can promote alignment and consistency on the desired level of protection and maximum tolerable impacts across regulated stressors.

Following a request from the European Commission, a set of assessment criteria was developed to support the selection of existing environmental surveillance networks for post‐market environmental monitoring (PMEM) of genetically modified plants (GMPs). In compliance with these criteria, some networks and associated programmes were identified as being of potential use subject to further case‐by‐case analysis. When considering PMEM of GMPs, the approach would also require comparing sites monitored by the networks and the locations where GMPs are cultivated. The reporting of the sites surveyed by networks and locations of cultivated GMPs should thus follow the same standards in order to ensure interoperability and to potentially establish a causal link between a change observed and the GMPs. In this respect, technical support might be required by networks to transform their data records into workable standards. Moreover, the EFSA GMO Panel was asked by the European Commission to examine the sensitivity of statistical analyses used by the networks to detect change. A decision tree is provided for selecting the optimal method for statistical analysis based on the study design and the datasets from networks. Sufficient statistical power needs to be ensured to detect an effect for a particular indicator. Sample size is one of the main contributing factors in determining the power of any network to detect an effect of a product release into the environment. Increasing the sample size implies variable extra‐costs depending on whether data are collected by volunteers or professionals. A more powerful statistical analysis can also be achieved by pooling datasets collected by different networks; this needs further investigation because of important covariates leading to differentiated responses. In general, PMEM would benefit from a move towards ‘open data’ policies for re‐analysis or pooling data collected by different networks.