ArticleInternational journal of biometeorology2009
Forecasting the start of Quercus pollen season using several methods - the evaluation of their efficiency.
Article in International journal of biometeorology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparative modeling approaches for predicting Olea and Quercus pollen seasons in Thessaloniki, Greece.Scientific reports · 2025Article
- Aerobiology in the International Journal of Biometeorology, 1957-2017.International journal of biometeorology · 2017Article
- The rise of phenology with climate change: an evaluation of IJB publications.International journal of biometeorology · 2017Article
- Climate change: consequences on the pollination of grasses in Perugia (Central Italy). A 33-year-long study.International journal of biometeorology · 2017Article
- Poaceae pollen in the air depending on the thermal conditions.International journal of biometeorology · 2014Article
- Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States.International journal of biometeorology · 2014Article
- Region-specific sensitivity of anemophilous pollen deposition to temperature and precipitation.PloS one · 2014Article
- Variations inAerobiologia · 2014Article
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1 author.
Funding
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Abstract
Forecasting the time when the atmospheric pollen season of allergenic plants begins is particularly important for doctors and their patients. The aim of this paper is to determine whether it is possible to forecast the start of the oak (Quercus) pollen season in Rzeszów, Poland. In the elaboration of the most effective model, various forecasting techniques were tested: growth degree days (GDD degrees C); meteorological factors; bioclimatic factors; and indicator taxon. The aerobiological monitoring was carried out in 1997-2005 and 2007 in Rzeszów (SE Poland). In the presented investigation, three methods defining the start of the Quercus pollen season were selected on the basis of accumulated sums of pollen or the constant occurrence of pollen grains in air. Despite the application of different combinations of GDD degrees C methods and threshold temperatures, the correlation coefficients between the expected and obtained values were low. In some cases, however, they proved highly effective for the test years (2005, 2007) with the accuracy of a few days. For GDD degrees C methods, the best threshold temperatures range between 5 and 6 degrees C. Models based on bioclimatic indices and meteorological variables were not satisfactory. On the basic of the 10 years of results, the method of indicator species were good for forecast the start of oak pollen season. Birch was the best indicator taxa.
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