Given the ongoing decline of both pollinators and plants, it is crucial to implement effective methods to describe complex pollination networks across time and space in a comprehensive and high-throughput way. Here we tested if metabarcoding may circumvent the limits of conventional methodologies in detecting and quantifying plant-pollinator interactions. Metabarcoding experiments on pollen DNA mixtures described a positive relationship between the amounts of DNA from focal species and the number of trnL and ITS1 sequences yielded. The study of pollen loads of insects captured in plant communities revealed that as compared to the observation of visits, metabarcoding revealed 2.5 times more plant species involved in plant-pollinator interactions. We further observed a tight positive relationship between the pollen-carrying capacities of insect taxa and the number of trnL and ITS1 sequences. The number of visits received per plant species also positively correlated to the number of their ITS1 and trnL sequences in insect pollen loads. By revealing interactions hard to observe otherwise, metabarcoding significantly enlarges the spatiotemporal observation window of pollination interactions. By providing new qualitative and quantitative information, metabarcoding holds great promise for investigating diverse facets of interactions and will provide a new perception of pollination networks as a whole.

Animal pollination, essential for both ecological services and ecosystem functioning, is threatened by ongoing global changes. New methodologies to decipher their effects on pollinator composition to ecosystem health are urgently required. We compare the main structural parameters of pollination networks based on DNA metabarcoding data with networks based on direct observations of insect visits to plants at three resolution levels. By detecting numerous additional hidden interactions, metabarcoding data largely alters the properties of the pollination networks compared to visit surveys. Molecular data shows that pollinators are much more generalist than expected from visit surveys. However, pollinator species were composed of relatively specialized individuals and formed functional groups highly specialized upon floral morphs. We discuss pros and cons of metabarcoding data relative to data obtained from traditional methods and their potential contribution to both current and future research. This molecular method seems a very promising avenue to address many outstanding scientific issues at a resolution level which remains unattained to date; especially for those studies requiring pollinator and plant community investigations over macro-ecological scales.