title: Predicting tree pollen season start dates using thermal conditions.
abstract: Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data ofAlnus,CorylusandBetulawere obtained in 1991-2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (forAlnusandCorylus) and mean (forBetula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models forBetula, comparing toAlnusandCorylus. The proposed model makes the accuracy of prediction in 83.58 % of cases forAlnus, in 84.29 % of cases forCorylusand in 90.41 % of cases forBetula. In years of model verification (2011 and 2012), the season start ofAlnusandCoryluswas predicted more precisely in 2011, while in case ofBetula,the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991-2010.
authors.affiliation: Department of Clinical and Environmental Allergology, Jagiellonian University Medical College, Śniadeckich 10, 31-531 Kraków, Poland.
authors.forename: Dorota
authors.initials: D
authors.lastname: Myszkowska
keywords: Alnus; Betula pollen seasons; Corylus; Logistic regression; Mean and maximum temperature fluctuations; Predictive models
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