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 para...

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Bibliographic Details
Published in:International journal of biometeorology 2015-01, Vol.59 (1), p.25-36
Main Authors: Sadyś, Magdalena, Strzelczak, Agnieszka, Grinn-Gofroń, Agnieszka, Kennedy, Roy
Format: Article
Language:English
Subjects:
air
Air Microbiology
Air Pollutants - analysis
allergenicity
Allergens - analysis
Animal Physiology
atmospheric pressure
Biological and Medical Physics
Biology
Biophysics
correspondence analysis
dew
Dew point
Earth and Environmental Science
England
Environment
Environmental factors
Environmental Health
Environmental Monitoring - methods
Environmental Monitoring - statistics & numerical data
fungal spores
Fungi
Fungi - classification
Fungi - isolation & purification
Meteorology
Ordination
Original Paper
Plant Physiology
rain
Relative humidity
spore traps
Spores, Fungal - isolation & purification
surveys
temperature
variance
Weather
wind direction
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Summary: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.
ISSN:0020-7128
1432-1254
DOI:10.1007/s00484-014-0818-4