title: [Prospective study of pollen dispersal prediction and identifying the usefulness of different parameters].
abstract: BACKGROUND
  Birch pollen is the major pollen allergen in Hokkaido, Northern Japan. We reported a Betula masting model based on the resource budget model hypothesis. In addition to weather conditions, cumulative hours of sunlight and mean temperature from May to July of the previous year, this model used the amount of annual pollen dispersed in previous and penultimate years as a parameter based on data from 1990 to 2000.
  
  
  OBJECTIVE
  We compared the predicted and observed amount of pollen dispersed for 3 years from 2001 to 2003 and evaluated the usefulness of each parameter in this model.
  
  
  METHODS
  Birch pollen was measured using the Durham sampler at the Hokkaido University Graduate School of Medicine Research Institute in Sapporo.
  
  
  RESULTS
  The difference between predicted and observed amounts of pollen dispersal was about 200-500 grains cm(-2). The annual pollen dispersed in the previous year was found to be the most useful parameter.
  
  
  CONCLUSIONS
  This model is useful in predicting whether the amount of birch pollen will be less than average, about average, more than average, or much more than average.
authors.affiliation: Department of Otolaryngology, Head and Neck Surgery, Hokkaido University Graduate School of Medicine, Sapporo.
authors.forename: Masanori
authors.initials: M
authors.lastname: Maeda
authors.forename: Shiro
authors.initials: S
authors.lastname: Maguchi
authors.forename: Yuji
authors.initials: Y
authors.lastname: Nakamaru
authors.forename: Dai
authors.initials: D
authors.lastname: Takagi
authors.forename: Satoshi
authors.initials: S
authors.lastname: Fukuda
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000485:Allergens / Q000032:analysis*; D029662:Betula; D004784:Environmental Monitoring / Q000379:methods*; D005544:Forecasting / Q000379:methods*; D007564:Japan; D015233:Models, Statistical; D011058:Pollen; D011446:Prospective Studies; D013997:Time Factors; D014887:Weather
chemical_list: D000393:Air Pollutants; D000485:Allergens