灾变模型在马尾松毛虫幼虫发生量预报中的应用  

A catastrophe model to forecast larvae occurrence of Dendrolimus punctatus

作　　者：张书平 余燕 毕守东[1] 周夏芝[2] 邹运鼎[2] 张国庆[3] 张桢 方国飞 宋玉双 ZHANG Shuping;YU Yan;BI Shoudong;ZHOU Xiazhi;ZOU Yunding;ZHANG Guoqing;ZHANG Zhen;FANG Guofei;SONG Yushuang(School of Science,Anhui Agricultural University,Hefei 230036,Anhui,China;School of Forestry and Landscape Architecture,Anhui Agricultural University,Hefei 230036,Anhui,China;Forestry Bureau of Qianshan County,Anhui Province,Qianshan 246300,Anhui,China;General Station of Forest Disease and Insect Pest Control of National Forestry and Grassland Administration,Shenyang 110034,Liaoning,China)

机构地区：[1]安徽农业大学理学院,安徽合肥230036 [2]安徽农业大学林学与园林学院,安徽合肥230036 [3]安徽省潜山县林业局,安徽潜山246300 [4]国家林业和草原局森林病虫害防治总站,辽宁沈阳110034

出　　处：《浙江农林大学学报》2020年第1期93-99,共7页Journal of Zhejiang A&F University

基　　金：国家林业公益性创业科研专项(201404410)

摘　　要：[目的] 提高马尾松毛虫Dendrolimus punctatus幼虫发生量预测预报结果的准确性。 [方法] 利用灰色灾变预测GM(1, 1)模型预测了安徽省潜山县1989-2016年马尾松毛虫越冬代、1代和2代严重发生的年份。 [结果] 马尾松毛虫越冬代虫口数的GM(1, 1)灾变预测模型为:z^(1)(k+1)=9.58075e0.26933k−8.58075, 其中k为年序号, z^(1)(k+1)为灾变年序号。1代幼虫虫口数的GM(1, 1)灾变预测模型为:z^(1)(k+1)=18.1818e0.24187k−17.1818。2代幼虫虫口数的GM(1, 1)灾变预测模型为:z^(1)(k+1)=20.123 7e0.197 58k-19.123 7。根据此模型求得已知年份的拟合值与观察值, 对两者差异进行t检验, 差异均不显著, 即拟合值与观察值间吻合度高, 各灾变年精度值平均为84.40%, 84.85%和84.08%, 总体平均精度依次为96.25%, 92.34%和94.09%, 模型精度高。由此推算未来时刻的预测值得到, 从2011年马尾松毛虫越冬代幼虫灾变年算起, 再过10 a即2021年为马尾松毛虫越冬代大发生年。从2011年马尾松毛虫1代幼虫灾变年算起, 再过11 a即2022年为马尾松毛虫1代幼虫大发生年。从2011年马尾松毛虫2代幼虫灾变年算起, 再过9 a即2020年为马尾松毛虫2代幼虫大发生年。 [结论] 灾变预测对马尾松毛虫幼虫发生量灾变的预报是一种较理想的预报方法。Objective The aim is to improve control of Dendrolimus punctatus larval occurrence, and to select a suitable prediction model by increasing prediction accuracy through a catastrophe prediction method. Method The prediction model GM(1, 1) for D. punctatus was used over 28 years from 1989 to 2016 in Qianshan County, Anhui Province. Result The GM(1, 1) cataclysmic prediction model for the overwintering generation of D. punctatus was as follows:z^(1)(k+1)=9.580 75e0.269 33k-8.580 75, where k was the annual serial number and z^(1)(k+1) was the disaster year serial number. The GM(1, 1) cataclysmic prediction model for the number of larvae of the first generation was:z^(1)(k+1)=18.181 8e0.241 87k-17.181 8, and the second generation larval population was:z^(1)(k+1)=20.123 7e0.197 58k-19.123 7. According to this model, fitted and observed values of known years were obtained. Results of a t test for t0.05 were not significant. The average annual accuracy of three disasters was 84.40%, 84.85%, and 84.08% with the total average accuracy of the first being 96.25%, of the second being 92.34%, and of the third being 94.09%. The predicted future times were as follows:for the wintering D. punctatus disaster of 2011, it would be another 10 years (2021) before the next overwintering. For the first generation D. punctatus larvae in the catastrophic year 2011, it would be another 11 years (2022), until the great occurrence of the first generation larvae. For the second generation D. punctatus larvae, the next disaster after 2011 would occur 9 years later (2020). Conclusion Thus, the catastrophe prediction method could be an ideal method for predicting the occurrence of larval cataclysm with D. punctatus.

关 键 词：森林保护学 马尾松毛虫幼虫 灾变预测 GM(1 1)模型 

分 类 号：S763.3[农业科学—森林保护学]