桉树枝瘿姬小蜂灾害预测预报综合技术

Comprehensive technology for the disaster forecast of Leptocybe invasa

桉树枝瘿姬小蜂Leptocybe invasa是严重危害桉树的叶梢致瘿性害虫,准确预报是防治其疫情扩散蔓延的关键。2014—2020年连续7 a利用黄色粘虫板对桉树枝瘿姬小蜂成虫种群动态进行监测,并与气象因子进行回归分析,据此建立成虫发生量预测预报模型;利用有效积温预测法进行越冬代成虫发生期预测;采用5月成虫监测数量预测6月第1代幼虫危害程度。结果表明,月平均气温(x5)、月平均最高气温(x2)、月降雨天数(x7)是影响赣南桉树枝瘿姬小蜂成虫发生量的主要气象因子,月平均气温、月平均最高气温是该蜂成虫发生量的最主要的决策因子,而月降雨天数则是该蜂成虫发生量的主要制约因子;经逐步回归分析,建立该蜂成虫发生量短期预测预报模型,经检验,其预报准确率可达94.16%;根据调查所得越冬虫蛹始盛发育进度,利用有效积温公式,可以准确预测越冬代成虫始盛发生期;利用5月的成虫监测数量可以准确预测6月的虫瘿数(危害程度)。经过系统研究,总结出了一套对桉树枝瘿姬小蜂成虫发生期、成虫发生量和虫瘿危害程度的预测预报方法和模型。经在生产中验证,预测结果与实际结果基本吻合,说明所获得的预测模型是可靠的、测报方法是可行的。

Leptocybe invasa is a gall pest that seriously damages leaves and shoots of Eucalyptus.Accurate forecast is the key to prevent and control the spread of the epidemic.From 2014 to 2020,the yellow sticky insect board was used to monitor the adult population dynamics of L.invasa,and the prediction model of adult occurrence amount was established based on the regression analysis between the population dynamics of adults and meteorological factors.The effective accumulated temperature prediction method was used to predict the occurrence period of overwintering adults.The damage degree of the first generation larvae in June was predicted by the monitoring amount of adults in May.The results showed that monthly average temperature(x5),monthly average maximum temperature(x2)and monthly rainfall days(x7)were main meteorological factors affecting the occurrence amount of L.invasa adults in Gannan,Jiangxi province.The monthly average temperature and the monthly average maximum temperature were main decision factors for the occurrence amount of the adult,while the days of monthly rainfall were main limiting factors.Through stepwise regression analysis,the short-term prediction model of adult population of this wasp was established.This is verified that the accuracy of the forecast is 94.16%.According to the development progress of overwintering pupae,the effective accumulated temperature formula can accurately predict the occurrence period of overwintering adults.The number of galls(damage degree)in June can be accurately predicted by using the number of adult monitoring in May.A set of forecasting methods and models for adult occurrence period,adult quantity and gall damage degree of L.invasa were summarized.The prediction results were consistent with the actual results,which showed that the prediction model was reliable and the prediction method was feasible.