Dew point temperature affects ascospore release of allergenic genus Leptosphaeria

Abstract

The genus Leptosphaeria contains numerous fungi that cause the symptoms of asthma and also parasitize wild and crop plants. In search of a robust and universal forecast model, the ascospore concentration in air was measured and weather data recorded from 1 March to 31 October between 2006 and 2012. The experiment was conducted in three European countries of the temperate climate, i.e., Ukraine, Poland, and the UK. Out of over 150 forecast models produced using artificial neural networks (ANNs) and multivariate regression trees (MRTs), we selected the best model for each site, as well as for joint two-site combinations. The performance of all computed models was tested against records from 1 year which had not been used for model construction. The statistical analysis of the fungal spore data was supported by a comprehensive study of both climate and land cover within a 30-km radius from the air sampler location. High-performance forecasting models were obtained for individual sites, showing that the local micro-climate plays a decisive role in biology of the fungi. Based on the previous epidemiological studies, we hypothesized that dew point temperature (DPT) would be a critical factor in the models. The impact of DPT was confirmed only by one of the final best neural models, but the MRT analyses, similarly to the Spearman’s rank test, indicated the importance of DPT in all but one of the studied cases and in half of them ranked it as a fundamental factor. This work applies artificial neural modeling to predict the Leptosphaeria airborne spore concentration in urban areas for the first time.Electronic supplementary materialThe online version of this article (10.1007/s00484-018-1500-z) contains supplementary material, which is available to authorized users.

Aerosol measurement methods to quantify spore emissions from fungi and cryptogamic covers in the Amazon

“…The highest numbers of basidiospores were emitted under naturally moist and artificially moistened conditions at water contents of the fungal fruiting body ranging between 244 10 and 169 %. Thus, the water content seems to play a relevant role in the spore emission process, which is in close agreement with other reports (Ehlert et al, 2017;Ingold, 1985;Sadyś et al, 2018) and with the fact that water condensation is essential for the active discharge of basidiospores. However, for this technique the fruiting bodies are mostly separated from their vegetative mycelium in the substrate (dead wood) that provides water, minerals, and nutrients for the fruiting body.…”

Aerosol measurement methods to quantify spore emissions from fungi and cryptogamic covers in the Amazon

“…The highest numbers of basidiospores were emitted under naturally moist and artificially moistened conditions at water contents of the fungal fruiting body ranging from 244 % to 169 %. Thus, the water content seems to play a relevant role in the spore emission process, which is in close agreement with other reports (Ehlert et al, 2017;Ingold, 1985;Sadyś et al, 2018) and with the fact that wa-ter condensation is essential for the active discharge of basidiospores. However, for this technique the fruiting bodies are mostly separated from their vegetative mycelium in the substrate (dead wood) that provides water, minerals, and nutrients for the fruiting body.…”

“…The majority of these studies focuses on the aerosol or spore concentration in the atmosphere. However, the emission patterns of the source organisms, i.e., the spore release characteristics depending on climatic conditions and the physiological activity status, might also be relevant to explain the atmospheric concentrations (Šantl-Temkiv et al, 2019). To fill that gap, a setup focused on the aerosol release patterns and mechanisms of the organisms could generate new insights into the relevance of local bioaerosol emissions.…”

Airborne Fungal Spore Review, New Advances and Automatisation

“…The effects and correlation of various meteorological conditions on spore release has been covered well in numerous studies [17,109,[113][114][115][116][117][118]. The complex relationship between the ambient fungal spore concentrations and meteorological parameters is often examined using statistical tests, such as correlation analysis and ordination techniques.…”

“…The application of ANNs have been used extensively in the literature to successfully model a range of fungal spore types, including allergenic spores such as Ganoderma [115,[145][146][147], Alternaria [44,[148][149][150][151][152][153] and Cladosporium [151][152][153], amongst others [126]. The use of ANNs has also been used to predict phytopathogenic spores, such as Pleospora [149,153,154], Leptosphaeria [118] and Pyricularia [155]. Many of these particular studies have highlighted the dual aspect of fungal spore prediction models with regards to alerting the public to both periods of potential allergenic and crop-infection risk.…”