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Densities of coconut mite, Aceria guerreronis Keifer (Acari: Eriophyidae) and its predatory mite, Neoseiulus baraki Athias-Henriot (Acari: Phytoseiidae) were monitored on coconut fruits in two coconut mite infested areas, Kalpitiya and Madurankuliya, in Sri Lanka, over a period of 3 years and were compared with local rainfall records. Significant differences in A. guerreronis densities were observed among years and months of the year. Rainfall (amount and frequency, i.e. the total number of days with rainfall of >5 mm) was not significantly correlated with the variation of A. guerreronis densities. But the drought length (i.e. the number of days without rainfall of >5 mm) significantly influenced A. guerreronis densities. Generally, peak densities of A. guerreronis were observed during February-March and June-September in both areas. The differences in the N. baraki densities were significantly different between the two areas and among the 3 years but not among months of the year. Although the amount of rainfall was not significantly correlated with the population densities of N. baraki, frequency of rainfall showed a negative significant correlation and drought length showed a positive significant correlation with the population densities. The results of this experiment indicated that the application of control methods for A. guerreronis may be more advantageous if they are carried out at the onset and during the dry seasons.

Soil temperature is an important climatic variable in regulating ecosystem process, yet it is difficult and costly to measure daily. Several mathematical models are available to estimate soil temperature; however, most are with complicated independent variables. In this research, site specific parsimonious models were developed to estimate daily mean soil temperature in deeper depths (i.e.>10 cm) using air temperature, soil temperature at 5 cm depth and day of the year as independent variables. Different models were developed for four Coconut growing sites and results showed that 5 cm depth soil temperature along with day of the year estimate the soil temperature at deeper depths with high accuracy. Further, models with air temperature and day of the year estimate the soil temperature at 5 and 10 cm depths satisfactorily. These models can be used to estimate the daily mean soil temperature simply and cost effectively and it also allows the reconstruction of missing soil temperature values. COCOS Vol. 20: 9-25 (2013)