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甜菜夜蛾Spodoptera exigua(Hbner)是我国多种农作物上的重要害虫,在我国许多地区频繁暴发成灾。为探索甜菜夜蛾种群动态规律并建立种群数量发生趋势预测模型,作者应用时间序列分析和逐步回归分析方法研究了我国广域(较大范围)温度和广域降雨量变化趋势对我国广域甜菜夜蛾年暴发频度的影响规律。结果表明:甜菜夜蛾发生的长期趋势和年间波动状况均与广域温度和广域降雨量具有复杂的影响关系。在1979-2008年间,我国甜菜夜蛾暴发频度呈现出波浪式上升趋势,其暴发指数平均年递增率为0.076,而我国广域温度(以27个省市级气象台数据统计为例)在1990-2008年间的平均年递升率为0.039℃,即我国甜菜夜蛾暴发频度上升趋势与我国广域温度升高趋势同向而行。作者从52个因素(当年和上年1-12月各月及全年日均温和月均降雨量)中筛选出了具有显著回归影响(P<0.05或0.01)的10个因素进入回归模型,初步找出了能够预测广域甜菜夜蛾暴发趋势指数的温度与降雨量或其组合因素,并使其模型达到99%以上的历史符合率和预测准确度。作者认为,广域温、雨因素与广域甜菜夜蛾暴发趋势指数的这种密切相关性,不是偶然的巧合,而是必然的环境(温度和降雨量)作用于生物(甜菜夜蛾)的因果关系。
Spodoptera exigua (Hbner) is an important pest on many kinds of crops in our country. It has been frequently erupted in many parts of our country. In order to explore the dynamics of beet armyworm population and to establish the tendency prediction model of population quantity, the authors studied the changes of the wide-area (wide-range) temperature and wide-area rainfall in China using the time series analysis and stepwise regression analysis, The influence rule of frequency of annual outbreak of The results showed that both the long-term trend of Beet armyworm occurrence and the annual fluctuation were related to the complex influence of wide-area temperature and wide-area rainfall. During the period of 1979-2008, the outbreak frequency of beet armyworm in our country showed a wave-like upward trend, with an average annual increment rate of 0.076 for the outbreak index, while the wide-area temperature in China (taking the data of 27 provincial and municipal meteorological stations as an example) - The average annual rate of increase during 2008 was 0.039 ℃, indicating that the upward trend in the frequency of outbreaks of beet armyworm in China is in the same direction as the trend of wide-area temperature rise in China. The authors screened 10 factors with significant regression effects (P <0.05 or 0.01) into the regression model from 52 factors (monthly and monthly average monthly rainfall over the January-December of the previous year and the whole year) The temperature and rainfall, or combination of factors, that can predict the outbreak trend index of Beet armyworm were preliminary found out, and the historical coincidence rate and prediction accuracy of the model reached more than 99%. The authors conclude that this close correlation of the wide-area temperature and rain factors with the outbreak trend index of the broad-spectrum beet armyworm is not a coincidental coincidence, but a necessary environment (temperature and rainfall) to act on the beet armyworm Causal relationship.