Resumen:
Fungi are an important component of ecosystems. Some fungi are widely distributed, while others are limited to certain habitats. Studies based on airborne fungal spores can help to know the geographical distribution of fungi in the territory. Our aim was to show that a gamma probability density function (gpdf) based on a database of 20 airborne fungal spore taxa concentrations in eight localities of Catalonia (NE Spain) for a period of 20 years was a useful tool to map the distribution of these taxa in this region, as well as to establish a general classification on their sporulation through the alpha parameter of the validated model. This allows a more efficient study of the atmospheric dynamics of the different taxa, since the number of taxa is reduced to a representative taxon for each of the categories of the generic classification. In general, the results obtained confirmed that the scale parameter of the gamma distribution changes from year to year, depending on the meteorological conditions, while the shape parameter remains fairly stable. At the temporal scale, airborne fungal spores of Agrocybe sp. showed the highest stability; at the spatial scale, Cladosporium sp. showed the highest stability. Regarding localities, Girona was the station with greater interannual variation, while Barcelona and Vielha showed the lowest. In addition, the results obtained allowed a non-subjective classification of these taxa in five groups, based on the gamma (shape) parameter. The taxa Alternaria sp., Cladosporium sp., Ganoderma sp., Pleospora sp., Leptosphaeria sp., Aspergillus sp.-Penicillium sp. were cosmopolitan and showed a similar behavior across the whole study area, with any of them possible candidates for used in predictive models; airborne fungal spores of Agrocybe sp., Arthrinium sp., Epicoccum sp., Drechslera sp.-Helminthosporium sp., Pithomyces sp., Thelephoraceae, Stemphylium sp., Xylariaceae can be used as meteorological indicators and Agaricus sp., Coprinaceae sp., Torula sp. can be used as indicators of anthropogenic activities. The results obtained could be used to reduce the number of spore taxa analyzed and subsequently develop generic predictive models.
