关键词: 生命表, 自我重复取样技术； 随机匹配； 滞育昆虫； 计算机模拟； 梨小食心虫

Abstract: 【Aim】 This study aims to introduce a suitable life table construction technique for some insects whose data of development, survival and reproduction of all individuals from birth to death could not be recorded continuously or were difficult to be recorded, and demonstrate the reliability of this technique. 【Methods】 We split 24 life tables, whose data were constructed in the usual manner, i.e., the development and survival of all individuals and fecundity of female adults were recorded from birth to their deaths, and then used the bootstrap-match technique to reconstruct them as complete life tables. The main population parameters of the bootstrap-match life tables were compared with and validated against those of the original life tables. Subsequently, we applied this technique to reconstruct the life table of Grapholita molesta with diapause period, and then used simulation program to predict the growth trends of overwintering populations. The projected population data were compared with field sampling data. 【Results】 The population parameters of 24 bootstrap-match life tables constracted based on the 0.5th percentile of R₀ and 0.5th percentile of λ were highly consistent with those of the original life tables. The bootstrap-match life table of G. molesta without diapause period showed significant differences in finite rate of increase (λ), intrinsic rate of increase (r), and mean generation time (T) compared to the life table with a 180-d diapause period, but there were no significant differences in net reproductive rate (R₀) and mean fecundity (F). Ignoring the diapause period in population growth prediction would overestimate the growth potential of field populations, and result in an unrealistic rapid increase. The life table including a 180-d diapause period with reduced fecundity and increased mortality of overwintering larvae, however, could generate the population structure close to the field observations. 【Conclusion】 This study presented a technique to independently collect data of immature and adult stages, and then constructed a complete life table by using TWOSEX-MSChart with 100 000 bootstrap-match resamplings. Computer simulations based on the age-stage, two-sex life table can then be used to predict the growth of pest populations, which will be helpful to determine the optimal timing of effective pest management programs for sustainable agricultural development.

Key words: Life table, bootstrap technique, random match, diapause insects, computer simulation, Grapholita molesta