Start Of Pollen Season Research Articles

Predicting the start, peak and end of the Betula pollen season in Bavaria, Germany

Betula pollen is frequently found in the atmosphere of central and northern Europe. Betula pollen are health relevant as they cause severe allergic reactions in the population. We developed models of thermal requirements to predict start, peak and end dates of the Betula main pollen season for Bavaria (Germany). Betula pollen data of one season from 19 locations were used to train the models. Estimated dates were compared with observed dates, and the errors were spatially represented. External validation was carried out with time series datasets of 3 different locations (36years in total). ResultsThe temperature requirements to detonate the main pollen season proved non-linear. For the start date model (error of 8,75days during external validation), daily mean temperatures above a threshold of 10°C from 28th of February onwards were the most relevant. The peak model (error of 3.58days) takes into account mean daily temperatures accumulated since the first date of the main pollen season in which the daily average temperature exceeded 11°C. The end model (error of 3.75days) takes into account all temperatures accumulated since the start of the main pollen season. ConclusionThese models perform predictions that enable the allergic population to better manage their disease. With the established relationship between temperatures and pollen season dates, changes in the phenological behaviour of Betula species due to climate change can be also estimated in future studies by taking into account the different climate scenarios proposed by previous climate change studies.

Alder pollen season in selected cities of Poland in 2019

The pollen of grass is the primary trigger of pollen allergies during the summer months. It causes some of the most severe and difficult-to-treat symptoms. During the flowering of grass, over 90% of patients allergic to grass pollen suffer from allergic conditions. The symptoms caused by grass pollen allergens appear in some patients after exceeding the concentration of 20 grains in m3 of air. The aim of this study was to compare Poaceae pollen seasons in 2019 in 11 cities located in different regions of Poland. Pollen monitoring was conducted in Bialystok, Bydgoszcz, Sosnowiec, Lublin, Olsztyn, Szczecin, Piotrkow Trybunalski, Warsaw, Opole, Zielona Gora and Wroclaw. Airborne pollen was monitored by the volumetric method using Burkard or Lanzoni pollen samplers. Pollen season length was determined by the 98% method, where the start of the season was defined as the date when 1% of the seasonal pollen total was trapped and the end of the season as the date, when 99% of the seasonal pollen total was reached.The pollen season start date was recorded earliest in Zielona Gora (April 27th), latest in Szczecin (May 25th). The highest grass pollen concentration values were found in Lublin, Piotrkow Trybunalski and Warsaw, whereas the lowest ones in Bialystok. The annual grass pollen sum was highest in Lublin (4715 pollen grains), whereas it was lowest in Bialystok (1256 pollen grains). A relatively high pollen count was also recorded in Warsaw (4106 pollen grains) and Zielona Gora (4077 pollen grains). The longest grass pollination season was recorded in Zielona Gora (139 days) and the shortest in Szczecin (110 days). In the remaining measuring points, grass pollen in the air maintained from 112 to 131 days. The highest grass pollen allergen risk occurred in Lublin, Olsztyn and Zielona Gora and the lowest in Bialystok.

The variability of pollen concentrations at two stations in the city of Wroc\u0142aw in Poland

The aim of the study was to investigate the variability of Alnus and Corylus pollen concentrations at two stations located in the city of Wrocław, Poland—one at the city centre and the other 4 km from the city centre. Our goal was to compare measurements from these stations in relation to meteorology and land cover. We used Spearman’s correlation coefficient to investigate any dependence between meteorological factors and pollen concentration. Additionally, to check the relation between the direction of inflow of air masses and pollen concentration, we calculated the backward trajectories using the HYSPLIT model. The results have shown that despite the short distance between the stations, the characteristic of the pollen season is different for both stations (i.a. date of start and end of pollen season, duration of the season). The Spearman’s correlation coefficient between relative humidity and air temperature and pollen concentration was found to be statistically significant. The backward trajectories calculated with HYSPLIT suggested a different origin of air masses between stations for high-concentration episodes in the case of Alnus. Our study has shown that analysis of meteorological conditions and influence of air transport into pollen concentration makes it possible to ascertain the reasons for differences in pollen level at these two stations, both of which are located in the same climatological domain. The study also shows that the aerobiological condition may change significantly over a short distance, which is a major challenge, for example, for pollen emission, transport, and concentration modelling.

Characterizing the relationship between satellite phenology and pollen season: A case study of birch

Pollen released by vegetation in urban and surrounding rural areas is an important risk factor for respiratory allergies. Mapping the onset, duration, and severity of pollen is difficult, because of insufficient stations and/or monitoring networks at the national and international levels. To address this challenge, we evaluated the spatiotemporal relationship between satellite derived vegetation phenology and in-situ station derived information of pollen season during 2001–2015 at five stations in Canada. First, we calculated annual indicators of start of season (SOS) and start of pollen season (SPS) for birch from Landsat time series and pollen concentration data, respectively, at the five stations. Second, we explored the relationship between derived indicators of SOS and SPS and investigated the scale effect on the relationship. Our results indicate the Landsat based SOS is a good proxy for the indicator of SPS in the birch dominated area. The mean SOS and SPS in the study period are close (within 2.7 days) across the five stations. The interannual variability of SOS and SPS suggests the satellite derived phenology indicator can capture well the dynamics of pollen season in spring. Our analysis also indicates that the annual SOS at a finer resolution (30 m) is more consistent with SPS as compared to the indicators derived from coarser resolution satellite observations. This study shows the potential of using fine spatial resolution satellite data (e.g., Landsat) to derive the pollen season indicators, which is important for predicting pollen season severity and risk, and assessment of their impacts on respiratory allergies in urban domains.

Ambrosia pollen season in selected cities in Poland in 2018

Ambrosia causes most pollen allergies in North America. After several Ambrosia species were introduced to Europe, an increase in the incidence of allergy to pollen of these plants has been observed in many countries. The aim of this study was to compare Ambrosia pollen seasons in 2018 in 13 cities located in different regions of Poland: Bialystok, Bydgoszcz, Cracow, Drawsko Pomorskie, Lublin, Olsztyn, Opole, Piotrkow Trybunalski, Sosnowiec, Szczecin, Warsaw, Wroclaw and Zielona Gora. The study was conducted by the volumetric method using Burkard or Lanzoni pollen samplers. The pollen season was determined by the 98% method. The earliest pollen season start dates (the end of July) were recorded in Zielona Gora, Bydgoszcz, Opole and Szczecin, while the latest ones in Drawsko Pomorskie and Bialystok. The longest pollen seasons occurred in Opole, Szczecin and Zielona Gora (79 days). The highest average daily concentrations of Ambrosia pollen were recorded in Bialystok (129 P/m3) and Lublin (99 P/m3), while the lowest ones in Drawsko Pomorskie and Szczecin (4 and 10 P/m3, respectively). The annual pollen sum reached the highest value in Opole (567 pollen grains) and Zielona Gora (555 pollen grains). It can be concluded from the pattern of Ambrosia pollen seasons at the monitoring sites studied that pollen of this taxon originates not only from Ambrosia locations in Poland but also from long-distance transport.

Google Trends reflect allergic rhinitis symptoms related to birch and grass pollen seasons

Google Trends (GT) describes the variation of the relevant interest of internet searches toward medical conditions and related symptoms. Allergic rhinitis symptom levels result from the intensity of exposure to aeroallergens in combination with relevant medication use. We analyze data from Germany to examine the relationship between hay fever-related Google search terms, symptom levels, medication use, and pollen count levels. For doing so, we also employ the new definitions on pollen season and peak pollen period start and end as proposed by the European Academy of Allergy and Clinical Immunology in a recently published position paper. We extract GT data for a number of search terms related to allergic rhinitis for Germany. We use total nasal symptom and mediation scores as reported by patients via a patient hay fever diary in the Berlin and Brandenburg areas in Germany for 3 years (2014–2016), accompanied by pollen data. Then a Pearson and Spearman correlation analysis is performed between symptom data and GT data. A graphical analysis is conducted, and the identification of pollen season and peak pollen periods is done based on the EAACI criteria. The analysis reveals that GT data are highly correlated with symptom levels and follow peak pollen period start–end, concerning grass and birch pollen-induced allergic rhinitis symptoms. GT data can be used as a proxy for the identification of the onset and variation of nasal symptom and medication score for allergic rhinitis sufferers.

New European Academy of Allergy and Clinical Immunology definition on pollen season mirrors symptom load for grass and birch pollen-induced allergic rhinitis.

The use of allergen immunotherapy (AIT) for allergic rhinitis and its clinical efficacy in clinical trials depends on the effective determination of pollen allergen exposure time periods. We evaluate pollen data from Germany to examine the new definitions on pollen season and peak pollen period start and end as proposed by the European Academy of Allergy and Clinical Immunology (EAACI) in a recently published Position Paper. The aim was to demonstrate the ability of these definitions to mirror symptom loads for grass and birch pollen-induced allergic rhinitis based on real-life data. Data coming from four pollen monitoring stations in the Berlin and Brandenburg area in Germany and for 3years (2014-2016) were used to investigate the correlation of season definitions, birch and grass pollen counts and total nasal symptom and mediation scores as reported by patients in "Patients Hay fever Diaries" (PHDs). After the identification of pollen periods on the basis of the EACCI criteria, a statistical analysis was employed, followed by a detailed graphical investigation. The analysis revealed that the definitions of pollen season as well as peak pollen period start and end as proposed by the EAACI are correlated to symptom loads for grass and birch pollen-induced allergic rhinitis reported by patients in PHDs. Based on our analysis, the validity of the EAACI definitions on pollen season is confirmed. Their use is recommended in future clinical trials on AIT as well as in daily routine for optimal patient care.

Analysis of Fraxinus pollen seasons and forecast models based on meteorological factors.

The timings of Fraxinus and Betula flowering and pollen release overlap, which may cause increased allergic reactions in sensitive people. The aim of the present study was to characterize Fraxinus pollen seasons in Lublin (central-eastern Poland) and to identify meteorological factors that most determine the occurrence of airborne pollen of this taxon, as well as obtain forecast models for the basic characteristics of the pollen season. The study was conducted in Lublin during the period 2001-2016, employing the volumetric method. The seasons were compared by PCA (Principal Component Analysis). To determine relationships between meteorological conditions and the pattern of pollen seasons, regression analysis was used. Data for the period 2001-2015 were used to create forecast models by applying regression analysis, while the 2016 data served to verify these models. Season end date and seasonal peak date were characterized by the lowest variation. The biggest differences were found for peak value and total annual pollen sum. The average dates of occurrence of ash pollen grains in the air of Lublin were between 13 April 13 - 3 May 3, whereas, on average, the pollen peak date occurred on 23 April. The factor loading values for the PC1 variable indicate that it is most strongly correlated with peak value and total pollen sum, while the PC2 variable correlated with the pollen season start date and season duration (a negative correlation). Regression models were developed for the following pollen season characteristics: season start, end and duration, seasonal peak date, and total annual pollen sum. The fit of the forecast models was at the level of 62-94%. Analysis of the data showed that weather conditions mainly in February were important factors controlling the Fraxinus pollen season.

A prognostic pollen emissions model for climate models (PECM1.0)

Abstract. We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

Mapping the birch and grass pollen seasons in the UK using satellite sensor time-series

Grass and birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the UK and parts of Europe affecting around 15–20% of the population. Current prediction of these allergens in the UK is based on (i) measurements of pollen concentrations at a limited number of monitoring stations across the country and (ii) general information about the phenological status of the vegetation. Thus, the current prediction methodology provides information at a coarse spatial resolution only. Most station-based approaches take into account only local observations of flowering, while only a small number of approaches take into account remote observations of land surface phenology. The systematic gathering of detailed information about vegetation status nationwide would therefore be of great potential utility. In particular, there exists an opportunity to use remote sensing to estimate phenological variables that are related to the flowering phenophase and, thus, pollen release. In turn, these estimates can be used to predict pollen release at a fine spatial resolution. In this study, time-series of MERIS Terrestrial Chlorophyll Index (MTCI) data were used to predict two key phenological variables: the start of season and peak of season. A technique was then developed to estimate the flowering phenophase of birch and grass from the MTCI time-series. For birch, the timing of flowering was defined as the time after the start of the growing season when the MTCI value reached 25% of the maximum. Similarly, for grass this was defined as the time when the MTCI value reached 75% of the maximum. The predicted pollen release dates were validated with data from nine pollen monitoring stations in the UK. For both birch and grass, we obtained large positive correlations between the MTCI-derived start of pollen season and the start of the pollen season defined using station data, with a slightly larger correlation observed for birch than for grass. The technique was applied to produce detailed maps for the flowering of birch and grass across the UK for each of the years from 2003 to 2010. The results demonstrate that the remote sensing-based maps of onset flowering of birch and grass for the UK together with the pollen forecast from the Meteorology Office and National Pollen and Aerobiology Research Unit (NPARU) can potentially provide more accurate information to pollen allergy sufferers in the UK.

OLIVE YIELDS FORECASTS AND OIL PRICE TRENDS IN MEDITERRANEAN AREAS: A COMPREHENSIVE ANALYSIS OF THE LAST TWO DECADES

SUMMARYThe main objective of this research was to utilize pollen monitoring methodology to predict olive yields in three Mediterranean olive cultivation areas (Spain, Italy and Tunisia) and their relationships with the olive oil price dynamics. Moreover, olive yield and olive oil production compared with olive oil price trends in the last two decades was evaluated. The statistical analyses confirmed that biological parameters such as the pollen emission, the pollen season start (Pss), the full flowering (Ff) date or the pollen season length (Psl) showed positive correlation values with productive parameters, especially the Pollen Index (Pi). However, the difficulty to define clear relationships with oil price for optimizing the marketing strategies can be due to the olive sector European policy and to the complex international olive oil market situation. The occurrence of unharvested trees was increased and the reduction in agricultural operations as well as non-harvesting could become more widespread above all in traditional extensive systems.

Modelling the pollen season start in Corylus avellana and Alnus glutinosa

Hazel (Corylus avellana L.) and black alder (Alnus glutinosa (L.) Gaertn.) are important sources of airborne pollen and represent an allergen threat during the flowering period. Researches on airborne pollen concentrations in both species are useful in allergology, as well as for fruit production for hazel. The aims of the present study were: (1) to investigate the relationships between environmental conditions and the airborne pollen concentration of hazel and black alder during the flowering period by correlation and multiple regression analysis and (2) to predict the pollen season start (PSS) by using a sequential model, in order to obtain a helpful tool in allergology and hazel cultivation. In this study, the applied method defines the pollen season as the period in which 90 % of the total season’s catch occurred, using a data set of 18 years (1996–2014). The relationships between daily meteorological parameters (temperature, humidity, rainfall and wind speed) during the 14-day period that precedes the PSS and the PSS of hazel and black alder (day of the year) were investigated. The results showed that mean temperature and the number of rainy days before the PSS are the main factors influencing PSS for both taxa. Moreover, the chilling and heat needed to break dormancy were estimated in order to predict the PSS of both species. Different years and different thresholds of temperature and chill days were used to calibrate and validate the model.

Effect of the meteorological parameters on the Olea europaea L. pollen season in Bahía Blanca (Argentina)

Olea europaea is one of the most prevalent aeroallergens causing allergenic reactions in the city of Bahia Blanca, Argentina. The aim of this study was to evaluate the influence of meteorological factors on the pollen season of Olea europaea L. The aerobiological analysis was performed over an 11-year period in the city. Sampling was carried out with a Rotorod model 40 volumetric impact sampler. The pollen season started in the middle of October and showed the highest values between 16 October and 24 November. A marked difference was noted over the years of this study, especially in 2005 and 2008, due to a significant decrease in the precipitation during the months prior flowering and high temperatures during the pollen season. A decreasing trend of pollen index during the study period coincided with a reduction in the precipitation from June to October (winter and spring). As expected, the air temperature prior to the onset of flowering is of great importance in determining the start of the pollen season.

Pollen calendars: a guide to common airborne pollen in Andalusia

This paper presents pollen calendars for the capital cities of the eight provinces of Andalusia (south of Spain) based on the airborne pollen counts recorded in a 10-year historical database. Pollen calendars are useful in the prevention and diagnosis of hay fever, in that they enable the timing and severity of the pollen season to be clearly defined. The differences encountered—in terms of both pollen spectra and the length and timing of the pollen season (start date, peak date, peak concentration and end date)—highlight not only the considerable diversity of urban landscapes in the eight Andalusian cities, but also the effect of urban green areas and periurban landscapes on airborne pollen levels. Green areas should be designed with a view to promoting benefits for the local population and avoiding the problems associated with the massive use of allergenic plants.

Grass pollen seasons in Poland against a background of the meteorological conditions

The paper refers to the estimation of Poaceae pollen seasons in Poland in selected areas. The aim of the study was to present the long-term variability of the start, end and duration of grass pollen seasons and the seasonal pollen index (SPI) in Poland against a background of the meteorological conditions over pollen seasons. The study was performed in eight Polish cities in 1992–2014 (the common seasons were 2003–2012). Pollen season start was relatively stable in the studied period, the seasons began about the 10th of May, a bit earlier in the south part of Poland. Pollen season ends were more changeable in comparison to the season start and fluctuated from the middle of July to the middle of September. SPI clearly depended on temperature and precipitation in April–August. Daily maximum pollen concentrations were achieved between the end of May and the first decade of July and no evident relationship between this day and weather conditions was found, apart from 2004.

Airborne pollen of Olea europaea L. in Tetouan (NW Morocco): heat requirements and forecasts

The northwest of Morocco is one of the major areas dedicated to olive tree crop in Morocco. Airborne pollen of Olea was recorded during 2008–2012 to determine its annual load and variation. Aerobiological sampling was undertaken over five seasons in Tetouan using the volumetric method. This study used also a thermal model to calculate growing degree-days required until the start of the pollen season and the peak day. For this purpose, a range of the threshold temperatures between 0 and 10 °C was tested. The pollen season started from the second decade of March and showed the highest pollen index in May or April. The annual pollen score recorded varied from year to year between 4,168 and 1,953. The main pollen season lasted 62–105 days, with peak days occurring in April or May; the highest concentration reached 379 pollen grains/m3. The sum of the difference between mean temperature and threshold temperatures of 10 and 7 °C from 51 and 61 days before the season start and peak day accumulated averages heat units of 278 and 624 growing degree days, respectively. In order to validate the forecast of these parameters of the pollen season, we have used the year 2012 as external data. The dates predicted did not differ from those observed when threshold temperatures 10 and 7 °C were tested to forecast the onset of the Olea pollen season and the full anthesis, respectively. The method performed in this study showed a high coincidence between expected and observed data and should be useful to allow olive crop yield management in the area of Tetouan.

Models to predict the start of the airborne pollen season.

Aerobiological data can be used as indirect but reliable measures of flowering phenology to analyze the response of plant species to ongoing climate changes. The aims of this study are to evaluate the performance of several phenological models for predicting the pollen start of season (PSS) in seven spring-flowering trees (Alnus glutinosa, Acer negundo, Carpinus betulus, Platanus occidentalis, Juglans nigra, Alnus viridis, and Castanea sativa) and in two summer-flowering herbaceous species (Artemisia vulgaris and Ambrosia artemisiifolia) by using a 26-year aerobiological data set collected in Turin (Northern Italy). Data showed a reduced interannual variability of the PSS in the summer-flowering species compared to the spring-flowering ones. Spring warming models with photoperiod limitation performed best for the greater majority of the studied species, while chilling class models were selected only for the early spring flowering species. For Ambrosia and Artemisia, spring warming models were also selected as the best models, indicating that temperature sums are positively related to flowering. However, the poor variance explained by the models suggests that further analyses have to be carried out in order to develop better models for predicting the PSS in these two species. Modeling the pollen season start on a very wide data set provided a new opportunity to highlight the limits of models in elucidating the environmental factors driving the pollen season start when some factors are always fulfilled, as chilling or photoperiod or when the variance is very poor and is not explained by the models.

Assessment of Quercus flowering trends in NW Spain.

This paper sought to chart airborne Quercus pollen counts over the last 20 years in the region of Galicia (NW Spain) with a view to detecting the possible influence of climate change on the Quercus airborne pollen season (APS). Pollen data from Ourense, Santiago de Compostela, Vigo and Lugo were used. The Quercus airborne pollen season was characterized in terms of the following parameters: pollen season start and end dates, peak pollen count, pollen season length and pollen index. Several methods, dates and threshold temperatures for determining the chill and heat requirements needed to trigger flowering were applied. A diverse APS onset timing sequence was observed for the four cities as Quercus flowers few days in advance in Vigo. The variations observed could be related to differences in the meteorological conditions or the thermal requirements needed for flowering. Thermal requirements differed depending on local climate conditions in the study cities: the lowest values for chilling accumulation were recorded in Vigo and the highest in Lugo, whereas the lowest heat accumulation was achieved in Vigo. Differences in APS trends between cities may reflect variations in weather-related trends. A significant trend towards rising Quercus pollen indices and higher maximum daily mean pollen counts was observed in Ourense, linked to the more marked temperature increase across southern Galicia. A non-uniform trend towards increased temperatures was noted over the study period, particularly in late summer and early autumn in all four study cities. Additionally, an increase in spring temperatures was observed in south-western Galicia.

Comparison of Poaceae pollen counts recorded at sites in Portugal, Spain and the UK

The main aim of this study was to analyse the temporal and spatial variations in grass (Poaceae) pollen counts (2005–2011) recorded in Evora (Portugal), Badajoz (Spain) and Worcester (UK). Weekly average data were examined using nonparametric statistics to compare differences between places. On average, Evora recorded the earliest start dates of the Poaceae pollen seasons and Worcester the latest. The intensity of the Poaceae pollen season varied between sites, with Worcester usually recording the least and Evora the most grass pollen in a season. Mean durations of grass pollen seasons were 77 days in Evora, 78 days in Badajoz and 59 days in Worcester. Overall, longer Poaceae pollen seasons coincided with earlier pollen season start dates. Weekly pollen data, from March to September, from the three pollen-monitoring stations studied were compared. The best fit and most statistically significant correlations were obtained by moving Worcester data backward by 4 weeks (Evora, r = 0.810, p < 0.001) and 5 weeks (Badajoz,r = 0.849, p < 0.001). Weekly data from Worcester therefore followed a similar pattern to that of Badajoz and Evora but at a distance of more than 1,500 km and 4–5 weeks later. The sum of pollen recorded in a season was compared with monthly rainfall between January and May. The strongest positive relationship between season intensity and rainfall was between the annual sum of Poaceae pollen recorded in the season at Badajoz and Evora and total rainfall during January and February. Winter rainfall noticeably affects the intensity of Poaceae pollen seasons in Mediterranean areas, but this was not as important in Worcester.

Predicting tree pollen season start dates using thermal conditions.

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 of Alnus, Corylus and Betula were 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 (for Alnus and Corylus) and mean (for Betula) 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 for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, 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.