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The atmosphere is host to a complex electric environment, ranging from a global electric circuit generating fluctuating atmospheric electric fields to local lightning strikes and ions. While research on interactions of organisms with their electrical environment is deeply rooted in the aquatic environment, it has hitherto been confined to interactions with local electrical phenomena and organismal perception of electric fields. However, there is emerging evidence of coupling between large- and small-scale atmospheric electrical phenomena and various biological processes in terrestrial environments that even appear to be tied to continental waters. Here, we synthesize our current understanding of this connectivity, discussing how atmospheric electricity can affect various levels of biological organization across multiple ecosystems. We identify opportunities for research, highlighting its complexity and interdisciplinary nature and draw attention to both conceptual and technical challenges lying ahead of our future understanding of the relationship between atmospheric electricity and the organization and functioning of biological systems. [ABSTRACT FROM AUTHOR]

Alternaria and Cladosporium are the most common airborne fungal spores responsible for health problems, as well as for crop pathologies. The study of their behavior in the air is a necessary step for establishing control and prevention measures. The aim of this paper is to develop a logistic regression model for predicting the daily concentrations of airborne Alternaria and Cladosporium fungal spores from meteorological variables. To perform the logistic regression analysis, the concentration levels are binarized using concentration thresholds. The fungal spore data have been obtained at eight aerobiological monitoring stations of the Aerobiological Network of Catalonia (NE Spain). The meteorological data used were the maximum and minimum daily temperatures and daily rainfall provided by the meteorological services. The relationship between the meteorological variables and the fungal spore levels has been modeled by means of logistic regression equations, using data from the period 1995–2012. Values from years 2013–2014 were used for validation. In the case of Alternaria, three equations for predicting the presence and the exceedance of the thresholds 10 and 30 spores/m3 have been established. For Cladosporium, four equations for the thresholds 200, 500, 1000, and 1500 spores/m3 have been established. The temperature and cumulative rainfall in the last 3 days showed a positive correlation with airborne fungal spore levels, while the rain on the same day had a negative correlation. Sensitivity and specificity were calculated to measure the predictive power of the model, showing a reasonable percentage of correct predictions (ranging from 48 to 99%). The simple equations proposed allow us to forecast the levels of fungal spores that will be in the air the next day, using only the maximum and minimum temperatures and rainfall values provided by weather forecasting services. [ABSTRACT FROM AUTHOR]

Atmospheric electricity has been studied since the early 1700s. This special issue unites new research that links atmospheric electricity with biology and human well-being that collectively highlight the importance of a rejuvenated interest in this field. The contributions show how atmospheric electricity can govern human well-being as well as a wide array of organisms and the processes they sustain and therefore serve as an appraisal to consider atmospheric electricity as a significant direct and indirect driver of biology. [Extracted from the article]

Alternaria is frequently found as airborne fungal spores and is recognized as an important cause of respiratory allergies. The aerobiological monitoring of fungal spores was performed using a Burkard volumetric spore traps. To establish predicting variables for daily and weakly spore counts, a stepwise multiple regression between spore concentrations and independent variables (meteorological parameters and lagged values from the series of spore concentrations: previous day or week concentration (Alt) and mean concentration of the same day or week in other years ( C)) was made with data obtained during 2009-2011. Alternaria conidia are present throughout the year in the atmosphere of Tetouan, although they show important seasonal fluctuations. The highest levels of Alternaria spores were recorded during the spring and summer or autumn. Alternaria showed maximum daily values in April, May or October depending on year. When the spore variables of Alternaria, namely C and Alt, and meteorological parameters were included in the equation, the resulting R satisfactorily predict future concentrations for 55.5 to 81.6 % during the main spore season and the pre-peak 2. In the predictive model using weekly values, the adjusted R varied from 0.655 to 0.676. The Wilcoxon test was used to compare the results from the expected values and the pre-peak spore data or weekly values for 2012, indicating that there were no significant differences between series compared. This test showed the C, Alt, frequency of the wind third quadrant, maximum wind speed and minimum relative humidity as the most efficient independent variables to forecast the overall trend of this spore in the air. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper provides an updated of airborne Alternaria spore spatial and temporal distribution patterns in the Iberian Peninsula, using a common non-viable volumetric sampling method. The highest mean annual spore counts were recorded in Sevilla (39,418 spores), Mérida (33,744) and Málaga (12,947), while other sampling stations never exceeded 5,000. The same cities also recorded the highest mean daily spore counts (Sevilla 109 spores m; Mérida 53 spores m and Málaga 35 spores m) and the highest number of days on which counts exceeded the threshold levels required to trigger allergy symptoms (Sevilla 38 % and Mérida 30 % of days). Analysis of annual spore distribution patterns revealed either one or two peaks, depending on the location and prevailing climate of sampling stations. For all stations, average temperature was the weather parameter displaying the strongest positive correlation with airborne spore counts, whilst negative correlations were found for rainfall and relative humidity. [ABSTRACT FROM AUTHOR]