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林业科学 ›› 2016, Vol. 52 ›› Issue (7): 78-86.doi: 10.11707/j.1001-7488.20160710

• 论文与研究报告 • 上一篇    下一篇

杜仲梦尼夜蛾危害的风险分级

孙志强1,2, 赵阳1,2, 马志刚1,2, 杜红岩1,2, 朱景乐1,2, 王浩3, 陈军华4, 傅建敏1,2   

  1. 1. 国家林业局泡桐研究开发中心 郑州 450003;
    2. 国家林业局杜仲工程技术研究中心 郑州 450003;
    3. 北京市黄垡苗圃 北京 102601;
    4. 国家林业局盐碱地研究中心 北京 100091
  • 收稿日期:2015-09-29 修回日期:2016-02-21 出版日期:2016-07-25 发布日期:2016-08-16
  • 通讯作者: 傅建敏
  • 基金资助:
    国家林业公益性行业科研专项项目“杜仲主要食叶害虫综合防控技术研究”(201304406)。

Risk Grading for Damage of the Defoliator Orthosia songi (Lepidoptera: Noctuidae)

Sun Zhiqaing1,2, Zhao Yang1,2, Ma Zhigang1,2, Du Hongyan1,2, Zhu Jingle1,2, Wang Hao3, Chen Junhua4, Fu Jianmin1,2   

  1. 1. Paulownia R & D Center of China, State Forestry Administration Zhengzhou 450003;
    2. Eucommia Engineering Research Center of State Forestry Administration Zhengzhou 450003;
    3. Beijing Huangfa Nursery Beijing 102601;
    4. Saline Alkali Land Research Center of State Forestry Administration Beijing 100091
  • Received:2015-09-29 Revised:2016-02-21 Online:2016-07-25 Published:2016-08-16

摘要: [目的] 对杜仲主要食叶害虫——杜仲梦尼夜蛾危害风险进行分级,为构建杜仲梦尼夜蛾预警技术提供依据,也为其他农林业食叶害虫危害等级划分及预警技术构建提供参考。[方法] 借鉴我国民政行业推荐性标准《自然灾害风险分级方法》,以灵宝市的杜仲梦尼夜蛾-杜仲系统为研究对象,通过不同虫口密度导致的叶面积损失率和落果率为主要依据,以预期百叶虫口密度作为种群发生的可能性指标(P),以预期叶面积损失率范围、落果率范围以及预期发生面积率和管理成本增加率范围为依据,制定相应的风险等级分值(C)。运用归一化原理对量化估算的结果进行赋值,建立杜仲梦尼夜蛾危害的风险(R)分级矩阵。同时,通过对成虫数量进行监测并结合设立标准地进行卵期、幼虫期调查,对种群数量及发生面积的预期大小对其危害等级进行预测,以危害后期实际叶面积损失率和落果率为依据对分级效果的实用性和可操作性进行评估。[结果] 不同虫口密度导致的叶面积损失率和落果率差异均达到极显著水平。百叶虫口密度16头以上时可造成叶面积损失率60%以上,平均每头虫取食造成的叶面积损失率为2.8%。百叶虫口密度24头以上时落果率达到17%以上,平均每头虫取食造成的落果率为0.8%。根据2015年5月调查的卵块密度、虫口密度和有虫株率等数据,按照发生面积占总面积的权重对各项数据进行加权平均,得到预期百叶虫口密度范围在11~35头之间,P=2。在该虫口密度下的危害风险等级包括:预期发生面积率75%,C=2;预期叶面积损失率范围16%~49%,C=2;预期落果率范围6%~10%,C=3;管理成本增加率为0,C=4。根据等级C取指标分值中的最小者,即C=2。对应风险分级矩阵计算风险等级分值R=P×C=2×2=4,属高风险,发布当年第2代杜仲梦尼夜蛾发生风险的橙色预警,且不排除个别区域的极高风险。7月实测的平均叶面积损失率和平均落果率分别为17.2%和9.4%,均在预期损失范围内,其中占总面积17%的区域受害极严重,表明这种风险分级是实用的和可操作的。[结论] 杜仲梦尼夜蛾危害的风险分值R可划分为4个等级并赋以4种颜色,表示杜仲梦尼夜蛾发生风险的4个等级:极高风险(R为1~2),红色;高风险(R为3~4),橙色;中风险(R为6~9),黄色;低风险(R为12~16),绿色。本分级方法适宜于短期预警,即杜仲梦尼夜蛾种群某一个世代的危害预期。下一步研究重点是将各项指标进一步细化,使之能够应用于中长期的预测。

关键词: 杜仲, 杜仲梦尼夜蛾, 危害, 风险分级, 预警技术

Abstract: [Objective] This study was to establish an early warning technology for forecasting outbreaks of defoliator insects Orthosia songi Chen et Zhang based on a recommended standard "Grading Methods of Natural Disaster Risk" issued by Civil Affairs of China. The main aim was to provide relevant information for risk grading and establish a warning technology of outbreak for forest and agriculture defoliator insects.[Method] This study used O. songi-host tree Eucommia ulmoides system as a model located at Linbao City, Henan Province, China. Leaf area loss rate (%) and fruit dropped rate (%) were measured under different larval densities (larvae per hundred leaves). Probability index (P) of O. songi population occurrence was determined using the expected larval densities. Quantitative indexes of loss (C) caused by O. songi occurrence were used in basis of the expected scope of leaf area loss rate, fruit dropped rate, outbreak area rate and expected increasing management cost rate. A risk classification matrix of O. songi occurrence risk was set up based on the normalized risk probability index (P) and loss index (C). Meanwhile, the expected leaf area loss scope, fruit dropped loss scope and occurrence area was predicted using the observed egg and larval densities in permanent plots in Eucommia plantations. These data were used to forecast the risk grade. Feasibility and maneuverability of risk grading system were then evaluated through actual leaf area loss rate and fruit dropped rate during late development stage of the same generation.[Result] Leaf area loss rate and fruit dropped rate differed statistically significant among different larval densities. A larval density at 16 larvae per hundred leaves led to more than 60% of leaf area loss. Every single larva caused 2.8% of average leaf loss. The 17% or more of fruits premature drop when larval density was 24 larvae per hundred leaves or above. Every larva caused average 0.8% of fruit premature drop. Based on survey of egg density and larval density in May 2015, we predicted that larval density ranged 11 to 35 larvae per hundred leaves with a probability index P of 2, and the expected occurrence area rate of 75% at a loss index C of 2. The expected scope of leaf area loss rate at C=2 ranged from 16% to 49%, and the expected fruit drop rate at C=3 varied from 6% to 10%. The expected increase in management cost was 0 with a loss index C=4. Therefore the smallest value should be selected as loss index C when C had a different value in the risk classification matrix. Risk score R should be calculated as P×C, or 2×2=4 in the corresponding risk classification matrix. A high risk of orange alert was predicted and did not rule out extremely high risk in some plantations. The actual average leaf area loss rate and fruit dropped rate caused by O. songi surveyed in July 2015 were 17.2% and 9.4%, respectively, among which plantations accounted for 17% of the total area suffered extremely high damage. The results fitted well the prediction, indicating that the risk grading method is feasible.[Conclusion] Risk score R of O. songi disaster was divided into four grades and was given four different colors for different R values, or four different levels of risk of O. songi occurrence. Red color represent extremely-high risk with R value ranging 1-2; orange color, high risk with R from 3-4; yellow means medium risk with R from 6 to 9; green represents low risk, R ranging 12-16. The risk grading method in this study was well suited for short-term predictions, i.e. prediction of risk caused by one generation. Refining the indices for long-term prediction will be a focus of future studies.

Key words: Eucommia ulmoides, Orthosia songi, damage, risk grading, warning technology

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