Krystyna Piotrowska

Pollen–vegetation relationships for pine and spruce in southeast Poland on the basis of volumetric and Tauber trap records

Abstract The aim of the study was to determine the pollen–vegetation relationship for Pinus and Picea. Pollen deposition was monitored using Tauber traps in the Roztocze region of Poland. The pine and spruce pollen sums obtained were compared with annual sums recorded in volumetric samplers in the cities of Lublin and Rzeszów. Average values of pollen deposition were compared to a detailed inventory of vegetation within a radius of 1 km of the monitoring sites. A more robust vegetation survey, conducted at a distance of 15 km, was used to estimate the proportion of pine and spruce pollen in regional pollen rain. The occurrence of high and low pollen deposition years was studied. Between 2001 and 2006, the data from Lublin and Roztocze produced similar trends in the high or low Pinus pollen sums. The representation of pine in the pollen spectra was very high, due to both its abundance in the regional vegetation and the prevalence of long-distance transport of pine pollen. Comparison of pollen and vegetation data indicates that, in the case of spruce, the distance from the monitoring site and forest structure are the most important factors influencing pollen representation. The problems associated with estimating pollen productivity of both pine and spruce in relation to Poaceae is discussed.

Forecasting the Poaceae pollen season in eastern Poland

Abstract The aim of the present study was to develop forecast models for the grass pollen season by using regression analyses to predict such characteristics as onset, duration and peak pollen concentration (values and timing). The study shows a negative correlation between seasonal pollen index (SPI) and season duration as well as strong correlations between some features of the pollen season and meteorological data. The forecasting models may predict 86–98% of the variation in pollen onset and duration of the pollen season. Less satisfactory results were obtained for the peak date and peak value. The best prediction was obtained for the season duration. The mean minimum temperature of March and cloud cover in the first 10-day period of May were the best variables for forecasting the start of the grass pollen season in Lublin. The rainfall in May was the most important factor to determine season duration. When the developed models are applied for pollen season forecasting, it is possible to predict the season onset and duration with an accuracy of up to one or two days.