Seasonal activity and spatial distribution pattern of Eotetranychus frosti (Acari: Tetranychidae) in an unsprayed apple orchard of Kermanshah, Western Iran

Darbemamieh, Maryam; Shojaii, Mahmoud; Kamali, Karim

doi:10.22073/pja.v1i2.9934

Seasonal activity and spatial distribution pattern of Eotetranychus frosti (Acari: Tetranychidae) in an unsprayed apple orchard of Kermanshah, Western Iran

Authors

Maryam Darbemamieh

Mahmoud Shojaii

Karim Kamali

Department of Entomology, Facultyof Agriculture, Tarbiat Modares University, P. O. Box 14115-336, Tehran, Iran;

10.22073/pja.v1i2.9934

Abstract

Population density and spatial distribution pattern of Eotetranychus frosti (McGregor) was determined in an unsprayed apple orchard of Kermanshah, Western Iran, from 31^st May till 7^th November 2007. On each sample date 130 leaves were selected, with a relative variation of 4.31%. Different methods of indices of dispersion, regression models (Taylor and Iwao), Morisita’s index and Lloyd’s mean crowding to mean was used to determine the spatial distribution pattern of this mite. The mean population density of this mite per leaf was 2.079. The highest population density of E. frosti was in 9^th August (4.938 per leaf). Index of dispersion (S²/m= 6.516), aggregation index (1/k= 2.653) and Lloyd’s mean crowding to mean (m^*/m=3.653) showed an aggregated distribution for this species. The Taylor's power law and Iwao's patchiness regression methods showed aggregated spatial distribution too. Some changes in spatial distribution pattern from aggregated to random were observed using Morisita’s index in different sampling dates. Three different coefficients of Taylor, Iwao and K were used to optimize the sample size for future studies. The lowest optimized sample size (34.70) was obtained by using the Taylor's coefficients. Spatial distribution parameters of E. frosti can be used to improve a sampling program of this mite in a framework of an integrated pest management system.

Keywords

Eotetranychus frost

population density

spatial distribution

optimum sample size