The Potential Geographical Distribution of bactrocera Dorsalis (Diptera: Tephrididae) in China Based on Emergence Rate Model and Arcgis

The oriental fruit fly, Bactrocera dorsalis (Handel) (Dipteral: Tephrididae), is the important insect pest of fruits and vegetables in tropical and subtropical areas. It is necessary to know the potential geographical distribution of this pest in order to monitor and control it effectively. Pupal development takes place in the soil and is regulated by two key factors; soil temperature and moisture. These factors are primary determinants of fruit fly distribution. In this study, the potential geographical distribution of B. dorsalis from Jan. to Dec. in China was predicted based on the soil temperature and moisture data of Chinese meteorologic stations, the ER (Emergence rate) model constructed from empirical biological data, and analysis with ArcGIS. The ER data were obtained by observing the emergence of 7560 cultured pupae using a crossover design of 7 soil temperature grades and 6 soil moisture grades. The ER model (Z = – 0.0036X2 – 0.0001Y2 + 0.1681X + 0.0123Y – 1.5170) was established with stepwise regression method where emergence rate (Z) is a function of soil temperature (X) and soil moisture (Y). According to reported geographical 400 Ningbo Wang , Zhihong Li , Jiajiao Wu , Edwin G. Rajotte , Fanghao Wan , Zhiling Wang distributions in the world, four categories were used to describe different levels of suitability for B. dorsalis in China, including negligible (0 ER 0.01), low (0.01<ER 0.2), moderate (0.2<ER 0.45) and high (0.45<ER 1). The potential geographical distribution and suitable levels for every month in China were obtained and showed that main parts of the distribution were south of ±35°N, and most regions in China had high suitability levels from May to September. Further analysis showed the desireability of strengthening monitoring in the north parts of China from Apr. to Oct. and to institute whole year monitoring in Guangdong, Guangxi, Yunnan, and Hainan provinces.