RESUMEN
BACKGROUND: Grasses populate most biogeographical zones, and their diversity influences allergic sensitisation to pollen. Previously, the contribution of different Poaceae subfamilies to airborne pollen has mostly been inferred from historical herbarium records. We recently applied environmental (e)DNA metabarcoding at one subtropical site revealing that successive airborne grass pollen peaks were derived from repeated flowering of Chloridoid and Panicoid grasses over a season. This study aimed to compare spatiotemporal patterns in grass pollen exposure across seasons and climate zones. METHODS: Airborne pollen concentrations across two austral pollen seasons spanning 2017-2019 at subtropical (Mutdapilly and Rocklea, Queensland) and temperate (Macquarie Park and Richmond, New South Wales) sites, were determined with a routine volumetric impaction sampler and counting by light microscopy. Poaceae rbcL metabarcode sequences amplified from daily pollen samples collected once per week were assigned to subfamily and genus using a ribosomal classifier and compared with Atlas of Living Australia sighting records. RESULTS: eDNA analysis revealed distinct dominance patterns of grass pollen at various sites: Panicoid grasses prevailed in both subtropical Mutdapilly and temperate Macquarie Park, whilst Chloridoid grasses dominated the subtropical Rocklea site. Overall, subtropical sites showed significantly higher proportion of pollen from Chloridoid grasses than temperate sites, whereas the temperate sites showed a significantly higher proportion of pollen from Pooideae grasses than subtropical sites. Timing of airborne Pooid (spring), Panicoid and Chloridoid (late spring to autumn), and Arundinoid (autumn) pollen were significantly related to number of days from mid-winter. Proportions of eDNA for subfamilies correlated with distributions grass sighting records between climate zones. CONCLUSIONS: eDNA analysis enabled finer taxonomic discernment of Poaceae pollen records across seasons and climate zones with implications for understanding adaptation of grasslands to climate change, and the complexity of pollen exposure for patients with allergic respiratory diseases.