Over the last decade, Drosophila suzukii Matsumura, an invasive pest of soft-skinned fruits, gradually established itself in Europe, often resulting in significant economic losses. In 2011, when D. suzukii was first described for Germany, the Julius Kühn Institut (JKI) started a monitoring program in southwest Germany to study the occurrence and activity of the fly. Capture data from late 2011–early 2018 from 100 traps were analyzed for the effect of weather and immediate habitat on trap captures at different times of the year. We identified five phases in the annual population development cycle of D. suzukii. We found that the mild winter of 2013/2014 helped the thorough establishment of D. suzukii in Germany. Habitat types in the immediate vicinity of the trap and local weather conditions had a strong influence on trap captures. Forest borders and hedges were found to provide adequate overwintering shelter for the flies. Trap captures in forests and hedges were generally higher than those of vineyards and orchards, even during the fruiting seasons. Summer capture rates were correlated with the number of heat days and precipitation. We also discuss briefly the limitations of using trap captures as representative of fly density in the field.

The sclerotia of Sclerotinia sclerotiorum serve as a primary inoculum source for initiating infections. This study aimed to evaluate the effects of environmental factors on sclerotial germination under field conditions by establishing sclerotia depots to monitor apothecia appearance over four consecutive years. Additionally, the effects of soil moisture content (25%, 50%, 75%, and 95%), air temperature (10 °C/10 °C, 14 °C/10 °C, and 18 °C/10 °C), and light conditions (white and UV light) on sclerotial germination and apothecial formation were investigated under controlled conditions with a 17 h day/7 h night regime. Furthermore, variability in carpogenic germination among S. sclerotiorum isolates was examined. From 2021 to 2024, significant differences were observed in both the sclerotia germination rate and timing of germination within the season. High soil moisture, particularly prolonged wetness, and soil temperatures between 10 and 14 °C were key factors for apothecial formation under field conditions. Under controlled conditions, higher soil moisture levels (75% and 95%) accelerated sclerotial germination, with sclerotia incubated at 14 °C/10 °C germinating earlier after 38 days than those at 10 °C/10 °C or 18 °C/10 °C. Additionally, the type of light significantly affected apothecial formation, which was observed only in treatments exposed to a combination of white and UV light. Furthermore, significant variations were also found in the duration until sclerotia of different S. sclerotiorum isolates produced the first stipe and the first apothecium, indicating that the genetic characteristics of each isolate affect carpogenic germination.

This data paper presents a harmonized set of spatial datasets describing 60 agricultural landscapes (10 × 10 km each) generated for selected agricultural regions across six European countries—Denmark, Finland, France, Germany, the Netherlands, and Poland—within the Horizon 2020 EcoStack project. These landscape datasets were developed for use within the Animal, Landscape and Man Simulation System (ALMaSS) and applied within an integrated modeling framework designed to identify management strategies that effectively enhance multiple beneficial organisms, i.e., ecosystem service providers, within European agroecosystems. All landscape models were generated following the methodology detailed in Ziółkowska et al. (2026). Because input data availability and structure varied among countries, the full set of data sources and the processing steps required to account for national and regional specificities are documented. All inputs were harmonized to a common structure, spatial resolution, and Type of Landscape Element (TOLE) legend to support comparability across landscapes. The resulting datasets capture major gradients in farmland structure, composition, and management intensity across Europe. They can support not only agent-based simulations and scenario analyses but also ecological modeling and biodiversity assessments more broadly. All landscape models, associated files, metadata, and landscape-window selection criteria are provided in an open, citable format to facilitate reuse and further development.