Identification of the species origin of pollen has many applications, including assessment of plant–pollinator networks, reconstruction of ancient plant communities, product authentication, allergen monitoring, and forensics. Such applications, however, have previously been limited by microscopy-based identification of pollen, which is slow, has low taxonomic resolution, and has few expert practitioners. One alternative is pollen DNA barcoding, which could overcome these issues. Recent studies demonstrate that both chloroplast and nuclear barcoding markers can be amplified from pollen. These recent validations of pollen metabarcoding indicate that now is the time for researchers in various fields to consider applying these methods to their research programs. In this paper, we review the nascent field of pollen DNA barcoding and discuss potential new applications of this technology, highlighting existing limitations and future research developments that will improve its utility in a wide range of applications.

Acacia s.l. farnesiana , which originates from Mesoamerica, is the most widely distributed Acacia s.l. species across the tropics. It is assumed that the plant was transferred across the Atlantic to southern Europe by Spanish explorers, and then spread across the Old World tropics through a combination of chance long-distance and human-mediated dispersal. Our study uses genetic analysis and information from historical sources to test the relative roles of chance and human-mediated dispersal in its distribution. The results confirm the Mesoamerican origins of the plant and show three patterns of human-mediated dispersal. Samples from Spain showed greater genetic diversity than those from other Old World tropics, suggesting more instances of transatlantic introductions from the Americas to that country than to other parts of Africa and Asia. Individuals from the Philippines matched a population from South Central Mexico and were likely to have been direct, trans-Pacific introductions. Australian samples were genetically unique, indicating that the arrival of the species in the continent was independent of these European colonial activities. This suggests the possibility of pre-European human-mediated dispersal across the Pacific Ocean. These significant findings raise new questions for biogeographic studies that assume chance or transoceanic dispersal for disjunct plant distributions.

Premise of the study: To study pollination networks in a changing environment, we need accurate, high‐throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer‐scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks.Methods: We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases.Results: We successfully built a proof‐of‐concept quantitative pollination network using pollen metabarcoding.Discussion: Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant–pollinator interactions.

Premise of the study: DNA metabarcoding has broad‐ranging applications in ecology, aerobiology, biosecurity, and forensics. A bioinformatics pipeline has recently been published for identification using a comprehensive database of ITS2, one of the common plant DNA barcoding markers. There is, however, no corresponding database for rbcL, the other primary marker used in plants.Methods: Using publicly available data, we compiled a reference library of rbcL sequences and trained databases for use with UTAX and RDP classifier algorithms. We used this reference library, along with the existing bioinformatics pipeline and ITS2 reference library, to identify species in an artificial mixture of nine species of pollen. We have made this database publicly available in multiple formats, to allow use with multiple bioinformatics pipelines, now and in the future.Results: Using the rbcL database, in addition to the ITS2 database, we succeeded in making species‐level identifications for eight species and a family‐level identification of the ninth species. This is an improvement on ITS2 sequence alone.Discussion: The reference library described here will assist with identification of plant species using rbcL. By making another gene region available for standard barcoding, this will increase the resolution and accuracy of identifications.