The European Commission Cooperation in Science and Technology (COST) Action FA1203 “SMARTER” aims to make recommendations for the sustainable management of Ambrosia across Europe and for monitoring its efficiency and cost-effectiveness. The goal of the present study is to provide a baseline for spatial and temporal variations in airborne Ambrosia pollen in Europe that can be used for the management and evaluation of this noxious plant. The study covers the full range of Ambrosia artemisiifolia L. distribution over Europe (39°N–60°N; 2°W–45°E). Airborne Ambrosia pollen data for the principal flowering period of Ambrosia (August–September) recorded during a 10-year period (2004–2013) were obtained from 242 monitoring sites. The mean sum of daily average airborne Ambrosia pollen and the number of days that Ambrosia pollen was recorded in the air were analysed. The mean and standard deviation (SD) were calculated regardless of the number of years included in the study period, while trends are based on those time series with 8 or more years of data. Trends were considered significant at p < 0.05. There were few significant trends in the magnitude and frequency of atmospheric Ambrosia pollen (only 8% for the mean sum of daily average Ambrosia pollen concentrations and 14% for the mean number of days Ambrosia pollen were recorded in the air). The direction of any trends varied locally and reflected changes in sources of the pollen, either in size or in distance from the monitoring station. Pollen monitoring is important for providing an early warning of the expansion of this invasive and noxious plant.Electronic supplementary materialThe online version of this article (doi:10.1007/s10453-016-9463-1) contains supplementary material, which is available to authorized users.

Aim We examine issues of uncertainty regarding the spatial and temporal representativeness of phenological observations using a newly compiled Europe-wide data base of phenological observations for Betula species. Location Europe.Methods A new data base was compiled from national phenological observations covering 15 European countries, with the longest observational periods exceeding several decades for some sites. From this, the spatial and temporal representativeness of phenological observations were evaluated via statistical analysis. ResultsThe results showed that there was a significant and irreducible uncertainty related to the use of data of a single station, which varied from 3 to 8 days depending on the station location. In more continental and northern climatic zones the uncertainty was lower, probably due to faster spring-time weather developments. In mild climatic conditions, the uncertainty of dates of the phenological phases registered by a single station exceeded 1 week. The considerable number of data allowed us to preliminarily estimate the features of some stations, marking them as 'late' , 'early' , 'representative' or 'random' , depending on the dates reported by these sites and the corresponding regional means. Main conclusionsThe uncertainties discovered in single-site phenological observations are significant for virtually any potential application. Possible approaches for handling the uncertainty problem are station pre-averaging and spatial regularization of the data set, pre-selection (down-sampling) or changing the description of the phenomena from deterministic to probabilistic.

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within factor of 2 from observations, stays within 40-70%. In particular, model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down.

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Extensive use of sporo-pollen analysis is largely conditioned by such specific features of pollen and spores as their very-large-scale production in plants, the ability to preserve in soils, presence of characteristic morphological features enabling to distinguish and identify individual taxa, etc. In Belarus, the method of sporo-pollen analysis has also been implemented while forensic soil examination: it is increasingly applied to solve identification tasks in comparative analysis to establish the belonging of soil layers on physical evidence to the searched area. Its main advantage is that it is a multicomponent analysis allowing to evaluate both the composition of palynoflora and the percentage of several dozen components of sporo-pollen spectra contained in soil samples. Therefore, to determine the belonging of soil layers on physical evidence to the searched area, most informative are data obtained while sporo-pollen analysis, helping forensic experts on the basis of a specific taxonomic composition  of pollen and spores and percentage of spectra components to draw the most valid conclusions. Detection of pollen and spores in studied samples in a quantity sufficient for comparative analysis enables to statistically process data of samples microscopic examination. Statistical processing of results is one of the characteristic features of sporo-pollen analysis as a method that distinguishes it from other methods implemented in multidisciplinary forensic examination of soil.