Impacts of earlier spring snowmelt on plant-pollinator interactions using a pollen metabarcoding approach

Many alpine environments have experienced earlier spring snowmelt with increased global temperatures and reduced snowpacks. Plant and pollinator species are likely to respond differently to this environmental change, leading to potential shifts in community composition and patterns of interactions. To understand the implications of these environmental changes, we conducted a snowmelt acceleration experiment across several sites in the Rocky Mountains and measured the impacts to plant-pollinator interactions through observations and DNA metabarcoding of insect pollen loads from collected specimens. Pollen DNA metabarcoding allows us to identify the plant species present in an insect’s pollen load and provides information on the flowers visited by that individual during foraging. We used both the observed interactions and data from pollen metabarcoding to create networks of plant-pollinator interactions under control and accelerated snowmelt conditions. Preliminary results show changes in plant-pollinator network structure, including specialization and connectance, in the communities where snowmelt timing was accelerated. We also found differences in the networks created using observational data compared to those using pollen metabarcoding data, underscoring the importance of this method for understanding community-level interactions. By examining changes in network structure through the experimental manipulation of snowmelt timing, we are better able to understand how future plant and insect pollinator populations may persist and interact with one another as climates continue to shift.