1. Habitat fragmentation can affect pollinator and plant population structure in terms of species composition, abundance, area covered and density of flowering plants. This, in turn, may affect pollinator visitation frequency, pollen deposition, seed set and plant fitness.
2. A reduction in the quantity of flower visits can be coupled with a reduction in the quality of pollination service and hence the plants’ overall reproductive success and long-term survival. Understanding the relationship be
tween plant population size and/or isolation and pollination limitation is of fundamental importance for plant conservation.
3. We examined flower visitation and seed set of 10 different plant species from five European countries to investigate the general effects of plant populations size and density, both within (patch level) and between populations (population level), on seed set and pollination limitation.
4. We found evidence that the effects of area and density of flowering plant assemblages were generally more pronounced at the patch level than at the population level. We also found that patch and population level together influenced flower visitation and seed set, and the latter increased with increasing patch area and density, but this effect was only apparent in small populations.
5. Synthesis. By using an extensive pan-European data set on flower visitation and seed set we have identified a general pattern in the interplay between the attractiveness of flowering plant patches for pollinators and density dependence of flower visitation, and also a strong plant species-specific response to habitat fragmentation effects. This can guide efforts to conserve plant–pollinator interactions, ecosystem functioning and plant fitness in fragmented habitats.
Pollination Ecology is a dynamic field of scientific research constantly adopting novel methods and making progress in understanding the interactions between plants and their pollinators. A recent paper listed the main scientific questions in this field focussing on the ecological and biological system itself. Here, we follow up on that paper and present some ideas on how to broaden our perspective and explore the role that pollination research can play in answering both ecological and societal
questions relevant to a range of different stakeholders. We hope this paper may be useful to researchers aiming at improving both the scientific and societal impact of their research.
In this paper, we develop a method, termed the Interaction Distribution (ID) method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference
of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2), qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.
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.