A comprehensive dataset on plant-associated invertebrates and gardening activities, from 100 sites across five urban green space types in Zurich, Lugano, and Geneva, Switzerland

Sebastian Ruile, Arthur Knecht, Alessandra Knuser, Leona Hug, Majken Grimm, Kilian Perrelet, Vivien Grothe, Louise Dädlow, Bertrand Fournier, Joan Casanelles Abella, Marco Moretti

This dataset describes plant-associated invertebrates, gardening activities, and habitat diversity across five urban green spaces (UGS) types in the cities of Zurich, Lugano, and Geneva, Switzerland. The UGS types, namely allotment lot, private garden, residential estate, park, and ruderal area, cover different purposes, ownership, and management regimes. While Zurich was the core study region, we partly replicated the procedure in Geneva and Lugano to validate the results. Specifically, in Zurich, we selected twelve sites per UGS type and sampled invertebrates using an entomological net for flower-associated invertebrates and a hand vacuum for foliage-associated invertebrates, while in Lugano and Geneva, we focused on flower-associated invertebrates at four sites per UGS type. By applying a combination of morphospecies and DNA metabarcoding approaches, we obtained high taxonomic resolution and abundance information. In addition, we assessed the gardening activities within the sites using a questionnaire targeting the decision makers responsible for the green spaces and the habitat diversity using remote sensing and orthophotos. In total, we collected and identified 94’740 individual invertebrates, of which 58% were identified at the species level, 22.8% at the genus level, and the remaining at higher taxonomic levels. This dataset enables the investigation of invertebrate community composition, plant-invertebrate interaction networks, supports comparative analyses across urban systems, and, due to the gardening activity questionnaire, allows interdisciplinary analyses at the border of ecology and social sciences. Furthermore, the combination of taxonomic and abundance data allows the integration with other datasets for meta-analyses and cross-city comparison.