Periodic Reporting for period 1 - PollinERA (Understanding pesticide-Pollinator interactions to support EU Environmental Risk Assessment and policy)
Reporting period: 2024-01-01 to 2025-06-30
Pollinators such as wild bees, butterflies, moths and hoverflies are vital for biodiversity, food production, and ecosystem health. In the EU alone, over 80% of wild flowering plants and 75% of food crops depend to some degree on animal pollination. Yet many pollinator species are in decline, with pesticide exposure, habitat loss, climate change, and disease among the main drivers. Current EU risk assessments for pesticides focus almost exclusively on honey bees and individual substances, which does not reflect the complexity of real agricultural landscapes, where multiple pollinator species encounter mixtures of chemicals over time.
PollinERA is developing a next-generation, systems-based approach to assessing and managing pesticide risks to a broad diversity of pollinators. The project combines field monitoring, laboratory testing, predictive toxicology, population and landscape modelling, and active stakeholder engagement. Over its first 18 months, it has:
1. Filled critical ecotoxicological knowledge gaps through standardised test protocols and species sensitivity data for multiple underrepresented pollinator taxa;
2. Implemented integrated pesticide–pollinator co-monitoring in three countries across two major cropping systems;
3. Developed advanced predictive toxicology and population modelling tools;
4. Built a prototype web-based ERA platform to test scenarios at the landscape scale.
These outputs will enable more representative, realistic, and policy-relevant risk assessments, contributing directly to EU biodiversity targets, the Farm to Fork Strategy, and the EU Pollinators Initiative.
PollinERA is developing a next-generation, systems-based approach to assessing and managing pesticide risks to a broad diversity of pollinators. The project combines field monitoring, laboratory testing, predictive toxicology, population and landscape modelling, and active stakeholder engagement. Over its first 18 months, it has:
1. Filled critical ecotoxicological knowledge gaps through standardised test protocols and species sensitivity data for multiple underrepresented pollinator taxa;
2. Implemented integrated pesticide–pollinator co-monitoring in three countries across two major cropping systems;
3. Developed advanced predictive toxicology and population modelling tools;
4. Built a prototype web-based ERA platform to test scenarios at the landscape scale.
These outputs will enable more representative, realistic, and policy-relevant risk assessments, contributing directly to EU biodiversity targets, the Farm to Fork Strategy, and the EU Pollinators Initiative.
Field teams in Italy, Poland, and Sweden collected 180 environmental samples (nectar, pollen, plants, soil, water) from 18 monitoring sites in three countries, representing gradients of expected pesticide use and habitat availability for potential mitigation. Laboratory protocols for acute, sublethal, and chronic toxicity testing were developed and validated for wild bees, hoverflies, and other taxa, generating initial datasets for six species. Predictive toxicology advanced through curated datasets, mode-of-action–based Cumulative Assessment Groups, and new in silico models integrated into VEGAHUB.
Modelling progress included the BufferGUTS toxicokinetic–toxicodynamic framework calibrated for multiple exposure routes, four agent-based pollinator population models with realistic behaviours and life histories, and major performance upgrades to the ALMaSS pesticide fate engine. The co-monitoring protocols were developed and implemented across all sites, producing directly linked pollinator community data and 143 pesticide residue samples. Landscape models are now fully operational for five countries, with high-resolution data processing underway for Sweden and Italy. A functional systems ERA prototype integrates species, fate, and exposure models with interactive scenario configuration, enabling simulation of pesticide impacts under varied management and environmental conditions.
Modelling progress included the BufferGUTS toxicokinetic–toxicodynamic framework calibrated for multiple exposure routes, four agent-based pollinator population models with realistic behaviours and life histories, and major performance upgrades to the ALMaSS pesticide fate engine. The co-monitoring protocols were developed and implemented across all sites, producing directly linked pollinator community data and 143 pesticide residue samples. Landscape models are now fully operational for five countries, with high-resolution data processing underway for Sweden and Italy. A functional systems ERA prototype integrates species, fate, and exposure models with interactive scenario configuration, enabling simulation of pesticide impacts under varied management and environmental conditions.
PollinERA is delivering scientific and technical innovations that go well beyond current practice in pesticide ERA. Standardised testing protocols and sensitivity data for wild bees, butterflies, moths and hoverflies provide, for the first time, regulatory-ready methods covering a representative range of pollinators. The integrated co-monitoring scheme is unprecedented in its scope, combining high-resolution pesticide residue data from multiple matrices with simultaneous pollinator biodiversity surveys across contrasting European landscapes.
Predictive toxicology advances include the first mode-of-action–based grouping and modelling of pesticides for multiple pollinator species, enabling mixture risk assessment and prediction of toxicity for untested substances. BufferGUTS allows realistic simulation of multi-pathway exposures over time, while agent-based species models in ALMaSS integrate fate simulations and landscape structure to predict population-level outcomes. The web-based ERA tool under development integrates these components into a single, user-accessible platform that can run complex “what-if” policy or management scenarios. These methods could be adapted for other chemical classes, including biocontrol products, pesticide alternatives, and other altered agricultural management practices.
Predictive toxicology advances include the first mode-of-action–based grouping and modelling of pesticides for multiple pollinator species, enabling mixture risk assessment and prediction of toxicity for untested substances. BufferGUTS allows realistic simulation of multi-pathway exposures over time, while agent-based species models in ALMaSS integrate fate simulations and landscape structure to predict population-level outcomes. The web-based ERA tool under development integrates these components into a single, user-accessible platform that can run complex “what-if” policy or management scenarios. These methods could be adapted for other chemical classes, including biocontrol products, pesticide alternatives, and other altered agricultural management practices.