The effects of meteorological factors on the occurrence of Ganoderma sp. spores in the air

A systematic review of outdoor airborne fungal spore seasonality across Europe and the implications for health

Fungal spores make up a significant proportion of organic matter within the air. Allergic sensitisation to fungi is associated with conditions including allergic fungal airway disease. This systematic review analyses outdoor fungal spore seasonality across Europe and considers the implications for health. Seventy-four studies met the inclusion criteria, the majority of which (n = 64) were observational sampling studies published between 1978 and 2020. The most commonly reported genera were the known allergens Alternaria and Cladosporium, measured in 52 and 49 studies, respectively. Both displayed statistically significant increased season length in south-westerly (Mediterranean) versus north-easterly (Atlantic and Continental) regions. Although there was a trend for reduced peak or annual Alternaria and Cladosporium spore concentrations in more northernly locations, this was not statistically significant. Peak spore concentrations of Alternaria and Cladosporium exceeded clinical thresholds in nearly all locations, with median peak concentrations of 665 and 18,827 per m³, respectively. Meteorological variables, predominantly temperature, precipitation and relative humidity, were the main factors associated with fungal seasonality. Land-use was identified as another important factor, particularly proximity to agricultural and coastal areas. While correlations of increased season length or decreased annual spore concentrations with increasing average temperatures were reported in multi-decade sampling studies, the number of such studies was too small to make any definitive conclusions. Further, up-to-date studies covering underrepresented geographical regions and fungal taxa (including the use of modern molecular techniques), and the impact of land-use and climate change will help address remaining knowledge gaps. Such knowledge will help to better understand fungal allergy, develop improved fungal spore calendars and forecasts with greater geographical coverage, and promote increased awareness and management strategies for those with allergic fungal disease.

Airborne Fungal Spore Review, New Advances and Automatisation

Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the public, the factors affecting their growth/dispersal, and different methods of predicting fungal spore concentrations currently in use.

Aerobiological modeling I: A review of predictive models

The present work is the first of two reviews on applied modeling in the field of aerobiology. The aerobiological predictive models for pollen and fungal spores, usually defined as predictive statistical models, will, amongst other objectives, forecast airborne particles' concentration or dynamical behavior of the particles. These models can be classified into Observation Based Models (OBM), Phenological Based Models (PHM), or OTher Models (OTM). The aim of this review is to show, analyze and discuss the different predictive models used in pollen and spore aerobiological studies. The analysis was performed on published electronic scientific articles from 1998 to 2016 related to the type of model, the taxa and the modelled parameters. From a total of 503 studies, 55.5% used OBM (44.8% on pollen and 10.7% on fungal spores), 38.5% PHM (all on pollen) and 6% OTM (5.4% on pollen and 0.6% on fungal spores). OBM have been used with high frequency to forecast concentration. The most frequent model of OBM was linear regression (18.5% out of 503) on pollen and artificial neural networks (4.6%) on fungal spores. In the PHM, the principal use was to characterize the main pollen season (flowering season) based on the model of growth degree days. Finally, OTM have been used to estimate concentrations at unmonitored areas. Olea (14,5%) on pollen and Alternaria (4,8%) on fungal spores were the taxa most frequently modelled. Daily concentration was the most modelled parameter by OBM (25.2%) and season start day by PHM (35.6%). The PHM approaches include greater model diversity and use fewer independent variables than OBM. In addition, PHM show to be easier to apply than OBM; however, the wide range of criteria to define the parameters to use in PHM (e.g.: pollination start day) makes that each model is used with a lesser frequency than other models.

Abundance of Ganoderma sp. in Europe and SW Asia: modelling the pathogen infection levels in local trees using the proxy of airborne fungal spore concentrations

Ganoderma comprises a common bracket fungal genus that causes basal stem rot in deciduous and coniferous trees and palms, thus having a large economic impact on forestry production. We estimated pathogen abundance using long-term, daily spore concentration data collected in five biogeographic regions in Europe and SW Asia. We hypothesized that pathogen abundance in the air depends on the density of potential hosts (trees) in the surrounding area, and that its spores originate locally. We tested this hypothesis by (1) calculating tree cover density, (2) assessing the impact of local meteorological variables on spore concentration, (3) computing back trajectories, (4) developing random forest models predicting daily spore concentration. The area covered by trees was calculated based on Tree Density Datasets within a 30 km radius from sampling sites. Variations in daily and seasonal spore concentrations were cross-examined between sites using a selection of statistical tools including HYSPLIT and random forest models. Our results showed that spore concentrations were higher in Northern and Central Europe than in South Europe and SW Asia. High and unusually high spore concentrations (> 90th and > 98th percentile, respectively) were partially associated with long distance transported spores: at least 33% of Ganoderma spores recorded in Madeira during days with high concentrations originated from the Iberian Peninsula located >900 km away. Random forest models developed on local meteorological data performed better in sites where the contribution of long distance transported spores was lower. We found that high concentrations were recorded in sites with low host density (Leicester, Worcester), and low concentrations in Kastamonu with high host density. This suggests that south European and SW Asian forests may be less severely affected by Ganoderma. This study highlights the effectiveness of monitoring airborne Ganoderma spore concentrations as a tool for assessing local Ganoderma pathogen infection levels.

Assessing Performance of Spore Samplers in Monitoring Aeromycobiota and Fungal Plant Pathogen Diversity in Canada

Spore samplers are widely used in pathogen surveillance but not so much for monitoring the composition of aeromycobiota. In Canada, a nationwide spore-sampling network (AeroNet) was established as a pilot project to assess fungal community composition in air and rain samples collected using three different spore samplers in the summers of 2010 and 2011. Metabarcodes of the internal transcribed spacer (ITS) were exhaustively characterized for three of the network sites, in British Columbia (BC), Québec (QC), and Prince Edward Island (PEI), to compare performance of the samplers. Sampler type accounted for ca. 20% of the total explainable variance in aeromycobiota compositional heterogeneity, with air samplers recovering more Ascomycota and rain samplers recovering more Basidiomycota. Spore samplers showed different abilities to collect 27 fungal genera that are plant pathogens. For instance, Cladosporium spp., Drechslera spp., and Entyloma spp. were collected mainly by air samplers, while Fusarium spp., Microdochium spp., and Ustilago spp. were recovered more frequently with rain samplers. The diversity and abundance of some fungi were significantly affected by sampling location and time (e.g., Alternaria and Bipolaris) and weather conditions (e.g., Mycocentrospora and Leptosphaeria), and depended on using ITS1 or ITS2 as the barcoding region (e.g., Epicoccum and Botrytis). The observation that Canada's aeromycobiota diversity correlates with cooler, wetter conditions and northward wind requires support from more long-term data sets. Our vision of the AeroNet network, combined with high-throughput sequencing (HTS) and well-designed sampling strategies, may contribute significantly to a national biovigilance network for protecting plants of agricultural and economic importance in Canada.IMPORTANCE The current study compared the performance of spore samplers for collecting broad-spectrum air- and rain-borne fungal pathogens using a metabarcoding approach. The results provided a thorough characterization of the aeromycobiota in the coastal regions of Canada in relation to the influence of climatic factors. This study lays the methodological basis to eventually develop knowledge-based guidance on pest surveillance by assisting in the selection of appropriate spore samplers.

A review on airborne microorganisms in particulate matters: Composition, characteristics and influence factors

Airborne microorganisms (AM), vital components of particulate matters (PM), are widespread in the atmosphere. Since some AM have pathogenicity, they can lead to a wide range of diseases in human and other organisms, meanwhile, some AM act as cloud condensation nuclei and ice nuclei which let them can affect the climate. The inherent characteristics of AM play critical roles in many aspects which, in turn, can decide microbial traits. The uncertain factors bring various influences on AM, which make it difficult to elaborate effect trends as whole. Because of the potential roles of AM in environment and potent effects of factors on AM, detailed knowledge of them is of primary significance. This review highlights the issues of composition and characteristics of AM with size-distribution, species diversity, variation and so on, and summarizes the main factors which affect airborne microbial features. This general information is a knowledge base for further thorough researches of AM and relevant aspects. Besides, current knowledge gaps and new perspectives are offered to roundly understand the impacts and application of AM in nature and human health.

Aerobiology in the International Journal of Biometeorology, 1957-2017

Aerobiology and biometeorology are related fields. Here we provide a broad review of aerobiology articles published in the International Journal of Biometeorology (IJB) over the past 60 years. We consider how the quantity of such work has varied over this period as well as which regions and countries have been the focus of such work, and where there is a relative paucity. We then focus on a number of highlights and themes in this research, including aerobiology and climate change and aerobiological modelling and forecasting. While much of the article focusses on airborne pollen research, we also discuss the extent to which other airborne organic particles such as fungal spores and bacteria have been the focus of research published in IJB. Also considered are knowledge gaps and research needs and priorities with respect to the field of aerobiology. While the IJB has been one of the main platforms for presenting aerobiological research over recent decades, the article highlights the need for the field of aerobiology to embrace new sampling technologies such as spectral analysis and next-generation sequencing to identify and quantify airborne biological particles.

Early Detection of Ganoderma Basal Stem Rot of Oil Palms Using Artificial Neural Network Spectral Analysis

Ganoderma boninense is a causal agent of basal stem rot (BSR) and is responsible for a significant portion of oil palm (Elaeis guineensis) losses, which can reach US$500 million a year in Southeast Asia. At the early stage of this disease, infected palms are symptomless, which imposes difficulties in detecting the disease. In spite of the availability of tissue and DNA sampling techniques, there is a particular need for replacing costly field data collection methods for detecting Ganoderma in its early stage with a technique derived from spectroscopic and imagery data. Therefore, this study was carried out to apply the artificial neural network (ANN) analysis technique for discriminating and classifying fungal infections in oil palm trees at an early stage using raw, first, and second derivative spectroradiometer datasets. These were acquired from 1,016 spectral signatures of foliar samples in four disease levels (T1: healthy, T2: mildly-infected, T3: moderately infected, and T4: severely infected). Most of the satisfactory results occurred in the visible range, especially in the green wavelength. The healthy oil palms and those which were infected by Ganoderma at an early stage (T2) were classified satisfactorily with an accuracy of 83.3%, and 100.0% in 540 to 550 nm, respectively, by ANN using first derivative spectral data. The results further indicated that the sensitive frond number modeled by ANN provided the highest accuracy of 100.0% for frond number 9 compared with frond 17. This study showed evidence that employment of ANN can predict the early infection of BSR disease on oil palm with a high degree of accuracy.

Forecasting methodologies for Ganoderma spore concentration using combined statistical approaches and model evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006-2010. These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximum temperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0-49 s m(-3)), moderate (50-99 s m(-3)), high (100-149 s m(-3)) and very high (150 < n s m(-3)), could be designated. Despite some deviation in results obtained by artificial neural networks, authors have achieved a forecasting model, which was accurate (correlation between observed and predicted values varied from r s = 0.57 to r s = 0.68).

Application of redundancy analysis for aerobiological data

An aerobiological survey was conducted through five consecutive years (2006-2010) at Worcester (England). The concentration of 20 allergenic fungal spore types was measured using a 7-day volumetric spore trap. The relationship between investigated fungal spore genera and selected meteorological parameters (maximum, minimum, mean and dew point temperatures, rainfall, relative humidity, air pressure, wind direction) was examined using an ordination method (redundancy analysis) to determine which environmental factors favoured their most abundance in the air and whether it would be possible to detect similarities between different genera in their distribution pattern. Redundancy analysis provided additional information about the biology of the studied fungi through the results of the Spearman's rank correlation. Application of the variance inflation factor in canonical correspondence analysis indicated which explanatory variables were auto-correlated and needed to be excluded from further analyses. Obtained information will be consequently implemented in the selection of factors that will be a foundation for forecasting models for allergenic fungal spores in the future.

Effects of meteorological factors on the composition of selected fungal spores in the air

The aim of the study was to determine functional relationships between composition of air spora and meteorological factors, using multivariate statistical technique: canonical correspondence analysis (CCA). Analyses were conducted for the data collected during the 4 year (2007-2010) and, in order to show the dynamics of such relationships, for each year separately. The CCA results indicated that all statistically significant variables accounted for 15.3 % of the total variance in the spore data in the 4 years. The largest amount of the total variance was explained in this period by the mean air temperature (9.2 %). The meteorological factors impacted spore composition differently in different years, when analysis was done for each year separately. The highest values of the total variance in the spore data, explained by the statistically significant variables, were found in 2010 (32.3 %), with the highest contribution of mean air temperature (23.8 %). In that year, the above-mentioned parameter had the lowest value in comparison to other years. Canonical correspondence analysis provides not only a comprehensive assessment of the impact of meteorological factors on specific spore combinations in the air, but also informative graphical presentations of the results, illustrating the correlation between the occurrence of particular spore taxa and meteorological variables.

Aeromycology: studies of fungi in aeroplankton

Air is a natural environment for spores of many genera and species of fungi. Despite its small size and a significant dispersion they have a great impact on human health and different areas of our activities, such as agricultural production. The study on spores of fungi that belong to aeroplankton or bioaerosole is called aeromycology. The most frequent fungi present in the air are Cladosporium and Alternaria species. Their numbers are abundant regardless of latitude and height above the sea level and above the ground. They mostly originate from agricultural environment. Other frequently listed species of fungi, whose spores are present in the air include of Aspergillus, Penicillium, Fusarium, Sclerotinia and Ganoderma. The concentration of spores in the air strongly depends on the abundance of their formation during the studied period. This in turn relates to geobotanical region, vegetation, degree of urbanization, climatic conditions, season, current weather, wind force and direction, local microclimate, and many other factors. Changes in humidity affect the concentration of different types of fungal spores. In general they are divided to ‘dry’ (Alternaria, Cladosporium, Puccinia, Ustilago, Melampsora, Epicoccum, Drechslera) and ‘wet’ (Didymella, Fusarium, Ganoderma, Gliocladium, Leptosphaeria, Verticillium). Study of the composition of species and genera are being done using different types of spore samplers, mostly volumetric instruments. Visual identification is based on colony morphology of the fungus and the shape and size of spores. The identification at the species level is possible with molecular tools. Methods based on DNA/RNA amplification are very sensitive and accurate. They allow the identification below the species level, e.g. chemotypes, mating types or isolates with genes or alleles of interest. Aerobiological monitoring is widely used in the epidemiology of human diseases (inhalant allergies) and infections of arable crops (decision support systems for the protection of cultivated plants). Aeromycology is interconnected with such diverse areas as industrial aerobiology, bioterrorism, ecology, climatology or even speleology and cultural heritage.

Temporal dynamics of airborne fungi in Havana (Cuba) during dry and rainy seasons: influence of meteorological parameters

The aim of this paper was to determine for first time the influence of the main meteorological parameters on the atmospheric fungal spore concentration in Havana (Cuba). This city is characterized by a subtropical climate with two different marked annual rainfall seasons during the year: a "dry season" and a "rainy season". A nonviable volumetric methodology (Lanzoni VPPS-2000 sampler) was used to sample airborne spores. The total number of spores counted during the 2 years of study was 293,594, belonging to 30 different genera and five spore types. Relative humidity was the meteorological parameter most influencing the atmospheric concentration of the spores, mainly during the rainy season of the year. Winds coming from the SW direction also increased the spore concentration in the air. In terms of spore intradiurnal variation we found three different patterns: morning maximum values for Cladosporium, night peaks for Coprinus and Leptosphaeria, and uniform behavior throughout the whole day for Aspergillus/Penicillium."