Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.

Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

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.

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, communityweighted 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.

Summary 1.One of the most noticeable effects of anthropogenic climate change is the shift in timing of seasonal events towards earlier occurrence. The high degree of variation in species' phenological shifts has raised concerns about the temporal decoupling of interspecific interactions, but the extent and implications of this effect are largely unknown. In the case of plant-pollinator systems, more specialized species are predicted to be particularly threatened by phenological decoupling, since they are assumed to be less flexible in the choice of interaction partners, but until now this hypothesis has not been tested. 2. In this paper, we studied phenology and interactions of plant and pollinator communities along an altitudinal gradient in the Alps as a model for the possible effects of climate change in time. 3. Our results show that even relatively specialized pollinators were much more flexible in their use of plant species as floral resources than their local flower visitation suggested. We found no relationship between local specialization of pollinators and the consistency of their visitation patterns across sites, and also no relationship between specialization and phenological synchrony of pollinators with particular plants. 4. Thus, in contrast to the conclusions of a recent simulation study, our results suggest that most pollinator species included in this study are not threatened by phenological decoupling from specific flowering plants. However, the flexibility of many rarely observed pollinator species remains unknown. Moreover, our results suggest that specialized flower visitors select plant species based on certain floral traits such as the length of the nectar holder tube. If that is the case, the observed flexibility of plant-pollinator interactions likely depends on a high degree of functional redundancy in the plant community, which may not exist in less diverse systems.