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The study of mutualistic interaction networks has led to valuable insights into ecological and evolutionary processes. However, our understanding of network structure may depend upon the temporal scale at which we sample and analyze network data. To date, we lack a comprehensive assessment of the temporal scale-dependence of network structure across a wide range of temporal scales and geographic locations. If network structure is temporally scale-dependent, networks constructed over different temporal scales may provide very different perspectives on the structure and composition of species interactions. Furthermore, it remains unclear how various factors – including species richness, species turnover, link rewiring and sampling effort – act in concert to shape network structure across different temporal scales. To address these issues, we used a large database of temporally-resolved plant–pollinator networks to investigate how temporal aggregation from the scale of one day to multiple years influences network structure. In addition, we used structural equation modeling to explore the direct and indirect effects of temporal scale, species richness, species turnover, link rewiring and sampling effort on network structural properties. We find that plant–pollinator network structure is strongly temporally-scale dependent. This general pattern arises because the temporal scale determines the degree to which temporal dynamics (i.e. phenological turnover of species and links) are included in the network, in addition to how much sampling effort is put into constructing the network. Ultimately, the temporal scale-dependence of our plant–pollinator networks appears to be mostly driven by species richness, which increases with sampling effort, and species turnover, which increases with temporal extent. In other words, after accounting for variation in species richness, network structure is increasingly shaped by its underlying temporal dynamics. Our results suggest that considering multiple temporal scales may be necessary to fully appreciate the causes and consequences of interaction network structure. Fil: Schwarz, Benjamin. Albert Ludwigs University of Freiburg; Alemania Fil: Vazquez, Diego P.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; Argentina Fil: Cara Donna, Paul J.. Chicago Botanic Garden; Estados Unidos Fil: Knight, Tiffany M.. German Centre for Integrative Biodiversity Research; Alemania Fil: Benadi, Gita. Albert Ludwigs University of Freiburg; Alemania Fil: Dormann, Carsten F.. Albert Ludwigs University of Freiburg; Alemania Fil: Gauzens, Benoit. German Centre for Integrative Biodiversity Research; Alemania Fil: Motivans, Elena. German Centre for Integrative Biodiversity Research; Alemania Fil: Resasco, Julian. University of Colorado; Estados Unidos Fil: Blüthgen, Nico. Universitat Technische Darmstadt; Alemania Fil: Burkle, Laura A.. Montana State University; Alemania Fil: Fang, Qiang. Henan University of Science and Technology; China Fil: Kaiser Bunbury, Christopher N.. University of Exeter; Reino Unido Fil: Alarcón, Ruben. California State University; Estados Unidos Fil: Bain, Justin A.. Chicago Botanic Garden; Estados Unidos Fil: Chacoff, Natacha Paola. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina Fil: Huang, Shuang Quan. Central China Normal University; China Fil: LeBuhn, Gretchen. San Francisco State University; Estados Unidos Fil: MacLeod, Molly. Rutgers University; Estados Unidos Fil: Petanidou, Theodora. Univversity of the Aegean; Estados Unidos Fil: Rasmussen, Claus. University Aarhus; Dinamarca Fil: Simanonok, Michael P.. Montana State University; Estados Unidos Fil: Thompson, Amibeth H.. German Centre for Integrative Biodiversity Research; Alemania Fil: Fründ, Jochen. Albert Ludwigs University of Freiburg; Alemania

Recent studies have shown that the diversity of flowering plants can enhance pollinator richness and visitation frequency and thereby increase the resilience of pollination. It is assumed that flower traits explain these effects, but it is still unclear which flower traits are responsible, and knowing that, if pollinator richness and visitation frequency are more driven by mass-ratio effects (mean trait values) or by trait diversity. Here, we analyse a three-year data set of pollinator observations collected in a European grassland plant diversity experiment (The Jena experiment). The data entail comprehensive flower trait measurements, including reward traits (nectar and pollen amount), morphological traits (height, symmetry, area, colour spectra) and chemical traits (nectar-amino acid and nectar-sugar concentration). We test if pollinator species richness and visitation frequency of flower communities depend on overall functional diversity combining all flower traits within a community, single trait diversities (within trait variation) and community-weighted means of the single traits, using Bayesian inference. Overall functional diversity did not affect pollinator species richness, but reduced visitation frequency. When looking at individual flower traits separately, we found that single trait diversity of flower reflectance and flower morphology were important predictors of pollinator visitation frequency. Moreover, independent of total flower abundance, community-weighted means of flower height, area, reflectance, nectar-sugar concentration and nectar-amino acid concentration strongly affected both pollinator species richness and visitation frequency. Our results, challenge the idea that functional diversity always positively affects ecosystem functions. Nonetheless, we demonstrate that both single trait diversity and mass-ratio effects of flower traits play an important role for diverse and frequent flower visits, which underlines the functionality of flower traits for pollination services.