Our understanding of the ecological and evolutionary consequences of plant-pollinator interactions has often relied on the study of interactions between species pairs despite that these take place within multi-species communities. The use of network theory to study complex multi-species interactions has allowed novel insights into the structure of plant-pollinator communities. However, network studies have relied on floral visitation data, although, this may be insufficient to fully characterize the diversity and strength of plant-pollinator interactions. By using pollen transport data (i.e. pollen on pollinators), new insights can be gained on the structure and function of plant-pollinator communities. Yet studies that characterize and compare pollen-transport with floral-visitation networks are scarce. Furthermore, the strength and frequency of plant-pollinator interactions can vary across temporal scales. In spite of this, within-season (monthly variation) and within-day (morning vs. evening) variation in plant-pollinator network structure has been little studied. This fine-scale temporal variation can be important in structuring plant-pollinator interactions. By evaluating variation in network structure across these biologically relevant time scales we will gain a better understanding of the factors that shape plant-pollinator communities. Here, we build plant-pollinator interactions networks based on floral visitation and pollen transport data by observing, collecting and sampling pollen from floral visitors across replicated transects in a southern Appalachian floral community within an entire flowering season. We aim to 1) compare the congruence of plant-pollinator networks built on floral visitation and pollen transport data and 2) evaluate within season and within-day variation in plant-pollinator network structure.
Results/Conclusions
Preliminary results show that the structure of floral visitation and pollen transport networks are significantly different from each other (P <0.01; Procrustes analysis with 999 permutations). For instance, pollen-transport network size is almost four times larger (496 links) compared to the floral-visitation network (109 links). Species in the pollen transport network tend to be more connected (connectance = 2.3) and have five times more links per species on average (5.22 links) than floral visitation networks (connectance = 1.1, links = 1.8). Within-season and within-day differences in network structure are currently being evaluated. Our results so far show that pollen transport networks at our study site captured 78% more unique interactions and thus provide a more accurate representation of network structure. Differences in the interpretation of pollen transfer versus floral visitation networks can have important implications for our understanding of community-level functions such as their resilience and stability.