[Forecast of total pollen counts of sugi (Cryptomeria japonica) from the amount of male flower development and the revised total pollen counts].
We have successfully forecast the total pollen counts of sugi (Cryptomeria japonica) since 1996 by the amount of male flower development. The amount of male flower development was observed at 11 forests in the Tanba Mountains and 10 forests in the Chugoku Mountains depending on both in Hyogo Prefecture. The amount of male flower development on each tree was assigned to one of five classes by the number of male flowers per spring. After a large harvest of male flowers, the production of male flowers declined in the following years, especially at high altitudes. It was also followed by a decrease in the number of airborne pollen grains in the later pollen season. According to an analysis of weather conditions, total pollen counts were correlated with the high temperature between July 6 and 20 and the total pollen counts of the previous season. However, the amount of male flower development was the most significant indicator for forecasting total pollen counts. Decrease in total pollen counts due to abnormal weather during the pollen season was correlated with discrepancies in forest flowering time according to observations made in the Rokko Mountains. Increase in total pollen counts was connected by a development of the sugi forest areas. Twenty percent of mature sugi forests from 1992 which showed an annual increase were associated with an increase in total pollen counts. The accuracy of the forecast was improved by revising the total pollen counts for weather conditions during the dispersion stage, a decrease in the production of male flowers at high altitude, and an increase in the production of male flowers connected by a developing forest areas.
Ogasawara
H
H
Department of Otolaryngology, Hyogo College of Medicine, Nishinomiya.
Adachi
O
O
Sakagami
M
M
Yoshimura
S
S
Fujitani
T
T
D000393:Air Pollutants / Q000032:analysis*; D005306:Fertilization; D011058:Pollen; D011237:Predictive Value of Tests; D012621:Seasons; D013696:Temperature; D013997:Time Factors; D014197:Trees; D014887:Weather
D000393:Air Pollutants