Plant biodiversity assessment through pollen DNA metabarcoding in Natura 2000 habitats (Italian Alps).

Monitoring biodiversity is of increasing importance in natural ecosystems. Metabarcoding can be used as a powerful molecular tool to complement traditional biodiversity monitoring, as total environmental DNA can be analyzed from complex samples containing DNA of different origin. The aim of this research was to demonstrate the potential of pollen DNA metabarcoding using the chloroplast trnL partial gene sequencing to characterize plant biodiversity. Collecting airborne biological particles with gravimetric Tauber traps in four Natura 2000 habitats within the Natural Park of Paneveggio Pale di San Martino (Italian Alps), at three-time intervals in 1 year, metabarcoding identified 68 taxa belonging to 32 local plant families. Metabarcoding could identify with finer taxonomic resolution almost all non-rare families found by conventional light microscopy concurrently applied. However, compared to microscopy quantitative results, Poaceae, Betulaceae, and Oleaceae were found to contribute to a lesser extent to the plant biodiversity and Pinaceae were more represented. Temporal changes detected by metabarcoding matched the features of each pollen season, as defined by aerobiological studies running in parallel, and spatial heterogeneity was revealed between sites. Our results showcase that pollen metabarcoding is a promising approach in detecting plant species composition which could provide support to continuous monitoring required in Natura 2000 habitats for biodiversity conservation.

A DNA barcoding approach to characterize pollen collected by honeybees.

In the present study, we investigated DNA barcoding effectiveness to characterize honeybee pollen pellets, a food supplement largely used for human nutrition due to its therapeutic properties. We collected pollen pellets using modified beehives placed in three zones within an alpine protected area (Grigna Settentrionale Regional Park, Italy). A DNA barcoding reference database, including rbcL and trnH-psbA sequences from 693 plant species (104 sequenced in this study) was assembled. The database was used to identify pollen collected from the hives. Fifty-two plant species were identified at the molecular level. Results suggested rbcL alone could not distinguish among congeneric plants; however, psbA-trnH identified most of the pollen samples at the species level. Substantial variability in pollen composition was observed between the highest elevation locality (Alpe Moconodeno), characterized by arid grasslands and a rocky substrate, and the other two sites (Cornisella and Ortanella) at lower altitudes. Pollen from Ortanella and Cornisella showed the presence of typical deciduous forest species; however in samples collected at Ortanella, pollen of the invasive Lonicera japonica, and the ornamental Pelargonium x hortorum were observed. Our results indicated pollen composition was largely influenced by floristic local biodiversity, plant phenology, and the presence of alien flowering species. Therefore, pollen molecular characterization based on DNA barcoding might serve useful to beekeepers in obtaining honeybee products with specific nutritional or therapeutic characteristics desired by food market demands.