Project description:Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R<sup>2</sup> = 0.821) than for trnL (R<sup>2</sup> = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trnL or microscopic investigation (Alnus × spaethii, Cupressus arizonica, Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trnL. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.
Project description:Genetic analysis of airborne plant material has historically focused (generally implicitly rather than as a stated goal) on pollen from anemophilous (wind-pollinated) species, such as in multiple studies examining the relationship of allergens to human health. Inspired by the recent influx of literature applying environmental DNA (eDNA) approaches to targeted-species and whole-ecosystem study, we conducted a proof-of-concept experiment to determine whether airborne samples reliably detect genetic material from non-anemophilous species that may not be releasing large plumes of pollen. We collected airborne eDNA using Big Spring Number Eight dust traps and quantified the amount of eDNA present for a flowering wind-pollinated genus (Bouteloua) and insect-pollinated honey mesquite (Prosopis glandulosa) that was not flowering at the time of the study. We were able to detect airborne eDNA from both species. Since honey mesquite is insect-pollinated and was not flowering during the time of this study, our results confirm that airborne eDNA consists of and can detect species through more than just pollen. Additionally, we were able to detect temporal patterns reflecting Bouteloua reproductive ecology and suggest that airborne honey mesquite eDNA responded to weather conditions during our study. These findings suggest a need for more study of the ecology of airborne eDNA to uncover its potential for single-species and whole-community research and management in terrestrial ecosystems.
Project description: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.
Project description:Airborne pollen causes various types of allergies in humans, and the extent of allergic infection is related to the presence of different types of sporo–pollen and existing meteorological conditions in a certain area. Therefore, an aeropalynological study of 72 airborne samples with a hydrofluoric acid (HF) treatment was conducted in the Haizhu district of Guangzhou, China, in 2016, to identify the temporal variations in airborne sporo–pollen and the relationship between airborne sporo–pollen concentrations and different meteorological variables in Guangzhou, China. Forty-five types of airborne pollen, seven types of airborne spores, and some undetermined sporo–pollen taxa were identified with two separate plant habitats occurring during this period (from January to December 2016): arboreal pollen (tree-based) and non-arboreal pollen (herb, shrub, aquatic, liane, etc.). Furthermore, the daily records of four key meteorological variables (temperature, precipitation, relative humidity, and wind speed) were acquired to distinguish the pollen seasons and correlated with Spearman's rho test to establish a pollen-weather data book with the seasonal variations. The two leading seasons were identified based on pollen abundance: spring and autumn. Among them, the primary dominant sporo–pollen families during the spring season were Poaceae, Pinaceae, Euphorbiaceae, Moraceae, Microlepia sp., and Polypodiaceae. Conversely, Artemisia sp., Asteraceae, Cyperaceae, Poaceae, Alnus sp., Corylus sp., Myrtaceae, and Rosaceae were the dominant pollen species during autumn. However, few pollen grains were identified in January, May–July, and December. The statistical analysis revealed that temperature had both positive and negative correlations with sporo–pollen concentrations. However, precipitation and relative humidity had a strong impact on the sporo–pollen dispersion and exhibited a negative correlation with the sporo–pollen concentrations. The wind speed had a positive but strong correlation with the sporo–pollen concentration during the study period. Some inconsistent results were found due to environmental variations, vegetation type, and climate change around the study area. This study will facilitate the identification of pollen seasons to prevent the occurrence of pollen-related allergies in the Guangzhou city area. Aeropalynology, seasonal variation, climate, bioaerosol, airborne pollen and spore concentration.