Comparisons of Fungal Spore Distributions Using Air Sampling at Worcester, England (2006-2010)

This study determined annual and monthly fluctuations in concentration of 20 fungal genera. The selection of taxa was made based upon their high frequency in the air as well as their well-known allergenic properties. Air samples were collected using a spore trap of Hirst design at an urban site where the trap continuously worked throughout a 5-year survey. Weather data were acquired from a meteorological station co-located with the air sampler. Influence of several meteorological parameters was then examined to reveal species–environment interactions and the potential location of fungal spore sources within the urban area. The maximum monthly sum of mean daily spore concentration varied between genera, and the earliest peaks were recorded for Pleospora sp. in April and Ustilago sp. in June. However, the majority of investigated spore types occurred in the greatest concentrations between August and September. Out of the 20 studied taxa, the most dominant genus was Cladosporium sp., which exceeded an allergenic threshold of 3000 s m-3 40 times during very rainy years and twice as much during dry years. A Spearman’s rank test showed that statistically significant (p B 0.05) relationships between spore concentration and weather parameters were mainly rs B 0.50. Potential sources of spores at Worcester were likely to be localised outside the city area.

Modelling Atmospheric Concentrations of Ragweed Pollen From Local and Distant Sources

Pollen grains from the genus ragweed (Ambrosia spp.) are important aeroallergens. In Europe, the largest sources of atmospheric ragweed pollen are the Rhône Valley (France), parts of Northern Italy, the Pannonian Plain and Ukraine. Episodes of Long Distance Transport (LDT) of ragweed pollen from these centres can cover large parts of Europe and are predominantly studied using receptor based models (Smith et al., (2013) and references therein). The clinical impact of allergenic ragweed pollen arriving from distant sources remains unclear (Cecchi et al. 2010). Although a recent study has found the major allergens of ragweed in air samples collected in Poznań, Poland, during episodes of long-distance transport from the Pannonian Plain (Grewling et al. 2013). The source orientated models SILAM, DEHM, COSMO-Art, METRAS and ENVIRO-HIRLAM currently report having the capability of modelling atmospheric concentrations of pollen in Europe. The performance of such source-orientated models is strongly dependent on the quality of the emissions data, which is a focus of current research (e.g. Thibaudon et al. (2014)). The output from these models are important for warning allergy sufferers in areas polluted by ragweed, but could also be used to warn the public of ragweed pollen being transported into areas where the plant is not abundant. Areas outside of the main areas of ragweed infection that contain considerable local populations must, however, also include local scale models. These models can be used to predict local concentrations, even when LDT is not present. This concept of combined LDT and local scale calculations has been shown to be work for air pollutants and is considered usable for urban scale calculations of aeroallergens once urban scale maps of aeroallergen sources have been produced.

Determination of Alternaria spp. Habitats Using 7-Day Volumetric Spore Trap, Hybrid Single Particle Lagrangian Integrated Trajectory Model and Geographic Information System

There are many species among the Alternaria genus, which hosts on economically important crops causing significant yield losses. Less attention has been paid to fungi hosting on plants constituting substantial components of pastures and meadows. Alternaria spp. spores are also recognised as important allergens. A 7-day volumetric spore trap was used to monitor the concentration of airborne fungal spores. Air samples were collected in Worcester, England (2006–2010). Days with a high spore count were then selected. The longest episode that occurred within a five year study was chosen for modelling. Two source maps presenting distribution of crops under rotation and pastures in the UK were produced. Back trajectories were calculated using the HYSPLIT model. In ArcGIS clusters of trajectories were studied in connection with source maps by including the height above ground level and the speed of the air masses. During the episode no evidence for a long distance transport from the continent of Alternaria spp. spores was detected. The overall direction of the air masses fell within the range from South-West to North. The back trajectories indicated that the most important sources of Alternaria spp. spores were located in the West Midlands of England.

Field Evaluation of a Competitive Lateral-flow Assay for Detection of Alternaria brassicae in Vegetable Brassica Crops

On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.