摘要
将西太平洋海温作为长期预报因子,根据场相关分析方法进行相关普查,用GRADS软件绘制了江苏省宜兴、盐都、靖江地区稻纵卷叶螟迁入峰期、峰期持续时间及峰期蛾量等各虫情指标与各格点逐月的月海温值间相关系数的时、空分布图,从中找出了与稻纵卷叶螟迁入期各虫情指标相关的强信号海区,并对预测因子进行最优化相关处理,建立了三地区稻纵卷叶螟迁入期各虫情指标的长期预报模型.结果表明:三地区稻纵卷叶螟迁入峰期与西太平洋海温存在共同的高相关区;稻纵卷叶螟迁入持续时间与西太平洋海温具有较好的相关关系;海温显著影响迁入峰期蛾量,二者间具有较稳定的相关关系,且其相关程度随季节变化而变化;所有预报模型均通过了α=0.01的显著性水平检验,说明预报结果与实际值较吻合,预报模型切实可行.该预报模型将能提前1~2个月做出预测意见,对江苏省水稻虫害防治、水稻生产以及最大限度地减轻化学农药污染、改善环境质量具有重要意义.
The correlations between the situation indicators (peak time of ingoing, last length of peak period, and moth quantity in peak period) of rice leaf roller in Yixing, Yandu and Jingjiang of Jiangsu Province and the grid monthly sea surface temperature (SST) of west Pacific were analyzed by statistical method, and the correlation maps were produced by using GRADS software. The regions in which the SST was significantly correlated with the situation indicators were identified, and the SST at these regions, which was processed by optimization correlation technique, was used as the predictor to set up the long-term models for predicting the situation indicators of rice leaf roller during its immigration period in the three regions. The results showed that the immigration time of rice leaf roller in each of the regions was highly correlated with the SST in that region, and the du- ration of immigration peak was well correlated with the SST of west Pacific. The correlations between moth amount and SST were significant and stable, and showed some seasonality. Model cali- brations indicated that the agreements between outputs from all models and observations were statistically significant ( ct = 0. 01 ), and model validations demonstrated the applicability of the models developed in this study in predicting the situation indicators of rice leaf roller. These models were capable of predicting the possible occurrence situation of rice leaf roller one to two months in advance, being of significance in the prevention and control of rice leaf roller, suitable management of rice production, reduction of pesticide pollution, and protection of environment.
出处
《应用生态学报》
CAS
CSCD
北大核心
2008年第9期2056-2066,共11页
Chinese Journal of Applied Ecology
基金
国家高技术研究发展项目(2006AA10Z203)
国家科技支撑计划资助项目(2006BAB10A01,2006BAJ10B03)
关键词
稻纵卷叶螟
海温
遥相关
最优化相关处理技术
长期预测模型
rice leaf roller
sea surface temperature
remote correlation
optimization correlationtechnique
long-term prediction model.