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The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for non-EU regulated cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A non-EU regulated cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other

Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi‐faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time‐horizons: 1) reactive, when there is an imminent threat to ES resilience and a high pressure to act, 2) adjustive, when the threat is known in general but there is still time to adapt management and 3) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology and engineering are often implicitly focussing on provident, adjustive or reactive resilience, respectively, but these different notions of resilience and their corresponding social, ecological and economic tradeoffs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer‐term management actions are not missed while urgent threats to ES are given priority.

African swine fever (ASF) entered Georgia in 2007 and the EU in 2014. In the EU, the virus primarily spread in wild boar (Sus scrofa) in the period from 2014–2018. However, from the summer 2018, numerous domestic pig farms in Romania were affected by ASF. In contrast to the existing knowledge on ASF transmission routes, the understanding of risk factors and the importance of different transmission routes is still limited. In the period from May to September 2019, 655 Romanian pig farms were included in a matched case-control study investigating possible risk factors for ASF incursion in commercial and backyard pig farms. The results showed that close proximity to outbreaks in domestic farms was a risk factor in commercial as well as backyard farms. Furthermore, in backyard farms, herd size, wild boar abundance around the farm, number of domestic outbreaks within 2 km around farms, short distance to wild boar cases and visits of professionals working on farms were statistically significant risk factors. Additionally, growing crops around the farm, which could potentially attract wild boar, and feeding forage from ASF affected areas to the pigs were risk factors for ASF incursion in backyard farms.

Following a request from the European Commission, the EFSA Panel on Plant Health performed a risk assessment of the entry of Pantoea stewartii subsp. stewartii on maize seed imported by the EU from the USA. This pest is a Gram-negative bacterium which causes Stewart's vascular wilt and leaf blight of maize (including sweet corn), a disease responsible for serious crop losses throughout the world. The following scenarios were considered: scenario A0 (current practice), scenario A1 (US request for modification of EU conditions for derogation), and scenario A2 (EU conditions for derogation). Results from the quantitative seed pathway model presented here show that, despite the low rates of plant-to-seed and seed-to-seedling transmission that have been reported in the literature for Stewart's wilt, given the amount of traded seed, and in the case of voluntary (i.e. not mandatory) inspections of seed production fields at the origin (i.e. scenario A0), the frequency of introducing the disease is in the order of magnitude of some hundred introductions per year (median number). The EU conditions for derogation would lead to a decrease in the likelihood of entry compared to scenarios A0 (about 10,000 times fewer introductions) and A1 (about 2,000 times fewer introductions). This protective effect is mainly due to the requirement that only genotypes resistant to Stewart's wilt are traded, with the additional field inspection (two instead of one per season) providing additional reassurance. The Panel also concluded that seed lot inspections, as currently carried out (e.g. with a sample of 400 seeds) are not likely to lead to a relevant reduction in the level of infected imported maize seed, given the low prevalence of Stewart's wilt at the origin. If, however, there is aggregation in infection among consignments, inspection would work towards identifying the highly infected consignments. Recently, outbreaks of Stewart's wilt have occurred in Italy (Emilia Romagna, Fr

The Panel on Plant Health performed a pest categorisation of the fungus Thecaphora solani, the causal agent of smut of potato, for the EU. The identity of the pest is well established and reliable methods exist for its detection and identification. T solani is present in Bolivia, Chile, Colombia, Ecuador, Mexico, Panama, Peru and Venezuela. The pathogen is not known to occur in the EU and is listed in Annex IAI of Directive 2000/29/EC, meaning its introduction into the EU is prohibited. The major host is Solanum tuberosum (potato), but various other tuber-forming Solanum species are also affected. The pest has also been reported on Solanum lycopersicum (tomato), and wild solanaceous plants are also affected. All the major hosts and pathways of entry are currently regulated. Host availability and climate matching suggest that T solani could establish in parts of the EU and further spread by human-assisted means. The disease induces gall formation on potato tubers, stolons and underground stem parts, reducing yield and making tubers unmarketable. The pest introduction in the EU would potentially cause impacts to potato production. In the infested areas, the only available strategy to control the disease and prevent it from spreading is the application of quarantine and sanitation measures and the cultivation of resistant varieties. The main uncertainties concern the host range, the biology and epidemiology of the pest, and the potential of the pest to enter the EU through three unregulated minor pathways. T solani meets all the criteria assessed by EFSA for consideration as potential Union quarantine pest. The criteria for considering T solani as a potential Union regulated non-quarantine pest are not met, since the pest is not known to occur in the EU. (C) 2018 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.

The Panel on Plant Health performed a pest categorisation of Stagonosporopsis andigena, the causal agent of black blight of potato, for the EU. The pest is a well-defined fungal species and reliable methods exist for its detection and identification. S. andigena is present in Bolivia and Peru. The pest is not known to occur in the EU and is listed in Annex IAI of Directive 2000/29/EC as Phoma andina, meaning its introduction into the EU is prohibited. The major cultivated host is Solanum tuberosum (potato); other tuber-forming Solanum species and wild solanaceous plants are also affected. All hosts and pathways of entry of the pest into the EU are currently regulated. Host availability and climate matching suggest that S. andigena could establish in parts of the EU and further spread mainly by human-assisted means. The pest affects leaves, stems and petioles of potato plants causing lesions and premature leaf drop but not the underground parts, including tubers. The disease causes yield reductions up to 80%, depending on the susceptibility of potato cultivars. Early application of fungicide sprays and cultivation of resistant potato cultivars are the most effective measures for disease management. The pest introduction in the EU would potentially cause impacts to potato production. The main uncertainties concern the host range, the maximum period the pest survives on host debris in soil, the maximum distance over which conidia of the pest could be dispersed by wind-blown rain, and the magnitude of potential impacts to the EU. S. andigena meets all the criteria assessed by EFSA for consideration as potential Union quarantine pest. The criteria for considering S. andigena as a potential Union regulated non-quarantine pest are not met, since the pest is not known to occur in the EU. (C) 2018 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.

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.

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity., Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.